A cautionary note on genomic complexity and bioinformatic analysis in cancer

Abstract

Variant calling in complex genomic regions remains a critical challenge in cancer genomics, yet systematic evaluations of false positive rates in such regions are rarely reported. This investigative study examined somatic mutations in esophageal squamous cell carcinoma (ESCC) using Whole Genome Sequencing (WGS) data, that identified a high frequency of putative mutations in MUC3A, a gene with an inherently complex sequence architecture. Quantitative laboratory validation attempts failed to confirm any of these computationally predicted mutations, prompting systematic re-analysis. By assessing multiple variant calling algorithms and implementing a Panel of Normals (PON) filtering strategy, we demonstrate that standard bioinformatics pipelines generated extensive false positive calls in MUC3A, with false positive rates approaching 100 % for this gene. While previous studies have acknowledged limitations in variant calling for repetitive or homologous regions, our work provides evidence of complete analytical failure in the MUC3A gene, and establishes a reproducible framework for identifying such artefacts. These findings address a critical research gap by quantifying the magnitude of false discovery in complex genomic contexts and demonstrating that multi-tool consensus approaches combined with PON filtering are insufficient without accompanied experimental validation. We recommend mandatory quantitative confirmation for variants identified in sequence-complex genes and advocate for transparent reporting of validation rates in cancer genomic studies to prevent propagation of spurious findings in literature. This paper provides a cautionary warning to future research to take into consideration the limitations of alignment and variant calling tools and to employ a combination of tools to obtain robust and reliable results.