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. 2025 Nov 18:JCO2500596.
doi: 10.1200/JCO-25-00596. Online ahead of print.

Individual Patient Data Meta-Analysis of Consensus Molecular Subtypes as Biomarkers of First-Line Treatment in RAS Wild-Type Metastatic Colorectal Cancer

Arndt Stahler  1   2 , Dominik Paul Modest  1   2 , Sebastian Stintzing  1   2 , Beatrice Borelli  3 , Theresa Keller  4 , Swantje Held  5 , Ludwig Fischer von Weikersthal  6 , Lothar Müller  7 , Ullrich Graeven  8 , Thomas Decker  9 , Tobias Heintges  10 , Christoph Kahl  11   12 , Beeke Hoppe  1 , Alexander Kiani  13   14 , Florian Kaiser  15 , Ingo Schwaner  16 , Stefan Fruehauf  17 , Meinolf Karthaus  18 , Tanja Trarbach  19   20 , Frederick Klauschen  21 , David Horst  22 , Chiara Cremolini  3 , Volker Heinemann  23   24
Affiliations

Individual Patient Data Meta-Analysis of Consensus Molecular Subtypes as Biomarkers of First-Line Treatment in RAS Wild-Type Metastatic Colorectal Cancer

Arndt Stahler et al. J Clin Oncol. .

Abstract

Purpose: Consensus molecular subtypes (CMSs) of metastatic colorectal cancer (mCRC) are debatable biomarkers. An individual patient data (IPD) meta-analysis was performed to test for impact on objective response rates (ORRs), progression-free survival (PFS) and overall survival (OS), and treatment interaction.

Methods: IPD (RAS wild-type [WT] tumors treated per protocol [fluorouracil/capecitabine, irinotecan/oxaliplatin, anti-vascular endothelial growth factor {VEGF}/anti-epidermal growth factor receptor {EGFR} antibodies] and with evaluable CMSs) were collected from five trials identified in PubMed, Embase, Medline, Cochrane Library, and proceedings of ASCO/European Society for Medical Oncology: FIRE1 (no identifier), FIRE3 (ClinicalTrials.gov identifier: NCT00433927), XELAVIRI (ClinicalTrials.gov identifier: NCT01249638), PanaMa (ClinicalTrials.gov identifier: NCT01991873), and TRIBE2 (ClinicalTrials.gov identifier: NCT02339116). The one-step IPD meta-analysis approach assessed data taking the clustering of patients in the studies into account (ORR: generalized estimating equations models; PFS/OS: Cox models).

Results: Seven hundred ninety patients were included: CMS1, n = 77 (9.7%); CMS2, n = 345 (43.7%); CMS3, n = 74 (9.4%); and CMS4, n = 294 (37.2%). Between-study heterogeneity was negligible (variance < 1 × 10-6). Compared with CMS1, CMS2 and CMS4 tumors had numerically higher odds ratios (OR) for ORR (CMS2: OR, 1.668 [95% CI, 0.982 to 2.836]; P = .059; CMS4: OR, 1.369 [95% CI, 0.874 to 2.146]; P = .170), and longer PFS (CMS2: hazard ratios [HR], 0.64 [95% CI, 0.48 to 0.85]; P = .002; CMS4: HR, 0.67 [95% CI, 0.50 to 0.91]; P = .009) and OS (CMS2: HR, 0.59 [95% CI, 0.43 to 0.80]; P < .001; CMS4: HR, 0.67 [95% CI, 0.49 to 0.92]; P = .01). The use of anti-EGFR versus anti-VEGF antibodies meaningfully improved PFS (HR, 0.67 [95% CI, 0.46 to 0.97]; P = .03) and OS (HR, 0.49 [95% CI, 0.33 to 0.72]; P < .001) in CMS4 tumors and was consistently observed for CMS4 RAS/BRAF WT (HR, 0.55 [95% CI, 0.37 to 0.83]; P = .004) or microsatellite stable status (HR, 0.52 [95% CI, 0.32 to 0.86]; P = .01). The interaction test of antibody treatment with CMSs was significant for PFS (P < .001) and OS (P < .001) in all patients and for OS in patients with RAS/BRAF WT tumors (P = .02).

Conclusion: CMS4 might be an additional biomarker of anti-EGFR treatment efficacy in RAS (and BRAF) WT mCRC.

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