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Ball M, Ourailidis I, Kluck K, Menzel M, Kirchner M, Allgäuer M, Tay TKY, Schnecko F, Volckmar AL, Goldschmid H, Neuman O, Fröhling S, Schirmacher P, Budczies J, Stenzinger A, Kazdal D. Leveraging Off-Target Reads in Panel Sequencing for Homologous Recombination Repair Deficiency Screening in Tumor. J Mol Diagn 2024; 26:479-486. [PMID: 38522840 DOI: 10.1016/j.jmoldx.2024.02.008] [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: 09/22/2023] [Revised: 01/24/2024] [Accepted: 02/14/2024] [Indexed: 03/26/2024] Open
Abstract
Targeted tumor only sequencing has become a standard practice in cancer diagnostics. This study aims to develop an approach for robust copy number variant calling in tumor samples using only off-target region (OTR) reads. We also established a clinical use case for homologous recombination deficiency (HRD) score estimation (HRDest) using the sum of telomeric-allelic imbalance and large-scale state transition scores without the need for loss of heterozygosity information. A strong correlation was found between HRD score and the sum of telomeric-allelic imbalance + large-scale state transition in The Cancer Genome Atlas cohort (ρ = 0.99, P < 2.2 × 10-16) and in a clinical in-house cohort of 34 tumors (ρ = 0.9, P = 5.1 × 10-13) comparing whole-exome sequencing and targeted sequencing data. HRDest scores from 1086 clinical cases were compared with The Cancer Genome Atlas data set. There were no significant differences in HRD score distribution within the analyzed tumor types. As a control, commercially available HRD standards were also sequenced, and the HRDest scores obtained from the OTR reads were well within the HRD reference range provided by the manufacturer. In conclusion, OTR reads of tumor-only panel sequencing can be used to determine genome-wide copy number variant profiles and to approximate HRD scores.
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Affiliation(s)
- Markus Ball
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Klaus Kluck
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Michael Menzel
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Martina Kirchner
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Michael Allgäuer
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Timothy Kwang Yong Tay
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany; Department of Anatomical Pathology, Singapore General Hospital, Singapore; Department of Molecular Pathology, Singapore General Hospital, Singapore
| | - Fabian Schnecko
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Anna-Lena Volckmar
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Hannah Goldschmid
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Olaf Neuman
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Stefan Fröhling
- Department of Translational Medical Oncology, National Center for Tumor Diseases, Heidelberg, Germany; German Cancer Consortium, Heidelberg, Germany
| | - Peter Schirmacher
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany; Center for Personalized Medicine Heidelberg, Heidelberg, Germany
| | - Jan Budczies
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany; German Cancer Consortium, Heidelberg, Germany; Center for Personalized Medicine Heidelberg, Heidelberg, Germany; Translational Lung Research Center Heidelberg, German Center for Lung Research, Heidelberg, Germany
| | - Albrecht Stenzinger
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany; German Cancer Consortium, Heidelberg, Germany; Center for Personalized Medicine Heidelberg, Heidelberg, Germany; Translational Lung Research Center Heidelberg, German Center for Lung Research, Heidelberg, Germany.
| | - Daniel Kazdal
- Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany; German Cancer Consortium, Heidelberg, Germany; Translational Lung Research Center Heidelberg, German Center for Lung Research, Heidelberg, Germany.
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2
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Houlahan KE, Khan A, Greenwald NF, Vivas CS, West RB, Angelo M, Curtis C. Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity. Science 2024; 384:eadh8697. [PMID: 38815010 DOI: 10.1126/science.adh8697] [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: 03/19/2023] [Accepted: 04/05/2024] [Indexed: 06/01/2024]
Abstract
Tumors with the same diagnosis can have different molecular profiles and response to treatment. It remains unclear when and why these differences arise. Somatic genomic aberrations occur within the context of a highly variable germline genome. Interrogating 5870 breast cancer lesions, we demonstrated that germline-derived epitopes in recurrently amplified genes influence somatic evolution by mediating immunoediting. Individuals with a high germline-epitope burden in human epidermal growth factor receptor 2 (HER2/ERBB2) are less likely to develop HER2-positive breast cancer compared with other subtypes. The same holds true for recurrent amplicons defining three aggressive estrogen receptor (ER)-positive subgroups. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an "immune cold" phenotype. These data show that the germline genome plays a role in dictating somatic evolution.
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Affiliation(s)
- Kathleen E Houlahan
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Aziz Khan
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Noah F Greenwald
- Cancer Biology Program, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | | | - Robert B West
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Michael Angelo
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Christina Curtis
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Medicine, Division of Oncology, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
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3
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Olivucci G, Iovino E, Innella G, Turchetti D, Pippucci T, Magini P. Long read sequencing on its way to the routine diagnostics of genetic diseases. Front Genet 2024; 15:1374860. [PMID: 38510277 PMCID: PMC10951082 DOI: 10.3389/fgene.2024.1374860] [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: 01/22/2024] [Accepted: 02/26/2024] [Indexed: 03/22/2024] Open
Abstract
The clinical application of technological progress in the identification of DNA alterations has always led to improvements of diagnostic yields in genetic medicine. At chromosome side, from cytogenetic techniques evaluating number and gross structural defects to genomic microarrays detecting cryptic copy number variants, and at molecular level, from Sanger method studying the nucleotide sequence of single genes to the high-throughput next-generation sequencing (NGS) technologies, resolution and sensitivity progressively increased expanding considerably the range of detectable DNA anomalies and alongside of Mendelian disorders with known genetic causes. However, particular genomic regions (i.e., repetitive and GC-rich sequences) are inefficiently analyzed by standard genetic tests, still relying on laborious, time-consuming and low-sensitive approaches (i.e., southern-blot for repeat expansion or long-PCR for genes with highly homologous pseudogenes), accounting for at least part of the patients with undiagnosed genetic disorders. Third generation sequencing, generating long reads with improved mappability, is more suitable for the detection of structural alterations and defects in hardly accessible genomic regions. Although recently implemented and not yet clinically available, long read sequencing (LRS) technologies have already shown their potential in genetic medicine research that might greatly impact on diagnostic yield and reporting times, through their translation to clinical settings. The main investigated LRS application concerns the identification of structural variants and repeat expansions, probably because techniques for their detection have not evolved as rapidly as those dedicated to single nucleotide variants (SNV) identification: gold standard analyses are karyotyping and microarrays for balanced and unbalanced chromosome rearrangements, respectively, and southern blot and repeat-primed PCR for the amplification and sizing of expanded alleles, impaired by limited resolution and sensitivity that have not been significantly improved by the advent of NGS. Nevertheless, more recently, with the increased accuracy provided by the latest product releases, LRS has been tested also for SNV detection, especially in genes with highly homologous pseudogenes and for haplotype reconstruction to assess the parental origin of alleles with de novo pathogenic variants. We provide a review of relevant recent scientific papers exploring LRS potential in the diagnosis of genetic diseases and its potential future applications in routine genetic testing.
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Affiliation(s)
- Giulia Olivucci
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
- Department of Surgical and Oncological Sciences, University of Palermo, Palermo, Italy
| | - Emanuela Iovino
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Giovanni Innella
- Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy
- Medical Genetics Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Daniela Turchetti
- Department of Medical and Surgical Sciences (DIMEC), University of Bologna, Bologna, Italy
- Medical Genetics Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Tommaso Pippucci
- IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Pamela Magini
- Medical Genetics Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
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4
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Nakamura W, Hirata M, Oda S, Chiba K, Okada A, Mateos RN, Sugawa M, Iida N, Ushiama M, Tanabe N, Sakamoto H, Sekine S, Hirasawa A, Kawai Y, Tokunaga K, Tsujimoto SI, Shiba N, Ito S, Yoshida T, Shiraishi Y. Assessing the efficacy of target adaptive sampling long-read sequencing through hereditary cancer patient genomes. NPJ Genom Med 2024; 9:11. [PMID: 38368425 PMCID: PMC10874402 DOI: 10.1038/s41525-024-00394-z] [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: 05/28/2023] [Accepted: 01/15/2024] [Indexed: 02/19/2024] Open
Abstract
Innovations in sequencing technology have led to the discovery of novel mutations that cause inherited diseases. However, many patients with suspected genetic diseases remain undiagnosed. Long-read sequencing technologies are expected to significantly improve the diagnostic rate by overcoming the limitations of short-read sequencing. In addition, Oxford Nanopore Technologies (ONT) offers adaptive sampling and computationally driven target enrichment technology. This enables more affordable intensive analysis of target gene regions compared to standard non-selective long-read sequencing. In this study, we developed an efficient computational workflow for target adaptive sampling long-read sequencing (TAS-LRS) and evaluated it through application to 33 genomes collected from suspected hereditary cancer patients. Our workflow can identify single nucleotide variants with nearly the same accuracy as the short-read platform and elucidate complex forms of structural variations. We also newly identified several SINE-R/VNTR/Alu (SVA) elements affecting the APC gene in two patients with familial adenomatous polyposis, as well as their sites of origin. In addition, we demonstrated that off-target reads from adaptive sampling, which is typically discarded, can be effectively used to accurately genotype common single-nucleotide polymorphisms (SNPs) across the entire genome, enabling the calculation of a polygenic risk score. Furthermore, we identified allele-specific MLH1 promoter hypermethylation in a Lynch syndrome patient. In summary, our workflow with TAS-LRS can simultaneously capture monogenic risk variants including complex structural variations, polygenic background as well as epigenetic alterations, and will be an efficient platform for genetic disease research and diagnosis.
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Affiliation(s)
- Wataru Nakamura
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan
- Department of Pediatrics, Yokohama City University Hospital, Kanagawa, Japan
| | - Makoto Hirata
- Division of Genetic Medicine and Services, National Cancer Center Hospital, Tokyo, Japan
- Department of Molecular Pathology, National Cancer Center Research Institute, Tokyo, Japan
| | - Satoyo Oda
- Division of Genetic Medicine and Services, National Cancer Center Hospital, Tokyo, Japan
- Division of Laboratory Medicine, National Cancer Center Hospital, Tokyo, Japan
| | - Kenichi Chiba
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Ai Okada
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Raúl Nicolás Mateos
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Masahiro Sugawa
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Naoko Iida
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Mineko Ushiama
- Division of Genetic Medicine and Services, National Cancer Center Hospital, Tokyo, Japan
- Department of Clinical Genetics, National Cancer Center Research Institute, Tokyo, Japan
| | - Noriko Tanabe
- Division of Genetic Medicine and Services, National Cancer Center Hospital, Tokyo, Japan
| | - Hiromi Sakamoto
- Division of Genetic Medicine and Services, National Cancer Center Hospital, Tokyo, Japan
- Department of Clinical Genetics, National Cancer Center Research Institute, Tokyo, Japan
| | - Shigeki Sekine
- Division of Molecular Pathology, National Cancer Center Research Institute, Tokyo, Japan
| | - Akira Hirasawa
- Department of Clinical Genetics and Genomic Medicine, Okayama University Hospital, Okayama, Japan
| | - Yosuke Kawai
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Katsushi Tokunaga
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
- Central Biobank, National Center Biobank Network, Tokyo, Japan
| | - Shin-Ichi Tsujimoto
- Department of Pediatrics, Yokohama City University Hospital, Kanagawa, Japan
| | - Norio Shiba
- Department of Pediatrics, Yokohama City University Hospital, Kanagawa, Japan
| | - Shuichi Ito
- Department of Pediatrics, Yokohama City University Hospital, Kanagawa, Japan
| | - Teruhiko Yoshida
- Division of Genetic Medicine and Services, National Cancer Center Hospital, Tokyo, Japan
- Department of Clinical Genetics, National Cancer Center Research Institute, Tokyo, Japan
| | - Yuichi Shiraishi
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan.
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5
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Taraszka K, Groha S, King D, Tell R, White K, Ziv E, Zaitlen N, Gusev A. A comprehensive analysis of clinical and polygenic germline influences on somatic mutational burden. Am J Hum Genet 2024; 111:242-258. [PMID: 38211585 PMCID: PMC10870141 DOI: 10.1016/j.ajhg.2023.12.010] [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: 07/18/2023] [Revised: 12/04/2023] [Accepted: 12/06/2023] [Indexed: 01/13/2024] Open
Abstract
Tumor mutational burden (TMB), the total number of somatic mutations in the tumor, and copy number burden (CNB), the corresponding measure of aneuploidy, are established fundamental somatic features and emerging biomarkers for immunotherapy. However, the genetic and non-genetic influences on TMB/CNB and, critically, the manner by which they influence patient outcomes remain poorly understood. Here, we present a large germline-somatic study of TMB/CNB with >23,000 individuals across 17 cancer types, of which 12,000 also have extensive clinical, treatment, and overall survival (OS) measurements available. We report dozens of clinical associations with TMB/CNB, observing older age and male sex to have a strong effect on TMB and weaker impact on CNB. We additionally identified significant germline influences on TMB/CNB, including fine-scale European ancestry and germline polygenic risk scores (PRSs) for smoking, tanning, white blood cell counts, and educational attainment. We quantify the causal effect of exposures on somatic mutational processes using Mendelian randomization. Many of the identified features associated with TMB/CNB were additionally associated with OS for individuals treated at a single tertiary cancer center. For individuals receiving immunotherapy, we observed a complex relationship between PRSs for educational attainment, self-reported college attainment, TMB, and survival, suggesting that the influence of this biomarker may be substantially modified by socioeconomic status. While the accumulation of somatic alterations is a stochastic process, our work demonstrates that it can be shaped by host characteristics including germline genetics.
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Affiliation(s)
- Kodi Taraszka
- Department of Computer Science, University of California, Los Angeles, CA 90095, USA; Department of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA 02215, USA.
| | - Stefan Groha
- Department of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA 02215, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA
| | - David King
- Tempus Labs, Inc, Chicago, IL 60654, USA
| | | | | | - Elad Ziv
- Department of Medicine, University of California San Francisco Helen Diller Family Comprehensive Cancer Center, San Francisco, CA 94158, USA
| | - Noah Zaitlen
- Department of Neurology, University of California, Los Angeles, CA 90095, USA
| | - Alexander Gusev
- Department of Medical Oncology, Dana-Farber Cancer Institute & Harvard Medical School, Boston, MA 02215, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA.
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6
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Sun S, Aboelenain M, Ariad D, Haywood ME, Wageman CR, Duke M, Bag A, Viotti M, Katz-Jaffe M, McCoy RC, Schindler K, Xing J. Identifying risk variants for embryo aneuploidy using ultra-low coverage whole-genome sequencing from preimplantation genetic testing. Am J Hum Genet 2023; 110:2092-2102. [PMID: 38029743 PMCID: PMC10716496 DOI: 10.1016/j.ajhg.2023.11.002] [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: 07/23/2023] [Revised: 11/08/2023] [Accepted: 11/08/2023] [Indexed: 12/01/2023] Open
Abstract
Aneuploidy frequently arises during human meiosis and is the primary cause of early miscarriage and in vitro fertilization (IVF) failure. Individuals undergoing IVF exhibit significant variability in aneuploidy rates, although the exact genetic causes of the variability in aneuploid egg production remain unclear. Preimplantation genetic testing for aneuploidy (PGT-A) using next-generation sequencing is a standard test for identifying and selecting IVF-derived euploid embryos. The wealth of embryo aneuploidy data and ultra-low coverage whole-genome sequencing (ulc-WGS) data from PGT-A have the potential to discover variants in parental genomes that are associated with aneuploidy risk in their embryos. Using ulc-WGS data from ∼10,000 PGT-A biopsies, we imputed genotype likelihoods of genetic variants in embryo genomes. We then used the imputed variants and embryo aneuploidy calls to perform a genome-wide association study of aneuploidy incidence. Finally, we carried out functional evaluation of the identified candidate gene in a mouse oocyte system. We identified one locus on chromosome 3 that is significantly associated with meiotic aneuploidy risk. One candidate gene, CCDC66, encompassed by this locus, is involved in chromosome segregation during meiosis. Using mouse oocytes, we showed that CCDC66 regulates meiotic progression and chromosome segregation fidelity, especially in older mice. Our work extended the research utility of PGT-A ulc-WGS data by allowing robust association testing and improved the understanding of the genetic contribution to maternal meiotic aneuploidy risk. Importantly, we introduce a generalizable method that has potential to be leveraged for similar association studies that use ulc-WGS data.
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Affiliation(s)
- Siqi Sun
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Mansour Aboelenain
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA; Department of Theriogenology, Faculty of Veterinary Medicine, Mansoura University, Mansoura, Egypt
| | - Daniel Ariad
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | | | | | - Marlena Duke
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Aishee Bag
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Manuel Viotti
- Zouves Foundation for Reproductive Medicine, Foster City, CA, USA; Kindlabs, Kindbody, New York, NY, USA
| | | | - Rajiv C McCoy
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Karen Schindler
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA; Human Genetics Institute of New Jersey, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Jinchuan Xing
- Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA; Human Genetics Institute of New Jersey, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.
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7
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Vasavda C, Wan G, Szeto MD, Marani M, Sutaria N, Rajeh A, Lu C, Lee KK, Nguyen NTT, Adawi W, Deng J, Parthasarathy V, Bordeaux ZA, Taylor MT, Alphonse MP, Kwatra MM, Kang S, Semenov YR, Gusev A, Kwatra SG. A Polygenic Risk Score for Predicting Racial and Genetic Susceptibility to Prurigo Nodularis. J Invest Dermatol 2023; 143:2416-2426.e1. [PMID: 37245863 DOI: 10.1016/j.jid.2023.04.033] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 04/07/2023] [Accepted: 04/17/2023] [Indexed: 05/30/2023]
Abstract
Prurigo nodularis (PN) is an understudied inflammatory skin disease characterized by pruritic, hyperkeratotic nodules. Identifying the genetic factors underlying PN could help to better understand its etiology and guide the development of therapies. In this study, we developed a polygenic risk score that predicts a diagnosis of PN (OR = 1.41, P = 1.6 × 10-5) in two independent and continentally distinct populations. We also performed GWASs, which uncovered genetic variants associated with PN, including one near PLCB4 (rs6039266: OR = 3.15, P = 4.8 × 10-8) and others near TXNRD1 (rs34217906: OR = 1.71, P = 6.4 × 10-7; rs7134193: OR = 1.57, P = 1.1 × 10-6). Finally, we discovered that Black patients have over a two-times greater genetic risk of developing PN (OR = 2.63, P = 7.8 × 10-4). Combining the polygenic risk score and self-reported race together was significantly predictive of PN (OR = 1.32, P = 4.7 × 10-3). Strikingly, this association was more significant with race than after adjusting for genetic ancestry. Because race is a sociocultural construct and not a genetically bound category, our findings suggest that genetics, environmental influence, and social determinants of health likely affect the development of PN and may contribute to clinically observed racial disparities.
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Affiliation(s)
- Chirag Vasavda
- The Solomon H. Snyder Department of Neuroscience, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA; Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Guihong Wan
- Department of Dermatology, Massachusetts General Hospital, Boston, Massachusetts, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Mindy D Szeto
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Melika Marani
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Nishadh Sutaria
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Ahmad Rajeh
- Department of Dermatology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Chenyue Lu
- Department of Dermatology, Massachusetts General Hospital, Boston, Massachusetts, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
| | - Kevin K Lee
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Nga T T Nguyen
- Department of Dermatology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Waleed Adawi
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Junwen Deng
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Varsha Parthasarathy
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Zachary A Bordeaux
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Matthew T Taylor
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Martin P Alphonse
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Madan M Kwatra
- Department of Anesthesiology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Sewon Kang
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Yevgeniy R Semenov
- Department of Dermatology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Alexander Gusev
- Division of Genetics, Brigham & Women's Hospital, Boston, Massachusetts, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Shawn G Kwatra
- Department of Dermatology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA; Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
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8
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Gusev A. Germline mechanisms of immunotherapy toxicities in the era of genome-wide association studies. Immunol Rev 2023; 318:138-156. [PMID: 37515388 DOI: 10.1111/imr.13253] [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: 03/14/2023] [Accepted: 06/29/2023] [Indexed: 07/30/2023]
Abstract
Cancer immunotherapy has revolutionized the treatment of advanced cancers and is quickly becoming an option for early-stage disease. By reactivating the host immune system, immunotherapy harnesses patients' innate defenses to eradicate the tumor. By putatively similar mechanisms, immunotherapy can also substantially increase the risk of toxicities or immune-related adverse events (irAEs). Severe irAEs can lead to hospitalization, treatment discontinuation, lifelong immune complications, or even death. Many irAEs present with similar symptoms to heritable autoimmune diseases, suggesting that germline genetics may contribute to their onset. Recently, genome-wide association studies (GWAS) of irAEs have identified common germline associations and putative mechanisms, lending support to this hypothesis. A wide range of well-established GWAS methods can potentially be harnessed to understand the etiology of irAEs specifically and immunotherapy outcomes broadly. This review summarizes current findings regarding germline effects on immunotherapy outcomes and discusses opportunities and challenges for leveraging germline genetics to understand, predict, and treat irAEs.
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Affiliation(s)
- Alexander Gusev
- Division of Population Sciences, Dana-Farber Cancer Institute and Harvard Medical School, Boston, Massachusetts, USA
- Division of Genetics, Brigham & Women's Hospital, Boston, Massachusetts, USA
- The Broad Institute, Cambridge, Massachusetts, USA
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9
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Petter E, Ding Y, Hou K, Bhattacharya A, Gusev A, Zaitlen N, Pasaniuc B. Genotype error due to low-coverage sequencing induces uncertainty in polygenic scoring. Am J Hum Genet 2023; 110:1319-1329. [PMID: 37490908 PMCID: PMC10432141 DOI: 10.1016/j.ajhg.2023.06.015] [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: 12/21/2022] [Revised: 06/30/2023] [Accepted: 06/30/2023] [Indexed: 07/27/2023] Open
Abstract
Polygenic scores (PGSs) have emerged as a standard approach to predict phenotypes from genotype data in a wide array of applications from socio-genomics to personalized medicine. Traditional PGSs assume genotype data to be error-free, ignoring possible errors and uncertainties introduced from genotyping, sequencing, and/or imputation. In this work, we investigate the effects of genotyping error due to low coverage sequencing on PGS estimation. We leverage SNP array and low-coverage whole-genome sequencing data (lcWGS, median coverage 0.04×) of 802 individuals from the Dana-Farber PROFILE cohort to show that PGS error correlates with sequencing depth (p = 1.2 × 10-7). We develop a probabilistic approach that incorporates genotype error in PGS estimation to produce well-calibrated PGS credible intervals and show that the probabilistic approach increases classification accuracy by up to 6% as compared to traditional PGSs that ignore genotyping error. Finally, we use simulations to explore the combined effect of genotyping and effect size errors and their implication on PGS-based risk-stratification. Our results illustrate the importance of considering genotyping error as a source of PGS error especially for cohorts with varying genotyping technologies and/or low-coverage sequencing.
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Affiliation(s)
- Ella Petter
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA 90095, USA.
| | - Yi Ding
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Kangcheng Hou
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Alexander Gusev
- Dana-Farber Cancer Institute, Boston, MA, USA; Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Noah Zaitlen
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Neurology, UCLA, Los Angeles, CA, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Institute for Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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10
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Moon I, LoPiccolo J, Baca SC, Sholl LM, Kehl KL, Hassett MJ, Liu D, Schrag D, Gusev A. Machine learning for genetics-based classification and treatment response prediction in cancer of unknown primary. Nat Med 2023; 29:2057-2067. [PMID: 37550415 DOI: 10.1038/s41591-023-02482-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 06/30/2023] [Indexed: 08/09/2023]
Abstract
Cancer of unknown primary (CUP) is a type of cancer that cannot be traced back to its primary site and accounts for 3-5% of all cancers. Established targeted therapies are lacking for CUP, leading to generally poor outcomes. We developed OncoNPC, a machine-learning classifier trained on targeted next-generation sequencing (NGS) data from 36,445 tumors across 22 cancer types from three institutions. Oncology NGS-based primary cancer-type classifier (OncoNPC) achieved a weighted F1 score of 0.942 for high confidence predictions ([Formula: see text]) on held-out tumor samples, which made up 65.2% of all the held-out samples. When applied to 971 CUP tumors collected at the Dana-Farber Cancer Institute, OncoNPC predicted primary cancer types with high confidence in 41.2% of the tumors. OncoNPC also identified CUP subgroups with significantly higher polygenic germline risk for the predicted cancer types and with significantly different survival outcomes. Notably, patients with CUP who received first palliative intent treatments concordant with their OncoNPC-predicted cancers had significantly better outcomes (hazard ratio (HR) = 0.348; 95% confidence interval (CI) = 0.210-0.570; P = [Formula: see text]). Furthermore, OncoNPC enabled a 2.2-fold increase in patients with CUP who could have received genomically guided therapies. OncoNPC thus provides evidence of distinct CUP subgroups and offers the potential for clinical decision support for managing patients with CUP.
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Affiliation(s)
- Intae Moon
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Division of Population Sciences, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Jaclyn LoPiccolo
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Sylvan C Baca
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Lynette M Sholl
- Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kenneth L Kehl
- Division of Population Sciences, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Michael J Hassett
- Division of Population Sciences, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - David Liu
- Division of Population Sciences, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- The Broad Institute of MIT & Harvard, Cambridge, MA, USA
| | - Deborah Schrag
- Memorial Sloan Kettering Cancer Center, New York City, NY, USA
| | - Alexander Gusev
- Division of Population Sciences, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.
- The Broad Institute of MIT & Harvard, Cambridge, MA, USA.
- Division of Genetics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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11
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Sun S, Aboelenain M, Ariad D, Haywood ME, Wageman CR, Duke M, Bag A, Viotti M, Katz-Jaffe M, McCoy RC, Schindler K, Xing J. Identifying risk genes for embryo aneuploidy using ultra-low coverage whole-genome sequencing. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.22.23292618. [PMID: 37546814 PMCID: PMC10402236 DOI: 10.1101/2023.07.22.23292618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Background Aneuploidy, the state of a cell containing extra or missing chromosomes, frequently arises during human meiosis and is the primary cause of early miscarriage and maternal age-related in vitro fertilization (IVF) failure. IVF patients exhibit significant variability in aneuploidy rates, although the exact genetic causes of the variability in aneuploid egg production remain unclear. Preimplantation genetic testing for aneuploidy (PGT-A) using ultra-low coverage whole-genome sequencing (ulc-WGS) is a standard test for identifying and selecting IVF-derived embryos with a normal chromosome complement. The wealth of embryo aneuploidy data and ulc-WGS data from PGT-A has potential for discovering variants in paternal genomes that are associated with aneuploidy risk in their embryos. Methods Using ulc-WGS data from ∼10,000 PGT-A biopsies, we imputed genotype likelihoods of genetic variants in parental genomes. We then used the imputed variants and aneuploidy calls from the embryos to perform a genome-wide association study of aneuploidy incidence. Finally, we carried out functional evaluation of the identified candidate gene in a mouse oocyte system. Results We identified one locus on chromosome 3 that is significantly associated with maternal meiotic aneuploidy risk. One candidate gene, CCDC66, encompassed by this locus, is involved in chromosome segregation during meiosis. Using mouse oocytes, we showed that CCDC66 regulates meiotic progression and chromosome segregation fidelity, especially in older mice. Conclusions Our work extended the research utility of PGT-A ulc-WGS data by allowing robust association testing and improved the understanding of the genetic contribution to maternal meiotic aneuploidy risk. Importantly, we introduce a generalizable method that can be leveraged for similar association studies using ulc-WGS data.
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12
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Liu Y, Gusev A, Kraft P. Germline Cancer Gene Expression Quantitative Trait Loci Are Associated with Local and Global Tumor Mutations. Cancer Res 2023; 83:1191-1202. [PMID: 36745477 PMCID: PMC10106413 DOI: 10.1158/0008-5472.can-22-2624] [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: 08/19/2022] [Revised: 12/13/2022] [Accepted: 02/01/2023] [Indexed: 02/07/2023]
Abstract
Somatic mutations drive cancer development and are relevant to patient responses to treatment. Emerging evidence shows that variations in the somatic genome can be influenced by the germline genetic background. However, the mechanisms underlying these germline-somatic associations remain largely obscure. We hypothesized that germline variants can influence somatic mutations in a nearby cancer gene ("local impact") or a set of recurrently mutated cancer genes across the genome ("global impact") through their regulatory effect on gene expression. To test this hypothesis, tumor targeted sequencing data from 12,413 patients across 11 cancer types in the Dana-Farber Profile cohort were integrated with germline cancer gene expression quantitative trait loci (eQTL) from the Genotype-Tissue Expression Project. Variants that upregulate ATM expression were associated with a decreased risk of somatic ATM mutations across 8 cancer types. GLI2, WRN, and CBFB eQTL were associated with global tumor mutational burden of cancer genes in ovarian cancer, glioma, and esophagogastric carcinoma, respectively. An EPHA5 eQTL was associated with mutations in cancer genes specific to colorectal cancer, and eQTL related to expression of APC, WRN, GLI1, FANCA, and TP53 were associated with mutations in genes specific to endometrial cancer. These findings provide evidence that germline-somatic associations are mediated through expression of specific cancer genes, opening new avenues for research on the underlying biological processes. SIGNIFICANCE Analysis of associations between the germline genetic background and somatic mutations in patients with cancer suggests that germline variants can influence local and global tumor mutations by altering expression of cancer-related genes. See related commentary by Kar, p. 1165.
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Affiliation(s)
- Yuxi Liu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Alexander Gusev
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, 02215, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
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13
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Kar SP. A New Frontier for Cancer Genetics: Identification of Germline-Somatic Associations. Cancer Res 2023; 83:1165-1166. [PMID: 37057597 DOI: 10.1158/0008-5472.can-23-0152] [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: 02/20/2023] [Accepted: 02/21/2023] [Indexed: 04/15/2023]
Abstract
Studies of the inherited or germline genome have identified rare mutations with large effects and common polymorphisms of more modest effect sizes that are associated with cancer risk. This research has substantially illuminated the etiology and development of cancer, with particular relevance to cancer prevention. In parallel, studies of the somatic or tumor genome have been instrumental in identifying the key drivers of cancer progression, significantly informing modern cancer therapy. While these studies have thus far largely been performed separately, integrative studies where the germline and somatic genomes are mapped in the same individuals have the potential to yield novel and holistic insights into cancer biology. In this issue of Cancer Research, Liu and colleagues report the results of integrative germline-somatic analyses in over 12,000 patients with cancer and 11 cancer types, identifying several associations where inherited variants that regulate the expression of a nearby gene in normal tissues are associated with tumor mutations in the same gene or with genome-wide somatic traits such as the tumor mutational burden. Although considerable follow-up work is required, the study is an important contribution to an emerging body of evidence that is demonstrating that the germline has a vital role in shaping the tumor genome. See related article by Liu et al., p. 1191.
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Affiliation(s)
- Siddhartha P Kar
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
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14
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Houlahan KE, Khan A, Greenwald NF, West RB, Angelo M, Curtis C. Germline-mediated immunoediting sculpts breast cancer subtypes and metastatic proclivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.15.532870. [PMID: 36993286 PMCID: PMC10055121 DOI: 10.1101/2023.03.15.532870] [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: 06/19/2023]
Abstract
Cancer represents a broad spectrum of molecularly and morphologically diverse diseases. Individuals with the same clinical diagnosis can have tumors with drastically different molecular profiles and clinical response to treatment. It remains unclear when these differences arise during disease course and why some tumors are addicted to one oncogenic pathway over another. Somatic genomic aberrations occur within the context of an individual's germline genome, which can vary across millions of polymorphic sites. An open question is whether germline differences influence somatic tumor evolution. Interrogating 3,855 breast cancer lesions, spanning pre-invasive to metastatic disease, we demonstrate that germline variants in highly expressed and amplified genes influence somatic evolution by modulating immunoediting at early stages of tumor development. Specifically, we show that the burden of germline-derived epitopes in recurrently amplified genes selects against somatic gene amplification in breast cancer. For example, individuals with a high burden of germline-derived epitopes in ERBB2, encoding human epidermal growth factor receptor 2 (HER2), are significantly less likely to develop HER2-positive breast cancer compared to other subtypes. The same holds true for recurrent amplicons that define four subgroups of ER-positive breast cancers at high risk of distant relapse. High epitope burden in these recurrently amplified regions is associated with decreased likelihood of developing high risk ER-positive cancer. Tumors that overcome such immune-mediated negative selection are more aggressive and demonstrate an "immune cold" phenotype. These data show the germline genome plays a previously unappreciated role in dictating somatic evolution. Exploiting germline-mediated immunoediting may inform the development of biomarkers that refine risk stratification within breast cancer subtypes.
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Affiliation(s)
- Kathleen E. Houlahan
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Aziz Khan
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Noah F Greenwald
- Cancer Biology Program, Stanford University School of Medicine, Stanford, CA, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Robert B. West
- Cancer Biology Program, Stanford University School of Medicine, Stanford, CA, USA
| | - Michael Angelo
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Christina Curtis
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine (Oncology), Stanford University School of Medicine, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
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15
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Mroczek M, Liu J, Sypniewski M, Pieńkowski T, Itrych B, Stojak J, Pronobis-Szczylik B, Stępień M, Kaja E, Dąbrowski M, Suchocki T, Wojtaszewska M, Zawadzki P, Mach A, Sztromwasser P, Król ZJ, Szyda J, Dobosz P. The cancer-risk variant frequency among Polish population reported by the first national whole-genome sequencing study. Front Oncol 2023; 13:1045817. [PMID: 36845707 PMCID: PMC9950741 DOI: 10.3389/fonc.2023.1045817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 01/20/2023] [Indexed: 02/12/2023] Open
Abstract
Introduction Population-based cancer screening has raised many controversies in recent years, not only regarding the costs but also regarding the ethical nature and issues related to variant interpretation. Nowadays, genetic cancer screening standards are different in every country and usually encompass only individuals with a personal or family history of relevant cancer. Methods Here we performed a broad genetic screening for cancer-related rare germline variants on population data from the Thousand Polish Genomes database based on 1076 Polish unrelated individuals that underwent whole genome sequencing (WGS). Results We identified 19 551 rare variants in 806 genes related to oncological diseases, among them 89% have been located in non-coding regions. The combined BRCA1/BRCA2 pathogenic/likely pathogenic according to ClinVar allele frequency in the unselected population of 1076 Poles was 0.42%, corresponding to nine carriers. Discussion Altogether, on the population level, we found especially problematic the assessment of the pathogenicity of variants and the relation of ACMG guidelines to the population frequency. Some of the variants may be overinterpreted as disease-causing due to their rarity or lack of annotation in the databases. On the other hand, some relevant variants may have been overseen given that there is little pooled population whole genome data on oncology. Before population WGS screening will become a standard, further studies are needed to assess the frequency of the variants suspected to be pathogenic on the population level and with reporting of likely benign variants.
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Affiliation(s)
- Magdalena Mroczek
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland,*Correspondence: Magdalena Mroczek,
| | - Jakub Liu
- Biostatistics Group, Wrocław University of Environmental and Life Sciences, Wrocław, Poland
| | - Mateusz Sypniewski
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland
| | - Tadeusz Pieńkowski
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland,Postgraduate Medical Education Center, Warsaw, Poland
| | - Bartosz Itrych
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland
| | - Joanna Stojak
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland,Department of Experimental Embryology, Institute of Genetics and Animal Biotechnology, Polish Academy of Science, Jastrzębiec, Poland
| | | | - Maria Stępień
- Department of Sports Medicine, Doctoral School, Medical University of Lublin, Lublin, Poland
| | - Elżbieta Kaja
- Department of Medical Chemistry and Laboratory Medicine, Poznan University of Medical Sciences, Poznan, Poland
| | | | - Tomasz Suchocki
- Biostatistics Group, Wrocław University of Environmental and Life Sciences, Wrocław, Poland,National Research Institute of Animal Production, Balice, Poland
| | - Marzena Wojtaszewska
- Department of Haematology, Institute of Medical Sciences, College of Medical Sciences, University of Rzeszów, Rzeszów, Poland,Department of Haematology, Frederic Chopin Provincial Specialist Hospital, Rzeszów, Poland
| | | | - Anna Mach
- Department of Psychiatry, Medical University of Warsaw, Warsaw, Poland
| | | | - Zbigniew J. Król
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland
| | - Joanna Szyda
- Biostatistics Group, Wrocław University of Environmental and Life Sciences, Wrocław, Poland,National Research Institute of Animal Production, Balice, Poland
| | - Paula Dobosz
- Central Clinical Hospital of Ministry of the Interior and Administration in Warsaw, Warsaw, Poland
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16
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Nachmanson D, Pagadala M, Steward J, Cheung C, Bruce LK, Lee NQ, O'Keefe TJ, Lin GY, Hasteh F, Morris GP, Carter H, Harismendy O. Accurate genome-wide genotyping from archival tissue to explore the contribution of common genetic variants to pre-cancer outcomes. J Transl Med 2022; 20:623. [PMID: 36575447 PMCID: PMC9793518 DOI: 10.1186/s12967-022-03810-z] [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: 09/03/2022] [Accepted: 12/05/2022] [Indexed: 12/28/2022] Open
Abstract
PURPOSE The contribution of common genetic variants to pre-cancer progression is understudied due to long follow-up time, rarity of poor outcomes and lack of available germline DNA collection. Alternatively, DNA from diagnostic archival tissue is available, but its somatic nature, limited quantity and suboptimal quality would require an accurate cost-effective genome-wide germline genotyping methodology. EXPERIMENTAL DESIGN Blood and tissue DNA from 10 individuals were used to benchmark the accuracy of Single Nucleotide Polymorphisms (SNP) genotypes, Polygenic Risk Scores (PRS) or HLA haplotypes using low-coverage whole-genome sequencing (lc-WGS) and genotype imputation. Tissue-derived PRS were further evaluated for 36 breast cancer patients (11.7 years median follow-up time) diagnosed with DCIS and used to model the risk of Breast Cancer Subsequent Events (BCSE). RESULTS Tissue-derived germline DNA profiling resulted in accurate genotypes at common SNPs (blood correlation r2 > 0.94) and across 22 disease-related polygenic risk scores (PRS, mean correlation r = 0.93). Imputed Class I and II HLA haplotypes were 96.7% and 82.5% concordant with clinical-grade blood HLA haplotypes, respectively. In DCIS patients, tissue-derived PRS was significantly associated with BCSE (HR = 2, 95% CI 1.2-3.8). The top and bottom decile patients had an estimated 28% and 5% chance of BCSE at 10 years, respectively. CONCLUSIONS Archival tissue DNA germline profiling using lc-WGS and imputation, represents a cost and resource-effective alternative in the retrospective design of long-term disease genetic studies. Initial results in breast cancer suggest that common risk variants contribute to pre-cancer progression.
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Affiliation(s)
- Daniela Nachmanson
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA
| | - Meghana Pagadala
- Biomedical Science Graduate Program, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA
| | - Joseph Steward
- Moores Cancer Center, University of California San Diego, 3855 Health Science Drive, San Diego, CA, 92093, USA
| | - Callie Cheung
- Moores Cancer Center, University of California San Diego, 3855 Health Science Drive, San Diego, CA, 92093, USA
| | - Lauryn Keeler Bruce
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA
| | - Nicole Q Lee
- Moores Cancer Center, University of California San Diego, 3855 Health Science Drive, San Diego, CA, 92093, USA
| | - Thomas J O'Keefe
- Department of Surgery, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA
| | - Grace Y Lin
- Department of Pathology, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA
| | - Farnaz Hasteh
- Department of Pathology, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA
| | - Gerald P Morris
- Department of Pathology, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA
| | - Hannah Carter
- Moores Cancer Center, University of California San Diego, 3855 Health Science Drive, San Diego, CA, 92093, USA
- Division of Medical Genetics, Department of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Olivier Harismendy
- Moores Cancer Center, University of California San Diego, 3855 Health Science Drive, San Diego, CA, 92093, USA.
- Division of Biomedical Informatics, Department of Medicine, University of California San Diego, 9500 Gilman Drive, San Diego, CA, 92093, USA.
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17
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Groha S, Alaiwi SA, Xu W, Naranbhai V, Nassar AH, Bakouny Z, El Zarif T, Saliby RM, Wan G, Rajeh A, Adib E, Nuzzo PV, Schmidt AL, Labaki C, Ricciuti B, Alessi JV, Braun DA, Shukla SA, Keenan TE, Van Allen E, Awad MM, Manos M, Rahma O, Zubiri L, Villani AC, Fairfax B, Hammer C, Khan Z, Reynolds K, Semenov Y, Schrag D, Kehl KL, Freedman ML, Choueiri TK, Gusev A. Germline variants associated with toxicity to immune checkpoint blockade. Nat Med 2022; 28:2584-2591. [PMID: 36526723 PMCID: PMC10958775 DOI: 10.1038/s41591-022-02094-6] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 10/18/2022] [Indexed: 12/23/2022]
Abstract
Immune checkpoint inhibitors (ICIs) have yielded remarkable responses but often lead to immune-related adverse events (irAEs). Although germline causes for irAEs have been hypothesized, no individual variant associated with developing irAEs has been identified. We carried out a genome-wide association study of 1,751 patients on ICIs across 12 cancer types. We investigated two irAE phenotypes: (1) high-grade (3-5) and (2) all-grade events. We identified 3 genome-wide significant associations (P < 5 × 10-8) in the discovery cohort associated with all-grade irAEs: rs16906115 near IL7 (combined P = 3.6 × 10-11; hazard ratio (HR) = 2.1); rs75824728 near IL22RA1 (combined P = 3.5 × 10-8; HR = 1.8); and rs113861051 on 4p15 (combined P = 1.2 × 10-8, HR = 2.0); rs16906115 was replicated in 3 independent studies. The association near IL7 colocalized with the gain of a new cryptic exon for IL7, a critical regulator of lymphocyte homeostasis. Patients carrying the IL7 germline variant exhibited significantly increased lymphocyte stability after ICI initiation, which was itself predictive of downstream irAEs and improved survival.
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Affiliation(s)
- Stefan Groha
- Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Broad Institute of Harvard & MIT, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Sarah Abou Alaiwi
- Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Wenxin Xu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Vivek Naranbhai
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Amin H Nassar
- Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Ziad Bakouny
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Talal El Zarif
- Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Renee Maria Saliby
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Guihong Wan
- Harvard Medical School, Boston, MA, USA
- Department of Dermatology, Massachusetts General Hospital, Boston, MA, USA
| | - Ahmad Rajeh
- Department of Dermatology, Massachusetts General Hospital, Boston, MA, USA
| | - Elio Adib
- Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Pier V Nuzzo
- Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Internal Medicine and Medical Specialties, School of Medicine, University of Genoa, Genoa, Italy
| | - Andrew L Schmidt
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Chris Labaki
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Biagio Ricciuti
- Lowe Center for Thoracic Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Joao Victor Alessi
- Department of Internal Medicine and Medical Specialties, School of Medicine, University of Genoa, Genoa, Italy
| | - David A Braun
- Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Center of Molecular and Cellular Oncology, Yale Cancer Center, Yale School of Medicine, New Haven, CT, USA
| | - Sachet A Shukla
- Broad Institute of Harvard & MIT, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Translational Immunogenomics Lab, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Tanya E Keenan
- Broad Institute of Harvard & MIT, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Breast Oncology Program, Dana-Farber/Brigham and Women's Cancer Center, Boston, MA, USA
| | - Eliezer Van Allen
- Broad Institute of Harvard & MIT, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Center for Cancer Precision Medicine, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Mark M Awad
- Department of Internal Medicine and Medical Specialties, School of Medicine, University of Genoa, Genoa, Italy
| | - Michael Manos
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Osama Rahma
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Alexandra-Chloe Villani
- Broad Institute of Harvard & MIT, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Immunology and Inflammatory Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Zia Khan
- Genentech, South San Francisco, CA, USA
| | - Kerry Reynolds
- Harvard Medical School, Boston, MA, USA
- Division of Medical Oncology, Bartlett, Massachusetts General Hospital, Boston, MA, USA
| | - Yevgeniy Semenov
- Harvard Medical School, Boston, MA, USA
- Department of Dermatology, Massachusetts General Hospital, Boston, MA, USA
| | - Deborah Schrag
- Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Kenneth L Kehl
- Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Matthew L Freedman
- Broad Institute of Harvard & MIT, Cambridge, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
| | - Toni K Choueiri
- Harvard Medical School, Boston, MA, USA
- Lank Center for Genitourinary Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Alexander Gusev
- Division of Population Sciences, Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
- Broad Institute of Harvard & MIT, Cambridge, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Division of Genetics, Brigham and Women's Hospital, Boston, MA, USA.
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18
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Arora K, Tran TN, Kemel Y, Mehine M, Liu YL, Nandakumar S, Smith SA, Brannon AR, Ostrovnaya I, Stopsack KH, Razavi P, Safonov A, Rizvi HA, Hellmann MD, Vijai J, Reynolds TC, Fagin JA, Carrot-Zhang J, Offit K, Solit DB, Ladanyi M, Schultz N, Zehir A, Brown CL, Stadler ZK, Chakravarty D, Bandlamudi C, Berger MF. Genetic Ancestry Correlates with Somatic Differences in a Real-World Clinical Cancer Sequencing Cohort. Cancer Discov 2022; 12:2552-2565. [PMID: 36048199 PMCID: PMC9633436 DOI: 10.1158/2159-8290.cd-22-0312] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 07/12/2022] [Accepted: 08/29/2022] [Indexed: 01/12/2023]
Abstract
Accurate ancestry inference is critical for identifying genetic contributors of cancer disparities among populations. Although methods to infer genetic ancestry have historically relied upon genome-wide markers, the adaptation to targeted clinical sequencing panels presents an opportunity to incorporate ancestry inference into routine diagnostic workflows. We show that global ancestral contributions and admixture of continental populations can be quantitatively inferred using markers captured by the MSK-IMPACT clinical panel. In a pan-cancer cohort of 45,157 patients, we observed differences by ancestry in the frequency of somatic alterations, recapitulating known associations and revealing novel associations. Despite the comparable overall prevalence of driver alterations by ancestry group, the proportion of patients with clinically actionable alterations was lower for African (30%) compared with European (33%) ancestry. Although this result is largely explained by population-specific cancer subtype differences, it reveals an inequity in the degree to which different populations are served by existing precision oncology interventions. SIGNIFICANCE We performed a comprehensive analysis of ancestral associations with somatic mutations in a real-world pan-cancer cohort, including >5,000 non-European individuals. Using an FDA-authorized tumor sequencing panel and an FDA-recognized oncology knowledge base, we detected differences in the prevalence of clinically actionable alterations, potentially contributing to health care disparities affecting underrepresented populations. This article is highlighted in the In This Issue feature, p. 2483.
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Affiliation(s)
- Kanika Arora
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Thinh Ngoc. Tran
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yelena Kemel
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Robert and Kate Niehaus Center for Inherited Cancer Genomics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Miika Mehine
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ying L. Liu
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Subhiksha Nandakumar
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Shaleigh A Smith
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - A. Rose Brannon
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Irina Ostrovnaya
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Konrad H. Stopsack
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Pedram Razavi
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Anton Safonov
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Hira A. Rizvi
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Matthew D. Hellmann
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Joseph Vijai
- Robert and Kate Niehaus Center for Inherited Cancer Genomics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Thomas C. Reynolds
- Office of Health Equity, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - James A. Fagin
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jian Carrot-Zhang
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Kenneth Offit
- Robert and Kate Niehaus Center for Inherited Cancer Genomics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - David B. Solit
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Marc Ladanyi
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Nikolaus Schultz
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ahmet Zehir
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Carol L. Brown
- Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Office of Health Equity, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Zsofia K. Stadler
- Robert and Kate Niehaus Center for Inherited Cancer Genomics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Debyani Chakravarty
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Chaitanya Bandlamudi
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Michael F. Berger
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Marie-Josée and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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19
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Serzan M, Atkins MB. Adjuvant therapy for patients with renal cell carcinoma following surgery: a focus on pembrolizumab. Expert Rev Anticancer Ther 2022; 22:565-574. [PMID: 35483033 DOI: 10.1080/14737140.2022.2072300] [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: 11/04/2022]
Abstract
INTRODUCTION Many patients with renal cell carcinoma (RCC) who undergo surgery with curative intent have a high risk of disease recurrence and until recently no palatable adjuvant systemic therapy options. Blocking the programmed death ligand (PD-1) immune checkpoint pathway with pembrolizumab has robust clinical efficacy in patients with metastatic RCC. Results from the KEYNOTE 564 trial demonstrate that adjuvant pembrolizumab significantly improves disease- free survival after nephrectomy or metastatectomy. AREAS COVERED We provide an overview of efforts to develop an adjuvant therapy in patients with high-risk RCC. This includes a critical review of efficacy, toxicity, and clinical implications from a large phase III trial leading to the FDA and EMA approvals of adjuvant pembrolizumab. EXPERT OPINION Pembrolizumab offers an effective and well-tolerated adjuvant therapy for patients with surgically resected RCC at high-risk of disease recurrence. Future research will focus on optimal patient selection and biomarkers that predict benefit and/or toxicity from therapy.
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Affiliation(s)
- Michael Serzan
- Department of Oncology, Georgetown-Lombardi Comprehensive Cancer Center, Washington DC.,Department of Medicine, Medstar Georgetown University Hospital, Washington DC
| | - Michael B Atkins
- Department of Oncology, Georgetown-Lombardi Comprehensive Cancer Center, Washington DC.,Department of Medicine, Medstar Georgetown University Hospital, Washington DC
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20
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Adib E, Nassar AH, Abou Alaiwi S, Groha S, Akl EW, Sholl LM, Michael KS, Awad MM, Jӓnne PA, Gusev A, Kwiatkowski DJ. Variation in targetable genomic alterations in non-small cell lung cancer by genetic ancestry, sex, smoking history, and histology. Genome Med 2022; 14:39. [PMID: 35428358 PMCID: PMC9013075 DOI: 10.1186/s13073-022-01041-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 03/22/2022] [Indexed: 11/21/2022] Open
Abstract
Background Genomic alterations in 8 genes are now the targets of FDA-approved therapeutics in non-small cell lung cancer (NSCLC), but their distribution according to genetic ancestry, sex, histology, and smoking is not well established. Methods Using multi-institutional genetic testing data from GENIE, we characterize the distribution of targetable genomic alterations in 8 genes among 8675 patients with NSCLC (discovery cohort: DFCI, N = 3115; validation cohort: Duke, Memorial Sloan Kettering Cancer Center, Vanderbilt, N = 5560). For the discovery cohort, we impute genetic ancestry from tumor-only sequencing and identify differences in the frequency of targetable alterations across ancestral groups, smoking pack-years, and histologic subtypes. Results We identified variation in the prevalence of KRASG12C, sensitizing EGFR mutations, MET alterations, ALK, and ROS1 fusions according to the number of smoking pack-years. A novel method for computing continental (African, Asian, European) and Ashkenazi Jewish ancestries from panel sequencing enables quantitative analysis of the correlation between ancestry and mutation rates. This analysis identifies a correlation between Asian ancestry and EGFR mutations and an anti-correlation between Asian ancestry and KRASG12C mutation. It uncovers 2.7-fold enrichment for MET exon 14 skipping mutations and amplifications in patients of Ashkenazi Jewish ancestry. Among never/light smokers, targetable alterations in LUAD are significantly enriched in those with Asian (80%) versus African (49%) and European (55%) ancestry. Finally, we show that 5% of patients with squamous cell carcinoma (LUSC) and 17% of patients with large cell carcinoma (LCLC) harbor targetable alterations. Conclusions Among patients with NSCLC, there was significant variability in the prevalence of targetable genomic alterations according to genetic ancestry, histology, and smoking. Patients with LUSC and LCLC have 5% rates of targetable alterations supporting consideration for sequencing in those subtypes. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-022-01041-x.
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