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Choi J, Park KH, Kim YH, Sa JK, Sung HJ, Chen YW, Chen Z, Li C, Wen W, Zhang Q, Shu XO, Zheng W, Kim JS, Guo X. Large-Scale Cancer Genomic Analysis Reveals Significant Disparities between Microsatellite Instability and Tumor Mutational Burden. Cancer Epidemiol Biomarkers Prev 2024; 33:712-720. [PMID: 38393316 DOI: 10.1158/1055-9965.epi-23-1466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 01/23/2024] [Accepted: 02/20/2024] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND Microsatellite instability (MSI) and tumor mutational burden (TMB) are predictive biomarkers for pan-cancer immunotherapy. The interrelationship between MSI-high (MSI-H) and TMB-high (TMB-H) in human cancers and their predictive value for immunotherapy in lung cancer remain unclear. METHODS We analyzed somatic mutation data from the Genomics Evidence Neoplasia Information Exchange (n = 46,320) to determine the relationship between MSI-H and TMB-H in human cancers using adjusted multivariate regression models. Patient survival was examined using the Cox proportional hazards model. The association between MSI and genetic mutations was assessed. RESULTS Patients (31-89%) with MSI-H had TMB-low phenotypes across 22 cancer types. Colorectal and stomach cancers showed the strongest association between TMB and MSI. TMB-H patients with lung cancer who received immunotherapy exhibited significantly higher overall survival [HR, 0.61; 95% confidence interval (CI), 0.44-0.86] and progression-free survival (HR, 0.65; 95% CI, 0.47-0.91) compared to the TMB-low group; no significant benefit was observed in the MSI-H group. Patients with TMB and MSI phenotypes showed further improvement in overall survival and PFS. We identified several mutated genes associated with MSI-H phenotypes, including known mismatch repair genes and novel mutated genes, such as ARID1A and ARID1B. CONCLUSIONS Our results demonstrate that TMB-H and/or a combination of MSI-H can serve as biomarkers for immunotherapies in lung cancer. IMPACT These findings suggest that distinct or combined biomarkers should be considered for immunotherapy in human cancers because notable discrepancies exist between MSI-H and TMB-H across different cancer types.
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Affiliation(s)
- Jungyoon Choi
- Division of Oncology/Hematology, Department of Internal Medicine, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Republic of Korea
| | - Kyong Hwa Park
- Division of Oncology/Hematology, Department of Internal Medicine, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Yeul Hong Kim
- Division of Oncology/Hematology, Department of Internal Medicine, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Jason K Sa
- BK21 Graduate Program, Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Hwa Jung Sung
- Division of Oncology/Hematology, Department of Internal Medicine, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Republic of Korea
| | - Yu-Wei Chen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Zhishan Chen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Chao Li
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Qingrun Zhang
- Department of Mathematics and Statistics, Alberta Children's Hospital Research Institute, Arnie Charbonneau Cancer Institute, University of Calgary, Calgary, Canada
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Jung Sun Kim
- Division of Oncology/Hematology, Department of Internal Medicine, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Republic of Korea
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee
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2
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Yin G, Liu L, Yu T, Yu L, Feng M, Zhou C, Wang X, Teng G, Ma Z, Zhou W, Ye C, Zhang J, Ji C, Zhao L, Zhou P, Guo Y, Meng X, Fu Q, Zhang Q, Li L, Zhou F, Zheng C, Xiang Y, Guo M, Wang Y, Wang F, Huang S, Yu Z. Genomic and transcriptomic analysis of breast cancer identifies novel signatures associated with response to neoadjuvant chemotherapy. Genome Med 2024; 16:11. [PMID: 38217005 PMCID: PMC10787499 DOI: 10.1186/s13073-024-01286-8] [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: 07/24/2023] [Accepted: 01/09/2024] [Indexed: 01/14/2024] Open
Abstract
BACKGROUND Neoadjuvant chemotherapy (NAC) has become a standard treatment strategy for breast cancer (BC). However, owing to the high heterogeneity of these tumors, it is unclear which patient population most likely benefit from NAC. Multi-omics offer an improved approach to uncovering genomic and transcriptomic changes before and after NAC in BC and to identifying molecular features associated with NAC sensitivity. METHODS We performed whole-exome and RNA sequencing on 233 samples (including matched pre- and post-treatment tumors) from 50 BC patients with rigorously defined responses to NAC and analyzed changes in the multi-omics landscape. Molecular features associated with NAC response were identified and validated in a larger internal, and two external validation cohorts, as well as in vitro experiments. RESULTS The most frequently altered genes were TP53, TTN, and MUC16 in both pre- and post-treatment tumors. In comparison with pre-treatment tumors, there was a significant decrease in C > A transversion mutations in post-treatment tumors (P = 0.020). NAC significantly decreased the mutation rate (P = 0.006) of the DNA repair pathway and gene expression levels (FDR = 0.007) in this pathway. NAC also significantly changed the expression level of immune checkpoint genes and the abundance of tumor-infiltrating immune and stroma cells, including B cells, activated dendritic cells, γδT cells, M2 macrophages and endothelial cells. Furthermore, there was a higher rate of C > T substitutions in NAC nonresponsive tumors than responsive ones, especially when the substitution site was flanked by C and G. Importantly, there was a unique amplified region at 8p11.23 (containing ADGRA2 and ADRB3) and a deleted region at 3p13 (harboring FOXP1) in NAC nonresponsive and responsive tumors, respectively. Particularly, the CDKAL1 missense variant P409L (p.Pro409Leu, c.1226C > T) decreased BC cell sensitivity to docetaxel, and ADGRA2 or ADRB3 gene amplifications were associated with worse NAC response and poor prognosis in BC patients. CONCLUSIONS Our study has revealed genomic and transcriptomic landscape changes following NAC in BC, and identified novel biomarkers (CDKAL1P409L, ADGRA2 and ADRB3) underlying chemotherapy resistance and poor prognosis, which could guide the development of personalized treatments for BC.
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Affiliation(s)
- Gengshen Yin
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Liyuan Liu
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Ting Yu
- Research Center for Mathematics and Interdisciplinary Sciences, Shandong University, Qingdao, 266237, China
| | - Lixiang Yu
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Man Feng
- Department of Pathology, The Third Affiliated Hospital of Shandong First Medical University (Affiliated Hospital of Shandong Academy of Medical Sciences), Jinan, 250031, China
| | - Chengjun Zhou
- Department of Pathology, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Xiaoying Wang
- Department of Pathology, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Guoxin Teng
- Department of Pathology, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Zhongbing Ma
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Wenzhong Zhou
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Chunmiao Ye
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Jialin Zhang
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Changhua Ji
- Department of Pathology, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Linfeng Zhao
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Institute of Medical Sciences, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Peng Zhou
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Yaxun Guo
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
| | - Xingchen Meng
- Department of Breast Surgery, Weifang People's Hospital, Weifang, 261041, China
| | - Qinye Fu
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Qiang Zhang
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Liang Li
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Fei Zhou
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Chao Zheng
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Yujuan Xiang
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Mingming Guo
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Yongjiu Wang
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China
| | - Fei Wang
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China.
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China.
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China.
| | - Shuya Huang
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China.
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China.
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China.
| | - Zhigang Yu
- Department of Breast Surgery, The Second Hospital of Shandong University, Jinan, 250033, China.
- Institute of Translational Medicine of Breast Disease Prevention and Treatment, Shandong University, Jinan, 250033, China.
- Shandong Provincial Engineering Laboratory of Translational Research On Prevention and Treatment of Breast Disease, Jinan, 250033, China.
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Ugai T, Haruki K, Harrison TA, Cao Y, Qu C, Chan AT, Campbell PT, Akimoto N, Berndt S, Brenner H, Buchanan DD, Chang-Claude J, Fujiyoshi K, Gallinger SJ, Gunter MJ, Hidaka A, Hoffmeister M, Hsu L, Jenkins MA, Milne RL, Moreno V, Newcomb PA, Nishihara R, Pai RK, Sakoda LC, Slattery ML, Sun W, Amitay EL, Alwers E, Thibodeau SN, Toland AE, Van Guelpen B, Woods MO, Zaidi SH, Potter JD, Giannakis M, Song M, Nowak JA, Phipps AI, Peters U, Ogino S. Molecular Characteristics of Early-Onset Colorectal Cancer According to Detailed Anatomical Locations: Comparison With Later-Onset Cases. Am J Gastroenterol 2023; 118:712-726. [PMID: 36707929 PMCID: PMC10065351 DOI: 10.14309/ajg.0000000000002171] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 12/16/2022] [Indexed: 01/29/2023]
Abstract
INTRODUCTION Early-onset colorectal cancer diagnosed before the age of 50 years has been increasing. Likely reflecting the pathogenic role of the intestinal microbiome, which gradually changes across the entire colorectal length, the prevalence of certain tumor molecular characteristics gradually changes along colorectal subsites. Understanding how colorectal tumor molecular features differ by age and tumor location is important in personalized patient management. METHODS Using 14,004 cases with colorectal cancer including 3,089 early-onset cases, we examined microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and KRAS and BRAF mutations in carcinomas of the cecum, ascending colon, transverse colon, descending colon, sigmoid colon, and rectum and compared early-onset cases with later-onset cases. RESULTS The proportions of MSI-high, CIMP-high, and BRAF -mutated early-onset tumors were lowest in the rectum (8.8%, 3.4%, and 3.5%, respectively) and highest in the ascending colon (46% MSI-high; 15% CIMP-high) or transverse colon (8.6% BRAF -mutated) (all Ptrend <0.001 across the rectum to ascending colon). Compared with later-onset tumors, early-onset tumors showed a higher prevalence of MSI-high status and a lower prevalence of CIMP-high status and BRAF mutations in most subsites. KRAS mutation prevalence was higher in the cecum compared with that in the other subsites in both early-onset and later-onset tumors ( P < 0.001). Notably, later-onset MSI-high tumors showed a continuous decrease in KRAS mutation prevalence from the rectum (36%) to ascending colon (9%; Ptrend <0.001), followed by an increase in the cecum (14%), while early-onset MSI-high cancers showed no such trend. DISCUSSION Our findings support biogeographical and pathogenic heterogeneity of colorectal carcinomas in different colorectal subsites and age groups.
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Affiliation(s)
- Tomotaka Ugai
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Koichiro Haruki
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Tabitha A. Harrison
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Yin Cao
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St Louis, MO
- Division of Gastroenterology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
| | - Conghui Qu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Andrew T. Chan
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA
- Division of Gastroenterology, Massachusetts General Hospital, Boston, MA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Peter T. Campbell
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Naohiko Akimoto
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Sonja Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daniel D. Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria, Australia
- Genetic Medicine and Family Cancer Clinic, The Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- University Medical Centre Hamburg-Eppendorf, University Cancer Centre Hamburg (UCCH), Hamburg, Germany
| | - Kenji Fujiyoshi
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Steven J. Gallinger
- Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Marc J. Gunter
- Nutrition and Metabolism Section, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Akihisa Hidaka
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Li Hsu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Mark A. Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Roger L. Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Victor Moreno
- Oncology Data Analytics Program, Catalan Institute of Oncology (IDIBELL), L’Hospitalet de Llobregat, Barcelona, Spain
- CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute-IDIBELL, Hospitalet de Llobregat, Barcelona, Spain
| | - Polly A. Newcomb
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Reiko Nishihara
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Rish K. Pai
- Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Scottsdale, AZ
| | - Lori C. Sakoda
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | | | - Wei Sun
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Efrat L. Amitay
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Elizabeth Alwers
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stephen N. Thibodeau
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Amanda E. Toland
- Departments of Cancer Biology and Genetics and Internal Medicine, Comprehensive Cancer Center, The Ohio State University, Columbus, OH
| | - Bethany Van Guelpen
- Department of Radiation Sciences, Oncology Unit, Umeå University, Umeå, Sweden
- Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Michael O. Woods
- Memorial University of Newfoundland, Discipline of Genetics, St. John’s, Canada
| | - Syed H. Zaidi
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - John D. Potter
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Marios Giannakis
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA
- Broad Institute of MIT and Harvard, Cambridge, MA
| | - Mingyang Song
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St Louis, MO
- Division of Gastroenterology, Department of Medicine, Washington University School of Medicine, St. Louis, MO
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Jonathan A. Nowak
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Amanda I. Phipps
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA
| | - Shuji Ogino
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- Broad Institute of MIT and Harvard, Cambridge, MA
- Cancer Immunology and Cancer Epidemiology Programs, Dana-Farber Harvard Cancer Center, Boston, MA
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Holowatyj AN, Washington MK, Tavtigian SV, Eng C, Horton C. Inherited Cancer Susceptibility Gene Sequence Variations Among Patients With Appendix Cancer. JAMA Oncol 2022; 9:2798729. [PMID: 36368039 PMCID: PMC9652767 DOI: 10.1001/jamaoncol.2022.5425] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 09/05/2022] [Indexed: 11/13/2022]
Abstract
Importance Germline sequence variations in APC, BMPR1A, CDH1, CHEK2, EPCAM, MLH1, MSH2, MSH6, MUTYH, PMS2, PTEN, SMAD4, STK11, and TP53 genes are associated with susceptibility to gastrointestinal cancers. As a rare cancer, the evaluation of appendiceal cancer (AC) predisposition has been limited. Objective To assess the prevalence and spectrum of inherited cancer susceptibility gene sequence variations in patients with AC and the utility of germline genetic testing for this population. Design, Setting, and Participants This cohort study included patients with AC who underwent germline genetic testing of 14 cancer susceptibility genes performed by a clinical testing laboratory between March 1, 2012, and December 31, 2016. Data were analyzed from March to August 2022. Clinical, individual, and family histories were obtained from clinician-completed test requisition forms. Multigene panel testing was performed by targeted custom capture and sequencing and chromosome rearrangement analysis. Main Outcomes and Measures The main outcomes were germline sequence variation prevalence and spectrum in patients with AC. Results Among the 131 patients with AC in the cohort (90 female [68.7%]), a total of 16 deleterious sequence variations were identified in 15 patients (11.5%). Similarly, when limited to the 74 patients with AC as the first and only primary tumor, a total of 8 patients (10.8%) had at least 1 deleterious sequence variation in a cancer susceptibility gene. Overall, 6 patients (4.6%) had a deleterious sequence variation observed in MUTYH (5 with monoallelic MUTYH and 1 with biallelic MUTYH). All 4 patients with Lynch syndrome (3.1%) had a sequence variation in the MLH1 gene, of whom 3 were aged 50 years or older at AC diagnosis. Five patients (3.8%) had deleterious sequence variations in other cancer predisposition genes (1 with APC [c.3920T>A, p.I1307K], 2 with CHEK2 [c.470T>C, p.I157T], 1 with SMAD4 [c.263 287dup, p.L98IFS*14], and 1 with TP53 [c.524G>A, p.R175H]). Conclusions and Relevance In this cohort study, 1 in every 10 patients with AC who underwent testing for hereditary cancer predisposition carried an inherited gene sequence variation associated with cancer susceptibility. Given the high frequency and broad spectrum of germline gene sequence variations, these data suggest that genetic evaluation might be warranted for all patients diagnosed with this rare malignant tumor. A systemic sequencing effort for all patients with AC may also identify cancer vulnerabilities to exploit for therapeutic development in a cancer type for which clinical trials are limited.
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Affiliation(s)
- Andreana N. Holowatyj
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
- Department of Population Health Sciences, University of Utah, Salt Lake City
| | - Mary K. Washington
- Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sean V. Tavtigian
- Department of Oncological Sciences, University of Utah, Salt Lake City
| | - Cathy Eng
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
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Weitz J, Hurtado de Mendoza T, Tiriac H, Lee J, Sun S, Garg B, Patel J, Li K, Baumgartner J, Kelly KJ, Veerapong J, Hosseini M, Chen Y, Lowy AM. An Ex Vivo Organotypic Culture Platform for Functional Interrogation of Human Appendiceal Cancer Reveals a Prominent and Heterogenous Immunological Landscape. Clin Cancer Res 2022; 28:4793-4806. [PMID: 36067351 DOI: 10.1158/1078-0432.ccr-22-0980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 04/04/2022] [Accepted: 08/31/2022] [Indexed: 01/24/2023]
Abstract
PURPOSE Epithelial neoplasms of the appendix are difficult to study preclinically given their low incidence, frequent mucinous histology, and absence of a comparable organ in mice for disease modeling. Although surgery is an effective treatment for localized disease, metastatic disease has a poor prognosis as existing therapeutics borrowed from colorectal cancer have limited efficacy. Recent studies reveal that appendiceal cancer has a genomic landscape distinct from colorectal cancer and thus preclinical models to study this disease are a significant unmet need. EXPERIMENTAL DESIGN We adopted an ex vivo slice model that permits the study of cellular interactions within the tumor microenvironment. Mucinous carcinomatosis peritonei specimens obtained at surgical resection were cutoff using a vibratome to make 150-μm slices cultured in media. RESULTS Slice cultures were viable and maintained their cellular composition regarding the proportion of epithelial, immune cells, and fibroblasts over 7 days. Within donor specimens, we identified a prominent and diverse immune landscape and calcium imaging confirmed that immune cells were functional for 7 days. Given the diverse immune landscape, we treated slices with TAK981, an inhibitor of SUMOylation with known immunomodulatory functions, in early-phase clinical trials. In 5 of 6 donor samples, TAK981-treated slices cultures had reduced viability, and regulatory T cells (Treg). These data were consistent with TAK981 activity in purified Tregs using an in vitro murine model. CONCLUSIONS This study demonstrates an approach to study appendiceal cancer therapeutics and pathobiology in a preclinical setting. These methods may be broadly applicable to the study of other malignancies.
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Affiliation(s)
- Jonathan Weitz
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
| | - Tatiana Hurtado de Mendoza
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
| | - Herve Tiriac
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
| | - James Lee
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
| | - Siming Sun
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
| | - Bharti Garg
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
| | - Jay Patel
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
| | - Kevin Li
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
| | - Joel Baumgartner
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
| | - Kaitlin J Kelly
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
| | - Jula Veerapong
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
| | - Mojgan Hosseini
- Department of Pathology and Laboratory Medicine, University of California, San Diego, California
| | - Yuan Chen
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
| | - Andrew M Lowy
- Division of Surgical Oncology, Department of Surgery, Moores Cancer Center, University of California, San Diego, California
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6
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Pugh TJ, Bell JL, Bruce JP, Doherty GJ, Galvin M, Green MF, Hunter-Zinck H, Kumari P, Lenoue-Newton ML, Li MM, Lindsay J, Mazor T, Ovalle A, Sammut SJ, Schultz N, Yu TV, Sweeney SM, Bernard B. AACR Project GENIE: 100,000 Cases and Beyond. Cancer Discov 2022; 12:2044-2057. [PMID: 35819403 PMCID: PMC9437568 DOI: 10.1158/2159-8290.cd-21-1547] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 05/20/2022] [Accepted: 07/07/2022] [Indexed: 01/26/2023]
Abstract
The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) is an international pan-cancer registry with the goal to inform cancer research and clinical care worldwide. Founded in late 2015, the milestone GENIE 9.1-public release contains data from >110,000 tumors from >100,000 people treated at 19 cancer centers from the United States, Canada, the United Kingdom, France, the Netherlands, and Spain. Here, we demonstrate the use of these real-world data, harmonized through a centralized data resource, to accurately predict enrollment on genome-guided trials, discover driver alterations in rare tumors, and identify cancer types without actionable mutations that could benefit from comprehensive genomic analysis. The extensible data infrastructure and governance framework support additional deep patient phenotyping through biopharmaceutical collaborations and expansion to include new data types such as cell-free DNA sequencing. AACR Project GENIE continues to serve a global precision medicine knowledge base of increasing impact to inform clinical decision-making and bring together cancer researchers internationally. SIGNIFICANCE AACR Project GENIE has now accrued data from >110,000 tumors, placing it among the largest repository of publicly available, clinically annotated genomic data in the world. GENIE has emerged as a powerful resource to evaluate genome-guided clinical trial design, uncover drivers of cancer subtypes, and inform real-world use of genomic data. This article is highlighted in the In This Issue feature, p. 2007.
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Affiliation(s)
- Trevor J. Pugh
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.,Ontario Institute for Cancer Research, Toronto, Ontario, Canada.,University of Toronto, Toronto, Ontario, Canada.,Corresponding Authors: Trevor J. Pugh, Princess Margaret Cancer Centre, University Health Network, MaRS Centre, 101 College Street, Toronto, Ontario M5G 1L7, Canada. Phone: 416-946-2000; E-mail: ; and Brady Bernard, 4805 NE Glisan Street, Suite 2N35, Portland, OR 97213. Phone: 503-215-6588; E-mail:
| | | | - Jeff P. Bruce
- Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada
| | - Gary J. Doherty
- Cancer Research United Kingdom (CRUK) Cambridge Centre, Cambridge, United Kingdom.,Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Matthew Galvin
- Earle A. Chiles Research Institute, Portland, Oregon.,Providence Cancer Institute, Portland, Oregon
| | | | | | - Priti Kumari
- Dana-Farber Cancer Institute, Boston, Massachusetts
| | - Michele L. Lenoue-Newton
- Vanderbilt University Medical Center, Nashville, Tennessee.,Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
| | - Marilyn M. Li
- The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.,University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania
| | | | - Tali Mazor
- Dana-Farber Cancer Institute, Boston, Massachusetts
| | | | - Stephen-John Sammut
- Cancer Research United Kingdom (CRUK) Cambridge Centre, Cambridge, United Kingdom.,Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | | | | | - Shawn M. Sweeney
- American Association for Cancer Research, Philadelphia, Pennsylvania
| | - Brady Bernard
- Earle A. Chiles Research Institute, Portland, Oregon.,Providence Cancer Institute, Portland, Oregon.,Corresponding Authors: Trevor J. Pugh, Princess Margaret Cancer Centre, University Health Network, MaRS Centre, 101 College Street, Toronto, Ontario M5G 1L7, Canada. Phone: 416-946-2000; E-mail: ; and Brady Bernard, 4805 NE Glisan Street, Suite 2N35, Portland, OR 97213. Phone: 503-215-6588; E-mail:
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7
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Choi J, Holowatyj AN, Du M, Chen Z, Wen W, Schultz N, Lipworth L, Guo X. Distinct Genomic Landscapes in Early-Onset and Late-Onset Endometrial Cancer. JCO Precis Oncol 2022; 6:e2100401. [PMID: 35108035 PMCID: PMC8820918 DOI: 10.1200/po.21.00401] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 11/26/2021] [Accepted: 12/22/2021] [Indexed: 02/04/2023] Open
Abstract
PURPOSE The spectrum of somatic mutations among women with endometrial cancer (EC) younger than 50 years (early-onset EC) remains unknown. We investigated distinct somatic mutation patterns among early-onset and late-onset (age ≥ 50 years) EC patients. METHODS This cohort study included individuals age 18+ years diagnosed with pathologically confirmed EC in the American Association of Cancer Research (AACR) Genomics Evidence Neoplasia Information Exchange (GENIE, v9.1) consortium. We explored tumor mutational burden (TMB) and genomic patterns of EC by age at clinical sequencing using multivariable regression models adjusted for race, ethnicity, histology, sequencing assay, sample type, and TMB. RESULTS Among 2,425 women with EC, 176 (7.3%) had early-onset EC and 1,923 (79.3%) had nonhypermutated (< 17.78 mutations/Mb) tumors. TMB significantly differed across age and histology groups. Among nonhypermutated ECs, early-onset patients had significantly lower odds of presenting with nonsilent FGFR2 and PIK3R1 somatic mutations compared with late-onset EC patients in adjusted models (FGFR2: odds ratio [OR] = 0.18, 95% CI, 0.04 to 0.76; PIK3R1: OR = 0.54, 95% CI, 0.31 to 0.92). By contrast, early-onset EC patients had increased odds of presenting with nonsilent CTNNB1 and BRCA2 mutations compared with late-onset patients (CTNNB1: OR = 3.32, 95% CI, 2.14 to 5.16; BRCA2: OR = 4.01, 95% CI, 1.55 to 10.38). Subsequent analyses stratified by race, ethnicity, and tumor histology identified distinct patterns of APC, KMT2D, KMT2C, and KRAS by race, ethnicity, and PTEN and APC patterns by histologic subtypes. CONCLUSION Early-onset EC harbors a unique genomic landscape compared with late-onset disease. A distinct molecular phenotype of early-onset EC provides novel insights into a unique etiology and may yield clinical implications for developing targeted treatment modalities for younger patients.
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Affiliation(s)
- Jungyoon Choi
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | - Andreana N. Holowatyj
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | - Mengmeng Du
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Zhishan Chen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | - Nikolaus Schultz
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Loren Lipworth
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
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8
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Li Y, Liu H, Zhou Y, Zhou Z, Liu W, Zhao L, Güngör C, Wang D, Pei Q, Pei H, Tan F. The Survival Effect of Radiotherapy on Stage II/III Rectal Cancer in Different Age Groups: Formulating Radiotherapy Decision-Making Based on Age. Front Oncol 2021; 11:695640. [PMID: 34395261 PMCID: PMC8356670 DOI: 10.3389/fonc.2021.695640] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 07/12/2021] [Indexed: 12/24/2022] Open
Abstract
Introduction Total mesorectal excision (TME), chemotherapy (CT), and radiotherapy (RT) are usually integrated into the comprehensive treatment of stage II/III rectal cancer (RC). Neoadjuvant radiotherapy (nRT) has become the standard treatment for stage II/III RC patients to help reduce the size of a tumor or kill cancer cells that have spread. Adjuvant RT is delivered after the resection to destroy remaining cancer cells and used mainly in stage II/III RC patients who have not received preoperative radiotherapy, such as those who suffered from a bowel obstruction before surgery. It is controversial whether radiotherapy can improve the survival of stage II/III RC patients. An increasing number of studies have reported that rectal cancer exhibited mismatched biology, epidemiology, and therapeutic response to current treatment strategy in different age groups. It is necessary to investigate whether radiotherapy exhibits disparate effects in different age groups of patients with stage II/III RC. Methods Data from the Surveillance, Epidemiology, and End Results (SEER) Program was extracted to identify stage II/III RC diagnosed in the periods of 2004-2016. The statistical methods included Pearson's chi-square test, log-rank test, Cox regression model, and propensity score matching. Results Neoadjuvant radiotherapy (nRT) cannot improve the prognosis, and postoperative RT may even reduce the survival time for early onset stage II/III RC. Postoperative RT was not able to improve the overall survival (OS), while nRT may provide limited survival improvement for middle-aged stage II/III RC patients. In addition, radiotherapy can significantly improve the prognosis for elderly stage II/III RC. Conclusions This study indicated the inconsistent survival effect of radiotherapy on stage II/III rectal cancer patients in different age groups. Hence, we formulated a novel flow chart of radiotherapy decision-making based on age in stage II/III RC patients.
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Affiliation(s)
- Yuqiang Li
- Department of General Surgery, Xiangya Hospital, Central South University, Changsha, China.,Department of General Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Heli Liu
- Department of General Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Yuan Zhou
- Department of General Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Zhongyi Zhou
- Department of General Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Wenxue Liu
- Department of Cardiology, Xiangya Hospital, Central South University, Changsha, China
| | - Lilan Zhao
- Department of Thoracic Surgery, Fujian Provincial Hospital, Fuzhou, China
| | - Cenap Güngör
- Department of General Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Dan Wang
- Department of General Surgery, Xiangya Hospital, Central South University, Changsha, China.,Department of General Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Qian Pei
- Department of General Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Haiping Pei
- Department of General Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Fengbo Tan
- Department of General Surgery, Xiangya Hospital, Central South University, Changsha, China
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9
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Gibbs T, Washington MK, Eng C, Idrees K, Davis J, Holowatyj AN. Histologic and Racial/Ethnic Patterns of Appendiceal Cancer among Young Patients. Cancer Epidemiol Biomarkers Prev 2021; 30:1149-1155. [PMID: 33795212 PMCID: PMC8806661 DOI: 10.1158/1055-9965.epi-20-1505] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 01/16/2021] [Accepted: 03/10/2021] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Appendiceal cancer incidence among individuals age < 50 years (early-onset appendiceal cancer) is rising with unknown etiologies. Distinct clinicopathologic/demographic features of early-onset appendiceal cancer remain unexplored. We compared patterns of appendiceal cancer among individuals by age of disease-onset. METHODS Using the NIH/NCI's Surveillance, Epidemiology, and End Results program data, we identified individuals age 20+ years diagnosed with appendiceal cancer from 2007 to 2016. Cochran-Armitage trend tests and multinomial logistic regression models were used to examine age-related differences in clinicopathologic/demographic features of appendiceal cancer. RESULTS We identified 8,851 patients with appendiceal cancer during the 10-year study period. Histologic subtype, tumor grade, stage, sex and race/ethnicity all significantly differed by age of appendiceal cancer diagnosis. After adjustment for race/ethnicity, sex, stage, insurance status, and tumor grade, young patients were 82% more likely to be Hispanic [OR, 1.82; 95% confidence interval (CI), 1.48-2.25; P < 0.001] and 4-fold more likely to be American Indian or Alaska Native (OR, 4.02; 95% CI, 1.77-9.16; P = 0.0009) compared with late-onset cases. Patients with early-onset appendiceal cancer were also 2- to 3.5-fold more likely to be diagnosed with neuroendocrine tumors of the appendix (goblet cell carcinoid: OR, 1.96; 95% CI, 1.59-2.41; P < 0.0001; carcinoid: OR, 3.52; 95% CI, 2.80-4.42; P < 0.0001) compared with patients with late-onset appendiceal cancer. Among patients with neuroendocrine tumors, early-onset cases were also 45% to 61% less likely to present with high-grade (III-IV) tumors. CONCLUSIONS Approximately one in every three patients with appendiceal cancer is diagnosed before age 50 years in the United States. Appendiceal cancer in young patients is classified by distinct histologic and demographic features. IMPACT Early-onset appendiceal cancer determinants can inform discovery of risk factors and molecular biomarkers of appendiceal cancer in young patients, with implications for appendiceal cancer prevention, detection, and treatment.
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Affiliation(s)
| | - Mary K Washington
- Department of Pathology, Microbiology and Immunology, Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
- Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
| | - Cathy Eng
- Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Kamran Idrees
- Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
- Department of Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | | | - Andreana N Holowatyj
- Vanderbilt-Ingram Cancer Center, Nashville, Tennessee.
- Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
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10
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Error in Reporting of Age Variable in Database. JAMA Netw Open 2021; 4:e216703. [PMID: 33769501 PMCID: PMC7998072 DOI: 10.1001/jamanetworkopen.2021.6703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
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