1
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Cornish AJ, Gruber AJ, Kinnersley B, Chubb D, Frangou A, Caravagna G, Noyvert B, Lakatos E, Wood HM, Thorn S, Culliford R, Arnedo-Pac C, Househam J, Cross W, Sud A, Law P, Leathlobhair MN, Hawari A, Woolley C, Sherwood K, Feeley N, Gül G, Fernandez-Tajes J, Zapata L, Alexandrov LB, Murugaesu N, Sosinsky A, Mitchell J, Lopez-Bigas N, Quirke P, Church DN, Tomlinson IPM, Sottoriva A, Graham TA, Wedge DC, Houlston RS. The genomic landscape of 2,023 colorectal cancers. Nature 2024; 633:127-136. [PMID: 39112709 PMCID: PMC11374690 DOI: 10.1038/s41586-024-07747-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 06/24/2024] [Indexed: 08/17/2024]
Abstract
Colorectal carcinoma (CRC) is a common cause of mortality1, but a comprehensive description of its genomic landscape is lacking2-9. Here we perform whole-genome sequencing of 2,023 CRC samples from participants in the UK 100,000 Genomes Project, thereby providing a highly detailed somatic mutational landscape of this cancer. Integrated analyses identify more than 250 putative CRC driver genes, many not previously implicated in CRC or other cancers, including several recurrent changes outside the coding genome. We extend the molecular pathways involved in CRC development, define four new common subgroups of microsatellite-stable CRC based on genomic features and show that these groups have independent prognostic associations. We also characterize several rare molecular CRC subgroups, some with potential clinical relevance, including cancers with both microsatellite and chromosomal instability. We demonstrate a spectrum of mutational profiles across the colorectum, which reflect aetiological differences. These include the role of Escherichia colipks+ colibactin in rectal cancers10 and the importance of the SBS93 signature11-13, which suggests that diet or smoking is a risk factor. Immune-escape driver mutations14 are near-ubiquitous in hypermutant tumours and occur in about half of microsatellite-stable CRCs, often in the form of HLA copy number changes. Many driver mutations are actionable, including those associated with rare subgroups (for example, BRCA1 and IDH1), highlighting the role of whole-genome sequencing in optimizing patient care.
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Affiliation(s)
- Alex J Cornish
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Andreas J Gruber
- Department of Biology, University of Konstanz, Konstanz, Germany
- Manchester Cancer Research Centre, Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - Ben Kinnersley
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
- University College London Cancer Institute, London, UK
| | - Daniel Chubb
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Anna Frangou
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Max Planck Institute for Molecular Cell Biology and Genetics, Dresden, Germany
| | - Giulio Caravagna
- Department of Mathematics and Geosciences, University of Trieste, Trieste, Italy
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
| | - Boris Noyvert
- Cancer Research UK Centre and Centre for Computational Biology, Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK
| | - Eszter Lakatos
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
- Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden
| | - Henry M Wood
- Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK
| | - Steve Thorn
- Department of Oncology, University of Oxford, Oxford, UK
| | - Richard Culliford
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Claudia Arnedo-Pac
- Institute for Research in Biomedicine Barcelona, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Jacob Househam
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
| | - William Cross
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
- Research Department of Pathology, University College London, UCL Cancer Institute, London, UK
| | - Amit Sud
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Philip Law
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | | | - Aliah Hawari
- Manchester Cancer Research Centre, Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - Connor Woolley
- Department of Oncology, University of Oxford, Oxford, UK
| | - Kitty Sherwood
- Department of Oncology, University of Oxford, Oxford, UK
- Edinburgh Cancer Research, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Nathalie Feeley
- Department of Oncology, University of Oxford, Oxford, UK
- Edinburgh Cancer Research, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Güler Gül
- Edinburgh Cancer Research, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | | | - Luis Zapata
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
| | - Ludmil B Alexandrov
- Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA, USA
- Department of Bioengineering, UC San Diego, La Jolla, CA, USA
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA
| | - Nirupa Murugaesu
- Genomics England, William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Alona Sosinsky
- Genomics England, William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Jonathan Mitchell
- Genomics England, William Harvey Research Institute, Queen Mary University of London, London, UK
| | - Nuria Lopez-Bigas
- Institute for Research in Biomedicine Barcelona, The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Philip Quirke
- Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK
| | - David N Church
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford NIHR Comprehensive Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | | | - Andrea Sottoriva
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
- Computational Biology Research Centre, Human Technopole, Milan, Italy
| | - Trevor A Graham
- Centre for Evolution and Cancer, Institute of Cancer Research, London, UK
| | - David C Wedge
- Manchester Cancer Research Centre, Division of Cancer Sciences, University of Manchester, Manchester, UK
| | - Richard S Houlston
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
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2
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Sehgal A, Ziaei Jam H, Shen A, Gymrek M. Genome-wide detection of somatic mosaicism at short tandem repeats. Bioinformatics 2024; 40:btae485. [PMID: 39078205 PMCID: PMC11319640 DOI: 10.1093/bioinformatics/btae485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 06/30/2024] [Accepted: 07/29/2024] [Indexed: 07/31/2024] Open
Abstract
MOTIVATION Somatic mosaicism has been implicated in several developmental disorders, cancers, and other diseases. Short tandem repeats (STRs) consist of repeated sequences of 1-6 bp and comprise >1 million loci in the human genome. Somatic mosaicism at STRs is known to play a key role in the pathogenicity of loci implicated in repeat expansion disorders and is highly prevalent in cancers exhibiting microsatellite instability. While a variety of tools have been developed to genotype germline variation at STRs, a method for systematically identifying mosaic STRs is lacking. RESULTS We introduce prancSTR, a novel method for detecting mosaic STRs from individual high-throughput sequencing datasets. prancSTR is designed to detect loci characterized by a single high-frequency mosaic allele, but can also detect loci with multiple mosaic alleles. Unlike many existing mosaicism detection methods for other variant types, prancSTR does not require a matched control sample as input. We show that prancSTR accurately identifies mosaic STRs in simulated data, demonstrate its feasibility by identifying candidate mosaic STRs in Illumina whole genome sequencing data derived from lymphoblastoid cell lines for individuals sequenced by the 1000 Genomes Project, and evaluate the use of prancSTR on Element and PacBio data. In addition to prancSTR, we present simTR, a novel simulation framework which simulates raw sequencing reads with realistic error profiles at STRs. AVAILABILITY AND IMPLEMENTATION prancSTR and simTR are freely available at https://github.com/gymrek-lab/trtools. Detailed documentation is available at https://trtools.readthedocs.io/.
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Affiliation(s)
- Aarushi Sehgal
- Department of Computer Science and Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, United States
| | - Helyaneh Ziaei Jam
- Department of Computer Science and Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, United States
| | - Andrew Shen
- Department of Computer Science and Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, United States
| | - Melissa Gymrek
- Department of Computer Science and Engineering, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, United States
- Department of Medicine, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, United States
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3
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Choi JW, Lee JO, Lee S. Detecting microsatellite instability by length comparison of microsatellites in the 3' untranslated region with RNA-seq. Brief Bioinform 2024; 25:bbae423. [PMID: 39210504 PMCID: PMC11361843 DOI: 10.1093/bib/bbae423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 07/30/2024] [Accepted: 08/09/2024] [Indexed: 09/04/2024] Open
Abstract
Microsatellite instability (MSI), a phenomenon caused by deoxyribonucleic acid (DNA) mismatch repair system deficiencies, is an important biomarker in cancer research and clinical diagnostics. MSI detection often involves next-generation sequencing data, with many studies focusing on DNA. Here, we introduce a novel approach by measuring microsatellite lengths directly from ribonucleic acid sequencing (RNA-seq) data and comparing its distribution to detect MSI. Our findings reveal distinct instability patterns between MSI-high (MSI-H) and microsatellite stable samples, indicating the efficacy of RNA-based MSI detection. Additionally, microsatellites in the 3'-untranslated regions showed the greatest predictive value for MSI detection. Notably, this efficacy extends to detecting MSI-H samples even in tumors not commonly associated with MSI. Our approach highlights the utility of RNA-seq data in MSI detection, facilitating more precise diagnostics through the integration of various biological data.
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Affiliation(s)
- Jin-Wook Choi
- Department of Health Science and Technology, Seoul National University, 1 Gwanak-ro, Gwanak-gu, 08826 Seoul, Republic of Korea
| | - Jin-Ok Lee
- Department of Health Science and Technology, Seoul National University, 1 Gwanak-ro, Gwanak-gu, 08826 Seoul, Republic of Korea
| | - Sejoon Lee
- Department of Health Science and Technology, Seoul National University, 1 Gwanak-ro, Gwanak-gu, 08826 Seoul, Republic of Korea
- Department of Pathology and Translational Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, 82 Gumi-ro 173beon-gil, Bundang-gu, 13620 Seongnam, Republic of Korea
- Precision Medicine Center, Seoul National University Bundang Hospital, 82 Gumi-ro, Bundang-gu, 13620 Seongnam, Republic of Korea
- Department of Genomic Medicine, Seoul National University Bundang Hospital, 82 Gumi-ro, Bundang-gu, 13620 Seongnam, Republic of Korea
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4
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Anthony H, Seoighe C. Performance assessment of computational tools to detect microsatellite instability. Brief Bioinform 2024; 25:bbae390. [PMID: 39129364 PMCID: PMC11317526 DOI: 10.1093/bib/bbae390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 06/26/2024] [Accepted: 07/25/2024] [Indexed: 08/13/2024] Open
Abstract
Microsatellite instability (MSI) is a phenomenon seen in several cancer types, which can be used as a biomarker to help guide immune checkpoint inhibitor treatment. To facilitate this, researchers have developed computational tools to categorize samples as having high microsatellite instability, or as being microsatellite stable using next-generation sequencing data. Most of these tools were published with unclear scope and usage, and they have yet to be independently benchmarked. To address these issues, we assessed the performance of eight leading MSI tools across several unique datasets that encompass a wide variety of sequencing methods. While we were able to replicate the original findings of each tool on whole exome sequencing data, most tools had worse receiver operating characteristic and precision-recall area under the curve values on whole genome sequencing data. We also found that they lacked agreement with one another and with commercial MSI software on gene panel data, and that optimal threshold cut-offs vary by sequencing type. Lastly, we tested tools made specifically for RNA sequencing data and found they were outperformed by tools designed for use with DNA sequencing data. Out of all, two tools (MSIsensor2, MANTIS) performed well across nearly all datasets, but when all datasets were combined, their precision decreased. Our results caution that MSI tools can have much lower performance on datasets other than those on which they were originally evaluated, and in the case of RNA sequencing tools, can even perform poorly on the type of data for which they were created.
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Affiliation(s)
- Harrison Anthony
- School of Mathematical and Statistical Sciences, University of Galway, Galway H91 TK33, Ireland
- The SFI Centre for Research Training in Genomics Data Science, Galway D02 FX65, Ireland
| | - Cathal Seoighe
- School of Mathematical and Statistical Sciences, University of Galway, Galway H91 TK33, Ireland
- The SFI Centre for Research Training in Genomics Data Science, Galway D02 FX65, Ireland
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5
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Culliford R, Lawrence SED, Mills C, Tippu Z, Chubb D, Cornish AJ, Browning L, Kinnersley B, Bentham R, Sud A, Pallikonda H, Frangou A, Gruber AJ, Litchfield K, Wedge D, Larkin J, Turajlic S, Houlston RS. Whole genome sequencing refines stratification and therapy of patients with clear cell renal cell carcinoma. Nat Commun 2024; 15:5935. [PMID: 39009593 PMCID: PMC11250826 DOI: 10.1038/s41467-024-49692-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Accepted: 06/17/2024] [Indexed: 07/17/2024] Open
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, but a comprehensive description of its genomic landscape is lacking. We report the whole genome sequencing of 778 ccRCC patients enrolled in the 100,000 Genomes Project, providing for a detailed description of the somatic mutational landscape of ccRCC. We identify candidate driver genes, which as well as emphasising the major role of epigenetic regulation in ccRCC highlight additional biological pathways extending opportunities for therapeutic interventions. Genomic characterisation identified patients with divergent clinical outcome; higher number of structural copy number alterations associated with poorer prognosis, whereas VHL mutations were independently associated with a better prognosis. The observations that higher T-cell infiltration is associated with better overall survival and that genetically predicted immune evasion is not common supports the rationale for immunotherapy. These findings should inform personalised surveillance and treatment strategies for ccRCC patients.
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Affiliation(s)
- Richard Culliford
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Samuel E D Lawrence
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Charlie Mills
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Zayd Tippu
- Renal and Skin Units, The Royal Marsden NHS Foundation Trust, London, UK
- Melanoma and Kidney Cancer Team, The Institute of Cancer Research, London, UK
- Cancer Dynamics Laboratory, The Francis Crick Institute, London, UK
| | - Daniel Chubb
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Alex J Cornish
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Lisa Browning
- Department of Cellular Pathology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Ben Kinnersley
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
- Department of Oncology, University College London Cancer Institute, London, UK
| | - Robert Bentham
- Department of Oncology, University College London Cancer Institute, London, UK
| | - Amit Sud
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Husayn Pallikonda
- Renal and Skin Units, The Royal Marsden NHS Foundation Trust, London, UK
- Melanoma and Kidney Cancer Team, The Institute of Cancer Research, London, UK
- Cancer Dynamics Laboratory, The Francis Crick Institute, London, UK
| | - Anna Frangou
- Nuffield Department of Medicine, Big Data Institute, University of Oxford, Oxford, UK
- Algebraic Systems Biology, Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
- Algebraic Systems Biology, Centre for Systems Biology Dresden, Dresden, Germany
| | - Andreas J Gruber
- Department of Biology, University of Konstanz, Konstanz, Germany
| | - Kevin Litchfield
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - David Wedge
- Manchester Cancer Research Centre, University of Manchester, Manchester, UK
- NIHR Manchester Biomedical Research Centre, Manchester, UK
| | - James Larkin
- Renal and Skin Units, The Royal Marsden NHS Foundation Trust, London, UK
- Melanoma and Kidney Cancer Team, The Institute of Cancer Research, London, UK
| | - Samra Turajlic
- Renal and Skin Units, The Royal Marsden NHS Foundation Trust, London, UK
- Melanoma and Kidney Cancer Team, The Institute of Cancer Research, London, UK
- Cancer Dynamics Laboratory, The Francis Crick Institute, London, UK
| | - Richard S Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK.
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6
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Mencel J, Alves A, Angelis V, Gerlinger M, Starling N. State of the art: Targeting microsatellite instability in gastrointestinal cancers. Crit Rev Oncol Hematol 2024; 199:104387. [PMID: 38734279 DOI: 10.1016/j.critrevonc.2024.104387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 05/01/2024] [Accepted: 05/06/2024] [Indexed: 05/13/2024] Open
Abstract
DNA mismatch repair (MMR) deficiency and the associated microsatellite instability (MSI) phenotype has become a subject of enormous interest in recent years due to the demonstrated efficacy of immune checkpoint inhibitors (ICI) in advanced tumours. Assessing MSI in patients with gastrointestinal tract (GI) cancers is useful to exclude Lynch syndrome, but also to predict benefit for ICI. Following review of the relevant literature, this review article aims to outline the clinicopathologic spectrum of MSI and mismatch repair deficiency (dMMR) in the GI tract, hepatobiliary system and pancreas and discuss the therapeutic consideration in this disease.
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Affiliation(s)
- Justin Mencel
- Gastrointestinal and Lymphoma Unit, Royal Marsden NHS Foundation, London, United Kingdom
| | - Anneke Alves
- Gastrointestinal and Lymphoma Unit, Royal Marsden NHS Foundation, London, United Kingdom
| | - Vasileios Angelis
- Gastrointestinal and Lymphoma Unit, Royal Marsden NHS Foundation, London, United Kingdom
| | - Marco Gerlinger
- Gastrointestinal and Lymphoma Unit, Royal Marsden NHS Foundation, London, United Kingdom
| | - Naureen Starling
- Gastrointestinal and Lymphoma Unit, Royal Marsden NHS Foundation, London, United Kingdom.
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7
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Kim M, Shim HS, Kim S, Lee IH, Kim J, Yoon S, Kim HD, Park I, Jeong JH, Yoo C, Cheon J, Kim IH, Lee J, Hong SH, Park S, Jung HA, Kim JW, Kim HJ, Cha Y, Lim SM, Kim HS, Lee CK, Kim JH, Chun SH, Yun J, Park SY, Lee HS, Cho YM, Nam SJ, Na K, Yoon SO, Lee A, Jang KT, Yun H, Lee S, Kim JH, Kim WS. Clinical Practice Recommendations for the Use of Next-Generation Sequencing in Patients with Solid Cancer: A Joint Report from KSMO and KSP. Cancer Res Treat 2024; 56:721-742. [PMID: 38037319 PMCID: PMC11261187 DOI: 10.4143/crt.2023.1043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 11/17/2023] [Indexed: 12/02/2023] Open
Abstract
In recent years, next-generation sequencing (NGS)-based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.
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Affiliation(s)
- Miso Kim
- Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Hyo Sup Shim
- Department of Pathology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sheehyun Kim
- Department of Genomic Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - In Hee Lee
- Department of Oncology/Hematology, Kyungpook National University Chilgok Hospital, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Jihun Kim
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Shinkyo Yoon
- Department of Oncology,Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Hyung-Don Kim
- Department of Oncology,Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Inkeun Park
- Department of Oncology,Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jae Ho Jeong
- Department of Oncology,Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Changhoon Yoo
- Department of Oncology,Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jaekyung Cheon
- Department of Oncology,Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - In-Ho Kim
- Division of Medical Oncology, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jieun Lee
- Division of Medical Oncology, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Sook Hee Hong
- Division of Medical Oncology, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Sehhoon Park
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Hyun Ae Jung
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jin Won Kim
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Han Jo Kim
- Division of Oncology and Hematology, Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, Korea
| | - Yongjun Cha
- Division of Medical Oncology, Center for Colorectal Cancer, National Cancer Center, Goyang, Korea
| | - Sun Min Lim
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Korea
| | - Han Sang Kim
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Korea
| | - Choong-kun Lee
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Korea
| | - Jee Hung Kim
- Division of Medical Oncology, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sang Hoon Chun
- Division of Medical Oncology, Department of Internal Medicine, Bucheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jina Yun
- Division of Hematology/Oncology, Department of Medicine, Soonchunhyang University Bucheon Hospital, Bucheon, Korea
| | - So Yeon Park
- Department of Pathology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Hye Seung Lee
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Yong Mee Cho
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Soo Jeong Nam
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Kiyong Na
- Department of Pathology, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul, Korea
| | - Sun Och Yoon
- Department of Pathology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Ahwon Lee
- Department of Hospital Pathology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Kee-Taek Jang
- Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Hongseok Yun
- Department of Genomic Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Sungyoung Lee
- Department of Genomic Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Jee Hyun Kim
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Wan-Seop Kim
- Department of Pathology, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Korea
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8
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Kim M, Shim HS, Kim S, Lee IH, Kim J, Yoon S, Kim HD, Park I, Jeong JH, Yoo C, Cheon J, Kim IH, Lee J, Hong SH, Park S, Jung HA, Kim JW, Kim HJ, Cha Y, Lim SM, Kim HS, Lee CK, Kim JH, Chun SH, Yun J, Park SY, Lee HS, Cho YM, Nam SJ, Na K, Yoon SO, Lee A, Jang KT, Yun H, Lee S, Kim JH, Kim WS. Clinical practice recommendations for the use of next-generation sequencing in patients with solid cancer: a joint report from KSMO and KSP. J Pathol Transl Med 2024; 58:147-164. [PMID: 39026440 PMCID: PMC11261170 DOI: 10.4132/jptm.2023.11.01] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/31/2023] [Accepted: 11/01/2023] [Indexed: 07/20/2024] Open
Abstract
In recent years, next-generation sequencing (NGS)-based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.
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Affiliation(s)
- Miso Kim
- Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Hyo Sup Shim
- Department of Pathology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sheehyun Kim
- Department of Genomic Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - In Hee Lee
- Department of Oncology/Hematology, Kyungpook National University Chilgok Hospital, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Jihun Kim
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Shinkyo Yoon
- Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Hyung-Don Kim
- Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Inkeun Park
- Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jae Ho Jeong
- Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Changhoon Yoo
- Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jaekyung Cheon
- Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - In-Ho Kim
- Division of Medical Oncology, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jieun Lee
- Division of Medical Oncology, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Sook Hee Hong
- Division of Medical Oncology, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Sehhoon Park
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Hyun Ae Jung
- Division of Hematology-Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jin Won Kim
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Han Jo Kim
- Division of Oncology and Hematology, Department of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan, Korea
| | - Yongjun Cha
- Division of Medical Oncology, Center for Colorectal Cancer, National Cancer Center, Goyang, Korea
| | - Sun Min Lim
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Korea
| | - Han Sang Kim
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Korea
| | - Choong-Kun Lee
- Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, Korea
| | - Jee Hung Kim
- Division of Medical Oncology, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sang Hoon Chun
- Division of Medical Oncology, Department of Internal Medicine, Bucheon St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jina Yun
- Division of Hematology/Oncology, Department of Medicine, Soonchunhyang University Bucheon Hospital, Bucheon, Korea
| | - So Yeon Park
- Department of Pathology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Hye Seung Lee
- Department of Pathology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Yong Mee Cho
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Soo Jeong Nam
- Department of Pathology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Kiyong Na
- Department of Pathology, Kyung Hee University Hospital, Kyung Hee University College of Medicine, Seoul, Korea
| | - Sun Och Yoon
- Department of Pathology, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Ahwon Lee
- Department of Hospital Pathology, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Kee-Taek Jang
- Department of Pathology and Translational Genomics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Hongseok Yun
- Department of Genomic Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Sungyoung Lee
- Department of Genomic Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Jee Hyun Kim
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Wan-Seop Kim
- Department of Pathology, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Korea
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9
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Gallon R, Herrero-Belmonte P, Phelps R, Hayes C, Sollars E, Egan D, Spiewak H, Nalty S, Mills S, Loo PS, Borthwick GM, Santibanez-Koref M, Burn J, McAnulty C, Jackson MS. A novel colorectal cancer test combining microsatellite instability and BRAF/RAS analysis: Clinical validation and impact on Lynch syndrome screening. BJC REPORTS 2024; 2:48. [PMID: 38962168 PMCID: PMC11216981 DOI: 10.1038/s44276-024-00072-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Revised: 05/31/2024] [Accepted: 06/09/2024] [Indexed: 07/05/2024]
Abstract
Background Lynch syndrome (LS) is under-diagnosed. UK National Institute for Health and Care Excellence guidelines recommend multistep molecular testing of all colorectal cancers (CRCs) to screen for LS. However, the complexity of the pathway has resulted in limited improvement in diagnosis. Methods One-step multiplex PCR was used to generate sequencing-ready amplicons from 14 microsatellite instability (MSI) markers and 22 BRAF, KRAS, and NRAS mutation hotspots. MSI and BRAF/RAS variants were detected using amplicon-sequencing and automated analysis. The assay was clinically validated and deployed into service in northern England, followed by regional and local audits to assess its impact. Results MSI analysis achieved 99.1% sensitivity and 99.2% specificity and was reproducible (r = 0.995). Mutation hotspot analysis had 100% sensitivity, 99.9% specificity, and was reproducible (r = 0.998). Assay-use in service in 2022-2023 increased CRC testing (97.2% (2466/2536) versus 28.6% (601/2104)), halved turnaround times, and identified more CRC patients at-risk of LS (5.5% (139/2536) versus 2.9% (61/2104)) compared to 2019-2020 when a multi-test pathway was used. Conclusion A novel amplicon-sequencing assay of CRCs, including all biomarkers for LS screening and anti-EGFR therapy, achieved >95% testing rate. Adoption of this low cost, scalable, and fully automatable test will complement on-going, national initiatives to improve LS screening.
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Affiliation(s)
- Richard Gallon
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Patricia Herrero-Belmonte
- Northern Genetics Service, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Rachel Phelps
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Christine Hayes
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Elizabeth Sollars
- North West Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University NHS Foundation Trust, Manchester, UK
| | - Daniel Egan
- North East and Yorkshire Genomic Laboratory Hub Central Lab, St James’s University Hospital, Leeds, UK
| | - Helena Spiewak
- North East and Yorkshire Genomic Laboratory Hub Central Lab, St James’s University Hospital, Leeds, UK
| | - Sam Nalty
- Sheffield Diagnostic Genetics Service, North East and Yorkshire Genomic Laboratory Hub, Sheffield Children’s NHS Foundation Trust, Sheffield, UK
| | - Sarah Mills
- Northumbria Healthcare NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Peh Sun Loo
- Department of Cellular Pathology, Royal Victoria Infirmary, The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Gillian M. Borthwick
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Mauro Santibanez-Koref
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - John Burn
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
| | - Ciaron McAnulty
- Northern Genetics Service, The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Michael S. Jackson
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
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10
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Anderson CE, Liska D. Treatment of Microsatellite-Unstable Rectal Cancer in Sporadic and Hereditary Settings. Clin Colon Rectal Surg 2024; 37:233-238. [PMID: 38882941 PMCID: PMC11178385 DOI: 10.1055/s-0043-1770717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
Microsatellite instability is rare in rectal cancer and associated with younger age of onset and Lynch syndrome. All rectal cancers should be tested for microsatellite instability prior to treatment decisions. Patients with microsatellite instability are relatively resistant to chemotherapy. However, recent small studies have shown dramatic response with neoadjuvant immunotherapy. Patients with Lynch syndrome have a hereditary predisposition to cancer and thus an elevated risk of metachronous cancer. Therefore, while "watch and wait" is a well-established practice for sporadic rectal cancers that obtain a complete clinical response after chemoradiation, its safety in patients with Lynch syndrome has not yet been defined. The extent of surgery for patients with Lynch syndrome and rectal cancer is controversial and there is significant debate as to the relative advantages of a segmental proctectomy with postoperative endoscopic surveillance versus a therapeutic and prophylactic total proctocolectomy. Surgical decision making for the patient with Lynch syndrome and rectal cancer is complex and demands a multidisciplinary approach, taking into account both patient- and tumor-specific factors. Neoadjuvant immunotherapy show great promise in the treatment of these patients, and further maturation of data from prospective trials will likely change the current treatment paradigm. Patients with Lynch syndrome and rectal cancer who do not undergo total proctocolectomy require yearly surveillance colonoscopies and should consider chemoprophylaxis with aspirin.
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Affiliation(s)
- Cristan E. Anderson
- Department of Colon and Rectal Surgery, Cleveland Clinic Foundation, Cleveland, Ohio
| | - David Liska
- Department of Colon and Rectal Surgery, Cleveland Clinic Foundation, Cleveland, Ohio
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11
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Kinnersley B, Sud A, Everall A, Cornish AJ, Chubb D, Culliford R, Gruber AJ, Lärkeryd A, Mitsopoulos C, Wedge D, Houlston R. Analysis of 10,478 cancer genomes identifies candidate driver genes and opportunities for precision oncology. Nat Genet 2024:10.1038/s41588-024-01785-9. [PMID: 38890488 DOI: 10.1038/s41588-024-01785-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 05/01/2024] [Indexed: 06/20/2024]
Abstract
Tumor genomic profiling is increasingly seen as a prerequisite to guide the treatment of patients with cancer. To explore the value of whole-genome sequencing (WGS) in broadening the scope of cancers potentially amenable to a precision therapy, we analysed whole-genome sequencing data on 10,478 patients spanning 35 cancer types recruited to the UK 100,000 Genomes Project. We identified 330 candidate driver genes, including 74 that are new to any cancer. We estimate that approximately 55% of patients studied harbor at least one clinically relevant mutation, predicting either sensitivity or resistance to certain treatments or clinical trial eligibility. By performing computational chemogenomic analysis of cancer mutations we identify additional targets for compounds that represent attractive candidates for future clinical trials. This study represents one of the most comprehensive efforts thus far to identify cancer driver genes in the real world setting and assess their impact on informing precision oncology.
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Affiliation(s)
- Ben Kinnersley
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
- University College London Cancer Institute, University College London, London, UK
| | - Amit Sud
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Centre for Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Andrew Everall
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Alex J Cornish
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Daniel Chubb
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Richard Culliford
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Andreas J Gruber
- Systems Biology & Biomedical Data Science Laboratory, University of Konstanz, Konstanz, Germany
| | - Adrian Lärkeryd
- Division of Molecular Pathology, The Institute of Cancer Research, London, UK
| | - Costas Mitsopoulos
- Division of Cancer Therapeutics, The Institute of Cancer Research, London, UK
| | - David Wedge
- Manchester Cancer Research Centre, University of Manchester, Manchester, UK
| | - Richard Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK.
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12
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Chen W, Yan YH, Young B, Pinto A, Jiang Q, Song N, Yaseen A, Yao W, Zhang DY, Zhang JX. Microsatellite Instability Detection in Cancer: A Multiplex qPCR Approach that Obviates the Need for Matching Normal Samples. Clin Chem 2024; 70:830-840. [PMID: 38581343 DOI: 10.1093/clinchem/hvae045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 03/07/2024] [Indexed: 04/08/2024]
Abstract
BACKGROUND Microsatellite instability (MSI) indicates DNA mismatch repair deficiency in certain types of cancer, such as colorectal cancer. The current gold standard technique, PCR-capillary electrophoresis (CE), requires matching normal samples and specialized instrumentation. We developed VarTrace, a rapid and low-cost quantitative PCR (qPCR) assay, to evaluate MSI using solely the tumor sample DNA, obviating the requirement for matching normal samples. METHODS One hundred and one formalin-fixed paraffin-embedded (FFPE) tumor samples were tested using VarTrace and compared with the Promega OncoMate assay utilizing PCR-CE. Tumor percentage limit of detection was evaluated on contrived samples derived from clinical high MSI (MSI-H) samples. Analytical sensitivity, specificity, limit of detection, and input requirements were assessed using synthetic commercial reference standards. RESULTS VarTrace successfully analyzed all 101 clinical FFPE samples, demonstrating 100% sensitivity and 98% specificity compared to OncoMate. It detected MSI-H with 97% accuracy down to 10% tumor. Analytical studies using synthetic samples showed a limit of detection of 5% variant allele frequency and a limit of input of 0.5 ng. CONCLUSIONS This study validates VarTrace as a swift, accurate, and economical assay for MSI detection in samples with low tumor percentages without the need for matching normal DNA. VarTrace's capacity for highly sensitive MSI analysis holds potential for enhancing the efficiency of clinical work flows and broadening the availability of this test.
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Affiliation(s)
- Wei Chen
- NuProbe USA, R&D and Innovation Department, Houston, TX, United States
| | - Yan Helen Yan
- NuProbe USA, R&D and Innovation Department, Houston, TX, United States
| | - Blake Young
- NuProbe USA, R&D and Innovation Department, Houston, TX, United States
| | - Alessandro Pinto
- NuProbe USA, R&D and Innovation Department, Houston, TX, United States
| | - Qi Jiang
- NuProbe USA, R&D and Innovation Department, Houston, TX, United States
| | - Nanjia Song
- NuProbe USA, R&D and Innovation Department, Houston, TX, United States
| | - Adam Yaseen
- NuProbe USA, R&D and Innovation Department, Houston, TX, United States
| | - Weijie Yao
- NuProbe USA, R&D and Innovation Department, Houston, TX, United States
| | - David Yu Zhang
- NuProbe USA, R&D and Innovation Department, Houston, TX, United States
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13
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Rosca OC, Vele OE. Microsatellite Instability, Mismatch Repair, and Tumor Mutation Burden in Lung Cancer. Surg Pathol Clin 2024; 17:295-305. [PMID: 38692812 DOI: 10.1016/j.path.2023.11.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2024]
Abstract
Since US Food and Drug Administration approval of programmed death ligand 1 (PD-L1) as the first companion diagnostic for immune checkpoint inhibitors (ICIs) in non-small cell lung cancer, many patients have experienced increased overall survival. To improve selection of ICI responders versus nonresponders, microsatellite instability/mismatch repair deficiency (MSI/MMR) and tumor mutation burden (TMB) came into play. Clinical data show PD-L1, MSI/MMR, and TMB are independent predictive immunotherapy biomarkers. Harmonization of testing methodologies, optimization of assay design, and results analysis are ongoing. Future algorithms to determine immunotherapy eligibility might involve complementary use of current and novel biomarkers. Artificial intelligence could facilitate algorithm implementation to convert complex genetic data into recommendations for specific ICIs.
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Affiliation(s)
- Oana C Rosca
- Molecular Pathologist/Cytopathologist, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell; Department of Pathology and Laboratory Medicine, 2200 Northern Boulevard, Suite 104, Greenvale, NY 11548, USA.
| | - Oana E Vele
- Molecular Pathologist/Cytopathologist, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell; Department of Pathology and Laboratory Medicine, Lenox Hill Hospital, New York, NY 10075, USA
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14
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Beech C, Hechtman JF. Molecular Approach to Colorectal Carcinoma: Current Evidence and Clinical Application. Clin Lab Med 2024; 44:221-238. [PMID: 38821642 DOI: 10.1016/j.cll.2023.08.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2024]
Abstract
Colorectal carcinoma is one of the most common cancer types in men and women, responsible for both the third highest incidence of new cancer cases and the third highest cause of cancer deaths. In the last several decades, the molecular mechanisms surrounding colorectal carcinoma's tumorigenesis have become clearer through research, providing new avenues for diagnostic testing and novel approaches to therapeutics. Laboratories are tasked with providing the most current information to help guide clinical decisions. In this review, we summarize the current knowledge surrounding colorectal carcinoma tumorigenesis and highlight clinically relevant molecular testing.
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Affiliation(s)
- Cameron Beech
- Department of Pathology, Yale New Haven Hospital, New Haven, CT, USA
| | - Jaclyn F Hechtman
- Molecular and GI Pathologist, NeoGenomics Laboratories, Fort Myers, FL, USA.
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15
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Dong F. Pan-Cancer Molecular Biomarkers: A Paradigm Shift in Diagnostic Pathology. Clin Lab Med 2024; 44:325-337. [PMID: 38821647 DOI: 10.1016/j.cll.2023.08.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2024]
Abstract
The rapid adoption of next-generation sequencing in clinical oncology has enabled the detection of molecular biomarkers shared between multiple tumor types. These pan-cancer biomarkers include sequence-altering mutations, copy number changes, gene rearrangements, and mutational signatures and have been demonstrated to predict response to targeted therapy. This article reviews issues surrounding current and emerging pan-cancer molecular biomarkers in clinical oncology: technological advances that enable the broad detection of cancer mutations across hundreds of genes, the spectrum of driver and passenger mutations derived from human cancer genomes, and implications for patient care now and in the near future.
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Affiliation(s)
- Fei Dong
- Department of Pathology, Stanford University School of Medicine, 3375 Hillview Ave, Palo Alto, CA 94304, USA.
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16
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Galant N, Krawczyk P, Monist M, Obara A, Gajek Ł, Grenda A, Nicoś M, Kalinka E, Milanowski J. Molecular Classification of Endometrial Cancer and Its Impact on Therapy Selection. Int J Mol Sci 2024; 25:5893. [PMID: 38892080 PMCID: PMC11172295 DOI: 10.3390/ijms25115893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 05/21/2024] [Accepted: 05/27/2024] [Indexed: 06/21/2024] Open
Abstract
Endometrial cancer (EC) accounts for 90% of uterine cancer cases. It is considered not only one of the most common gynecological malignancies but also one of the most frequent cancers among women overall. Nowadays, the differentiation of EC subtypes is based on immunohistochemistry and molecular techniques. It is considered that patients' prognosis and the implementation of the appropriate treatment depend on the cancer subtype. Patients with pathogenic variants in POLE have the most favorable outcome, while those with abnormal p53 protein have the poorest. Therefore, in patients with POLE mutation, the de-escalation of postoperative treatment may be considered, and patients with abnormal p53 protein should be subjected to intensive adjuvant therapy. Patients with a DNA mismatch repair (dMMR) deficiency are classified in the intermediate prognosis group as EC patients without a specific molecular profile. Immunotherapy has been recognized as an effective treatment method in patients with advanced or recurrent EC with a mismatch deficiency. Thus, different adjuvant therapy approaches, including targeted therapy and immunotherapy, are being proposed depending on the EC subtype, and international guidelines, such as those published by ESMO and ESGO/ESTRO/ESP, include recommendations for performing the molecular classification of all EC cases. The decision about adjuvant therapy selection has to be based not only on clinical data and histological type and stage of cancer, but, following international recommendations, has to include EC molecular subtyping. This review describes how molecular classification could support more optimal therapeutic management in endometrial cancer patients.
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Affiliation(s)
- Natalia Galant
- Department of Pneumonology, Oncology and Allergology, Medical University of Lublin, 20-090 Lublin, Poland; (N.G.); (P.K.); (M.N.); (J.M.)
| | - Paweł Krawczyk
- Department of Pneumonology, Oncology and Allergology, Medical University of Lublin, 20-090 Lublin, Poland; (N.G.); (P.K.); (M.N.); (J.M.)
| | - Marta Monist
- II Department of Gynecology, Medical University of Lublin, 20-090 Lublin, Poland;
| | - Adrian Obara
- Institute of Genetics and Immunology GENIM LCC, 20-609 Lublin, Poland; (A.O.); (Ł.G.)
| | - Łukasz Gajek
- Institute of Genetics and Immunology GENIM LCC, 20-609 Lublin, Poland; (A.O.); (Ł.G.)
| | - Anna Grenda
- Department of Pneumonology, Oncology and Allergology, Medical University of Lublin, 20-090 Lublin, Poland; (N.G.); (P.K.); (M.N.); (J.M.)
| | - Marcin Nicoś
- Department of Pneumonology, Oncology and Allergology, Medical University of Lublin, 20-090 Lublin, Poland; (N.G.); (P.K.); (M.N.); (J.M.)
| | - Ewa Kalinka
- Department of Oncology, Polish Mother’s Memorial Hospital-Research Institute, 93-338 Łódź, Poland;
| | - Janusz Milanowski
- Department of Pneumonology, Oncology and Allergology, Medical University of Lublin, 20-090 Lublin, Poland; (N.G.); (P.K.); (M.N.); (J.M.)
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17
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Nádorvári ML, Lotz G, Kulka J, Kiss A, Tímár J. Microsatellite instability and mismatch repair protein deficiency: equal predictive markers? Pathol Oncol Res 2024; 30:1611719. [PMID: 38655493 PMCID: PMC11036414 DOI: 10.3389/pore.2024.1611719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 03/27/2024] [Indexed: 04/26/2024]
Abstract
Current clinical guidelines recommend mismatch repair (MMR) protein immunohistochemistry (IHC) or molecular microsatellite instability (MSI) tests as predictive markers of immunotherapies. Most of the pathological guidelines consider MMR protein IHC as the gold standard test to identify cancers with MMR deficiency and recommend molecular MSI tests only in special circumstances or to screen for Lynch syndrome. However, there are data in the literature which suggest that the two test types may not be equal. For example, molecular epidemiology studies reported different rates of deficient MMR (dMMR) and MSI in various cancer types. Additionally, direct comparisons of the two tests revealed relatively frequent discrepancies between MMR IHC and MSI tests, especially in non-colorectal and non-endometrial cancers and in cases with unusual dMMR phenotypes. There are also scattered clinical data showing that the efficacy of immune checkpoint inhibitors is different if the patient selection was based on dMMR versus MSI status of the cancers. All these observations question the current dogma that dMMR phenotype and genetic MSI status are equal predictive markers of the immunotherapies.
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Affiliation(s)
| | | | | | | | - József Tímár
- Department of Pathology, Forensic and Insurance Medicine, Semmelweis University, Budapest, Hungary
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18
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Thomas CE, Georgeson P, Qu C, Steinfelder RS, Buchanan DD, Song M, Harrison TA, Um CY, Hullar MA, Jenkins MA, Guelpen BV, Lynch BM, Melaku YA, Huyghe JR, Aglago EK, Berndt SI, Boardman LA, Campbell PT, Cao Y, Chan AT, Drew DA, Figueiredo JC, French AJ, Giannakis M, Goode EL, Gruber SB, Gsur A, Gunter MJ, Hoffmeister M, Hsu L, Huang WY, Moreno V, Murphy N, Newcomb PA, Newton CC, Nowak JA, Obón-Santacana M, Ogino S, Sun W, Toland AE, Trinh QM, Ugai T, Zaidi SH, Peters U, Phipps AI. Epidemiologic Factors in Relation to Colorectal Cancer Risk and Survival by Genotoxic Colibactin Mutational Signature. Cancer Epidemiol Biomarkers Prev 2024; 33:534-546. [PMID: 38252034 PMCID: PMC10990777 DOI: 10.1158/1055-9965.epi-23-0600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 08/31/2023] [Accepted: 01/18/2024] [Indexed: 01/23/2024] Open
Abstract
BACKGROUND The genotoxin colibactin causes a tumor single-base substitution (SBS) mutational signature, SBS88. It is unknown whether epidemiologic factors' association with colorectal cancer risk and survival differs by SBS88. METHODS Within the Genetic Epidemiology of Colorectal Cancer Consortium and Colon Cancer Family Registry, we measured SBS88 in 4,308 microsatellite stable/microsatellite instability low tumors. Associations of epidemiologic factors with colorectal cancer risk by SBS88 were assessed using multinomial regression (N = 4,308 cases, 14,192 controls; cohort-only cases N = 1,911), and with colorectal cancer-specific survival using Cox proportional hazards regression (N = 3,465 cases). RESULTS 392 (9%) tumors were SBS88 positive. Among all cases, the highest quartile of fruit intake was associated with lower risk of SBS88-positive colorectal cancer than SBS88-negative colorectal cancer [odds ratio (OR) = 0.53, 95% confidence interval (CI) 0.37-0.76; OR = 0.75, 95% CI 0.66-0.85, respectively, Pheterogeneity = 0.047]. Among cohort studies, associations of body mass index (BMI), alcohol, and fruit intake with colorectal cancer risk differed by SBS88. BMI ≥30 kg/m2 was associated with worse colorectal cancer-specific survival among those SBS88-positive [hazard ratio (HR) = 3.40, 95% CI 1.47-7.84], but not among those SBS88-negative (HR = 0.97, 95% CI 0.78-1.21, Pheterogeneity = 0.066). CONCLUSIONS Most epidemiologic factors did not differ by SBS88 for colorectal cancer risk or survival. Higher BMI may be associated with worse colorectal cancer-specific survival among those SBS88-positive; however, validation is needed in samples with whole-genome or whole-exome sequencing available. IMPACT This study highlights the importance of identification of tumor phenotypes related to colorectal cancer and understanding potential heterogeneity for risk and survival.
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Affiliation(s)
- Claire E Thomas
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Peter Georgeson
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Australia
- University of Melbourne Centre for Cancer Research, The University of Melbourne, Parkville, Australia
| | - Conghui Qu
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Robert S Steinfelder
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Daniel D Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, Melbourne Medical School, The University of Melbourne, Parkville, Australia
- University of Melbourne Centre for Cancer Research, The University of Melbourne, Parkville, Australia
- Genomic Medicine and Family Cancer Clinic, The Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Mingyang Song
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
- Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
| | - Tabitha A Harrison
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Caroline Y Um
- Department of Population Science, American Cancer Society, Atlanta, Georgia
| | - Meredith A Hullar
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Mark A Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | - Bethany Van Guelpen
- Department of Radiation Sciences, Oncology Unit, Umeå University, Umeå, Sweden
- Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Brigid M Lynch
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Yohannes Adama Melaku
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- FHMRI Sleep, College of Medicine and Public Health, Flinders University, Adelaide, South Australia, Australia
| | - Jeroen R Huyghe
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Elom K Aglago
- Department of Epidemiology and Biostatistics, Imperial College London, School of Public Health, London, UK
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Lisa A Boardman
- Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA
| | - Peter T Campbell
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Yin Cao
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St Louis, Missouri, USA
- Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, Missouri, USA
- Division of Gastroenterology, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Andrew T Chan
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
| | - David A Drew
- Clinical & Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jane C Figueiredo
- Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Amy J French
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Marios Giannakis
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ellen L Goode
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Stephen B Gruber
- Department of Medical Oncology & Therapeutics Research and Center for Precision Medicine, City of Hope National Medical Center, Duarte CA, USA
| | - Andrea Gsur
- Center for Cancer Research, Medical University of Vienna, Vienna, Austria
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London W2 1PG, United Kingdom
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Li Hsu
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Wen-Yi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Victor Moreno
- Unit of Biomarkers and Suceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L’Hospitalet del Llobregat, 08908 Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat,08908 Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
- Department of Clinical Sciences, Faculty of Medicine and health Sciences and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona (UB), L’Hospitalet de Llobregat, 08908 Barcelona, Spain
| | - Neil Murphy
- Nutrition and Metabolism Section, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Polly A Newcomb
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Christina C Newton
- Department of Population Science, American Cancer Society, Atlanta, Georgia
| | - Jonathan A Nowak
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Department of Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Mireia Obón-Santacana
- Unit of Biomarkers and Suceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L’Hospitalet del Llobregat, 08908 Barcelona, Spain
- ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat,08908 Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
| | - Shuji Ogino
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Wei Sun
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Amanda E Toland
- Departments of Cancer Biology and Genetics and Internal Medicine, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio, USA
| | - Quang M Trinh
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Tomotaka Ugai
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
| | - Syed H Zaidi
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Amanda I Phipps
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
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19
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Edsjö A, Gisselsson D, Staaf J, Holmquist L, Fioretos T, Cavelier L, Rosenquist R. Current and emerging sequencing-based tools for precision cancer medicine. Mol Aspects Med 2024; 96:101250. [PMID: 38330674 DOI: 10.1016/j.mam.2024.101250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 01/22/2024] [Indexed: 02/10/2024]
Abstract
Current precision cancer medicine is dependent on the analyses of a plethora of clinically relevant genomic aberrations. During the last decade, next-generation sequencing (NGS) has gradually replaced most other methods for precision cancer diagnostics, spanning from targeted tumor-informed assays and gene panel sequencing to global whole-genome and whole-transcriptome sequencing analyses. The shift has been impelled by a clinical need to assess an increasing number of genomic alterations with diagnostic, prognostic and predictive impact, including more complex biomarkers (e.g. microsatellite instability, MSI, and homologous recombination deficiency, HRD), driven by the parallel development of novel targeted therapies and enabled by the rapid reduction in sequencing costs. This review focuses on these sequencing-based methods, puts their emergence in a historic perspective, highlights their clinical utility in diagnostics and decision-making in pediatric and adult cancer, as well as raises challenges for their clinical implementation. Finally, the importance of applying sensitive tools for longitudinal monitoring of treatment response and detection of measurable residual disease, as well as future avenues in the rapidly evolving field of sequencing-based methods are discussed.
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Affiliation(s)
- Anders Edsjö
- Department of Clinical Genetics, Pathology and Molecular Diagnostics, Office for Medical Services, Region Skåne, Lund, Sweden; Division of Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden.
| | - David Gisselsson
- Department of Clinical Genetics, Pathology and Molecular Diagnostics, Office for Medical Services, Region Skåne, Lund, Sweden; Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden
| | - Johan Staaf
- Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Medicon Village, Lund, Sweden
| | - Louise Holmquist
- Department of Clinical Genetics, Pathology and Molecular Diagnostics, Office for Medical Services, Region Skåne, Lund, Sweden
| | - Thoas Fioretos
- Department of Clinical Genetics, Pathology and Molecular Diagnostics, Office for Medical Services, Region Skåne, Lund, Sweden; Division of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden; Clinical Genomics Lund, Science for Life Laboratory, Lund University, Lund, Sweden
| | - Lucia Cavelier
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden
| | - Richard Rosenquist
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; Clinical Genetics and Genomics, Karolinska University Hospital, Stockholm, Sweden; Genomic Medicine Center Karolinska, Karolinska University Hospital, Stockholm, Sweden
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20
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Georgeson P, Steinfelder RS, Harrison TA, Pope BJ, Zaidi SH, Qu C, Lin Y, Joo JE, Mahmood K, Clendenning M, Walker R, Aglago EK, Berndt SI, Brenner H, Campbell PT, Cao Y, Chan AT, Chang-Claude J, Dimou N, Doheny KF, Drew DA, Figueiredo JC, French AJ, Gallinger S, Giannakis M, Giles GG, Goode EL, Gruber SB, Gsur A, Gunter MJ, Harlid S, Hoffmeister M, Hsu L, Huang WY, Huyghe JR, Manson JE, Moreno V, Murphy N, Nassir R, Newton CC, Nowak JA, Obón-Santacana M, Ogino S, Pai RK, Papadimitrou N, Potter JD, Schoen RE, Song M, Sun W, Toland AE, Trinh QM, Tsilidis K, Ugai T, Um CY, Macrae FA, Rosty C, Hudson TJ, Winship IM, Phipps AI, Jenkins MA, Peters U, Buchanan DD. Genotoxic colibactin mutational signature in colorectal cancer is associated with clinicopathological features, specific genomic alterations and better survival. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.03.10.23287127. [PMID: 37090539 PMCID: PMC10120801 DOI: 10.1101/2023.03.10.23287127] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Background and Aims The microbiome has long been suspected of a role in colorectal cancer (CRC) tumorigenesis. The mutational signature SBS88 mechanistically links CRC development with the strain of Escherichia coli harboring the pks island that produces the genotoxin colibactin, but the genomic, pathological and survival characteristics associated with SBS88-positive tumors are unknown. Methods SBS88-positive CRCs were identified from targeted sequencing data from 5,292 CRCs from 17 studies and tested for their association with clinico-pathological features, oncogenic pathways, genomic characteristics and survival. Results In total, 7.5% (398/5,292) of the CRCs were SBS88-positive, of which 98.7% (392/398) were microsatellite stable/microsatellite instability low (MSS/MSI-L), compared with 80% (3916/4894) of SBS88 negative tumors (p=1.5x10-28). Analysis of MSS/MSI-L CRCs demonstrated that SBS88 positive CRCs were associated with the distal colon (OR=1.84, 95% CI=1.40-2.42, p=1x10-5) and rectum (OR=1.90, 95% CI=1.44-2.51, p=6x10-6) tumor sites compared with the proximal colon. The top seven recurrent somatic mutations associated with SBS88-positive CRCs demonstrated mutational contexts associated with colibactin-induced DNA damage, the strongest of which was the APC:c.835-8A>G mutation (OR=65.5, 95%CI=39.0-110.0, p=3x10-80). Large copy number alterations (CNAs) including CNA loss on 14q and gains on 13q, 16q and 20p were significantly enriched in SBS88-positive CRCs. SBS88-positive CRCs were associated with better CRC-specific survival (p=0.007; hazard ratio of 0.69, 95% CI=0.52-0.90) when stratified by age, sex, study, and by stage. Conclusion SBS88-positivity, a biomarker of colibactin-induced DNA damage, can identify a novel subtype of CRC characterized by recurrent somatic mutations, copy number alterations and better survival. These findings provide new insights for treatment and prevention strategies for this subtype of CRC.
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Affiliation(s)
- Peter Georgeson
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010 Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria 3010 Australia
| | - Robert S. Steinfelder
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Tabitha A. Harrison
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Bernard J. Pope
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010 Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria 3010 Australia
- Melbourne Bioinformatics, The University of Melbourne, Carlton, Australia
| | - Syed H. Zaidi
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Conghui Qu
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Yi Lin
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Jihoon E. Joo
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010 Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria 3010 Australia
| | - Khalid Mahmood
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010 Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria 3010 Australia
- Melbourne Bioinformatics, The University of Melbourne, Carlton, Australia
| | - Mark Clendenning
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010 Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria 3010 Australia
| | - Romy Walker
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010 Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria 3010 Australia
| | - Elom K Aglago
- Department of Epidemiology and Biostatistics, Imperial College London, School of Public Health, London, UK
| | - Sonja I. Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center(DKFZ), Heidelberg, Germany
| | - Peter T. Campbell
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Yin Cao
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St Louis, Missouri, USA
- Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, Missouri, USA
- Division of Gastroenterology, Department of Medicine, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Andrew T. Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- University Medical Centre Hamburg-Eppendorf, University Cancer Centre Hamburg (UCCH), Hamburg, Germany
| | - Niki Dimou
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Kimberly F. Doheny
- Center for Inherited Disease Research (CIDR), Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - David A. Drew
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Jane C. Figueiredo
- Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Amy J. French
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Steven Gallinger
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
- Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Marios Giannakis
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Graham G. Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Ellen L Goode
- Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Stephen B Gruber
- Department of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte CA, USA
| | - Andrea Gsur
- Center for Cancer Research, Medical University Vienna, Vienna, Austria
| | - Marc J. Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Sophia Harlid
- Department of Radiation Sciences, Oncology Unit, Umeå University, Umeå, Sweden
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Li Hsu
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | - Wen-Yi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Jeroen R Huyghe
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - JoAnn E. Manson
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Victor Moreno
- Unit of Biomarkers and Suceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L’Hospitalet del Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- ONCOBEL Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Barcelona, Spain
- Department of Clinical Sciences, Faculty of Medicine and health Sciences and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona (UB), L’Hospitalet de Llobregat, 08908 Barcelona, Spain
| | - Neil Murphy
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Rami Nassir
- Department of Pathology, College of Medicine, Umm Al-Qura University, Saudi Arabia
| | | | - Jonathan A. Nowak
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Mireia Obón-Santacana
- Unit of Biomarkers and Suceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L’Hospitalet del Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- ONCOBEL Program, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Barcelona, Spain
| | - Shuji Ogino
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Cancer Immunology Program, Dana-Farber Harvard Cancer Center, Boston, Massachusetts, USA
| | - Rish K. Pai
- Department of Pathology and Laboratory Medicine, Mayo Clinic Arizona, Scottsdale, Arizona, USA
| | - Nikos Papadimitrou
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - John D. Potter
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Research Centre for Hauora and Health, Massey University, Wellington, New Zealand
| | - Robert E. Schoen
- Departments of Medicine and Epidemiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Mingyang Song
- Departments of Epidemiology and Nutrition, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
- Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Wei Sun
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
| | - Amanda E. Toland
- Departments of Cancer Biology and Genetics and Internal Medicine, Comprehensive Cancer Center, The Ohio State University, Columbus, Ohio, USA
| | - Quang M. Trinh
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Kostas Tsilidis
- Department of Epidemiology and Biostatistics, Imperial College London, School of Public Health, London, UK
| | - Tomotaka Ugai
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Caroline Y Um
- Department of Population Science, American Cancer Society, Atlanta, Georgia, USA
| | - Finlay A. Macrae
- Parkville Familial Cancer Centre, and Dept of Colorectal Medicine and Genetics The Royal Melbourne Hospital
- Colorectal Medicine and Genetics, Royal Melbourne Hospital, Parkville, Australia
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Australia
| | - Christophe Rosty
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010 Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria 3010 Australia
- Envoi Specialist Pathologists, Brisbane, Australia
- University of Queensland, Brisbane, Australia
| | | | - Ingrid M. Winship
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Australia
- Department of Medicine, The University of Melbourne, Parkville, Australia
| | - Amanda I. Phipps
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Mark A. Jenkins
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria 3010 Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Daniel D. Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010 Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria 3010 Australia
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Australia
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21
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Chakraborty B, Agarwal S, Kori S, Das R, Kashaw V, Iyer AK, Kashaw SK. Multiple Protein Biomarkers and Different Treatment Strategies for Colorectal Carcinoma: A Comprehensive Prospective. Curr Med Chem 2024; 31:3286-3326. [PMID: 37151060 DOI: 10.2174/0929867330666230505165031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 02/20/2023] [Accepted: 02/24/2023] [Indexed: 05/09/2023]
Abstract
In this review, we emphasized important biomarkers, pathogenesis, and newly developed therapeutic approaches in the treatment of colorectal cancer (CRC). This includes a complete description of small-molecule inhibitors, phytopharmaceuticals with antiproliferative potential, monoclonal antibodies for targeted therapy, vaccinations as immunotherapeutic agents, and many innovative strategies to intervene in the interaction of oncogenic proteins. Many factors combine to determine the clinical behavior of colorectal cancer and it is still difficult to comprehend the molecular causes of a person's vulnerability to CRC. It is also challenging to identify the causes of the tumor's onset, progression, and responsiveness or resistance to antitumor treatment. Current recommendations for targeted medications are being updated by guidelines throughout the world in light of the growing number of high-quality clinical studies. So, being concerned about the aforementioned aspects, we have tried to present a summarized pathogenic view, including a brief description of biomarkers and an update of compounds with their underlying mechanisms that are currently under various stages of clinical testing. This will help to identify gaps or shortfalls that can be addressed in upcoming colorectal cancer research.
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Affiliation(s)
- Biswadip Chakraborty
- Integrated Drug Discovery Research Laboratory, Department of Pharmaceutical Sciences, Dr. Harisingh Gour University (A Central University), Sagar (MP), India
| | - Shivangi Agarwal
- Integrated Drug Discovery Research Laboratory, Department of Pharmaceutical Sciences, Dr. Harisingh Gour University (A Central University), Sagar (MP), India
| | - Shivam Kori
- Integrated Drug Discovery Research Laboratory, Department of Pharmaceutical Sciences, Dr. Harisingh Gour University (A Central University), Sagar (MP), India
| | - Ratnesh Das
- Department of Chemistry, ISF College of Pharmacy, Moga-Punjab, India
| | - Varsha Kashaw
- Sagar Institute of Pharmaceutical Sciences, Sagar (M.P.), India
| | - Arun K Iyer
- Use-inspired Biomaterials & Integrated Nano Delivery (U-BiND) Systems Laboratory, Department of Pharmaceutical Sciences, Wayne State University, Detroit, Michigan, USA
- Molecular Imaging Program, Karmanos Cancer Institute, Detroit, Michigan, USA
| | - Sushil Kumar Kashaw
- Integrated Drug Discovery Research Laboratory, Department of Pharmaceutical Sciences, Dr. Harisingh Gour University (A Central University), Sagar (MP), India
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22
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Chandran EBA, Iannantuono GM, Atiq SO, Akbulut D, Sinaii N, Simon NI, Banday AR, Boudjadi S, Gurram S, Nassar AH, Rosenberg JE, Butera G, Teo MY, Sonpavde G, Coleman JA, Apolo AB. Mismatch repair deficiency and microsatellite instability in urothelial carcinoma: a systematic review and meta-analysis. BMJ ONCOLOGY 2024; 3:e000335. [PMID: 39086924 PMCID: PMC11203074 DOI: 10.1136/bmjonc-2024-000335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
Background Mismatch repair deficiency (dMMR) and microsatellite instability-high (MSI-H) occur in a subset of cancers and have been shown to confer sensitivity to immune checkpoint inhibition (ICI); however, there is a lack of prospective data in urothelial carcinoma (UC). Methods and analysis We performed a systematic review to estimate the prevalence of dMMR and MSI-H in UC, including survival and clinical outcomes. We searched for studies published up to 26 October 2022 in major scientific databases. We screened 1745 studies and included 110. Meta-analyses were performed if the extracted data were suitable. Results The pooled weighted prevalences of dMMR in bladder cancer (BC) and upper tract UC (UTUC) were 2.30% (95% CI 1.12% to 4.65%) and 8.95% (95% CI 6.81% to 11.67%), respectively. The pooled weighted prevalences of MSI-H in BC and UTUC were 2.11% (95% CI 0.82% to 5.31%) and 8.36% (95% CI 5.50% to 12.53%), respectively. Comparing localised versus metastatic disease, the pooled weighted prevalences for MSI-H in BC were 5.26% (95% CI 0.86% to 26.12%) and 0.86% (95% CI 0.59% to 1.25%), respectively; and in UTUC, they were 18.04% (95% CI 13.36% to 23.91%) and 4.96% (95% CI 2.72% to 8.86%), respectively. Cumulatively, the response rate in dMMR/MSI-H metastatic UC treated with an ICI was 22/34 (64.7%) compared with 1/9 (11.1%) with chemotherapy. Conclusion Both dMMR and MSI-H occur more frequently in UTUC than in BC. In UC, MSI-H occurs more frequently in localised disease than in metastatic disease. These biomarkers may predict sensitivity to ICI in metastatic UC and resistance to cisplatin-based chemotherapy.
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Affiliation(s)
- Elias B A Chandran
- Genitourinary Malignancies Branch, National Institutes of Health, Bethesda, Maryland, USA
| | | | - Saad O Atiq
- Genitourinary Malignancies Branch, National Institutes of Health, Bethesda, Maryland, USA
| | - Dilara Akbulut
- Laboratory of Pathology, National Institutes of Health, Bethesda, Maryland, USA
| | - Ninet Sinaii
- Biostatistics and Clinical Epidemiology Service, National Institutes of Health, Bethesda, Maryland, USA
| | - Nicholas I Simon
- Genitourinary Malignancies Branch, National Institutes of Health, Bethesda, Maryland, USA
| | - Abdul Rouf Banday
- Genitourinary Malignancies Branch, National Institutes of Health, Bethesda, Maryland, USA
| | - Salah Boudjadi
- Genitourinary Malignancies Branch, National Institutes of Health, Bethesda, Maryland, USA
| | - Sandeep Gurram
- Urologic Oncology Branch, National Institutes of Health, Bethesda, Maryland, USA
| | - Amin H Nassar
- Department of Hematology/Oncology, Yale New Haven Hospital, New Haven, Connecticut, USA
| | | | - Gisela Butera
- Division of Library Services, National Institutes of Health, Bethesda, Maryland, USA
| | - Min Yuen Teo
- Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Guru Sonpavde
- Medical Oncology, AdventHealth Central Florida, Orlando, Florida, USA
| | | | - Andrea B Apolo
- Genitourinary Malignancies Branch, National Institutes of Health, Bethesda, Maryland, USA
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Houlston R, Culliford R, Lawrence S, Mills C, Tippu Z, Chubb D, Cornish A, Browining L, Kinnersley B, Bentham R, Sud A, Pallikonda H, Frangou A, Gruber A, Litchfield K, Wedge D, Larkin J, Turajlic S. Whole genome sequencing refines stratification and therapy of patients with clear cell renal cell carcinoma. RESEARCH SQUARE 2023:rs.3.rs-3675752. [PMID: 38106039 PMCID: PMC10723546 DOI: 10.21203/rs.3.rs-3675752/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer, but a comprehensive description of its genomic landscape is lacking. We report the whole genome sequencing of 778 ccRCC patients enrolled in the 100,000 Genomes Project, providing the most detailed somatic mutational landscape to date. We identify new driver genes, which as well as emphasising the major role of epigenetic regulation in ccRCC highlight additional biological pathways extending opportunities for drug repurposing. Genomic characterisation identified patients with divergent clinical outcome; higher number of structural copy number alterations associated with poorer prognosis, whereas VHL mutations were independently associated with a better prognosis. The twin observations that higher T-cell infiltration is associated with better outcome and that genetically predicted immune evasion is not common supports the rationale for immunotherapy. These findings should inform personalised surveillance and treatment strategies for ccRCC patients.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Amit Sud
- The Institute of Cancer Research
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24
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Baranov E, Nowak JA. Pathologic Evaluation of Therapeutic Biomarkers in Colorectal Adenocarcinoma. Surg Pathol Clin 2023; 16:635-650. [PMID: 37863556 DOI: 10.1016/j.path.2023.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2023]
Abstract
Molecular testing is an essential component of the pathologic evaluation of colorectal carcinoma providing diagnostic, prognostic, and predictive therapeutic information. Mismatch repair status evaluation is required for all tumors. Advanced and metastatic tumors also require determination of tumor mutational burden, KRAS, NRAS, and BRAF mutation status, ERBB2 amplification status, and NTRK and RET gene rearrangement status to guide therapy. Multiple assays, including immunohistochemistry, microsatellite instability testing, MLH1 promoter methylation, and next-generation sequencing, are typically needed. Pathologists must be aware of these requirements to optimally triage tissue. Advances in colorectal cancer molecular diagnostics will continue to drive refinements in colorectal cancer personalized therapy.
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Affiliation(s)
- Esther Baranov
- Department of Pathology, Brigham & Women's Hospital, 75 Francis Street, Boston, MA 02115, USA
| | - Jonathan A Nowak
- Department of Pathology, Brigham & Women's Hospital, 75 Francis Street, Boston, MA 02115, USA.
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25
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El Hajj J, Reddy S, Verma N, Huang EH, Kazmi SM. Immune Checkpoint Inhibitors in pMMR/MSS Colorectal Cancer. J Gastrointest Cancer 2023; 54:1017-1030. [PMID: 37009977 DOI: 10.1007/s12029-023-00927-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/09/2023] [Indexed: 04/04/2023]
Abstract
BACKGROUND Immune checkpoint inhibitors have recently replaced over chemotherapy as the first-line treatment for microsatellite instability-high or mismatch repair deficient (dMMR/MSI-H) stage 4 colorectal cancers. Considering this success, many studies have tried to replicate the use of immune checkpoint inhibitors, either as a single agent or in combination with other therapeutic agents, in the treatment of proficient mismatch repair (pMMR/MSS) stage 4 colorectal cancers. This review summarizes the seminal clinical data about the immune checkpoint inhibitors used in pMMR/MSS colorectal cancers and some future directions. RESULTS Studies concerning the use of immune checkpoint inhibitors as a single agent or in combination with other immune checkpoint inhibitors, targeted therapy, chemotherapy, or radiotherapy have proven inefficient in the treatment of pMMR/MSS colorectal cancer. However, a small subset of patients with pMMR/MSS colorectal cancer who has a mutation in POLE and POLD1 enzymes may respond to immunotherapy. Moreover, patients without liver metastasis appear to have a better chance of response. New immune checkpoint targets are being identified, such as VISTA, TIGIT, LAG3, STING signal pathway, and BTLA, and studies are ongoing to determine their efficiency in this disease type. CONCLUSION Immune checkpoint inhibitor-based regimens have not yet shown any meaningful positive outcomes for most pMMR/MSS colorectal cancers. A beneficial effect among a minority of these patients has been observed, but concrete biomarkers of response are lacking. Understanding the underlying mechanisms of immune resistance should guide further research for overcoming these obstacles.
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Affiliation(s)
- Joanna El Hajj
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
- Division of Hematology and Oncology, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA
| | - Sarah Reddy
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Nilesh Verma
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
- Division of Hematology and Oncology, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA
| | - Emina H Huang
- Department of Surgery, Division of Surgical Oncology, UT Southwestern Medical Center, Dallas, TX, USA
| | - Syed M Kazmi
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA.
- Division of Hematology and Oncology, UT Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX, 75390, USA.
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Xu H, Jia Z, Liu F, Li J, Huang Y, Jiang Y, Pu P, Shang T, Tang P, Zhou Y, Yang Y, Su J, Liu J. Biomarkers and experimental models for cancer immunology investigation. MedComm (Beijing) 2023; 4:e437. [PMID: 38045830 PMCID: PMC10693314 DOI: 10.1002/mco2.437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 11/01/2023] [Accepted: 11/10/2023] [Indexed: 12/05/2023] Open
Abstract
The rapid advancement of tumor immunotherapies poses challenges for the tools used in cancer immunology research, highlighting the need for highly effective biomarkers and reproducible experimental models. Current immunotherapy biomarkers encompass surface protein markers such as PD-L1, genetic features such as microsatellite instability, tumor-infiltrating lymphocytes, and biomarkers in liquid biopsy such as circulating tumor DNAs. Experimental models, ranging from 3D in vitro cultures (spheroids, submerged models, air-liquid interface models, organ-on-a-chips) to advanced 3D bioprinting techniques, have emerged as valuable platforms for cancer immunology investigations and immunotherapy biomarker research. By preserving native immune components or coculturing with exogenous immune cells, these models replicate the tumor microenvironment in vitro. Animal models like syngeneic models, genetically engineered models, and patient-derived xenografts provide opportunities to study in vivo tumor-immune interactions. Humanized animal models further enable the simulation of the human-specific tumor microenvironment. Here, we provide a comprehensive overview of the advantages, limitations, and prospects of different biomarkers and experimental models, specifically focusing on the role of biomarkers in predicting immunotherapy outcomes and the ability of experimental models to replicate the tumor microenvironment. By integrating cutting-edge biomarkers and experimental models, this review serves as a valuable resource for accessing the forefront of cancer immunology investigation.
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Affiliation(s)
- Hengyi Xu
- State Key Laboratory of Molecular OncologyNational Cancer Center /National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Eight‐year MD ProgramSchool of Clinical Medicine, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Ziqi Jia
- Department of Breast Surgical OncologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Fengshuo Liu
- Eight‐year MD ProgramSchool of Clinical Medicine, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Jiayi Li
- Eight‐year MD ProgramSchool of Clinical Medicine, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Department of Breast Surgical OncologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yansong Huang
- Eight‐year MD ProgramSchool of Clinical Medicine, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Department of Breast Surgical OncologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yiwen Jiang
- Eight‐year MD ProgramSchool of Clinical Medicine, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Pengming Pu
- Eight‐year MD ProgramSchool of Clinical Medicine, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Tongxuan Shang
- Eight‐year MD ProgramSchool of Clinical Medicine, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Pengrui Tang
- Eight‐year MD ProgramSchool of Clinical Medicine, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yongxin Zhou
- Eight‐year MD ProgramSchool of Clinical Medicine, Chinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
| | - Yufan Yang
- School of MedicineTsinghua UniversityBeijingChina
| | - Jianzhong Su
- Oujiang LaboratoryZhejiang Lab for Regenerative Medicine, Vision, and Brain HealthWenzhouZhejiangChina
| | - Jiaqi Liu
- State Key Laboratory of Molecular OncologyNational Cancer Center /National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
- Department of Breast Surgical OncologyNational Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina
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27
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Sehgal A, Ziaei-Jam H, Shen A, Gymrek M. Genome-wide detection of somatic mosaicism at short tandem repeats. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.22.568371. [PMID: 38045311 PMCID: PMC10690266 DOI: 10.1101/2023.11.22.568371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Motivation Somatic mosaicism, in which a mutation occurs post-zygotically, has been implicated in several developmental disorders, cancers, and other diseases. Short tandem repeats (STRs) consist of repeated sequences of 1-6bp and comprise more than 1 million loci in the human genome. Somatic mosaicism at STRs is known to play a key role in the pathogenicity of loci implicated in repeat expansion disorders and is highly prevalent in cancers exhibiting microsatellite instability. While a variety of tools have been developed to genotype germline variation at STRs, a method for systematically identifying mosaic STRs (mSTRs) is lacking. Results We introduce prancSTR, a novel method for detecting mSTRs from individual high-throughput sequencing datasets. Unlike many existing mosaicism detection methods for other variant types, prancSTR does not require a matched control sample as input. We show that prancSTR accurately identifies mSTRs in simulated data and demonstrate its feasibility by identifying candidate mSTRs in whole genome sequencing (WGS) data derived from lymphoblastoid cell lines for individuals sequenced by the 1000 Genomes Project. Our analysis identified an average of 76 and 577 non-homopolymer and homopolymer mSTRs respectively per cell line as well as multiple cell lines with outlier mSTR counts more than 6 times the population average, suggesting a subset of cell lines have particularly high STR instability rates. Availability prancSTR is freely available at https://github.com/gymrek-lab/trtools. Documentation Detailed documentation is available at https://trtools.readthedocs.io/.
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Affiliation(s)
- Aarushi Sehgal
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, USA
| | - Helyaneh Ziaei-Jam
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, USA
| | - Andrew Shen
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, USA
| | - Melissa Gymrek
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, USA
- Department of Medicine, University of California San Diego, La Jolla, USA
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28
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Chung Y, Nam SK, Chang HE, Lee C, Kang GH, Lee HS, Park KU. Evaluation of an eight marker-panel including long mononucleotide repeat markers to detect microsatellite instability in colorectal, gastric, and endometrial cancers. BMC Cancer 2023; 23:1100. [PMID: 37953261 PMCID: PMC10641958 DOI: 10.1186/s12885-023-11607-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 11/02/2023] [Indexed: 11/14/2023] Open
Abstract
BACKGROUND Accurate determination of microsatellite instability (MSI) status is critical for optimal treatment in cancer patients. Conventional MSI markers can sometimes display subtle shifts that are difficult to interpret, especially in non-colorectal cases. We evaluated an experimental eight marker-panel including long mononucleotide repeat (LMR) markers for detection of MSI. METHODS The eight marker-panel was comprised of five conventional markers (BAT-25, BAT-26, NR-21, NR-24, and NR-27) and three LMR markers (BAT-52, BAT-59 and BAT-62). MSI testing was performed against 300 specimens of colorectal, gastric, and endometrial cancers through PCR followed by capillary electrophoresis length analysis. RESULTS The MSI testing with eight marker-panel showed 99.3% (295/297) concordance with IHC analysis excluding 3 MMR-focal deficient cases. The sensitivity of BAT-59 and BAT-62 was higher than or comparable to that of conventional markers in gastric and endometrial cancer. The mean shift size was larger in LMR markers compared to conventional markers for gastric and endometrial cancers. CONCLUSIONS The MSI testing with eight maker-panel showed comparable performance with IHC analysis. The LMR markers, especially BAT-59 and BAT-62, showed high sensitivity and large shifts which can contribute to increased confidence in MSI classification, especially in gastric and endometrial cancers. Further study is needed with large number of samples for the validation of these LMR markers.
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Affiliation(s)
- Yousun Chung
- Department of Laboratory Medicine, Kangdong Sacred Heart Hospital, Seoul, Republic of Korea
| | - Soo Kyung Nam
- Department of Interdisciplinary Program in Cancer Biology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Ho Eun Chang
- Department of Laboratory Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Cheol Lee
- Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Pathology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Gyeong Hoon Kang
- Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Pathology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea
| | - Hye Seung Lee
- Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea.
- Department of Pathology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
| | - Kyoung Un Park
- Department of Laboratory Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.
- Department of Laboratory Medicine, Seoul National University Bundang Hospital, 82 Gumi-ro 173, Bundang-gu, Seongnam, 13620, Republic of Korea.
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29
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Chao J, Wang S, Wang H, Zhang N, Wang Y, Yang X, Zhu C, Ning C, Zhang X, Xue J, Zhang L, Piao M, Wang M, Yang X, Lu L, Zhao H. Real-world cohort study of PD-1 blockade plus lenvatinib for advanced intrahepatic cholangiocarcinoma: effectiveness, safety, and biomarker analysis. Cancer Immunol Immunother 2023; 72:3717-3726. [PMID: 37787790 DOI: 10.1007/s00262-023-03523-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 08/10/2023] [Indexed: 10/04/2023]
Abstract
BACKGROUND In clinical practice, some patients with advanced intrahepatic cholangiocarcinoma (ICC) cannot tolerate or refuse chemotherapy due to the toxicity, necessitating alternative treatments. PD-1 blockade combined with lenvatinib showed promising results in phase II studies with small sample size, but there is a lack of data on the routine use with this regimen. This study aimed to evaluate the effectiveness and safety of the regimen in patients with advanced ICC, and to identify predictors for treatment response and prognosis. METHODS We conducted a retrospective cohort study of patients treated with PD-1 inhibitors plus lenvatinib for advanced ICC between July 2017 and August 2022. The study endpoints were progression-free survival (PFS), overall survival (OS), objective response rate (ORR), disease control rate (DCR), and safety. Biomarker analysis for CA19-9 and PD-L1 expression was performed. Exploratory analysis for genetic alternation was conducted. RESULTS The study included 103 patients. It demonstrated a median PFS of 5.9 months and a median OS of 11.4 months. ORR was 18.4% and DCR was 80.6%. The incidence of grade 3 or 4 adverse events was 50.5%. Positive PD-L1 expression (TPS ≥ 1%) was associated with higher ORR (P = 0.013) and prolonged PFS (P = 0.023). Elevated CA19-9 (> 37 U/ml) was associated with decreased ORR (P = 0.019), poorer PFS (P = 0.005) and OS (P = 0.034). Patients with IDH1 mutations exhibited a favorable response to the treatment (P = 0.011), and patients with TP53 mutations tended to have worse OS (P = 0.031). CONCLUSIONS PD-1 blockade plus lenvatinib is effective and safe in routine practice. PD-L1 expression and CA19-9 level appear to predict the treatment efficacy. IDH1 mutations might indicate a better treatment response. CLINICAL TRIAL REGISTRATION NCT03892577.
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Affiliation(s)
- Jiashuo Chao
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
- Research Unit of Liver Transplantation and Transplant Immunology, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Nanjing, China
| | - Shanshan Wang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Hao Wang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
- Research Unit of Liver Transplantation and Transplant Immunology, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Nanjing, China
| | - Nan Zhang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Yunchao Wang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Xu Yang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Chengpei Zhu
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Cong Ning
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Xinmu Zhang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Jingnan Xue
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Longhao Zhang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Mingjian Piao
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Mingming Wang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
- Research Unit of Liver Transplantation and Transplant Immunology, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Nanjing, China
| | - Xiaobo Yang
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China
| | - Ling Lu
- Research Unit of Liver Transplantation and Transplant Immunology, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Nanjing, China.
- Affiliated Hospital of Xuzhou Medical University, Xuzhou, China.
| | - Haitao Zhao
- Department of Liver Surgery, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (CAMS & PUMC), Beijing, China.
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30
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Yu J, Ding PR, Jiang W. Screening and Management of Lynch Syndrome: The Chinese Experience. Clin Colon Rectal Surg 2023; 36:369-377. [PMID: 37795465 PMCID: PMC10547539 DOI: 10.1055/s-0043-1767706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/06/2023]
Abstract
Lynch syndrome (LS), caused by germline mutations in the mismatch repair genes, is the most common hereditary colorectal cancer. While LS is also associated with various cancers, early detection of the proband is meaningful for tumor prevention, treatment, and familial management. It has been a dramatic shift on the screening approaches for LS. As the rapid development of the molecular biological methods, a comprehensive understanding of the LS screening strategies will help to improve the clinical care for this systematic disease. The current screening strategies have been well validated but mainly by evidence derived from western population, lacking consideration of the ethnic heterogeneity, which hampers the universality and clinical application in China. Hence, this review will focus on the Chinese experience in LS screening, aiming to help better understand the ethnic diversity and further optimize the screening strategies.
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Affiliation(s)
- Jiehai Yu
- Department of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou Guangdong, P. R. China
| | - Pei-Rong Ding
- Department of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou Guangdong, P. R. China
| | - Wu Jiang
- Department of Colorectal Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou Guangdong, P. R. China
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31
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Bacher JW, Udho EB, Strauss EE, Vyazunova I, Gallinger S, Buchanan DD, Pai RK, Templeton AS, Storts DR, Eshleman JR, Halberg RB. A Highly Sensitive Pan-Cancer Test for Microsatellite Instability. J Mol Diagn 2023; 25:806-826. [PMID: 37544360 PMCID: PMC10629437 DOI: 10.1016/j.jmoldx.2023.07.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 07/10/2023] [Accepted: 07/18/2023] [Indexed: 08/08/2023] Open
Abstract
Microsatellite instability (MSI) is an evolving biomarker for cancer detection and treatment. MSI was first used to identify patients with Lynch syndrome, a hereditary form of colorectal cancer (CRC), but has recently become indispensable in predicting patient response to immunotherapy. To address the need for pan-cancer MSI detection, a new multiplex assay was developed that uses novel long mononucleotide repeat (LMR) markers to improve sensitivity. A total of 469 tumor samples from 20 different cancer types, including 319 from patients with Lynch syndrome, were tested for MSI using the new LMR MSI Analysis System. Results were validated by using deficient mismatch repair (dMMR) status according to immunohistochemistry as the reference standard and compared versus the Promega pentaplex MSI panel. The sensitivity of the LMR panel for detection of dMMR status by immunohistochemistry was 99% for CRC and 96% for non-CRC. The overall percent agreement between the LMR and Promega pentaplex panels was 99% for CRC and 89% for non-CRC tumors. An increased number of unstable markers and the larger size shifts observed in dMMR tumors using the LMR panel increased confidence in MSI determinations. The LMR MSI Analysis System expands the spectrum of cancer types in which MSI can be accurately detected.
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Affiliation(s)
- Jeffery W Bacher
- R&D Clinical Diagnostics, Promega Corporation, Madison, Wisconsin; Department of Medicine, University of Wisconsin, Madison, Wisconsin.
| | - Eshwar B Udho
- R&D Clinical Diagnostics, Promega Corporation, Madison, Wisconsin
| | | | - Irina Vyazunova
- R&D Clinical Diagnostics, Promega Corporation, Madison, Wisconsin
| | - Steven Gallinger
- Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Daniel D Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia; University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria, Australia; Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Rish K Pai
- Health Science Research, Mayo Clinic, Scottsdale, Arizona
| | | | - Douglas R Storts
- R&D Clinical Diagnostics, Promega Corporation, Madison, Wisconsin
| | - James R Eshleman
- School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Richard B Halberg
- Department of Medicine, University of Wisconsin, Madison, Wisconsin; Department of Oncology, McArdle Laboratory of Cancer Research, University of Wisconsin, Madison, Wisconsin; University of Wisconsin Carbone Cancer Center, Madison, Wisconsin.
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Edsjö A, Holmquist L, Geoerger B, Nowak F, Gomon G, Alix-Panabières C, Ploeger C, Lassen U, Le Tourneau C, Lehtiö J, Ott PA, von Deimling A, Fröhling S, Voest E, Klauschen F, Dienstmann R, Alshibany A, Siu LL, Stenzinger A. Precision cancer medicine: Concepts, current practice, and future developments. J Intern Med 2023; 294:455-481. [PMID: 37641393 DOI: 10.1111/joim.13709] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Precision cancer medicine is a multidisciplinary team effort that requires involvement and commitment of many stakeholders including the society at large. Building on the success of significant advances in precision therapy for oncological patients over the last two decades, future developments will be significantly shaped by improvements in scalable molecular diagnostics in which increasingly complex multilayered datasets require transformation into clinically useful information guiding patient management at fast turnaround times. Adaptive profiling strategies involving tissue- and liquid-based testing that account for the immense plasticity of cancer during the patient's journey and also include early detection approaches are already finding their way into clinical routine and will become paramount. A second major driver is the development of smart clinical trials and trial concepts which, complemented by real-world evidence, rapidly broaden the spectrum of therapeutic options. Tight coordination with regulatory agencies and health technology assessment bodies is crucial in this context. Multicentric networks operating nationally and internationally are key in implementing precision oncology in clinical practice and support developing and improving the ecosystem and framework needed to turn invocation into benefits for patients. The review provides an overview of the diagnostic tools, innovative clinical studies, and collaborative efforts needed to realize precision cancer medicine.
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Affiliation(s)
- Anders Edsjö
- Department of Clinical Genetics, Pathology and Molecular Diagnostics, Office for Medical Services, Region Skåne, Lund, Sweden
- Division of Pathology, Department of Clinical Sciences, Lund University, Lund, Sweden
- Genomic Medicine Sweden (GMS), Kristianstad, Sweden
| | - Louise Holmquist
- Department of Clinical Genetics, Pathology and Molecular Diagnostics, Office for Medical Services, Region Skåne, Lund, Sweden
- Genomic Medicine Sweden (GMS), Kristianstad, Sweden
| | - Birgit Geoerger
- Department of Pediatric and Adolescent Oncology, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
- INSERM U1015, Gustave Roussy Cancer Campus, Université Paris-Saclay, Villejuif, France
| | | | - Georgy Gomon
- Department of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
- Department of Medical Oncology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Catherine Alix-Panabières
- Laboratory of Rare Human Circulating Cells, University Medical Center of Montpellier, Montpellier, France
- CREEC, MIVEGEC, University of Montpellier, Montpellier, France
| | - Carolin Ploeger
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
- Centers for Personalized Medicine (ZPM), Heidelberg, Germany
| | - Ulrik Lassen
- Department of Oncology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Christophe Le Tourneau
- Department of Drug Development and Innovation (D3i), Institut Curie, Paris, France
- INSERM U900 Research Unit, Saint-Cloud, France
- Faculty of Medicine, Paris-Saclay University, Paris, France
| | - Janne Lehtiö
- Department of Oncology Pathology, Karolinska Institutet, Science for Life Laboratory, Stockholm, Sweden
| | - Patrick A Ott
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
| | - Andreas von Deimling
- Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Stefan Fröhling
- Division of Translational Medical Oncology, National Center for Tumor Diseases (NCT) Heidelberg and German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), Heidelberg, Germany
| | - Emile Voest
- Department of Molecular Oncology and Immunology, The Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands
- Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Frederick Klauschen
- Institute of Pathology, Charite - Universitätsmedizin Berlin, Berlin, Germany
- German Cancer Consortium (DKTK), Partner Site Berlin, and German Cancer Research Center (DKFZ), Heidelberg, Germany
- BIFOLD - Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
- Institute of Pathology, Ludwig-Maximilians-University, Munich, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Munich Partner Site, Heidelberg, Germany
| | | | | | - Lillian L Siu
- Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Albrecht Stenzinger
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
- Centers for Personalized Medicine (ZPM), Heidelberg, Germany
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Cao Y, Wang D, Wu J, Yao Z, Shen S, Niu C, Liu Y, Zhang P, Wang Q, Wang J, Li H, Wei X, Wang X, Dong Q. MSI-XGNN: an explainable GNN computational framework integrating transcription- and methylation-level biomarkers for microsatellite instability detection. Brief Bioinform 2023; 24:bbad362. [PMID: 37833839 DOI: 10.1093/bib/bbad362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 09/05/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023] Open
Abstract
Microsatellite instability (MSI) is a hypermutator phenotype caused by DNA mismatch repair deficiency. MSI has been reported in various human cancers, particularly colorectal, gastric and endometrial cancers. MSI is a promising biomarker for cancer prognosis and immune checkpoint blockade immunotherapy. Several computational methods have been developed for MSI detection using DNA- or RNA-based approaches based on next-generation sequencing. Epigenetic mechanisms, such as DNA methylation, regulate gene expression and play critical roles in the development and progression of cancer. We here developed MSI-XGNN, a new computational framework for predicting MSI status using bulk RNA-sequencing and DNA methylation data. MSI-XGNN is an explainable deep learning model that combines a graph neural network (GNN) model to extract features from the gene-methylation probe network with a CatBoost model to classify MSI status. MSI-XGNN, which requires tumor-only samples, exhibited comparable performance with two well-known methods that require tumor-normal paired sequencing data, MSIsensor and MANTIS and better performance than several other tools. MSI-XGNN also showed good generalizability on independent validation datasets. MSI-XGNN identified six MSI markers consisting of four methylation probes (EPM2AIP1|MLH1:cg14598950, EPM2AIP1|MLH1:cg27331401, LNP1:cg05428436 and TSC22D2:cg15048832) and two genes (RPL22L1 and MSH4) constituting the optimal feature subset. All six markers were significantly associated with beneficial tumor microenvironment characteristics for immunotherapy, such as tumor mutation burden, neoantigens and immune checkpoint molecules such as programmed cell death-1 and cytotoxic T-lymphocyte antigen-4. Overall, our study provides a powerful and explainable deep learning model for predicting MSI status and identifying MSI markers that can potentially be used for clinical MSI evaluation.
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Affiliation(s)
- Yang Cao
- Department of Environmental Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | - Dan Wang
- Department of Bioinformatics, Yicon (Beijing) Biomedical Technology Inc
| | - Jin Wu
- Tianjin Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | - Zhanxin Yao
- Tianjin Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | - Si Shen
- School and Hospital of Stomatology, Tianjin Medical University, Tianjin 300050, China
| | - Chao Niu
- Department of Environmental Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | - Ying Liu
- Department of Environmental Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | - Pengcheng Zhang
- Department of Environmental Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | | | - Jinhao Wang
- Department of Environmental Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | - Hua Li
- Department of Diagnostic and Therapeutic Ultrasonography, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| | - Xi Wei
- Department of Diagnostic and Therapeutic Ultrasonography, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| | - Xinxing Wang
- Department of Environmental Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin 300050, China
| | - Qingyang Dong
- Department of Environmental Medicine, Tianjin Institute of Environmental and Operational Medicine, Tianjin 300050, China
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Kazdal D, Menzel M, Budczies J, Stenzinger A. [Molecular tumor diagnostics as the driving force behind precision oncology]. Dtsch Med Wochenschr 2023; 148:1157-1165. [PMID: 37657453 DOI: 10.1055/a-1937-0347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/03/2023]
Abstract
Molecular pathological diagnostics plays a central role in personalized oncology and requires multidisciplinary teamwork. It is just as relevant for the individual patient who is being treated with an approved therapy method or an individual treatment attempt as it is for prospective clinical studies that require the identification of specific therapeutic target structures or complex biomarkers for study inclusion. It is also of crucial importance for the generation of real-world data, which is becoming increasingly important for drug development. Future developments will be significantly shaped by improvements in scalable molecular diagnostics, in which increasingly complex and multi-layered data sets must be quickly converted into clinically useful information. One focus will be on the development of adaptive diagnostic strategies in order to be able to depict the enormous plasticity of a cancer disease over time.
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35
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Rodriguez IV, Strickland S, Wells D, Manhardt E, Konnick EQ, Garcia R, Swisher E, Kilgore M, Norquist B. Adoption of Universal Testing in Endometrial Cancers for Microsatellite Instability Using Next-Generation Sequencing. JCO Precis Oncol 2023; 7:e2300033. [PMID: 37856764 PMCID: PMC10861015 DOI: 10.1200/po.23.00033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 06/28/2023] [Accepted: 08/18/2023] [Indexed: 10/21/2023] Open
Abstract
PURPOSE To assess implementation of a next-generation sequencing (NGS) assay to detect microsatellite instability (MSI) as a screen for Lynch syndrome (LS) in endometrial cancer (EC), while determining and comparing characteristics of the four molecular subtypes. METHODS A retrospective review was performed of 408 total patients with newly diagnosed EC: 140 patients who underwent universal screening with NGS and 268 patients who underwent screening via mismatch repair immunohistochemistry (MMR IHC) as part of a historical screening paradigm. In the NGS cohort, incidental POLE and TP53 mutations along with MSI were identified and used to characterize EC into molecular subtypes: POLE-ultramutated, MSI high (MSI-H), TP53-mutated, and no specific molecular profile (NSMP). In historical cohorts, age- and/or family history-directed screening was performed with MMR IHC. Statistical analysis was performed using a t-test for continuous variables and chi-square or Fisher's exact test for categorical variables. RESULTS In the NGS cohort, 38 subjects (27%) had MSI-H EC, 100 (71%) had microsatellite stable EC, and two (1%) had an indeterminate result. LS was diagnosed in two subjects (1%), and all but five patients completed genetic screening (96%). Molecular subtypes were ascertained: eight had POLE-ultramutated EC, 28 had TP53-mutated EC (20%), and 66 (47%) had NSMP. MSI-H and TP53-mutated EC had worse prognostic features compared with NSMP EC. Comparison with historical cohorts demonstrated a significant increase in follow-up testing after an initial positive genetic screen in the MSI NGS cohort (56% v 89%; P = .001). CONCLUSION MSI by NGS allowed for simultaneous screening for LS and categorization of EC into molecular subtypes with prognostic and therapeutic implications.
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Affiliation(s)
- Isabel V. Rodriguez
- Department of Obstetrics and Gynecology, University of Washington, Seattle, WA
| | - Sarah Strickland
- Department of Pathology and Laboratory Medicine, University of Ottawa, Ottawa, Canada
| | - David Wells
- Department of Pathology and Laboratory Medicine, University of Washington, Seattle, WA
| | - Enna Manhardt
- Department of Obstetrics and Gynecology, University of Washington, Seattle, WA
| | - Eric Q. Konnick
- Department of Pathology and Laboratory Medicine, University of Washington, Seattle, WA
| | - Rochelle Garcia
- Department of Pathology and Laboratory Medicine, University of Washington, Seattle, WA
| | - Elizabeth Swisher
- Department of Obstetrics and Gynecology, University of Washington, Seattle, WA
| | - Mark Kilgore
- Department of Pathology and Laboratory Medicine, University of Washington, Seattle, WA
| | - Barbara Norquist
- Department of Obstetrics and Gynecology, University of Washington, Seattle, WA
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Yang L, Wang J, Altreuter J, Jhaveri A, Wong CJ, Song L, Fu J, Taing L, Bodapati S, Sahu A, Tokheim C, Zhang Y, Zeng Z, Bai G, Tang M, Qiu X, Long HW, Michor F, Liu Y, Liu XS. Tutorial: integrative computational analysis of bulk RNA-sequencing data to characterize tumor immunity using RIMA. Nat Protoc 2023; 18:2404-2414. [PMID: 37391666 DOI: 10.1038/s41596-023-00841-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 02/22/2023] [Indexed: 07/02/2023]
Abstract
RNA-sequencing (RNA-seq) has become an increasingly cost-effective technique for molecular profiling and immune characterization of tumors. In the past decade, many computational tools have been developed to characterize tumor immunity from gene expression data. However, the analysis of large-scale RNA-seq data requires bioinformatics proficiency, large computational resources and cancer genomics and immunology knowledge. In this tutorial, we provide an overview of computational analysis of bulk RNA-seq data for immune characterization of tumors and introduce commonly used computational tools with relevance to cancer immunology and immunotherapy. These tools have diverse functions such as evaluation of expression signatures, estimation of immune infiltration, inference of the immune repertoire, prediction of immunotherapy response, neoantigen detection and microbiome quantification. We describe the RNA-seq IMmune Analysis (RIMA) pipeline integrating many of these tools to streamline RNA-seq analysis. We also developed a comprehensive and user-friendly guide in the form of a GitBook with text and video demos to assist users in analyzing bulk RNA-seq data for immune characterization at both individual sample and cohort levels by using RIMA.
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Affiliation(s)
- Lin Yang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Jin Wang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- School of Life Science and Technology, Tongji University, Shanghai, China
| | - Jennifer Altreuter
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Aashna Jhaveri
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Cheryl J Wong
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Li Song
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Jingxin Fu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- School of Life Science and Technology, Tongji University, Shanghai, China
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Len Taing
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Sudheshna Bodapati
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Avinash Sahu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Collin Tokheim
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Yi Zhang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Zexian Zeng
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Gali Bai
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Ming Tang
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Xintao Qiu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Henry W Long
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Franziska Michor
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
- Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA, USA
- The Ludwig Center at Harvard, Boston, MA, USA
| | - Yang Liu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA.
| | - X Shirley Liu
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA.
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA.
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Bartels S, Grote I, Wagner M, Boog J, Schipper E, Reineke‐Plaass T, Kreipe H, Lehmann U. Concordance in detection of microsatellite instability by PCR and NGS in routinely processed tumor specimens of several cancer types. Cancer Med 2023; 12:16707-16715. [PMID: 37376830 PMCID: PMC10501280 DOI: 10.1002/cam4.6293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 06/14/2023] [Accepted: 06/15/2023] [Indexed: 06/29/2023] Open
Abstract
BACKGROUND Microsatellite instability (MSI) occurs in several cancer types and is commonly used for prognosis and as a predictive biomarker for immune checkpoint therapy. METHODS We analyzed n = 263 formalin-fixed paraffin-embedded (FFPE) tumor specimens (127 colorectal cancer (CRC), 55 endometrial cancer (EC), 33 stomach adenocarcinoma (STAD), and 48 solid tumor specimens of other tumor types) with a capillary electrophoresis based multiplex monomorphic marker MSI-PCR panel and an amplicon-based NGS assay for microsatellite instability (MSI+). In total, n = 103 (39.2%) cases with a known defect of the DNA mismatch repair system (dMMR), determined by a loss in protein expression of MSH2/MSH6 (n = 48, 46.6%) or MLH1/PMS2 (n = 55, 53.4%), were selected. Cases with an isolated loss of MSH6 or PMS2 were excluded. RESULTS The overall sensitivity and specificity of the NGS assay in comparison with the MSI-PCR were 92.2% and 98.8%. With CRC cases a nearly optimal concordance was reached (sensitivity 98.1% and specificity 100.0%). Whereas EC cases only show a sensitivity of 88.6% and a specificity of 95.2%, caused by several cases with instability in less than five monomorphic markers, which could be difficult to analyze by NGS (subtle MSI+ phenotype). CONCLUSIONS MSI analysis of FFPE DNA by NGS is feasible and the results show a high concordance in comparison with the monomorphic marker MSI-PCR. However, cases with a subtle MSI+ phenotype, most frequently manifest in EC, have a risk of a false-negative result by NGS and should be preferentially analyzed by capillary electrophoresis.
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Affiliation(s)
- Stephan Bartels
- Institute of Pathology, Hannover Medical SchoolHannoverGermany
| | - Isabel Grote
- Institute of Pathology, Hannover Medical SchoolHannoverGermany
| | | | - Jannik Boog
- Institute of Pathology, Hannover Medical SchoolHannoverGermany
| | - Elisa Schipper
- Institute of Pathology, Hannover Medical SchoolHannoverGermany
| | | | - Hans Kreipe
- Institute of Pathology, Hannover Medical SchoolHannoverGermany
| | - Ulrich Lehmann
- Institute of Pathology, Hannover Medical SchoolHannoverGermany
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Grypari IM, Tzelepi V, Gyftopoulos K. DNA Damage Repair Pathways in Prostate Cancer: A Narrative Review of Molecular Mechanisms, Emerging Biomarkers and Therapeutic Targets in Precision Oncology. Int J Mol Sci 2023; 24:11418. [PMID: 37511177 PMCID: PMC10380086 DOI: 10.3390/ijms241411418] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Revised: 07/09/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
Prostate cancer (PCa) has a distinct molecular signature, including characteristic chromosomal translocations, gene deletions and defective DNA damage repair mechanisms. One crucial pathway involved is homologous recombination deficiency (HRD) and it is found in almost 20% of metastatic castrate-resistant PCa (mCRPC). Inherited/germline mutations are associated with a hereditary predisposition to early PCa development and aggressive behavior. BRCA2, ATM and CHECK2 are the most frequently HRD-mutated genes. BRCA2-mutated tumors have unfavorable clinical and pathological characteristics, such as intraductal carcinoma. PARP inhibitors, due to the induction of synthetic lethality, have been therapeutically approved for mCRPC with HRD alterations. Mutations are detected in metastatic tissue, while a liquid biopsy is utilized during follow-up, recognizing acquired resistance mechanisms. The mismatch repair (MMR) pathway is another DNA repair mechanism implicated in carcinogenesis, although only 5% of metastatic PCa is affected. It is associated with aggressive disease. PD-1 inhibitors have been used in MMR-deficient tumors; thus, the MMR status should be tested in all metastatic PCa cases. A surrogate marker of defective DNA repair mechanisms is the tumor mutational burden. PDL-1 expression and intratumoral lymphocytes have ambivalent predictive value. Few experimental molecules have been so far proposed as potential biomarkers. Future research may further elucidate the role of DNA damage pathways in PCa, revealing new therapeutic targets and predictive biomarkers.
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Affiliation(s)
- Ioanna-Maria Grypari
- Cytology Department, Aretaieion University Hospital, National Kapodistrian University of Athens, 11528 Athens, Greece
| | - Vasiliki Tzelepi
- Department of Pathology, School of Medicine, University of Patras, 26504 Patras, Greece
| | - Kostis Gyftopoulos
- Department of Anatomy, School of Medicine, University of Patras, 26504 Patras, Greece
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39
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Elze L, van der Post RS, Vos JR, Mensenkamp AR, de Hullu MSC, Nagtegaal ID, Hoogerbrugge N, de Voer RM, Ligtenberg MJL. Microsatellite instability in noncolorectal and nonendometrial malignancies in patients with Lynch syndrome. J Natl Cancer Inst 2023; 115:853-860. [PMID: 37018159 PMCID: PMC10323896 DOI: 10.1093/jnci/djad063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 02/27/2023] [Accepted: 04/02/2023] [Indexed: 04/06/2023] Open
Abstract
BACKGROUND Individuals with Lynch syndrome are at increased hereditary risk of colorectal and endometrial carcinomas with microsatellite instability (MSI-H) and mismatch repair-deficiency (dMMR), which make these tumors vulnerable to therapy with immune checkpoint inhibitors. Our aim is to assess how often other tumor types in these individuals share these characteristics. METHODS We retrieved the full tumor history of a historical clinic-based cohort of 1745 individuals with Lynch syndrome and calculated the standardized incidence ratio for all tumor types. MSI status, somatic second hit alterations, and immunohistochemistry-based MMR status were analyzed in 236 noncolorectal and nonendometrial malignant tumors. RESULTS In individuals with Lynch syndrome MSI-H/dMMR occurred both in Lynch-spectrum and in non-Lynch-spectrum malignancies (85% vs 37%, P < .01). MSI-H/dMMR malignancies were found in nearly all non-Lynch-spectrum tumor types. Almost all breast carcinomas had medullary features, and most of them were MSI-H/dMMR. Breast carcinoma with medullary features were shown to be associated with Lynch syndrome (standardized incidence ratio = 38.8, 95% confidence interval = 16.7 to 76.5). CONCLUSIONS In individuals with Lynch syndrome, MSI-H/dMMR occurs in more than one-half of the malignancies other than colorectal and endometrial carcinomas, including tumor types without increased incidence. The Lynch-spectrum tumors should be expanded to breast carcinomas with medullary features. All malignancies in patients with Lynch syndrome, independent of subtype, should be tested for MSI-H/dMMR in case therapy with immune checkpoint inhibitors is considered. Moreover, Lynch syndrome should be considered an underlying cause of all MSI-H/dMMR malignancies other than colorectal and endometrial carcinomas.
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Affiliation(s)
- Lisa Elze
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, the Netherlands
| | - Rachel S van der Post
- Department of Pathology, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, the Netherlands
| | - Janet R Vos
- Department of Human Genetics, Radboud Institute for Health Sciences, Radboud university medical center, Nijmegen, the Netherlands
| | - Arjen R Mensenkamp
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, the Netherlands
| | - Mirjam S C de Hullu
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, the Netherlands
| | - Iris D Nagtegaal
- Department of Pathology, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, the Netherlands
| | - Nicoline Hoogerbrugge
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, the Netherlands
| | - Richarda M de Voer
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, the Netherlands
| | - Marjolijn J L Ligtenberg
- Department of Human Genetics, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, the Netherlands
- Department of Pathology, Radboud Institute for Molecular Life Sciences, Radboud university medical center, Nijmegen, the Netherlands
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40
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Zhan Y, Ni K, Liu Z, Xin R, Han Q, Ping H, Liu Y, Zhao X, Wang W, Yan S, Sun J, Zhang Q, Wang G, Zhang Z, Zhang X, Hu X, Li G, Zhang C. Stage III deficient mismatch repair colon patients get greater benefit from earlier starting oxaliplatin-based chemotherapy regimen. Sci Rep 2023; 13:8969. [PMID: 37268749 DOI: 10.1038/s41598-023-33153-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 04/07/2023] [Indexed: 06/04/2023] Open
Abstract
We evaluate the prognostic value of chemotherapy and other prognostic factors on overall survival among colon patients with deficient mismatch repair (dMMR), and determine the optimum time to start chemotherapy after surgery. Data of 306 colon cancer patients with dMMR who received radical surgery were collected from three Chinese centers between August 2012 and January 2018. Overall survival (OS) was assessed with the Kaplan-Meier method and log-rank. Cox regression analysis were used to assess influencing prognosis factors. The median follow-up time for all patients was 45.0 months (range, 1.0-100). There was a nonsignificant OS benefit from chemotherapy for patients with stage I and stage II disease, including high-risk stage II disease (log-rank p: 0.386, 0.779, 0.921), and a significant OS benefit for patients with stage III and stage IV disease for receiving post-operation chemotherapy (log-rank p = 0.002, 0.019). Stage III patients benefitted from chemotherapy regimens that contained oxaliplatin (log-rank p = 0.004), and Starting chemotherapy with oxaliplatin treatment earlier resulted in better outcomes (95% CI 0.013-0.857; p = 0.035). Chemotherapy regimens containing oxaliplatin can prolong the survival time of stage III and IV dMMR colon cancer patients. This beneficial manifestation was more pronounced after starting chemotherapy treatment early post operation. High risk stage II dMMR colon patients including T4N0M0 cannot benefit from chemotherapy.
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Affiliation(s)
- Yixiang Zhan
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China
- School of Medicine, Nankai University, Tianjin, China
| | - Kemin Ni
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China
- School of Medicine, Nankai University, Tianjin, China
| | - Zhaoce Liu
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China
- School of Medicine, Nankai University, Tianjin, China
| | - Ran Xin
- School of Medicine, Nankai University, Tianjin, China
| | - Qiurong Han
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China
- Tianjin Institute of Coloproctology, Tianjin, China
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Hangyu Ping
- School of Medicine, Nankai University, Tianjin, China
| | - Yaohong Liu
- School of Medicine, Nankai University, Tianjin, China
| | - Xuanzhu Zhao
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China
- Tianjin Institute of Coloproctology, Tianjin, China
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Wanting Wang
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China
- Tianjin Institute of Coloproctology, Tianjin, China
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Suying Yan
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China
- Tianjin Institute of Coloproctology, Tianjin, China
- School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Jing Sun
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China
- Tianjin Institute of Coloproctology, Tianjin, China
- The Institute of Translational Medicine, Tianjin Union Medical Center of Nankai University, Tianjin, China
| | - Qinghuai Zhang
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China
- Tianjin Institute of Coloproctology, Tianjin, China
- The Institute of Translational Medicine, Tianjin Union Medical Center of Nankai University, Tianjin, China
| | - Guihua Wang
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zili Zhang
- The Third Central, Clinical College of Tianjin Medical University, Tianjin, China
| | - Xipeng Zhang
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China
- Tianjin Institute of Coloproctology, Tianjin, China
- The Institute of Translational Medicine, Tianjin Union Medical Center of Nankai University, Tianjin, China
| | - Xia Hu
- Department of Agriculture Insect, Institute of Plant Protection, Tianjin Academy of Agricultural Sciences, Tianjin, China
| | - Guoxun Li
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China.
- Tianjin Institute of Coloproctology, Tianjin, China.
- The Institute of Translational Medicine, Tianjin Union Medical Center of Nankai University, Tianjin, China.
| | - Chunze Zhang
- Department of Colorectal Surgery, Tianjin Union Medical Center, Tianjin, 300121, China.
- Tianjin Institute of Coloproctology, Tianjin, China.
- The Institute of Translational Medicine, Tianjin Union Medical Center of Nankai University, Tianjin, China.
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Yakushina V, Kavun A, Veselovsky E, Grigoreva T, Belova E, Lebedeva A, Mileyko V, Ivanov M. Microsatellite Instability Detection: The Current Standards, Limitations, and Misinterpretations. JCO Precis Oncol 2023; 7:e2300010. [PMID: 37315263 DOI: 10.1200/po.23.00010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 04/06/2023] [Accepted: 04/26/2023] [Indexed: 06/16/2023] Open
Affiliation(s)
- Valentina Yakushina
- OncoAtlas LLC, Moscow, Russian Federation
- Laboratory of Epigenetics, Research Centre for Medical Genetics, Moscow, Russian Federation
| | | | - Egor Veselovsky
- OncoAtlas LLC, Moscow, Russian Federation
- Department of Evolutionary Genetics of Development, Koltzov Institute of Developmental Biology of the Russian Academy of Sciences, Moscow, Russian Federation
| | - Tatiana Grigoreva
- OncoAtlas LLC, Moscow, Russian Federation
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russian Federation
| | - Ekaterina Belova
- OncoAtlas LLC, Moscow, Russian Federation
- Lomonosov Moscow State University, Moscow, Russian Federation
| | | | | | - Maxim Ivanov
- OncoAtlas LLC, Moscow, Russian Federation
- Moscow Institute of Physics and Technology, Moscow, Russian Federation
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Zhang Z, Wan H, Xu B, He H, Shan G, Zhang J, Wu Q, Li T. A robust microsatellite instability detection model for unpaired colorectal cancer tissue samples. Chin Med J (Engl) 2023; 136:1082-1088. [PMID: 37022939 PMCID: PMC10228480 DOI: 10.1097/cm9.0000000000002216] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Indexed: 04/07/2023] Open
Abstract
BACKGROUND Microsatellite instability (MSI) is a key biomarker for cancer immunotherapy and prognosis. Integration of MSI testing into a next-generation-sequencing (NGS) panel could save tissue sample, reduce turn-around time and cost, and provide MSI status and comprehensive genomic profiling in single test. We aimed to develop an MSI calling model to detect MSI status along with the NGS panel-based profiling test using tumor-only samples. METHODS From January 2019 to December 2020, a total of 174 colorectal cancer (CRC) patients were enrolled, including 31 MSI-high (MSI-H) and 143 microsatellite stability (MSS) cases. Among them, 56 paired tumor and normal samples (10 MSI-H and 46 MSS) were used for modeling, and another 118 tumor-only samples were used for validation. MSI polymerase chain reaction (MSI-PCR) was performed as the gold standard. A baseline was built for the selected microsatellite loci using the NGS data of 56 normal blood samples. An MSI detection model was constructed by analyzing the NGS data of tissue samples. The performance of the model was compared with the results of MSI-PCR. RESULTS We first intersected the target genomic regions of the NGS panels used in this study to select common microsatellite loci. A total of 42 loci including 23 mononucleotide repeat sites and 19 longer repeat sites were candidates for modeling. As mononucleotide repeat sites are more sensitive and specific for detecting MSI status than sites with longer length motif and the mononucleotide repeat sites performed even better than the total sites, a model containing 23 mononucleotide repeat sites was constructed and named Colorectal Cancer Microsatellite Instability test (CRC-MSI). The model achieved 100% sensitivity and 100% specificity when compared with MSI-PCR in both training and validation sets. Furthermore, the CRC-MSI model was robust with the tumor content as low as 6%. In addition, 8 out of 10 MSI-H samples showed alternations in the four mismatch repair genes ( MLH1 , MSH2 , MSH6 , and PMS2 ). CONCLUSION MSI status can be accurately determined along the targeted NGS panels using only tumor samples. The performance of mononucleotide repeat sites surpasses loci with longer repeat motif in MSI calling.
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Affiliation(s)
- Zili Zhang
- Department of General Surgery, The Third Central Clinical College of Tianjin Medical University, The Third Central Hospital of Tianjin, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, Tianjin 300170, China
| | - Hua Wan
- Department of Medicine, Beijing USCI Medical Laboratory, Beijing 100195, China
| | - Bing Xu
- Department of Medicine, Beijing USCI Medical Laboratory, Beijing 100195, China
| | - Hongyang He
- Department of General Surgery, The First Affiliated Hospital of Dali University, Dali, Yunnan 671013, China
| | - Guangyu Shan
- Department of Medicine, Beijing USCI Medical Laboratory, Beijing 100195, China
| | - Jingbo Zhang
- Department of Medicine, Beijing USCI Medical Laboratory, Beijing 100195, China
| | - Qixi Wu
- Department of Medicine, Beijing USCI Medical Laboratory, Beijing 100195, China
| | - Tong Li
- Department of Heart Center, The Third Central Clinical College of Tianjin Medical University, The Third Central Hospital of Tianjin, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, Tianjin 300170, China
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Nourmohammadi Abadchi S, Sena LA, Antonarakis ES, Pritchard CC, Eshleman JR, Konnick EQ, Salipante SJ, Shenderov E, Lotan TL. MLH1 Loss in Primary Prostate Cancer. JCO Precis Oncol 2023; 7:e2200611. [PMID: 37196219 PMCID: PMC10309570 DOI: 10.1200/po.22.00611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 01/25/2023] [Accepted: 03/17/2023] [Indexed: 05/19/2023] Open
Abstract
PURPOSE Among mismatch repair-deficient (MMRd) prostate cancers, loss of MLH1 is relatively uncommon and few cases have been reported in detail. METHODS Here, we describe the molecular features of two cases of primary prostate cancer with MLH1 loss detected by immunohistochemistry, and in one case, confirmed via transcriptomic profiling. RESULTS Both cases were microsatellite stable on standard polymerase chain reaction (PCR)-based microsatellite instability (MSI) testing, but showed evidence of MSI on a newer PCR-based long mononucleotide repeat (LMR) assay and by next-generation sequencing. Germline testing was negative for Lynch syndrome-associated mutations in both cases. Targeted or whole-exome tumor sequencing using multiple commercial/academic platforms (Foundation, Tempus, JHU, and UW-OncoPlex) showed modestly elevated, though variable, tumor mutation burden estimates (2.3-10 mutations/Mb) consistent with MMRd, but without identifiable pathogenic single-nucleotide or indel mutations in MLH1. Copy-number analysis confirmed biallelic MLH1 loss in one case and monoallelic MLH1 loss in the second case, without evidence of MLH1 promoter hypermethylation in either. The second patient was treated with single-agent pembrolizumab and demonstrated a short-lived prostate-specific antigen response. CONCLUSION These cases highlight the challenges in identifying MLH1-deficient prostate cancers using standard MSI testing and commercial sequencing panels, and support the utility of immunohistochemical assays and LMR- or sequencing-based MSI testing for detection of MMRd prostate cancers.
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Affiliation(s)
| | - Laura A. Sena
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD
| | - Emmanuel S. Antonarakis
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD
- University of Minnesota Masonic Cancer Center, Minneapolis, MN
| | - Colin C. Pritchard
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA
| | - James R. Eshleman
- Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD
| | - Eric Q. Konnick
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA
| | - Stephen J. Salipante
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA
| | - Eugene Shenderov
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD
- The Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins School of Medicine, Baltimore, MD
| | - Tamara L. Lotan
- Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Oncology, Johns Hopkins School of Medicine, Baltimore, MD
- Department of Urology, Johns Hopkins School of Medicine, Baltimore, MD
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Sertier AS, Ferrari A, Pommier RM, Treilleux I, Boyault S, Devouassoux-Shisheboran M, Kielbassa J, Thomas E, Tonon L, Le Texier V, Charreton A, Morel AP, Floquet A, Joly F, Berton-Rigaud D, Ferron G, Arnould L, Croce S, Bataillon G, Saintigny P, Mery-Lamarche E, Sagan C, Senaratne AP, Gut IG, Calvo F, Viari A, Ouzounova M, Ray-Coquard I, Puisieux A. Dissecting the Origin of Heterogeneity in Uterine and Ovarian Carcinosarcomas. CANCER RESEARCH COMMUNICATIONS 2023; 3:830-841. [PMID: 37377900 PMCID: PMC10171113 DOI: 10.1158/2767-9764.crc-22-0520] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 02/28/2023] [Accepted: 04/18/2023] [Indexed: 06/29/2023]
Abstract
Gynecologic carcinosarcomas (CS) are biphasic neoplasms composed of carcinomatous (C) and sarcomatous (S) malignant components. Because of their rarity and histologic complexity, genetic and functional studies on CS are scarce and the mechanisms of initiation and development remain largely unknown. Whole-genome analysis of the C and S components reveals shared genomic alterations, thus emphasizing the clonal evolution of CS. Reconstructions of the evolutionary history of each tumor further reveal that C and S samples are composed of both ancestral cell populations and component-specific subclones, supporting a common origin followed by distinct evolutionary trajectories. However, while we do not find any recurrent genomic features associated with phenotypic divergence, transcriptomic and methylome analyses identify a common mechanism across the cohort, the epithelial-to-mesenchymal transition (EMT), suggesting a role for nongenetic factors in inflicting changes to cellular fate. Altogether, these data accredit the hypothesis that CS tumors are driven by both clonal evolution and transcriptomic reprogramming, essential for susceptibility to transdifferentiation upon encountering environmental cues, thus linking CS heterogeneity to genetic, transcriptomic, and epigenetic influences. Significance We have provided a detailed characterization of the genomic landscape of CS and identified EMT as a common mechanism associated with phenotypic divergence, linking CS heterogeneity to genetic, transcriptomic, and epigenetic influences.
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Affiliation(s)
- Anne-Sophie Sertier
- Synergie Lyon Cancer, Plateforme de bioinformatique Gilles Thomas, Centre Léon Bérard, Lyon, France
| | - Anthony Ferrari
- Synergie Lyon Cancer, Plateforme de bioinformatique Gilles Thomas, Centre Léon Bérard, Lyon, France
| | - Roxane M. Pommier
- Synergie Lyon Cancer, Plateforme de bioinformatique Gilles Thomas, Centre Léon Bérard, Lyon, France
- Centre Léon Bérard, Lyon, France
| | | | - Sandrine Boyault
- Synergie Lyon Cancer, Plateforme de bioinformatique Gilles Thomas, Centre Léon Bérard, Lyon, France
- Centre Léon Bérard, Lyon, France
| | - Mojgan Devouassoux-Shisheboran
- Department of Pathology, Hospices Civils de Lyon, Lyon, France
- Université de Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286 Centre Léon Bérard, Cancer Research Center of Lyon, Lyon, France
| | - Janice Kielbassa
- Synergie Lyon Cancer, Plateforme de bioinformatique Gilles Thomas, Centre Léon Bérard, Lyon, France
- Centre Léon Bérard, Lyon, France
| | - Emilie Thomas
- Synergie Lyon Cancer, Plateforme de bioinformatique Gilles Thomas, Centre Léon Bérard, Lyon, France
| | - Laurie Tonon
- Synergie Lyon Cancer, Plateforme de bioinformatique Gilles Thomas, Centre Léon Bérard, Lyon, France
| | - Vincent Le Texier
- Synergie Lyon Cancer, Plateforme de bioinformatique Gilles Thomas, Centre Léon Bérard, Lyon, France
| | | | | | - Anne Floquet
- Institut Bergonié Comprehensive Cancer Centre, Bordeaux, France
| | | | | | - Gwenaël Ferron
- Institut Claudius-Regaud, IUCT Oncopole, Toulouse, France
| | - Laurent Arnould
- Department of Pathology, Centre Georges François Leclerc, Comprehensive Cancer Centre, Dijon, France
| | - Sabrina Croce
- Department of Biopathology, Institut Bergonié Comprehensive Cancer Centre, Bordeaux, France
| | | | - Pierre Saintigny
- Centre Léon Bérard, Lyon, France
- Department of Translational Medicine, Centre Léon Bérard, Lyon, France
- Department of Medical Oncology, Centre Léon Bérard, Lyon, France
| | | | - Christine Sagan
- Institut de Cancérologie de l'Ouest René-Gauducheau, Saint-Herblain, France
| | | | - Ivo G. Gut
- CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), Carrer Baldiri i Reixac 4, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Fabien Calvo
- Centre de Recherche des Cordeliers, Université de Paris-Cité, Paris France
| | - Alain Viari
- Synergie Lyon Cancer, Plateforme de bioinformatique Gilles Thomas, Centre Léon Bérard, Lyon, France
| | - Maria Ouzounova
- Université de Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286 Centre Léon Bérard, Cancer Research Center of Lyon, Lyon, France
| | | | - Alain Puisieux
- Centre Léon Bérard, Lyon, France
- Institut Curie, PSL Research University, Paris, France
- Chemical Biology of Cancer Laboratory, CNRS UMR 3666, INSERM U1143, Paris, France
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Rasmussen M, Sowter P, Gallon R, Durhuus JA, Hayes C, Andersen O, Nilbert M, Schejbel L, Høgdall E, Santibanez-Koref M, Jackson MS, Burn J, Therkildsen C. Mismatch repair deficiency testing in Lynch syndrome-associated urothelial tumors. Front Oncol 2023; 13:1147591. [PMID: 37143941 PMCID: PMC10151563 DOI: 10.3389/fonc.2023.1147591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 03/23/2023] [Indexed: 05/06/2023] Open
Abstract
Introduction Lynch syndrome-associated cancer develops due to germline pathogenic variants in one of the mismatch repair (MMR) genes, MLH1, MSH2, MSH6 or PMS2. Somatic second hits in tumors cause MMR deficiency, testing for which is used to screen for Lynch syndrome in colorectal cancer and to guide selection for immunotherapy. Both MMR protein immunohistochemistry and microsatellite instability (MSI) analysis can be used. However, concordance between methods can vary for different tumor types. Therefore, we aimed to compare methods of MMR deficiency testing in Lynch syndrome-associated urothelial cancers. Methods Ninety-seven urothelial (61 upper tract and 28 bladder) tumors diagnosed from 1980 to 2017 in carriers of Lynch syndrome-associated pathogenic MMR variants and their first-degree relatives (FDR) were analyzed by MMR protein immunohistochemistry, the MSI Analysis System v1.2 (Promega), and an amplicon sequencing-based MSI assay. Two sets of MSI markers were used in sequencing-based MSI analysis: a panel of 24 and 54 markers developed for colorectal cancer and blood MSI analysis, respectively. Results Among the 97 urothelial tumors, 86 (88.7%) showed immunohistochemical MMR loss and 68 were successfully analyzed by the Promega MSI assay, of which 48 (70.6%) were MSI-high and 20 (29.4%) were MSI-low/microsatellite stable. Seventy-two samples had sufficient DNA for the sequencing-based MSI assay, of which 55 (76.4%) and 61 (84.7%) scored as MSI-high using the 24-marker and 54-marker panels, respectively. The concordance between the MSI assays and immunohistochemistry was 70.6% (p = 0.003), 87.5% (p = 0.039), and 90.3% (p = 1.00) for the Promega assay, the 24-marker assay, and the 54-marker assay, respectively. Of the 11 tumors with retained MMR protein expression, four were MSI-low/MSI-high or MSI-high by the Promega assay or one of the sequencing-based assays. Conclusion Our results show that Lynch syndrome-associated urothelial cancers frequently had loss of MMR protein expression. The Promega MSI assay was significantly less sensitive, but the 54-marker sequencing-based MSI analysis showed no significant difference compared to immunohistochemistry. Data from this study alongside previous studies, suggest that universal MMR deficiency testing of newly diagnosed urothelial cancers, using immunohistochemistry and/or sequencing-based MSI analysis of sensitive markers, offer a potentially useful approach to identification of Lynch syndrome cases.
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Affiliation(s)
- Maria Rasmussen
- Department of Clinical Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Peter Sowter
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Richard Gallon
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Jon Ambæk Durhuus
- Department of Clinical Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
- Center for Healthy Aging, Department of Cellular and Molecular Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Christine Hayes
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Ove Andersen
- Department of Clinical Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Mef Nilbert
- Institute of Clinical Sciences, Division of Oncology and Pathology, Lund University, Lund, Sweden
| | - Lone Schejbel
- Molecular Unit, Department of Pathology, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark
| | - Estrid Høgdall
- Molecular Unit, Department of Pathology, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark
| | - Mauro Santibanez-Koref
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Michael S Jackson
- Biosciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - John Burn
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Christina Therkildsen
- The Danish HNPCC Register, Gastro Unit, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
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Shimozaki K, Nakayama I, Hirota T, Yamaguchi K. Current Strategy to Treat Immunogenic Gastrointestinal Cancers: Perspectives for a New Era. Cells 2023; 12:1049. [PMID: 37048122 PMCID: PMC10093684 DOI: 10.3390/cells12071049] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/15/2023] [Accepted: 03/29/2023] [Indexed: 04/14/2023] Open
Abstract
Since pembrolizumab, an anti-programmed death-1 (PD-1) antibody, showed a dramatic response to immunogenic cancers with microsatellite instability-high (MSI-H) and/or deficient mismatch repair (dMMR) in the pilot clinical trial KEYNOTE-016, subsequent studies have confirmed durable responses of anti-PD-1 inhibitors for MSI-H/dMMR solid tumors. As immunotherapy is described as a "game changer," the therapeutic landscape for MSI-H/dMMR solid tumors including gastrointestinal cancers has changed considerably in the last decade. An MSI/MMR status has been established as the predictive biomarker for immune checkpoint blockades, playing an indispensable role in the clinical practice of patients with MSI-H/dMMR tumors. Immunotherapy is also now investigated for locally advanced MSI-H/dMMR gastrointestinal cancers. Despite this great success, a few populations with MSI-H/dMMR gastrointestinal cancers do not respond to immunotherapy, possibly due to the existence of intrinsic or acquired resistance mechanisms. Clarifying the underlying mechanisms of resistance remains a future task, whereas attempts to overcome resistance and improve the efficacy of immunotherapy are currently ongoing. Herein, we review recent clinical trials with special attention to MSI-H/dMMR gastrointestinal cancers together with basic/translational findings, which provide their rationale, and discuss perspectives for the further therapeutic development of treatment in this field.
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Affiliation(s)
- Keitaro Shimozaki
- Department of Gastrointestinal Oncology, Cancer Institute Hospital of the Japanese Foundation for Cancer Research, Tokyo 135-0063, Japan
- Department of Gastroenterology and Hepatology, Division of Internal Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan
| | - Izuma Nakayama
- Department of Gastrointestinal Oncology, Cancer Institute Hospital of the Japanese Foundation for Cancer Research, Tokyo 135-0063, Japan
| | - Toru Hirota
- Department of Experimental Pathology, Cancer Institute of the Japanese Foundation for Cancer Research, Tokyo 135-8550, Japan
| | - Kensei Yamaguchi
- Department of Gastrointestinal Oncology, Cancer Institute Hospital of the Japanese Foundation for Cancer Research, Tokyo 135-0063, Japan
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47
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Santamarina-García M, Brea-Iglesias J, Bramsen JB, Fuentes-Losada M, Caneiro-Gómez FJ, Vázquez-Bueno JÁ, Lázare-Iglesias H, Fernández-Díaz N, Sánchez-Rivadulla L, Betancor YZ, Ferreiro-Pantín M, Conesa-Zamora P, Antúnez-López JR, Kawazu M, Esteller M, Andersen CL, Tubio JMC, López-López R, Ruiz-Bañobre J. MSIMEP: Predicting microsatellite instability from microarray DNA methylation tumor profiles. iScience 2023; 26:106127. [PMID: 36879816 PMCID: PMC9984554 DOI: 10.1016/j.isci.2023.106127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 12/15/2022] [Accepted: 01/31/2023] [Indexed: 02/05/2023] Open
Abstract
Deficiency in DNA MMR activity results in tumors with a hypermutator phenotype, termed microsatellite instability (MSI). Beyond its utility in Lynch syndrome screening algorithms, today MSI has gained importance as predictive biomarker for various anti-PD-1 therapies across many different tumor types. Over the past years, many computational methods have emerged to infer MSI using either DNA- or RNA-based approaches. Considering this together with the fact that MSI-high tumors frequently exhibit a hypermethylated phenotype, herein we developed and validated MSIMEP, a computational tool for predicting MSI status from microarray DNA methylation tumor profiles of colorectal cancer samples. We demonstrated that MSIMEP optimized and reduced models have high performance in predicting MSI in different colorectal cancer cohorts. Moreover, we tested its consistency in other tumor types with high prevalence of MSI such as gastric and endometrial cancers. Finally, we demonstrated better performance of both MSIMEP models vis-à-vis a MLH1 promoter methylation-based one in colorectal cancer.
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Affiliation(s)
- Martín Santamarina-García
- Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain
| | - Jenifer Brea-Iglesias
- Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.,Translational Oncology Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, Álvaro Cunqueiro Hospital, 36213 Vigo, Spain
| | | | - Mar Fuentes-Losada
- Department of Medical Oncology, University Clinical Hospital of Santiago de Compostela (SERGAS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.,Translational Medical Oncology Group (ONCOMET), Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain
| | - Francisco Javier Caneiro-Gómez
- Department of Pathology, University Clinical Hospital of Santiago de Compostela, University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain
| | | | - Héctor Lázare-Iglesias
- Department of Pathology, University Clinical Hospital of Santiago de Compostela, University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain
| | - Natalia Fernández-Díaz
- Department of Medical Oncology, University Clinical Hospital of Santiago de Compostela (SERGAS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.,Translational Medical Oncology Group (ONCOMET), Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain
| | - Laura Sánchez-Rivadulla
- Department of Gynaecology and Obstetrics, Complejo Hospitalario Universitario de Ferrol, 15405 Ferrol, Spain
| | - Yoel Z Betancor
- Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.,Translational Medical Oncology Group (ONCOMET), Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain
| | - Miriam Ferreiro-Pantín
- Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.,Translational Medical Oncology Group (ONCOMET), Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain
| | - Pablo Conesa-Zamora
- Department of Clinical Analysis, Santa Lucía University Hospital, 30202 Cartagena, Spain
| | - José Ramón Antúnez-López
- Department of Pathology, University Clinical Hospital of Santiago de Compostela, University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain
| | - Masahito Kawazu
- Chiba Cancer Center, Research Institute, 260-0801 Chiba, Japan.,Division of Cellular Signaling, National Cancer Center Research Institute, 104-0045 Tokyo, Japan
| | - Manel Esteller
- Josep Carreras Leukaemia Research Institute (IJC), 08916 Badalona, Barcelona, Spain.,Institucio Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain.,Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona (UB), 08907 Barcelona, Spain.,Centro de Investigación Biomédica en Red Cáncer (CIBERONC), 28029 Madrid, Spain
| | | | - Jose M C Tubio
- Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain
| | - Rafael López-López
- Department of Medical Oncology, University Clinical Hospital of Santiago de Compostela (SERGAS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.,Translational Medical Oncology Group (ONCOMET), Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.,Centro de Investigación Biomédica en Red Cáncer (CIBERONC), 28029 Madrid, Spain
| | - Juan Ruiz-Bañobre
- Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.,Department of Medical Oncology, University Clinical Hospital of Santiago de Compostela (SERGAS), University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.,Translational Medical Oncology Group (ONCOMET), Health Research Institute of Santiago de Compostela (IDIS), University Clinical Hospital of Santiago de Compostela, University of Santiago de Compostela (USC), 15706 Santiago de Compostela, Spain.,Centro de Investigación Biomédica en Red Cáncer (CIBERONC), 28029 Madrid, Spain
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48
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Xing J, Chen J, You T, Sun Z, Lu T, Cheng Y, Wu H, Bai C. Expression of p53 and Rb reveal subtypes of gastric neuroendocrine carcinoma with distinct prognosis. J Neuroendocrinol 2023; 35:e13257. [PMID: 36964649 DOI: 10.1111/jne.13257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 02/07/2023] [Accepted: 03/09/2023] [Indexed: 03/17/2023]
Abstract
Gastric neuroendocrine carcinoma (NEC) is a rare tumor with a poor prognosis. Due to its rarity and disparity in prevalence across populations, there is limited data on gastric NEC. TP53 and RB1 genetic alterations or expression were reported for predictive value in neuroendocrine neoplasm and classification in pulmonary large cell NEC. This study investigated the genetic alteration and protein expression of TP53 and RB1 in gastric NEC. Thirty-nine patients were categorized as type A and B subtypes by p53 and Rb expression. Patients with concurrent abnormal p53 and Rb expression were defined as the type A group, and the remainder were defined as the type B group. Significant differences in TNM stages, tumor size, and lymph node metastasis were observed between the two subtypes. Type A characteristic is an independent predictor for worse overall survival (HR: 3.27; 95% CI: 1.12-9.58; p = .022). We further evaluated and compared immunotherapy-related markers, including PD-L1 expression, CD8 T cell infiltration, tumor mutation burden, and microsatellite instability in these two subtypes, whereas no significant differences were detected.
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Affiliation(s)
- Jiazhang Xing
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Jingci Chen
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Tingting You
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Zhao Sun
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Tao Lu
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Yuejuan Cheng
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Huanwen Wu
- Department of Pathology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Chunmei Bai
- Department of Medical Oncology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
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49
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MSINGB: A Novel Computational Method Based on NGBoost for Identifying Microsatellite Instability Status from Tumor Mutation Annotation Data. Interdiscip Sci 2023; 15:100-110. [PMID: 36350503 DOI: 10.1007/s12539-022-00544-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 10/19/2022] [Accepted: 10/22/2022] [Indexed: 11/11/2022]
Abstract
Microsatellite instability (MSI), a vital mutator phenotype caused by DNA mismatch repair deficiency, is frequently observed in several tumors. MSI is recognized as a critical molecular biomarker for diagnosis, prognosis, and therapeutic selection in several cancers. Identifying MSI status for current gold standard methods based on experimental analysis is laborious, time-consuming, and costly. Although several computational methods based on machine learning have been proposed to identify MSI status, we need to further understand which machine learning model would favor identification for MSI and which feature subset is strongly related to MSI. On this basis, more effective machine learning-based methods can be developed to improve the performance of MSI status identification. In this work, we present MSINGB, an NGBoost-based method for identifying MSI status from tumor somatic mutation annotation data. MSINGB first evaluates the prediction performance of 11 popular machine learning algorithms and 9 deep learning models to identify MSI. Among 20 models, NGBoost, a novel natural gradient boosting method, achieves the overall best performance. MSINGB then introduces two feature selection strategies to find the compact feature subset, which is strongly related to MSI, and employs the SHAP approach to interpreting how selected features impact the model prediction. MSINGB achieves a better prediction performance on both the tenfold cross-validation test and independent test compared with state-of-the-art methods.
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50
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Swaerts K, Dedeurwaerdere F, De Smet D, De Jaeger P, Martens GA. DeltaMSI: artificial intelligence-based modeling of microsatellite instability scoring on next-generation sequencing data. BMC Bioinformatics 2023; 24:73. [PMID: 36859168 PMCID: PMC9976396 DOI: 10.1186/s12859-023-05186-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 02/14/2023] [Indexed: 03/03/2023] Open
Abstract
BACKGROUND DNA mismatch repair deficiency (dMMR) testing is crucial for detection of microsatellite unstable (MSI) tumors. MSI is detected by aberrant indel length distributions of microsatellite markers, either by visual inspection of PCR-fragment length profiles or by automated bioinformatic scoring on next-generation sequencing (NGS) data. The former is time-consuming and low-throughput while the latter typically relies on simplified binary scoring of a single parameter of the indel distribution. The purpose of this study was to use machine learning to process the full complexity of indel distributions and integrate it into a robust script for screening of dMMR on small gene panel-based NGS data of clinical tumor samples without paired normal tissue. METHODS Scikit-learn was used to train 7 models on normalized read depth data of 36 microsatellite loci in a cohort of 133 MMR proficient (pMMR) and 46 dMMR tumor samples, taking loss of MLH1/MSH2/PMS2/MSH6 protein expression as reference method. After selection of the optimal model and microsatellite panel the two top-performing models per locus (logistic regression and support vector machine) were integrated into a novel script (DeltaMSI) for combined prediction of MSI status on 28 marker loci at sample level. Diagnostic performance of DeltaMSI was compared to that of mSINGS, a widely used script for MSI detection on unpaired tumor samples. The robustness of DeltaMSI was evaluated on 1072 unselected, consecutive solid tumor samples in a real-world setting sequenced using capture chemistry, and 116 solid tumor samples sequenced by amplicon chemistry. Likelihood ratios were used to select result intervals with clinical validity. RESULTS DeltaMSI achieved higher robustness at equal diagnostic power (AUC = 0.950; 95% CI 0.910-0.975) as compared to mSINGS (AUC = 0.876; 95% CI 0.823-0.918). Its sensitivity of 90% at 100% specificity indicated its clinical potential for high-throughput MSI screening in all tumor types. Clinical Trial Number/IRB B1172020000040, Ethical Committee, AZ Delta General Hospital.
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Affiliation(s)
- Koen Swaerts
- grid.478056.80000 0004 0439 8570Department of Laboratory Medicine, AZ Delta General Hospital, Deltalaan 1, 8800 Roeselare, Belgium ,grid.478056.80000 0004 0439 8570RADar Innovation Center, AZ Delta General Hospital, Roeselare, Belgium
| | - Franceska Dedeurwaerdere
- grid.478056.80000 0004 0439 8570Department of Pathology, AZ Delta General Hospital, Roeselare, Belgium
| | - Dieter De Smet
- grid.478056.80000 0004 0439 8570Department of Laboratory Medicine, AZ Delta General Hospital, Deltalaan 1, 8800 Roeselare, Belgium ,grid.478056.80000 0004 0439 8570RADar Innovation Center, AZ Delta General Hospital, Roeselare, Belgium
| | - Peter De Jaeger
- grid.478056.80000 0004 0439 8570RADar Innovation Center, AZ Delta General Hospital, Roeselare, Belgium
| | - Geert A. Martens
- grid.478056.80000 0004 0439 8570Department of Laboratory Medicine, AZ Delta General Hospital, Deltalaan 1, 8800 Roeselare, Belgium ,grid.478056.80000 0004 0439 8570RADar Innovation Center, AZ Delta General Hospital, Roeselare, Belgium ,grid.5342.00000 0001 2069 7798Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
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