Abstract 3964
Background
Immune checkpoint inhibitors (CPI) have revolutionised the treatment of solid tumours with durable responses in cancers with previously limited treatment options. Despite significant improvements in overall survival for some patients(pt), identifying biomarkers to select a population most likely to benefit from CPIs remains challenging.
Methods
We characterized fresh tumour biopsies from 82 pts with metastatic cancer through the Personalised OncoGenomics (POG) program at BC Cancer using whole genome (80X tumour, 40X normal) and transcriptome analysis (WGTA). Subsequently pts were treated with a CPI as part of their standard cancer care. Baseline characteristics and follow up data were collected retrospectively. Durable clinical benefit (DCB) was defined as > 6 months(m) without disease progression and overall survival (OS) from date of first CPI treatment to death.
Results
The 82 pts (59% female) biopsied comprised a heterogeneous cohort: non-small cell lung cancer (30%), breast (17%) and colorectal cancer (13%) were most common, and most patients (45%) had received 1-2 prior treatments. 17 patients (21%) had a DCB and the median follow-up from first dose CPI was 9.2m. Higher tumour mutation burden (>10mut/Mb exome) was predictive of a longer median time to progression/death (TTPD) (5.9 vs 2.6m, p = 0.0055, HR = 0.44) and OS (14.6 vs 7.9m, p = 0.039, HR = 0.52). A higher predicted CD8+ T cell score (CIBERSORT) also predicted for a prolonged median TTPD (3.4 vs 2.4 m, p = 0.0094, HR = 0.51) and OS (12.9 vs 5.3m, p = 0.0014, HR = 0.42). In contrast, patients with PD-L1 expression > 80th percentile did not have a significantly different TTPD or OS. In addition to characterizing individual biomarkers, we note that patients with combinations of markers, particularly high TMB and CD8+ T cell scores, have a further improvement in median TTPD (5.9 vs 2.4m, p = 0.013) and OS (14.5 vs 5.4m, p = 0.014).
Conclusions
The complexity of interpreting the tumour-immune interface to predict CPI efficacy remains challenging, but WGTA allows for identification of combination biomarkers that may help to identify responders. The presence of two or more biomarkers predicted for CPI response in this patient cohort and may more successfully identify these patients in prospective studies.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
BC Cancer Foundation.
Disclosure
J. Lavoie: Research grant / Funding (self): University of British Columbia. S. Yip: Advisory / Consultancy: Pfizer; Advisory / Consultancy: Roche; Advisory / Consultancy: Bayer. D. Renouf: Honoraria (self): Celgene; Honoraria (self): Servier; Honoraria (self): Taiho; Honoraria (self): Ipsen; Honoraria (self), Research grant / Funding (institution): Bayer. J.J. Laskin: Honoraria (self), Research grant / Funding (institution): Roche Canada; Honoraria (self): BI Canada; Honoraria (self), Research grant / Funding (institution): AstraZeneca Canada; Research grant / Funding (institution): Pfizer Canada. All other authors have declared no conflicts of interest.
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