Inocras and Broad Institute Researchers Present New TCGA Whole-Genome Cancer Insights, Accelerating Discovery in Cancer Genomics
Insights derived from one of the largest datasets with over 250 million harmonized variant calls from over 8,000 tumor-normal whole genomes from more than 30 different cancer types will be presented at the AACR Annual Meeting 2026




SAN DIEGO & CAMBRIDGE, Mass.--(BUSINESS WIRE)--#CancerGenome--Researchers from Inocras, a bioinformatics-led company harnessing the power of whole-genome data and proprietary analytics to advance precision health, and the Broad Institute of MIT and Harvard will jointly present new insights from a collaborative initiative to analyze large-scale whole genome data during the AACR Annual Meeting 2026 in San Diego. The collaboration delivers one of the largest cancer whole-genome analyses from over 8,000 cancer whole-genomes, generated by the NCI’s The Cancer Genome Atlas (TCGA), across more than 30 cancer types.
For two decades, cancer genomic data has underpinned many of the most important discoveries in cancer genomics. However, most studies have relied primarily on whole-exome sequencing (WES), which covers only ~1–2% of the genome, leaving the majority of the genome unexplored. The Inocras-Broad collaboration analyzes whole-genome sequences (WGS) released by TCGA, delivering an unprecedented, well-curated genomic dataset that can serve as an ideal training set for building artificial intelligence (AI) models to usher in a new era of whole-genome AI-driven precision oncology.
Cancer WGS analysis and dataset comparison
TCGA WGS data was analyzed in parallel with two variant calling pipelines from Broad and Inocras; the December 1, 2025 analysis freeze marks a joint commitment to ensure variant call quality, integrity, and reproducibility. All the data were consolidated into a single frozen dataset to enable a consistent analysis across both groups and robust benchmarking of computational and AI methods.
“With this analysis initiative, we are collectively setting a new standard for cancer genomics,” said the principal investigators (PIs) of the Inocras-Broad collaboration: Drs. Gad Getz, PhD, a professor of pathology at Harvard Medical School, Director of Bioinformatics at the Krantz Family Center for Cancer Research and Dept. of Pathology at Massachusetts General Hospital and Core Institute Member at Broad Institute of MIT and Harvard; Esther Rheinbay, PhD, Assistant Professor of Medicine at Harvard Medical School and Massachusetts General Hospital Cancer Center and Associate Member at the Broad Institute of MIT and Harvard; and Young Seok Ju, MD, PhD, co-founder of Incoras and Associate professor at the Korea Advanced Institute of Science and Technology. “Whole-exome data has already transformed our understanding of cancer based on a narrow slice of the genome. Now, with harmonized full whole-genome insights, researchers can explore the complete landscape of cancer to identify noncoding driver mutations, genome ploidy assessment, structural variants (SVs) across intergenic and intronic regions, and mutational signatures, among other new insights to further advance translational cancer research.”
Key insights from the Inocras-Broad collaboration
Leveraging high-depth, PCR-free WGS, the new analysis of the somatic mutation landscape in 31 cancer types improved the discovery of new driver events by incorporating the analysis of non-coding regions, genome-wide copy number alterations, and genomic rearrangements.
Some of the insights include: Across all tumors, (i) more than 250 million variants were identified with >1 million somatic SVs, as well as (ii) new coding and non-coding candidate driver mutations, (iii) new genomic signatures of chromosomal instability, (iv) new promoter/enhancer somatic copy number alterations, (v) new patterns of alterations in the previously understudied X and Y chromosomes, and (vi) new candidate SV drivers; moreover, the data show (vii) pathogenic and likely pathogenic germline variants in established cancer predisposition genes affecting about 10% of all cases.
Strong foundation for future cancer research and cancer intelligence
Through the initiative, the PIs have together built a robust foundation to analyze cancer whole genomes at industry-scale. “The Inocras-Broad collaboration reflects our belief that the most impactful discoveries emerge from open, rigorous, and deeply collaborative science,” said Jehee Suh, CEO of Inocras. “Through this partnership, we are not just generating findings—we are building the foundation of a scalable, whole-genome–driven ecosystem for cancer research and clinical translation. I believe this foundation will accelerate discovery, enable clinical adoption, and advance the next generation of cancer intelligence.”
The PIs from Inocras and the Broad Institute will jointly present data highlights and discuss future initiatives during the Exhibitor Spotlight session “TCGA and Beyond: Whole-Genome Data Powering the Next Era of Cancer Intelligence” on Monday, April 20th.
About Inocras
Inocras is a bioinformatics-led company redefining precision health through whole genome data and proprietary analytics. Our oncology and rare disease platforms integrate comprehensive whole genome data with advanced automation to deliver curated and actionable insights at scale that accelerate discovery and diagnostics to improve patient care, bringing a real-world impact. Inocras operates a CLIA/CAP-certified laboratory and partners with leading hospitals, pharmaceutical companies, and research institutions worldwide. For more information, please visit inocras.com and follow the Inocras LinkedIn page.
“The Exhibitor Spotlight Theater is a promotional activity and is not approved for continuing education credit. The content of this Exhibitor Spotlight Theater are the opinions of the presenter and do not represent the position or the opinion of the American Association for Cancer Research® (AACR) or its members.” “Not affiliated with or endorsed by AACR.”
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Vikki Herrera, Oak Street Communications for Inocras
vikki@oakstreetcommunications.com
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