To date, all population-based epidemiologic data on gastrointestinal stromal tumor (GIST) in the United States predate the 2001 implementation of GIST-specific histology coding. As such, results from previous studies were limited because of inclusion of non-GIST abdominal or gastrointestinal sarcomas. We used a national cancer registry with modern day histologic codes to gain greater insight into the true epidemiology of GIST in the United States. We identified 6,142 patients diagnosed with GIST between 2001 and 2011 in the Surveillance, Epidemiology, and End Results database. Incidence, survival, demographic risk factors, and prognostic factors were analyzed. Annual age-adjusted incidence rose from 0.55/100,000 in 2001 to 0.78/100,000 in 2011 and increased with age, peaking among 70- to 79-year-olds (3.06/100,000). GIST was also more common in males than females [rate ratio (RR), 1.35], non-Hispanics than Hispanics (RR, 1.23), and blacks (RR, 2.07) or Asians/Pacific Islanders (RR, 1.50) than whites. The study period had 5-year overall and GIST-specific survival rates of 65% and 79%, respectively. The 5-year overall survival rates for those with localized, regional, and metastatic disease at diagnosis were 77%, 64%, and 41%, respectively. Multivariate analyses demonstrated that older age at diagnosis, male sex, black race, and advanced stage at diagnosis were independent risk factors for worse overall survival. Multivariate analysis also showed the four aforementioned characteristics, along with earlier year of diagnosis, to be independent risk factors for worse GIST-specific survival. As the first population-based, epidemiologic study of histologically confirmed disease, our findings provide a robust representation of GIST in the era of immunohistochemical diagnoses.

Background

Survival rates in pediatric oncology have improved dramatically, in part due to high patient participation in clinical trials. Although racial/ethnic inequalities in clinical trial participation have been reported in adults, pediatric data and studies comparing participation rates by socio-demographic characteristics are scarce. The goal of this study was to assess differences in research protocol participation for childhood cancer by age, sex, race/ethnicity, parental language, cancer type, and insurance status.

Procedure

Data on enrollment in any protocol, biospecimen, or therapeutic protocols were collected and analyzed for newly diagnosed pediatric patients with cancer from 2008-2012 at Rady Children's Hospital.

Results

Among the 353 patients included in the analysis, 304 (86.1%) were enrolled in any protocol. Enrollment in biospecimen and therapeutic protocols was 84.2% (261/310) and 81.1% (206/254), respectively. Logistic regression analyzes revealed significant enrollment underrepresentation in any protocol for Hispanics compared to Non-Hispanic whites (81% vs. 91%; Odds Ratio [OR], 0.43; 95% Confidence Interval [CI], 0.21-0.90; P = 0.021) and among children of Spanish-speaking vs. English-speaking parents (78% vs. 89%; OR, 0.45; 95%CI, 0.23-0.87; P = 0.016). Compared to patients aged 0-4 years, significant underrepresentation was also found among patients 15-21 years old (92% vs.72%; OR, 0.21; 95% CI, 0.09-0.48; P < 0.001). Similar trends were observed when analyzing enrollment in biospecimen and therapeutic protocols separately.

Conclusions

There was significant underrepresentation in protocol participation for Hispanics, children of Spanish-speaking parents, and patients ages 15-21. Research is needed to understand barriers to research participation among these groups underrepresented in pediatric oncology clinical trials.

To examine 143 diabetes risk single nucleotide polymorphisms (SNPs), identified from genome-wide association studies, in association with breast cancer (BC) incidence and subsequent mortality. A population-based sample of Caucasian women with first primary invasive BC (n = 817) and controls (n = 1021) were interviewed to assess diabetes status. Using the National Death Index, women with BC were followed for >18 years during which 340 deaths occurred (139 BC deaths). Genotyping was done using DNA extracted from blood samples. We used unconditional logistic regression to estimate age-adjusted odds ratios and 95% confidence intervals (CIs) for BC incidence, and Cox regression to estimate age-adjusted hazard ratios and CIs for all-cause and BC-specific mortality. Twelve SNPs were associated with BC risk in additive genotype models, at α = 0.05. The top three significant SNPs included SLC30A8-rs4876369 (P = 0.0034), HHEX-rs11187146 (P = 0.0086), and CDKN2A/CDKN2B-rs1333049 (P = 0.0094). Diabetes status modified the associations between rs4876369 and rs2241745 and BC incidence, on the multiplicative interaction scale. Six SNPs were associated with all-cause (CDKAL1-rs981042, P = 0.0032; HHEX-rs1111875, P = 0.0361; and INSR-rs919275, P = 0.0488) or BC-specific (CDKN2A/CDKN2B-rs3218020, P = 0.0225; CDKAL1-rs981042, P = 0.0246; and TCF2/HNF1B-rs3094508, P = 0.0344) mortality in additive genotype models, at α = 0.05. Genetic polymorphisms that increase the risk of developing diabetes may also increase the risk of developing and dying from BC.

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.