Autologous reference types can confound the detection of somatic mutation in solid cancers.

Area of Science:

• Genomics
• Cancer Research
• Bioinformatics

Background:

• Somatic mutation detection is crucial for cancer research.
• Factors like sequencing and analysis pipelines influence mutation calls.
• The choice of normal reference tissue is a critical, often overlooked, variable.

Purpose of the Study:

• To investigate the impact of different autologous normal reference tissue types on the detection of cancer-associated somatic single nucleotide variations (SNVs).
• To evaluate how whole genome sequencing (WGS) and whole exome sequencing (WXS) are affected by reference type.
• To provide recommendations for improving the accuracy of somatic mutation detection in cancer studies.

Main Methods:

• Analysis of somatic SNVs and clinical data from solid tumors in The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC).
• Comparison of SNV detection using different autologous normal reference tissues (blood, adjacent normal tissue, solid tissue).
• Utilized whole genome sequencing (WGS) and whole exome sequencing (WXS) data.

Main Results:

• Significant differences in somatic SNV distribution were observed based on autologous reference types across multiple cancers.
• Whole exome sequencing (WXS) showed particular sensitivity to reference type in protein-coding regions.
• Low concordance rates were found between SNVs called from blood versus solid tissue (60.24%) and adjacent tissue versus blood (31.78%).

Conclusions:

• The selection of normal reference tissue type substantially influences the landscape of detected cancer-associated somatic mutations.
• Current reference strategies, particularly relying on blood, may lead to underestimation of true somatic SNVs.
• Incorporating more representative normal tissue types is essential for accurate cancer mutation detection and downstream analysis.