The development of immunotherapy is an important breakthrough for the treatment of cancer, with antitumor efficacy observed in a wide variety of tumors. To optimize immunotherapy use, approaches must be developed to identify which patients are likely to achieve benefit. To minimize therapeutic toxicities and costs, understanding the ideal choice and sequencing of the numerous immuno-oncology agents available for individual patients is thus critical, but fraught with challenges. The immune tumor microenvironment (TME) is a unique aspect of the response to immuno-oncology agents and measurement of single biomarkers does not adequately capture these complex interactions. Therefore, multiple potential biomarkers are likely needed. Current candidates in this area include PD-L1 expression, CD8⁺ tumor-infiltrating lymphocytes, tumor mutation load and neoantigen burden, immune-related gene signatures, and multiplex IHC assays that examine the pharmacodynamic and spatial interactions of the TME. The most fruitful investigations are likely to use several techniques to predict response and interrogate mechanisms of resistance. Immuno-oncology biomarker research must employ validated assays to ask focused research questions utilizing clinically annotated tissue collections and biomarker-focused clinical trial designs to investigate specific endpoints. Real-time input from patients and their advocates into biomarker discovery is necessary to ensure that the investigations pursued will improve both clinical outcomes and quality of life. We herein provide a framework of recommendations to guide the search for immuno-oncology biomarkers of value.

Introduction

Biomarkers, such as Estrogen Receptor, are used to determine therapy and prognosis in breast carcinoma. Immunostaining assays of biomarker expression have a high rate of inaccuracy; for example, estimates are as high as 20% for Estrogen Receptor. Biomarkers have been shown to be heterogeneously expressed in breast tumors and this heterogeneity may contribute to the inaccuracy of immunostaining assays. Currently, no evidence-based standards exist for the amount of tumor that must be sampled in order to correct for biomarker heterogeneity. The aim of this study was to determine the optimal number of 20X fields that are necessary to estimate a representative measurement of expression in a whole tissue section for selected biomarkers: ER, HER-2, AKT, ERK, S6K1, GAPDH, Cytokeratin, and MAP-Tau.

Methods

Two collections of whole tissue sections of breast carcinoma were immunostained for biomarkers. Expression was quantified using the Automated Quantitative Analysis (AQUA) method of quantitative immunofluorescence. Simulated sampling of various numbers of fields (ranging from one to thirty five) was performed for each marker. The optimal number was selected for each marker via resampling techniques and minimization of prediction error over an independent test set.

Results

The optimal number of 20X fields varied by biomarker, ranging between three to fourteen fields. More heterogeneous markers, such as MAP-Tau protein, required a larger sample of 20X fields to produce representative measurement.

Conclusions

The optimal number of 20X fields that must be sampled to produce a representative measurement of biomarker expression varies by marker with more heterogeneous markers requiring a larger number. The clinical implication of these findings is that breast biopsies consisting of a small number of fields may be inadequate to represent whole tumor biomarker expression for many markers. Additionally, for biomarkers newly introduced into clinical use, especially if therapeutic response is dictated by level of expression, the optimal size of tissue sample must be determined on a marker-by-marker basis.