Introduction:Colorectal cancers are the world’s third most commonly diagnosed type
of cancer. Currently, there are several diagnostic and treatment options to combat it. However, a
delay in detection of the disease is life-threatening. Additionally, a thorough analysis of the exomes
of cancers reveals potential variation data that can be used for early disease prognosis.Methods:By utilizing a comprehensive computational investigation, the present study aimed to reveal
mutations that could potentially predispose to colorectal cancer. Ten colorectal cancer exomes
were retrieved. Quality control assessments were performed using FastQC and MultiQC,
gapped alignment to the human reference genome (hg19) using Bowtie2 and calling the germline
variants using Haplotype caller in the GATK pipeline. The variants were filtered and annotated using
SIFT and PolyPhen2 successfully categorized the mutations into synonymous, non-synonymous,
start loss and stop gain mutations as well as marked them as possibly damaging, probably
damaging and benign. This mutational profile helped in shortlisting frequently occurring mutations
and associated genes, for which the downstream multi-dimensional expression analyses were
carried out.Results:Our work involved prioritizing the non-synonymous, deleterious SNPs since these polymorphisms
bring about a functional alteration to the phenotype. The top variations associated with
their genes with the highest frequency of occurrence included LGALS8, CTSB, RAD17, CPNE1,
OPRM1, SEMA4D, MUC4, PDE4DIP, ELN and ADRA1A. An in-depth multi-dimensional downstream
analysis of all these genes in terms of gene expression profiling and analysis and differential
gene expression with regard to various cancer types revealed CTSB and CPNE1 as highly expressed
and overregulated genes in colorectal cancer.Conclusion:Our work provides insights into the various alterations that might possibly lead to colorectal
cancer and suggests the possibility of utilizing the most important genes identified for wetlab
experimentation.