Clinical Quality in Cancer Research: Strategy to Assess Data Integrity of Germline Variants Inferred from Tumor-Only...

Area of Science:

• Genomic Medicine
• Cancer Genomics
• Bioinformatics

Background:

• Germline pathogenic variants (PGPVs) contribute to 5-10% of adult cancers and some childhood tumors.
• Tumor-DNA sequencing increasingly identifies PGPVs, necessitating robust data quality assessment.
• Existing quality guidelines (GxP) do not comprehensively cover statistically derived variables like PGPVs.

Purpose of the Study:

• To propose a strategy and tactics for assessing the clinical quality of PGPVs.
• To ensure data integrity in exploratory research using clinico-genomic databases (CGDB).
• To address the lack of specific quality assessment guidelines for statistically derived sequencing data.

Main Methods:

• Development of statistical methods to infer PGPVs from tumor-DNA sequencing without normal samples.
• Application of these methods in real-world clinico-genomic databases (CGDB).
• Establishment of a quality management system and oversight activities for clinical quality risks.

Main Results:

• Identification of potential germline pathogenic variants (PGPVs) through tumor-DNA sequencing is expanding.
• Statistical methods enable PGPV inference from tumor data, supporting exploratory research.
• A proposed strategy aims to assess PGPV quality and ensure data integrity.

Conclusions:

• A systematic approach is needed to evaluate the quality of statistically derived PGPVs.
• Ensuring data integrity is crucial for reliable insights from clinico-genomic databases.
• The proposed strategy provides a framework for assessing PGPV quality in cancer research.