T-Cell Heterogeneity in Baseline Tumor Samples: Implications for Early Clinical Trial Design and Analysis.

Background: In early stage clinical trials, changes to levels of tumor infiltrating lymphocytes (TILs) in the tumor microenvironment (TME) are critical biomarkers of the mechanism of action of novel immunotherapies. However, baseline heterogeneity of tumor samples, both between and within patients, and the resultant impact on the validity of clinical trial data is not well defined. Here we identify and quantify the impact of baseline variables on the heterogeneity of FoxP3+ and proliferating CD8+ T-cells levels (MKi67+CD8A+) in the TME both between and within patients for the purpose of informing clinical trial design and analysis. Methods: We compared levels of FoxP3+ and MKi67+CD8+ cell densities (counts/mm2) from >1000 baseline tumor samples from clinical trials and commercially available sources. Using multivariate hierarchical regression techniques, we investigated whether inter-person heterogeneity of activated or regulatory T-cells could be attributed to baseline characteristics including demographics, indication, lesion type, tissue of excision, biopsy method, prior cancer treatment, and tissue type i.e., "fresh" or "archival" status. We also sought to characterize within-patient heterogeneity by lesion type and tissue type. Results: Prior cancer treatment with hormone therapy or chemotherapy that induces immunogenic cell death may alter the TME. Archival tissue is an unreliable substitute for fresh tissue for determining baseline TIL levels. Baseline and on treatment biopsies should be matched by lesion type to avoid bias.

Analysis of Spatial Organization of Suppressive Myeloid Cells and Effector T Cells in Colorectal Cancer-A Potential Tool for Discovering Prognostic Biomarkers in Clinical Research.

The development and progression of solid tumors such as colorectal cancer (CRC) are known to be affected by the immune system and cell types such as T cells, natural killer (NK) cells, and natural killer T (NKT) cells are emerging as interesting targets for immunotherapy and clinical biomarker research. In addition, CD3+ and CD8+ T cell distribution in tumors has shown positive prognostic value in stage I-III CRC. Recent developments in digital computational pathology support not only classical cell density based tumor characterization, but also a more comprehensive analysis of the spatial cell organization in the tumor immune microenvironment (TiME). Leveraging that methodology in the current study, we tried to address the question of how the distribution of myeloid derived suppressor cells in TiME of primary CRC affects the function and location of cytotoxic T cells. We applied multicolored immunohistochemistry to identify monocytic (CD11b+CD14+) and granulocytic (CD11b+CD15+) myeloid cell populations together with proliferating and non-proliferating cytotoxic T cells (CD8+Ki67+/-). Through automated object detection and image registration using HALO software (IndicaLabs), we applied dedicated spatial statistics to measure the extent of overlap between the areas occupied by myeloid and T cells. With this approach, we observed distinct spatial organizational patterns of immune cells in tumors obtained from 74 treatment-naive CRC patients. Detailed analysis of inter-cell distances and myeloid-T cell spatial overlap combined with integrated gene expression data allowed to stratify patients irrespective of their mismatch repair (MMR) status or consensus molecular subgroups (CMS) classification. In addition, generation of cell distance-derived gene signatures and their mapping to the TCGA data set revealed associations between spatial immune cell distribution in TiME and certain subsets of CD8+ and CD4+ T cells. The presented study sheds a new light on myeloid and T cell interactions in TiME in CRC patients. Our results show that CRC tumors present distinct distribution patterns of not only T effector cells but also tumor resident myeloid cells, thus stressing the necessity of more comprehensive characterization of TiME in order to better predict cancer prognosis. This research emphasizes the importance of a multimodal approach by combining computational pathology with its detailed spatial statistics and gene expression profiling. Finally, our study presents a novel approach to cancer patients' characterization that can potentially be used to develop new immunotherapy strategies, not based on classical biomarkers related to CRC biology.

Data-Driven Discovery of Immune Contexture Biomarkers.

Background: Features characterizing the immune contexture (IC) in the tumor microenvironment can be prognostic and predictive biomarkers. Identifying novel biomarkers can be challenging due to complex interactions between immune and tumor cells and the abundance of possible features. Methods: We describe an approach for the data-driven identification of IC biomarkers. For this purpose, we provide mathematical definitions of different feature classes, based on cell densities, cell-to-cell distances, and spatial heterogeneity thereof. Candidate biomarkers are ranked according to their potential for the predictive stratification of patients. Results: We evaluated the approach on a dataset of colorectal cancer patients with variable amounts of microsatellite instability. The most promising features that can be explored as biomarkers were based on cell-to-cell distances and spatial heterogeneity. Both the tumor and non-tumor compartments yielded features that were potentially predictive for therapy response and point in direction of further exploration. Conclusion: The data-driven approach simplifies the identification of promising IC biomarker candidates. Researchers can take guidance from the described approach to accelerate their biomarker research.

Atezolizumab in combination with bevacizumab enhances antigen-specific T-cell migration in metastatic renal cell carcinoma.

Anti-tumour immune activation by checkpoint inhibitors leads to durable responses in a variety of cancers, but combination approaches are required to extend this benefit beyond a subset of patients. In preclinical models tumour-derived VEGF limits immune cell activity while anti-VEGF augments intra-tumoral T-cell infiltration, potentially through vascular normalization and endothelial cell activation. This study investigates how VEGF blockade with bevacizumab could potentiate PD-L1 checkpoint inhibition with atezolizumab in mRCC. Tissue collections are before treatment, after bevacizumab and after the addition of atezolizumab. We discover that intra-tumoral CD8(+) T cells increase following combination treatment. A related increase is found in intra-tumoral MHC-I, Th1 and T-effector markers, and chemokines, most notably CX3CL1 (fractalkine). We also discover that the fractalkine receptor increases on peripheral CD8(+) T cells with treatment. Furthermore, trafficking lymphocyte increases are observed in tumors following bevacizumab and combination treatment. These data suggest that the anti-VEGF and anti-PD-L1 combination improves antigen-specific T-cell migration.

EGFR protein expression in non-small cell lung cancer predicts response to an EGFR tyrosine kinase inhibitor--a novel antibody for immunohistochemistry or AQUA technology.

INTRODUCTION: Epidermal growth factor receptor (EGFR) protein expression in non-small cell lung cancer (NSCLC) is not recommended for predicting response to EGFR tyrosine kinase inhibitors (TKI) due to conflicting results, all using antibodies detecting EGFR external domain (ED). We tested the predictive value of EGFR protein expression for response to an EGFR TKI with an antibody that detects the intracellular domain (ID) and compared fluorescence-based Automated QUantitative Analysis (AQUA) technology to immunohistochemistry (IHC). METHODS: Specimens from 98 gefitinib-treated NSCLC Japanese patients were evaluated by IHC (n = 98 of 98) and AQUA technology (n = 70 of 98). EGFR ID (5B7)- and ED-specific antibodies (3C6 and 31G7) were compared. RESULTS: EGFR expression evaluated with 5B7 was significantly higher in responders versus nonresponders to gefitinib both with IHC and with AQUA. ED-specific antibodies did not significantly predict response. Using AQUA and ID-specific antibody resulted in the best prediction performance with a positive and negative predictive value (PPV/NPV) for responders of 50% and 87%, respectively. EGFR expression with ID-specific antibody and AQUA also predicted responders in EGFR-mutated patients. Increased EGFR expression with the ID antibody is associated with increased median progression free survival (PFS; 11.7 months vs. 5.0, log rank, P = 0.034) and overall survival (OS; 38.6 vs. 14.9, P = 0.040) from gefitinib therapy. CONCLUSIONS: EGFR protein expression using an ID-specific antibody specifically predicts response to gefitinib in NSCLC patients, including in EGFR-mutated patients, and increased PFS/OS from gefitinib. These data suggest that the choice of diagnostic antibody and methodology matters to predict response and outcome to specific therapies. The potential clinical application needs further validation. Clin Cancer Res; 17(24); 7796-807. ©2011 AACR.

Increased insulin-like growth factor 1 receptor protein expression and gene copy number in small cell lung cancer.

PURPOSE: Identification of new therapies in small cell lung cancer (SCLC) is urgently needed. Insulin-like growth factor 1 receptor (IGF1R) is a tyrosine kinase receptor implicated in the pathogenesis of several malignancies and is potentially an attractive target for anticancer treatment. Knowledge about IGF1R protein expression, gene copy number, and the prognostic relevance of these features in SCLC is limited. METHODS: We analyzed IGF1R protein expression and gene copy number in primary tumors from 90 patients with SCLC (67 men and 23 women) who underwent pulmonary resection. IGF1R expression assessed by immunohistochemistry with H scores from 0 to 400 was evaluable in 84 patients and IGF1R gene copy number assessed by silver in situ hybridization technique in 81 patients. RESULTS: Median H score for IGF1R protein expression was 88 (range, 0-400), and the proportion of positive immunostaining using cutoff H score of 10 was 74%. Increased IGF1R gene copy number (an average of four or more copies per cell) was found in 15 cases (18.5%), five of whom (6.2%) showed gene amplification. There was a significant correlation between protein expression and gene copy number (r = 0.49, p < 0.005). IGF1R expression and gene copy number did not associate with clinicopathological factors such as patient age, tumor size, lymph node involvement, stage, and survival. CONCLUSIONS: SCLC is characterized by frequent high-IGF1R protein expression, increased gene copy number, and occasional occurrence of true gene amplification. These features may have important implications for future anti-IGF1R therapeutic approaches.

Silver in situ hybridization (SISH) for determination of HER2 gene status in breast carcinoma: comparison with FISH and assessment of interobserver reproducibility.

The importance of HER2 status in breast cancer management has focused attention on the ability of clinical assays to correctly assign HER2 amplification status. There is no consensus as to the best method for assessing HER2 status. Disadvantages of fluorescence in situ hybridization (FISH) testing include longer time required for staining and scoring slides, requirements for specialized training and fluorescence microscopy, and loss of the signal due to quenching of the fluorescent dye. Silver-enhanced in situ hybridization (SISH) is a rapid fully automated assay providing permanently stained slides that are interpreted by conventional bright field microscopy which enables pathologists to evaluate slides within the context of tissue morphology. This study evaluates the concordance between SISH and FISH assays in determining the status of HER2 gene amplification in a cohort of 298 primary invasive breast carcinomas. Furthermore, we assessed in detail the variables contributing to interobserver interpretive reproducibility of HER2 SISH among 10 pathologists. HER2 was quantified using the ratio of HER2 to CHR17 signals using the conventional historical interpretation scale and also by the American Society of Clinical Oncology/College of American Pathologists reporting scheme. For SISH status determined by consensus among 10 pathologists, overall concordance between SISH and FISH was identified in 288 of 298 cases (96.6%) using the conventional Food and Drug Administration approved criteria. Overall agreement was observed in 282 of 285 cases (98.9%) using the American Society of Clinical Oncology/College of American Pathologists result reporting scheme (with equivocal cases removed). In conclusion, SISH represents a novel approach for the determination of HER2 status in breast cancer. The overall concordance between SISH and FISH is excellent, and the interpretation of SISH results by pathologists is most reproducible using the HER2/CHR17 ratio.

Development of automated brightfield double in situ hybridization (BDISH) application for HER2 gene and chromosome 17 centromere (CEN 17) for breast carcinomas and an assay performance comparison to manual dual color HER2 fluorescence in situ hybridization (FISH).

BACKGROUND: Human epidermal growth factor receptor 2 (HER2) fluorescence in situ hybridization (FISH) is a quantitative assay for selecting breast cancer patients for trastuzumab therapy. However, current HER2 FISH procedures are labor intensive, manual methods that require skilled technologists and specialized fluorescence microscopy. Furthermore, FISH slides cannot be archived for long term storage and review. Our objective was to develop an automated brightfield double in situ hybridization (BDISH) application for HER2 gene and chromosome 17 centromere (CEN 17) and test the assay performance with dual color HER2 FISH evaluated breast carcinomas. METHODS: The BDISH assay was developed with the nick translated dinitrophenyl (DNP)-labeled HER2 DNA probe and DNP-labeled CEN 17 oligoprobe on the Ventana BenchMark(R) XT slide processing system. Detection of HER2 and CEN 17 signals was accomplished with the silver acetate, hydroquinone, and H2O2 reaction with horseradish peroxidase (HRP) and the fast red and naphthol phosphate reaction with alkaline phosphatase (AP), respectively. The BDISH specificity was optimized with formalin-fixed, paraffin-embedded xenograft tumors, MCF7 (non-amplified HER2 gene) and BT-474 (amplified HER2 gene). Then, the BDISH performance was evaluated with 94 routinely processed breast cancer tissues. Interpretation of HER2 and CEN 17 BDISH slides was conducted by 4 observers using a conventional brightfield microscope without oil immersion objectives. RESULTS: Sequential hybridization and signal detection for HER2 and CEN 17 ISH demonstrated both DNA targets in the same cells. HER2 signals were visualized as discrete black metallic silver dots while CEN 17 signals were detected as slightly larger red dots. Our study demonstrated a high consensus concordance between HER2 FISH and BDISH results of clinical breast carcinoma cases based on the historical scoring method (98.9%, Simple Kappa = 0.9736, 95% CI = 0.9222 - 1.0000) and the ASCO/CAP scoring method with the FISH equivocal cases (95.7%, Simple Kappa = 0.8993%, 95% CI = 0.8068 - 0.9919) and without the FISH equivocal cases (100%, Simple Kappa = 1.0000%, 95% CI = 1.0000 - 1.0000). CONCLUSION: Automated BDISH applications for HER2 and CEN 17 targets were successfully developed and it might be able to replace manual two-color HER2 FISH methods. The application also has the potential to be used for other gene targets. The use of BDISH technology allows the simultaneous analyses of two DNA targets within the context of tissue morphological observation.