Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

Poster Display session 3

3964 - Predictive markers of checkpoint inhibitor activity in adult metastatic solid tumours

Date

30 Sep 2019

Session

Poster Display session 3

Topics

Immunotherapy

Tumour Site

Presenters

Alexandra Pender

Citation

Annals of Oncology (2019) 30 (suppl_5): v475-v532. 10.1093/annonc/mdz253

Authors

A. Pender1, E. Titmuss2, E. Pleasance2, K. Fan2, H. Pearson2, M. Bonakdar2, G. Taylor2, K. Mungall2, R. Moore2, J. Lavoie1, S. Yip3, H. Lim1, D. Renouf1, S.J. Jones2, M.A. Marra4, J.J. Laskin1

Author affiliations

  • 1 Medical Oncology, BC Cancer Agency - Vancouver, V5Z 4E6 - Vancouver/CA
  • 2 Bioinformatics, Canada's Michael Smith Genome Sciences Centre, V5Z 4S6 - Vancouver/CA
  • 3 Department Of Pathology And Laboratory Medicine, University of British Columbia, V6T 2B5 - Vancouver/CA
  • 4 Medical Genetics, Canada's Michael Smith Genome Sciences Centre, V5Z 4S6 - Vancouver/CA

Resources

Login to access the resources on OncologyPRO.

If you do not have an ESMO account, please create one for free.

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.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.