Topography of cancer-associated immune cells in human solid tumors

Phase I trial combining chemokine-targeting with loco-regional chemo-immunotherapy for recurrent, platinum-sensitive ovarian cancer shows induction of CXCR3 ligands and markers of type 1 immunity

BACKGROUND

Increased prevalence of cytotoxic T lymphocytes (CTL) in the tumor microenvironment (TME) predicts positive outcomes in patients with epithelial ovarian cancer (EOC), while the regulatory Treg cells predict poor outcomes. Guided by the synergistic activity of TLR3 ligands, interferon-a (IFNa) and cyclooxygenase-2 (COX-2) blockers in selectively enhancing CTL-attractants but suppressing Treg-attractants, we tested a novel intraperitoneal (IP) chemo-immunotherapy combination, to assess its tolerability and TME-modulatory impact in patients with recurrent EOC.

METHODS

Twelve patients were enrolled in phase I portion of the trial NCT02432378, and treated with IP cisplatin, IP rintatolimod (dsRNA, TLR3 ligand) and oral celecoxib (COX-2 blocker). Patients in cohorts 2, 3 and 4 also received IP IFNa at 2, 6 and 18 million units (MU), respectively. Primary objectives were to evaluate safety, identify phase 2 recommended dose (P2RD) and characterize changes in the immune TME. Peritoneal resident cells and IP wash fluid were profiled via NanoString and Meso Scale Discovery (MSD) multiplex assay, respectively.

RESULTS

The P2RD of IFNa was 6 MU. Median progression-free and overall survival were 8.4 and 30 months, respectively. Longitudinal sampling of the peritoneal cavity via IP washes demonstrated local upregulation of interferon-stimulated genes (ISG), including CTL-attracting chemokines (CXCL-9, -10, -11), MHC I/II, perforin and granzymes. These changes were present two days post chemokine modulation and subsided within one week.

CONCLUSION

The chemokine-modulating IP-CITC is safe, tolerable, and associated with ISG changes that favor CTL chemoattraction and function. This combination (plus DC vaccine) will be tested in a phase II trial.

Evolution under Spatially Heterogeneous Selection in Solid Tumors

Spatial genetic and phenotypic diversity within solid tumors has been well documented. Nevertheless, how this heterogeneity affects temporal dynamics of tumorigenesis has not been rigorously examined because solid tumors do not evolve as the standard population genetic model due to the spatial constraint. We therefore, propose a neutral spatial (NS) model whereby the mutation accumulation increases toward the periphery; the genealogical relationship is spatially determined and the selection efficacy is blunted (due to kin competition). In this model, neutral mutations are accrued and spatially distributed in manners different from those of advantageous mutations. Importantly, the distinctions could be blurred in the conventional model. To test the NS model, we performed a three-dimensional multiple microsampling of two hepatocellular carcinomas. Whole-genome sequencing (WGS) revealed a 2-fold increase in mutations going from the center to the periphery. The operation of natural selection can then be tested by examining the spatially determined clonal relationships and the clonal sizes. Due to limited migration, only the expansion of highly advantageous clones can sweep through a large part of the tumor to reveal the selective advantages. Hence, even multiregional sampling can only reveal a fraction of fitness differences in solid tumors. Our results suggest that the NS patterns are crucial for testing the influence of natural selection during tumorigenesis, especially for small solid tumors.

Cancer-Immunity Cycle and Therapeutic Interventions- Opportunities for Including Pet Dogs With Cancer

The tumor-immune interplay represents a dynamic series of events executed by cellular and soluble participants that either promote or inhibit successful tumor formation and growth. Throughout a tumor’s development and progression, the host organism’s immune system reacts by generating anti-cancer defenses through various incremental and combinatorial mechanisms, and this reactive orchestration is termed the cancer-immunity cycle. Success or failure of the cancer-immunity cycle dictates the fate of both host and tumor as winner or loser. Insights into how the tumor and host immune system continuously adapt to each other throughout the lifecycle of the tumor is necessary to rationally develop new effective immunotherapies. Additionally, the evolving nature of the cancer-immunity cycle necessitates therapeutic agility, requiring real-time serial assessment of immunobiologic markers that permits tailoring of therapies to the everchanging tumor immune microenvironment. In order to accelerate advances in the field of immuno-oncology, this review summarizes the steps comprising the cancer-immunity cycle, and underscores key breakpoints in the cycle that either favor cancer regression or progression, as well as shaping of the tumor microenvironment and associated immune phenotypes. Furthermore, specific large animal models of spontaneous cancers that are deemed immunogenic will be reviewed and proposed as unique resources for validating investigational immunotherapeutic protocols that are informed by the cancer-immunity cycle. Collectively, this review will provide a progressive look into the dynamic interplay between tumor and host immune responses and raise awareness for how large animal models can be included for developing combinatorial and sequenced immunotherapies to maximizing favorable treatment outcomes.

Spatial Distribution of Immune Cells in Head and Neck Squamous Cell Carcinomas

Background

Head and neck squamous cell carcinomas (HNSCCs) have a very moderate response rate to immune checkpoint inhibitor (ICI) treatment compared to other cancer types. Lacking predictive markers for treatment response, we analyzed the immune status of HNSCC and assessed the spatial distribution of immune cells.

Materials and Methods

Via assessing hematoxylin–eosin (H&E) stains, we divided HNSCCs by the immune cell distribution in hot, cold, and excluded tumors. For each group, each with 10 tumors, we performed serial immunohistochemical (IHC) staining of the immune cell markers, checkpoint molecules, and immune regulators.

Results

The spatial distributions were different for each immune cell type, allocating regulatory T cells (Tregs) and CD11b cells predominantly in the stroma. CD4 and CD8 cells were present either in the tumor stroma or between cancer cells. Interestingly, the expressions of PD-1 (programmed cell death 1 receptor) and PD-L1 (programmed death-ligand 1) were higher in hot tumors in comparison to cold and excluded tumors. The expression of pSMAD [indicating active transforming growth factor beta (TGF-β)] was higher in excluded tumors.

Conclusion

Different immune cell distribution patterns within tumors might be crucial for ICI treatment response since hot tumors have the highest expressions of PD-1 and PD-L1. TGF-β might be a key regulator for immune cell distribution and a promising therapeutic target that determines the formation of hot or excluded immune patterns.

Advances with antibody-drug conjugates in breast cancer treatment

Antibody-drug conjugate-based therapy for treatment of cancer has attracted much attention because of its enhanced efficacy against numerous cancer types. Commonly, an ADC includes a mAb linked to a therapeutic payload. Antibody, linker and payload are the three main components of ADCs. The high specificity of antibodies is integrated with the strong potency of payloads in ADCs. ADCs with potential cytotoxic small molecules as payloads, generate antibody-mediated cancer therapy. Recently, ADCs with DNA-damaging agents have shown favor over microtubule-targeting agents as payloads. Although ADC resistance can be a barrier to effectiveness, several ADC therapies have been either approved or are in clinical trials for cancer treatment. The ADC-based treatments of breast cancers, particularly TNBC, MDR and metastatic breast cancers, have shown promise in recent years. This review discusses ADC drug designs, and developed for different types of breast cancer including TNBC, MDR and metastatic breast cancer.

The Immune Landscape of Colorectal Cancer

Simple Summary

We sought to provide a detailed overview of the immune landscape of colorectal cancer in the largest study to date in terms of patient numbers and analyzed immune cell types. We applied a multiplex in situ staining method in combination with an advanced scanning and image analysis pipeline akin to flow cytometry, and analyzed 5968 individual multi-layer images of tissue defining in a total of 39,078,450 cells. We considered the location of immune cells with respect to the stroma, and tumor cell compartment and tumor regions in the central part or the invasive margin. To the best of our knowledge, this study is the first comprehensive spatial description of the immune landscape in colorectal cancer using a large population-based cohort and a multiplex immune cell identification.

Abstract

While the clinical importance of CD8+ and CD3+ cells in colorectal cancer (CRC) is well established, the impact of other immune cell subsets is less well described. We sought to provide a detailed overview of the immune landscape of CRC in the largest study to date in terms of patient numbers and in situ analyzed immune cell types. Tissue microarrays from 536 patients were stained using multiplexed immunofluorescence panels, and fifteen immune cell subclasses, representing adaptive and innate immunity, were analyzed. Overall, therapy-naïve CRC patients clustered into an ‘inflamed’ and a ‘desert’ group. Most T cell subsets and M2 macrophages were enriched in the right colon (p-values 0.046–0.004), while pDC cells were in the rectum (p = 0.008). Elderly patients had higher infiltration of M2 macrophages (p = 0.024). CD8+ cells were linked to improved survival in colon cancer stages I-III (q = 0.014), while CD4+ cells had the strongest impact on overall survival in metastatic CRC (q = 0.031). Finally, we demonstrated repopulation of the immune infiltrate in rectal tumors post radiation, following an initial radiation-induced depletion. This study provides a detailed analysis of the in situ immune landscape of CRC paving the way for better diagnostics and providing hints to better target the immune microenvironment.

Identification of Three Core Secretome Genes Associated with Immune Infiltration in High Tumor Mutation Burden Across 14 Major Solid Tumors

Background

Secretome genes, encoding proteins secreted from the cell, are involved in the tumor immune response and correlated with levels of tumor mutation burden (TMB) in multiple tumors. This study aimed to identify core secretome genes and their potential association with immunomodulators and immune infiltration in high TMB groups across 14 major solid tumors through bioinformatics analysis.

Methods

Multi-omics data for 14 major solid tumors were downloaded from The Cancer Genome Atlas (TCGA) database. Patients were divided into high TMB (TMB-high) and low TMB (TMB-low) groups using the median TMB values for each of the solid tumors. The CIBERSORT algorithm was conducted to estimate the proportion of 22 tumor-infiltrating immune cells (TIICs). Kaplan-Meier analysis and the log-rank test were utilized to screened prognosis-related genes. The correlations between core secretome genes and TIICs were analyzed using Spearman correlation coefficients.

Results

In TMB-high groups, multi-omics data analysis revealed that secretome genes were strongly associated with clinical characteristics, and 65 prognosis-related secretome genes were screened. Among the prognosis-related genes, 21 core secretome genes were identified, and strongly associated with five types of TIICs, namely activated NK cells, follicular helper T cells, CD8 T cells, and macrophages M0 and M2. Notably, three secretome genes (ADAMTS12, COL12A1, and COL5A2) were significantly related to immunomodulators and TIICs in multiple solid tumors. In addition, 12 core secretome genes were significantly differentially expressed between responding and non-responding patients receiving immunotherapy. Furthermore, core secretome genes may be involved in the PI3K/AKT signaling pathway.

Conclusion

We examined the prognostic significance of secretome genes and their potential association with immunomodulators and immune infiltration across 14 major solid tumors. In summary, three secretome genes (ADAMTS12, COL12A1, and COL5A2) may be pivotal mediators of immune infiltration in TMB-high patients, which may help to identify patients who could benefit from immunotherapy.

Low tumour-infiltrating lymphocyte density in primary and recurrent glioblastoma

Immunotherapies targeting tumour-infiltrating lymphocytes (TILs) that express the immune checkpoint molecule programmed cell death-1 (PD-1) have shown promise in preclinical glioblastoma models but have had limited success in clinical trials. To assess when glioblastoma is most likely to benefit from immune checkpoint inhibitors we determined the density of TILs in primary and recurrent glioblastoma. Thirteen cases of matched primary and recurrent glioblastoma tissue were immunohistochemically labelled for CD3, CD8, CD4 and PD-1, and TIL density assessed. CD3+ TILs were observed in all cases, with the majority of both primary (69.2%) and recurrent (61.5%) tumours having low density of TILs present. CD8+ TILs were observed at higher densities than CD4+ TILs in both tumour groups. PD-1+ TILs were sparse and present in only 25% of primary and 50% of recurrent tumours. Quantitative analysis of TILs demonstrated significantly higher CD8+ TIL density at recurrence (p = 0.040). No difference was observed in CD3+ (p = 0.191), CD4+ (p = 0.607) and PD-1+ (p = 0.070) TIL density between primary and recurrent groups. This study shows that TILs are present at low densities in both primary and recurrent glioblastoma. Furthermore, PD-1+ TILs were frequently absent, which may provide evidence as to why anti-PD-1 immunotherapy trials have been largely unsuccessful in glioblastoma.

Multiparameter persistent homology landscapes identify immune cell spatial patterns in tumors

Highly resolved spatial data of complex systems encode rich and nonlinear information. Quantification of heterogeneous and noisy data-often with outliers, artifacts, and mislabeled points-such as those from tissues, remains a challenge. The mathematical field that extracts information from the shape of data, topological data analysis (TDA), has expanded its capability for analyzing real-world datasets in recent years by extending theory, statistics, and computation. An extension to the standard theory to handle heterogeneous data is multiparameter persistent homology (MPH). Here we provide an application of MPH landscapes, a statistical tool with theoretical underpinnings. MPH landscapes, computed for (noisy) data from agent-based model simulations of immune cells infiltrating into a spheroid, are shown to surpass existing spatial statistics and one-parameter persistent homology. We then apply MPH landscapes to study immune cell location in digital histology images from head and neck cancer. We quantify intratumoral immune cells and find that infiltrating regulatory T cells have more prominent voids in their spatial patterns than macrophages. Finally, we consider how TDA can integrate and interrogate data of different types and scales, e.g., immune cell locations and regions with differing levels of oxygenation. This work highlights the power of MPH landscapes for quantifying, characterizing, and comparing features within the tumor microenvironment in synthetic and real datasets.

Characterization of immune cell infiltrate in tumor stroma and epithelial compartments in oral squamous cell carcinomas of Sudanese patients

BACKGROUND

Tumor immune infiltrate has been explored in oral squamous cell carcinoma (OSCC), but studies on simultaneous characterization of multiple immune cell subtypes separately in stromal and intraepithelial tumor compartments are limited.

OBJECTIVES

We aimed to investigate the immune cell infiltrate in OSCC by using immunohistochemistry (IHC) for a panel of inflammatory cells in stromal and epithelial tumor compartments for a better characterization of the tumors.

METHODS

Thirty-six OSCC lesions and nine normal oral mucosa (NOM) samples from patients attending Khartoum Dental Teaching Hospital, Sudan were investigated for presence of tumor infiltrating lymphocytes, tumor-associated macrophages, tumor-associated neutrophils, and PD-L1 positive cells in the inflammatory infiltrate by single and double IHC. Digital quantitative analysis (Aperio Technologies Inc.) was performed separately for stromal and epithelial compartments.

RESULTS

OSCC cases displayed a higher inflammatory infiltrate in the associated stroma, but not in the epithelial compartment when compared to NOM. The immunosuppressive type of inflammatory infiltrate, that is, T regulatory cells (FoxP3⁺ cells) was identified to be significantly higher in the epithelial compartment of tumors with advanced clinical state. An immunoscore developed by combining intraepithelial FoxP3⁺ and CD4⁺ cells was found significantly higher in lesions from elderly patients, localized at toombak dipping-related sites, poorly differentiated OSCCs, or with loco-regional lymph node spreading.

CONCLUSIONS

Despite heavy immune cell infiltration in tumor-associated stroma, the majority of OSCCs in this cohort displayed a low intraepithelial immune infiltration. An immunoscore based on combined CD4 and FoxP3 intraepithelial expression may serve as an indicator of advanced tumor progression and should be further investigated for its use as potential prognostic biomarker in OSCC.

Improving the therapeutic index in adoptive cell therapy: key factors that impact efficacy

The therapeutic index (TI) is a quantitative assessment of a drug safety proportional to its effectiveness. The estimation is intuitive when the engagement of the product with its target is dependent on stable chemistry and predictable pharmacokinetics as is the case for small molecules or antibodies. But for therapeutics with complex biodistribution and context-dependent potency such as adoptive cell therapy (ACT) products, TI estimations need to consider a broader array of factors. These include product-dependent variability such as functional fitness, unpredictable pharmacokinetics due to non-specific trapping, sequestration and extravasation into normal tissues and variable rates of in vivo expansion. In the case of solid malignancies, additional modifiers dependent on individual tumor immune biology may affect pharmacodynamics, including differential trafficking to benign compared with cancer tissue, hampered engagement with target cells, immune suppression and cellular dysfunction due to unfavorable metabolic conditions. Here, we propose a patient-specific assessment of factors affecting on-tumor from off-tumor activity in disparate immunologic environments that impact ACT’s clinical efficacy and may favorably balance the TI. for ACT products.

Tumor-Infiltrating PD-1hiCD8+-T-Cell Signature as an Effective Biomarker for Immune Checkpoint Inhibitor Therapy Response Across Multiple Cancers

Background

Stratification of patients who could benefit from immune checkpoint inhibitor (ICI) therapy is of much importance. PD-1^hiCD8⁺ T cells represent a newly identified and effective biomarker for ICI therapy response biomarker in lung cancer. Accurately quantifying these T cells using commonly available RNA sequencing (RNA-seq) data may extend their applications to more cancer types.

Method

We built a transcriptome signature of PD-1^hiCD8⁺ T cells from bulk RNA-seq and single-cell RNA-seq (scRNA-seq) data of tumor-infiltrating immune cells. The signature was validated by flow cytometry and in independent datasets. The clinical applications of the signature were explored in non-small-cell lung cancer, melanoma, gastric cancer, urothelial cancer, and a mouse model of breast cancer samples treated with ICI, and systematically evaluated across 21 cancer types in The Cancer Genome Atlas (TCGA). Its associations with other biomarkers were also determined.

Results

Signature scores could be used to identify the PD-1^hiCD8⁺ T subset and were correlated with the fraction of PD-1^hiCD8⁺ T cells in tumor tissue (Pearson correlation, R=0.76, p=0.0004). Furthermore, in the scRNA-seq dataset, we confirmed the capability of PD-1^hiCD8⁺ T cells to secrete CXCL13, as well as their interactions with other immune cells. In 581 clinical samples and 204 mouse models treated with ICIs, high signature scores were associated with increased survival, and the signature achieved area under the receiver operating characteristic curve scores of 0.755 (ranging from 0.61 to 0.91) in predicting therapy response. In TCGA pan-cancer datasets, our signature scores were consistently correlated with therapy response (R=0.78, p<0.0001) and partially explained the diverse response rates among different cancer types. Finally, our signature generally outperformed other mRNA-based predictors and showed improved predictive performance when used in combination with tumor mutational burden (TMB). The signature score is available in the R package “PD1highCD8Tscore” (https://github.com/Liulab/PD1highCD8Tscore).

Conclusion

Through estimating the fraction of the PD-1^hiCD8⁺ T cell, our signature could predict response to ICI therapy across multiple cancers and could serve as a complementary biomarker to TMB.

Tumor microenvironment is not an 'innocent bystander' in the resistance to treatment of head and neck cancers (Review)

Head and neck cancers are still one of the most common types of cancer in the world. They rank in the leading sixth place in terms of incidence globally, and the incidence continues to rise. The mortality rates remain at high levels. Pathological subclassification places squamous cell carcinoma of the head and neck (HNSCC) in the first place concerning the histological forms of head and neck cancers; a tumor with extremely aggressive behavior and high mortality rates. The tumor microenvironment is a very complex ecosystem of cellular and non-cellular components, characterized by unique features, that contribute to the appearance of immunosuppression and diminished anticancer immunity, impacting patient prognosis and treatment outcome. Despite many important advances in therapy, resistance to therapy represents a difficult challenge in HNSCC patients. Tumor progression, metastasis, and response to therapy are all influenced by the complex ecosystem represented by the tumor microenvironment and by the interactions between cellular and non-cellular components of this system. Therefore, the tumor microenvironment, in the light of recent data, is not an innocent bystander. In the last few years, there has been a sustained effort to characterize the tumor microenvironment, to identify targets of response and identify other mechanisms of tumor-specific immune responses, or to discover other biomarkers of response. There is an urgent need to understand how to properly select patients, the therapy sequence, and how to use feasible biomarkers that can help to identify the patient who may obtain the most benefit from available therapies.

NSCLC Biomarkers to Predict Response to Immunotherapy with Checkpoint Inhibitors (ICI): From the Cells to In Vivo Images

Lung cancer remains the leading cause of cancer-related death, and it is usually diagnosed in advanced stages (stage III or IV). Recently, the availability of targeted strategies and of immunotherapy with checkpoint inhibitors (ICI) has favorably changed patient prognosis. Treatment outcome is closely related to tumor biology and interaction with the tumor immune microenvironment (TME). While the response in molecular targeted therapies relies on the presence of specific genetic alterations in tumor cells, accurate ICI biomarkers of response are lacking, and clinical outcome likely depends on multiple factors that are both host and tumor-related. This paper is an overview of the ongoing research on predictive factors both from in vitro/ex vivo analysis (ranging from conventional pathology to molecular biology) and in vivo analysis, where molecular imaging is showing an exponential growth and use due to technological advancements and to the new bioinformatics approaches applied to image analyses that allow the recovery of specific features in specific tumor subclones.

Identification of prognostic biomarkers related to the tumor microenvironment in thyroid carcinoma

Thyroid Carcinoma (THCA) is the most common endocrine tumor that is mainly treated using surgery and radiotherapy. In addition, immunotherapy is a recently developed treatment option that has played an essential role in the management of several types of tumors. However, few reports exist on the use of immunotherapy to treat THCA. The study downloaded the miRNA, mRNA and lncRNA data for THCA patients from the TCGA database ( https://portal.gdc.cancer.gov/ ). Thereafter, the tumor samples were divided into cold and hot tumors, based on the immune score of the tumor microenvironment. Moreover, the differentially expressed lncRNAs and miRNAs were obtained. Finally, the study jointly constructed a ceRNA network through differential analysis of the mRNA data for cold and hot tumors. The study first assessed the level of immune infiltration in the THCA tumor microenvironment then divided the samples into cold and hot tumors, based on the immune score. Additionally, a total of 568 up-regulated and 412 down-regulated DEGs were screened by analyzing the differences between hot and cold tumors. Thereafter, the study examined the differentially expressed genes for lncRNA and miRNA. The results revealed 629 differentially expressed genes related to lncRNA and 114 associated with miRNA. Finally, a ceRNA network of the differentially expressed genes was constructed. The results showed a five-miRNA hubnet, i.e., hsa-mir-204, hsa-mir-128, hsa-mir-214, hsa-mir-150 and hsa-mir-338. The present study identified the immune-related mRNA, lncRNA and miRNA in THCA then constructed a ceRNA network. These results are therefore important as they provide more insights on the immune mechanisms in THCA. The findings also provides additional information for possible THCA immunotherapy.

A Spatial Quantitative Systems Pharmacology Platform spQSP-IO for Simulations of Tumor-Immune Interactions and Effects of Checkpoint Inhibitor Immunotherapy

Quantitative systems pharmacology (QSP) models have become increasingly common in fundamental mechanistic studies and drug discovery in both academic and industrial environments. With imaging techniques widely adopted and other spatial quantification of tumor such as spatial transcriptomics gaining traction, it is crucial that these data reflecting tumor spatial heterogeneity be utilized to inform the QSP models to enhance their predictive power. We developed a hybrid computational model platform, spQSP-IO, to extend QSP models of immuno-oncology with spatially resolved agent-based models (ABM), combining their powers to track whole patient-scale dynamics and recapitulate the emergent spatial heterogeneity in the tumor. Using a model of non-small-cell lung cancer developed based on this platform, we studied the role of the tumor microenvironment and cancer-immune cell interactions in tumor development and applied anti-PD-1 treatment to virtual patients and studied how the spatial distribution of cells changes during tumor growth in response to the immune checkpoint inhibition treatment. Using parameter sensitivity analysis and biomarker analysis, we are able to identify mechanisms and pretreatment measurements correlated with treatment efficacy. By incorporating spatial data that highlight both heterogeneity in tumors and variability among individual patients, spQSP-IO models can extend the QSP framework and further advance virtual clinical trials.

Prognostic and predictive value of PD-L1 expression and tumour infiltrating lymphocytes (TiLs) in locally advanced NSCLC treated with simultaneous radiochemotherapy in the randomized, multicenter, phase III German Intergroup lung Trial (GILT)

OBJECTIVES

Immune checkpoint inhibition after radiochemotherapy (RTCT) has become a new standard of care for locally advanced non-small cell lung cancer with programmed death-ligand 1 (PD-L1) expression. However, little is known about the prognostic role of immune response markers in this setting. We analysed PD-L1 expression and tumour infiltrating lymphocytes (TiLs) in tumour biopsies from the multicenter German Intergroup Lung Trial (GILT), which previously randomised patients with stage III NSCLC to RTCT with or without consolidation chemotherapy.

MATERIALS AND METHODS

We retrospectively analyzed tumour biopsies from patients treated in the GILT trial. PD-L1 expression was analysed using the Ventana SP263 assay and TiL score (low, intermediate, high) and pattern (excluded, inflamed, desert) were assessed. The primary endpoint of the biomarker analysis was PFS in patients with PD-L1 ≥ 1% vs. PD-L1 < 1% NSCLC. Secondary endpoints explored the prognostic relevance of additional PD-L1 expression levels and TiL score and pattern.

RESULTS

Biopsies were available from 92 patients treated with RTCT. Patients with available tumor tissue did not differ significantly from the whole study population. PD-L1 scores from 78 samples were available for analysis. There was no difference in PFS in the PD-L1 < 1% vs. PD-L1 ≥ 1% subgroups. TiL score was available in 66 patients. Patients with high TiL score showed favourable overall survival compared to the low TiL subgroup. This trend was most pronounced in those patients treated with consolidative chemotherapy.

CONCLUSION

In this analysis, PD-L1 expression did not correlate with PFS following RTCT. However, patients with TiLs > 10% were found to have longer overall survival, especially for those patients treated with consolidation chemotherapy after the end of RTCT. Further analyses to explore the prognostic and predictive relevance of TiLs in the context of consolidative checkpoint inhibition with durvalumab are required.

Spatial distribution of B cells and lymphocyte clusters as a predictor of triple-negative breast cancer outcome

While tumor infiltration by CD8+ T cells is now widely accepted to predict outcomes, the clinical significance of intratumoral B cells is less clear. We hypothesized that spatial distribution rather than density of B cells within tumors may provide prognostic significance. We developed statistical techniques (fractal dimension differences and a box-counting method 'occupancy') to analyze the spatial distribution of tumor-infiltrating lymphocytes (TILs) in human triple-negative breast cancer (TNBC). Our results indicate that B cells in good outcome tumors (no recurrence within 5 years) are spatially dispersed, while B cells in poor outcome tumors (recurrence within 3 years) are more confined. While most TILs are located within the stroma, increased numbers of spatially dispersed lymphocytes within cancer cell islands are associated with a good prognosis. B cells and T cells often form lymphocyte clusters (LCs) identified via density-based clustering. LCs consist either of T cells only or heterotypic mixtures of B and T cells. Pure B cell LCs were negligible in number. Compared to tertiary lymphoid structures (TLS), LCs have fewer lymphocytes at lower densities. Both types of LCs are more abundant and more spatially dispersed in good outcomes compared to poor outcome tumors. Heterotypic LCs in good outcome tumors are smaller and more numerous compared to poor outcome. Heterotypic LCs are also closer to cancer islands in a good outcome, with LC size decreasing as they get closer to cancer cell islands. These results illuminate the significance of the spatial distribution of B cells and LCs within tumors.

Run for your life: an integrated virtual tissue platform for incorporating exercise oncology into immunotherapy

The purpose of this paper is to introduce a novel in silico platform for simulating early-stage solid tumor growth and anti-tumor immune response. We present the model, test the sensitivity and robustness of its parameters, and calibrate it with clinical data from exercise oncology experiments which offer a natural biological backdrop for modulation of anti-tumor immune response. We then perform two virtual experiments with the model that demonstrate its usefulness in guiding pre-clinical and clinical studies of immunotherapy. The first virtual experiment describes the intricate dynamics in the tumor microenvironment between the tumor and the infiltrating immune cells. Such dynamics is difficult to probe during a pre-clinical study as it requires significant redundancy in lab animals and is prohibitively time-consuming and labor-intensive. The result is a series of spatiotemporal snapshots of the tumor and its microenvironment that can serve as a platform to test mechanistic hypotheses on the role and dynamics of different immune cells in anti-tumor immune response. The second virtual experiment shows how dosage and/or frequency of immunotherapy drugs can be optimized based on the aerobic fitness of the patient, so that possible adverse side effects of the treatment can be minimized.

Analysis of Immune Landscape in Pancreatic and Ileal Neuroendocrine Tumours Demonstrates an Immune Cold Tumour Microenvironment

INTRODUCTION

Neuroendocrine tumours (NETs) are rare tumours with an increasing incidence. While low- and intermediate-grade pancreatic NET (PanNET) and small intestinal NET (siNET) are slow growing, they have a relatively high rate of metastasizing to the liver, leading to substantially worse outcomes. In many solid tumours, the outcome is determined by the quality of the antitumour immune response. However, the quality and significance of antitumour responses in NETs are incompletely understood. This study provides clinico-pathological analyses of the tumour immune microenvironment in PanNET and siNETs.

METHODS

Formalin-fixed paraffin-embedded tissue from consecutive resected PanNETs (61) and siNETs (131) was used to construct tissue microarrays (TMAs); 1-mm cores were taken from the tumour centre, stroma, tumour edge, and adjacent healthy tissue. TMAs were stained with antibodies against CD8, CD4, CD68, FoxP3, CD20, and NCR1. T-cell counts were compared with counts from lung cancers.

RESULTS

For PanNET, median counts were CD8+ 35.4 cells/mm2, CD4+ 7.6 cells/mm2, and CD68+ macrophages 117.7 cells/mm2. For siNET, there were CD8+ 39.2 cells/mm2, CD4+ 24.1 cells/mm2, and CD68+ 139.2 cells/mm2. The CD8+ cell density in the tumour and liver metastases were significantly lower than in the adjacent normal tissues, without evidence of a cell-rich area at the tumour edge that might have suggested immune exclusion. T-cell counts in lung cancer were significantly higher than those in PanNET and siNETs: CD8+ 541 cells/mm2 and CD4+ 861 cells/mm2 (p ≤ 0.0001).

CONCLUSION

PanNETs and siNETs are immune cold with no evidence of T cell exclusion; the low density of immune infiltrates indicates poor antitumour immune responses.

Distinct Patterns of Myeloid Cell Infiltration in Patients With hrHPV-Positive and hrHPV-Negative Penile Squamous Cell Carcinoma: The Importance of Assessing Myeloid Cell Densities Within the Spatial Context of the Tumor

Comprehensive analysis of tumor infiltrating myeloid cells in the tumor microenvironment of penile squamous cell carcinoma (PSCC) is lacking. In this retrospective study, for the first time, PSCC resection specimens (N = 103) were annotated into the following compartments: intratumoral tumor (IT Tumor), intratumoral stroma (IT Stroma), peritumoral tumor (PT Tumor) and peritumoral stroma (PT Stroma) compartments. We then quantified CD14+, CD68+ and CD163+ myeloid cells within these compartments using an image analysis software and assessed their association with various clinical parameters, including high-risk human papillomavirus (hrHPV) status. In the total cohort, hrHPV status, grade of differentiation, age and tumor size were associated with myeloid cell densities. hrHPV⁺ tumors had higher infiltration rates of CD14+, CD68+ and CD163+ myeloid cells in the IT tumor compartment (p < 0.001, for all) compared to hrHPV^- tumors. Furthermore, when examining the association between compartment-specific infiltration and differentiation grade, increased myeloid cell densities in the IT tumor compartment were associated with a more advanced histological grade (p < 0.001, for all). This association remained significant when the hrHPV^- cohort (N = 60) was analyzed (CD14+ p = 0.001; CD68+ p < 0.001; CD163+ p = 0.004). Subgroup analysis in the hrHPV⁺ group (N = 43) showed that high infiltration rates of CD68+ and CD163+ cells in the PT tumor compartment were associated with lymph node (LN) metastasis (p = 0.031 and p = 0.026, respectively). Regarding the association between myeloid cell densities and disease-specific survival, the risk of death was found to decrease slightly as the number of myeloid cells in the IT tumor compartment increased (CD14+ p = 0.04; CD68+ p = 0.05; CD163+ p = 0.02). However, after adjusting for hrHPV, no independent association between myeloid densities and disease-specific survival were found. Altogether, these findings demonstrate the importance of assessing myeloid cell densities within the spatial context of the tumor. Further studies are needed to unravel the specific phenotype of myeloid cells residing in the different compartments, their effect on clinical parameters and the impact of hrHPV on the recruitment of myeloid cell populations in PSCC.

The REASON score: an epigenetic and clinicopathologic score to predict risk of poor survival in patients with early stage oral squamous cell carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is a capricious cancer with poor survival rates, even for early-stage patients. There is a pressing need to develop more precise risk assessment methods to appropriately tailor clinical treatment. Genome-wide association studies have not produced a viable biomarker. However, these studies are limited by using heterogeneous cohorts, not focusing on methylation although OSCC is a heavily epigenetically-regulated cancer, and not combining molecular data with clinicopathologic data for risk prediction. In this study we focused on early-stage (I/II) OSCC and created a risk score called the REASON score, which combines clinicopathologic characteristics with a 12-gene methylation signature, to predict the risk of 5-year mortality.

METHODS

We combined data from an internal cohort (n = 515) and The Cancer Genome Atlas (TCGA) cohort (n = 58). We collected clinicopathologic data from both cohorts to derive the non-molecular portion of the REASON score. We then analyzed the TCGA cohort DNA methylation data to derive the molecular portion of the risk score.

RESULTS

5-year disease specific survival was 63% for the internal cohort and 86% for the TCGA cohort. The clinicopathologic features with the highest predictive ability among the two the cohorts were age, race, sex, tobacco use, alcohol use, histologic grade, stage, perineural invasion (PNI), lymphovascular invasion (LVI), and margin status. This panel of 10 non-molecular features predicted 5-year mortality risk with a concordance (c)-index = 0.67. Our molecular panel consisted of a 12-gene methylation signature (i.e., HORMAD2, MYLK, GPR133, SOX8, TRPA1, ABCA2, HGFAC, MCPH1, WDR86, CACNA1H, RNF216, CCNJL), which had the most significant differential methylation between patients who survived vs. died by 5 years. All 12 genes have already been linked to survival in other cancers. Of the genes, only SOX8 was previously associated with OSCC; our study was the first to link the remaining 11 genes to OSCC survival. The combined molecular and non-molecular panel formed the REASON score, which predicted risk of death with a c-index = 0.915.

CONCLUSIONS

The REASON score is a promising biomarker to predict risk of mortality in early-stage OSCC patients. Validation of the REASON score in a larger independent cohort is warranted.

A Sweet Approach to Heat Up Cancer Response to Immunotherapy

Song and colleagues describe how N-glycans stabilize expression of checkpoint molecule B7-H4 that suppresses T-cell function. Inhibiting N-glycan stabilization of B7-H4 generates an immune hot cancer that is more responsive to combination therapies.See related article by Song et al., p. 1872.

A Review on Cancer Immunotherapy and Applications of Nanotechnology to Chemoimmunotherapy of Different Cancers

Clinically, different approaches are adopted worldwide for the treatment of cancer, which still ranks second among all causes of death. Immunotherapy for cancer treatment has been the focus of attention in recent years, aiming for an eventual antitumoral effect through the immune system response to cancer cells both prophylactically and therapeutically. The application of nanoparticulate delivery systems for cancer immunotherapy, which is defined as the use of immune system features in cancer treatment, is currently the focus of research. Nanomedicines and nanoparticulate macromolecule delivery for cancer therapy is believed to facilitate selective cytotoxicity based on passive or active targeting to tumors resulting in improved therapeutic efficacy and reduced side effects. Today, with more than 55 different nanomedicines in the market, it is possible to provide more effective cancer diagnosis and treatment by using nanotechnology. Cancer immunotherapy uses the body's immune system to respond to cancer cells; however, this may lead to increased immune response and immunogenicity. Selectivity and targeting to cancer cells and tumors may lead the way to safer immunotherapy and nanotechnology-based delivery approaches that can help achieve the desired success in cancer treatment.

Direct Tumor Killing and Immunotherapy through Anti-SerpinB9 Therapy

Cancer therapies kill tumors either directly or indirectly by evoking immune responses and have been combined with varying levels of success. Here, we describe a paradigm to control cancer growth that is based on both direct tumor killing and the triggering of protective immunity. Genetic ablation of serine protease inhibitor SerpinB9 (Sb9) results in the death of tumor cells in a granzyme B (GrB)-dependent manner. Sb9-deficient mice exhibited protective T cell-based host immunity to tumors in association with a decline in GrB-expressing immunosuppressive cells within the tumor microenvironment (TME). Maximal protection against tumor development was observed when the tumor and host were deficient in Sb9. The therapeutic utility of Sb9 inhibition was demonstrated by the control of tumor growth, resulting in increased survival times in mice. Our studies describe a molecular target that permits a combination of tumor ablation, interference within the TME, and immunotherapy in one potential modality.

Multiplex Immunofluorescence Tyramide Signal Amplification for Immune Cell Profiling of Paraffin-Embedded Tumor Tissues

Every day, more evidence is revealed regarding the importance of the relationship between the response to cancer immunotherapy and the cancer immune microenvironment. It is well established that a profound characterization of the immune microenvironment is needed to identify prognostic and predictive immune biomarkers. To this end, we find phenotyping cells by multiplex immunofluorescence (mIF) a powerful and useful tool to identify cell types in biopsy specimens. Here, we describe the use of mIF tyramide signal amplification for labeling up to eight markers on a single slide of formalin-fixed, paraffin-embedded tumor tissue to phenotype immune cells in tumor tissues. Different panels show different markers, and the different panels can be used to characterize immune cells and relevant checkpoint proteins. The panel design depends on the research hypothesis, the cell population of interest, or the treatment under investigation. To phenotype the cells, image analysis software is used to identify individual marker expression or specific co-expression markers, which can differentiate already selected phenotypes. The individual-markers approach identifies a broad number of cell phenotypes, including rare cells, which may be helpful in a tumor microenvironment study. To accurately interpret results, it is important to recognize which receptors are expressed on different cell types and their typical location (i.e., nuclear, membrane, and/or cytoplasm). Furthermore, the amplification system of mIF may allow us to see weak marker signals, such as programmed cell death ligand 1, more easily than they are seen with single-marker immunohistochemistry (IHC) labeling. Finally, mIF technologies are promising resources for discovery of novel cancer immunotherapies and related biomarkers. In contrast with conventional IHC, which permits only the labeling of one single marker per tissue sample, mIF can detect multiple markers from a single tissue sample, and at the same time, deliver extensive information about the cell phenotypes composition and their spatial localization. In this matter, the phenotyping process is critical and must be done accurately by a highly trained personal with knowledge of immune cell protein expression and tumor pathology.

Comprehensive Analysis of Myeloid Signature Genes in Head and Neck Squamous Cell Carcinoma to Predict the Prognosis and Immune Infiltration

Myeloid cells are a major heterogeneous cell population in the tumor immune microenvironment (TIME). Imbalance of myeloid response remains a major obstacle to a favorable prognosis and successful immune therapy. Therefore, we aimed to construct a risk model to evaluate the myeloid contexture, which may facilitate the prediction of prognosis and immune infiltration in patients with head and neck squamous cell carcinoma (HNSCC). In our study, six myeloid signature genes (including CCL13, CCR7, CD276, IL1B, LYVE1 and VEGFC) analyzed from 52 differentially expressed myeloid signature genes were finally pooled to establish a prognostic risk model, termed as myeloid gene score (MGS) in a training cohort and validated in a test cohort and an independent external cohort. Furthermore, based on the MGS subgroups, we were able to effectively identify patients with a poor prognosis, aggressive clinical parameters, immune cell infiltration status and immunotherapy response. Thus, MGS may serve as an effective prognostic signature and predictive indicator for immunotherapy response in patients with HNSCC.

The Future of Cancer Diagnosis, Treatment and Surveillance: A Systemic Review on Immunotherapy and Immuno-PET Radiotracers

Immunotherapy is an effective therapeutic option for several cancers. In the last years, the introduction of checkpoint inhibitors (ICIs) has shifted the therapeutic landscape in oncology and improved patient prognosis in a variety of neoplastic diseases. However, to date, the selection of the best patients eligible for these therapies, as well as the response assessment is still challenging. Patients are mainly stratified using an immunohistochemical analysis of the expression of antigens on biopsy specimens, such as PD-L1 and PD-1, on tumor cells, on peritumoral immune cells and/or in the tumor microenvironment (TME). Recently, the use and development of imaging biomarkers able to assess in-vivo cancer-related processes are becoming more important. Today, positron emission tomography (PET) with 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) is used routinely to evaluate tumor metabolism, and also to predict and monitor response to immunotherapy. Although highly sensitive, FDG-PET in general is rather unspecific. Novel radiopharmaceuticals (immuno-PET radiotracers), able to identify specific immune system targets, are under investigation in pre-clinical and clinical settings to better highlight all the mechanisms involved in immunotherapy. In this review, we will provide an overview of the main new immuno-PET radiotracers in development. We will also review the main players (immune cells, tumor cells and molecular targets) involved in immunotherapy. Furthermore, we report current applications and the evidence of using [18F]FDG PET in immunotherapy, including the use of artificial intelligence (AI).

Bioinspired Cell Silicification: From Extracellular to Intracellular

In nature, biosilicification directs the formation of elaborate amorphous silica exoskeletons that provide diatoms mechanically strong, chemically inert, non-decomposable silica armor conferring chemical and thermal stability as well as resistance to microbial attack, without changing the optical transparency or adversely effecting nutrient and waste exchange required for growth. These extraordinary silica/cell biocomposites have inspired decades of biomimetic research aimed at replication of diatoms' hierarchically organized exoskeletons, immobilization of cells or living organisms within silica matrices and coatings to protect them against harmful external stresses, genetic re-programming of cellular functions by virtue of physico-chemical confinement within silica, cellular integration into devices, and endowment of cells with non-native, abiotic properties through facile silica functionalization. In this Perspective, we focus our discussions on the development and concomitant challenges of bioinspired cell silicification ranging from "cells encapsulated within 3D silica matrices" and "cells encapsulated within 2D silica shells" to extra- and intracellular silica replication, wherein all biomolecular interfaces are encased within nanoscopic layers of amorphous silica. We highlight notable examples of advances in the science and technology of biosilicification and consider challenges to advancing the field, where we propose cellular "mineralization" with arbitrary nanoparticle exoskeletons as a generalizable means to impart limitless abiotic properties and functions to cells, and, based on the interchangeability of water and silicic acid and analogies between amorphous ice and amorphous silica, we consider "freezing" cells within amorphous silica as an alternative to cryo-preservation.

Myeloid cell heterogeneity in lung cancer: implication for immunotherapy

Lung is a specialized tissue where metastases from primary lung tumors takeoff and those originating from extra-pulmonary sites land. One commonality characterizing these processes is the supportive role exerted by myeloid cells, particularly neutrophils, whose recruitment is facilitated in this tissue microenvironment. Indeed, neutrophils have important part in the pathophysiology of this organ and the key mechanisms regulating neutrophil expansion and recruitment during infection can be co-opted by tumor cells to promote growth and metastasis. Although neutrophils dominate the myeloid landscape of lung cancer other populations including macrophages, dendritic cells, mast cells, basophils and eosinophils contribute to the complexity of lung cancer TME. In this review, we discuss the origin and significance of myeloid cells heterogeneity in lung cancer, which translates not only in a different frequency of immune populations but it encompasses state of activation, morphology, localization and mutual interactions. The relevance of such heterogeneity is considered in the context of tumor growth and response to immunotherapy.

Assessment of Immunological Features in Muscle-Invasive Bladder Cancer Prognosis Using Ensemble Learning

The clinical staging and prognosis of muscle-invasive bladder cancer (MIBC) routinely includes the assessment of patient tissue samples by a pathologist. Recent studies corroborate the importance of image analysis in identifying and quantifying immunological markers from tissue samples that can provide further insight into patient prognosis. In this paper, we apply multiplex immunofluorescence to MIBC tissue sections to capture whole-slide images and quantify potential prognostic markers related to lymphocytes, macrophages, tumour buds, and PD-L1. We propose a machine-learning-based approach for the prediction of 5 year prognosis with different combinations of image, clinical, and spatial features. An ensemble model comprising several functionally different models successfully stratifies MIBC patients into two risk groups with high statistical significance (p value < 1×10-5). Critical to improving MIBC survival rates, our method correctly classifies 71.4% of the patients who succumb to MIBC, which is significantly more than the 28.6% of the current clinical gold standard, the TNM staging system.

The microbiome and human cancer

Microbial roles in cancer formation, diagnosis, prognosis, and treatment have been disputed for centuries. Recent studies have provocatively claimed that bacteria, viruses, and/or fungi are pervasive among cancers, key actors in cancer immunotherapy, and engineerable to treat metastases. Despite these findings, the number of microbes known to directly cause carcinogenesis remains small. Critically evaluating and building frameworks for such evidence in light of modern cancer biology is an important task. In this Review, we delineate between causal and complicit roles of microbes in cancer and trace common themes of their influence through the host's immune system, herein defined as the immuno-oncology-microbiome axis. We further review evidence for intratumoral microbes and approaches that manipulate the host's gut or tumor microbiome while projecting the next phase of experimental discovery.

Leukocyte Heterogeneity in Pancreatic Ductal Adenocarcinoma: Phenotypic and Spatial Features Associated with Clinical Outcome

Immunotherapies targeting aspects of T cell functionality are efficacious in many solid tumors, but pancreatic ductal adenocarcinoma (PDAC) remains refractory to these treatments. Deeper understanding of the PDAC immune ecosystem is needed to identify additional therapeutic targets and predictive biomarkers for therapeutic response and resistance monitoring. To address these needs, we quantitatively evaluated leukocyte contexture in 135 human PDACs at single-cell resolution by profiling density and spatial distribution of myeloid and lymphoid cells within histopathologically defined regions of surgical resections from treatment-naive and presurgically (neoadjuvant)-treated patients and biopsy specimens from metastatic PDAC. Resultant data establish an immune atlas of PDAC heterogeneity, identify leukocyte features correlating with clinical outcomes, and, through an in silico study, provide guidance for use of PDAC tissue microarrays to optimally measure intratumoral immune heterogeneity. Atlas data have direct applicability as a reference for evaluating immune responses to investigational neoadjuvant PDAC therapeutics where pretherapy baseline specimens are not available. SIGNIFICANCE: We provide a phenotypic and spatial immune atlas of human PDAC identifying leukocyte composition at steady state and following standard neoadjuvant therapies. These data have broad utility as a resource that can inform on leukocyte responses to emerging therapies where baseline tissues were not acquired.This article is highlighted in the In This Issue feature, p. 1861.

Layilin augments integrin activation to promote antitumor immunity

Tumor-infiltrating CD8+ T cells mediate antitumor immune responses. However, the mechanisms by which T cells remain poised to kill cancer cells despite expressing high levels of inhibitory receptors are unknown. Here, we report that layilin, a C-type lectin domain-containing membrane glycoprotein, is selectively expressed on highly activated, clonally expanded, but phenotypically exhausted CD8+ T cells in human melanoma. Lineage-specific deletion of layilin on murine CD8+ T cells reduced their accumulation in tumors and increased tumor growth in vivo. Congruently, gene editing of LAYN in human CD8+ T cells reduced direct tumor cell killing ex vivo. On a molecular level, layilin colocalized with integrin αLβ2 (LFA-1) on T cells, and cross-linking layilin promoted the activated state of this integrin. Accordingly, LAYN deletion resulted in attenuated LFA-1-dependent cellular adhesion. Collectively, our results identify layilin as part of a molecular pathway in which exhausted or "dysfunctional" CD8+ T cells enhance cellular adhesiveness to maintain their cytotoxic potential.

Deep learning quantified mucus-tumor ratio predicting survival of patients with colorectal cancer using whole-slide images

Background

In colorectal cancer (CRC), mucinous adenocarcinoma differs from other adenocarcinomas in gene-phenotype, morphology, and prognosis. However, mucinous components are present in a large number of adenocarcinomas, and the prognostic value of mucus proportion has not been investigated. Artificial intelligence provides a way to quantify mucus proportion on whole-slide images (WSIs) accurately. We aimed to quantify mucus proportion by deep learning and further investigate its prognostic value in two CRC patient cohorts.

Methods

Deep learning was used to segment WSIs stained with hematoxylin and eosin. Mucus-tumor ratio (MTR) was defined as the proportion of mucinous component in the tumor area. A training cohort (N = 419) and a validation cohort (N = 315) were used to evaluate the prognostic value of MTR. Survival analysis was performed using the Cox proportional hazard model.

Result

Patients were stratified to mucus-low and mucus-high groups, with 24.1% as the threshold. In the training cohort, patients with mucus-high had unfavorable outcomes (hazard ratio for high vs. low 1.88, 95% confidence interval 1.18-2.99, P = 0.008), with 5-year overall survival rates of 54.8% and 73.7% in mucus-high and mucus-low groups, respectively. The results were confirmed in the validation cohort (2.09, 1.21-3.60, 0.008; 62.8% vs. 79.8%). The prognostic value of MTR was maintained in multivariate analysis for both cohorts.

Conclusion

The deep learning quantified MTR was an independent prognostic factor in CRC. With the advantages of advanced efficiency and high consistency, our method is suitable for clinical application and promotes precision medicine development.

Current and Future Perspectives of PD-1/PDL-1 Blockade in Cancer Immunotherapy

Cancer immunotherapy, which reactivates weakened immune cells of cancer patients, has yielded great success in recent years. Among immunotherapeutic agents, immune checkpoint inhibitors have been of particular interest and have gained approval by the FDA for treatment of cancers. Immune checkpoint blockade through targeting programmed cell death protein-1 (PD-1) has demonstrated promising antitumor effects in cancer immunotherapy of many different solid and hematologic malignancies. However, despite promising results, a favorable response is observed only in a fraction of patients, and there is still lack of a single therapy modality with curative ability. In this paper, we review the current and future perspectives of PD-1/L1 blockade in cancer immunotherapy, with a particular focus on predictive biomarkers of response to therapy. We also discuss the adverse events associated with PD-1/L1/2 inhibitors, ranging from severe life-threatening conditions such as autoimmune myocarditis to mild and moderate reactions such as skin rashes, and explore the potential strategies for improving the efficacy of immunotherapy with PD-1/L1 checkpoint inhibitors.

Physics approaches to the spatial distribution of immune cells in tumors

The goal of immunotherapy is to mobilize the immune system to kill cancer cells. Immunotherapy is more effective and, in general, the prognosis is better, when more immune cells infiltrate the tumor. We explore the question of whether the spatial distribution rather than just the density of immune cells in the tumor is important in forecasting whether cancer recurs. After reviewing previous work on this issue, we introduce a novel application of maximum entropy to quantify the spatial distribution of discrete point-like objects. We apply our approach to B and T cells in images of tumor tissue taken from triple negative breast cancer patients. We find that the immune cells are more spatially dispersed in good clinical outcome (no recurrence of cancer within at least 5 years of diagnosis) compared to poor clinical outcome (recurrence within 3 years of diagnosis). Our results highlight the importance of spatial distribution of immune cells within tumors with regard to clinical outcome, and raise new questions on their role in cancer recurrence.

Immunosuppressive Myeloid Cells Induce Nitric Oxide-Dependent DNA Damage and p53 Pathway Activation in CD8+ T Cells

Tumor-infiltrating myeloid-derived suppressor cells (MDSC) are associated with poor survival outcomes in many human cancers. MDSCs inhibit T cell-mediated tumor immunity in part because they strongly inhibit T-cell function. However, whether MDSCs inhibit early or later steps of T-cell activation is not well established. Here we show that MDSCs inhibited proliferation and induced apoptosis of CD8⁺ T cells even in the presence of dendritic cells (DC) presenting a high-affinity cognate peptide. This inhibitory effect was also observed with delayed addition of MDSCs to cocultures, consistent with functional data showing that T cells expressed multiple early activation markers even in the presence of MDSCs. Single-cell RNA-sequencing analysis of CD8⁺ T cells demonstrated a p53 transcriptional signature in CD8⁺ T cells cocultured with MDSCs and DCs. Confocal microscopy showed induction of DNA damage and nuclear accumulation of activated p53 protein in a substantial fraction of these T cells. DNA damage in T cells was dependent on the iNOS enzyme and subsequent nitric oxide release by MDSCs. Small molecule-mediated inhibition of iNOS or inactivation of the Nos2 gene in MDSCs markedly diminished DNA damage in CD8⁺ T cells. DNA damage in CD8⁺ T cells was also observed in KPC pancreatic tumors but was reduced in tumors implanted into Nos2-deficient mice compared with wild-type mice. These data demonstrate that MDSCs do not block early steps of T-cell activation but rather induce DNA damage and p53 pathway activation in CD8⁺ T cells through an iNOS-dependent pathway.

Immunologic "Cold" Squamous Cell Carcinomas of the Head and Neck Are Associated With an Unfavorable Prognosis

Background: Head and neck squamous cell carcinoma (HNSCC) represents a common cancer worldwide. Past therapeutic advances have not significantly improved HNSCC prognosis. Therefore, it is necessary to further stratify HNSCC, especially with recent advances in tumor immunology.

Methods: Tissue microarrays were assembled from tumor tissue samples and were complemented with comprehensive clinicopathological data of n = 419 patients. H&E whole slides from resection specimen (n = 289) were categorized according to their immune cell infiltrate as “hot,” “cold,” or “excluded.”

Results: Investigating tumor immune cell patterns, we found significant differences in survival rates. Immunologic “hot” and “excluded” HNSCCs are associated with better overall survival than “cold” HNSCC patients (p < 0.05). Interestingly, the percentage of all three patterns is nearly identical in p16 positive and negative HNSCCs.

Conclusions: Using a plain histological H&E approach to categorize HNSCC as being immunologic “hot,” “cold,” or “excluded” can offer a forecast of patients' prognosis and may thus aid as a potential prognostic tool in routine pathology reports. This “hot-cold-excluded” scheme needs to be applied to more HNSCC cohorts and possibly to other cancer types to determine prognostic meaning, e.g., regarding OS or DFS. Furthermore, our cohort reflects epidemiological data in the national, European, and international context. It may, therefore, be of use for future HNSCC characterization.

Next Generation Imaging Techniques to Define Immune Topographies in Solid Tumors

In recent years, cancer immunotherapy experienced remarkable developments and it is nowadays considered a promising therapeutic frontier against many types of cancer, especially hematological malignancies. However, in most types of solid tumors, immunotherapy efficacy is modest, partly because of the limited accessibility of lymphocytes to the tumor core. This immune exclusion is mediated by a variety of physical, functional and dynamic barriers, which play a role in shaping the immune infiltrate in the tumor microenvironment. At present there is no unified and integrated understanding about the role played by different postulated models of immune exclusion in human solid tumors. Systematically mapping immune landscapes or "topographies" in cancers of different histology is of pivotal importance to characterize spatial and temporal distribution of lymphocytes in the tumor microenvironment, providing insights into mechanisms of immune exclusion. Spatially mapping immune cells also provides quantitative information, which could be informative in clinical settings, for example for the discovery of new biomarkers that could guide the design of patient-specific immunotherapies. In this review, we aim to summarize current standard and next generation approaches to define Cancer Immune Topographies based on published studies and propose future perspectives.

Addressing resistance to immune checkpoint inhibitor therapy: an urgent unmet need

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of various cancers by reversing the immunosuppressive mechanisms employed by tumors to restore anticancer immunity. Although ICIs have demonstrated substantial clinical efficacy, patient response can vary in depth and duration, and many do not respond at all or eventually develop resistance. ICI resistance mechanisms can be tumor-intrinsic, related to the tumor microenvironment or patient-specific factors. Multiple resistance mechanisms may be present within one tumor subtype, or heterogeneity exists among patients with the same tumor type. Consequently, designing effective combination treatment strategies is challenging. This review will discuss ICI resistance mechanisms, and summarize findings from key preclinical and clinical trials of ICIs, to identify potential treatment strategies or pathways to overcome ICI resistance.

QuPath: The global impact of an open source digital pathology system

QuPath, originally created at the Centre for Cancer Research & Cell Biology at Queen's University Belfast as part of a research programme in digital pathology (DP) funded by Invest Northern Ireland and Cancer Research UK, is arguably the most wildly used image analysis software program in the world. On the back of the explosion of DP and a need to comprehensively visualise and analyse whole slides images (WSI), QuPath was developed to address the many needs associated with tissue based image analysis; these were several fold and, predominantly, translational in nature: from the requirement to visualise images containing billions of pixels from files several GBs in size, to the demand for high-throughput reproducible analysis, which the paradigm of routine visual pathological assessment continues to struggle to deliver. Resultantly, large-scale biomarker quantification must increasingly be augmented with DP. Here we highlight the impact of the open source Quantitative Pathology & Bioimage Analysis DP system since its inception, by discussing the scope of scientific research in which QuPath has been cited, as the system of choice for researchers.

The right Timing, right combination, right sequence, and right delivery for Cancer immunotherapy

Cancer immunotherapy (CI) represented by immune checkpoint inhibitors (ICIs) presents a new paradigm for cancer treatment. However, the types of cancer that attain a therapeutic benefit from ICIs are limited, and the efficacy of these treatments does not meet expectations. To date, research on ICIs has mainly focused on identifying biomarkers and patient characteristics that can enhance the therapeutic effect on tumors. However, studies on combinational strategies for CI are being actively conducted to overcome the resistance to ICI treatment. Moreover, it has been confirmed that dramatic anticancer effects are achieved through "neoadjuvant" immunotherapy with ICIs in treatment-naïve cancer patients; consequently, it has become necessary to consider how to best apply cancer immunotherapies for patients, even with respect to their tumor stages. In this review, we sought to discuss the right timing of ICI treatment in consideration of the progression of cancer with a changing tumor-immune microenvironment. Furthermore, we investigated which types of combinational treatments and their corresponding sequences of administration could optimize the therapeutic effect of ICIs to expand the applicable target of ICIs and increase their therapeutic efficacy. Finally, we discussed several delivery pathways and methods that can maximize the effect of ICIs.

Hypoxia and the phenomenon of immune exclusion

Over the last few years, cancer immunotherapy experienced tremendous developments and it is nowadays considered a promising strategy against many types of cancer. However, the exclusion of lymphocytes from the tumor nest is a common phenomenon that limits the efficiency of immunotherapy in solid tumors. Despite several mechanisms proposed during the years to explain the immune excluded phenotype, at present, there is no integrated understanding about the role played by different models of immune exclusion in human cancers. Hypoxia is a hallmark of most solid tumors and, being a multifaceted and complex condition, shapes in a unique way the tumor microenvironment, affecting gene transcription and chromatin remodeling. In this review, we speculate about an upstream role for hypoxia as a common biological determinant of immune exclusion in solid tumors. We also discuss the current state of ex vivo and in vivo imaging of hypoxic determinants in relation to T cell distribution that could mechanisms of immune exclusion and discover functional-morphological tumor features that could support clinical monitoring.

Prognostic value of a modified Immunoscore in patients with stage IIII resectable colon cancer

Objective

The Immunoscore method has proved fruitful for predicting prognosis in patients with colon cancer. However, there is still room for improvement in this scoring method to achieve further advances in its clinical translation. This study aimed to develop and validate a modified Immunoscore (IS-mod) system for predicting overall survival (OS) in patients with stage I-III colon cancer.

Methods

The IS-mod was proposed by counting CD3+ and CD8+ immune cells in regions of the tumor core and its invasive margin by drawing two lines of interest. A discovery cohort (N=212) and validation cohort (N=103) from two centers were used to evaluate the prognostic value of the IS-mod.

Results

In the discovery cohort, 5-year survival rates were 88.6% in the high IS-mod group and 60.7% in the low IS-mod group. Multivariate analysis confirmed that the IS-mod was an independent prognostic factor for OS [adjusted hazard ratio (HR)=0.36, 95% confidence interval (95% CI): 0.20-0.63]. With less annotation and computation cost, the IS-mod achieved performance comparable to that of the Immunoscore-like (IS-like) system (C-index, 0.676 vs. 0.661, P=0.231). The 2-category IS-mod using 47.5% as the threshold had a better prognostic value than that using a fixed threshold of 25% (C-index, 0.653 vs. 0.573, P=0.004). Similar results were confirmed in the validation cohort.

Conclusions

Our method simplifies the annotation and accelerates the calculation of Immunoscore method, thus making it easier for clinical implementation. The IS-mod achieved comparable prognostic performance when compared to the IS-like system in both cohorts. Besides, we further found that even with a small reference set (N≥120), the IS-mod still demonstrated a stable prognostic value. This finding may inspire other institutions to develop a local reference set of an IS-mod system for more accurate risk stratification of colon cancer.

Spatial Distribution and Prognostic Implications of Tumor-Infiltrating FoxP3- CD4+ T Cells in Biliary Tract Cancer

PURPOSE

The clinical implications of tumor-infiltrating T cell subsets and their spatial distribution in biliary tract cancer (BTC) patients treated with gemcitabine plus cisplatin were investigated.

MATERIALS AND METHODS

A total of 52 BTC patients treated with palliative gemcitabine plus cisplatin were included. Multiplexed immunohistochemistry was performed on tumor tissues, and immune infiltrates were separately analyzed for the stroma, tumor margin, and tumor core.

RESULTS

The density of CD8+ T cells, FoxP3- CD4+ helper T cells, and FoxP3+ CD4+ regulatory T cells was significantly higher in the tumor margin than in the stroma and tumor core. The density of LAG3- or TIM3-expressing CD8+ T cell and FoxP3- CD4+ helper T cell infiltrates was also higher in the tumor margin. In extrahepatic cholangiocarcinoma, there was a higher density of T cell subsets in the tumor core and regulatory T cells in all regions. A high density of FoxP3- CD4+ helper T cells in the tumor margin showed a trend toward better progression-free survival (PFS) (p=0.092) and significantly better overall survival (OS) (p=0.012). In multivariate analyses, a high density of FoxP3- CD4+ helper T cells in the tumor margin was independently associated with favorable PFS and OS.

CONCLUSION

The tumor margin is the major site for the active infiltration of T cell subsets with higher levels of LAG3 and TIM3 expression in BTC. The density of tumor margin-infiltrating FoxP3- CD4+ helper T cells may be associated with clinical outcomes in BTC patients treated with gemcitabine plus cisplatin.

Spatial immunoprofiling of the intratumoral and peritumoral tissue of renal cell carcinoma patients

While the abundance and phenotype of tumor-infiltrating lymphocytes are linked with clinical survival, their spatial coordination and its clinical significance remain unclear. Here, we investigated the immune profile of intratumoral and peritumoral tissue of clear cell renal cell carcinoma patients (n = 64). We trained a cell classifier to detect lymphocytes from hematoxylin and eosin stained tissue slides. Using unsupervised classification, patients were further classified into immune cold, hot and excluded topographies reflecting lymphocyte abundance and localization. The immune topography distribution was further validated with The Cancer Genome Atlas digital image dataset. We showed association between PBRM1 mutation and immune cold topography, STAG1 mutation and immune hot topography and BAP1 mutation and immune excluded topography. With quantitative multiplex immunohistochemistry we analyzed the expression of 23 lymphocyte markers in intratumoral and peritumoral tissue regions. To study spatial interactions, we developed an algorithm quantifying the proportion of adjacent immune cell pairs and their immunophenotypes. Immune excluded tumors were associated with superior overall survival (HR 0.19, p = 0.02) and less extensive metastasis. Intratumoral T cells were characterized with pronounced expression of immunological activation and exhaustion markers such as granzyme B, PD1, and LAG3. Immune cell interaction occurred most frequently in the intratumoral region and correlated with CD45RO expression. Moreover, high proportion of peritumoral CD45RO+ T cells predicted poor overall survival. In summary, intratumoral and peritumoral tissue regions represent distinct immunospatial profiles and are associated with clinicopathologic characteristics.

Distribution pattern of tumor infiltrating lymphocytes and tumor microenvironment composition as prognostic indicators in anorectal malignant melanoma

Anorectal malignant melanoma (ARMM) is a rare disease with poor prognosis. Determining ARMM prognosis precisely is difficult due to the lack of proper assessment techniques. Immunotherapy has proven effective against cutaneous malignant melanoma and may show efficacy in ARMM. Herein, we assessed the immune profile of ARMM to identify possible prognostic biomarkers. Twenty-two ARMM formalin-fixed and paraffin-embedded samples were evaluated using an nCounter^® PanCancer Immune Profiling Panel. Validation was performed through immunohistochemical staining for CD3, CD8, Foxp3, CD68, CD163, and PD-L1. RNA analysis revealed significantly decreased scores for pathways involved in cell regulation and function, as well as chemokines, in recurrent patients compared to nonrecurrent patients. In cell-type profiling, the recurrent cases displayed significantly low tumor infiltrating lymphocyte (TIL) scores. Recurrence/death prediction models were defined using logistic regression and showed significantly lower scores in recurrent and deceased patients (all, P < 0.001) compared to those in nonrecurrent and surviving patients. The high total TIL and tumor-associated macrophage (TAM) groups had significantly better overall survival outcomes compared to the low total TIL and TAM groups (P = 0.007 and P = 0.035, respectively). In addition, the presence of CD3 + TILs in the invasion front was an independent favorable prognostic indicator (P = 0.003, hazard ratio = 0.21, 95% confidential interval, 0.01-0.41). Patients with inflamed or brisk-infiltration type tumors also had a significantly better overall survival than that of patients with immune-desert/excluded and absent/non-brisk type tumors (P = 0.03 and P = 0.0023, respectively). In conclusion, TILs have a strong prognostic value in ARMM, and the quantification of TILs and an analysis of the TIL phenotype and infiltration pattern during pathological diagnosis are essential to guide treatment strategies and accurate prognosis in ARMM.