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Supplementary Methods and Tables Supplementary Table S1. Patient characteristics Supplementary Table S2. Antibodies with isotope tags used in CyTOF analysis Supplementary Table S3. Standard therapy of HPV16+ OPSCC patients

Solid tumors are rich ecosystems of numerous different cell types whose interactions lead to immune escape and resistance to immunotherapy in virtually all patients with metastatic cancer. Here, we have developed a 3D model of human solid tumor tissue that includes tumor cells, fibroblasts, and myeloid and lymphoid immune cells and can represent over a million cells over clinically relevant timeframes. This model accurately reproduced key features of the tissue architecture of human colorectal cancer and could be informed by individual patient data, yielding in silico tumor explants. Stratification of growth kinetics of these explants corresponded to significantly different overall survival in a cohort of patients with metastatic colorectal cancer. We used the model to simulate the effect of chemotherapy, immunotherapies, and cell migration inhibitors alone and in combination. We classified tumors according to tumor and host characteristics, showing that optimal treatment strategies markedly differed between these classes. This platform can complement other patient-specific ex vivo models and can be used for high-throughput screening of combinatorial immunotherapies.Significance: This patient-informed in silico tumor growth model allows testing of different cancer treatment strategies and immunotherapies on a cell/tissue level in a clinically relevant scenario. Cancer Res; 78(17); 5155–63. ©2018 AACR.

Detailed information on the procedure of fitting the mathematical model to clinical data as well as details on treatment simulation.

Purpose: Human papillomavirus (HPV)–associated oropharyngeal squamous cell cancer (OPSCC) has a much better prognosis than HPV-negative OPSCC, and this is linked to dense tumor immune infiltration. As the viral antigens may trigger potent immunity, we studied the relationship between the presence of intratumoral HPV-specific T-cell responses, the immune contexture in the tumor microenvironment, and clinical outcome.Experimental Design: To this purpose, an in-depth analysis of tumor-infiltrating immune cells in a prospective cohort of 97 patients with HPV16-positive and HPV16-negative OPSCC was performed using functional T-cell assays, mass cytometry (CyTOF), flow cytometry, and fluorescent immunostaining of tumor tissues. Key findings were validated in a cohort of 75 patients with HPV16-positive OPSCC present in the publicly available The Cancer Genome Atlas database.Results: In 64% of the HPV16-positive tumors, type I HPV16-specific T cells were present. Their presence was not only strongly related to a better overall survival, a smaller tumor size, and less lymph node metastases but also to a type I–oriented tumor microenvironment, including high numbers of activated CD161+ T cells, CD103+ tissue-resident T cells, dendritic cells (DC), and DC-like macrophages.Conclusions: The viral antigens trigger a tumor-specific T-cell response that shapes a favorable immune contexture for the response to standard therapy. Hence, reinforcement of HPV16-specific T-cell reactivity is expected to boost this process. Clin Cancer Res; 24(3); 634–47. ©2017 AACR.See related commentary by Laban and Hoffmann, p. 505

Supplemental tables

Purpose:The tumor immune microenvironment determines clinical outcome. Whether the original tissue in which a primary tumor develops influences this microenvironment is not well understood.Experimental Design:We applied high-dimensional single-cell mass cytometry [Cytometry by Time-Of-Flight (CyTOF)] analysis and functional studies to analyze immune cell populations in human papillomavirus (HPV)–induced primary tumors of the cervix (cervical carcinoma) and oropharynx (oropharyngeal squamous cell carcinoma, OPSCC).Results:Despite the same etiology of these tumors, the composition and functionality of their lymphocytic infiltrate substantially differed. Cervical carcinoma displayed a 3-fold lower CD4:CD8 ratio and contained more activated CD8+CD103+CD161+ effector T cells and less CD4+CD161+ effector memory T cells than OPSCC. CD161+ effector cells produced the highest cytokine levels among tumor-specific T cells. Differences in CD4+ T-cell infiltration between cervical carcinoma and OPSCC were reflected in the detection rate of intratumoral HPV-specific CD4+ T cells and in their impact on OPSCC and cervical carcinoma survival. The peripheral blood mononuclear cell composition of these patients, however, was similar.Conclusions:The tissue of origin significantly affects the overall shape of the immune infiltrate in primary tumors.

Despite the fact that the local immunological microenvironment shapes the prognosis of colorectal cancer, immunotherapy has shown no benefit for the vast majority of colorectal cancer patients. A better understanding of the complex immunological interplay within the microenvironment is required. In this study, we utilized wet lab migration experiments and quantitative histological data of human colorectal cancer tissue samples (n = 20) including tumor cells, lymphocytes, stroma, and necrosis to generate a multiagent spatial model. The resulting data accurately reflected a wide range of situations of successful and failed immune surveillance. Validation of simulated tissue outcomes on an independent set of human colorectal cancer specimens (n = 37) revealed the model recapitulated the spatial layout typically found in human tumors. Stroma slowed down tumor growth in a lymphocyte-deprived environment but promoted immune escape in a lymphocyte-enriched environment. A subgroup of tumors with less stroma and high numbers of immune cells showed high rates of tumor control. These findings were validated using data from colorectal cancer patients (n = 261). Low-density stroma and high lymphocyte levels showed increased overall survival (hazard ratio 0.322, P = 0.0219) as compared with high stroma and high lymphocyte levels. To guide immunotherapy in colorectal cancer, simulation of immunotherapy in preestablished tumors showed that a complex landscape with optimal stroma permeabilization and immune cell activation is able to markedly increase therapy response in silico. These results can help guide the rational design of complex therapeutic interventions, which target the colorectal cancer microenvironment. Cancer Res; 77(22); 6442–52. ©2017 AACR.

Supplemental figures

Supplementary Figure S1. Handling of oropharyngeal squamous cell carcinoma (OPSCC) material. Supplementary Figure S2. HPV16-positive OPSCC harbor T-cells that specifically recognize the HPV16 oncoproteins E6 and E7. Supplementary Figure S3. High expression of HPV16 antigens by HPV16-positive OPSCC results in induction of HPV16-specific T-cells. Supplementary Figure S4. PHA stimulation of TILs results in differential cytokine production in the various groups of OPSCC patients. Supplementary Figure S5. Mass cytometry analysis reveals importance of CD161 and CD103 expressing intratumoral T-cells in HPV16-positive OPSCC. Supplementary Figure S6. T-helper supernatant neutralizes the type 2 macrophage-like skewing effect of OPSCC tumors. Supplementary Figure S7. Sensitivity and resistance of OPSCC tumor cell lines. Supplementary Figure S8. HPV16-specific CD161+ T-cells are important for controlling the disease.

This file contains all supplementary Tables and Figures. Supplementary Tables show detailed information on the model parameters and on the patient samples that were used in this study. Supplementary Figures show additional details on the model calibration process and on the model behavior and resulting phenotypes.

Supplementary Methods, Figures 4-6 from Coordination of Intratumoral Immune Reaction and Human Colorectal Cancer Recurrence

Supplementary Table 1 from Coordination of Intratumoral Immune Reaction and Human Colorectal Cancer Recurrence

Supplementary Table 3 from Coordination of Intratumoral Immune Reaction and Human Colorectal Cancer Recurrence

A role for the immune system in controlling the progression of solid tumors has been established in several mouse models. However, the effect of immune responses and tumor escape on patient prognosis in the context of human cancer is poorly understood. Here, we investigate the cellular and molecular parameters that could describe in situ immune responses in human colorectal cancer according to clinical parameters of metastatic lymph node or distant organ invasion (META− or META+ patients). Primary tumor samples of colorectal carcinoma were analyzed by integrating large-scale phenotypic (flow cytometry, 39 patients) and gene expression (real time reverse transcription-PCR, 103 patients) data sets related to immune and protumoral processes. In META− colorectal cancer primary tumors with high densities of T cells, we observed significant positive correlations between markers of innate immune cells [tumor-associated macrophages, dendritic cells, natural killer (NK) cells, and NKT cells] and markers of early-activated T cells. Significant correlations were also observed between markers of cytotoxic and effector memory T-cell subpopulations. These correlation profiles were absent in tumors with low T-cell infiltrates and were altered in META+ tumors with high T-cell infiltrates. We show that the coexpression of genes mediating cytotoxicity (GNLY) and Th1 adaptive immune responses (IRF1) accurately predicted patient survival independently of the metastatic status. High intratumoral mRNA expression of the proangiogenic mediator vascular endothelial growth factor was associated with significantly reduced survival rates in patients expressing high mRNA levels of GNLY. Investigation of the colorectal cancer primary tumor microenvironment allowed us to uncover the association of favorable outcomes with efficient coordination of the intratumoral immune response. [Cancer Res 2009;69(6):2685–93]

Supplementary Table 2 from Coordination of Intratumoral Immune Reaction and Human Colorectal Cancer Recurrence

BackgroundPrimary and secondary resistance is a major hurdle in cancer immunotherapy. Therefore, a better understanding of the underlying mechanisms involved in immunotherapy resistance is of pivotal importance to improve therapy outcome.MethodHere, two mouse models with resistance against therapeutic vaccine-induced tumor regression were studied. Exploration of the tumor microenvironment by high dimensional flow cytometry in combination with therapeuticin vivosettings allowed for the identification of immunological factors driving immunotherapy resistance.ResultsComparison of the tumor immune infiltrate during early and late regression revealed a change from tumor-rejecting toward tumor-promoting macrophages. In concert, a rapid exhaustion of tumor-infiltrating T cells was observed. Perturbation studies identified a small but discernible CD163himacrophage population, with high expression of several tumor-promoting macrophage markers and a functional anti-inflammatory transcriptome profile, but not other macrophages, to be responsible. In-depth analyses revealed that they localize at the tumor invasive margins and are more resistant to Csf1r inhibition when compared with other macrophages.In vivostudies validated the activity of heme oxygenase-1 as an underlying mechanism of immunotherapy resistance. The transcriptomic profile of CD163himacrophages is highly similar to a human monocyte/macrophage population, indicating that they represent a target to improve immunotherapy efficacy.ConclusionsIn this study, a small population of CD163hitissue-resident macrophages is identified to be responsible for primary and secondary resistance against T-cell-based immunotherapies. While these CD163hiM2 macrophages are resistant to Csf1r-targeted therapies, in-depth characterization and identification of the underlying mechanisms driving immunotherapy resistance allows the specific targeting of this subset of macrophages, thereby creating new opportunities for therapeutic intervention with the aim to overcome immunotherapy resistance.

BackgroundThe composition of the tumor immune microenvironment (TIME) associated with good prognosis generally also predicts the success of immunotherapy, and both entail the presence of pre-existing tumor-specific T cells. Here, the blueprint of the TIME associated with such an ongoing tumor-specific T-cell response was dissected in a unique prospective oropharyngeal squamous cell carcinoma (OPSCC) cohort, in which tumor-specific tumor-infiltrating T cells were detected (immune responsiveness (IR+)) or not (lack of immune responsiveness (IR−)).MethodsA comprehensive multimodal, high-dimensional strategy was applied to dissect the TIME of treatment-naive IR+ and IR− OPSCC tissue, including bulk RNA sequencing (NanoString), imaging mass cytometry (Hyperion) for phenotyping and spatial interaction analyses of immune cells, and combined single-cell gene expression profiling and T-cell receptor (TCR) sequencing (single-cell RNA sequencing (scRNAseq)) to characterize the transcriptional states of clonally expanded tumor-infiltrating T cells.ResultsIR+ patients had an excellent survival during >10 years follow-up. The tumors of IR+ patients expressed higher levels of genes strongly related to interferon gamma signaling, T-cell activation, TCR signaling, and mononuclear cell differentiation, as well as genes involved in several immune signaling pathways, than IR− patients. The top differently overexpressed genes included CXCL12 and LTB, involved in ectopic lymphoid structure development. Moreover, scRNAseq not only revealed that CD4+ T cells were the main producers of LTB but also identified a subset of clonally expanded CD8+ T cells, dominantly present in IR+ tumors, which secreted the T cell and dendritic cell (DC) attracting chemokine CCL4. Indeed, immune cell infiltration in IR+ tumors is stronger, highly coordinated, and has a distinct spatial phenotypical signature characterized by intratumoral microaggregates of CD8+CD103+ and CD4+ T cells with DCs. In contrast, the IR− TIME comprised spatial interactions between lymphocytes and various immunosuppressive myeloid cell populations. The impact of these chemokines on local immunity and clinical outcome was confirmed in an independent The Cancer Genome Atlas OPSCC cohort.ConclusionThe production of lymphoid cell attracting and organizing chemokines by tumor-specific T cells in IR+ tumors constitutes a positive feedback loop to sustain the formation of the DC–T-cell microaggregates and identifies patients with excellent survival after standard therapy.

The surface inhibitory receptor NKG2A forms heterodimers with the invariant CD94 chain and is expressed on a subset of activated CD8 T cells. As antibodies to block NKG2A are currently tested in several efficacy trials for different tumor indications, it is important to characterize the NKG2A+ CD8 T cell population in the context of other inhibitory receptors. Here we used a well-controlled culture system to study the kinetics of inhibitory receptor expression. Naïve mouse CD8 T cells were synchronously and repeatedly activated by artificial antigen presenting cells in the presence of the homeostatic cytokine IL-7. The results revealed NKG2A as a late inhibitory receptor, expressed after repeated cognate antigen stimulations. In contrast, the expression of PD-1, TIGIT and LAG-3 was rapidly induced, hours after first contact and subsequently down regulated during each resting phase. This late, but stable expression kinetics of NKG2A was most similar to that of TIM-3 and CD39. Importantly, single-cell transcriptomics of human tumor-infiltrating lymphocytes (TILs) showed indeed that these receptors were often coexpressed by the same CD8 T cell cluster. Furthermore, NKG2A expression was associated with cell division and was promoted by TGF-β in vitro, although TGF-β signaling was not necessary in a mouse tumor model in vivo. In summary, our data show that PD-1 reflects recent TCR triggering, but that NKG2A is induced after repeated antigen stimulations and represents a late inhibitory receptor. Together with TIM-3 and CD39, NKG2A might thus mark actively dividing tumor-specific TILs.

BackgroundOropharyngeal squamous cell carcinoma (OPSCC) is the most prevalent type of head and neck cancer. The survival of patients with OPSCC is tightly linked to the intratumoral presence of tumor-specific CD4+ and CD8+ T cells. Yet, immunotherapy is currently far from effective in OPSCC partly due to our limited understanding of its immune microenvironment.MethodsHere a multi-modal, high-dimensional approach was used to dissect the immune landscape in a unique cohort of pre-therapy OPSCC patient samples (n=20) in which intratumoral tumor-specific T cells were either detected (immune response positive, IR+) or not (IR-). This included imaging mass cytometry (Hyperion) for high-dimensional phenotyping, spatial localization and interaction analyses of the cells in the tumor mircoenvironment with our newly developed imaging processing pipeline employing machine learning, Nanostring PanCancer IO360 panel analysis of immune signaling pathways, and combined single-cell gene expression profiling and T cell receptor sequencing (scRNAseq) to characterize the transcriptional states of clonally expanded tumor-infiltrating T cells.ResultsImmune cell infiltration in IR+ tumors is stronger and highly coordinated, with a distinct spatial phenotypic signature characterized by microaggregates of tumor-resident (CD103+) CD8+ and CD4+ T cells and dendritic cells within the tumor cell beds, which retained after permutation based correction for differences in cell frequencies. Furthermore, the increased expression of CXCL12 and LTB produced by CD4+ T cells, both involved in the spatial organization of immune cell infiltration, and the clonal expansion of CD8+ T cells producing the DC-attracting chemokines CCL4 or XCL1 in IR+ OPSCC, indicate that tumor-reactive T cells act as a positive feedback loop in the formation of these aggregates. The impact of these chemokines on local immunity and clinical outcome was confirmed in an independent TCGA OPSCC cohort. In contrast, the IR- OPSCC signature comprised spatial interactions between lymphocytes and different subpopulations of immunosuppressive myeloid cells.ConclusionsOur study reveals that the chemokine-driven spatial immune signature of OPSCC has strong potential as a prognostic and predictive biomarker. While the immune signature of IR+ OPSCC suggests potential benefit from neoadjuvant immunotherapeutic approaches to limit the side effects of current radio(chemo)therapy, that of IR- OPSCC calls for strategies focused on stimulating T cells and counteracting immune suppressive mechanisms.

BackgroundA profound insight into the immune landscape of vulvar squamous cell carcinoma (VSCC) is lacking. Here, an in-depth interrogation of T cell infiltration, local immune contexture, signaling pathways and checkpoint molecule expression was performed in early-stage and late-stage VSCC.MethodsThe type, location, and infiltration pattern of T cells were studied in 109 patients with primary VSCC FIGO stage I–III. RNA expression of genes involved in immune oncology and oncogenic signaling pathways was analyzed in 40 VSCC, matched for prognostic clinicopathological variables, analyzed for HPV and p53 status, and selected based on T cell infiltration.ResultsHigh intraepithelial infiltration with CD4 or CD8 T cells was associated with longer overall and recurrence-free survival and formed an independent prognostic factor, outperforming molecular subtype and stage of the disease. Strong T cell infiltrated VSCC displayed a coordinated immune response reflected by a positive association between T cells and different lymphocyte and myeloid cell subsets. The expression of genes involved in the migration of T cells and myeloid cells, T cell activation and costimulation, interferon (IFN)-γ signaling, cytotoxicity and apoptosis was higher than in low infiltrated tumors. An active immune signaling profile was observed in all inflamed, part of the altered-excluded and not in altered-immunosuppressed or deserted VSCC. While several checkpoint molecules were overexpressed, only PD-L1 expression displayed discriminatory ability and clinical usefulness. High PD-L1 expression was detected in all inflamed and ~60% of the altered-excluded VSCC.ConclusionAn active immune signaling profile is present in 35% of primary FIGO I–III VSCCs, suggesting potential responsiveness to neoadjuvant PD-1/PD-L1 immunotherapy.

Induction of anti-tumor immunity in pancreatic ductal adenocarcinoma (PDA) is an unresolved challenge. Systematic investigation of the microenvironment of primary pancreatic tumors revealed a role of endocrine Langerhans islets in the coordination of immune activation. We found that intratumoral β-cells, regulated via STAT3, secrete C-C motif chemokine ligand 27 (CCL27) and thereby promote a TH1 phenotype in the microenvironment resulting in an enhanced T cell infiltration and prolonged patient survival. The local effect can be abrogated in a patient-based human explant model by inhibition of the CCL27 receptor CCR10. This defense mechanism is paralleled by an impaired metabolic function of Langerhans islets with reduced insulin levels resulting in a dysregulation of glycemic control in patients. Based on these findings, screening of PDA cases (n= 2264) led to the identification of type 2 diabetes mellitus (T2DM) and extractable glycated haemoglobin (HbA1c) levels as response markers for neoadjuvant chemotherapy with fluorouracil, leucovorin, irinotecan and oxaliplatin (FOLFIRINOX). Collectively these data provide insights into the interconnection of T2DM and PDA, and link declining glycemic control to therapeutic efficacy, which can be utilized as a tool for clinical decision-making and improve patient management.

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community.

PURPOSE Conversion of tumor subtype frequently occurs in the course of metastatic breast cancer but is a poorly understood phenomenon. This study aims to compare molecular subtypes with subsequent lung or pleural metastasis. PATIENTS AND METHODS In a cohort of 57 patients with breast cancer and lung or pleural metastasis (BCLPM), we investigated paired primary and metastatic tissues for differential gene expression of 269 breast cancer genes. The PAM50 classifier was applied to identify intrinsic subtypes, and differential gene expression and cluster analysis were used to further characterize subtypes and tumors with subtype conversion. RESULTS In primary breast cancer, the most frequent molecular subtype was luminal A (lumA; 49.1%); it was luminal B (lumB) in BCLPM (38.6%). Subtype conversion occurred predominantly in lumA breast cancers compared with other molecular subtypes (57.1% v 27.6%). In lumA cancers, 62 genes were identified with differential expression in metastatic versus primary disease, compared with only 10 differentially expressed genes in lumB, human epidermal growth factor receptor 2 (HER2)–enriched, and basal subtypes combined. Gene expression changes in lumA cancers affected not only the repression of the estrogen receptor pathway and cell cycle–related genes but also the WNT pathway, proteinases ( MME, MMP11), and motility-associated cytoskeletal proteins (CK5, CK14, CK17). Subtype-switched lumA cancers were further characterized by cell proliferation and cell cycle checkpoint gene upregulation and dysregulation of the p53 pathway. This involved 83 notable gene expression changes. CONCLUSION Our results indicate that gene expression changes and subsequent subtype conversion occur on a large scale in metastatic luminal A–type breast cancer compared with other molecular subtypes. This underlines the significance of molecular changes in metastatic disease, especially in tumors of initially low aggressive potential.

Tumors have evolved mechanisms to escape anti-tumor immunosurveillance. They limit humoral and cellular immune activities in the stroma and render tumors resistant to immunotherapy. Sensitizing tumor cells to immune attack is an important strategy to revert immunosuppression. However, the underlying mechanisms of immune escape are still poorly understood. Here we discover Indoleamine-2,3-dioxygenase-1 (IDO1)+ Paneth cells in the stem cell niche of intestinal crypts and tumors, which promoted immune escape of colorectal cancer (CRC). Ido1 expression in Paneth cells was strictly Stat1 dependent. Loss of IDO1+ Paneth cells in murine intestinal adenomas with tumor cell-specific Stat1 deletion had profound effects on the intratumoral immune cell composition. Patient samples and TCGA expression data suggested corresponding cells in human colorectal tumors. Thus, our data uncovered an immune escape mechanism of CRC and identify IDO1+ Paneth cells as a target for immunotherapy., Pflügler, Svinka et al. identify a subset of Paneth cells in mouse intestinal crypts and tumors, which express the immune checkpoint molecule Ido1 in a Stat1-dependent manner and promote tumor growth. Gene expression data from human colorectal cancer (CRC) suggest that a similar population is present in human cancer and opens the door for further studies of immune escape mechanisms in CRC.

Solid tumors are rich ecosystems of numerous different cell types whose interactions lead to immune escape and resistance to immunotherapy in virtually all patients with metastatic cancer. Here, we have developed a 3D model of human solid tumor tissue that includes tumor cells, fibroblasts, and myeloid and lymphoid immune cells and can represent over a million cells over clinically relevant timeframes. This model accurately reproduced key features of the tissue architecture of human colorectal cancer and could be informed by individual patient data, yielding in silico tumor explants. Stratification of growth kinetics of these explants corresponded to significantly different overall survival in a cohort of patients with metastatic colorectal cancer. We used the model to simulate the effect of chemotherapy, immunotherapies, and cell migration inhibitors alone and in combination. We classified tumors according to tumor and host characteristics, showing that optimal treatment strategies markedly differed between these classes. This platform can complement other patient-specific ex vivo models and can be used for high-throughput screening of combinatorial immunotherapies. Significance: This patient-informed in silico tumor growth model allows testing of different cancer treatment strategies and immunotherapies on a cell/tissue level in a clinically relevant scenario. Cancer Res; 78(17); 5155–63. ©2018 AACR.

It was highlighted that the original article [1] contained a typesetting mistake in the name of Noel Filipe da Cunha Carvalho de Miranda. This was incorrectly captured as Noel Filipe da Cunha Carvahlo de Miranda. It was also highlighted that in Fig. 3C the left panels Y-axis were cropped and in Fig. 5C, CD8 bar was cropped. This Correction article shows the correct Figs. 3 and 5. The original article has been updated.

Despite the fact that the local immunological microenvironment shapes the prognosis of colorectal cancer, immunotherapy has shown no benefit for the vast majority of colorectal cancer patients. A better understanding of the complex immunological interplay within the microenvironment is required. In this study, we utilized wet lab migration experiments and quantitative histological data of human colorectal cancer tissue samples (n = 20) including tumor cells, lymphocytes, stroma, and necrosis to generate a multiagent spatial model. The resulting data accurately reflected a wide range of situations of successful and failed immune surveillance. Validation of simulated tissue outcomes on an independent set of human colorectal cancer specimens (n = 37) revealed the model recapitulated the spatial layout typically found in human tumors. Stroma slowed down tumor growth in a lymphocyte-deprived environment but promoted immune escape in a lymphocyte-enriched environment. A subgroup of tumors with less stroma and high numbers of immune cells showed high rates of tumor control. These findings were validated using data from colorectal cancer patients (n = 261). Low-density stroma and high lymphocyte levels showed increased overall survival (hazard ratio 0.322, P = 0.0219) as compared with high stroma and high lymphocyte levels. To guide immunotherapy in colorectal cancer, simulation of immunotherapy in preestablished tumors showed that a complex landscape with optimal stroma permeabilization and immune cell activation is able to markedly increase therapy response in silico. These results can help guide the rational design of complex therapeutic interventions, which target the colorectal cancer microenvironment. Cancer Res; 77(22); 6442–52. ©2017 AACR.

Purpose: The tumor immune microenvironment determines clinical outcome. Whether the original tissue in which a primary tumor develops influences this microenvironment is not well understood. Experimental Design: We applied high-dimensional single-cell mass cytometry [Cytometry by Time-Of-Flight (CyTOF)] analysis and functional studies to analyze immune cell populations in human papillomavirus (HPV)–induced primary tumors of the cervix (cervical carcinoma) and oropharynx (oropharyngeal squamous cell carcinoma, OPSCC). Results: Despite the same etiology of these tumors, the composition and functionality of their lymphocytic infiltrate substantially differed. Cervical carcinoma displayed a 3-fold lower CD4:CD8 ratio and contained more activated CD8+CD103+CD161+ effector T cells and less CD4+CD161+ effector memory T cells than OPSCC. CD161+ effector cells produced the highest cytokine levels among tumor-specific T cells. Differences in CD4+ T-cell infiltration between cervical carcinoma and OPSCC were reflected in the detection rate of intratumoral HPV-specific CD4+ T cells and in their impact on OPSCC and cervical carcinoma survival. The peripheral blood mononuclear cell composition of these patients, however, was similar. Conclusions: The tissue of origin significantly affects the overall shape of the immune infiltrate in primary tumors.

Background For virtually every patient with colorectal cancer (CRC), hematoxylin–eosin (HE)–stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers. In the present study, we investigated whether deep convolutional neural networks (CNNs) can extract prognosticators directly from these widely available images. Methods and findings We hand-delineated single-tissue regions in 86 CRC tissue slides, yielding more than 100,000 HE image patches, and used these to train a CNN by transfer learning, reaching a nine-class accuracy of >94% in an independent data set of 7,180 images from 25 CRC patients. With this tool, we performed automated tissue decomposition of representative multitissue HE images from 862 HE slides in 500 stage I–IV CRC patients in the The Cancer Genome Atlas (TCGA) cohort, a large international multicenter collection of CRC tissue. Based on the output neuron activations in the CNN, we calculated a “deep stroma score,” which was an independent prognostic factor for overall survival (OS) in a multivariable Cox proportional hazard model (hazard ratio [HR] with 95% confidence interval [CI]: 1.99 [1.27–3.12], p = 0.0028), while in the same cohort, manual quantification of stromal areas and a gene expression signature of cancer-associated fibroblasts (CAFs) were only prognostic in specific tumor stages. We validated these findings in an independent cohort of 409 stage I–IV CRC patients from the “Darmkrebs: Chancen der Verhütung durch Screening” (DACHS) study who were recruited between 2003 and 2007 in multiple institutions in Germany. Again, the score was an independent prognostic factor for OS (HR 1.63 [1.14–2.33], p = 0.008), CRC-specific OS (HR 2.29 [1.5–3.48], p = 0.0004), and relapse-free survival (RFS; HR 1.92 [1.34–2.76], p = 0.0004). A prospective validation is required before this biomarker can be implemented in clinical workflows. Conclusions In our retrospective study, we show that a CNN can assess the human tumor microenvironment and predict prognosis directly from histopathological images., Jakob Nikolas Kather and colleagues demonstrate the ability of deep convolutional neural networks to extract prognostically relevant information from routine histopathological images collected from colorectal cancer patients., Author summary Why was this study done? Colorectal cancer (CRC) is a common disease with a variable clinical course, and there is a high clinical need to more accurately predict the outcome of individual patients. For almost every CRC patient, histological slides of tumor tissue are routinely available. Deep learning can be used to extract information from very complex images, and we hypothesized that deep learning can predict clinical outcome directly from histological images of CRC. What did the researchers do and find? We trained a deep neural network to identify different tissue types that are abundant in histological images of CRC, especially nontumorous (“stromal”) tissue types. We showed that this deep neural network can decompose complex tissue into its constituent parts and that the abundance of each of these tissue parts can be aggregated in a prognostic score. In two independent, multicenter patient cohorts, we showed that this score improves survival prediction compared to the Union Internationale Contre le Cancer (UICC) staging system, which is the current state of the art. What do these findings mean? Deep learning is an inexpensive tool to predict the clinical course of CRC patients based on ubiquitously available histological images. Prospective validation studies are needed to firmly establish this biomarker for routine clinical use.

Lymphoid and myeloid cells are abundant in the tumor microenvironment, can be quantified by immunohistochemistry and shape the disease course of human solid tumors. Yet, there is no comprehensive understanding of spatial immune infiltration patterns (‘topography’) across cancer entities and across various immune cell types. In this study, we systematically measure the topography of multiple immune cell types in 965 histological tissue slides from N = 177 patients in a pan-cancer cohort. We provide a definition of inflamed (‘hot’), non-inflamed (‘cold’) and immune excluded patterns and investigate how these patterns differ between immune cell types and between cancer types. In an independent cohort of N = 287 colorectal cancer patients, we show that hot, cold and excluded topographies for effector lymphocytes (CD8) and tumor-associated macrophages (CD163) alone are not prognostic, but that a bivariate classification system can stratify patients. Our study adds evidence to consider immune topographies as biomarkers for patients with solid tumors.

Summary Tumor-infiltrating CD8 T cells were found to frequently express the inhibitory receptor NKG2A, particularly in immune-reactive environments and after therapeutic cancer vaccination. High-dimensional cluster analysis demonstrated that NKG2A marks a unique immune effector subset preferentially co-expressing the tissue-resident CD103 molecule, but not immune checkpoint inhibitors. To examine whether NKG2A represented an adaptive resistance mechanism to cancer vaccination, we blocked the receptor with an antibody and knocked out its ligand Qa-1b, the conserved ortholog of HLA-E, in four mouse tumor models. The impact of therapeutic vaccines was greatly potentiated by disruption of the NKG2A/Qa-1b axis even in a PD-1 refractory mouse model. NKG2A blockade therapy operated through CD8 T cells, but not NK cells. These findings indicate that NKG2A-blocking antibodies might improve clinical responses to therapeutic cancer vaccines.

Solid tumors are rich ecosystems of numerous different cell types whose interactions lead to immune escape and resistance to immunotherapy in virtually all patients with metastatic cancer. Here, we have developed a 3D model of human solid tumor tissue that includes tumor cells, fibroblasts, and myeloid and lymphoid immune cells and can represent over a million cells over clinically relevant timeframes. This model accurately reproduced key features of the tissue architecture of human colorectal cancer and could be informed by individual patient data, yielding

Purpose: Human papillomavirus (HPV)–associated oropharyngeal squamous cell cancer (OPSCC) has a much better prognosis than HPV-negative OPSCC, and this is linked to dense tumor immune infiltration. As the viral antigens may trigger potent immunity, we studied the relationship between the presence of intratumoral HPV-specific T-cell responses, the immune contexture in the tumor microenvironment, and clinical outcome. Experimental Design: To this purpose, an in-depth analysis of tumor-infiltrating immune cells in a prospective cohort of 97 patients with HPV16-positive and HPV16-negative OPSCC was performed using functional T-cell assays, mass cytometry (CyTOF), flow cytometry, and fluorescent immunostaining of tumor tissues. Key findings were validated in a cohort of 75 patients with HPV16-positive OPSCC present in the publicly available The Cancer Genome Atlas database. Results: In 64% of the HPV16-positive tumors, type I HPV16-specific T cells were present. Their presence was not only strongly related to a better overall survival, a smaller tumor size, and less lymph node metastases but also to a type I–oriented tumor microenvironment, including high numbers of activated CD161+ T cells, CD103+ tissue-resident T cells, dendritic cells (DC), and DC-like macrophages. Conclusions: The viral antigens trigger a tumor-specific T-cell response that shapes a favorable immune contexture for the response to standard therapy. Hence, reinforcement of HPV16-specific T-cell reactivity is expected to boost this process. Clin Cancer Res; 24(3); 634–47. ©2017 AACR. See related commentary by Laban and Hoffmann, p. 505

The cancer immunoediting hypothesis postulates a dual role of the immune system: protecting the host by eliminating tumor cells, and shaping the tumor by editing the genome. However, to what extent immunoediting is shaping the cancer genome is still a matter of debate. Moreover, the impact of cancer immunotherapy with checkpoint blockers on modulating immunoediting remains largely unexplored. Here we elucidated the impact of evolutionary and immune-related forces on editing the tumor in a mouse model of colorectal cancer (CRC). We first show that MC38 cell line is a valid model for hypermutated and microsatellite-unstable (MSI) CRC. Analyses of longitudinal samples of wild type and immunodeficient RAG1 knockout mice transplanted with MC38 cells revealed that upregulation of checkpoint molecules and infiltration of Tregs are the major tumor escape mechanisms. Strikingly, the impact of neutral evolution on sculpting the tumor outweighed immunoediting. Targeting the PD-1/PD-L1 pathway potentiated immunoediting and rendered tumors more homogeneous in the MC38 model. The immunoediting effects were less pronounced in a nonhypermutated/MSI- model CT26. Our study demonstrates that neutral evolution is the major force that sculpts the tumor, and that checkpoint blockade effectively enforces T cell dependent immunoselective pressure in a hypermutated/MSI model of CRC.