“If you have a tumor that’s already been recognized by T cells and has become T-cell-inflamed, or immunologically ‘hot,’ but the immune cells have been suppressed by PD-L1 expression, then when you administer an immunotherapy drug, it increases T-cell activity against the tumor cells,” he explained. “When a patient has more than 40% PD-L1 expression, we know they might be good candidates for an immunotherapy drug. What that tells us is the tumor’s already been seen by the immune system and the immune cells have already infiltrated the tumor. Now we give the drug to allow the immune cells to do their job because immunotherapy drugs can block the tumor’s immune-suppressive mechanism. Therefore, the tumor cannot affect the T cells anymore.”

An ideal predictive biomarker “would be one that essentially looks at crosstalk – tumor mutation genotype and immune phenotype,” he said.

Several candidate predictive biomarkers are in development but there haven’t been many prospective studies. And, the studies that have been done have involved relatively few patients, Dr Maleki noted. “They’re hypothesis-generating studies, but not really good for biomarker validation. The numbers are so small they need additional, prospective randomized study with large patient cohorts — and these randomized prospective studies should be done separately for each cancer type.”

Related Articles

A new meta-analysis of data from 50 immunotherapy-predictive biomarker studies representing more than 8000 patients, suggested that multimodality biomarker strategies appear to outperform other candidate biomarkers that are measured alone.6 The study, published in JAMA Oncology, also found that multiplex immunofluorescence, which allows for the simultaneous assessment of multiple proteins’ expression on cells in the tumor microenvironment, better predicted positive responses to immunotherapy, and yielded fewer false-positive results than did other candidate predictive biomarkers used alone, including gene expression and tumor mutation burden.6

Echoing Dr Maleki, the authors said more clinical research is needed to identify the best combinations of biomarkers for different tumor types.

Disclosure: The study was funded by Ono Pharmaceutical and Bristol-Myers Squibb, and some of the authors disclosed financial ties to pharmaceutical companies. For a full list of disclosures, please refer to the original study.


  1. Vareki SM, Garrigós C, Duran I. Biomarkers of response to PD-1/PD-L1 inhibition. Crit Rev Oncol Hematol. 2017;116:116-124.
  2. Munari E, Zamboni G, Lunardi G, et al. PD-L1 expression heterogeneity in non-small cell lung cancer: defining criteria for harmonization between biopsy specimens and whole sections. J Thorac Oncol. 2018;13(8):1113-1120.
  3. Yu H, Boyle TA, Zhou C, Rimm DL, Hirsch FR. PD-L1 expression in lung cancer. J Thorac Oncol. 2016;11(7):964-975.
  4. Naito T, Udagawa H, Sato J, et al. A minimum of 100 tumor cells in a single biopsy sample is required to assess programmed cell death ligand 1 expression in predicting patient response to nivolumab treatment in non-squamous non-small cell lung carcinoma [published online June 10, 2019]. J Thorac Oncol. doi: 10.1016/jtho.2019.06.019
  5. Dong W, Wu X, Ma S, et al. The mechanism of anti-PD-L1 antibody efficacy against PD-L1 negative tumors identifies NK cells expressing PD-L1 as a cytolytic effector [published online July 24, 2019]. Cancer Discov. doi: 10.1158/2159-8290.CD-18-1259
  6. Lu S, Stein JE, Rimm DL, et al. Comparison of biomarker modalities for predicting response to PD-1/PD-L1 checkpoint blockade: a systematic review and meta-analysis [published online July 18, 2019]. JAMA Oncol. doi: 10.1001/jamaoncol.2019.1549