title: Pan-Cancer Analysis of Genomic Sequencing Among the Elderly.
abstract: We hypothesized that elderly patients might have age-specific genetic abnormalities yet be underrepresented in currently available sequencing repositories, which could limit the effect of sequencing efforts for this population.
  
  
  
  Leveraging The Cancer Genome Atlas (TCGA) data portal, 9 tumor types were analyzed. The frequency distribution of cancer by age was determined and compared with Surveillance, Epidemiology, and End Results data. Using the estimated median somatic mutational frequency of each tumor type, the samples needed beyond TCGA to detect a 10% mutational frequency were calculated. Microarray data from a separate prospective cohort were obtained from primary prostatectomy samples to determine whether elderly-specific transcriptomic alterations could be identified.
  
  
  
  Of the 5236 TCGA samples, 73% were from patients aged <70 years. Comparing the distribution of TCGA samples by age to the Surveillance, Epidemiology, and End Results data, patients <70 years were well represented across most tumor types, but patients aged 80 to 99 years were underrepresented in all cancers (median TCGA underrepresentation of 167%). All cancers (except for colorectal) contained enough samples to detect a 10% mutational frequency in patients aged <60 years. In contrast, no cancer type had enough samples for which a 10% mutational frequency could be detected in patients aged ≥80 years. To further interrogate whether elderly patients with cancer were likely to harbor age-specific molecular abnormalities, we accessed transcriptomic data from a separate, larger database of >2000 prostate cancer samples. That analysis revealed significant differences in the expression of 10 genes in patients aged ≥70 years compared with those <70 years, of which 7 are involved in androgen signaling and/or DNA repair.
  
  
  
  Elderly patients have been underrepresented in genomic sequencing studies. Our data suggest the presence of elderly-specific molecular alterations. Further dedicated efforts to understand the biology of cancer among the elderly will be important moving forward.
authors.affiliation: Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
authors.forename: Daniel R
authors.initials: DR
authors.lastname: Wahl
authors.affiliation: Department of Radiation Oncology, Dana Farber Cancer Institute, Boston, Massachusetts.
authors.forename: Paul L
authors.initials: PL
authors.lastname: Nguyen
authors.affiliation: GenomeDx Biosciences, Vancouver, British Columbia, Canada.
authors.forename: Maria
authors.initials: M
authors.lastname: Santiago
authors.affiliation: GenomeDx Biosciences, Vancouver, British Columbia, Canada.
authors.forename: Kasra
authors.initials: K
authors.lastname: Yousefi
authors.affiliation: GenomeDx Biosciences, Vancouver, British Columbia, Canada.
authors.forename: Elai
authors.initials: E
authors.lastname: Davicioni
authors.affiliation: Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
authors.forename: Dean A
authors.initials: DA
authors.lastname: Shumway
authors.affiliation: Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
authors.forename: Corey
authors.initials: C
authors.lastname: Speers
authors.affiliation: Department of Pathology, University of Michigan, Ann Arbor, Michigan.
authors.forename: Rohit
authors.initials: R
authors.lastname: Mehra
authors.affiliation: Department of Radiation Oncology, University of California, San Francisco, San Francisco, California.
authors.forename: Felix Y
authors.initials: FY
authors.lastname: Feng
authors.affiliation: Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York.
authors.forename: Joseph R
authors.initials: JR
authors.lastname: Osborne
authors.affiliation: Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan. Electronic address: sprattda@med.umich.edu.
authors.forename: Daniel E
authors.initials: DE
authors.lastname: Spratt
mesh_terms: D000230:Adenocarcinoma / Q000235:genetics / Q000601:surgery; D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001943:Breast Neoplasms / Q000235:genetics; D002292:Carcinoma, Renal Cell / Q000235:genetics; D002294:Carcinoma, Squamous Cell / Q000235:genetics; D002648:Child; D015179:Colorectal Neoplasms / Q000235:genetics; D004252:DNA Mutational Analysis / Q000706:statistics & numerical data; D030561:Databases, Nucleic Acid / Q000706:statistics & numerical data*; D005260:Female; D006258:Head and Neck Neoplasms / Q000235:genetics; D006801:Humans; D007680:Kidney Neoplasms / Q000235:genetics; D008175:Lung Neoplasms / Q000235:genetics; D008297:Male; D008875:Middle Aged; D009154:Mutation; D009369:Neoplasms / Q000235:genetics*; D010051:Ovarian Neoplasms / Q000235:genetics; D011468:Prostatectomy / Q000706:statistics & numerical data; D011471:Prostatic Neoplasms / Q000235:genetics / Q000601:surgery; D018426:SEER Program / Q000706:statistics & numerical data*; D014481:United States; D014594:Uterine Neoplasms / Q000235:genetics