51
|
Ragone C, Cavalluzzo B, Mauriello A, Tagliamonte M, Buonaguro L. Lack of shared neoantigens in prevalent mutations in cancer. J Transl Med 2024; 22:344. [PMID: 38600547 PMCID: PMC11005154 DOI: 10.1186/s12967-024-05110-0] [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: 02/26/2024] [Accepted: 03/19/2024] [Indexed: 04/12/2024] Open
Abstract
Tumors are mostly characterized by genetic instability, as result of mutations in surveillance mechanisms, such as DNA damage checkpoint, DNA repair machinery and mitotic checkpoint. Defect in one or more of these mechanisms causes additive accumulation of mutations. Some of these mutations are drivers of transformation and are positively selected during the evolution of the cancer, giving a growth advantage on the cancer cells. If such mutations would result in mutated neoantigens, these could be actionable targets for cancer vaccines and/or adoptive cell therapies. However, the results of the present analysis show, for the first time, that the most prevalent mutations identified in human cancers do not express mutated neoantigens. The hypothesis is that this is the result of the selection operated by the immune system in the very early stages of tumor development. At that stage, the tumor cells characterized by mutations giving rise to highly antigenic non-self-mutated neoantigens would be efficiently targeted and eliminated. Consequently, the outgrowing tumor cells cannot be controlled by the immune system, with an ultimate growth advantage to form large tumors embedded in an immunosuppressive tumor microenvironment (TME). The outcome of such a negative selection operated by the immune system is that the development of off-the-shelf vaccines, based on shared mutated neoantigens, does not seem to be at hand. This finding represents the first demonstration of the key role of the immune system on shaping the tumor antigen presentation and the implication in the development of antitumor immunological strategies.
Collapse
Affiliation(s)
- Concetta Ragone
- Lab of Innovative Immunological Models Unit, Istituto Nazionale Tumori, IRCCS - "Fondazione Pascale", Via Mariano Semmola, 52, 80131, Naples, Italy
| | - Beatrice Cavalluzzo
- Lab of Innovative Immunological Models Unit, Istituto Nazionale Tumori, IRCCS - "Fondazione Pascale", Via Mariano Semmola, 52, 80131, Naples, Italy
| | - Angela Mauriello
- Lab of Innovative Immunological Models Unit, Istituto Nazionale Tumori, IRCCS - "Fondazione Pascale", Via Mariano Semmola, 52, 80131, Naples, Italy
| | - Maria Tagliamonte
- Lab of Innovative Immunological Models Unit, Istituto Nazionale Tumori, IRCCS - "Fondazione Pascale", Via Mariano Semmola, 52, 80131, Naples, Italy.
| | - Luigi Buonaguro
- Lab of Innovative Immunological Models Unit, Istituto Nazionale Tumori, IRCCS - "Fondazione Pascale", Via Mariano Semmola, 52, 80131, Naples, Italy.
| |
Collapse
|
52
|
Maura F, Rajanna AR, Ziccheddu B, Poos AM, Derkach A, Maclachlan K, Durante M, Diamond B, Papadimitriou M, Davies F, Boyle EM, Walker B, Hultcrantz M, Silva A, Hampton O, Teer JK, Siegel EM, Bolli N, Jackson GH, Kaiser M, Pawlyn C, Cook G, Kazandjian D, Stein C, Chesi M, Bergsagel L, Mai EK, Goldschmidt H, Weisel KC, Fenk R, Raab MS, Van Rhee F, Usmani S, Shain KH, Weinhold N, Morgan G, Landgren O. Genomic Classification and Individualized Prognosis in Multiple Myeloma. J Clin Oncol 2024; 42:1229-1240. [PMID: 38194610 PMCID: PMC11095887 DOI: 10.1200/jco.23.01277] [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: 06/14/2023] [Revised: 09/08/2023] [Accepted: 10/23/2023] [Indexed: 01/11/2024] Open
Abstract
PURPOSE Outcomes for patients with newly diagnosed multiple myeloma (NDMM) are heterogenous, with overall survival (OS) ranging from months to over 10 years. METHODS To decipher and predict the molecular and clinical heterogeneity of NDMM, we assembled a series of 1,933 patients with available clinical, genomic, and therapeutic data. RESULTS Leveraging a comprehensive catalog of genomic drivers, we identified 12 groups, expanding on previous gene expression-based molecular classifications. To build a model predicting individualized risk in NDMM (IRMMa), we integrated clinical, genomic, and treatment variables. To correct for time-dependent variables, including high-dose melphalan followed by autologous stem-cell transplantation (HDM-ASCT), and maintenance therapy, a multi-state model was designed. The IRMMa model accuracy was significantly higher than all comparator prognostic models, with a c-index for OS of 0.726, compared with International Staging System (ISS; 0.61), revised-ISS (0.572), and R2-ISS (0.625). Integral to model accuracy was 20 genomic features, including 1q21 gain/amp, del 1p, TP53 loss, NSD2 translocations, APOBEC mutational signatures, and copy-number signatures (reflecting the complex structural variant chromothripsis). IRMMa accuracy and superiority compared with other prognostic models were validated on 256 patients enrolled in the GMMG-HD6 (ClinicalTrials.gov identifier: NCT02495922) clinical trial. Individualized patient risks were significantly affected across the 12 genomic groups by different treatment strategies (ie, treatment variance), which was used to identify patients for whom HDM-ASCT is particularly effective versus patients for whom the impact is limited. CONCLUSION Integrating clinical, demographic, genomic, and therapeutic data, to our knowledge, we have developed the first individualized risk-prediction model enabling personally tailored therapeutic decisions for patients with NDMM.
Collapse
Affiliation(s)
- Francesco Maura
- Myeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL
| | - Arjun Raj Rajanna
- Myeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL
| | - Bachisio Ziccheddu
- Myeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL
| | - Alexandra M. Poos
- Heidelberg Myeloma Center, Department of Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit (CCU) Molecular Hematology/Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andriy Derkach
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Kylee Maclachlan
- Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Michael Durante
- Myeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL
| | - Benjamin Diamond
- Myeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL
| | - Marios Papadimitriou
- Myeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL
| | - Faith Davies
- Myeloma Research Program, New York University Langone, Perlmutter Cancer Center, New York, NY
| | - Eileen M. Boyle
- Myeloma Research Program, New York University Langone, Perlmutter Cancer Center, New York, NY
| | - Brian Walker
- Division of Hematology Oncology, Melvin and Bren Simon Comprehensive Cancer Center, Indiana University, Indianapolis, IN
| | - Malin Hultcrantz
- Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Ariosto Silva
- Department of Malignant Hematology, Moffitt Cancer Center, Tampa, FL
| | | | - Jamie K. Teer
- Department of Biostatistics & Bioinformatics, Moffitt Cancer Center & Research Institute, Tampa, FL
| | - Erin M. Siegel
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL
| | - Niccolò Bolli
- Hematology Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
- Department of Oncology and Onco-Hematology, University of Milan, Milan, Italy
| | - Graham H. Jackson
- Freeman Hospital, The Newcastle Upon Tyne Hospitals NHS Foundation Trust, Newcastle, United Kingdom
| | - Martin Kaiser
- The Institute of Cancer Research, London, United Kingdom
| | - Charlotte Pawlyn
- Leeds Cancer Research UK Clinical Trials Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, United Kingdom
| | - Gordon Cook
- Division of Hematology/Oncology, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Dickran Kazandjian
- Myeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL
| | - Caleb Stein
- Division of Hematology/Oncology, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Marta Chesi
- Division of Hematology/Oncology, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Leif Bergsagel
- Division of Hematology/Oncology, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Elias K. Mai
- Heidelberg Myeloma Center, Department of Medicine V, University Hospital Heidelberg, Heidelberg, Germany
| | - Hartmut Goldschmidt
- Heidelberg Myeloma Center, Department of Medicine V, University Hospital Heidelberg, Heidelberg, Germany
| | - Katja C. Weisel
- Department of Oncology, Hematology and Blood and Marrow Transplant, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Roland Fenk
- Department of Hematology, Oncology and Clinical Immunology, University-Hospital Duesseldorf, Duesseldorf, Germany
| | - Marc S. Raab
- Heidelberg Myeloma Center, Department of Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit (CCU) Molecular Hematology/Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Fritz Van Rhee
- Myeloma Institute for Research & Therapy, University of Arkansas for Medical Sciences, Little Rock, AR
| | - Saad Usmani
- Myeloma Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Kenneth H. Shain
- Department of Malignant Hematology, Moffitt Cancer Center, Tampa, FL
| | - Niels Weinhold
- Heidelberg Myeloma Center, Department of Medicine V, University Hospital Heidelberg, Heidelberg, Germany
- Clinical Cooperation Unit (CCU) Molecular Hematology/Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Gareth Morgan
- Myeloma Research Program, New York University Langone, Perlmutter Cancer Center, New York, NY
| | - Ola Landgren
- Myeloma Division, Sylvester Comprehensive Cancer Center, University of Miami, Miami, FL
| |
Collapse
|
53
|
Nakauma-González JA, Rijnders M, Noordsij MTW, Martens JWM, van der Veldt AAM, Lolkema MPJ, Boormans JL, van de Werken HJG. Whole-genome mapping of APOBEC mutagenesis in metastatic urothelial carcinoma identifies driver hotspot mutations and a novel mutational signature. CELL GENOMICS 2024; 4:100528. [PMID: 38552621 PMCID: PMC11019362 DOI: 10.1016/j.xgen.2024.100528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 12/22/2023] [Accepted: 03/06/2024] [Indexed: 04/13/2024]
Abstract
Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like (APOBEC) enzymes mutate specific DNA sequences and hairpin-loop structures, challenging the distinction between passenger and driver hotspot mutations. Here, we characterized 115 whole genomes of metastatic urothelial carcinoma (mUC) to identify APOBEC mutagenic hotspot drivers. APOBEC-associated mutations were detected in 92% of mUCs and were equally distributed across the genome, while APOBEC hotspot mutations (ApoHMs) were enriched in open chromatin. Hairpin loops were frequent targets of didymi (twins in Greek), two hotspot mutations characterized by the APOBEC SBS2 signature, in conjunction with an uncharacterized mutational context (Ap[C>T]). Next, we developed a statistical framework that identified ApoHMs as drivers in coding and non-coding genomic regions of mUCs. Our results and statistical framework were validated in independent cohorts of 23 non-metastatic UCs and 3,744 samples of 17 metastatic cancers, identifying cancer-type-specific drivers. Our study highlights the role of APOBEC in cancer development and may contribute to developing novel targeted therapy options for APOBEC-driven cancers.
Collapse
Affiliation(s)
- J Alberto Nakauma-González
- Cancer Computational Biology Center, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands; Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands; Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands.
| | - Maud Rijnders
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands
| | - Minouk T W Noordsij
- Cancer Computational Biology Center, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands
| | - John W M Martens
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands
| | - Astrid A M van der Veldt
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands; Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands
| | - Martijn P J Lolkema
- Department of Medical Oncology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands
| | - Joost L Boormans
- Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands
| | - Harmen J G van de Werken
- Cancer Computational Biology Center, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands; Department of Urology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands; Department of Immunology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, 3015 GD Rotterdam, the Netherlands.
| |
Collapse
|
54
|
Lin CJ, Jin X, Ma D, Chen C, Ou-Yang Y, Pei YC, Zhou CZ, Qu FL, Wang YJ, Liu CL, Fan L, Hu X, Shao ZM, Jiang YZ. Genetic interactions reveal distinct biological and therapeutic implications in breast cancer. Cancer Cell 2024; 42:701-719.e12. [PMID: 38593782 DOI: 10.1016/j.ccell.2024.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 01/16/2024] [Accepted: 03/13/2024] [Indexed: 04/11/2024]
Abstract
Co-occurrence and mutual exclusivity of genomic alterations may reflect the existence of genetic interactions, potentially shaping distinct biological phenotypes and impacting therapeutic response in breast cancer. However, our understanding of them remains limited. Herein, we investigate a large-scale multi-omics cohort (n = 873) and a real-world clinical sequencing cohort (n = 4,405) including several clinical trials with detailed treatment outcomes and perform functional validation in patient-derived organoids, tumor fragments, and in vivo models. Through this comprehensive approach, we construct a network comprising co-alterations and mutually exclusive events and characterize their therapeutic potential and underlying biological basis. Notably, we identify associations between TP53mut-AURKAamp and endocrine therapy resistance, germline BRCA1mut-MYCamp and improved sensitivity to PARP inhibitors, and TP53mut-MYBamp and immunotherapy resistance. Furthermore, we reveal that precision treatment strategies informed by co-alterations hold promise to improve patient outcomes. Our study highlights the significance of genetic interactions in guiding genome-informed treatment decisions beyond single driver alterations.
Collapse
Affiliation(s)
- Cai-Jin Lin
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Xi Jin
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Ding Ma
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Chao Chen
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Yang Ou-Yang
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Yu-Chen Pei
- Precision Cancer Medical Center, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Chao-Zheng Zhou
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Fei-Lin Qu
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Yun-Jin Wang
- Precision Cancer Medical Center, Fudan University Shanghai Cancer Center, Shanghai 200032, China
| | - Cheng-Lin Liu
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Lei Fan
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Xin Hu
- Precision Cancer Medical Center, Fudan University Shanghai Cancer Center, Shanghai 200032, China.
| | - Zhi-Ming Shao
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.
| | - Yi-Zhou Jiang
- Key Laboratory of Breast Cancer, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China.
| |
Collapse
|
55
|
Heid J, Cutler R, Sun S, Lee M, Maslov AY, Dong X, Sidoli S, Vijg J. Evidence for negative selection in human primary fibroblasts to tolerate high somatic mutation loads upon treatment with multiple low doses of N-ethyl-N-nitrosourea. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.07.588286. [PMID: 38617356 PMCID: PMC11014556 DOI: 10.1101/2024.04.07.588286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
High-throughput sequencing at the single-cell and single-molecule level has shown that mutation rate is much higher in somatic cells than in the germline, with thousands of mutations accumulating with age in most human tissues. While there is now ample evidence that some of these mutations can clonally amplify and lead to disease, most notably cancer, the total burden of mutations a cell can tolerate without functional decline remains unknown. Here we addressed this question by exposing human primary fibroblasts multiple times to low doses of N-ethyl-N-nitrosourea (ENU) and quantitatively analyzing somatic mutation burden using single-cell whole genome sequencing. The results indicate that individual cells can sustain ∼60,000 single-nucleotide variants (SNVs) with only a slight adverse effect on growth rate. We found evidence for selection against potentially deleterious variants in gene coding regions as well as depletion of mutations in sequences associated with genetic pathways expressed in these human fibroblasts, most notably those relevant for maintaining basic cellular function and growth. However, no evidence of negative selection was found for variants in non-coding regions. We conclude that actively proliferating fibroblasts can tolerate very high levels of somatic mutations without major adverse effects on growth rate via negative selection against damaging coding mutations. Since most tissues in adult organisms have very limited capacity to select against mutations based on a growth disadvantage, these results suggest that a causal effect of somatic mutations in aging and disease cannot be ruled out.
Collapse
|
56
|
Chatsirisupachai K, de Magalhães JP. Somatic mutations in human ageing: New insights from DNA sequencing and inherited mutations. Ageing Res Rev 2024; 96:102268. [PMID: 38490496 DOI: 10.1016/j.arr.2024.102268] [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: 08/23/2023] [Revised: 02/19/2024] [Accepted: 03/06/2024] [Indexed: 03/17/2024]
Abstract
The accumulation of somatic mutations is a driver of cancer and has long been associated with ageing. Due to limitations in quantifying mutation burden with age in non-cancerous tissues, the impact of somatic mutations in other ageing phenotypes is unclear. Recent advances in DNA sequencing technologies have allowed the large-scale quantification of somatic mutations in ageing tissues. These studies have revealed a gradual accumulation of mutations in normal tissues with age as well as a substantial clonal expansion driven mostly by cancer-related mutations. Nevertheless, it is difficult to envision how the burden and stochastic nature of age-related somatic mutations identified so far can explain most ageing phenotypes that develop gradually. Studies across species have also found that longer-lived species have lower somatic mutation rates, though these could be due to selective pressures acting on other phenotypes such as perhaps cancer. Recent studies in patients with higher somatic mutation burden and no signs of accelerated ageing further question the role of somatic mutations in ageing. Overall, with a few exceptions like cancer, recent DNA sequencing studies and inherited mutations do not support the idea that somatic mutations accumulating with age drive ageing phenotypes, and the phenotypic role, if any, of somatic mutations in ageing remains unclear.
Collapse
Affiliation(s)
- Kasit Chatsirisupachai
- Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L7 8TX, UK; European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - João Pedro de Magalhães
- Integrative Genomics of Ageing Group, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L7 8TX, UK; Institute of Inflammation and Ageing, University of Birmingham, Queen Elizabeth Hospital, Mindelsohn Way, Birmingham, UK.
| |
Collapse
|
57
|
Sud A, Parry EM, Wu CJ. The molecular map of CLL and Richter's syndrome. Semin Hematol 2024; 61:73-82. [PMID: 38368146 DOI: 10.1053/j.seminhematol.2024.01.009] [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: 10/31/2023] [Revised: 01/16/2024] [Accepted: 01/20/2024] [Indexed: 02/19/2024]
Abstract
Clonal expansion of B-cells, from the early stages of monoclonal B-cell lymphocytosis through to chronic lymphocytic leukemia (CLL), and then in some cases to Richter's syndrome (RS) provides a comprehensive model of cancer evolution, notable for the marked morphological transformation and distinct clinical phenotypes. High-throughput sequencing of large cohorts of patients and single-cell studies have generated a molecular map of CLL and more recently, of RS, yielding fundamental insights into these diseases and of clonal evolution. A selection of CLL driver genes have been functionally interrogated to yield novel insights into the biology of CLL. Such findings have the potential to impact patient care through risk stratification, treatment selection and drug discovery. However, this molecular map remains incomplete, with extant questions concerning the origin of the B-cell clone, the role of the TME, inter- and intra-compartmental heterogeneity and of therapeutic resistance mechanisms. Through the application of multi-modal single-cell technologies across tissues, disease states and clinical contexts, these questions can now be addressed with the answers holding great promise of generating translatable knowledge to improve patient care.
Collapse
Affiliation(s)
- Amit Sud
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA; Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA; Department of Immuno-Oncology, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
| | - Erin M Parry
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA; Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA.
| | - Catherine J Wu
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA; Harvard Medical School, Boston, MA; Broad Institute of MIT and Harvard, Cambridge, MA; Department of Medicine, Brigham and Women's Hospital, Boston, MA
| |
Collapse
|
58
|
White B, Swietach P. What can we learn about acid-base transporters in cancer from studying somatic mutations in their genes? Pflugers Arch 2024; 476:673-688. [PMID: 37999800 PMCID: PMC11006749 DOI: 10.1007/s00424-023-02876-y] [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: 09/25/2023] [Revised: 10/24/2023] [Accepted: 10/30/2023] [Indexed: 11/25/2023]
Abstract
Acidosis is a chemical signature of the tumour microenvironment that challenges intracellular pH homeostasis. The orchestrated activity of acid-base transporters of the solute-linked carrier (SLC) family is critical for removing the end-products of fermentative metabolism (lactate/H+) and maintaining a favourably alkaline cytoplasm. Given the critical role of pH homeostasis in enabling cellular activities, mutations in relevant SLC genes may impact the oncogenic process, emerging as negatively or positively selected, or as driver or passenger mutations. To address this, we performed a pan-cancer analysis of The Cancer Genome Atlas simple nucleotide variation data for acid/base-transporting SLCs (ABT-SLCs). Somatic mutation patterns of monocarboxylate transporters (MCTs) were consistent with their proposed essentiality in facilitating lactate/H+ efflux. Among all cancers, tumours of uterine corpus endometrial cancer carried more ABT-SLC somatic mutations than expected from median tumour mutation burden. Among these, somatic mutations in SLC4A3 had features consistent with meaningful consequences on cellular fitness. Definitive evidence for ABT-SLCs as 'cancer essential' or 'driver genes' will have to consider microenvironmental context in genomic sequencing because bulk approaches are insensitive to pH heterogeneity within tumours. Moreover, genomic analyses must be validated with phenotypic outcomes (i.e. SLC-carried flux) to appreciate the opportunities for targeting acid-base transport in cancers.
Collapse
Affiliation(s)
- Bobby White
- Department of Physiology, Anatomy and Genetics, University of Oxford, Parks Road, Oxford, OX1 3PT, UK.
| | - Pawel Swietach
- Department of Physiology, Anatomy and Genetics, University of Oxford, Parks Road, Oxford, OX1 3PT, UK
| |
Collapse
|
59
|
Xu R, Chen R, Tu C, Gong X, Liu Z, Mei L, Ren X, Li Z. 3D Models of Sarcomas: The Next-generation Tool for Personalized Medicine. PHENOMICS (CHAM, SWITZERLAND) 2024; 4:171-186. [PMID: 38884054 PMCID: PMC11169319 DOI: 10.1007/s43657-023-00111-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 05/16/2023] [Accepted: 05/23/2023] [Indexed: 06/18/2024]
Abstract
Sarcoma is a complex and heterogeneous cancer that has been difficult to study in vitro. While two-dimensional (2D) cell cultures and mouse models have been the dominant research tools, three-dimensional (3D) culture systems such as organoids have emerged as promising alternatives. In this review, we discuss recent developments in sarcoma organoid culture, with a focus on their potential as tools for drug screening and biobanking. We also highlight the ways in which sarcoma organoids have been used to investigate the mechanisms of gene regulation, drug resistance, metastasis, and immune interactions. Sarcoma organoids have shown to retain characteristics of in vivo biology within an in vitro system, making them a more representative model for sarcoma research. Our review suggests that sarcoma organoids offer a potential path forward for translational research in this field and may provide a platform for developing personalized therapies for sarcoma patients.
Collapse
Affiliation(s)
- Ruiling Xu
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| | - Ruiqi Chen
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| | - Chao Tu
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| | - Xiaofeng Gong
- College of Life Science, Fudan University, Shanghai, 200433 China
| | - Zhongyue Liu
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| | - Lin Mei
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| | - Xiaolei Ren
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| | - Zhihong Li
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, No. 139 Renmin Road, Changsha, 410011 Hunan China
- Hunan Key Laboratory of Tumor Models and Individualized Medicine, No. 139 Renmin Road, Changsha, 410011 Hunan China
| |
Collapse
|
60
|
Klim J, Zielenkiewicz U, Kaczanowski S. Loss-of-function mutations are main drivers of adaptations during short-term evolution. Sci Rep 2024; 14:7128. [PMID: 38532077 DOI: 10.1038/s41598-024-57694-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 03/20/2024] [Indexed: 03/28/2024] Open
Abstract
We noticed that during short-term experimental evolution and carcinogenesis, mutations causing gene inactivation (i.e., nonsense mutations or frameshifts) are frequent. Our meta-analysis of 65 experiments using modified dN/dS statistics indicated that nonsense mutations are adaptive in different experimental conditions and we empirically confirmed this prediction. Using yeast S. cerevisiae as a model we show that fixed or highly frequent gene loss-of-function mutations are almost exclusively adaptive in the majority of experiments.
Collapse
Affiliation(s)
- Joanna Klim
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Pawinskiego 5a, 02-106, Warsaw, Poland
| | - Urszula Zielenkiewicz
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Pawinskiego 5a, 02-106, Warsaw, Poland
| | - Szymon Kaczanowski
- Institute of Biochemistry and Biophysics, Polish Academy of Sciences, Pawinskiego 5a, 02-106, Warsaw, Poland.
| |
Collapse
|
61
|
Holguin-Cruz JA, Bui JM, Jha A, Na D, Gsponer J. Widespread alteration of protein autoinhibition in human cancers. Cell Syst 2024; 15:246-263.e7. [PMID: 38366601 DOI: 10.1016/j.cels.2024.01.009] [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: 01/31/2019] [Revised: 06/20/2023] [Accepted: 01/26/2024] [Indexed: 02/18/2024]
Abstract
Autoinhibition is a prevalent allosteric regulatory mechanism in signaling proteins. Reduced autoinhibition underlies the tumorigenic effect of some known cancer drivers, but whether autoinhibition is altered generally in cancer remains elusive. Here, we demonstrate that cancer-associated missense mutations, in-frame insertions/deletions, and fusion breakpoints are enriched within inhibitory allosteric switches (IASs) across all cancer types. Selection for IASs that are recurrently mutated in cancers identifies established and unknown cancer drivers. Recurrent missense mutations in IASs of these drivers are associated with distinct, cancer-specific changes in molecular signaling. For the specific case of PPP3CA, the catalytic subunit of calcineurin, we provide insights into the molecular mechanisms of altered autoinhibition by cancer mutations using biomolecular simulations, and demonstrate that such mutations are associated with transcriptome changes consistent with increased calcineurin signaling. Our integrative study shows that autoinhibition-modulating genetic alterations are positively selected for by cancer cells.
Collapse
Affiliation(s)
- Jorge A Holguin-Cruz
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Jennifer M Bui
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Ashwani Jha
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Dokyun Na
- School of Integrative Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 156-756, Republic of Korea
| | - Jörg Gsponer
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
| |
Collapse
|
62
|
Schupp PG, Shelton SJ, Brody DJ, Eliscu R, Johnson BE, Mazor T, Kelley KW, Potts MB, McDermott MW, Huang EJ, Lim DA, Pieper RO, Berger MS, Costello JF, Phillips JJ, Oldham MC. Deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial sections. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.06.21.545365. [PMID: 37645893 PMCID: PMC10461981 DOI: 10.1101/2023.06.21.545365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Tumors may contain billions of cells including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA). By combining deep sampling of IDH-mutant astrocytomas with integrative analysis of single-nucleotide variants, copy-number variants, and gene expression, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones. By genotyping nuclei analyzed by single-nucleus RNA-seq for truncal mutations, we further show that commonly used algorithms for identifying cancer cells from single-cell transcriptomes may be inaccurate. We also demonstrate that correlating gene expression with tumor purity in bulk samples can reveal optimal markers of malignant cells and use this approach to identify a core set of genes that is consistently expressed by astrocytoma truncal clones, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. In summary, MOMA provides a robust and flexible strategy for precisely deconstructing intratumoral heterogeneity and clarifying the core molecular properties of distinct cellular populations in solid tumors.
Collapse
Affiliation(s)
- Patrick G. Schupp
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
- Biomedical Sciences Graduate Program, University of California San Francisco, San Francisco, California, USA
| | - Samuel J. Shelton
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
| | - Daniel J. Brody
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
| | - Rebecca Eliscu
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
| | - Brett E. Johnson
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
| | - Tali Mazor
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
- Biomedical Sciences Graduate Program, University of California San Francisco, San Francisco, California, USA
- Medical Scientist Training Program and Neuroscience Graduate Program, University of California San Francisco, San Francisco, California, USA
| | - Kevin W. Kelley
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
- Medical Scientist Training Program and Neuroscience Graduate Program, University of California San Francisco, San Francisco, California, USA
- Neuroscience Graduate Program, University of California San Francisco, San Francisco, California, USA
| | - Matthew B. Potts
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
| | - Michael W. McDermott
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
| | - Eric J. Huang
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
| | - Daniel A. Lim
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
| | - Russell O. Pieper
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
| | - Mitchel S. Berger
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
| | - Joseph F. Costello
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
| | - Joanna J. Phillips
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
- Department of Pathology, University of California, San Francisco, San Francisco, California, USA
| | - Michael C. Oldham
- Department of Neurological Surgery, University of California, San Francisco, San Francisco,California, USA
| |
Collapse
|
63
|
Srivatsa A, Schwartz R. Optimizing Design of Genomics Studies for Clonal Evolution Analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.14.585055. [PMID: 38559253 PMCID: PMC10980045 DOI: 10.1101/2024.03.14.585055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Genomic biotechnologies have seen rapid development over the past two decades, allowing for both the inference and modification of genetic and epigenetic information at the single cell level. While these tools present enormous potential for basic research, diagnostics, and treatment, they also raise difficult issues of how to design research studies to deploy these tools most effectively. In designing a study at the population or individual level, a researcher might combine several different sequencing modalities and sampling protocols, each with different utility, costs, and other tradeoffs. The central problem this paper attempts to address is then how one might create an optimal study design for a genomic analysis, with particular focus on studies involving somatic variation, typically for applications in cancer genomics. We pose the study design problem as a stochastic constrained nonlinear optimization problem and introduce a simulation-centered optimization procedure that iteratively optimizes the objective function using surrogate modeling combined with pattern and gradient search. Finally, we demonstrate the use of our procedure on diverse test cases to derive resource and study design allocations optimized for various objectives for the study of somatic cell populations.
Collapse
Affiliation(s)
- Arjun Srivatsa
- Ray and Stephanie Lane Computational Biology Department, Carnegie Mellon University, Pittsburgh PA 15213, USA
| | - Russell Schwartz
- Ray and Stephanie Lane Computational Biology Department, Carnegie Mellon University, Pittsburgh PA 15213, USA
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh PA 15213, USA
| |
Collapse
|
64
|
Wang S, Zhang M, Sun H, Li T, Hao J, Fang M, Dong J, Xu H. Multi-omics analysis of TLCD1 as a promising biomarker in pan-cancer. Front Cell Dev Biol 2024; 11:1305906. [PMID: 38559424 PMCID: PMC10978584 DOI: 10.3389/fcell.2023.1305906] [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: 10/06/2023] [Accepted: 12/31/2023] [Indexed: 04/04/2024] Open
Abstract
Background: The TLC Domain Containing 1 (TLCD1) protein, a key regulator of phosphatidylethanolamine (PE) composition, is distributed across several cellular membranes, including mitochondrial plasma membranes. Existing research has revealed the impact of TLCD1 on the development of non-alcoholic fatty liver disease. However, there remains a gap in comprehensive pan-cancer analyses of TLCD1, and the precise role of TLCD1 in cancer patient prognosis and immunological responses remains elusive. This study aims to provide a comprehensive visualization of the prognostic landscape associated with TLCD1 across a spectrum of cancers, while shedding light on the potential links between TLCD1 expression within the tumor microenvironment and immune infiltration characteristics. Methods: TLCD1 expression data were obtained from GTEx, TCGA, and HPA data repositories. Multiple databases including TIMER, HPA, TISIDB, cBioPortal, GEPIA2, STRING, KEGG, GO, and CancerSEA were used to investigate the expression pattern, diagnostic and prognostic significance, mutation status, functional analysis, and functional status of TLCD1. In addition, we evaluated the relationship between TLCD1 expression and immune infiltration, tumor mutational burden (TMB), microsatellite instability (MSI), and immune-related genes in pan-cancer. Furthermore, the association of TLCD1 with drug sensitivity was analyzed using the CellMiner database. Results: We found that TLCD1 is generally highly expressed in pan-cancers and is significantly associated with the staging and prognosis of various cancers. Furthermore, our results also showed that TLCD1 was significantly associated with immune cell infiltration and immune regulatory factor expression. Using CellMiner database analysis, we then found a strong correlation between TLCD1 expression and sensitivity to anticancer drugs, indicating its potential as a therapeutic target. The most exciting finding is that high TLCD1 expression is associated with worse survival and prognosis in GBM and SKCM patients receiving anti-PD1 therapy. These findings highlight the potential of TLCD1 as a predictive biomarker for response to immunotherapy. Conclusion: TLCD1 plays a role in the regulation of immune infiltration and affects the prognosis of patients with various cancers. It serves as both a prognostic and immunologic biomarker in human cancer.
Collapse
Affiliation(s)
- Shengli Wang
- Zhuhai Institute of Translational Medicine, Zhuhai People’s Hospital Affiliated With Jinan University, Jinan University, Zhuhai, Guangdong, China
- The Biomedical Translational Research Institute, Faculty of Medical Science, Jinan University, Guangzhou, Guangdong, China
| | - Mingyue Zhang
- Zhuhai Institute of Translational Medicine, Zhuhai People’s Hospital Affiliated With Jinan University, Jinan University, Zhuhai, Guangdong, China
- The Biomedical Translational Research Institute, Faculty of Medical Science, Jinan University, Guangzhou, Guangdong, China
| | - Hongyan Sun
- Zhuhai Institute of Translational Medicine, Zhuhai People’s Hospital Affiliated With Jinan University, Jinan University, Zhuhai, Guangdong, China
- The Biomedical Translational Research Institute, Faculty of Medical Science, Jinan University, Guangzhou, Guangdong, China
| | - Tao Li
- Zhuhai Institute of Translational Medicine, Zhuhai People’s Hospital Affiliated With Jinan University, Jinan University, Zhuhai, Guangdong, China
- The Biomedical Translational Research Institute, Faculty of Medical Science, Jinan University, Guangzhou, Guangdong, China
| | - Jianlei Hao
- Zhuhai Institute of Translational Medicine, Zhuhai People’s Hospital Affiliated With Jinan University, Jinan University, Zhuhai, Guangdong, China
- The Biomedical Translational Research Institute, Faculty of Medical Science, Jinan University, Guangzhou, Guangdong, China
| | - Meixia Fang
- Department of Laboratory Animal, Institute of Laboratory Animal Science, Jinan University, Guangzhou, Guangdong, China
| | - Jie Dong
- Department of Clinical Laboratory, Guangzhou Twelfth People’s Hospital, Guangzhou, Guangdong, China
| | - Hongbiao Xu
- Department of Thyroid and Breast Surgery, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
| |
Collapse
|
65
|
Cai H, Zhang B, Ahrenfeldt J, Joseph JV, Riedel M, Gao Z, Thomsen SK, Christensen DS, Bak RO, Hager H, Vendelbo MH, Gao X, Birkbak N, Thomsen MK. CRISPR/Cas9 model of prostate cancer identifies Kmt2c deficiency as a metastatic driver by Odam/Cabs1 gene cluster expression. Nat Commun 2024; 15:2088. [PMID: 38453924 PMCID: PMC10920892 DOI: 10.1038/s41467-024-46370-0] [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: 06/02/2023] [Accepted: 02/20/2024] [Indexed: 03/09/2024] Open
Abstract
Metastatic prostate cancer (PCa) poses a significant therapeutic challenge with high mortality rates. Utilizing CRISPR-Cas9 in vivo, we target five potential tumor suppressor genes (Pten, Trp53, Rb1, Stk11, and RnaseL) in the mouse prostate, reaching humane endpoint after eight weeks without metastasis. By further depleting three epigenetic factors (Kmt2c, Kmt2d, and Zbtb16), lung metastases are present in all mice. While whole genome sequencing reveals few mutations in coding sequence, RNA sequencing shows significant dysregulation, especially in a conserved genomic region at chr5qE1 regulated by KMT2C. Depleting Odam and Cabs1 in this region prevents metastasis. Notably, the gene expression signatures, resulting from our study, predict progression-free and overall survival and distinguish primary and metastatic human prostate cancer. This study emphasizes positive genetic interactions between classical tumor suppressor genes and epigenetic modulators in metastatic PCa progression, offering insights into potential treatments.
Collapse
Affiliation(s)
- Huiqiang Cai
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Bin Zhang
- Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Johanne Ahrenfeldt
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Justin V Joseph
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Maria Riedel
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Zongliang Gao
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Sofie K Thomsen
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Ditte S Christensen
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Rasmus O Bak
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Henrik Hager
- Department of Pathology, Aarhus University Hospital, Aarhus, Denmark
| | - Mikkel H Vendelbo
- Department of Nuclear Medicine & PET Centre, Aarhus University Hospital, Aarhus, Denmark
| | - Xin Gao
- Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
- Computer Science Program, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Nicolai Birkbak
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Martin K Thomsen
- Department of Biomedicine, Aarhus University, Aarhus, Denmark.
- Aarhus Institute of Advanced Studies (AIAS), Aarhus University, Aarhus, Denmark.
| |
Collapse
|
66
|
Xu X, Qi Z, Wang L, Zhang M, Geng Z, Han X. Gsw-fi: a GLM model incorporating shrinkage and double-weighted strategies for identifying cancer driver genes with functional impact. BMC Bioinformatics 2024; 25:99. [PMID: 38448819 PMCID: PMC10916024 DOI: 10.1186/s12859-024-05707-8] [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: 12/15/2022] [Accepted: 02/16/2024] [Indexed: 03/08/2024] Open
Abstract
BACKGROUND Cancer, a disease with high morbidity and mortality rates, poses a significant threat to human health. Driver genes, which harbor mutations accountable for the initiation and progression of tumors, play a crucial role in cancer development. Identifying driver genes stands as a paramount objective in cancer research and precision medicine. RESULTS In the present work, we propose a method for identifying driver genes using a Generalized Linear Regression Model (GLM) with Shrinkage and double-Weighted strategies based on Functional Impact, which is named GSW-FI. Firstly, an estimating model is proposed for assessing the background functional impacts of genes based on GLM, utilizing gene features as predictors. Secondly, the shrinkage and double-weighted strategies as two revising approaches are integrated to ensure the rationality of the identified driver genes. Lastly, a statistical method of hypothesis testing is designed to identify driver genes by leveraging the estimated background function impacts. Experimental results conducted on 31 The Cancer Genome Altas datasets demonstrate that GSW-FI outperforms ten other prediction methods in terms of the overlap fraction with well-known databases and consensus predictions among different methods. CONCLUSIONS GSW-FI presents a novel approach that efficiently identifies driver genes with functional impact mutations using computational methods, thereby advancing the development of precision medicine for cancer.
Collapse
Affiliation(s)
- Xiaolu Xu
- School of Computer and Artificial Intelligence, Liaoning Normal University, Dalian, China
| | - Zitong Qi
- Department of Statistics, University of Washington, Seattle, USA
| | - Lei Wang
- Center for Reproductive and Genetic Medicine, Dalian Women and Children's Medical Group, Dalian, China.
| | - Meiwei Zhang
- Center for Reproductive and Genetic Medicine, Dalian Women and Children's Medical Group, Dalian, China.
| | - Zhaohong Geng
- Department of Cardiology, Second Affiliated Hospital of Dalian Medical University, Dalian, China
| | - Xiumei Han
- College of Artificial Intelligence, Dalian Maritime University, Dalian, China
| |
Collapse
|
67
|
Kapadia CD, Goodell MA. Tissue mosaicism following stem cell aging: blood as an exemplar. NATURE AGING 2024; 4:295-308. [PMID: 38438628 DOI: 10.1038/s43587-024-00589-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 02/07/2024] [Indexed: 03/06/2024]
Abstract
Loss of stem cell regenerative potential underlies aging of all tissues. Somatic mosaicism, the emergence of cellular patchworks within tissues, increases with age and has been observed in every organ yet examined. In the hematopoietic system, as in most tissues, stem cell aging through a variety of mechanisms occurs in lockstep with the emergence of somatic mosaicism. Here, we draw on insights from aging hematopoiesis to illustrate fundamental principles of stem cell aging and somatic mosaicism. We describe the generalizable changes intrinsic to aged stem cells and their milieu that provide the backdrop for somatic mosaicism to emerge. We discuss genetic and nongenetic mechanisms that can result in tissue somatic mosaicism and existing methodologies to detect such clonal outgrowths. Finally, we propose potential avenues to modify mosaicism during aging, with the ultimate aim of increasing tissue resiliency.
Collapse
Affiliation(s)
- Chiraag D Kapadia
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA
- Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, TX, USA
| | - Margaret A Goodell
- Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, USA.
- Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, TX, USA.
| |
Collapse
|
68
|
Chen L, Zhang C, Xue R, Liu M, Bai J, Bao J, Wang Y, Jiang N, Li Z, Wang W, Wang R, Zheng B, Yang A, Hu J, Liu K, Shen S, Zhang Y, Bai M, Wang Y, Zhu Y, Yang S, Gao Q, Gu J, Gao D, Wang XW, Nakagawa H, Zhang N, Wu L, Rozen SG, Bai F, Wang H. Deep whole-genome analysis of 494 hepatocellular carcinomas. Nature 2024; 627:586-593. [PMID: 38355797 DOI: 10.1038/s41586-024-07054-3] [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: 06/13/2022] [Accepted: 01/10/2024] [Indexed: 02/16/2024]
Abstract
Over half of hepatocellular carcinoma (HCC) cases diagnosed worldwide are in China1-3. However, whole-genome analysis of hepatitis B virus (HBV)-associated HCC in Chinese individuals is limited4-8, with current analyses of HCC mainly from non-HBV-enriched populations9,10. Here we initiated the Chinese Liver Cancer Atlas (CLCA) project and performed deep whole-genome sequencing (average depth, 120×) of 494 HCC tumours. We identified 6 coding and 28 non-coding previously undescribed driver candidates. Five previously undescribed mutational signatures were found, including aristolochic-acid-associated indel and doublet base signatures, and a single-base-substitution signature that we termed SBS_H8. Pentanucleotide context analysis and experimental validation confirmed that SBS_H8 was distinct to the aristolochic-acid-associated SBS22. Notably, HBV integrations could take the form of extrachromosomal circular DNA, resulting in elevated copy numbers and gene expression. Our high-depth data also enabled us to characterize subclonal clustered alterations, including chromothripsis, chromoplexy and kataegis, suggesting that these catastrophic events could also occur in late stages of hepatocarcinogenesis. Pathway analysis of all classes of alterations further linked non-coding mutations to dysregulation of liver metabolism. Finally, we performed in vitro and in vivo assays to show that fibrinogen alpha chain (FGA), determined as both a candidate coding and non-coding driver, regulates HCC progression and metastasis. Our CLCA study depicts a detailed genomic landscape and evolutionary history of HCC in Chinese individuals, providing important clinical implications.
Collapse
Affiliation(s)
- Lei Chen
- National Center for Liver Cancer/Eastern Hepatobiliary Surgery Hospital, Shanghai, China.
| | - Chong Zhang
- Biomedical Pioneering Innovation Center (BIOPIC), Beijing Advanced Innovation Center for Genomics (ICG), School of Life Sciences, Peking University, Beijing, China
| | - Ruidong Xue
- Peking University-Yunnan Baiyao International Medical Research Center, International Cancer Institute, Department of Medical Bioinformatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China
- Translational Cancer Research Center, Peking University First Hospital, Beijing, China
| | - Mo Liu
- Centre for Computational Biology and Programme in Cancer & Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore
| | - Jian Bai
- Berry Oncology Corporation, Beijing, China
| | - Jinxia Bao
- Model Animal Research Center, Medical School, Nanjing University, Nanjing, China
| | - Yin Wang
- Berry Oncology Corporation, Beijing, China
| | - Nanhai Jiang
- Centre for Computational Biology and Programme in Cancer & Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore
| | - Zhixuan Li
- National Center for Liver Cancer/Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | - Wenwen Wang
- The International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | - Ruiru Wang
- Berry Oncology Corporation, Beijing, China
| | - Bo Zheng
- National Center for Liver Cancer/Eastern Hepatobiliary Surgery Hospital, Shanghai, China
- The International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | | | - Ji Hu
- National Center for Liver Cancer/Eastern Hepatobiliary Surgery Hospital, Shanghai, China
- The International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | - Ke Liu
- Berry Oncology Corporation, Beijing, China
| | - Siyun Shen
- National Center for Liver Cancer/Eastern Hepatobiliary Surgery Hospital, Shanghai, China
- The International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | - Yangqianwen Zhang
- National Center for Liver Cancer/Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | - Mixue Bai
- National Center for Liver Cancer/Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | - Yan Wang
- Berry Oncology Corporation, Beijing, China
| | - Yanjing Zhu
- National Center for Liver Cancer/Eastern Hepatobiliary Surgery Hospital, Shanghai, China
- The International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | - Shuai Yang
- National Center for Liver Cancer/Eastern Hepatobiliary Surgery Hospital, Shanghai, China
- The International Cooperation Laboratory on Signal Transduction, Eastern Hepatobiliary Surgery Hospital, Shanghai, China
| | - Qiang Gao
- Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jin Gu
- MOE Key Laboratory for Bioinformatics, Department of Automation, Tsinghua University, Beijing, China
| | - Dong Gao
- State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, CAS, Shanghai, China
| | - Xin Wei Wang
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Hidewaki Nakagawa
- Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Ning Zhang
- Peking University-Yunnan Baiyao International Medical Research Center, International Cancer Institute, Department of Medical Bioinformatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China
- Translational Cancer Research Center, Peking University First Hospital, Beijing, China
| | - Lin Wu
- Berry Oncology Corporation, Beijing, China.
| | - Steven G Rozen
- Centre for Computational Biology and Programme in Cancer & Stem Cell Biology, Duke-NUS Medical School, Singapore, Singapore.
| | - Fan Bai
- Biomedical Pioneering Innovation Center (BIOPIC), Beijing Advanced Innovation Center for Genomics (ICG), School of Life Sciences, Peking University, Beijing, China.
| | - Hongyang Wang
- National Center for Liver Cancer/Eastern Hepatobiliary Surgery Hospital, Shanghai, China.
| |
Collapse
|
69
|
Desai S, Ahmad S, Bawaskar B, Rashmi S, Mishra R, Lakhwani D, Dutt A. Singleton mutations in large-scale cancer genome studies: uncovering the tail of cancer genome. NAR Cancer 2024; 6:zcae010. [PMID: 38487301 PMCID: PMC10939354 DOI: 10.1093/narcan/zcae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Accepted: 02/23/2024] [Indexed: 03/17/2024] Open
Abstract
Singleton or low-frequency driver mutations are challenging to identify. We present a domain driver mutation estimator (DOME) to identify rare candidate driver mutations. DOME analyzes positions analogous to known statistical hotspots and resistant mutations in combination with their functional and biochemical residue context as determined by protein structures and somatic mutation propensity within conserved PFAM domains, integrating the CADD scoring scheme. Benchmarked against seven other tools, DOME exhibited superior or comparable accuracy compared to all evaluated tools in the prediction of functional cancer drivers, with the exception of one tool. DOME identified a unique set of 32 917 high-confidence predicted driver mutations from the analysis of whole proteome missense variants within domain boundaries across 1331 genes, including 1192 noncancer gene census genes, emphasizing its unique place in cancer genome analysis. Additionally, analysis of 8799 TCGA (The Cancer Genome Atlas) and in-house tumor samples revealed 847 potential driver mutations, with mutations in tyrosine kinase members forming the dominant burden, underscoring its higher significance in cancer. Overall, DOME complements current approaches for identifying novel, low-frequency drivers and resistant mutations in personalized therapy.
Collapse
Affiliation(s)
- Sanket Desai
- Integrated Cancer Genomics Laboratory, Advanced Centre for Treatment, Research, and Education in Cancer, Kharghar, Navi Mumbai 410210, Maharashtra, India
- Homi Bhabha National Institute, Training School Complex, Anushakti Nagar, Mumbai 400094, Maharashtra, India
| | - Suhail Ahmad
- Integrated Cancer Genomics Laboratory, Advanced Centre for Treatment, Research, and Education in Cancer, Kharghar, Navi Mumbai 410210, Maharashtra, India
- Homi Bhabha National Institute, Training School Complex, Anushakti Nagar, Mumbai 400094, Maharashtra, India
| | - Bhargavi Bawaskar
- Integrated Cancer Genomics Laboratory, Advanced Centre for Treatment, Research, and Education in Cancer, Kharghar, Navi Mumbai 410210, Maharashtra, India
| | - Sonal Rashmi
- Integrated Cancer Genomics Laboratory, Advanced Centre for Treatment, Research, and Education in Cancer, Kharghar, Navi Mumbai 410210, Maharashtra, India
| | - Rohit Mishra
- Integrated Cancer Genomics Laboratory, Advanced Centre for Treatment, Research, and Education in Cancer, Kharghar, Navi Mumbai 410210, Maharashtra, India
| | - Deepika Lakhwani
- Integrated Cancer Genomics Laboratory, Advanced Centre for Treatment, Research, and Education in Cancer, Kharghar, Navi Mumbai 410210, Maharashtra, India
| | - Amit Dutt
- Integrated Cancer Genomics Laboratory, Advanced Centre for Treatment, Research, and Education in Cancer, Kharghar, Navi Mumbai 410210, Maharashtra, India
- Homi Bhabha National Institute, Training School Complex, Anushakti Nagar, Mumbai 400094, Maharashtra, India
- Department of Genetics, University of Delhi, South Campus, New Delhi 110021, India
| |
Collapse
|
70
|
George J, Maas L, Abedpour N, Cartolano M, Kaiser L, Fischer RN, Scheel AH, Weber JP, Hellmich M, Bosco G, Volz C, Mueller C, Dahmen I, John F, Alves CP, Werr L, Panse JP, Kirschner M, Engel-Riedel W, Jürgens J, Stoelben E, Brockmann M, Grau S, Sebastian M, Stratmann JA, Kern J, Hummel HD, Hegedüs B, Schuler M, Plönes T, Aigner C, Elter T, Toepelt K, Ko YD, Kurz S, Grohé C, Serke M, Höpker K, Hagmeyer L, Doerr F, Hekmath K, Strapatsas J, Kambartel KO, Chakupurakal G, Busch A, Bauernfeind FG, Griesinger F, Luers A, Dirks W, Wiewrodt R, Luecke A, Rodermann E, Diel A, Hagen V, Severin K, Ullrich RT, Reinhardt HC, Quaas A, Bogus M, Courts C, Nürnberg P, Becker K, Achter V, Büttner R, Wolf J, Peifer M, Thomas RK. Evolutionary trajectories of small cell lung cancer under therapy. Nature 2024; 627:880-889. [PMID: 38480884 PMCID: PMC10972747 DOI: 10.1038/s41586-024-07177-7] [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: 01/25/2023] [Accepted: 02/07/2024] [Indexed: 03/18/2024]
Abstract
The evolutionary processes that underlie the marked sensitivity of small cell lung cancer (SCLC) to chemotherapy and rapid relapse are unknown1-3. Here we determined tumour phylogenies at diagnosis and throughout chemotherapy and immunotherapy by multiregion sequencing of 160 tumours from 65 patients. Treatment-naive SCLC exhibited clonal homogeneity at distinct tumour sites, whereas first-line platinum-based chemotherapy led to a burst in genomic intratumour heterogeneity and spatial clonal diversity. We observed branched evolution and a shift to ancestral clones underlying tumour relapse. Effective radio- or immunotherapy induced a re-expansion of founder clones with acquired genomic damage from first-line chemotherapy. Whereas TP53 and RB1 alterations were exclusively part of the common ancestor, MYC family amplifications were frequently not constituents of the founder clone. At relapse, emerging subclonal mutations affected key genes associated with SCLC biology, and tumours harbouring clonal CREBBP/EP300 alterations underwent genome duplications. Gene-damaging TP53 alterations and co-alterations of TP53 missense mutations with TP73, CREBBP/EP300 or FMN2 were significantly associated with shorter disease relapse following chemotherapy. In summary, we uncover key processes of the genomic evolution of SCLC under therapy, identify the common ancestor as the source of clonal diversity at relapse and show central genomic patterns associated with sensitivity and resistance to chemotherapy.
Collapse
Affiliation(s)
- Julie George
- Department of Translational Genomics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
- Department of Otorhinolaryngology, Head and Neck Surgery, Faculty of Medicine and University Hospital Cologne, University Hospital of Cologne, Cologne, Germany.
| | - Lukas Maas
- Department of Translational Genomics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Nima Abedpour
- Department of Translational Genomics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Department I of Internal Medicine, Centre for Integrated Oncology Aachen Bonn Cologne Duesseldorf, University Hospital Cologne, Cologne, Germany
- Cancer Research Centre Cologne Essen, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Maria Cartolano
- Department of Translational Genomics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Centre for Molecular Medicine, University of Cologne, Cologne, Germany
| | - Laura Kaiser
- Department of Translational Genomics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Rieke N Fischer
- Department I of Internal Medicine, Lung Cancer Group Cologne, University Hospital Cologne, Cologne, Germany
| | - Andreas H Scheel
- Institute of Pathology, Medical Faculty, University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Jan-Philipp Weber
- Department I of Internal Medicine, Lung Cancer Group Cologne, University Hospital Cologne, Cologne, Germany
| | - Martin Hellmich
- Institute of Medical Statistics, and Computational Biology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Graziella Bosco
- Department of Translational Genomics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Caroline Volz
- Department I of Internal Medicine, Centre for Integrated Oncology Aachen Bonn Cologne Duesseldorf, University Hospital Cologne, Cologne, Germany
- Centre for Molecular Medicine, University of Cologne, Cologne, Germany
| | - Christian Mueller
- Department of Translational Genomics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Department of Otorhinolaryngology, Head and Neck Surgery, Faculty of Medicine and University Hospital Cologne, University Hospital of Cologne, Cologne, Germany
| | - Ilona Dahmen
- Department of Translational Genomics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Felix John
- Department I of Internal Medicine, Lung Cancer Group Cologne, University Hospital Cologne, Cologne, Germany
| | - Cleidson Padua Alves
- Department of Translational Genomics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Lisa Werr
- Department of Translational Genomics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Jens Peter Panse
- Department of Haematology, Oncology, Haemostaseology and Stem Cell Transplantation, University Hospital RWTH Aachen, Aachen, Germany
- Centre for Integrated Oncology, Aachen Bonn Cologne Düsseldorf, Aachen, Germany
| | - Martin Kirschner
- Department of Haematology, Oncology, Haemostaseology and Stem Cell Transplantation, University Hospital RWTH Aachen, Aachen, Germany
- Centre for Integrated Oncology, Aachen Bonn Cologne Düsseldorf, Aachen, Germany
| | - Walburga Engel-Riedel
- Department of Pneumology, City of Cologne Municipal Hospitals, Lung Hospital Cologne Merheim, Cologne, Germany
| | - Jessica Jürgens
- Department of Pneumology, City of Cologne Municipal Hospitals, Lung Hospital Cologne Merheim, Cologne, Germany
| | - Erich Stoelben
- Thoraxclinic Cologne, Thoracic Surgery, St. Hildegardis-Krankenhaus, Cologne, Germany
| | - Michael Brockmann
- Department of Pathology, City of Cologne Municipal Hospitals, Witten/Herdecke University, Cologne, Germany
| | - Stefan Grau
- Department of General Neurosurgery, Centre of Neurosurgery, University Hospital Cologne, Cologne, Germany
- University Medicine Marburg - Campus Fulda, Department of Neurosurgery, Fulda, Germany
| | - Martin Sebastian
- Department of Medicine II, Haematology/Oncology, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
- Frankfurt Cancer Institute, Goethe University Frankfurt, Frankfurt, Germany
- DKFZ, German Cancer Research Centre, German Cancer Consortium, Heidelberg, Germany
| | - Jan A Stratmann
- Department of Medicine II, Haematology/Oncology, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
- Frankfurt Cancer Institute, Goethe University Frankfurt, Frankfurt, Germany
| | - Jens Kern
- Klinikum Würzburg Mitte - Missioklinik site, Pneumology and Respiratory Medicine, Würzburg, Germany
| | - Horst-Dieter Hummel
- Translational Oncology/Early Clinical Trial Unit, Comprehensive Cancer Centre Mainfranken, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Balazs Hegedüs
- Department of Thoracic Surgery, University Medicine Essen - Ruhrlandklinik, University Duisburg-Essen, Essen, Germany
| | - Martin Schuler
- DKFZ, German Cancer Research Centre, German Cancer Consortium, Heidelberg, Germany
- Department of Medical Oncology, West German Cancer Centre Essen, University Duisburg-Essen, Essen, Germany
| | - Till Plönes
- Department of Medical Oncology, West German Cancer Centre Essen, University Duisburg-Essen, Essen, Germany
- Division of Thoracic Surgery, Department of General, Thoracic and Vascular Surgery, University Hospital Carl Gustav Carus, Dresden, Germany
| | - Clemens Aigner
- Department of Thoracic Surgery, University Medicine Essen - Ruhrlandklinik, University Duisburg-Essen, Essen, Germany
- Department of Thoracic Surgery, Medical University of Vienna, Vienna General Hospital, Vienna, Austria
| | - Thomas Elter
- Department I of Internal Medicine, Centre for Integrated Oncology Aachen Bonn Cologne Duesseldorf, University Hospital Cologne, Cologne, Germany
| | - Karin Toepelt
- Department I of Internal Medicine, Centre for Integrated Oncology Aachen Bonn Cologne Duesseldorf, University Hospital Cologne, Cologne, Germany
| | | | - Sylke Kurz
- Department of Respiratory Diseases, Evangelische Lungenklinik, Berlin, Germany
| | - Christian Grohé
- Department of Respiratory Diseases, Evangelische Lungenklinik, Berlin, Germany
| | - Monika Serke
- DGD Lungenklinik Hemer, Internal Medicine, Pneumology and Oncology, Hemer, Germany
| | - Katja Höpker
- Clinic III for Internal Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Lars Hagmeyer
- Clinic of Pneumology and Allergology, Centre for Sleep Medicine and Respiratory Care, Bethanien Hospital Solingen, Solingen, Germany
| | - Fabian Doerr
- Department of Thoracic Surgery, University Medicine Essen - Ruhrlandklinik, University Duisburg-Essen, Essen, Germany
- Department of Cardiothoracic Surgery, University Hospital of Cologne, Cologne, Germany
| | - Khosro Hekmath
- Department of Cardiothoracic Surgery, University Hospital of Cologne, Cologne, Germany
| | - Judith Strapatsas
- Department of Haematology, Oncology and Clinical Immunology, University Hospital of Duesseldorf, Düsseldorf, Germany
| | | | | | - Annette Busch
- Medical Clinic III for Oncology, Haematology, Immune-Oncology and Rheumatology, Centre for Integrative Medicine, University Hospital Bonn, Bonn, Germany
| | - Franz-Georg Bauernfeind
- Medical Clinic III for Oncology, Haematology, Immune-Oncology and Rheumatology, Centre for Integrative Medicine, University Hospital Bonn, Bonn, Germany
| | - Frank Griesinger
- Pius-Hospital Oldenburg, Department of Haematology and Oncology, University Department Internal Medicine-Oncology, University Medicine Oldenburg, Oldenburg, Germany
| | - Anne Luers
- Pius-Hospital Oldenburg, Department of Haematology and Oncology, University Department Internal Medicine-Oncology, University Medicine Oldenburg, Oldenburg, Germany
| | - Wiebke Dirks
- Pius-Hospital Oldenburg, Department of Haematology and Oncology, University Department Internal Medicine-Oncology, University Medicine Oldenburg, Oldenburg, Germany
| | - Rainer Wiewrodt
- Pulmonary Division, Department of Medicine A, Münster University Hospital, Münster, Germany
| | - Andrea Luecke
- Pulmonary Division, Department of Medicine A, Münster University Hospital, Münster, Germany
| | - Ernst Rodermann
- Onkologie Rheinsieg, Praxisnetzwerk Hämatologie und Internistische Onkologie, Troisdorf, Germany
| | - Andreas Diel
- Onkologie Rheinsieg, Praxisnetzwerk Hämatologie und Internistische Onkologie, Troisdorf, Germany
| | - Volker Hagen
- Clinic II for Internal Medicine, St.-Johannes-Hospital Dortmund, Dortmund, Germany
| | - Kai Severin
- Haematologie und Onkologie Köln MV-Zentrum, Cologne, Germany
| | - Roland T Ullrich
- Department I of Internal Medicine, Centre for Integrated Oncology Aachen Bonn Cologne Duesseldorf, University Hospital Cologne, Cologne, Germany
- Centre for Molecular Medicine, University of Cologne, Cologne, Germany
| | - Hans Christian Reinhardt
- Department of Haematology and Stem Cell Transplantation, University Hospital Essen, Essen, Germany
- West German Cancer Centre, University Hospital Essen, Essen, Germany
| | - Alexander Quaas
- Institute of Pathology, Medical Faculty, University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Magdalena Bogus
- Institute of Legal Medicine, University of Cologne, Cologne, Germany
| | - Cornelius Courts
- Institute of Legal Medicine, University of Cologne, Cologne, Germany
| | - Peter Nürnberg
- Cologne Centre for Genomics, West German Genome Centre, University of Cologne, Cologne, Germany
| | - Kerstin Becker
- Cologne Centre for Genomics, West German Genome Centre, University of Cologne, Cologne, Germany
| | - Viktor Achter
- Computing Centre, University of Cologne, Cologne, Germany
| | - Reinhard Büttner
- Institute of Pathology, Medical Faculty, University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Jürgen Wolf
- Department I of Internal Medicine, Lung Cancer Group Cologne, University Hospital Cologne, Cologne, Germany
| | - Martin Peifer
- Department of Translational Genomics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
- Centre for Molecular Medicine, University of Cologne, Cologne, Germany.
| | - Roman K Thomas
- Department of Translational Genomics, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
- Institute of Pathology, Medical Faculty, University Hospital Cologne, University of Cologne, Cologne, Germany.
- DKFZ, German Cancer Research Centre, German Cancer Consortium, Heidelberg, Germany.
| |
Collapse
|
71
|
Vlasschaert C, Lanktree MB, Rauh MJ, Kelly TN, Natarajan P. Clonal haematopoiesis, ageing and kidney disease. Nat Rev Nephrol 2024; 20:161-174. [PMID: 37884787 PMCID: PMC10922936 DOI: 10.1038/s41581-023-00778-x] [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] [Accepted: 09/29/2023] [Indexed: 10/28/2023]
Abstract
Clonal haematopoiesis of indeterminate potential (CHIP) is a preclinical condition wherein a sizeable proportion of an individual's circulating blood cells are derived from a single mutated haematopoietic stem cell. CHIP occurs frequently with ageing - more than 10% of individuals over 65 years of age are affected - and is associated with an increased risk of disease across several organ systems and premature death. Emerging evidence suggests that CHIP has a role in kidney health, including associations with predisposition to acute kidney injury, impaired recovery from acute kidney injury and kidney function decline, both in the general population and among those with chronic kidney disease. Beyond its direct effect on the kidney, CHIP elevates the susceptibility of individuals to various conditions that can detrimentally affect the kidneys, including cardiovascular disease, obesity and insulin resistance, liver disease, gout, osteoporosis and certain autoimmune diseases. Aberrant pro-inflammatory signalling, telomere attrition and epigenetic ageing are potential causal pathophysiological pathways and mediators that underlie CHIP-related disease risk. Experimental animal models have shown that inhibition of inflammatory cytokine signalling can ameliorate many of the pathological effects of CHIP, and assessment of the efficacy and safety of this class of medications for human CHIP-associated pathology is ongoing.
Collapse
Affiliation(s)
| | - Matthew B Lanktree
- Department of Medicine and Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Ontario, Canada
- St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada
- Population Health Research Institute, Hamilton, Ontario, Canada
| | - Michael J Rauh
- Department of Pathology and Molecular Medicine, Kingston, Ontario, Canada
| | - Tanika N Kelly
- Division of Nephrology, Department of Medicine, College of Medicine, University of Illinois at Chicago, Chicago, IL, USA
| | - Pradeep Natarajan
- Cardiovascular Research Center and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
| |
Collapse
|
72
|
Akalu YT, Bogunovic D. Inborn errors of immunity: an expanding universe of disease and genetic architecture. Nat Rev Genet 2024; 25:184-195. [PMID: 37863939 DOI: 10.1038/s41576-023-00656-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/06/2023] [Indexed: 10/22/2023]
Abstract
Inborn errors of immunity (IEIs) are generally considered to be rare monogenic disorders of the immune system that cause immunodeficiency, autoinflammation, autoimmunity, allergy and/or cancer. Here, we discuss evidence that IEIs need not be rare disorders or exclusively affect the immune system. Namely, an increasing number of patients with IEIs present with severe dysregulations of the central nervous, digestive, renal or pulmonary systems. Current challenges in the diagnosis of IEIs that result from the segregated practice of specialized medicine could thus be mitigated, in part, by immunogenetic approaches. Starting with a brief historical overview of IEIs, we then discuss the technological advances that are facilitating the immunogenetic study of IEIs, progress in understanding disease penetrance in IEIs, the expanding universe of IEIs affecting distal organ systems and the future of genetic, biochemical and medical discoveries in this field.
Collapse
Affiliation(s)
- Yemsratch T Akalu
- Center for Inborn Errors of Immunity, Precision Immunology Institute, Department of Immunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Dusan Bogunovic
- Center for Inborn Errors of Immunity, Precision Immunology Institute, Department of Immunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| |
Collapse
|
73
|
Dymerska D, Marusiak AA. Drivers of cancer metastasis - Arise early and remain present. Biochim Biophys Acta Rev Cancer 2024; 1879:189060. [PMID: 38151195 DOI: 10.1016/j.bbcan.2023.189060] [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: 09/22/2023] [Revised: 12/09/2023] [Accepted: 12/15/2023] [Indexed: 12/29/2023]
Abstract
Cancer and its metastases arise from mutations of genes, drivers that promote a tumor's growth. Analyses of driver events provide insights into cancer cell history and may lead to a better understanding of oncogenesis. We reviewed 27 metastatic research studies, including pan-cancer studies, individual cancer studies, and phylogenetic analyses, and summarized our current knowledge of metastatic drivers. All of the analyzed studies had a high level of consistency of driver mutations between primary tumors and metastasis, indicating that most drivers appear early in cancer progression and are maintained in metastatic cells. Additionally, we reviewed data from around 50,000 metastatic cancer patients and compiled a list of genes altered in metastatic lesions. We performed Gene Ontology analysis and confirmed that the most significantly enriched processes in metastatic lesions were the epigenetic regulation of gene expression, signal transduction, cell cycle, programmed cell death, DNA damage, hypoxia and EMT. In this review, we explore the most recent discoveries regarding genetic factors in the advancement of cancer, specifically those that drive metastasis.
Collapse
Affiliation(s)
- Dagmara Dymerska
- Laboratory of Molecular OncoSignalling, IMol Polish Academy of Sciences, Warsaw, Poland.
| | - Anna A Marusiak
- Laboratory of Molecular OncoSignalling, IMol Polish Academy of Sciences, Warsaw, Poland.
| |
Collapse
|
74
|
Stonestrom AJ, Menghrajani KN, Devlin SM, Franch-Expósito S, Ptashkin RN, Patel SY, Spitzer B, Wu X, Jee J, Sánchez Vela P, Milbank JH, Shah RH, Mohanty AS, Brannon AR, Xiao W, Berger MF, Mantha S, Levine RL. High-risk and silent clonal hematopoietic genotypes in patients with nonhematologic cancer. Blood Adv 2024; 8:846-856. [PMID: 38147626 PMCID: PMC10875331 DOI: 10.1182/bloodadvances.2023011262] [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: 07/19/2023] [Revised: 11/15/2023] [Accepted: 11/20/2023] [Indexed: 12/28/2023] Open
Abstract
ABSTRACT Clonal hematopoiesis (CH) identified by somatic gene variants with variant allele fraction (VAF) ≥ 2% is associated with an increased risk of hematologic malignancy. However, CH defined by a broader set of genotypes and lower VAFs is ubiquitous in older individuals. To improve our understanding of the relationship between CH genotype and risk of hematologic malignancy, we analyzed data from 42 714 patients who underwent blood sequencing as a normal comparator for nonhematologic tumor testing using a large cancer-related gene panel. We cataloged hematologic malignancies in this cohort using natural language processing and manual curation of medical records. We found that some CH genotypes including JAK2, RUNX1, and XPO1 variants were associated with high hematologic malignancy risk. Chronic disease was predicted better than acute disease suggesting the influence of length bias. To better understand the implications of hematopoietic clonality independent of mutational function, we evaluated a set of silent synonymous and noncoding mutations. We found that silent CH, particularly when multiple variants were present or VAF was high, was associated with increased risk of hematologic malignancy. We tracked expansion of CH mutations in 26 hematologic malignancies sequenced with the same platform. JAK2 and TP53 VAF consistently expanded at disease onset, whereas DNMT3A and silent CH VAFs mostly decreased. These data inform the clinical and biological interpretation of CH in the context of nonhematologic cancer.
Collapse
Affiliation(s)
- Aaron J. Stonestrom
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Kamal N. Menghrajani
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Sean M. Devlin
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Sebastià Franch-Expósito
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Ryan N. Ptashkin
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Barbara Spitzer
- Department of Pediatrics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Xiaodi Wu
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Justin Jee
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Pablo Sánchez Vela
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Jennifer H. Milbank
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Ronak H. Shah
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Abhinita S. Mohanty
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - A. Rose Brannon
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Wenbin Xiao
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Michael F. Berger
- Department of Pathology and Laboratory Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Simon Mantha
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Ross L. Levine
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY
| |
Collapse
|
75
|
Thakur A, Gizzio J, Levy RM. Potts Hamiltonian Models and Molecular Dynamics Free Energy Simulations for Predicting the Impact of Mutations on Protein Kinase Stability. J Phys Chem B 2024; 128:1656-1667. [PMID: 38350894 PMCID: PMC10939730 DOI: 10.1021/acs.jpcb.3c08097] [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] [Indexed: 02/15/2024]
Abstract
Single-point mutations in kinase proteins can affect their stability and fitness, and computational analysis of these effects can provide insights into the relationships among protein sequence, structure, and function for this enzyme family. To assess the impact of mutations on protein stability, we used a sequence-based Potts Hamiltonian model trained on a kinase family multiple-sequence alignment (MSA) to calculate the statistical energy (fitness) effects of mutations and compared these against relative folding free energies (ΔΔGs) calculated from all-atom molecular dynamics free energy perturbation (FEP) simulations in explicit solvent. The fitness effects of mutations in the Potts model (ΔEs) showed good agreement with experimental thermostability data (Pearson r = 0.68), similar to the correlation we observed with ΔΔGs predicted from structure-based relative FEP simulations. Recognizing the possible advantages of using Potts models to rapidly estimate protein stability effects of kinase mutations seen in cancer genomics data, we used the Potts statistical energy model to estimate the stability effects of 65 conservative and nonconservative mutations across three distinct kinases (Wee1, Abl1, and Cdc7) with somatic mutations reported in the Genomic Data Commons (GDC) database. The ΔEs of these mutations calculated from the Potts model are consistent with the corresponding ΔΔGs from FEP simulations (Pearson ratio of 0.72). The agreement between these methods suggests that the Potts model may be used as a sequence-based tool for high-throughput screening of mutational effects as part of a computational pipeline for predicting the stability effects of mutations. We also demonstrate how the scalability of the fitness-based Potts model calculations permits analyses that are not easily accessed using FEP simulations. To this end, we employed site-saturation mutagenesis in the Potts model in order to investigate the relative stability effects of mutations seen in different cancer evolutionary scenarios. We used this approach to analyze the effects of drug pressure in Abl kinase by contrasting the relative fitness penalties of somatic mutations seen in miscellaneous cancer types with those calculated for mutations associated with cancer drug resistance. We observed that, in contrast to somatic mutations of Abl seen in various tumors that appear to have evolved neutrally, cancer mutations that evolved under drug pressure in Abl-targeted therapies tend to preserve enzyme stability.
Collapse
Affiliation(s)
- Abhishek Thakur
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - Joan Gizzio
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
| | - Ronald M Levy
- Center for Biophysics and Computational Biology, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Chemistry, Temple University, Philadelphia, Pennsylvania 19122, United States
- Department of Physics, Temple University, Philadelphia, Pennsylvania 19122, United States
| |
Collapse
|
76
|
Fabre MA, Vassiliou GS. The lifelong natural history of clonal hematopoiesis and its links to myeloid neoplasia. Blood 2024; 143:573-581. [PMID: 37992214 DOI: 10.1182/blood.2023019964] [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: 07/28/2023] [Revised: 10/26/2023] [Accepted: 11/13/2023] [Indexed: 11/24/2023] Open
Abstract
ABSTRACT The study of somatic mutations and the associated clonal mosaicism across the human body has transformed our understanding of aging and its links to cancer. In proliferative human tissues, stem cells compete for dominance, and those with an advantage expand clonally to outgrow their peers. In the hematopoietic system, such expansion is termed clonal hematopoiesis (CH). The forces driving competition, namely heterogeneity of the hematopoietic stem cell (HSC) pool and attrition of their environment, become increasingly prominent with age. As a result, CH becomes progressively more common through life to the point of becoming essentially ubiquitous. We are beginning to unravel the specific intracellular and extracellular factors underpinning clonal behavior, with somatic mutations in specific driver genes, inflammation, telomere maintenance, extraneous exposures, and inherited genetic variation among the important players. The inevitability of CH with age combined with its unequivocal links to myeloid cancers poses a scientific and clinical challenge. Specifically, we need to decipher the factors determining clonal behavior and develop prognostic tools to identify those at high risk of malignant progression, for whom preventive interventions may be warranted. Here, we discuss how recent advances in our understanding of the natural history of CH have provided important insights into these processes and helped define future avenues of investigation.
Collapse
Affiliation(s)
- Margarete A Fabre
- Department of Haematology, Cambridge University Hospitals National Health Service Trust, Cambridge, United Kingdom
- Centre for Genomics Research, Discovery Sciences, BioPharmaceuticals Research & Development, AstraZeneca, Cambridge, United Kingdom
| | - George S Vassiliou
- Department of Haematology, Cambridge University Hospitals National Health Service Trust, Cambridge, United Kingdom
- Department of Haematology, University of Cambridge, Cambridge, United Kingdom
- Wellcome-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge, United Kingdom
| |
Collapse
|
77
|
Memon D, Schoenfeld AJ, Ye D, Fromm G, Rizvi H, Zhang X, Keddar MR, Mathew D, Yoo KJ, Qiu J, Lihm J, Miriyala J, Sauter JL, Luo J, Chow A, Bhanot UK, McCarthy C, Vanderbilt CM, Liu C, Abu-Akeel M, Plodkowski AJ, McGranahan N, Łuksza M, Greenbaum BD, Merghoub T, Achour I, Barrett JC, Stewart R, Beltrao P, Schreiber TH, Minn AJ, Miller ML, Hellmann MD. Clinical and molecular features of acquired resistance to immunotherapy in non-small cell lung cancer. Cancer Cell 2024; 42:209-224.e9. [PMID: 38215748 PMCID: PMC11249385 DOI: 10.1016/j.ccell.2023.12.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 09/13/2023] [Accepted: 12/13/2023] [Indexed: 01/14/2024]
Abstract
Although immunotherapy with PD-(L)1 blockade is routine for lung cancer, little is known about acquired resistance. Among 1,201 patients with non-small cell lung cancer (NSCLC) treated with PD-(L)1 blockade, acquired resistance is common, occurring in >60% of initial responders. Acquired resistance shows differential expression of inflammation and interferon (IFN) signaling. Relapsed tumors can be separated by upregulated or stable expression of IFNγ response genes. Upregulation of IFNγ response genes is associated with putative routes of resistance characterized by signatures of persistent IFN signaling, immune dysfunction, and mutations in antigen presentation genes which can be recapitulated in multiple murine models of acquired resistance to PD-(L)1 blockade after in vitro IFNγ treatment. Acquired resistance to PD-(L)1 blockade in NSCLC is associated with an ongoing, but altered IFN response. The persistently inflamed, rather than excluded or deserted, tumor microenvironment of acquired resistance may inform therapeutic strategies to effectively reprogram and reverse acquired resistance.
Collapse
Affiliation(s)
- Danish Memon
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK; Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, UK; M:M Bio Limited, 99 Park Drive, Milton, Abingdon, UK
| | - Adam J Schoenfeld
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Darwin Ye
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Parker Institute for Cancer Immunotherapy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Mark Foundation Center for Immunotherapy, Immune Signaling, and Radiation, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Hira Rizvi
- Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Early Clinical Development, Oncology R&D, AstraZeneca, New York, NY, USA
| | - Xiang Zhang
- Data Sciences and Quantitative Biology, Discovery Sciences, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | | | - Divij Mathew
- Parker Institute for Cancer Immunotherapy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Institute for Immunology and Immune Health, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA; Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | | | - Jingya Qiu
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Parker Institute for Cancer Immunotherapy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Mark Foundation Center for Immunotherapy, Immune Signaling, and Radiation, University of Pennsylvania, Philadelphia, PA, USA
| | - Jayon Lihm
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Jennifer L Sauter
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jia Luo
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Andrew Chow
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Umesh K Bhanot
- Precision Pathology Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Caroline McCarthy
- Druckenmiller Center for Lung Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Chad M Vanderbilt
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Cailian Liu
- Ludwig Collaborative and Swim Across America Laboratory, Memorial Sloan Kettering Cancer Center (MSK), New York, NY, USA
| | - Mohsen Abu-Akeel
- Ludwig Collaborative and Swim Across America Laboratory, Memorial Sloan Kettering Cancer Center (MSK), New York, NY, USA
| | - Andrew J Plodkowski
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Nicholas McGranahan
- Cancer Genome Evolution Research Group, University College London Cancer Institute, London, UK
| | - Marta Łuksza
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Benjamin D Greenbaum
- Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Taha Merghoub
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Weill Cornell Medicine, New York, NY, USA; Ludwig Collaborative and Swim Across America Laboratory, Memorial Sloan Kettering Cancer Center (MSK), New York, NY, USA; Parker Institute for Cancer Immunotherapy, MSK, New York, NY, USA; Human Oncology and Pathogenesis Program, MSK, New York, NY, USA
| | - Ikbel Achour
- Translational Medicine, Oncology R&D, AstraZeneca, Cambridge, UK
| | - J Carl Barrett
- Translational Medicine, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Ross Stewart
- Translational Medicine, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Pedro Beltrao
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK; Institute of Molecular Systems Biology, ETH Zürich, Zurich, Switzerland
| | | | - Andy J Minn
- Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Parker Institute for Cancer Immunotherapy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Mark Foundation Center for Immunotherapy, Immune Signaling, and Radiation, University of Pennsylvania, Philadelphia, PA, USA.
| | - Martin L Miller
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge, UK; Oncology Data Science, Oncology R&D, AstraZeneca, Cambridge, UK.
| | - Matthew D Hellmann
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Department of Medicine, Weill Cornell Medicine, New York, NY, USA; Early Clinical Development, Oncology R&D, AstraZeneca, New York, NY, USA; Parker Institute for Cancer Immunotherapy, MSK, New York, NY, USA.
| |
Collapse
|
78
|
Baker TM, Waise S, Tarabichi M, Van Loo P. Aneuploidy and complex genomic rearrangements in cancer evolution. NATURE CANCER 2024; 5:228-239. [PMID: 38286829 PMCID: PMC7616040 DOI: 10.1038/s43018-023-00711-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 12/14/2023] [Indexed: 01/31/2024]
Abstract
Mutational processes that alter large genomic regions occur frequently in developing tumors. They range from simple copy number gains and losses to the shattering and reassembly of entire chromosomes. These catastrophic events, such as chromothripsis, chromoplexy and the formation of extrachromosomal DNA, affect the expression of many genes and therefore have a substantial effect on the fitness of the cells in which they arise. In this review, we cover large genomic alterations, the mechanisms that cause them and their effect on tumor development and evolution.
Collapse
Affiliation(s)
- Toby M Baker
- The Francis Crick Institute, London, UK
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Sara Waise
- The Francis Crick Institute, London, UK
- Cancer Sciences Unit, University of Southampton, Southampton, UK
| | - Maxime Tarabichi
- The Francis Crick Institute, London, UK
- Institute for Interdisciplinary Research (IRIBHM), Université Libre de Bruxelles, Brussels, Belgium
| | - Peter Van Loo
- The Francis Crick Institute, London, UK.
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
| |
Collapse
|
79
|
Wang N, Chen P, Xu Y, Guo L, Li X, Yi H, Larkin RM, Zhou Y, Deng X, Xu Q. Phased genomics reveals hidden somatic mutations and provides insight into fruit development in sweet orange. HORTICULTURE RESEARCH 2024; 11:uhad268. [PMID: 38371640 PMCID: PMC10873711 DOI: 10.1093/hr/uhad268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Accepted: 12/01/2023] [Indexed: 02/20/2024]
Abstract
Although revisiting the discoveries and implications of genetic variations using phased genomics is critical, such efforts are still lacking. Somatic mutations represent a crucial source of genetic diversity for breeding and are especially remarkable in heterozygous perennial and asexual crops. In this study, we focused on a diploid sweet orange (Citrus sinensis) and constructed a haplotype-resolved genome using high fidelity (HiFi) reads, which revealed 10.6% new sequences. Based on the phased genome, we elucidate significant genetic admixtures and haplotype differences. We developed a somatic detection strategy that reveals hidden somatic mutations overlooked in a single reference genome. We generated a phased somatic variation map by combining high-depth whole-genome sequencing (WGS) data from 87 sweet orange somatic varieties. Notably, we found twice as many somatic mutations relative to a single reference genome. Using these hidden somatic mutations, we separated sweet oranges into seven major clades and provide insight into unprecedented genetic mosaicism and strong positive selection. Furthermore, these phased genomics data indicate that genomic heterozygous variations contribute to allele-specific expression during fruit development. By integrating allelic expression differences and somatic mutations, we identified a somatic mutation that induces increases in fruit size. Applications of phased genomics will lead to powerful approaches for discovering genetic variations and uncovering their effects in highly heterozygous plants. Our data provide insight into the hidden somatic mutation landscape in the sweet orange genome, which will facilitate citrus breeding.
Collapse
Affiliation(s)
- Nan Wang
- Institute of Horticultural Research, Hunan Academy of Agricultural Sciences, Changsha, China
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Peng Chen
- Institute of Horticultural Research, Hunan Academy of Agricultural Sciences, Changsha, China
- Yuelu Mountain Laboratory, Changsha, China
| | - Yuanyuan Xu
- Institute of Horticultural Research, Hunan Academy of Agricultural Sciences, Changsha, China
- Yuelu Mountain Laboratory, Changsha, China
| | - Lingxia Guo
- Institute of Horticultural Research, Hunan Academy of Agricultural Sciences, Changsha, China
- Yuelu Mountain Laboratory, Changsha, China
| | - Xianxin Li
- Institute of Horticultural Research, Hunan Academy of Agricultural Sciences, Changsha, China
- Yuelu Mountain Laboratory, Changsha, China
| | - Hualin Yi
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Robert M Larkin
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Yongfeng Zhou
- National Key Laboratory of Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
- National Key Laboratory of Tropical Crop Breeding, Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences, Haikou, China
| | - Xiuxin Deng
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Qiang Xu
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| |
Collapse
|
80
|
Wu S, Wagner G. Computational inference of eIF4F complex function and structure in human cancers. Proc Natl Acad Sci U S A 2024; 121:e2313589121. [PMID: 38266053 PMCID: PMC10835048 DOI: 10.1073/pnas.2313589121] [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: 08/10/2023] [Accepted: 12/18/2023] [Indexed: 01/26/2024] Open
Abstract
The canonical eukaryotic initiation factor 4F (eIF4F) complex, composed of eIF4G1, eIF4A1, and the cap-binding protein eIF4E, plays a crucial role in cap-dependent translation initiation in eukaryotic cells. An alternative cap-independent initiation can occur, involving only eIF4G1 and eIF4A1 through internal ribosome entry sites (IRESs). This mechanism is considered complementary to cap-dependent initiation, particularly in tumors under stress conditions. However, the selection and molecular mechanism of specific translation initiation remains poorly understood in human cancers. Thus, we analyzed gene copy number variations (CNVs) in TCGA tumor samples and found frequent amplification of genes involved in translation initiation. Copy number gains in EIF4G1 and EIF3E frequently co-occur across human cancers. Additionally, EIF4G1 expression strongly correlates with genes from cancer cell survival pathways including cell cycle and lipogenesis, in tumors with EIF4G1 amplification or duplication. Furthermore, we revealed that eIF4G1 and eIF4A1 protein levels strongly co-regulate with ribosomal subunits, eIF2, and eIF3 complexes, while eIF4E co-regulates with 4E-BP1, ubiquitination, and ESCRT proteins. Utilizing Alphafold predictions, we modeled the eIF4F structure with and without eIF4E binding. For cap-dependent initiation, our modeling reveals extensive interactions between the N-terminal eIF4E-binding domain of eIF4G1 and eIF4E. Furthermore, the eIF4G1 HEAT-2 domain positions eIF4E near the eIF4A1 N-terminal domain (NTD), resulting in the collaborative enclosure of the RNA binding cavity within eIF4A1. In contrast, during cap-independent initiation, the HEAT-2 domain directly binds the eIF4A1-NTD, leading to a stronger interaction between eIF4G1 and eIF4A1, thus closing the mRNA binding cavity without the involvement of eIF4E.
Collapse
Affiliation(s)
- Su Wu
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA02115
| | - Gerhard Wagner
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA02115
| |
Collapse
|
81
|
Panier S, Wang S, Schumacher B. Genome Instability and DNA Repair in Somatic and Reproductive Aging. ANNUAL REVIEW OF PATHOLOGY 2024; 19:261-290. [PMID: 37832947 DOI: 10.1146/annurev-pathmechdis-051122-093128] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/15/2023]
Abstract
Genetic material is constantly subjected to genotoxic insults and is critically dependent on DNA repair. Genome maintenance mechanisms differ in somatic and germ cells as the soma only requires maintenance during an individual's lifespan, while the germline indefinitely perpetuates its genetic information. DNA lesions are recognized and repaired by mechanistically highly diverse repair machineries. The DNA damage response impinges on a vast array of homeostatic processes and can ultimately result in cell fate changes such as apoptosis or cellular senescence. DNA damage causally contributes to the aging process and aging-associated diseases, most prominently cancer. By causing mutations, DNA damage in germ cells can lead to genetic diseases and impact the evolutionary trajectory of a species. The mechanisms ensuring tight control of germline DNA repair could be highly instructive in defining strategies for improved somatic DNA repair. They may provide future interventions to maintain health and prevent disease during aging.
Collapse
Affiliation(s)
- Stephanie Panier
- Institute for Genome Stability in Aging and Disease and Cluster of Excellence: Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne and University Hospital of Cologne, Cologne, Germany;
- Max Planck Institute for Biology of Ageing, Cologne, Germany
| | - Siyao Wang
- Institute for Genome Stability in Aging and Disease and Cluster of Excellence: Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne and University Hospital of Cologne, Cologne, Germany;
- Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany
- Institute of Molecular Biology (IMB), Mainz, Germany
| | - Björn Schumacher
- Institute for Genome Stability in Aging and Disease and Cluster of Excellence: Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne and University Hospital of Cologne, Cologne, Germany;
- Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany
| |
Collapse
|
82
|
Moeller ME, Mon Père NV, Werner B, Huang W. Measures of genetic diversification in somatic tissues at bulk and single-cell resolution. eLife 2024; 12:RP89780. [PMID: 38265286 PMCID: PMC10945735 DOI: 10.7554/elife.89780] [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] [Indexed: 01/25/2024] Open
Abstract
Intra-tissue genetic heterogeneity is universal to both healthy and cancerous tissues. It emerges from the stochastic accumulation of somatic mutations throughout development and homeostasis. By combining population genetics theory and genomic information, genetic heterogeneity can be exploited to infer tissue organization and dynamics in vivo. However, many basic quantities, for example the dynamics of tissue-specific stem cells remain difficult to quantify precisely. Here, we show that single-cell and bulk sequencing data inform on different aspects of the underlying stochastic processes. Bulk-derived variant allele frequency spectra (VAF) show transitions from growing to constant stem cell populations with age in samples of healthy esophagus epithelium. Single-cell mutational burden distributions allow a sample size independent measure of mutation and proliferation rates. Mutation rates in adult hematopietic stem cells are higher compared to inferences during development, suggesting additional proliferation-independent effects. Furthermore, single-cell derived VAF spectra contain information on the number of tissue-specific stem cells. In hematopiesis, we find approximately 2 × 105 HSCs, if all stem cells divide symmetrically. However, the single-cell mutational burden distribution is over-dispersed compared to a model of Poisson distributed random mutations. A time-associated model of mutation accumulation with a constant rate alone cannot generate such a pattern. At least one additional source of stochasticity would be needed. Possible candidates for these processes may be occasional bursts of stem cell divisions, potentially in response to injury, or non-constant mutation rates either through environmental exposures or cell-intrinsic variation.
Collapse
Affiliation(s)
- Marius E Moeller
- Department of Mathematics, Queen Mary University of LondonLondonUnited Kingdom
| | - Nathaniel V Mon Père
- Evolutionary Dynamics Group, Centre for Cancer Genomics and Computational Biology, Barts Cancer Centre, Queen Mary University of LondonLondonUnited Kingdom
- Interuniversity Institute of Bioinformatics in Brussels, Université Libre de BruxellesIxellesBelgium
| | - Benjamin Werner
- Evolutionary Dynamics Group, Centre for Cancer Genomics and Computational Biology, Barts Cancer Centre, Queen Mary University of LondonLondonUnited Kingdom
| | - Weini Huang
- Department of Mathematics, Queen Mary University of LondonLondonUnited Kingdom
- Group of Theoretical Biology, The State Key Laboratory of Biocontrol, School of Life Science, Sun Yat-sen UniversityGuangzhouChina
| |
Collapse
|
83
|
Nourbakhsh M, Degn K, Saksager A, Tiberti M, Papaleo E. Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks. Brief Bioinform 2024; 25:bbad519. [PMID: 38261338 PMCID: PMC10805075 DOI: 10.1093/bib/bbad519] [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: 06/09/2023] [Revised: 11/27/2023] [Accepted: 12/11/2023] [Indexed: 01/24/2024] Open
Abstract
The vast amount of available sequencing data allows the scientific community to explore different genetic alterations that may drive cancer or favor cancer progression. Software developers have proposed a myriad of predictive tools, allowing researchers and clinicians to compare and prioritize driver genes and mutations and their relative pathogenicity. However, there is little consensus on the computational approach or a golden standard for comparison. Hence, benchmarking the different tools depends highly on the input data, indicating that overfitting is still a massive problem. One of the solutions is to limit the scope and usage of specific tools. However, such limitations force researchers to walk on a tightrope between creating and using high-quality tools for a specific purpose and describing the complex alterations driving cancer. While the knowledge of cancer development increases daily, many bioinformatic pipelines rely on single nucleotide variants or alterations in a vacuum without accounting for cellular compartments, mutational burden or disease progression. Even within bioinformatics and computational cancer biology, the research fields work in silos, risking overlooking potential synergies or breakthroughs. Here, we provide an overview of databases and datasets for building or testing predictive cancer driver tools. Furthermore, we introduce predictive tools for driver genes, driver mutations, and the impact of these based on structural analysis. Additionally, we suggest and recommend directions in the field to avoid silo-research, moving towards integrative frameworks.
Collapse
Affiliation(s)
- Mona Nourbakhsh
- Cancer Systems Biology, Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Kristine Degn
- Cancer Systems Biology, Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Astrid Saksager
- Cancer Systems Biology, Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, 2800 Lyngby, Denmark
| | - Matteo Tiberti
- Cancer Structural Biology, Danish Cancer Institute, 2100 Copenhagen, Denmark
| | - Elena Papaleo
- Cancer Systems Biology, Section for Bioinformatics, Department of Health Technology, Technical University of Denmark, 2800 Lyngby, Denmark
- Cancer Structural Biology, Danish Cancer Institute, 2100 Copenhagen, Denmark
| |
Collapse
|
84
|
Wang M, Li SC, Shen B. Elevated incidence of somatic mutations at prevalent genetic sites. Brief Bioinform 2024; 25:bbae065. [PMID: 38426321 PMCID: PMC10939422 DOI: 10.1093/bib/bbae065] [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: 10/09/2023] [Revised: 01/03/2024] [Accepted: 02/03/2024] [Indexed: 03/02/2024] Open
Abstract
The common loci represent a distinct set of the human genome sites that harbor genetic variants found in at least 1% of the population. Small somatic mutations occur at the common loci and non-common loci, i.e. csmVariants and ncsmVariants, are presumed with similar probabilities. However, our work revealed that within the coding region, common loci constituted only 1.03% of all loci, yet they accounted for 5.14% of TCGA somatic mutations. Furthermore, the small somatic mutation incidence rate at these common loci was 2.7 times that observed in the non-common. Notably, the csmVariants exhibited an impressive recurrent rate of 36.14%, which was 2.59 times of the ncsmVariants. The C-to-T transition at the CpG sites accounted for 32.41% of the csmVariants, which was 2.93 times for the ncsmVariants. Interestingly, the aging-related mutational signature contributed to 13.87% of the csmVariants, 5.5 times that of ncsmVariants. Moreover, 35.93% of the csmVariants contexts exhibited palindromic features, outperforming ncsmVariant contexts by 1.84 times. Notably, cancer patients with higher csmVariants rates had better progression-free survival. Furthermore, cancer patients with high-frequency csmVariants enriched with mismatch repair deficiency were also associated with better progression-free survival. The accumulation of csmVariants during cancerogenesis is a complex process influenced by various factors. These include the presence of a substantial percentage of palindromic sequences at csmVariants sites, the impact of aging and DNA mismatch repair deficiency. Together, these factors contribute to the higher somatic mutation incidence rates of common loci and the overall accumulation of csmVariants in cancer development.
Collapse
Affiliation(s)
- Mengyao Wang
- Department of Computer Science, City University of Hong Kong, 83 Tat Chee Ave, Kowloon Tong, Hong Kong, China
- Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, Fuzhou, China
| | - Shuai Cheng Li
- Department of Computer Science, City University of Hong Kong, 83 Tat Chee Ave, Kowloon Tong, Hong Kong, China
| | - Bairong Shen
- Institutes for Systems Genetics, Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Joint Laboratory of Artificial Intelligence for Critical Care Medicine, Department of Critical Care Medicine and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, 610212, Chengdu, China
| |
Collapse
|
85
|
Hu Y, Sun H, Shi W, Chen C, Wu X, Jiang Y, Zhang G, Li N, Song J, Zhang H, Shen B, Zeng H, Zhang H. Immunogram defines four cancer-immunity cycle phenotypes with distinct clonal selection patterns across solid tumors. J Transl Med 2024; 22:69. [PMID: 38243238 PMCID: PMC10799518 DOI: 10.1186/s12967-023-04765-5] [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: 05/19/2023] [Accepted: 11/27/2023] [Indexed: 01/21/2024] Open
Abstract
BACKGROUND The cancer-immunity cycle (CI cycle) provides a theoretical framework to illustrate the process of the anticancer immune response. Recently, the update of the CI cycle theory emphasizes the importance of tumor's immunological phenotype. However, there is lack of immunological phenotype of pan-cancer based on CI cycle theory. METHODS Here, we applied a visualizing method termed 'cancer immunogram' to visualize the state of CI cycle of 8460 solid tumors from TCGA cohort. Unsupervised clustering of the cancer immunogram was performed using the nonnegative matrix factorization (NMF) analysis. We applied an evolutionary genomics approach (dN/dS ratio) to evaluate the clonal selection patterns of tumors with distinct immunogram subtypes. RESULTS We defined four major CI cycle patterns across 32 cancer types using a cancer immunogram approach. Immunogram-I was characterized by 'hot' and 'exhausted' features, indicating a favorable prognosis. Strikingly, immunogram-II, immunogram-III, and immunogram-IV represented distinct immunosuppressive patterns of 'cold' tumor. Immunogram-II was characterized by 'cold' and 'radical' features, which represented increased expression of immune inhibitor molecules and high levels of positive selection, indicating the worst prognosis. Immunogram-III was characterized by 'cold' and 'recognizable' features and upregulated expression of MHC I molecules. Immunogram-IV was characterized by 'cold' and 'inert' features, which represented overall immunosuppression, lower levels of immunoediting and positive selection, and accumulation of more tumor neoantigens. In particular, favorable overall survival was observed in metastatic urothelial cancer patients with immunogram-I and immunogram-IV after immune checkpoint inhibitor (ICI) therapy. Meanwhile, a higher response rate to ICI therapy was observed in metastatic gastric cancer patients with immunogram-I phenotype. CONCLUSIONS Our findings provide new insight into the interaction between immunity and cancer evolution, which may contribute to optimizing immunotherapy strategies.
Collapse
Affiliation(s)
- Ying Hu
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
- Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
| | - Huaibo Sun
- Beijing SinoMDgene Technology CO., LTD, Beijing, 100176, China
| | - Wei Shi
- Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Chen Chen
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
- Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
| | - Xueying Wu
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
- Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
| | - Yu Jiang
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
- Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
| | - Guoying Zhang
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
- Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
| | - Na Li
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
- Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China
| | - Jin Song
- Beijing Immupeutics Medicine Technology Limited, Beijing, 102609, China
| | - Hao Zhang
- Department of General Surgery, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Baiyong Shen
- Department of General Surgery, Pancreatic Disease Center, Research Institute of Pancreatic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- State Key Laboratory of Oncogenes and Related Genes, National Research Center for Translational Medicine (Shanghai), Shanghai, 200025, China.
| | - Hui Zeng
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China.
- Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China.
| | - Henghui Zhang
- Biomedical Innovation Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China.
- Beijing Key Laboratory for Therapeutic Cancer Vaccines, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, China.
- Beijing Engineering Research Center of Immunocellular therapy, Beijing, 102609, China.
| |
Collapse
|
86
|
Ciriello G, Magnani L, Aitken SJ, Akkari L, Behjati S, Hanahan D, Landau DA, Lopez-Bigas N, Lupiáñez DG, Marine JC, Martin-Villalba A, Natoli G, Obenauf AC, Oricchio E, Scaffidi P, Sottoriva A, Swarbrick A, Tonon G, Vanharanta S, Zuber J. Cancer Evolution: A Multifaceted Affair. Cancer Discov 2024; 14:36-48. [PMID: 38047596 PMCID: PMC10784746 DOI: 10.1158/2159-8290.cd-23-0530] [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: 05/04/2023] [Revised: 08/29/2023] [Accepted: 10/23/2023] [Indexed: 12/05/2023]
Abstract
Cancer cells adapt and survive through the acquisition and selection of molecular modifications. This process defines cancer evolution. Building on a theoretical framework based on heritable genetic changes has provided insights into the mechanisms supporting cancer evolution. However, cancer hallmarks also emerge via heritable nongenetic mechanisms, including epigenetic and chromatin topological changes, and interactions between tumor cells and the tumor microenvironment. Recent findings on tumor evolutionary mechanisms draw a multifaceted picture where heterogeneous forces interact and influence each other while shaping tumor progression. A comprehensive characterization of the cancer evolutionary toolkit is required to improve personalized medicine and biomarker discovery. SIGNIFICANCE Tumor evolution is fueled by multiple enabling mechanisms. Importantly, genetic instability, epigenetic reprogramming, and interactions with the tumor microenvironment are neither alternative nor independent evolutionary mechanisms. As demonstrated by findings highlighted in this perspective, experimental and theoretical approaches must account for multiple evolutionary mechanisms and their interactions to ultimately understand, predict, and steer tumor evolution.
Collapse
Affiliation(s)
- Giovanni Ciriello
- Swiss Cancer Center Leman, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Luca Magnani
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, United Kingdom
- Breast Epigenetic Plasticity and Evolution Laboratory, Division of Breast Cancer Research, The Institute of Cancer Research, London, United Kingdom
- Department of Surgery and Cancer, Imperial College London, London, United Kingdom
| | - Sarah J. Aitken
- Medical Research Council Toxicology Unit, University of Cambridge, Cambridge, United Kingdom
- Department of Histopathology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Leila Akkari
- Division of Tumor Biology and Immunology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Sam Behjati
- Wellcome Sanger Institute, Hinxton, United Kingdom
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
- Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom
| | - Douglas Hanahan
- Swiss Cancer Center Leman, Lausanne, Switzerland
- Ludwig Institute for Cancer Research, Lausanne, Switzerland
| | - Dan A. Landau
- New York Genome Center, New York, New York
- Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, New York
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, New York
| | - Nuria Lopez-Bigas
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Darío G. Lupiáñez
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Jean-Christophe Marine
- Laboratory for Molecular Cancer Biology, Center for Cancer Biology, VIB, Leuven, Belgium
- Laboratory for Molecular Cancer Biology, Department of Oncology, KULeuven, Leuven, Belgium
| | - Ana Martin-Villalba
- Department of Molecular Neurobiology, German Cancer Research Center (DFKZ), Heidelberg, Germany
| | - Gioacchino Natoli
- Department of Experimental Oncology, European Institute of Oncology IRCCS, Milan, Italy
| | - Anna C. Obenauf
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna, Austria
| | - Elisa Oricchio
- Swiss Cancer Center Leman, Lausanne, Switzerland
- Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland
| | - Paola Scaffidi
- Department of Experimental Oncology, European Institute of Oncology IRCCS, Milan, Italy
- Cancer Epigenetic Laboratory, The Francis Crick Institute, London, United Kingdom
| | - Andrea Sottoriva
- Computational Biology Research Centre, Human Technopole, Milan, Italy
| | - Alexander Swarbrick
- Cancer Ecosystems Program, Garvan Institute of Medical Research, Darlinghurst, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, UNSW Sydney, Sydney, Australia
| | - Giovanni Tonon
- Vita-Salute San Raffaele University, Milan, Italy
- Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Sakari Vanharanta
- Translational Cancer Medicine Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Biochemistry and Developmental Biology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Johannes Zuber
- Research Institute of Molecular Pathology, Vienna Biocenter, Vienna, Austria
- Medical University of Vienna, Vienna BioCenter (VBC), Vienna, Austria
| |
Collapse
|
87
|
Sondka Z, Dhir NB, Carvalho-Silva D, Jupe S, Madhumita, McLaren K, Starkey M, Ward S, Wilding J, Ahmed M, Argasinska J, Beare D, Chawla MS, Duke S, Fasanella I, Neogi AG, Haller S, Hetenyi B, Hodges L, Holmes A, Lyne R, Maurel T, Nair S, Pedro H, Sangrador-Vegas A, Schuilenburg H, Sheard Z, Yong S, Teague J. COSMIC: a curated database of somatic variants and clinical data for cancer. Nucleic Acids Res 2024; 52:D1210-D1217. [PMID: 38183204 PMCID: PMC10767972 DOI: 10.1093/nar/gkad986] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/13/2023] [Accepted: 10/16/2023] [Indexed: 01/07/2024] Open
Abstract
The Catalogue Of Somatic Mutations In Cancer (COSMIC), https://cancer.sanger.ac.uk/cosmic, is an expert-curated knowledgebase providing data on somatic variants in cancer, supported by a comprehensive suite of tools for interpreting genomic data, discerning the impact of somatic alterations on disease, and facilitating translational research. The catalogue is accessed and used by thousands of cancer researchers and clinicians daily, allowing them to quickly access information from an immense pool of data curated from over 29 thousand scientific publications and large studies. Within the last 4 years, COSMIC has substantially expanded its utility by adding new resources: the Mutational Signatures catalogue, the Cancer Mutation Census, and Actionability. To improve data accessibility and interoperability, somatic variants have received stable genomic identifiers that are associated with their genomic coordinates in GRCh37 and GRCh38, and new export files with reduced data redundancy have been made available for download.
Collapse
Affiliation(s)
- Zbyslaw Sondka
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Nidhi Bindal Dhir
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | | | - Steven Jupe
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Madhumita
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Karen McLaren
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Mike Starkey
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Sari Ward
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Jennifer Wilding
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Madiha Ahmed
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Joanna Argasinska
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - David Beare
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | | | - Stephen Duke
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Ilaria Fasanella
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Avirup Guha Neogi
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Susan Haller
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Balazs Hetenyi
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Leonie Hodges
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Alex Holmes
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Rachel Lyne
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Thomas Maurel
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Sumodh Nair
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Helder Pedro
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | | | - Helen Schuilenburg
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Zoe Sheard
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Siew Yit Yong
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Jon Teague
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| |
Collapse
|
88
|
Huang AY, Zhou Z, Talukdar M, Miller MB, Chhouk B, Enyenihi L, Rosen I, Stronge E, Zhao B, Kim D, Choi J, Khoshkhoo S, Kim J, Ganz J, Travaglini K, Gabitto M, Hodge R, Kaplan E, Lein E, De Jager PL, Bennett DA, Lee EA, Walsh CA. Somatic cancer driver mutations are enriched and associated with inflammatory states in Alzheimer's disease microglia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.03.574078. [PMID: 38260600 PMCID: PMC10802273 DOI: 10.1101/2024.01.03.574078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Alzheimer's disease (AD) is an age-associated neurodegenerative disorder characterized by progressive neuronal loss and pathological accumulation of the misfolded proteins amyloid-β and tau1,2. Neuroinflammation mediated by microglia and brain-resident macrophages plays a crucial role in AD pathogenesis1-5, though the mechanisms by which age, genes, and other risk factors interact remain largely unknown. Somatic mutations accumulate with age and lead to clonal expansion of many cell types, contributing to cancer and many non-cancer diseases6,7. Here we studied somatic mutation in normal aged and AD brains by three orthogonal methods and in three independent AD cohorts. Analysis of bulk RNA sequencing data from 866 samples from different brain regions revealed significantly higher (~two-fold) overall burdens of somatic single-nucleotide variants (sSNVs) in AD brains compared to age-matched controls. Molecular-barcoded deep (>1000X) gene panel sequencing of 311 prefrontal cortex samples showed enrichment of sSNVs and somatic insertions and deletions (sIndels) in cancer driver genes in AD brain compared to control, with recurrent, and often multiple, mutations in genes implicated in clonal hematopoiesis (CH)8,9. Pathogenic sSNVs were enriched in CSF1R+ microglia of AD brains, and the high proportion of microglia (up to 40%) carrying some sSNVs in cancer driver genes suggests mutation-driven microglial clonal expansion (MiCE). Analysis of single-nucleus RNA sequencing (snRNAseq) from temporal neocortex of 62 additional AD cases and controls exhibited nominally increased mosaic chromosomal alterations (mCAs) associated with CH10,11. Microglia carrying mCA showed upregulated pro-inflammatory genes, resembling the transcriptomic features of disease-associated microglia (DAM) in AD. Our results suggest that somatic driver mutations in microglia are common with normal aging but further enriched in AD brain, driving MiCE with inflammatory and DAM signatures. Our findings provide the first insights into microglial clonal dynamics in AD and identify potential new approaches to AD diagnosis and therapy.
Collapse
Affiliation(s)
- August Yue Huang
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Zinan Zhou
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Maya Talukdar
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard-MIT MD/PhD Program, Boston, MA, USA
| | - Michael B. Miller
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Neuropathology, Department of Pathology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Brian Chhouk
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
| | - Liz Enyenihi
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard-MIT MD/PhD Program, Boston, MA, USA
| | - Ila Rosen
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
| | - Edward Stronge
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard-MIT MD/PhD Program, Boston, MA, USA
| | - Boxun Zhao
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Dachan Kim
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Department of Otorhinolaryngology, Severance Hospital, Yonsei University Health System, Yonsei University College of Medicine, Seoul, South Korea
| | - Jaejoon Choi
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sattar Khoshkhoo
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
| | - Junho Kim
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biological Sciences, Sungkyunkwan University, Suwon, South Korea
| | - Javier Ganz
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | | | | | - Eitan Kaplan
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Ed Lein
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Philip L. De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology and the Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical College, Chicago, IL, USA
| | - Eunjung Alice Lee
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Christopher A. Walsh
- Division of Genetics and Genomics and Manton Center for Orphan Diseases, Boston Children’s Hospital, Boston, MA, USA
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Howard Hughes Medical Institute, Boston, MA USA
- Departments of Neurology, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
89
|
Nunney L. The effect of body size and inbreeding on cancer mortality in breeds of the domestic dog: a test of the multi-stage model of carcinogenesis. ROYAL SOCIETY OPEN SCIENCE 2024; 11:231356. [PMID: 38298404 PMCID: PMC10827441 DOI: 10.1098/rsos.231356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 01/02/2024] [Indexed: 02/02/2024]
Abstract
Cancer is a leading cause of death in domestic dogs. Deaths due to cancer vary widely among breeds, providing an opportunity for testing the multi-stage model of carcinogenesis. This model underpins evolutionary and basic studies of cancer suppression and predicts a linear increase in cancer with breed size, an expectation complicated by bigger breeds having a shorter lifespan (decreasing risk). Using three independent datasets, the weight and lifespan of breeds provided a good fit of lifetime cancer mortality to the multi-stage model, the fit suggesting many canine cancers are initiated by four driver mutations. Of 85 breeds in more than one dataset, only flat-coated retriever showed significantly elevated cancer mortality, with Scottish terrier, Bernese mountain dog and bullmastiff also showing notable risk (greater than 50% over expected). Analysis of breed clades suggested terriers experience elevated cancer mortality. There was no evidence that the lower mass-specific metabolic rate of larger breeds reduced cancer risk. Residuals indicated increased breed inbreeding shortened expected lifespan, but had no overall effect on cancer mortality. The results provide a baseline for identifying increased breed risk for specific cancers and demonstrate that, unless selection promotes increased cancer suppression, the evolution of larger longer-lived animals leads to a predictable increased cancer risk.
Collapse
Affiliation(s)
- Leonard Nunney
- Department of Evolution, Ecology, and Organismal Biology, University of California Riverside, 900 University Avenue, Riverside, CA 92521, USA
| |
Collapse
|
90
|
Kay JE, Brody JG, Schwarzman M, Rudel RA. Application of the Key Characteristics Framework to Identify Potential Breast Carcinogens Using Publicly Available in Vivo, in Vitro, and in Silico Data. ENVIRONMENTAL HEALTH PERSPECTIVES 2024; 132:17002. [PMID: 38197648 PMCID: PMC10777819 DOI: 10.1289/ehp13233] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 11/27/2023] [Accepted: 12/04/2023] [Indexed: 01/11/2024]
Abstract
BACKGROUND Chemicals that induce mammary tumors in rodents or activate estrogen or progesterone signaling are likely to increase breast cancer (BC) risk. Identifying chemicals with these activities can prompt steps to protect human health. OBJECTIVES We compiled data on rodent tumors, endocrine activity, and genotoxicity to assess the key characteristics (KCs) of rodent mammary carcinogens (MCs), and to identify other chemicals that exhibit these effects and may therefore increase BC risk. METHODS Using authoritative databases, including International Agency for Research on Cancer (IARC) Monographs and the US Environmental Protection's (EPA) ToxCast, we selected chemicals that induce mammary tumors in rodents, stimulate estradiol or progesterone synthesis, or activate the estrogen receptor (ER) in vitro. We classified these chemicals by their genotoxicity and strength of endocrine activity and calculated the overrepresentation (enrichment) of these KCs among MCs. Finally, we evaluated whether these KCs predict whether a chemical is likely to induce mammary tumors. RESULTS We identified 279 MCs and an additional 642 chemicals that stimulate estrogen or progesterone signaling. MCs were significantly enriched for steroidogenicity, ER agonism, and genotoxicity, supporting the use of these KCs to predict whether a chemical is likely to induce rodent mammary tumors and, by inference, increase BC risk. More MCs were steroidogens than ER agonists, and many increased both estradiol and progesterone. Enrichment among MCs was greater for strong endocrine activity vs. weak or inactive, with a significant trend. DISCUSSION We identified hundreds of compounds that have biological activities that could increase BC risk and demonstrated that these activities are enriched among MCs. We argue that many of these should not be considered low hazard without investigating their ability to affect the breast, and chemicals with the strongest evidence can be targeted for exposure reduction. We describe ways to strengthen hazard identification, including improved assessments for mammary effects, developing assays for more KCs, and more comprehensive chemical testing. https://doi.org/10.1289/EHP13233.
Collapse
Affiliation(s)
| | | | - Megan Schwarzman
- School of Public Health, University of California, Berkeley, Berkeley, California, USA
- Family and Community Medicine, University of California, San Francisco, San Francisco, California, USA
| | | |
Collapse
|
91
|
Abdilleh K, Khalid O, Ladnier D, Wan W, Seepo S, Rupp G, Corelj V, Worman ZF, Sain D, DiGiovanna J, Press B, Chandrashekhar S, Collisson E, Cui KY, Maitra A, Rejto PA, White KP, Matrisian L, Doss S. Pancreatic Cancer Action Network's SPARK: A Cloud-Based Patient Health Data and Analytics Platform for Pancreatic Cancer. JCO Clin Cancer Inform 2024; 8:e2300119. [PMID: 38166233 PMCID: PMC10803046 DOI: 10.1200/cci.23.00119] [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: 06/26/2023] [Revised: 09/06/2023] [Accepted: 11/03/2023] [Indexed: 01/04/2024] Open
Abstract
PURPOSE Pancreatic cancer currently holds the position of third deadliest cancer in the United States and the 5-year survival rate is among the lowest for major cancers at just 12%. Thus, continued research efforts to better understand the clinical and molecular underpinnings of pancreatic cancer are critical to developing both early detection methodologies as well as improved therapeutic options. This study introduces Pancreatic Cancer Action Network's (PanCAN's) SPARK, a cloud-based data and analytics platform that integrates patient health data from the PanCAN's research initiatives and aims to accelerate pancreatic cancer research by making real-world patient health data and analysis tools easier to access and use. MATERIALS AND METHODS The SPARK platform integrates clinical, molecular, multiomic, imaging, and patient-reported data generated from PanCAN's research initiatives. The platform is built on a cloud-based infrastructure powered by Velsera. Cohort exploration and browser capabilities are built using Velsera ARIA, a specialized product for leveraging clinicogenomic data to build cohorts, query variant information, and drive downstream association analyses. Data science and analytic capabilities are also built into the platform allowing researchers to perform simple to complex analysis. RESULTS Version 1 of the SPARK platform was released to pilot users, who represented diverse end users, including molecular biologists, clinicians, and bioinformaticians. Included in the pilot release of SPARK are deidentified clinical (including treatment and outcomes data), molecular, multiomic, and whole-slide pathology images for over 600 patients enrolled in PanCAN's Know Your Tumor molecular profiling service. CONCLUSION The pilot release of the SPARK platform introduces qualified researchers to PanCAN real-world patient health data and analytical resources in a centralized location.
Collapse
Affiliation(s)
| | - Omar Khalid
- Pancreatic Cancer Action Network, Manhattan Beach, CA
| | | | | | | | | | | | | | | | | | | | | | - Eric Collisson
- University of California San Francisco Helen Diller Family Comprehensive Cancer Center, San Francisco, CA
| | | | - Anirban Maitra
- The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | | | | | - Sudheer Doss
- Pancreatic Cancer Action Network, Manhattan Beach, CA
| |
Collapse
|
92
|
Wang K, Lou Y, Tao Z. A New Genetic Signature of Lactate Metabolism-Associated Genes Predicting Clinically Distinctive Features and Tumor Microenvironment in Colorectal Cancer. Cancer Control 2024; 31:10732748241272721. [PMID: 39121198 PMCID: PMC11316264 DOI: 10.1177/10732748241272721] [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: 12/07/2023] [Revised: 06/21/2024] [Accepted: 07/10/2024] [Indexed: 08/11/2024] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is characterized by its high malignancy and challenging prognosis. A significant aspect of cancer is metabolic reprogramming, where lactate serves as a crucial metabolite that contributes to the development of cancer and the tumor microenvironment (TME). Current studies have indicated that lactate plays a significant role in the progression of CRC. However, the relationship between lactate and the tumor microenvironment remains understudied, underscoring the potential of lactate as a novel biomarker. METHODS We sourced transcriptomic data for colorectal cancer (CRC) patients from The Cancer Genome Atlas (TCGA), the International Cancer Genome Consortium (ICGC), and the Gene Expression Omnibus (GEO) portals, along with the corresponding clinical information. Utilizing univariate Cox regression in conjunction with LASSO regression analysis, we identified genes involved in lactate metabolism that are associated with CRC prognosis. Subsequently, we developed models based on multi-factor Cox regression. To evaluate the correlation between tumor mutational burden (TMB), tumor microenvironment (TME), and lactate scores with patient survival, we conducted gene set enrichment analysis (GSEA) and immunogenic signature analyses. RESULTS 3 lactate metabolism-related genes (LMRGs) (SLC16A8, GATA1, and PYGL) were used to construct models that categorized patients into 2 subgroups based on their lactate scores. The function of the differential genes between the 2 subgroups was mainly enriched in cell cycle and mRNA division, and the prognosis of patients in the high score subgroup was poor. Furthermore, a significant positive correlation was observed between TMB and LMRGs scores in the high-scoring group (P = 0.003, r2 = 0.12). Lastly, LMRGs also reflected the characteristics of TME, with differences in immune cells and immune checkpoints between the 2 subgroups. CONCLUSIONS LMRGs may serve as a promising biomarker for predicting prognostic survival in CRC patients and to assess the TME.
Collapse
Affiliation(s)
- Kaiwen Wang
- Department of Oncology, Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yu Lou
- Department of Preventive Treatment of Disease, Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhihui Tao
- Department of Oncology, Seventh People’s Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China
| |
Collapse
|
93
|
Tijhuis AE, Foijer F. Characterizing chromosomal instability-driven cancer evolution and cell fitness at a glance. J Cell Sci 2024; 137:jcs260199. [PMID: 38224461 DOI: 10.1242/jcs.260199] [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] [Indexed: 01/16/2024] Open
Abstract
Chromosomal instability (CIN), an increased rate of chromosome segregation errors during mitosis, is a hallmark of cancer cells. CIN leads to karyotype differences between cells and thus large-scale heterogeneity among individual cancer cells; therefore, it plays an important role in cancer evolution. Studying CIN and its consequences is technically challenging, but various technologies have been developed to track karyotype dynamics during tumorigenesis, trace clonal lineages and link genomic changes to cancer phenotypes at single-cell resolution. These methods provide valuable insight not only into the role of CIN in cancer progression, but also into cancer cell fitness. In this Cell Science at a Glance article and the accompanying poster, we discuss the relationship between CIN, cancer cell fitness and evolution, and highlight techniques that can be used to study the relationship between these factors. To that end, we explore methods of assessing cancer cell fitness, particularly for chromosomally unstable cancer.
Collapse
Affiliation(s)
- Andréa E Tijhuis
- European Research Institute for the Biology of Ageing , University Medical Center Groningen, University of Groningen,9713 AV Groningen, The Netherlands
| | - Floris Foijer
- European Research Institute for the Biology of Ageing , University Medical Center Groningen, University of Groningen,9713 AV Groningen, The Netherlands
| |
Collapse
|
94
|
Arnedo-Pac C, Muiños F, Gonzalez-Perez A, Lopez-Bigas N. Hotspot propensity across mutational processes. Mol Syst Biol 2024; 20:6-27. [PMID: 38177930 PMCID: PMC10883281 DOI: 10.1038/s44320-023-00001-w] [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: 10/05/2023] [Revised: 10/30/2023] [Accepted: 11/09/2023] [Indexed: 01/06/2024] Open
Abstract
The sparsity of mutations observed across tumours hinders our ability to study mutation rate variability at nucleotide resolution. To circumvent this, here we investigated the propensity of mutational processes to form mutational hotspots as a readout of their mutation rate variability at single base resolution. Mutational signatures 1 and 17 have the highest hotspot propensity (5-78 times higher than other processes). After accounting for trinucleotide mutational probabilities, sequence composition and mutational heterogeneity at 10 Kbp, most (94-95%) signature 17 hotspots remain unexplained, suggesting a significant role of local genomic features. For signature 1, the inclusion of genome-wide distribution of methylated CpG sites into models can explain most (80-100%) of the hotspot propensity. There is an increased hotspot propensity of signature 1 in normal tissues and de novo germline mutations. We demonstrate that hotspot propensity is a useful readout to assess the accuracy of mutation rate models at nucleotide resolution. This new approach and the findings derived from it open up new avenues for a range of somatic and germline studies investigating and modelling mutagenesis.
Collapse
Affiliation(s)
- Claudia Arnedo-Pac
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
| | - Ferran Muiños
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
| | - Abel Gonzalez-Perez
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain.
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain.
| | - Nuria Lopez-Bigas
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain.
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain.
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
- Department of Medicine and Life Sciences (MELIS), Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| |
Collapse
|
95
|
Weeks LD, Ebert BL. Causes and consequences of clonal hematopoiesis. Blood 2023; 142:2235-2246. [PMID: 37931207 PMCID: PMC10862247 DOI: 10.1182/blood.2023022222] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 10/25/2023] [Accepted: 10/25/2023] [Indexed: 11/08/2023] Open
Abstract
ABSTRACT Clonal hematopoiesis (CH) is described as the outsized contribution of expanded clones of hematopoietic stem and progenitor cells (HSPCs) to blood cell production. The prevalence of CH increases dramatically with age. CH can be caused by somatic mutations in individual genes or by gains and/or losses of larger chromosomal segments. CH is a premalignant state; the somatic mutations detected in CH are the initiating mutations for hematologic malignancies, and CH is a strong predictor of the development of blood cancers. Moreover, CH is associated with nonmalignant disorders and increased overall mortality. The somatic mutations that drive clonal expansion of HSPCs can alter the function of terminally differentiated blood cells, including the release of elevated levels of inflammatory cytokines. These cytokines may then contribute to a broad range of inflammatory disorders that increase in prevalence with age. Specific somatic mutations in the peripheral blood in coordination with blood count parameters can powerfully predict the development of hematologic malignancies and overall mortality in CH. In this review, we summarize the current understanding of CH nosology and origins. We provide an overview of available tools for risk stratification and discuss management strategies for patients with CH presenting to hematology clinics.
Collapse
Affiliation(s)
- Lachelle D. Weeks
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
- Center for Early Detection and Interception of Blood Cancers, Dana-Farber Cancer Institute, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Benjamin L. Ebert
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
- Center for Early Detection and Interception of Blood Cancers, Dana-Farber Cancer Institute, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Howard Hughes Medical Institute, Boston, MA
| |
Collapse
|
96
|
Deneuve S, Fervers B, Senkin S, Bouaoun L, Pérol O, Chavanel B, Lu L, Coste I, Renno T, Zavadil J, Virard F. Molecular landscapes of oral cancers of unknown etiology. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.15.23299866. [PMID: 38168303 PMCID: PMC10760302 DOI: 10.1101/2023.12.15.23299866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
The incidence of the mobile tongue cancer in young patients has been rising. This oral cancer (OC) type has no identified risk factors (NIRF), no established molecular markers and is not yet recognized as a distinct clinical entity. To understand this emerging malignancy, we innovatively analyzed the public head and neck cancer multi-omics data. We identified mutational signatures that successfully stratified 307 OC and 109 laryngeal cancer cases according to their clinico-pathological characteristics. The NIRF OCs exhibited significantly increased activities of endogenous clock-like and APOBEC-associated mutagenesis, alongside specific cancer driver gene mutations, distinct methylome patterns and prominent antimicrobial transcriptomic responses. Furthermore, we show that mutational signature SBS16 in OCs reflects the combined effects of alcohol drinking and tobacco smoking. Our study characterizes the unique disease histories and molecular programs of the NIRF OCs revealing that this emerging cancer subtype is likely driven by increased endogenous mutagenesis correlated with responses to microbial insults.
Collapse
|
97
|
Demajo S, Ramis-Zaldivar JE, Muiños F, Grau ML, Andrianova M, López-Bigas N, González-Pérez A. Identification of Clonal Hematopoiesis Driver Mutations through In Silico Saturation Mutagenesis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.13.23299893. [PMID: 38168256 PMCID: PMC10760256 DOI: 10.1101/2023.12.13.23299893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Clonal hematopoiesis (CH) is a phenomenon of clonal expansion of hematopoietic stem cells driven by somatic mutations affecting certain genes. Recently, CH has been linked to the development of a number of hematologic malignancies, cardiovascular diseases and other conditions. Although the most frequently mutated CH driver genes have been identified, a systematic landscape of the mutations capable of initiating this phenomenon is still lacking. Here, we train high-quality machine-learning models for 12 of the most recurrent CH driver genes to identify their driver mutations. These models outperform an experimental base-editing approach and expert-curated rules based on prior knowledge of the function of these genes. Moreover, their application to identify CH driver mutations across almost half a million donors of the UK Biobank reproduces known associations between CH driver mutations and age, and the prevalence of several diseases and conditions. We thus propose that these models support the accurate identification of CH across healthy individuals.
Collapse
Affiliation(s)
- Santiago Demajo
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
| | - Joan Enric Ramis-Zaldivar
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Ferran Muiños
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
| | - Miguel L Grau
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Maria Andrianova
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
| | - Núria López-Bigas
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Abel González-Pérez
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Baldiri Reixac, 10, 08028 Barcelona, Spain
- Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Instituto de Salud Carlos III, Madrid, Spain
| |
Collapse
|
98
|
Chapdelaine AG, Ku GC, Sun G, Ayrapetov MK. The Targeted Degradation of BRAF V600E Reveals the Mechanisms of Resistance to BRAF-Targeted Treatments in Colorectal Cancer Cells. Cancers (Basel) 2023; 15:5805. [PMID: 38136350 PMCID: PMC10741866 DOI: 10.3390/cancers15245805] [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: 11/07/2023] [Revised: 12/08/2023] [Accepted: 12/09/2023] [Indexed: 12/24/2023] Open
Abstract
The BRAF V600E mutation is frequently found in cancer. It activates the MAPK pathway and promotes cancer cell proliferation, making BRAF an excellent target for anti-cancer therapy. While BRAF-targeted therapy is highly effective for melanoma, it is often ineffective against other cancers harboring the BRAF mutation. In this study, we evaluate the effectiveness of a proteolysis targeting chimera (PROTAC), SJF-0628, in directing the degradation of mutated BRAF across a diverse panel of cancer cells and determine how these cells respond to the degradation. SJF-0628 treatment results in the degradation of BRAF V600E and a decrease in Mek activation in all cell lines tested, but the effects of the treatment on cell signaling and cell proliferation are cell-line-specific. First, BRAF degradation killed DU-4475 and Colo-205 cells via apoptosis but only partially inhibited the proliferation of other cancer cell lines. Second, SJF-0628 treatment resulted in co-degradation of MEK in Colo-205 cells but did not have the same effect in other cell lines. Finally, cell lines partially inhibited by BRAF degradation also contain other oncogenic drivers, making them multi-driver cancer cells. These results demonstrate the utility of a PROTAC to direct BRAF degradation and reveal that multi-driver oncogenesis renders some colorectal cancer cells resistant to BRAF-targeted treatment.
Collapse
Affiliation(s)
| | | | - Gongqin Sun
- Department of Cell and Molecular Biology, University of Rhode Island, Kingston, RI 02881, USA; (A.G.C.); (G.C.K.)
| | | |
Collapse
|
99
|
Huang KK, Ma H, Chong RHH, Uchihara T, Lian BSX, Zhu F, Sheng T, Srivastava S, Tay ST, Sundar R, Tan ALK, Ong X, Lee M, Ho SWT, Lesluyes T, Ashktorab H, Smoot D, Van Loo P, Chua JS, Ramnarayanan K, Lau LHS, Gotoda T, Kim HS, Ang TL, Khor C, Lee JWJ, Tsao SKK, Yang WL, Teh M, Chung H, So JBY, Yeoh KG, Tan P. Spatiotemporal genomic profiling of intestinal metaplasia reveals clonal dynamics of gastric cancer progression. Cancer Cell 2023; 41:2019-2037.e8. [PMID: 37890493 PMCID: PMC10729843 DOI: 10.1016/j.ccell.2023.10.004] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 08/08/2023] [Accepted: 10/06/2023] [Indexed: 10/29/2023]
Abstract
Intestinal metaplasia (IM) is a pre-malignant condition of the gastric mucosa associated with increased gastric cancer (GC) risk. Analyzing 1,256 gastric samples (1,152 IMs) across 692 subjects from a prospective 10-year study, we identify 26 IM driver genes in diverse pathways including chromatin regulation (ARID1A) and intestinal homeostasis (SOX9). Single-cell and spatial profiles highlight changes in tissue ecology and IM lineage heterogeneity, including an intestinal stem-cell dominant cellular compartment linked to early malignancy. Expanded transcriptome profiling reveals expression-based molecular subtypes of IM associated with incomplete histology, antral/intestinal cell types, ARID1A mutations, inflammation, and microbial communities normally associated with the healthy oral tract. We demonstrate that combined clinical-genomic models outperform clinical-only models in predicting IMs likely to transform to GC. By highlighting strategies for accurately identifying IM patients at high GC risk and a role for microbial dysbiosis in IM progression, our results raise opportunities for GC precision prevention and interception.
Collapse
Affiliation(s)
- Kie Kyon Huang
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Haoran Ma
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Roxanne Hui Heng Chong
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Tomoyuki Uchihara
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Benedict Shi Xiang Lian
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Feng Zhu
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Taotao Sheng
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Supriya Srivastava
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Su Ting Tay
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Raghav Sundar
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore; Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore; Department of Haematology-Oncology, National University Health System, Singapore 119074, Singapore
| | - Angie Lay Keng Tan
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Xuewen Ong
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Minghui Lee
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Shamaine Wei Ting Ho
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | | | | | - Duane Smoot
- Department of Internal Medicine, Meharry Medical College, Nashville, TN, USA
| | - Peter Van Loo
- The Francis Crick Institute, London, UK; Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Joy Shijia Chua
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Kalpana Ramnarayanan
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore
| | - Louis Ho Shing Lau
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong
| | - Takuji Gotoda
- Division of Gastroenterology and Hepatology, Department of Medicine, Nihon University School of Medicine, Tokyo, Japan
| | - Hyun Soo Kim
- Department of Internal Medicine, Yonsei University Wonju College of Medicine, Seoul, Korea
| | - Tiing Leong Ang
- Department of Gastroenterology & Hepatology, Changi General Hospital, Singapore 529889, Singapore
| | - Christopher Khor
- Department of Gastroenterology & Hepatology, Singapore General Hospital, Singapore 169854, Singapore
| | - Jonathan Wei Jie Lee
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore; iHealthtech, National University of Singapore, Singapore, Singapore; SynCTI, National University of Singapore, Singapore 117599, Singapore; Department of Gastroenterology & Hepatology, National University Hospital, Singapore 119074, Singapore
| | - Stephen Kin Kwok Tsao
- Department of Gastroenterology & Hepatology, Tan Tock Seng Hospital, Singapore 308433, Singapore
| | - Wei Lyn Yang
- Department of Gastroenterology & Hepatology, Tan Tock Seng Hospital, Singapore 308433, Singapore
| | - Ming Teh
- Department of Pathology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
| | - Hyunsoo Chung
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea.
| | - Jimmy Bok Yan So
- Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore; NUS Centre for Cancer Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore; Division of Surgical Oncology, National University Cancer Institute of Singapore (NCIS), Singapore, Singapore.
| | - Khay Guan Yeoh
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore; Department of Gastroenterology & Hepatology, National University Hospital, Singapore 119074, Singapore.
| | - Patrick Tan
- Program in Cancer and Stem Cell Biology, Duke-NUS Medical School, Singapore 169857, Singapore; Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore; Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore; Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117593, Singapore; Cellular and Molecular Research, National Cancer Centre, Singapore, Singapore; Singhealth/Duke-NUS Institute of Precision Medicine, National Heart Centre Singapore, Singapore 168752, Singapore.
| |
Collapse
|
100
|
Chang J, Zhao X, Wang Y, Liu T, Zhong C, Lao Y, Zhang S, Liao H, Bai F, Lin D, Wu C. Genomic alterations driving precancerous to cancerous lesions in esophageal cancer development. Cancer Cell 2023; 41:2038-2050.e5. [PMID: 38039962 DOI: 10.1016/j.ccell.2023.11.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 07/26/2023] [Accepted: 11/04/2023] [Indexed: 12/03/2023]
Abstract
Esophageal squamous cell carcinoma (ESCC) develops through a series of increasingly abnormal precancerous lesions. Previous studies have revealed the striking differences between normal esophageal epithelium and ESCC in copy number alterations (CNAs) and mutations in genes driving clonal expansion. However, due to limited data on early precancerous lesions, the timing of these transitions and which among them are prerequisites for malignant transformation remained unclear. Here, we analyze 1,275 micro-biopsies from normal esophagus, early and late precancerous lesions, and esophageal cancers to decipher the genomic alterations at each stage. We show that the frequency of TP53 biallelic inactivation increases dramatically in early precancerous lesion stage while CNAs and APOBEC mutagenesis substantially increase at late stages. TP53 biallelic loss is the prerequisite for the development of CNAs of genes in cell cycle, DNA repair, and apoptosis pathways, suggesting it might be one of the earliest steps initiating malignant transformation.
Collapse
Affiliation(s)
- Jiang Chang
- Department of Health Toxicology, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
| | - Xuan Zhao
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China
| | - Yichen Wang
- Cancer, Ageing and Somatic Mutation, Wellcome Sanger Institute, Hinxton, UK
| | - Tianyuan Liu
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China
| | - Ce Zhong
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China
| | - Yueqiong Lao
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China
| | - Shaosen Zhang
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China
| | - Han Liao
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China
| | - Fan Bai
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing 100871, China; Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing 100871, China; Center for Translational Cancer Research, Peking University First Hospital, Beijing 100034, China.
| | - Dongxin Lin
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China; Key Laboratory of Cancer Genomic Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China; Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Guangzhou 510060, China.
| | - Chen Wu
- Department of Etiology and Carcinogenesis, National Cancer Center/National Clinical Research Center/Cancer Hospital, Chinese Academy of Medical Sciences (CAMS) and Peking Union Medical College (PUMC), Beijing 100021, China; Key Laboratory of Cancer Genomic Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China; Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, China; CAMS Oxford Institute, Chinese Academy of Medical Sciences, Beijing 100006, China.
| |
Collapse
|