The Relationship Between Tumor-Infiltrating Lymphocytes, PD-L1 Expression, Driver Mutations and Clinical Outcome Parameters in Non-Small Cell Lung Cancer Adenocarcinoma in Patients with a Limited to no Smoking History.

Tumor infiltrating lymphocytes (TIL), programmed death 1 (PD-1) and programmed death-ligand 1 (PD-L1) expression are important prognostic markers. This study aimed to investigate these markers in lung adenocarcinoma (ADC) biopsies from patients with stage IIIB or IV ADC with little or no smoking history, to investigate their prognostic value and to correlate these results with the presence of driver mutations in the tumors. TIL were retrospectively evaluated on hematoxylin and eosin stained slides from 152 tumor samples. PD-1/PD-L1 expression was retrospectively evaluated with PD-1/PD-L1 immunohistochemistry (IHC) double staining on 74 tumor samples with sufficient residual tissue. PD-L1 expression was analysed on stromal cells of the tumor compartment, the tumor cells and TIL and PD-1 on TIL. Median overall survival (OS) was longer in patients with high stromal TIL infiltration compared to patients with low stromal TIL infiltration (68 weeks vs. 35 weeks respectively; p = 0.003). This was observed most prominently in KRAS mutant tumors (95 weeks vs. 12 weeks; p = 0.003). Only PD-L1 expression on tumor stromal cells influenced OS and indicated a worse prognosis (77 weeks vs 25 weeks; p = 0.013). Stromal TIL counts nor PD-1/PD-L1 expression levels were associated with the presence of driver mutations. The results of the current study reinforce the prognostic role of TIL in lung ADC, which is most prominent in KRAS mutant cancers. The results of the PD-1/PD-L1 analysis suggest that stromal cells can effectively suppress the anti-tumor immune response via the PD-L1 pathway.

Tumor Fusion Burden as a Hallmark of Immune Infiltration in Prostate Cancer.

Prostate cancer is the second leading cause of cancer-related death in men. Despite having a relatively lower tumor mutational burden than most tumor types, multiple gene fusions such as TMPRSS2:ERG have been characterized and linked to more aggressive disease. Individual tumor samples have been found to contain multiple fusions, and it remains unknown whether these fusions increase tumor immunogenicity. Here, we investigated the role of fusion burden on the prevalence and expression of key molecular and immune effectors in prostate cancer tissue specimens that represented the different stages of disease progression and androgen sensitivity, including hormone-sensitive and castration-resistant prostate cancer. We found that tumor fusion burden was inversely correlated with tumor mutational burden and not associated with disease stage. High fusion burden correlated with high immune infiltration, PD-L1 expression on immune cells, and immune signatures, representing activation of T cells and M1 macrophages. High fusion burden inversely correlated with immune-suppressive signatures. Our findings suggest that high tumor fusion burden may be a more appropriate biomarker than tumor mutational burden in prostate cancer, as it more closely associates with immunogenicity, and suggests that tumors with high fusion burden could be potential candidates for immunotherapeutic agents.

Tumor Microvessel Density as a Potential Predictive Marker for Bevacizumab Benefit: GOG-0218 Biomarker Analyses.

Background: Combining bevacizumab with frontline chemotherapy statistically significantly improved progression-free survival (PFS) but not overall survival (OS) in the phase III GOG-0218 trial. Evaluation of candidate biomarkers was an exploratory objective. Methods: Patients with stage III (incompletely resected) or IV ovarian cancer were randomly assigned to receive six chemotherapy cycles with placebo or bevacizumab followed by single-agent placebo or bevacizumab. Five candidate tumor biomarkers were assessed by immunohistochemistry. The biomarker-evaluable population was categorized into high or low biomarker-expressing subgroups using median and quartile cutoffs. Associations between biomarker expression and efficacy were analyzed. All statistical tests were two-sided. Results: The biomarker-evaluable population (n = 980) comprising 78.5% of the intent-to-treat population had representative baseline characteristics and efficacy outcomes. Neither prognostic nor predictive associations were seen for vascular endothelial growth factor (VEGF) receptor-2, neuropilin-1, or MET. Higher microvessel density (MVD; measured by CD31) showed predictive value for PFS (hazard ratio [HR] for bevacizumab vs placebo = 0.40, 95% confidence interval [CI] = 0.29 to 0.54, vs 0.80, 95% CI = 0.59 to 1.07, for high vs low MVD, respectively, P interaction = .003) and OS (HR = 0.67, 95% CI = 0.51 to 0.88, vs 1.10, 95% CI = 0.84 to 1.44, P interaction = .02). Tumor VEGF-A was not predictive for PFS but showed potential predictive value for OS using a third-quartile cutoff for high VEGF-A expression. Conclusions: These retrospective tumor biomarker analyses suggest a positive association between density of vascular endothelial cells (the predominant cell type expressing VEGF receptors) and tumor VEGF-A levels and magnitude of bevacizumab effect in ovarian cancer. The potential predictive value of MVD (CD31) and tumor VEGF-A is consistent with a mechanism of action driven by VEGF-A signaling blockade.

Development and Validation of a Histological Method to Measure Microvessel Density in Whole-Slide Images of Cancer Tissue.

Despite all efforts made to develop predictive biomarkers for antiangiogenic therapies, no unambiguous markers have been identified so far. This is due to among others the lack of standardized tests. This study presents an improved microvessel density quantification method in tumor tissue based on stereological principles and using whole-slide images. Vessels in tissue sections of different cancer types were stained for CD31 by an automated and validated immunohistochemical staining method. The stained slides were digitized with a digital slide scanner. Systematic, uniform, random sampling of the regions of interest on the whole-slide images was performed semi-automatically with the previously published applications AutoTag and AutoSnap. Subsequently, an unbiased counting grid was combined with the images generated with these scripts. Up to six independent observers counted microvessels in up to four cancer types: colorectal carcinoma, glioblastoma multiforme, ovarian carcinoma and renal cell carcinoma. At first, inter-observer variability was found to be unacceptable. However, after a series of consensus training sessions and interim statistical analysis, counting rules were modified and inter-observer concordance improved considerably. Every CD31-positive object was counted, with exclusion of suspected CD31-positive monocytes, macrophages and tumor cells. Furthermore, if interconnected, stained objects were considered a single vessel. Ten regions of interest were sufficient for accurate microvessel density measurements. Intra-observer and inter-observer variability were low (intraclass correlation coefficient > 0.7) if the observers were adequately trained.

AutoTag and AutoSnap: Standardized, semi-automatic capture of regions of interest from whole slide images.

Tumor angiogenesis is measured by counting microvessels in tissue sections at high power magnification as a potential prognostic or predictive biomarker. Until now, regions of interest (ROIs) were selected by manual operations within a tumor by using a systematic uniform random sampling (SURS) approach. Although SURS is the most reliable sampling method, it implies a high workload. However, SURS can be semi-automated and in this way contribute to the development of a validated quantification method for microvessel counting in the clinical setting. Here, we report a method to use semi-automated SURS for microvessel counting: •Whole slide imaging with Pannoramic SCAN (3DHISTECH)•Computer-assisted sampling in Pannoramic Viewer (3DHISTECH) extended by two self-written AutoHotkey applications (AutoTag and AutoSnap)•The use of digital grids in Photoshop(®) and Bridge(®) (Adobe Systems) This rapid procedure allows traceability essential for high throughput protein analysis of immunohistochemically stained tissue.

Predictive tissue biomarkers for bevacizumab-containing therapy in metastatic colorectal cancer: an update.

Bevacizumab is the first anti-angiogenic agent approved for the treatment of metastatic colorectal cancer. The need for patient selection before initiating therapy necessitates the study of various proteins expressed in metastatic colorectal cancer tissue as candidate predictive markers. Immunohistochemistry is a valuable, commonly available and cost-effective method to assess predictive biomarkers. However, it is subject to variations and therefore requires rigorous protocol standardizations. Furthermore, validated quantification methodologies to study these angiogenic elements have to be applied. Based on their function in tumor angiogenesis and their relation to the mechanism of action of bevacizumab, protein markers were divided in four groups: VEGF A-signaling proteins; other relevant angiogenesis factors; factors regarding the tumor microenvironment and tumor intrinsic markers. Conceivably, nimbly selecting a small but relevant group of therapy-guided patients by the appropriate combination of predictive biomarkers may confer great value to this angiogenic inhibitor.