INTERNATIONAL CONGRESS OF
PharmacoGenetics
From Sequencing to Survival: Current Evidence and Gaps in Implementing Large-Scale Genomic Profiling for Advanced Cancer
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Sina Saadati,1,*
1. University of Tabriz
- Introduction: The integration of next-generation sequencing (NGS) into clinical oncology holds the promise of personalizing treatment by matching therapies to specific molecular drivers of a patient's tumor. Despite rapid technological advances, the practical feasibility, clinical utility, and optimal implementation of large-scale genomic profiling for patients with advanced, refractory cancers remain subjects of investigation. Key questions persist regarding the frequency of identifying therapeutically relevant alterations, the proportion of patients who ultimately benefit from sequencing-directed therapies (SDT), and the most effective methodologies for maximizing clinical insight. This review synthesizes findings from four landmark cohort studies to provide a comprehensive overview of the current landscape, highlighting successes, identifying critical barriers, and clarifying the clinical impact of deploying advanced genomic and data-integration strategies in precision oncology.
- Methods: A systematic literature search was performed across WoS, PubMed, and ScienceDirect for original research articles published between January 2017 and December 2025 using the keywords Precision Medicine, NGS, Targeted Therapy, Actionable Mutations, Cancer Genomics, and Clinical Trial. We screened English-language Q1 journals, excluded reviews and case reports, and selected four primary cohort studies from an initial nine articles for detailed synthesis. The included studies were large prospective cohorts of advanced or refractory solid tumors and predominantly employed centralized next-generation sequencing of tumor tissue, ranging from focused 143-410 gene panels to whole-exome or approximately 1700-gene platforms, with both tumor-only and matched tumor–normal DNA sequencing, supplemental tumor RNA-seq in some studies, and integration of genomic data with electronic health records using NLP.
- Results: Across studies, large-scale NGS is highly feasible, with successful sequencing reported in 89-93% of submitted tumor specimens. However, the rate of identifying actionable alterations varied significantly based on the breadth of the genomic panel and the definition of "actionability." Studies using more focused panels and stricter, therapy-linked criteria identified actionable alterations in 36.7-37.6% of patients. In contrast, a study employing broader genomic and transcriptomic profiling reported at least one potentially actionable alteration in 80.5% of its cohort. Despite the high frequency of identifying potential targets, the proportion of patients who were ultimately assigned to or a sequencing-directed therapy (SDT) was consistently more modest, ranging from 11% to 17.8% across the cohorts. A major barrier identified was the high prevalence of co-occurring resistance mutations, which excluded a significant fraction of patients from receiving matched therapy even when a target was present. Nonetheless, for patients who received SDT, a meaningful subset experienced substantial clinical benefit. One study reported 37.1% of treated patients remained on therapy for at least six months, with nearly 20% achieving exceptional responses lasting over a year. Methodological innovations proved highly valuable. The inclusion of matched-normal sequencing revealed pathogenic germline variants in 15.8% of patients, many therapeutically relevant. The addition of RNA-sequencing uniquely identified actionable events in approximately 5% of cases. Finally, integrating genomic data with NLP-derived clinical features from medical records significantly improved survival prognostication compared to models using genomics or clinical stage alone.
- Conclusion: These studies demonstrate that while large-scale genomic profiling in advanced cancer is technically feasible, a significant gap exists between identifying a molecular target and delivering effective therapy. The findings temper the initial hype of precision oncology, establishing that only one subset of patients, consistently around 11-18%, are ultimately able to receive genomically-matched treatment in the current landscape. However, for that subset, the potential for durable, exceptional responses significant. The synthesized results strongly advocate for adoption of more comprehensive methodological approaches. Specifically, routine matched tumor-normal sequencing is warranted to identify clinically important germline alterations. The integration of transcriptomics and advanced NLP to unlock data from unstructured clinical notes offer powerful, demonstrated avenues to improve both therapeutic matching and prognostication. Future research must focus on closing the efficacy gap. Prime directives should include development of combination therapies designed to overcome co-occurring resistance mutations that disqualify many patients from treatment. Further, efforts should concentrate on refining multimodal predictive models that fuse genomic, transcriptomic, and deep clinical phenotype data to more accurately identify patients most likely to derive profound benefit from targeted interventions.
- Keywords: Precision Medicine, NGS, Targeted Therapy, Actionable Mutations, Cancer Genomics, Clinical Trial.
