Modular and cloud-based bioinformatics pipelines for high-confidence biomarker detection in cancer immunotherapy clinical trials - Cu Nguyen; Trinh Nguyen; Gloria Trivitt; Brian Capaldo; Chunhua Yan; Qingrong Chen; Nicholas Renzette; Umit Topaloglu; Daoud Meerzaman (PLoS ONE, 2025)
Background The Cancer Immune Monitoring and Analysis Centers – Cancer Immunologic Data Center (CIMAC-CIDC) network aims to improve cancer immunotherapy by providing harmonized molecular assays and standardized bioinformatics analysis. Results In response to evolving bioinformatics standards and the migration of the CIDC to the National Cancer Institute (NCI), we undertook the enhancement of the CIDC’s extant whole exome sequencing (WES) and RNA sequencing (RNA-Seq) pipelines. Leveraging open-source tools and cloud-based technologies, we implemented modular workflows using Snakemake and Docker for efficient deployment on the Google Cloud Platform (GCP). Benchmarking analyses demonstrate improved reproducibility, precision, and recall across validated truth sets for variant calling, transcript quantification, and fusion detection. Conclusion This work establishes a scalable framework for harmonized multi-omic analyses, ensuring the continuity and reliability of bioinformatics workflows in multi-site clinical research aimed at advancing cancer biomarker discovery and personalized medicine.