Integrative genomic analysis identifies ancestry‐related expression quantitative trait loci on DNA polymerase β and supports the association of genetic ancestry with survival disparities in head and neck squamous cell carcinoma

Ramakodi, Meganathan P.; Devarajan, Karthik; Blackman, Elizabeth; Gibbs, Denise; Luce, Danièle; Deloumeaux, Jacqueline; Duflo, S.; Liu, Jeffrey; Mehra, Ranee; Kulathinal, Rob J.; Ragin, Camille

doi:10.1002/cncr.30457

Cited by 22 publications

(20 citation statements)

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“…One caveat of our analysis is that this inference applies to a population as though our data were a representative sample of the population. HPV infection prevalence varies with socioeconomic factors [54], racial disparities [35, 55] and genetic polymorphisms [56, 57] associated with outcomes in head and neck cancer so greater attention to representative sampling would provide more precise estimates of the frequencies of mutations within populations [58] and the net realized selection intensities in each population.…”

Section: Discussionmentioning

confidence: 99%

APOBEC-induced mutations and their cancer effect size in head and neck squamous cell carcinoma

et al. 2019

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Recent studies have revealed the mutational signatures underlying the somatic evolution of cancer, and the prevalences of associated somatic genetic variants. Here we estimate the intensity of positive selection that drives mutations to high frequency in tumors, yielding higher prevalences than expected on the basis of mutation and neutral drift alone. We apply this approach to a sample of 525 head and neck squamous cell carcinoma exomes, producing a rank-ordered list of gene variants by selection intensity. Our results illustrate the complementarity of calculating the intensity of selection on mutations along with tallying the prevalence of individual substitutions in cancer: while many of the most prevalently-altered genes were heavily selected, their relative importance to the cancer phenotype differs from their prevalence and from their P value, with some infrequent variants exhibiting evidence of strong positive selection. Furthermore, we extend our analysis of effect size by quantifying the degree to which mutational processes (such as APOBEC mutagenesis) contributes mutations that are highly selected, driving head and neck squamous cell carcinoma. We calculate the substitutions caused by APOBEC mutagenesis that make the greatest contribution to cancer phenotype among patients. Lastly, we demonstrate via in vitro biochemical experiments that the APOBEC3B protein can deaminate the cytosine bases at two sites whose mutant states are subject to high net realized selection intensities—PIK3CA E545K and E542K. By quantifying the effects of mutations, we deepen the molecular understanding of carcinogenesis in head and neck squamous cell carcinoma.

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Section: Discussionmentioning

confidence: 99%

APOBEC-induced mutations and their cancer effect size in head and neck squamous cell carcinoma

et al. 2019

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“…Also, for multiple myeloma, African American's higher levels of phenotypic heterogeneity and monoclonal immunoglobulin levels caused the unfavorable survival, compared with their white counterparts . Compared with Whites, African Americans have also been proved to have worse survival in other tumors due to racial genetic differences, including head and neck squamous cell carcinoma, kidney cancer . However, no study has specifically explored pancreatic NETs‐related genetic differences in races and ethnicities and their contribution to pancreatic NETs survival disparity.…”

Section: Discussionmentioning

confidence: 99%

Racial disparities in pancreatic neuroendocrine tumors survival: a SEER study

et al. 2017

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Pancreatic neuroendocrine tumor (pancreatic NETs), is an important cause of cancer‐related death worldwide. No study has rigorously explored the impact of ethnicity on pancreatic NETs. We aimed to demonstrate the relationship between ethnicity and the survival of patients with pancreatic NETs. We used the SEER database to identify patients with pancreatic NETs from 2004 to 2013. Kaplan–Meier methods and Cox proportional hazard models were used to evaluate the impact of race on survival in pancreatic NETs patients. A total of 3850 patients were included: 3357 Non‐Blacks, 493 Blacks. We stratified races as “Black” and “White/Other.” Blacks were more likely to be diagnosed with later stages of tumors (P = 0.021). As for the treatment, the access to surgery seemed to be more limited in Blacks than non‐Black patients (P = 0.012). Compared with non‐Black patients, Black patients have worse overall survival (OS) (HR = 1.17, 95% CI: 1.00–1.37, P = 0.046) and pancreatic neuroendocrine tumors specific survival (PNSS) (HR = 1.22, 95% CI: 1.01–1.48, P = 0.044). Multivariate Cox analysis identified that disease extension at the time of diagnosis and surgical status contributed to the ethnical survival disparity. Black patients whose stages at diagnosis were localized had significantly worse OS (HR = 2.09, 95% CI: 1.18–3.71, P = 0.011) and PNSS (HR = 3.79, 95% CI: 1.62–8.82, P = 0.002). As for the patients who did not receive surgery, Blacks also have a worse OS (HR = 1.18, 95% CI: 1.00–1.41, P = 0.045). The Black patients had both worse OS and PNSS compared to non‐Black patients. The restricted utilization of surgery, and the advanced disease extension at the time of diagnosis are the possible contributors to poorer survival of Blacks with pancreatic NETs.

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“…"omics" data such as feature expression data arising from next-generation sequencing, allele-specific expression, methylation, microarrays and SNP arrays as well as large-scale data from proteomics, metabolomics and DNA copy number studies, many of which have been utilized in this study. There has been a recent surge in integrative "omic" analyses that simultaneously involve different data types as well as other quantitative outcome variables using publicly available data from repositories such as TCGA and GEO (Ramakodi et al, 2016;Li et al, 2013;Lawrenson et al, 2015). Within this context, the proposed unifying framework offers a robust platform for analysis and interpretation.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Supervised Dimension Reduction for Large-Scale “Omics” Data With Censored Survival Outcomes Under Possible Non-Proportional Hazards

Spirko-Burns

Devarajan

2021

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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The past two decades have witnessed significant advances in high-throughput "omics" technologies such as genomics, proteomics, metabolomics, transcriptomics and radiomics. These technologies have enabled simultaneous measurement of the expression levels of tens of thousands of features from individual patient samples and have generated enormous amounts of data that require analysis and interpretation. One specific area of interest has been in studying the relationship between these features and patient outcomes, such as overall and recurrencefree survival, with the goal of developing a predictive "omics" profile. Large-scale studies often suffer from the presence of a large fraction of censored observations and potential time-varying effects of features, and methods for handling them have been lacking. In this paper, we propose supervised methods for feature selection and survival prediction that simultaneously deal with both issues. Our approach utilizes continuum power regression (CPR)-a framework that includes a variety of regression methods-in conjunction with the parametric or semi-parametric accelerated failure time (AFT) model. Both CPR and AFT fall within the linear models framework and, unlike black-box models, the proposed prognostic index has a simple yet useful interpretation. We demonstrate the utility of our methods using simulated and publicly available cancer genomics data. Supervised dimension reduction for large-scale "omics" data with censored survival outcomes under possible non-proportional hazards

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Integrative genomic analysis identifies ancestry‐related expression quantitative trait loci on DNA polymerase β and supports the association of genetic ancestry with survival disparities in head and neck squamous cell carcinoma

Cited by 22 publications

References 44 publications

APOBEC-induced mutations and their cancer effect size in head and neck squamous cell carcinoma

APOBEC-induced mutations and their cancer effect size in head and neck squamous cell carcinoma

Racial disparities in pancreatic neuroendocrine tumors survival: a SEER study

Supervised Dimension Reduction for Large-Scale “Omics” Data With Censored Survival Outcomes Under Possible Non-Proportional Hazards

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