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Updated: Jun 22, 2026
Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
Published on: October 18, 2013
Uniform Processing of Diverse Sequencing Data: A Cross-Population Comparison of Colon Cancer Genomic Landscapes from
Hsin-Yu Chang1,2, Chien-Jung Huang1, Yi-Chen Yeh2,3
1Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Background:
Colon cancer is genetically heterogeneous, necessitating standardized genomic analyses for cross-cohort comparisons. Although The Cancer Genome Atlas-colon adenocarcinoma (TCGA-COAD) is a widely used dataset, its comparability to other ethnically different populations remains unclear. This study systematically compares the genomic characteristics of TCGA-COAD and ChangKang, a Chinese colon cancer cohort, using an identical data processing pipeline to minimize methodologic biases.
Methods:
Whole-exome sequencing data from both cohorts were uniformly processed to analyze five key genomic features: tumor mutational burden (TMB), microsatellite instability (MSI), significantly mutated genes, mutational signatures, and copy-number variation (CNV). Samples were classified into hypermutated and non-hypermutated subgroups for further comparisons.
Results:
The TCGA-COAD cohort exhibited a higher overall TMB, driven by a greater proportion of hypermutated samples. However, the hypermutated subgroup of the ChangKang cohort included more ultramutated cases with polymerase epsilon (POLE) exonuclease domain mutations, leading to a higher subgroup TMB. MSI was more prevalent in TCGA-COAD, whereas significantly mutated gene frequencies varied, with lower APC and ACVR2A mutation rates in the ChangKang cohort. CNV patterns were largely similar though CNV frequencies were higher in TCGA-COAD.
Conclusions:
Despite differences in subgroup distributions and mutation frequencies, the overall genomic characteristics of colon cancer remain consistent between these ethnically different cohorts. This suggests that cross-population analyses are feasible when standardized processing methods are applied.
Impact:
This study provides a systematic, unbiased comparison of TCGA-COAD and the Chinese ChangKang cohort, demonstrating that the genomic characteristics remain largely consistent across ethnically distinct populations.
