How Reliable Is PD-L1 Expression as a Predictor of Immune Response?

Bradley J. Monk, MD, FACOG, FACS
Published: Thursday, Nov 09, 2017

Bradley J. Monk, MD
Bradley J. Monk, MD
Ovarian cancer is the most lethal of the gynecologic malignancies. Over 22,000 new cases of ovarian cancer are diagnosed each year in the United States, resulting in more than 14,000 deaths per year. The 5-year survival rate is less than 25% for women with a diagnosis of advanced stage disease (stage III or IV) despite aggressive treatment with surgery and adjuvant chemotherapy. Although more than 80% of patients will respond to initial therapy, epithelial ovarian cancer ultimately recurs in most of them. Recurrence is associated with a poor prognosis because of the eventual development of chemotherapy-resistant disease. Thus, there is a great need—and opportunity—to improve ovarian cancer outcomes by understanding the immune milieu of ovarian cancers and harnessing the power of immunotherapy.

While there have been various approaches, from cancer vaccines to adoptive immune-cell therapies, immune checkpoint inhibitors have caused a paradigm shift in cancer treatment (Table 1). The enthusiasm for this approach stems from evidence of complete and long-lasting tumor regression in malignancies that are often refractory to chemotherapy.

 

TABLE 1: Studies of Immune Checkpoint Inhibitors in Ovarian Cancer With Reported Results

Studies of Immune Checkpoint
Three principal measures have emerged to predict effective treatment with immune checkpoint inhibitors: (1) accessibility of the tumor by effector immune cells, (2) dominance of the immune checkpoint pathways in suppressing antitumor immunity, and (3) the number of neoantigens, sometimes expressed as mutational burden. The first is frequently defined by the presence of tumor-infiltrating lymphocytes (TIL) or the ratio of effector immune cells (Table 21 ).

 

TABLE 2: Classification of Tumors Based on Presence of Tumor-Infiltrating Lymphocytes and PD-L1 Expression1

Studies of Immune Checkpoint
The second principle is less well defined, as no accurate biomarker has been identified, although multiple approaches are being evaluated. Expression of PD-L1 on tumor cells has been suggested as a predictive biomarker to identify cancers that may be more responsive to PD-1/PD-L1 inhibitors. Evidence of the importance of the local tumor immune microenvironment in ovarian cancer emerged in 2003 when it was shown that infiltration of treatment-naïve tumors with T cells was associated with significantly improved median progression-free survival (22.4 vs 5.8 months, P <.001) and overall survival (50.3 vs 18 months, P <.001) compared with tumors with no T cells present.2

However, we have since learned not only that the presence of T cells is important but also that the type of T cells also influences outcomes. The proportion of regulatory T cells (Tregs) in the tumor negatively affects clinical outcomes and was a predictor of increased risk of death in a multivariate analysis. Multiple studies have since confirmed that the ratio of immune suppressive to immune effector cells within ovarian tumors is associated with clinical outcome. Immune responses to ovarian cancer appear to vary by histologic subtype, with high-grade serous cancers most likely to be associated with a prognostically favorable tumor-infiltrating lymphocyte response. Classification of different histologic subtypes of ovarian cancers based on TIL and PD-L1 revealed that type I patterns were more common in high-grade serous cancers, while type IV patterns predominated in other histologic subtypes.


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Online CME Activities
TitleExpiration DateCME Credits
35th Annual Chemotherapy Foundation Symposium: Innovative Cancer Therapy for Tomorrow® Clinical Vignette SeriesJan 31, 20192.0
Oncology Briefings™: Current Perspectives on Preventing and Managing Tumor Lysis SyndromeJun 30, 20191.0
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