Computational protocol: Mutational Landscapes of Smoking-Related Cancers in Caucasians and African Americans: Precision Oncology Perspectives at Wake Forest Baptist Comprehensive Cancer Center

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Protocol publication

[…] Nonsynonymous somatic mutation calls were quantified. Patients were assigned to low or high mutation load groups based on the cohort mean mutation number. Fisher's exact test and Benjamini-Hochberg multiple testing adjustments were used to determine associations between mutation load and DNA damage genes and chromatin remodeling genes. Smoking status was defined by self-reported smoking history obtained from Cancer Registry and/or Epic Electronic Medical Record. Never smokers were defined as respondents who smoked less than 100 cigarettes in their lifetime. Based on evidence that smoking cessation reduces cancer risk by half at five years, active smokers at the time of clinical data collection and those who had quit smoking within the previous five years were considered current/recent smokers , . Those having quit more than five years prior to data collection were defined as former smokers. Only white (Caucasian) and black (AA patients) were included in disparities analyses, as these are the two main ethnic groups of the WFBCCC catchment area. Other racial/ethnic populations were underrepresented in the sample (less than 5%). Analyses for discovery of smoking-related mutations focused on genes with functional roles in DNA Damage Repair and Chromatin Remodeling. Each set of analyses used the Cochran-Mantel- Haenszel test to uncover associations between smoking status (defined as an ordinal variable - Never, Former, Recent) and gene mutation. Fisher's exact test was used to assess significance (p < 0.05) of gene mutation frequencies that differed with respect to low and high mutation load and racial status (Caucasians versus AA). The Hochberg (1988) approach was used to adjust for multiple testing . MutSig algorithm, MutSigCV, was used to evaluate the significance of mutated genes. All analyses were performed with R statistical computing software version 3.3.0 . Mutagenic processes and tumor clonality were analyzed with R packages somaticSignatures and SciClone, respectively (Supplementary Methods) . […]

Pipeline specifications

Software tools MutSig, SomaticSignatures, SciClone
Application WGS analysis
Organisms Nicotiana tabacum, Homo sapiens
Diseases Neoplasms, Colorectal Neoplasms