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Supplementary Table S1. Clinicopathologic characteristics of the cohort separated by death at the 5-year time point. Supplementary Table S2. Primary and secondary antibody information and TSA dye pairings for multiplex IF panel. Supplementary Table S3. Twenty highest ranking variables associating with overall survival by univariate Cox regression analysis. Supplementary Table S4. Density and proximity variables selected by least absolute shrinkage and selection operator (LASSO) methods using a 5-fold cross-validation. Supplementary Figure S1. Image cytometry to quantify immune cell biomarkers in metastatic melanoma. Supplementary Figure S2. The expression of PD-L1 on tumor cells and 'Other' cells is determined by their proximity to CD8+ cells. Supplementary Figure S3. Characterization of immune neighborhoods associated with overall survival. Supplementary Computational Methods. Survival and clinical statistical analysis - R markdown document.

Multiplex immunofluorescence (mIF) can detail spatial relationships and complex cell phenotypes in the tumor microenvironment (TME). However, the analysis and visualization of mIF data can be complex and time-consuming. Here, we used tumor specimens from 93 patients with metastatic melanoma to develop and validate a mIF data analysis pipeline using established flow cytometry workflows (image cytometry). Unlike flow cytometry, spatial information from the TME was conserved at single-cell resolution. A spatial uniform manifold approximation and projection (UMAP) was constructed using the image cytometry output. Spatial UMAP subtraction analysis (survivors vs. nonsurvivors at 5 years) was used to identify topographic and coexpression signatures with positive or negative prognostic impact. Cell densities and proportions identified by image cytometry showed strong correlations when compared with those obtained using gold-standard, digital pathology software (R2 > 0.8). The associated spatial UMAP highlighted “immune neighborhoods” and associated topographic immunoactive protein expression patterns. We found that PD-L1 and PD-1 expression intensity was spatially encoded—the highest PD-L1 expression intensity was observed on CD163+ cells in neighborhoods with high CD8+ cell density, and the highest PD-1 expression intensity was observed on CD8+ cells in neighborhoods with dense arrangements of tumor cells. Spatial UMAP subtraction analysis revealed numerous spatial clusters associated with clinical outcome. The variables represented in the key clusters from the unsupervised UMAP analysis were validated using established, supervised approaches. In conclusion, image cytometry and the spatial UMAPs presented herein are powerful tools for the visualization and interpretation of single-cell, spatially resolved mIF data and associated topographic biomarker development.

Table S2. Oncogenic/Likely-oncogenic structural variants in GBC

Purpose:Gallbladder carcinoma (GBC) is an uncommon and aggressive disease, which remains poorly defined at a molecular level. Here, we aimed to characterize the molecular landscape of GBC and identify markers with potential prognostic and therapeutic implications.Experimental Design:GBC samples were analyzed using the MSK-IMPACT (Memorial Sloan Kettering–Integrated Mutation Profiling of Actionable Cancer Targets) platform (targeted NGS assay that analyzes 505 cancer-associated genes). Variants with therapeutic implications were identified using OncoKB database. The associations between recurrent genetic alterations and clinicopathologic characteristics (Fisher exact tests) or overall survival (univariate Cox regression) were evaluated. P values were adjusted for multiple testing.Results:Overall, 244 samples (57% primary tumors and 43% metastases) from 233 patients were studied (85% adenocarcinomas, 10% carcinomas with squamous differentiation, and 5% neuroendocrine carcinomas). The most common oncogenic molecular alterations appeared in the cell cycle (TP53 63% and CDKN2A 21%) and RTK_RAS pathways (ERBB2 15% and KRAS 11%). No recurrent structural variants were identified. There were no differences in the molecular landscape of primary and metastasis samples. Variants in SMAD4 and STK11 independently associated with reduced survival in patients with metastatic disease. Alterations considered clinically actionable in GBC or other solid tumor types (e.g., NTRK1 fusions or oncogenic variants in ERBB2, PIK3CA, or BRCA1/2) were identified in 35% of patients; 18% of patients with metastatic disease were treated off-label or enrolled in a clinical trial based on molecular findings.Conclusions:GBC is a genetically diverse malignancy. This large-scale genomic analysis revealed alterations with potential prognostic and therapeutic implications and provides guidance for the development of targeted therapies.

Figure S1. Mutation signatures and altered canonical pathways in GBC.

Table S3. Therapy regimens

Table S1. Sample list (cBioPortal identifiers, ‘DMP_SAMPLE_ID’). Only the primary tumor (if available) or the earliest collected metastasis are included (n=233)

Detailed statistical results

Consensus Molecular Subgroup-level statistics on each MCP-counter abundance estimates

Purpose: The efficacy of PD-1 checkpoint blockade as adjuvant therapy in localized clear cell renal cell carcinoma (ccRCC) is currently unknown. The identification of tumor microenvironment (TME) prognostic biomarkers in this setting may help define which patients could benefit from checkpoint blockade and uncover new therapeutic targets.Experimental Design: We performed multiparametric flow cytometric immunophenotypic analysis of T cells isolated from tumor tissue [tumor-infiltrating lymphocytes (TIL)], adjacent non-malignant renal tissue [renal-infiltrating lymphocytes (RIL)], and peripheral blood lymphocytes (PBL), in a cohort of patients (n = 40) with localized ccRCC. Immunophenotypic data were integrated with prognostic and histopathologic variables, T-cell receptor (TCR) repertoire analysis of sorted CD8+PD-1+ TILs, tumor mRNA expression, and digital quantitative immunohistochemistry.Results: On the basis of TIL phenotypic characterization, we identified three dominant immune profiles in localized ccRCC: (i) immune-regulated, characterized by polyclonal/poorly cytotoxic CD8+PD-1+Tim-3+Lag-3+ TILs and CD4+ICOS+ cells with a Treg phenotype (CD25+CD127−Foxp3+/Helios+GITR+), that developed in inflamed tumors with prominent infiltrations by dysfunctional dendritic cells and high PD-L1 expression; (ii) immune-activated, enriched in oligoclonal/cytotoxic CD8+PD-1+Tim-3+ TILs, that represented 22% of the tumors; and (iii) immune-silent, enriched in TILs exhibiting RIL-like phenotype, that represented 56% of patients in the cohort. Only immune-regulated tumors displayed aggressive histologic features, high risk of disease progression in the year following nephrectomy, and a CD8+PD-1+Tim-3+ and CD4+ICOS+ PBL phenotypic signature.Conclusions: In localized ccRCC, the infiltration with CD8+PD-1+Tim-3+Lag-3+ exhausted TILs and ICOS+ Treg identifies the patients with deleterious prognosis who could benefit from adjuvant therapy with TME-modulating agents and checkpoint blockade. This work also provides PBL phenotypic markers that could allow their identification. Clin Cancer Res; 23(15); 4416–28. ©2017 AACR.

Table S1. Demographic and clinical characteristics of the analyzed patients are depicted (Mean {plus minus} SD)

Figure S4. Inverse relation between TLS and immune checkpoints in primary ccRCC : photomicrographs of immunohistochemistry staining of PD-L1(red)/hematoxylin and TLS structures as revealed by CD3(Blue)DC-Lamp(Red), CD21(Blue)/CD20(Red), and of CD8(red)/hematoxylin in PD-L1+and/orPD-L2+ (A) and PD-L1-/PD-L2- (B) primary ccRCC

Table S1. Demographic and clinical characteristics of the analyzed patients; Table S2. Antibodies and conditions used for the IHC studies; Table S3. List of immune-related genes analyzed by Low Density Array; Figure S1. Gating and data analysis strategy; Figure S2. CD4+ and CD8+ T-cell differentiation in ccRCC TIL, and autologous PBL and RIL; Figure S3. Gap statistics according to the possible number of clusters of TIL phenotype. Optimal cut-off according to firstSEmax method (R package: cluster) is displayed (dotted line); Figure S4. PCA analysis including RIL and TIL phenotype. TIL clusters are displayed; Figure S5. Tumor size according to TIL clusters; Figure S6. Percentages of CD4+TIL expressing AM and InR according to tumor clusters. C1, Cluster1; C2, Cluster2; C3, Cluster3; Figure S7. Percentages of CD8+TIL expressing AM and InR according to tumor clusters. C1, Cluster1; C2, Cluster2; C3, Cluster3; Figure S8. Clonality Index and frequency of top 15 clonotypes in CD8+PD-1+ TIL according to tumor clusters. C1, Cluster1; C2, Cluster2; C3, Cluster3; Figure S9. Corrected P values for the differential gene expression between TIL clusters; Figure S10. Correlation matrix including TLS-related genes and immune cells densities in Immune-activated and Immune-regulated tumors; Figure S11. Percentages of CD4+PBL expressing differentiation markers, AM and InR in healthy controls (HC) and ccRCC-bearing patients; Figure S12. Percentages of CD8+PBL expressing differentiation markers, AM and InR in HC and ccRCC-bearing patients; Figure S13. Percentages of CD4+PBL expressing differentiation markers, AM and InR according to PBL Clusters; Figure S14. Percentages of CD8+PBL expressing differentiation markers, AM and InR according to PBL Clusters.

Purpose: The tumor microenvironment is formed by many distinct and interacting cell populations, and its composition may predict patients' prognosis and response to therapies. Colorectal cancer is a heterogeneous disease in which immune classifications and four consensus molecular subgroups (CMS) have been described. Our aim was to integrate the composition of the tumor microenvironment with the consensus molecular classification of colorectal cancer.Experimental Design: We retrospectively analyzed the composition and the functional orientation of the immune, fibroblastic, and angiogenic microenvironment of 1,388 colorectal cancer tumors from three independent cohorts using transcriptomics. We validated our findings using immunohistochemistry.Results: We report that colorectal cancer molecular subgroups and microenvironmental signatures are highly correlated. Out of the four molecular subgroups, two highly express immune-specific genes. The good-prognosis microsatellite instable–enriched subgroup (CMS1) is characterized by overexpression of genes specific to cytotoxic lymphocytes. In contrast, the poor-prognosis mesenchymal subgroup (CMS4) expresses markers of lymphocytes and of cells of monocytic origin. The mesenchymal subgroup also displays an angiogenic, inflammatory, and immunosuppressive signature, a coordinated pattern that we also found in breast (n = 254), ovarian (n = 97), lung (n = 80), and kidney (n = 143) cancers. Pathologic examination revealed that the mesenchymal subtype is characterized by a high density of fibroblasts that likely produce the chemokines and cytokines that favor tumor-associated inflammation and support angiogenesis, resulting in a poor prognosis. In contrast, the canonical (CMS2) and metabolic (CMS3) subtypes with intermediate prognosis exhibit low immune and inflammatory signatures.Conclusions: The distinct immune orientations of the colorectal cancer molecular subtypes pave the way for tailored immunotherapies. Clin Cancer Res; 22(16); 4057–66. ©2016 AACR.

Antibodies used for immunohistochemical analyses

Immune, and other stromal samples analyzed

Legends for supplementary figure and trables

Supplementary Figure 1 : Design and use of the Microenvironment Cell Populations (MCP)-counter algorithm a) Heatmap representation of the expression of selected transcriptomic markers underlying MCP-counter scores in transcriptomic profiles corresponding to microenvironment cell populations. These scores have been quantitatively validated for their ability to predict the abundance of the corresponding cell population from the gene expression profile of a cellularly heterogeneous sample. b) MCP-counter is implemented as an R package, which takes as input transcriptomic profiles of cellularly heterogeneous tissues, such as tumors. It first maps the previously-identified transcriptomic markers to the assayed gene-expression features (as illustrated here for the 'discovery' CIT CRC cohort, and summarize them to output a score per cell population per sample. These scores can then be used to compare samples against each-others and to determine whether a group of samples is more highly infiltrated by a given cell type than another group of samples.

Colorectal cancer samples constituting the 3 cohorts analyzed, along with their molecular subgroups

Levels of expression of genes related to inflammation, angiogenesis and immunomodulation in CRC cohorts

Samples from the Cancer Cell Line Encyclopedia

Purpose: Clear cell renal cell carcinoma (ccRCC) has shown durable responses to checkpoint blockade therapies. However, important gaps persist in the understanding of its immune microenvironment. This study aims to investigate the expression and prognostic significance of immune checkpoints in primary and metastatic ccRCC, in relation with mature dendritic cells (DC) and T-cell densities.Experimental Design: We investigated the infiltration and the localization of CD8+ T cells and mature DC, and the expression of immune checkpoints (PD-1, LAG-3, PD-L1, and PD-L2) in relation with prognosis, in 135 primary ccRCC tumors and 51 ccRCC lung metastases. RNA expression data for 496 primary ccRCC samples were used as confirmatory cohort.Results: We identify two groups of tumors with extensive CD8+ T-cell infiltrates. One group, characterized by high expression of immune checkpoints in the absence of fully functional mature DC, is associated with increased risk of disease progression. The second group, characterized by low expression of immune checkpoints and localization of mature DC in peritumoral immune aggregates (tertiary lymphoid structures), is associated with good prognosis.Conclusions: The expression of the immune checkpoints and the localization of DC in the tumor microenvironment modulate the clinical impact of CD8+ T cells in ccRCC. Clin Cancer Res; 21(13); 3031–40. ©2015 AACR.

Purpose: Gallbladder carcinoma (GBC) is an uncommon and aggressive disease, which remains poorly defined at a molecular level. Here, we aimed to characterize the molecular landscape of GBC and identify markers with potential prognostic and therapeutic implications. Experimental Design: GBC samples were analyzed using the MSK-IMPACT (Memorial Sloan Kettering–Integrated Mutation Profiling of Actionable Cancer Targets) platform (targeted NGS assay that analyzes 505 cancer-associated genes). Variants with therapeutic implications were identified using OncoKB database. The associations between recurrent genetic alterations and clinicopathologic characteristics (Fisher exact tests) or overall survival (univariate Cox regression) were evaluated. P values were adjusted for multiple testing. Results: Overall, 244 samples (57% primary tumors and 43% metastases) from 233 patients were studied (85% adenocarcinomas, 10% carcinomas with squamous differentiation, and 5% neuroendocrine carcinomas). The most common oncogenic molecular alterations appeared in the cell cycle (TP53 63% and CDKN2A 21%) and RTK_RAS pathways (ERBB2 15% and KRAS 11%). No recurrent structural variants were identified. There were no differences in the molecular landscape of primary and metastasis samples. Variants in SMAD4 and STK11 independently associated with reduced survival in patients with metastatic disease. Alterations considered clinically actionable in GBC or other solid tumor types (e.g., NTRK1 fusions or oncogenic variants in ERBB2, PIK3CA, or BRCA1/2) were identified in 35% of patients; 18% of patients with metastatic disease were treated off-label or enrolled in a clinical trial based on molecular findings. Conclusions: GBC is a genetically diverse malignancy. This large-scale genomic analysis revealed alterations with potential prognostic and therapeutic implications and provides guidance for the development of targeted therapies.

Introduction: Gallbladder carcinomas (GBC) are rare and aggressive neoplasms. Previous studies in small GBC cohorts have suggested potential molecular alterations associated with poor prognosis, however, a comprehensive understanding of the recurrent genetic events in this cancer type is very limited. In this study, we aim to characterize in detail the recurrent molecular alterations in GBC and their association with pathologic and clinical characteristics. Material and Methods: We studied the prevalence of somatic mutations and copy number alterations (CNA) in n=244 GBC samples (54% primary, 56% metastatic), collected from 2014 to 2021, and sequenced with the targeted NGS panel MSK-IMPACT. We assessed the correlation of the recurrent genomic variants with several pathologic (e.g., T stage, N stage, grade, histologic subtypes) and clinical characteristics (e.g., clinical stage) using Fisher's exact test. We also used Cox Proportional-Hazards modeling to assess the correlation between genetic variants and patient overall survival (OS). Results: The most common histologic subtypes in this GCB cohort included adenocarcinomas NOS (83%), carcinomas with squamous differentiation (9%), high-grade carcinomas (4%), and carcinomas with neuroendocrine differentiation (3%). Most patients were diagnosed with stage IV (65%) and stage III (11%) disease at the time of biopsy/resection, and the mean OS survival was 29.4 months. The most commonly mutated genes were TP53 (59%), SMAD4 (21%), ARID1A (19%), PIK3CA (10%), KRAS (7%), and ERBB2 (7%). Potentially recurrent oncogenic CNAs included deep deletions in CDKN2A (14%) and CDKN2B (14%), and amplifications in MDM2 (12%), ERBB2 (10%), CCNE1 (9%), MYC (7%), and KRAS (7%). RB1, PBRM1, and CTNNB1 variants were more common in cases with neuroendocrine differentiation, whereas alterations in IKZF1 and AGO2 were enriched in cases with squamous differentiation. The most significant event associated with shorted OS was chromosome 12q13-15 amplification i.e., CDK4 p=0.03 HR=2 [95% CI 1-3.6] and MDM2 p=0.05 HR=1.6 [1-2.5], which associated with a median OS of 20 months (vs. 34 months in the wild-type). Genomic variants associated with longer OS included ERBB2 (p=0.006 HR=0.2 [0.06-0.6]), KMT2C (p=0.03 HR=0.2 [0.1-0.9]) and KMT2D (p=0.01 HR=0.2 [0.04-0.7]) mutations, and CDK12 amplification (p=0.04 HR=0.4 [0.2-0.96]). Although ERBB2 amplification was not associated with prognosis, co-amplification of CDK12 and ERBB2 (chromosome 17q12) was frequently observed (Pearson correlation r=0.8). Conclusions: This large-scale genomic analysis reveals recurrent genomic events potentially associated with prognosis in GBC, including single nucleotide variants in ERBB2, KMT2C, and KMT2D, in addition to CNAs in chromosome 12q13-15 and 17q12 regions. This effort will continue to include a detailed analysis of recurrent structural variants, loss of heterozygosity loci, and analysis of the microbiota in this GBC cohort. Citation Format: Nicolas A. Giraldo, Abhinita Mohanty, Chad Vanderbilt, Rose Brannon, Ryma Benayed, Efsevia Vakiani, Ghassan Abou-Alfa, James Harding, Imane El Dika, Nikolaus Schultz, Bob Li, Michael F. Berger, Marc Ladanyi, Eileen O'Reilly, William Jarnagin, Olca Basturk, Maria Arcila. Molecular characterization of gallbladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 82.

For many years, the gold standard cancer grading and staging had focused on the characteristics of the cancer cells and often disregarded the non-tumoral cell compartments. The expansion of research on the tumor immune microenvironment, the successes and dissemination of immunotherapies to treat cancer, and the open access to large -omic databases have allowed the development of novel powerful immune-based prognostic and theranostic biomarkers. Although they often correlate with histopathologic characteristics and TNM staging, in many instances, they are independently associated with, and potentially superior predictors of, the patient's prognosis and response to immunotherapies. As pathologists in the era of precision medicine, we are uniquely positioned to participate in the integration of these histologic and molecular features of the tumor microenvironment to provide the best prognostic information to clinicians and patients. In this review, we summarize some of the most important immune-related prognostic biomarkers in solid cancer, how they integrate with traditional histopathologic (i.e., staging and grading) and novel molecular stratification systems, and their potential role as predictors to response to agents blocking the PD-1/PD-L1 axis.

International audience; The highly complex and heterogenous ecosystem of a tumour not only contains malignant cells, but also interacting cells from the host such as endothelial cells, stromal fibroblasts, and a variety of immune cells that control tumour growth and invasion. It is well established that anti-tumour immunity is a critical hurdle that must be overcome for tumours to initiate, grow and spread and that anti-tumour immunity can be modulated using current immunotherapies to achieve meaningful anti-tumour clinical responses. Pioneering studies in melanoma, ovarian and colorectal cancer have demonstrated that certain features of the tumour immune microenvironment (TME)-in particular, the degree of tumour infiltration by cytotoxic T cells-can predict a patient's clinical outcome. More recently, studies in renal cell cancer have highlighted the importance of assessing the phenotype of the infiltrating T cells to predict early relapse. Furthermore, intricate interactions with non-immune cellular players such as endothelial cells and fibroblasts modulate the clinical impact of immune cells in the TME. Here, we review the critical components of the TME in solid tumours and how they shape the immune cell contexture, and we summarise numerous studies evaluating its clinical significance from a prognostic and theranostic perspective.

IL-1 family cytokines play a dual role in the gut, with different family members contributing either protective or pathogenic effects. IL-36γ is an IL-1 family cytokine involved in polarizing Type-1 immune responses. However, its function in the gut, including in colorectal cancer pathogenesis, is not well appreciated. In a murine model of colon carcinoma, IL-36γ controls tertiary lymphoid structure formation and promotes a Type-1 immune response concurrently with a decrease in expression of immune checkpoint molecules in the tumor microenvironment. Here, we demonstrate that IL-36γ plays a similar role in driving a pro-inflammatory phenotype in human colorectal cancer. We analyzed a cohort of 33 primary colorectal carcinoma tumors using imaging, flow cytometry, and transcriptomics to determine the pattern and role of IL-36γ expression in this disease. In the colorectal tumor microenvironment, we observed IL-36γ to be predominantly expressed by M1 macrophages and cells of the vasculature, including smooth muscle cells and high endothelial venules. This pattern of IL-36γ expression is associated with a CD4(+) central memory T cell infiltrate and an increased density of B cells in tertiary lymphoid structures, as well as with markers of fibrosis. Conversely, expression of the antagonist to IL-36 signaling, IL-1F5, was associated with intratumoral expression of checkpoint molecules, including PD-1, PD-L1, and CTLA4, which can suppress the immune response. These data support a role for IL-36γ in the physiologic immune response to colorectal cancer by sustaining inflammation within the tumor microenvironment. PRECIS: This study reveals the association of intratumoral IL-36γ with established markers of cancer prognosis, indicating the translational relevance of investigating the IL-36 signaling pathway as a therapeutic target in colorectal cancer.

Tumors are highly heterogeneous structures where malignant cells interact with a large variety of cell populations, including a clinically-relevant immune component. We review and compare the most recent methods designed to analyze and quantify the composition of immune and stromal microenvironment of tumors and discuss their use in identification of patients for high risk of progression. If the impact of the various immune components on patient's relapse share common rules in most malignancies, clear cell renal cell tumors behave differently with regards to immunity. We focus on this specific pathology to show how the tumor interacts with the host's immune system and how this intricate relationship shapes the clinical outcome.

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.

Astronomy accelerates tumor imaging Immunohistochemical stains for individual markers revolutionized diagnostic pathology decades ago but cannot capture enough information to accurately predict response to immunotherapy. Newer multiplex immunofluorescent technologies provide the potential to visualize the expression patterns of many functionally relevant molecules but present numerous challenges in accurate image analysis and data handling, particularly over large tumor areas. Drawing from the field of astronomy, in which petabytes of imaging data are routinely analyzed across a wide spectral range, Berry et al. developed a platform for multispectral imaging of whole-tumor sections with high-fidelity single-cell resolution. The resultant AstroPath platform was used to develop a multiplex immunofluorescent assay highly predictive of responses and outcomes for melanoma patients receiving immunotherapy. Science , aba2609, this issue p. eaba2609

Clear-cell renal cell carcinoma (ccRCC) possesses an unmet medical need, particularly at the metastatic stage, when surgery is ineffective. Complement is a key factor in tissue inflammation, favoring cancer progression through the production of complement component 5a (C5a). However, the activation pathways that generate C5a in tumors remain obscure. By data mining, we identified ccRCC as a cancer type expressing concomitantly high expression of the components that are part of the classical complement pathway. To understand how the complement cascade is activated in ccRCC and impacts patients' clinical outcome, primary tumors from three patient cohorts (n = 106, 154, and 43), ccRCC cell lines, and tumor models in complement-deficient mice were used. High densities of cells producing classical complement pathway components C1q and C4 and the presence of C4 activation fragment deposits in primary tumors correlated with poor prognosis. The in situ orchestrated production of C1q by tumor-associated macrophages (TAM) and C1r, C1s, C4, and C3 by tumor cells associated with IgG deposits, led to C1 complex assembly, and complement activation. Accordingly, mice deficient in C1q, C4, or C3 displayed decreased tumor growth. However, the ccRCC tumors infiltrated with high densities of C1q-producing TAMs exhibited an immunosuppressed microenvironment, characterized by high expression of immune checkpoints (i.e., PD-1, Lag-3, PD-L1, and PD-L2). Our data have identified the classical complement pathway as a key inflammatory mechanism activated by the cooperation between tumor cells and TAMs, favoring cancer progression, and highlight potential therapeutic targets to restore an efficient immune reaction to cancer.

Background: Multidimensional, spatially resolved analyses of immune and tumor cells within the TME of patients treated with checkpoint inhibitors will provide clinically translatable mechanistic insights and potentiate biomarker discovery. To achieve this goal, information from pathology specimens needs to be captured at a single cell level with high fidelity and in meaningfully sized cohorts. To date, efforts have been limited by inadequate tissue sampling and previously unrecognized errors in staining, imaging and data analysis. Here we describe the ‘AstroPath' platform, where strategies from the field of astronomy were adapted to study pathology specimens and generate large high quality mIF data. Methods: Potential error was identified and addressed at each stage of 6-plex (PD-1, PD-L1, FoxP3, CD163, CD8, tumor marker) mIF assay development. Whole slides from formalin-fixed paraffin embedded tissue specimens were stained with the optimized assay and imaged using a multispectral microscope (Vectra 3.0) with 20% overlap of high power fields (HPFs). The overlaps were used to quantify and correct optical lens distortion, HPF alignment, and illumination variation. Errors from cell segmentation algorithms, batch-to-batch staining variation, and HPF sampling were also addressed. The resultant mIF data were organized and analyzed using a large, relational database. Results: The optimized mIF assay captured equivalent signal compared to gold standard chromogenic immunohistochemistry and 2x more signal for PD-1, PD-L1 and FoxP3 compared to the manufacturer's recommended protocol. Errors and corrections for imaging included: pixel alignment error reduced from ~10 to Conclusion: Here we present an end-to-end pathology workflow with rigorous quality control for creating quantitative, spatially resolved mIF datasets using lessons derived from the field of astronomy. Such approaches will vastly improve standardization and scalability of mIF technologies, enabling cross-site comparisons and eventual clinical translation as biomarker discovery platforms or standard diagnostic tests. Citation Format: Sneha Berry, Nicolas Giraldo, Benjamin Green, Elizabeth Engle, Haiying Xu, Aleksandra Ogurtsova, Daphne Wang, Julie E. Stein, Peter Nguyen, Suzanne Topalian, Angelo DeMarzo, Drew M. Pardoll, Robert A. Anders, Tricia R. Cottrell, Alexander S. Szalay, Janis M. Taube. The ‘AstroPath' platform for spatially resolved, single cell analysis of the tumor microenvironment (TME) using multispectral immunofluorescence (mIF) [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 6584.

Multiplex IF (mIF) provides a detailed characterization of spatial relationships and complex cell phenotypes in the tumor microenvironment. However, the data-analysis and visualization is complex and time-consuming. Here, we developed a platform to analyze mIF data through flow cytometry workflows (image cytometry), while maintaining spatial information, and applied it to tissue microarrays of metastatic melanoma specimens (n=93; 6-plex mIF panel: PD-1, PD-L1, CD163, CD8, FoxP3, Sox10/S100). Then, we used a UMAP-based approach driven by cell-to-cell distances (rather than fluorescence intensity) to display and analyze geographic organization and cell interactions. Our pipeline provided equivalent results to the digital pathology gold standard with faster run times (5-fold reduction) and higher reproducibility. We identified key prognostic immune variables, including CD8PD1Low and CD8PD1Neg cells which associated with longer overall survival (OS, both p

For many years, the gold standard cancer grading and staging had focused on the characteristics of the cancer cells and often disregarded the non-tumoral cell compartments. The expansion of research on the tumor immune microenvironment, the successes and dissemination of immunotherapies to treat cancer, and the open access to large -omic databases have allowed the development of novel powerful immune-based prognostic and theranostic biomarkers. Although they often correlate with histopathologic characteristics and TNM staging, in many instances, they are independently associated with, and potentially superior predictors of, the patient's prognosis and response to immunotherapies. As pathologists in the era of precision medicine, we are uniquely positioned to participate in the integration of these histologic and molecular features of the tumor microenvironment to provide the best prognostic information to clinicians and patients. In this review, we summarize some of the most important immune-related prognostic biomarkers in solid cancer, how they integrate with traditional histopathologic (i.e., staging and grading) and novel molecular stratification systems, and their potential role as predictors to response to agents blocking the PD-1/PD-L1 axis.

In the recent years, breakthrough advances in the characterization of the tumor-infiltrating immune cells and in the understanding of their influence on tumor invasion and metastasis have been accomplished. These studies have allowed the development of assays quantifying immune infil- trates to predict patient's clinical outcome. Increasing evi- dence supports their utility as prognostic and potentially teragnostic markers. The in-depth characterization of the tu- mor's immune profile and the standard histopathological criteria are becoming the optimal method of tumor classifica- tionin the era ofpersonalizedmedicine.Thisreviewdescribes the major concepts in the anti-tumor immunity field, with particular focus on the tumor immune microenvironment and the delicate balance between inflammatory and anti- tumor immune responses, its importance as a prognostic tool, and its utility as a teragnostic marker for patients receiving new-generation immunotherapies.

As immunotherapy has joined the ranks of mainstay cancer treatment modalities, biomarkers of response and resistance have become highly sought after. Pretreatment biomarkers have the potential to facilitate rational patient selection, perhaps even for those patients who demonstrate unconventional response patterns such as a delayed response or tumor “progression” before evident regression. Immune-related adverse events, some severe, are also observed with this group of agents. Biomarkers of response could help practitioners avoid exposing patients who are unlikely to respond to these potential immune-related side effects. Additionally, the elevated cost of the therapies is another factor driving intensive study in this area.

For a long time, cancer therapy has had as its sole objective the direct elimination of tumor cells. In case of nonmetastatic disease, this is accomplished by surgery, which removes the primary tumor. Radiotherapy and conventional chemotherapies also aimed at targeting tumor cells preferentially. The high capacity of tumor cells to divide as compared to the normal cells makes them more sensitive to agents that physically, in the case of radiotherapy, or chemically, in the case of chemotherapy, attack DNA and lead to cell death. Chemotherapies targeting mutations in tumor cells such as BRAF have been developed as well. However, these approaches also destroy the nonmalignant cells and have local and/or systemic consequences. To increase specificity toward the tumor cells, cytotoxic agents have been coupled to antibodies that bind to the tumor cells in order to allow their specific targeting to the tumor and not to the normal cells. However, the entry of such constructs into tumors still remains a major issue.

A tumour grows in a complex microenvironment composed of stromal cells, lymphoid and myeloid cells, vascular and lymphatic vessels, and the resultant cytokine and chemokine milieu. In most primary tumours, a strong Th1/cytotoxic T cells infiltration correlates with a longer survival. This beneficial effect can be hampered by the presence of M2 polarized macrophages and high VEGF production. Recent studies revealed that the pattern of the tumour microenvironment remains a major prognostic factor even in the metastatic lesions, while been reproducible between the primary and metastatic tumour. Nevertheless the prognostic impact of the Th1/cytotoxic T cell infiltrate could be different according to the origin of the primary tumour. This model highlights a novel tumour cell-dependent immune contexture that predicts patient's clinical outcome and has implications in the use of immunotherapies.

Cancer is a major public health issue and figures among the leading causes of death in the world. Cancer development is a long process, involving the mutation, amplification or deletion of genes and chromosomal rearrangements. The transformed cells change morphologically, enlarge, become invasive and finally detach from the primary tumor to metastasize in other organs through the blood and/or lymph. During this process, the tumor cells interact with their microenvironment, which is complex and composed of stromal and immune cells that penetrate the tumor site via blood vessels and lymphoid capillaries. All subsets of immune cells can be found in tumors, but their respective density, functionality and organization vary from one type of tumor to another. Whereas inflammatory cells play a protumoral role, there is a large body of evidence of effector memory T cells controlling tumor invasion and metastasis. Thus, high densities of memory Th1/CD8 cytotoxic T cells in the primary tumors correlate with good prognosis in most tumor types. Tertiary lymphoid structures, which contain mature dendritic cells (DC) in a T cell zone, proliferating B cells and follicular DC, are found in the tumor stroma and they correlate with intratumoral Th1/CD8 T cell and B cell infiltration. Eventually, tumors undergo genetic and epigenetic modifications that allow them to escape being controlled by the immune system. This comprehensive review describes the immune contexture of human primary and metastatic tumors, how it impacts on patient outcomes and how it could be used as a predictive biomarker and guide immunotherapies.

International audience; Tumors are highly heterogeneous tissues where malignant cells are surrounded by and interact with a complex tumor microenvironment (TME), notably composed of a wide variety of immune cells, as well as vessels and fibroblasts. As the dialectical influence between tumor cells and their TME is known to be clinically crucial, we need tools that allow us to study the cellular composition of the microenvironment. In this focused research review, we report MCP-counter, a methodology based on transcriptomic markers that assesses the proportion of several immune and stromal cell populations in the TME from transcriptomic data, and we highlight how it can provide a way to decipher the complex mechanisms at play in tumors. In several malignancies, MCP-counter scores have been used to show various prognostic impacts of the TME, which we also show to be linked with the mutational burden of tumors. We also compared established molecular classifications of colorectal cancer and clear-cell renal cell carcinoma with the output of MCP-counter, and show that molecular subgroups have different TME profiles, and that these profiles are consistent within a given subgroup. Finally, we provide insights as to how knowing the TME composition may shape patient care in the near future.

Purpose: The efficacy of PD-1 checkpoint blockade as adjuvant therapy in localized clear cell renal cell carcinoma (ccRCC) is currently unknown. The identification of tumor microenvironment (TME) prognostic biomarkers in this setting may help define which patients could benefit from checkpoint blockade and uncover new therapeutic targets. Experimental Design: We performed multiparametric flow cytometric immunophenotypic analysis of T cells isolated from tumor tissue [tumor-infiltrating lymphocytes (TIL)], adjacent non-malignant renal tissue [renal-infiltrating lymphocytes (RIL)], and peripheral blood lymphocytes (PBL), in a cohort of patients (n = 40) with localized ccRCC. Immunophenotypic data were integrated with prognostic and histopathologic variables, T-cell receptor (TCR) repertoire analysis of sorted CD8+PD-1+ TILs, tumor mRNA expression, and digital quantitative immunohistochemistry. Results: On the basis of TIL phenotypic characterization, we identified three dominant immune profiles in localized ccRCC: (i) immune-regulated, characterized by polyclonal/poorly cytotoxic CD8+PD-1+Tim-3+Lag-3+ TILs and CD4+ICOS+ cells with a Treg phenotype (CD25+CD127−Foxp3+/Helios+GITR+), that developed in inflamed tumors with prominent infiltrations by dysfunctional dendritic cells and high PD-L1 expression; (ii) immune-activated, enriched in oligoclonal/cytotoxic CD8+PD-1+Tim-3+ TILs, that represented 22% of the tumors; and (iii) immune-silent, enriched in TILs exhibiting RIL-like phenotype, that represented 56% of patients in the cohort. Only immune-regulated tumors displayed aggressive histologic features, high risk of disease progression in the year following nephrectomy, and a CD8+PD-1+Tim-3+ and CD4+ICOS+ PBL phenotypic signature. Conclusions: In localized ccRCC, the infiltration with CD8+PD-1+Tim-3+Lag-3+ exhausted TILs and ICOS+ Treg identifies the patients with deleterious prognosis who could benefit from adjuvant therapy with TME-modulating agents and checkpoint blockade. This work also provides PBL phenotypic markers that could allow their identification. Clin Cancer Res; 23(15); 4416–28. ©2017 AACR.

International audience; Tertiary lymphoid structures (TLS) are ectopic lymphoid aggregates that reflect lymphoid neogenesis occurring in tissues at sites of inflammation. They are detected in tumors where they orchestrate local and systemic anti-tumor responses. A correlation has been found between high densities of TLS and prolonged patient's survival in more than 10 different types of cancer. TLS can be regulated by the same set of chemokines and cytokines that orchestrate lymphoid organogenesis and by regulatory T cells. Thus, TLS offer a series of putative new targets that could be used to develop therapies aiming to increase the anti-tumor immune response.

International audience; The immune contexture that characterizes the density, the location, the organization and the functional orientation of tumor-infiltrating immune cells in cancers has a clinical impact on patient's outcome. It is, in great part, shaped by the malignant cells, as in a given cancer type, tumors presenting different oncogenic processes have different immune contextures. Moreover, the immune contexture in metastatic sites reflects that of the corresponding primary tumors. Finally, the components forming the immune contexture represent targets and markers of efficient anti-cancer immunotherapies.

The outcome of tumors results from genetic and epigenetic modifications of the transformed cells and also from the interactions of the malignant cells with their tumor microenvironment (TME), which includes immune and inflammatory cells. For a given cancer type, the composition of the immunological TME is not homogeneous. Heterogeneity is found between different cancer types and also between tumors from patients with the same type of cancer. Some tumors exhibit a poor infiltration by immune cells, and others are highly infiltrated by lymphocytes. Among the latter, the architecture of the TME, with the localization of immune cells in the invasive front and the center of the tumor, the presence of tumor-adjacent organized lymphoid aggregates, and the type of inflammatory context, determines the prognostic impact of the infiltrating cells. The description and the understanding of the immune and inflammatory landscape in human tumors are of paramount importance at different levels of patient's care. It completes the mutational, transcriptional, and epigenetic patterns of the malignant cells and open paths to understand how tumor cells shape their immune microenvironment and are shaped by the immune reaction. It provides prognostic and theranostic markers, as well as novel targets for immunotherapies.

The outcome of tumors results from genetic and epigenetic modifications of the transformed cells and also from the interactions of the malignant cells with their tumor microenvironment (TME), which includes immune and inflammatory cells. For a given cancer type, the composition of the immunological TME is not homogeneous. Heterogeneity is found between different cancer types and also between tumors from patients with the same type of cancer. Some tumors exhibit a poor infiltration by immune cells, and others are highly infiltrated by lymphocytes. Among the latter, the architecture of the TME, with the localization of immune cells in the invasive front and the center of the tumor, the presence of tumor-adjacent organized lymphoid aggregates, and the type of inflammatory context, determines the prognostic impact of the infiltrating cells. The description and the understanding of the immune and inflammatory landscape in human tumors are of paramount importance at different levels of patient's care. It completes the mutational, transcriptional, and epigenetic patterns of the malignant cells and open paths to understand how tumor cells shape their immune microenvironment and are shaped by the immune reaction. It provides prognostic and theranostic markers, as well as novel targets for immunotherapies.

Purpose: The tumor microenvironment is formed by many distinct and interacting cell populations, and its composition may predict patients' prognosis and response to therapies. Colorectal cancer is a heterogeneous disease in which immune classifications and four consensus molecular subgroups (CMS) have been described. Our aim was to integrate the composition of the tumor microenvironment with the consensus molecular classification of colorectal cancer. Experimental Design: We retrospectively analyzed the composition and the functional orientation of the immune, fibroblastic, and angiogenic microenvironment of 1,388 colorectal cancer tumors from three independent cohorts using transcriptomics. We validated our findings using immunohistochemistry. Results: We report that colorectal cancer molecular subgroups and microenvironmental signatures are highly correlated. Out of the four molecular subgroups, two highly express immune-specific genes. The good-prognosis microsatellite instable–enriched subgroup (CMS1) is characterized by overexpression of genes specific to cytotoxic lymphocytes. In contrast, the poor-prognosis mesenchymal subgroup (CMS4) expresses markers of lymphocytes and of cells of monocytic origin. The mesenchymal subgroup also displays an angiogenic, inflammatory, and immunosuppressive signature, a coordinated pattern that we also found in breast (n = 254), ovarian (n = 97), lung (n = 80), and kidney (n = 143) cancers. Pathologic examination revealed that the mesenchymal subtype is characterized by a high density of fibroblasts that likely produce the chemokines and cytokines that favor tumor-associated inflammation and support angiogenesis, resulting in a poor prognosis. In contrast, the canonical (CMS2) and metabolic (CMS3) subtypes with intermediate prognosis exhibit low immune and inflammatory signatures. Conclusions: The distinct immune orientations of the colorectal cancer molecular subtypes pave the way for tailored immunotherapies. Clin Cancer Res; 22(16); 4057–66. ©2016 AACR.

Molecular and immune classifications powerfully predict cancer patient's survival and response to therapies. We herein describe the immune tumor microenvironment of molecular subgroups of colorectal and renal cell cancers, revealing a strong correlation between tumor subtypes and distinct immune profiles. peerreview_statement: The publishing and review policy for this title is described in its Aims & Scope. aims_and_scope_url: http://www.tandfonline.com/action/journalInformation?show=aimsScope&journalCode=koni20 ispartof: OncoImmunology vol:4 issue:12 ispartof: location:United States status: published