AI Insight
This study evaluated the Immune Profile Score (IPS), a DNA- and RNA-based molecular signature, as a biomarker to identify cancer patients likely to benefit from immune checkpoint inhibitor therapy in populations where this treatment is not standard care. In two real-world cohorts—microsatellite stable colorectal cancer (46 patients) and rare solid tumors with low tumor mutational burden (90 patients across 26 cancer types)—patients classified as IPS-High showed significantly improved overall survival on immunotherapy compared to IPS-Low patients. Notably, IPS predicted response to immunotherapy but not to conventional chemotherapy in the same patients, suggesting it specifically identifies immune therapy responders.
Why it matters
This biomarker could help expand the use of immune checkpoint inhibitors to cancer patients who are currently excluded from immunotherapy because their tumors lack traditional predictive markers like microsatellite instability or high mutational burden. If validated, IPS could enable personalized treatment decisions and potentially improve outcomes for patients with difficult-to-treat cancers who have limited therapeutic options.
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⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Background Immune checkpoint inhibitor (ICI) therapies have revolutionized oncology, but identifying patients who benefit remains a challenge, particularly in populations where ICIs are not the standard of care, including microsatellite stable colorectal cancer (MSS CRC) and rare solid cancers. We evaluated real-world performance of the Immune Profile Score (IPS), a validated DNA- and RNA-based molecular signature, in these cohorts. Methods In an exploratory analysis, we analyzed two real-world cohorts: 1) MSS CRC; and 2) MSS, tumor mutational burden-low rare solid cancers treated with off-label ICI. IPS-High and IPS-Low were calculated using a previously validated threshold. Cox proportional hazards models were fit to demonstrate prognostic utility for real-world overall survival (rwOS). In MSS CRC, time-to-next-treatment (TTNT) on prior non-ICI therapy was compared to rwOS on subsequent ICI therapy. Results In MSS CRC (n=46), IPS-High patients (13%) demonstrated clinically meaningful improvement in rwOS versus IPS-Low (Median OS: not reached vs 7.3 months; HR = 0.22, 90% CI 0.04-1.16). While IPS was not associated with TTNT on the preceding non-ICI line (HR = 1.07, 90% CI 0.60-1.91), it was associated with OS in patients receiving later line ICI (HR 0.21, 90% CI 0.04-1.22). In the rare cancers cohort (n=90; 26 unique malignancies), IPS-High (17.8%) was associated with longer OS to ICI therapy (HR = 0.26, 90% CI 0.11-0.61), even when restricted to histologies represented in both IPS groups (HR = 0.18, 90%, CI 0.05-0.62). Conclusions Preliminary evidence suggests that IPS may serve as a generalizable, pan-cancer biomarker capable of stratifying outcomes for ICI treatment in populations traditionally excluded from immunotherapy benefit.