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We convened an ad hoc International Working Group for Antibody Validation in order to formulate the best approaches for validating antibodies used in common research applications and to provide guidelines that ensure antibody reproducibility. We recommend five conceptual 'pillars' for antibody validation to be used in an application-specific manner.

Resistance to DNA-damaging agents is a significant cause of treatment failure and poor outcomes in oncology. To identify unrecognized regulators of cell survival we performed a whole-genome CRISPR-Cas9 screen using treatment with ionizing radiation as a selective pressure, and identified STING (stimulator of interferon genes) as an intrinsic regulator of tumor cell survival. We show that STING regulates a transcriptional program that controls the generation of reactive oxygen species (ROS), and that STING loss alters ROS homeostasis to reduce DNA damage and to cause therapeutic resistance. In agreement with these data, analysis of tumors from head and neck squamous cell carcinoma patient specimens show that low STING expression is associated with worse outcomes. We also demonstrate that pharmacologic activation of STING enhances the effects of ionizing radiation in vivo, providing a rationale for therapeutic combinations of STING agonists and DNA-damaging agents. These results highlight a role for STING that is beyond its canonical function in cyclic dinucleotide and DNA damage sensing, and identify STING as a regulator of cellular ROS homeostasis and tumor cell susceptibility to reactive oxygen dependent, DNA damaging agents. The endoplasmic reticulum-localized adaptor STING regulates the innate immune response through its ability to sense DNA damage. Here the authors reveal that STING functions as a regulator of cellular ROS homeostasis and tumor cell susceptibility to reactive oxygen dependent, DNA damaging agents.

To update key recommendations of the American Society of Clinical Oncology/College of American Pathologists estrogen receptor (ER) and progesterone receptor (PgR) testing in breast cancer guideline. A multidisciplinary international Expert Panel was convened to update the clinical practice guideline recommendations informed by a systematic review of the medical literature. The Expert Panel continues to recommend ER testing of invasive breast cancers by validated immunohistochemistry as the standard for predicting which patients may benefit from endocrine therapy, and no other assays are recommended for this purpose. Breast cancer samples with 1% to 100% of tumor nuclei positive should be interpreted as ER positive. However, the Expert Panel acknowledges that there are limited data on endocrine therapy benefit for cancers with 1% to 10% of cells staining ER positive. Samples with these results should be reported using a new reporting category, ER Low Positive, with a recommended comment. A sample is considered ER negative if < 1% or 0% of tumor cell nuclei are immunoreactive. Additional strategies recommended to promote optimal performance, interpretation, and reporting of cases with an initial low to no ER staining result include establishing a laboratory-specific standard operating procedure describing additional steps used by the laboratory to confirm/adjudicate results. The status of controls should be reported for cases with 0% to 10% staining. Similar principles apply to PgR testing, which is used primarily for prognostic purposes in the setting of an ER-positive cancer. Testing of ductal carcinoma in situ (DCIS) for ER is recommended to determine potential benefit of endocrine therapies to reduce risk of future breast cancer, while testing DCIS for PgR is considered optional. Additional information can be found at www.asco.org/breast-cancer-guidelines .

Characterizing the tumor immune microenvironment enables the identification of new prognostic and predictive biomarkers, the development of novel therapeutic targets and strategies, and the possibility to guide first-line treatment algorithms. Although the driving elements within the tumor microenvironment of individual primary organ sites differ, many of the salient features remain the same. The presence of a robust antitumor milieu characterized by an abundance of CD8+ cytotoxic T-cells, Th1 helper cells, and associated cytokines often indicates a degree of tumor containment by the immune system and can even lead to tumor elimination. Some of these features have been combined into an ‘Immunoscore’, which has been shown to complement the prognostic ability of the current TNM staging for early stage colorectal carcinomas. Features of the immune microenvironment are also potential therapeutic targets, and immune checkpoint inhibitors targeting the PD-1/PD-L1 axis are especially promising. FDA-approved indications for anti-PD-1/PD-L1 are rapidly expanding across numerous tumor types and, in certain cases, are accompanied by companion or complimentary PD-L1 immunohistochemical diagnostics. Pathologists have direct visual access to tumor tissue and in-depth knowledge of the histological variations between and within tumor types and thus are poised to drive forward our understanding of the tumor microenvironment. This review summarizes the key components of the tumor microenvironment, presents an overview of and the challenges with PD-L1 antibodies and assays, and addresses newer candidate biomarkers, such as CD8+ cell density and mutational load. Characteristics of the local immune contexture and current pathology-related practices for specific tumor types are also addressed. In the future, characterization of the host antitumor immune response using multiplexed and multimodality biomarkers may help predict which patients will respond to immune-based therapies.

Background The role of tumor-associated macrophages (TAMs) in the cancer immune landscape and their potential as treatment targets or modulators of response to treatment are gaining increasing interest. TAMs display high molecular and functional complexity. Therefore their objective assessment as breast cancer biomarkers is critical. The aims of this study were to objectively determine the in situ expression and significance of TAM biomarkers (CD68, CD163, and MMP-9) in breast cancer and to identify subclasses of patients who could benefit from TAM-targeting therapies. Methods We measured CD68, CD163, and MMP-9 protein expression in formalin-fixed paraffin-embedded tissues of breast carcinomas represented in tissue microarray format using multiplexed quantitative immunofluorescence (QIF) in two independent Yale cohorts: cohort A— n = 398, estrogen receptor–positive (ER + ) and ER − cases—and the triple-negative breast cancer (TNBC)-only cohort B ( n = 160). Associations between macrophage markers, ER status, and survival were assessed. Protein expression measured by QIF was compared with mRNA expression data from the METABRIC study. Results All three macrophage markers were co-expressed, displaying higher expression in ER − cancers. High pan-macrophage marker CD68 correlated with poorer overall survival (OS) only in ER − cases of cohort A ( P = 0.02). High expression of CD163 protein in TAMs was associated with improved OS in ER − cases (cohort A, P = 0.03 and TNBC cohort B, P = 0.04, respectively) but not in ER + cancers. MMP-9 protein was not individually associated with OS. High expression of MMP-9 in the CD68 + /CD163 + TAMs was associated with worse OS in ER + tumors ( P <0.001) but not in ER − cancers. In the METABRIC dataset, mRNA levels followed the co-expression pattern observed in QIF but did not always show the same trend regarding OS. Conclusions Macrophage activity markers correlate with survival differently in ER + and ER − cancers. The association between high co-expression and co-localization of MMP-9/CD163/CD68 and poor survival in ER + cancers suggests that these cancers may be candidates for macrophage-targeted therapies.

Assessment of tumor infiltrating lymphocytes (TILs) as a prognostic variable in melanoma has not seen broad adoption due to lack of standardization. Automation could represent a solution. Here, using open source software, we build an algorithm for image-based automated assessment of TILs on hematoxylin-eosin stained sections in melanoma. Using a retrospective collection of 641 melanoma patients comprising four independent cohorts; one training set (N = 227) and three validation cohorts (N = 137, N = 201, N = 76) from 2 institutions, we show that the automated TIL scoring algorithm separates patients into favorable and poor prognosis cohorts, where higher TILs scores were associated with favorable prognosis. In multivariable analyses, automated TIL scores show an independent association with disease-specific overall survival. Therefore, the open source, automated TIL scoring is an independent prognostic marker in melanoma. With further study, we believe that this algorithm could be useful to define a subset of patients that could potentially be spared immunotherapy. Histology data exists for many cancer samples and the ability to automatically image this data may provide prognostic information. Here, the authors generated an algorithm to measure tumour infiltrating lymphocytes in melanoma histology specimens and show that the ratio of these immune cells to tumour cells has prognostic value.

PD-L1 is expressed in a percentage of lung cancer patients and those patients show increased likelihood of response to PD-1 axis therapies. However, the methods and assays for the assessment of PD-L1 using immunohistochemistry are variable and PD-L1 expression appears to be highly heterogeneous. Here, we examine assay heterogeneity parameters toward the goal of determining variability of sampling and the variability due to pathologist-based reading of the immunohistochemistry slide. SP142, a rabbit monoclonal antibody, was used to detect PD-L1 by both chromogenic immunohistochemistry and quantitative immunofluorescence using a laboratory-derived test. Five pathologists scored the percentage of PD-L1 positivity in tumor- and stromal-immune cells of 35 resected non-small cell lung cancer cases, each represented on three separate blocks. An intraclass correlation coefficient of 94% agreement was seen among the pathologists for the assessment of PD-L1 in tumor cells, but only 27% agreement was seen in stromal/immune cell PD-L1 expression. The block-to-block reproducibility of each pathologist’s score was 94% for tumor cells and 75% among stromal/immune cells. Lin’s concordance correlation coefficient between pathologists’ readings and the mean immunofluorescence score among blocks was 94% in tumor and 68% in stroma. Pathologists were highly concordant for PD-L1 tumor scoring, but not for stromal/immune cell scoring. Pathologist scores and immunofluorescence scores were concordant for tumor tissue, but not for stromal/immune cells. PD-L1 expression was similar among all the three blocks from each tumor, indicating that staining of one block is enough to represent the entire tumor and that the spatial distribution of heterogeneity of expression of PD-L1 is within the area represented in a single block. Future studies are needed to determine the minimum representative tumor area for PD-L1 assessment for response to therapy.

Many aspects of the evolutionary process of tumorigenesis that are fundamental to cancer biology and targeted treatment have been challenging to reveal, such as the divergence times and genetic clonality of metastatic lineages. To address these challenges, we performed tumor phylogenetics using molecular evolutionary models, reconstructed ancestral states of somatic mutations, and inferred cancer chronograms to yield three conclusions. First, in contrast to a linear model of cancer progression, metastases can originate from divergent lineages within primary tumors. Evolved genetic changes in cancer lineages likely affect only the proclivity toward metastasis. Single genetic changes are unlikely to be necessary or sufficient for metastasis. Second, metastatic lineages can arise early in tumor development, sometimes long before diagnosis. The early genetic divergence of some metastatic lineages directs attention toward research on driver genes that are mutated early in cancer evolution. Last, the temporal order of occurrence of driver mutations can be inferred from phylogenetic analysis of cancer chronograms, guiding development of targeted therapeutics effective against primary tumors and metastases.

BackgroundSmall cell lung cancer (SCLC) accounts for 10–15% of all lung malignancies and its prognosis is dismal. Although early studies have shown promising clinical activity of immune checkpoint blockers, the immune composition and expression of potentially actionable immunostimulatory targets in this malignancy are poorly understood.MethodsUsing multiplexed quantitative immunofluorescence (QIF), we measured the levels of 3 different B7 family ligands PD-L1, B7-H3, B7-H4 and major tumor infiltrating lymphocyte (TIL) subsets in 90 SCLC samples represented in tissue microarray format. Associations between the marker levels, clinicopathological variables and survival were studied.ResultsPD-L1 protein was detected in 7.3%, B7-H3 in 64.9% and B7-H4 in 2.6% of SCLC cases. The markers showed limited co-expression and were not associated with the level of TILs, age, gender and stage. Elevated B7-H4 was associated with shorter 5-year overall survival. The levels of CD3+, CD8+ and CD20+ TILs and the ratio of total/effector T-cells were significantly lower in SCLC than in non-small cell lung cancer. High levels of CD3+, but not CD8+ or CD20+ TILs were significantly associated with longer survival.ConclusionsTaken together, our study indicate variable expression and clinical role of B7-family ligands in SCLC with predominant expression of the candidate target B7-H3 and the presence of a limited cytotoxic anti-tumor immune response. These results support the evaluation of B7-H3 blockers and/or pro-inflammatory therapies in SCLC.

Background The effects of neoadjuvant chemotherapy on immune markers remain largely unknown. The specific aim of this study was to assess stromal tumor-infiltrating lymphocytes (TILs) and programmed death ligand 1 (PD-L1) protein expression in a cohort of breast cancer patients treated with neoadjuvant chemotherapy. Methods Using quantitative immunofluorescence, we investigated stromal TILs and PD-L1 protein expression in pre-treatment and residual breast cancer tissue from a Yale Cancer Center patient cohort of 58 patients diagnosed with breast cancer from 2003 to 2009 and treated with neoadjuvant chemotherapy. We compared the TIL count and PD-L1 status in paired pre-treatment and residual cancer tissues and correlated changes and baseline levels with survival. Results Of the 58 patients, 46 (79.3%) had hormone-positive and 34 (58.6%) had node-positive breast cancer. Eighty-six percent of residual cancer tissues had TIL infiltration and 17% had PD-L1 expression. There was a trend for higher TIL counts in postchemotherapy compared to prechemotherapy samples ( p  = 0.09). Increase in TIL count was associated with longer 5-year recurrence-free survival ( p  = 0.02, HR = 3.9, 95% CI = 1.179–15.39). PD-L1 expression (both stromal and tumor cells) was significantly lower in post-treatment samples ( p  = 0.001). Change in PD-L1 expression after therapy or TILs and PD-L1 expression in the posttreatment samples did not correlate with survival. Conclusions Increase in stromal TILs in residual cancer compared to pretreatment tissue is associated with improved recurrence-free survival. Despite a trend for increasing TIL counts, PD-L1 expression decreased in residual disease compared to pretreatment samples.