Detailed resolution analysis reveals spatial T cell heterogeneity in the invasive margin of colorectal cancer liver metastases associated with improved survival

The Efficacy and Safety of Durvalumab and Tremelimumab with Concomitant Treatment for MSS/pMMR Metastatic Colorectal Cancer: A Single Arm Meta-Analysis

OBJECTIVES

To address the issue that most microsatellite-stable (MSS) and proficient mismatch repair (pMMR) metastatic colorectal cancer (mCRC) patients have minimal response to immunotherapy, this meta-analysis evaluated the efficacy and safety of durvalumab and tremelimumab with concomitant treatment in treating MSS/pMMR metastatic colorectal cancer.

METHODS

All included trials were prospective studies with a median patient age of 63 years, of which 94.2% were MSS/pMMR mCRC patients, with a male to female ratio of 1.5:1. Based on durvalumab and tremelimumab treatment, one study performed surgical resection on resectable cases, while the other four studies performed radiotherapy or chemotherapy on unresectable cases. Analyses include objective response rate (ORR).etc. for drug activity, overall survival (OS) and progression-free survival (PFS) for therapeutic efficacy, and adverse events (AEs) for safety. The risk of bias was assessed by sensitivity analysis.

RESULTS

5 studies involving 228 patients were included in this meta-analysis. The pooled estimates showed a median OS of 9.26 months, median PFS of 2.53 months, partial response (PR) of 13.6%, stable disease (SD) of 32.8%, ORR of 12.5% and disease control rate (DCR) of 65.4%. AEs were generally low, with pruritus (27.5%), diarrhea (28.8%), and fatigue (53.9%) being the most common, while other AEs occurred at less frequencies.

CONCLUSIONS

Durvalumab and tremelimumab with concomitant treatment for MSS/pMMR mCRC patients is relatively effective and safe, which is helpful in addressing the problem of mCRC with MSS/pMMR that has minimal response to immunotherapy.

Crucial immunological roles of the invasion front in innate and adaptive immunity in cervical cancer

BACKGROUND

The immunostimulatory actions of innate and adaptive immune responses play a crucial role in the cancer-immunity cycle. Although cervical cancer (CC) exhibits a high recurrence rate, the relation with lymphocytes in the tumor tissue have not been analyzed.

METHODS

We analyzed NKT, NK, and T cells, not only in peripheral blood (PB), but also tumor tissue through histological analysis from 23 patients with CC collected before treatment. A correlation of them between PB and the tumor tissue were assessed.

RESULTS

We detected functional NKT and NKG2Dhi NK cells and effector CD4+ Tregs in PB. In the tumor, we detected the infiltration of LAG-3+ TIM-3+ CD4+ and CD8+ T cells rather than NK cells particularly in the invasion front (IF) by fluorescent multiplex immunohistochemistry. The heatmap and correlation analysis revealed that LAG-3+ TIM-3+ CD8+ T cells are highly associated with CD69+ CD103- exhausted CD8+ T cells. We identified the statistical relationship between CD4+Tregs in PB and the number of LAG-3+ TIM-3+ CD4+ T cells in the IF, which may be related to recurrence in patients with CC.

CONCLUSIONS

LAG-3+ TIM-3+ T cells located in the IF may play a key role in regulation of the tumor immune microenvironment.

Computer-aided diagnosis of liver cancer with improved SegNet and deep stacking ensemble model

Liver cancer is a leading cause of cancer-related deaths, often diagnosed at advanced stages due to reliance on traditional imaging methods. Existing computer-aided diagnosis systems struggle with noise, anatomical complexity, and ineffective feature integration, leading to inaccuracies in lesion segmentation and classification. By effectively addressing these challenges, the model aims to enhance early detection and assist clinicians in making informed decisions. Ultimately, this research seeks to contribute to more efficient and accurate liver cancer diagnosis. This paper presents a novel model for liver cancer classification, called SegNet-based Liver Cancer Classification via SqueezeNet (SgN-LCC-SqN). The model effectively executes liver cancer segmentation and classification through four key steps: preprocessing, segmentation, feature extraction, and classification. During preprocessing, Quadratic Mean Estimated Wiener Filtering (QMEWF) is utilized to minimize image noise. Segmentation divides the image into segments using Enhanced Feature Pyramid SegNet (EFP-SgN), which is essential for precise diagnosis. Feature extraction encompasses color features, Local Directional Pattern Variance, and Correlation Filtering-Local Gradient Increasing Pattern (CF-LGIP) features. The extracted features are then processed through an ensemble model, Deep Convolutional, Recurrent, Long Short Term Memory with SqueezeNet (DCR-LSTM-SqN), which includes Deep Convolutional Neural Network (DCNN), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Modified Loss Function in SqueezeNet (MLF-SqN) classifiers, sequentially analyzing the feature sets through DCNN, RNN, and LSTM before classification by MLF-SqN. The performance of the suggested DCR-LSTM-SqN model is evaluated over conventional methods for positive, negative and other metrics. The DCR-LSTM-SqN model consistently demonstrates superior accuracy, ranging from 0.947 to 0.984, across all training data percentages. Thus, the proposed model effectively segments liver lesions and classifies cancerous areas, demonstrating its potential as a valuable resource for clinicians to enhance the efficiency and accuracy of liver cancer diagnosis.

Deciphering the tumor immune microenvironment from a multidimensional omics perspective: insight into next-generation CAR-T cell immunotherapy and beyond

Tumor immune microenvironment (TIME) consists of intra-tumor immunological components and plays a significant role in tumor initiation, progression, metastasis, and response to therapy. Chimeric antigen receptor (CAR)-T cell immunotherapy has revolutionized the cancer treatment paradigm. Although CAR-T cell immunotherapy has emerged as a successful treatment for hematologic malignancies, it remains a conundrum for solid tumors. The heterogeneity of TIME is responsible for poor outcomes in CAR-T cell immunotherapy against solid tumors. The advancement of highly sophisticated technology enhances our exploration in TIME from a multi-omics perspective. In the era of machine learning, multi-omics studies could reveal the characteristics of TIME and its immune resistance mechanism. Therefore, the clinical efficacy of CAR-T cell immunotherapy in solid tumors could be further improved with strategies that target unfavorable conditions in TIME. Herein, this review seeks to investigate the factors influencing TIME formation and propose strategies for improving the effectiveness of CAR-T cell immunotherapy through a multi-omics perspective, with the ultimate goal of developing personalized therapeutic approaches.

Spatial Distribution and Densities of CD103+ and FoxP3+ Tumor Infiltrating Lymphocytes by Digital Analysis for Outcome Prediction in Breast Cancer

BACKGROUND

The evaluation of tumor-infiltrating lymphocytes (TILs) for breast cancer prognosis is now established. However, the clinical value for their spatial distributions of specific immune subsets, namely CD103+ tissue-resident memory T cells FoxP3+ regulatory T ells, have not been thoroughly examined.

METHOD

Representative whole sections of breast cancers were subjected to CD103 and FoxP3 double staining. Their density, ratio, and spatial features were analyzed in tumor area and tumor-stromal interface. Their associations with clinicopathological parameters and patient's prognosis were analyzed.

RESULTS

CD103 TILs were closer to tumor nests than FoxP3 TILs in the tumor-stromal interface. Their densities were associated with high-grade disease, TNBC, and stromal TILs. High stromal FoxP3 (sFoxP3) TILs and close proximity of sCD103 TILs to tumor were independently associated with better survival at multivariate analysis. Subgroup analysis showed the high FoxP3 TILs density associated better survival was seen in HER2-OE and TNBC subtypes while the proximity of CD103 TILs to tumor nests associated better survival was seen in luminal cancers.

CONCLUSION

The prognostic impact of CD103 and FoxP3 TILs in breast cancer depends on their spatial localization. High sFoxP3 TIL density and the lower distance of CD103 TILs from the tumor nests had independent favorable prognostic values.

Exploratory study of macrophage polarization and spatial distribution in colorectal cancer liver metastasis: a pilot study

Background

The liver is the most typical site of metastatic disease for patients with colorectal cancer (CRC), and up to half the patients with CRC will develop colorectal liver metastasis (CLM). Studying the tumor microenvironment, particularly macrophages and their spatial distribution, can give us critical insight into treatment.

Methods

Ten CLMs (five treatment-naïve and five post-neoadjuvant chemotherapy) were stained with multiplex immunofluorescence panels against cytokeratins, CD68, Arg1, CD206, CD86, CD163, PD-L1, and MRP8-14. Densities of cell phenotypes and their spatial distribution in the tumor center and the normal liver-tumor interface were correlated with clinicopathological variables.

Results

M2 macrophages were the predominant subtype in both the tumor center and the periphery, with a relatively higher density at the periphery. The larger tumors, more than 3.9 cm, were associated with higher densities of total CD68+ macrophages and CD68+CD163+ CD206neg and CD68+CD206+ CD163neg M2 macrophage subtypes. Total macrophages in the tumor periphery demonstrated significantly greater proximity to malignant cells than did those in the tumor center (p=0.0371). The presence of higher than median CD68+MRP8-14+CD86neg M1 macrophages in the tumor center was associated with poor overall survival (median 2.34 years) compared to cases with lower than median M1 macrophages at the tumor center (median 6.41 years) in univariate analysis.

Conclusion

The dominant polarization of the M2 macrophage subtype could drive new therapeutic approaches in CLM patients.

Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

First-line durvalumab and tremelimumab with chemotherapy in RAS-mutated metastatic colorectal cancer: a phase 1b/2 trial

Although patients with microsatellite instable metastatic colorectal cancer (CRC) benefit from immune checkpoint blockade, chemotherapy with targeted therapies remains the only therapeutic option for microsatellite stable (MSS) tumors. The single-arm, phase 1b/2 MEDITREME trial evaluated the safety and efficacy of durvalumab plus tremelimumab combined with mFOLFOX6 chemotherapy in first line, in 57 patients with RAS-mutant unresectable metastatic CRC. Safety was the primary objective of phase Ib; no safety issue was observed. The phase 2 primary objective of efficacy in terms of 3-month progression-free survival (PFS) in patients with MSS tumors was met, with 3-month PFS of 90.7% (95% confidence interval (CI): 79.2-96%). For secondary objectives, response rate was 64.5%; median PFS was 8.2 months (95% CI: 5.9-8.6); and overall survival was not reached in patients with MSS tumors. We observed higher tumor mutational burden and lower genomic instability in responders. Integrated transcriptomic analysis underlined that high immune signature and low epithelial-mesenchymal transition were associated with better outcome. Immunomonitoring showed induction of neoantigen and NY-ESO1 and TERT blood tumor-specific T cell response associated with better PFS. The combination of durvalumab-tremelimumab with mFOLFOX6 was tolerable with promising clinical activity in MSS mCRC. Clinicaltrials.gov identifier: NCT03202758 .

Investigating the spatial interaction of immune cells in colon cancer

The intricate network of interactions between cells and molecules in the tumor microenvironment creates a heterogeneous ecosystem. The proximity of the cells and molecules to their activators and inhibitors is essential in the progression of tumors. Here, we develop a system of partial differential equations coupled with linear elasticity to investigate the effects of spatial interactions on the tumor microenvironment. We observe interesting cell and cytokine distribution patterns, which are heavily affected by macrophages. We also see that cytotoxic T cells get recruited and suppressed at the site of macrophages. Moreover, we observe that anti-tumor macrophages reorganize the patterns in favor of a more spatially restricted cancer and necrotic core. Furthermore, the adjoint-based sensitivity analysis indicates that the most sensitive model's parameters are directly related to macrophages. The results emphasize the widely acknowledged effect of macrophages in controlling cancer cells population and spatially arranging cells in the tumor microenvironment.

Ex vivo explant model of adenoma and colorectal cancer to explore mechanisms of action and patient response to cancer prevention therapies

Colorectal cancer (CRC) is the second leading cause of cancer death in the UK. Novel therapeutic prevention strategies to inhibit the development and progression of CRC would be invaluable. Potential contenders include low toxicity agents such as dietary-derived agents or repurposed drugs. However, in vitro and in vivo models used in drug development often do not take into account the heterogeneity of tumours or the tumour microenvironment. This limits translation to a clinical setting. Our objectives were to develop an ex vivo method utilizing CRC and adenoma patient-derived explants (PDEs) which facilitates screening of drugs, assessment of toxicity, and efficacy. Our aims were to use a multiplexed immunofluorescence approach to demonstrate the viability of colorectal tissue PDEs, and the ability to assess immune cell composition and interactions. Using clinically achievable concentrations of curcumin, we show a correlation between curcumin-induced tumour and stromal apoptosis (P < .001) in adenomas and cancers; higher stromal content is associated with poorer outcomes. B cell (CD20+ve) and T cell (CD3+ve) density of immune cells within tumour regions in control samples correlated with curcumin-induced tumour apoptosis (P < .001 and P < .05, respectively), suggesting curcumin-induced apoptosis is potentially predicted by baseline measures of immune cells. A decrease in distance between T cells (CD3+ve) and cytokeratin+ve cells was observed, indicating movement of T cells (CD3+ve) towards the tumour margin (P < .001); this change is consistent with an immune environment associated with improved outcomes. Concurrently, an increase in distance between T cells (CD3+ve) and B cells (CD20+ve) was detected following curcumin treatment (P < .001), which may result in a less immunosuppressive tumour milieu. The colorectal tissue PDE model offers significant potential for simultaneously assessing multiple biomarkers in response to drug exposure allowing a greater understanding of mechanisms of action and efficacy in relevant target tissues, that maintain both their structural integrity and immune cell compartments.

Multi-perspective comparison of the immune microenvironment of primary colorectal cancer and liver metastases

BACKGROUND

Liver metastases are a major contributor to the poor immunotherapy response in colorectal cancer patients. However, the distinctions in the immune microenvironment between primary tumors and liver metastases are poorly characterized. The goal of this study was to compare the expression profile of multiple immune cells to further analyze the similarities and differences between the microenvironments of liver metastases and the primary tumor.

METHODS

Tissues from 17 patients with colorectal cancer who underwent resection of primary and liver metastases was analyzed using multispectral immunofluorescence. The expression of multiple immune cells (CD8, Foxp3, CD68, CD163, CD20, CD11c, CD66b, CD56, PD-L1, INF-γ, Ki67 and VEGFR-2) in the tumor center (TC), tumor invasive front (< 150 µm from the tumor center, TF) and peritumoral region (≥ 150 µm from the tumor center, PT) was evaluated via comparison. The expression of CD68 and CD163 in different regions was further analyzed based on the cell colocalization method. In addition, different immune phenotypes were studied and compared according to the degree of CD8 infiltration.

RESULTS

The expression trends of 12 markers in the TF and TC regions were basically the same in the primary tumor and liver metastasis lesions. However, in comparison of the TF and PT regions, the expression trends were not identical between primary and liver metastases, especially CD163, which was more highly expressed in the PT region relative to the TF region. In the contrast of different space distribution, the expression of CD163 was higher in liver metastases than in the primary foci. Further analysis of CD68 and CD163 via colocalization revealed that the distribution of macrophages in liver metastases was significantly different from that in the primary foci, with CD68^-CD163⁺ macrophages predominating in liver metastases. In addition, among the three immunophenotypes, CD163 expression was highest in the immune rejection phenotype.

CONCLUSIONS

The immune cells found in the primary tumors of colorectal cancer differed from those in liver metastases in terms of their spatial distribution. More immunosuppressive cells were present in the liver metastases, with the most pronounced differential distribution found for macrophages. CD68^-CD163⁺ macrophages may be associated with intrahepatic immunosuppression and weak immunotherapeutic effects.

Prognostic significance of spatial and density analysis of T lymphocytes in colorectal cancer

BACKGROUND

Although high T cell density is a strong favourable prognostic factor in colorectal cancer, the significance of the spatial distribution of T cells is incompletely understood. We aimed to evaluate the prognostic significance of tumour cell-T cell co-localisation and T cell densities.

METHODS

We analysed CD3 and CD8 immunohistochemistry in a study cohort of 983 colorectal cancer patients and a validation cohort (N = 246). Individual immune and tumour cells were identified to calculate T cell densities (to derive T cell density score) and G-cross function values, estimating the likelihood of tumour cells being co-located with T cells within 20 µm radius (to derive T cell proximity score).

RESULTS

High T cell proximity score associated with longer cancer-specific survival in both the study cohort [adjusted HR for high (vs. low) 0.33, 95% CI 0.20-0.52, P_trend < 0.0001] and the validation cohort [adjusted HR for high (vs. low) 0.15, 95% CI 0.05-0.45, P_trend < 0.0001] and its prognostic value was independent of T cell density score.

CONCLUSIONS

The spatial point pattern analysis of tumour cell-T cell co-localisation could provide detailed information on colorectal cancer prognosis, supporting the value of spatial measurement of T cell infiltrates as a novel, robust tumour-immune biomarker.

Spatial Immunology in Liver Metastases from Colorectal Carcinoma according to the Histologic Growth Pattern

Simple Summary

In the era of immunotherapy, the tumor microenvironment (TME) has attracted special interest. However, colorectal liver metastases (CRC-LM) present histological peculiarities that could affect the interaction of immune and tumor cells such as fibrotic encapsulation and dense intratumoral stroma. We explored the spatial distribution of lymphocytic infiltrates in CRC-LM in the context of the histologic growth patterns using multispectral digital pathology providing data on three different scenarios, tumor periphery, invasive margin, and central tumoral areas. Our results illustrate a similar poor cell density of CD8⁺ cells between different metastases subtypes in intratumoral regions. However, in encapsulated metastases, cytotoxic cells reach the tumor cells while remaining retained in stromal areas in non-encapsulating metastases. Some aspects are still unresolved, such as understanding the reason why most lymphocytes are largely retained in the capsule.

Abstract

Colorectal cancer liver metastases (CRC-LM) present differential histologic growth patterns (HGP) that determine the interaction between immune and tumor cells. We explored the spatial distribution of lymphocytic infiltrates in CRC-LM in the context of the HGP using multispectral digital pathology. We did not find statistically significant differences of immune cell densities in the central regions of desmoplastic (_dHGP) and non-desmoplastic (_ndHGP) metastases. The spatial evaluation reported that _dHGP-metastases displayed higher infiltration by CD8⁺ and CD20⁺ cells in peripheral regions as well as CD4⁺ and CD45RO⁺ cells in _ndHGP-metastases. However, the reactive stroma regions at the invasive margin (IM) of _ndHGP-metastases displayed higher density of CD4⁺, CD20⁺, and CD45RO⁺ cells. The antitumor status of the TIL infiltrates measured as CD8/CD4 reported higher values in the IM of encapsulated metastases up to 400 μm towards the tumor center (p < 0.05). Remarkably, the IM of _dHGP-metastases was characterized by higher infiltration of CD8⁺ cells in the epithelial compartment parameter assessed with the ratio CD8^epithelial/CD8^stromal, suggesting anti-tumoral activity in the encapsulating lesions. Taking together, the amount of CD8⁺ cells is comparable in the IM of both HGP metastases types. However, in _dHGP-metastases some cytotoxic cells reach the tumor nests while remaining retained in the stromal areas in _ndHGP-metastases.

Debating Pros and Cons of Total Neoadjuvant Therapy in Rectal Cancer

Simple Summary

Rectal cancers represent one third of all colorectal tumours. Patients diagnosed with localised colon cancer undergo surgery upfront, likely followed by adjuvant chemotherapy. Those diagnosed with localised rectal cancer, however, frequently benefit from neoadjuvant treatments with either radiotherapy or chemoradiotherapy before undergoing surgery. On the other hand, the benefit of adjuvant chemotherapy in this setting is more controversial. The main challenges in treating patients affected by rectal cancer encompass: decreasing the risks of local relapse and distant metastases, preserving the sphincter and minimising treatment-associated functional sequelae, and improving overall survival. Some of these fuelled the concept of total neoadjuvant therapy, namely giving all available treatments including radiotherapy and systemic chemotherapy before surgery. Here, we critically review the pros and cons of such a treatment strategy, but also discuss the biological rational to support neoadjuvant treatment intensification.

Abstract

Recently, two large, randomised phase III clinical trials of total neoadjuvant therapy (TNT) in locally advanced rectal cancer were published (RAPIDO and PRODIGE 23). These two trials compared short-course radiotherapy (SCRT) followed by chemotherapy with standard chemoradiotherapy (CRT) and chemotherapy followed by CRT with standard CRT, respectively. They showed improvement in some of the outcomes such as distant recurrence and pathological complete response (pCR). No improvement, however, was observed in local disease control or the de-escalation of surgical procedures. Although it seems lawful to integrate TNT within the treatment algorithm of localised stage II and III rectal cancer, many questions remain unanswered, including which are the optimal criteria to identify patients who are most likely to benefit from this intensive treatment. Instead of providing a sterile summary of trial results, we put these in perspective in a pros and cons manner. Moreover, we discuss some biological aspects of rectal cancer, which may provide some insights into the current decision-making process, and represent the basis for the future development of alternative, more effective treatment strategies.

Machine-Learning-Based Evaluation of Intratumoral Heterogeneity and Tumor-Stroma Interface for Clinical Guidance

Assessment of intratumoral heterogeneity and tumor-host interaction within the tumor microenvironment is becoming increasingly important for innovative cancer therapy decisions because of the unique information it can generate about the state of the disease. However, its assessment and quantification are limited by ambiguous definitions of the tumor-host interface and by human cognitive capacity in current pathology practice. Advances in machine learning and artificial intelligence have opened the field of digital pathology to novel tissue image analytics and feature extraction for generation of high-capacity computational disease management models. A particular benefit is expected from machine-learning applications that can perform extraction and quantification of subvisual features of both intratumoral heterogeneity and tumor microenvironment aspects. These methods generate information about cancer cell subpopulation heterogeneity, potential tumor-host interactions, and tissue microarchitecture, derived from morphologically resolved content using both explicit and implicit features. Several studies have achieved promising diagnostic, prognostic, and predictive artificial intelligence models that often outperform current clinical and pathology criteria. However, further effort is needed for clinical adoption of such methods through development of standardizable high-capacity workflows and proper validation studies.

Systemic Inflammation Associates With a Myeloid Inflamed Tumor Microenvironment in Primary Resected Colon Cancer-May Cold Tumors Simply Be Too Hot?

Systemic inflammation measured by the acute-phase protein CRP associates with poor outcome across cancer types. In contrast, local tumor-associated inflammation, primarily evaluated by T-lymphocytes, correlates with favorable prognosis. Yet, little is known whether these two responses are related or opposing processes and why elevated CRP in relation to cancer is detrimental for clinical outcome. As proof of concept, we developed a platform combining multiplexed IHC and digital imaging, enabling a virtual readout of both lymphoid and myeloid immune markers and their spatial patterns in the primary tumors of resected stage II and III colon cancer (CC) patients with and without accompanying systemic inflammation. Twenty-one patients with elevated CRP (>30 mg/l) and 15 patients with low CRP (<10 mg/l) were included in the analyses. Whole slides from the primary tumors were stained for markers of adaptive (CD8+, CD4+, foxp3 regulatory T cells, CD20+ B cells) and innate (CD68+ macrophages, CD66b+ neutrophils) immunity and the immune checkpoint molecule PD-L1. Associations between individual immune markers, preoperative CRP values, mismatch repair status (MMR), and risk of recurrence or death were assessed. Unsupervised hierarchical clustering was used to explore whether distinct immune phenotypes were present. Tumors from systemically inflamed patients (CRP >30 mg/l) displayed significantly more myeloid features in terms of higher densities of CD66b+neutrophils (p = 0.001) and CD68+macrophages (p = 0.04) and less lymphoid features (lower CD8 T cell, p = 0.03, and foxp3 regulatory T cell densities, p = 0.03) regardless of MMR status. Additionally, systemically inflamed patients harbored lower mean distances between neutrophils and tumor cells within the TME. Intriguingly, microsatellite instable (MSI) tumor status correlated with systemic inflammation. However, using a combinatorial approach, we found that regardless of an adaptive composite score (compounded CD4+ and CD8+ T cells), a high innate score (CD66b+ neutrophils and CD68+ macrophages) associated significantly with elevated CRP. In conclusion, tumor-associated systemic inflammation correlated with a myeloid-dominated TME in a small cohort of resectable CC patients. Our data highlight the importance of a comprehensive immune classification of tumors including players of innate immunity and support a role for CRP as an informative biomarker of the immune response taking place at the tumor site.

Histological tumor response to neoadjuvant chemotherapy correlates to Immunoscore in colorectal cancer liver metastases patients

BACKGROUND

This study investigated the correlation between tumor regression grade (TRG) score and Immunoscore, and prognostic values of TRG score and a risk score in colorectal cancer liver metastases (CRLMs) patients after neoadjuvant chemotherapy.

METHODS

Patients undergoing neoadjuvant chemotherapy from 2014 to 2019 were selected. TRG score and Immunoscore were evaluated in 200 CRLMs. A risk score combining TRG score, Immunoscore, and clinical risk score (CRS) was defined and divided patients into the low-, medium-, and high-risk groups. Differences in relapse-free survival (RFS) and overall survival (OS) between groups were determined.

RESULTS

The densities of CD3⁺ and CD8⁺ immune cells were higher in TRG1-3 group than in TRG4-5 group, and the ratio of high Immunoscores was higher in TRG1-3 group than in TRG4-5 group (60.0% vs. 15.8%, p < 0.001). Patients in TRG1-3 group had significantly longer RFS and OS than those in TRG4-5 group. The low-risk group shows a significantly higher 2-year RFS and 5-year OS rate than the medium- and high-risk group (RFS: 59.9%, 36.2%, and 6.4%, p < 0.001; OS: 82.0%, 41.0%, and 16.9%, p < 0.001).

CONCLUSION

TRG score may be proposed to evaluate the prognosis of neoadjuvant chemotherapy and may be used for predicting the postoperative survival of CRLMs.

Circulating PD-L1 is associated with T cell infiltration and predicts prognosis in patients with CRLM following hepatic resection

BACKGROUND

Exosomal PD-L1 (exoPD-L1) could induce immunosuppression functionally, thus impairing patients' survival in melanoma, NSCLC, and gastric cancer. However, no evidence demonstrates the feasibility of circulating exoPD-L1 and soluble PD-L1 (sPD-L1) as biomarkers for prognosis and early recurrence in colorectal liver metastasis (CRLM) patients following hepatectomy or their association with T cell infiltration at liver metastases.

METHODS

In cohort 1, exoPD-L1 and sPD-L1 were preoperatively tested using ELISA. CD3, CD8, granzyme B (GB) and PD1 expressed at liver metastases were evaluated using immunohistochemistry. In cohort 2, exoPD-L1 and sPD-L1 were detected at baseline, before hepatectomy, after hepatectomy, and after disease progression.

RESULTS

In cohort 1, higher preoperative exoPD-L1 or sPD-L1 significantly impaired RFS (exoPD-L1, P = 0.0043; sPD-L1, P = 0.0041) and OS (exoPD-L1, P = 0.0034; sPD-L1, P = 0.0061). Furthermore, preoperative exoPD-L1 was negatively correlated with CD3 + T-lymphocytes infiltrated at tumor center (CT), and GB and PD1 were expressed at tumor invasive margin (IM). Preoperative sPD-L1 was negatively correlated with CD3 + and CD8 + T-lymphocytes' infiltration at IM and CT, GB and PD1 expression at IM. In cohort 2, exoPD-L1 and sPD-L1 levels decreased following hepatectomy but increased when tumor progressed. Moreover, higher postoperative exoPD-L1 and sPD-L1 or a small reduction in exoPD-L1 and sPD-L1 levels after hepatectomy suggested higher early recurrence rate.

CONCLUSIONS

Both preoperative exoPD-L1 and sPD-L1 had promising prognostic values and were associated with T cell infiltration at liver metastases in CRLM patients following hepatectomy. Dynamically tracking exoPD-L1 and sPD-L1 levels could monitor disease status and detect early recurrence.

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.

Spatial architecture of the immune microenvironment orchestrates tumor immunity and therapeutic response

Tumors are not only aggregates of malignant cells but also well-organized complex ecosystems. The immunological components within tumors, termed the tumor immune microenvironment (TIME), have long been shown to be strongly related to tumor development, recurrence and metastasis. However, conventional studies that underestimate the potential value of the spatial architecture of the TIME are unable to completely elucidate its complexity. As innovative high-flux and high-dimensional technologies emerge, researchers can more feasibly and accurately detect and depict the spatial architecture of the TIME. These findings have improved our understanding of the complexity and role of the TIME in tumor biology. In this review, we first epitomized some representative emerging technologies in the study of the spatial architecture of the TIME and categorized the description methods used to characterize these structures. Then, we determined the functions of the spatial architecture of the TIME in tumor biology and the effects of the gradient of extracellular nonspecific chemicals (ENSCs) on the TIME. We also discussed the potential clinical value of our understanding of the spatial architectures of the TIME, as well as current limitations and future prospects in this novel field. This review will bring spatial architectures of the TIME, an emerging dimension of tumor ecosystem research, to the attention of more researchers and promote its application in tumor research and clinical practice.

Neoadjuvant PROSTVAC prior to radical prostatectomy enhances T-cell infiltration into the tumor immune microenvironment in men with prostate cancer

Background

Clinical trials have shown the ability of therapeutic vaccines to generate immune responses to tumor-associated antigens (TAAs). What is relatively less known is if this translates into immune-cell (IC) infiltration into the tumor microenvironment. This study examined whether neoadjuvant prostate-specific antigen (PSA)-targeted vaccination with PROSTVAC could induce T-cell immunity, particularly at the tumor site.

Methods

An open-label, phase II study of neoadjuvant PROSTVAC vaccine enrolled 27 patients with localized prostate cancer awaiting radical prostatectomy (RP). We evaluated increases in CD4 and CD8 T-cell infiltrates (RP tissue vs baseline biopsies) using a six-color multiplex immunofluorescence Opal method. Antigen-specific responses were assessed by intracellular cytokine staining after in vitro stimulation of peripheral blood mononuclear cells with overlapping 15-mer peptide pools encoding the TAAs PSA, brachyury and MUC-1.

Results

Of 27 vaccinated patients, 26 had matched prevaccination (biopsy) and postvaccination (RP) prostate samples available for non-compartmentalized analysis (NCA) and compartmentalized analysis (CA). Tumor CD4 T-cell infiltrates were significantly increased in postvaccination RP specimens compared with baseline biopsies by NCA (median 176/mm² vs 152/mm²; IQR 136–317/mm² vs 69–284/mm²; p=0.0249; median ratio 1.20; IQR 0.64–2.25). By CA, an increase in both CD4 T-cell infiltrates at the tumor infiltrative margin (median 198/mm² vs 151/mm²; IQR 123–500/mm² vs 85–256/mm²; p=0.042; median ratio 1.44; IQR 0.59–4.17) and in CD8 T-cell infiltrates at the tumor core (median 140/mm² vs 105/mm²; IQR 91–175/mm² vs 83–163/mm²; p=0.036; median ratio 1.25; IQR 0.88–2.09) were noted in postvaccination RP specimens compared with baseline biopsies. A total of 13/25 patients (52%) developed peripheral T-cell responses to any of the three tested TAAs (non-neoantigens); five of these had responses to more than one antigen of the three evaluated.

Conclusion

Neoadjuvant PROSTVAC can induce both tumor immune response and peripheral immune response.

Trial registration number

NCT02153918.

Emerging Trends for Radio-Immunotherapy in Rectal Cancer

Rectal cancer is a heterogeneous disease at the genetic and molecular levels, both aspects having major repercussions on the tumor immune contexture. Whilst microsatellite status and tumor mutational load have been associated with response to immunotherapy, presence of tumor-infiltrating lymphocytes is one of the most powerful prognostic and predictive biomarkers. Yet, the majority of rectal cancers are characterized by microsatellite stability, low tumor mutational burden and poor T cell infiltration. Consequently, these tumors do not respond to immunotherapy and treatment largely relies on radiotherapy alone or in combination with chemotherapy followed by radical surgery. Importantly, pre-clinical and clinical studies suggest that radiotherapy can induce a complete reprograming of the tumor microenvironment, potentially sensitizing it for immune checkpoint inhibition. Nonetheless, growing evidence suggest that this synergistic effect strongly depends on radiotherapy dosing, fractionation and timing. Despite ongoing work, information about the radiotherapy regimen required to yield optimal clinical outcome when combined to checkpoint blockade remains largely unavailable. In this review, we describe the molecular and immune heterogeneity of rectal cancer and outline its prognostic value. In addition, we discuss the effect of radiotherapy on the tumor microenvironment, focusing on the mechanisms and benefits of its combination with immune checkpoint inhibitors.

Distribution of tumor-infiltrating-T-lymphocytes and possible tumor-escape mechanisms avoiding immune cell attack in locally advanced adenocarcinomas of the esophagus

Introduction

The inflammatory microenvironment has emerged as one of the focuses of cancer research. Little is known about the immune environment in esophageal adenocarcinoma (EAC) and possible tumor-escape mechanisms to avoid immune cell attack.

Patients and methods

We measured T cell inflammation (CD3, CD8) in the microenvironment using a standardized software-based evaluation algorithm considering different predefined tumor areas as well as expression of MHC class 1 and PD-L1 on 75 analyzable primarily resected and locally advanced (≥ pT2) EACs. We correlated these findings statistically with clinical data.

Results

Patients with high amounts of T cell infiltration in their tumor center showed a significant survival benefit of 41.4 months compared to 16.3 months in T cell poor tumors (p = 0.025), although CD3 fails to serve as an independent prognostic marker in multivariate analysis. For the invasion zone, a correlation between number of T-cells and overall survival was not detectable. Loss of MHC1 protein expression on tumor cells was seen in 32% and PD-L1 expression using the combined positive score (CPS) in 21.2%. Most likely due to small numbers of cases, both markers are not prognostically relevant, even though PD-L1 expression correlates with advanced tumor stages.

Discussion

Our analyses reveal an outstanding, though not statistically independent, prognostic relevance of T-cell-rich inflammation in our group of EACs, in particular driven by the tumor center. For the first time, we describe that the inner part of the invasion zone in EACs shows significantly fewer T-cells than other tumor segments and is prognostically irrelevant. We also demonstrate that the loss of antigen presenting ability via MHC1 downregulation by the carcinoma cells is a common escape mechanism in EACs. Future work will need to show whether tumors with MHC class 1 loss respond less well to immunotherapy.

The Tumor Microenvironment in Liver Metastases from Colorectal Carcinoma in the Context of the Histologic Growth Patterns

Colorectal carcinoma (CRC) is the third most common cancer. Likewise, it is a disease that has a long survival if it is prematurely detected. However, more than 50% of patients will develop metastases, mainly in the liver (LM-CRC), throughout the evolution of their disease, which accounts for most CRC-related deaths. Treatment it is certainly a controversial issue, since it has not been shown to increase overall survival in the adjuvant setting, although it does improve disease free survival (DFS). Moreover, current chemotherapy combinations are administered based on data extrapolated from primary tumors (PT), not considering that LM-CRC present a very particular tumor microenvironment that can radically condition the effectiveness of treatments designed for a PT. The liver has a particular histology and microenvironment that can determine tumor growth and response to treatments: double blood supply, vascularization through fenestrated sinusoids and the presence of different mesenchymal cell types, among other particularities. Likewise, the liver presents a peculiar immune response against tumor cells, a fact that correlates with the poor response to immunotherapy. All these aspects will be addressed in this review, putting them in the context of the histological growth patterns of LM-CRC, a particular pathologic feature with both prognostic and predictive repercussions.

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.

Clinical Importance of CD200 Expression in Colorectal Liver Metastasis

BACKGROUND

Approximately 30% of patients diagnosed with colorectal cancer (CRC) develop liver metastases. We evaluated the role of CD200, a potent immunosuppressive molecule, in colorectal liver metastases (CRLM).

METHODS

We examined 110 patients who underwent curative liver resection for CRLM at our institution between 2000 and 2016. Based on the results of immunohistochemical analysis, the patients were divided into high-CD200 (n = 47) and low-CD200 (n = 63) expression groups. The relationships between CD200 expression and various clinicopathological outcomes were investigated.

RESULTS

The overall survival (OS) of patients in the high-CD200 group was significantly worse than that in the low-CD200 group (p = 0.009). Multivariate analysis showed that the independent prognostic factors in CRLM were maximum tumor size > 30 mm (p = 0.002), preoperative carcinoembryonic antigen level > 20 ng/mL (p < 0.001), primary CRC N2-3 (p = 0.049), and high-CD200 expression (p = 0.004). Furthermore, CD4+, CD8+, and CD45RO+ tumor-infiltrating lymphocytes in CRLM were significantly higher in the low-CD200 group than in the high-CD200 group (p = 0.005, p = 0.001, and p < 0.001, respectively). In addition, patients who had received preoperative chemotherapy had higher CD200 expression than those who had not received preoperative chemotherapy, and OS was significantly worse in patients in the high-CD200 group who had received preoperative chemotherapy.

CONCLUSIONS

CD200 expression was an independent prognostic factor in CRLM. CD200 may play a critical role in tumor immunity in CRLM, and can therefore be used as a potential therapeutic target in CRLM.

Histopathological growth patterns correlate with the immunoscore in colorectal cancer liver metastasis patients after hepatectomy

Various scoring systems have been proposed to predict the postoperative prognosis of colorectal liver metastasis (CRLM), including the clinical risk score (CRS), the immunoscore and so on. Recently, histopathological growth patterns (HGPs) have been recognized. However, the correlation between HGPs and the immunoscore, and their prognostic values in patients with CRLM after liver resection remain undetermined. In this study, HGPs were retrospectively evaluated in H&E-stained slides from 166 CRLM patients. The immunoscore was calculated according to the densities of immunostained CD3 + and CD8 + cells. A risk score combining HGPs, the immunoscore and the CRS was defined and divided patients into the low-, medium- and high-risk group. Our results showed that the densities of CD3 + and CD8 + cells were higher in the desmoplastic HGP (dHGP) group than in the non-dHGP group, and the proportion of high immunoscores was also higher in the dHGP group (51.9% vs. 33.0%, respectively, P = 0.020). Patients with the dHGP had significantly longer relapse-free survival (RFS) and overall survival (OS) than those with the non-HGP. The low-risk group showed significantly higher 2-year RFS and 5-year OS rates than the other two groups (RFS: 76.2%, 43.7% and 33.1%, respectively; P < 0.001; OS: 89.7%, 54.4% and 33.3%, respectively; P < 0.001). In conclusion, the dHGP correlates with relatively high immunoscores, predicting a favorable prognosis independent of the immunoscore and CRS. A novel risk score combining HGPs, the immunoscore and the CRS may be used for the stratification of CRLM patients' survival.

Interrogating the microenvironmental landscape of tumors with computational image analysis approaches

The tumor microenvironment is an interacting heterogeneous collection of cancer cells, resident as well as infiltrating host cells, secreted factors, and extracellular matrix proteins. With the growing importance of immunotherapies, it has become crucial to be able to characterize the composition and the functional orientation of the microenvironment. The development of novel computational image analysis methodologies may enable the robust quantification and localization of immune and related biomarker-expressing cells within the microenvironment. The aim of the review is to concisely highlight a selection of current and significant contributions pertinent to methodological advances coupled with biomedical or translational applications. A further aim is to concisely present computational advances that, to our knowledge, have currently very limited use for the assessment of the microenvironment but have the potential to enhance image analysis pipelines; on this basis, an example is shown for the detection and segmentation of cells of the microenvironment using a published pipeline and a public dataset. Finally, a general proposal is presented on the conceptual design of automation-optimized computational image analysis workflows in the biomedical and clinical domain.

Expression of Monocarboxylate Transporter 1 in Immunosuppressive Macrophages Is Associated With the Poor Prognosis in Breast Cancer

Monocarboxylate transporter 1 (MCT1) participates in the transport of lactate to facilitate metabolic reprogramming during tumor progression. Tumor-associated macrophages (TAMs) are also involved in the inflammatory adaptation of the tumor microenvironment (TME). This study aimed to determine the correlation between metabolite changes and the polarization of macrophages in the TME. We demonstrated that the expression of CD163 on macrophages was significantly higher in breast cancer tissues than in normal tissues, especially in the HER2 subtype, although it was not statistically associated with recurrence-free survival (RFS). The presence of MCT1⁺ and CD163⁺ macrophages in the invasive margin was significantly correlated with decreased RFS. A significant correlation existed between MCT1 and CD163 expression in the margin, and high infiltration of MCT1⁺CD163⁺ macrophages into the margin predicted rapid progression and poor survival outcomes for breast cancer patients. These data suggested that MCT1 at least partially promoted the alternative polarization of macrophages to inhibit antitumor immunity, and blocking this interaction may be a promising method for breast cancer therapy.

Immune contexture analysis in immuno-oncology: applications and challenges of multiplex fluorescent immunohistochemistry

The tumor microenvironment is an integral player in cancer initiation, tumor progression, response and resistance to anti-cancer therapy. Understanding the complex interactions of tumor immune architecture (referred to as 'immune contexture') has therefore become increasingly desirable to guide our approach to patient selection, clinical trial design, combination therapies, and patient management. Quantitative image analysis based on multiplexed fluorescence immunohistochemistry and deep learning technologies are rapidly developing to enable researchers to interrogate complex information from the tumor microenvironment and find predictive insights into treatment response. Herein, we discuss current developments in multiplexed fluorescence immunohistochemistry for immune contexture analysis, and their application in immuno-oncology, and discuss challenges to effectively use this technology in clinical settings. We also present a multiplexed image analysis workflow to analyse fluorescence multiplexed stained tumor sections using the Vectra Automated Digital Pathology System together with FCS express flow cytometry software. The benefit of this strategy is that the spectral unmixing accurately generates and analyses complex arrays of multiple biomarkers, which can be helpful for diagnosis, risk stratification, and guiding clinical management of oncology patients.

The Unmet Needs of the Diagnosis, Staging, and Treatment of Gastrointestinal Tumors

New scientific insights in cancer biology and immunobiology have changed the clinical practice of medical oncology in recent years. The molecular stratification of solid tumors has led to improved clinical outcomes and is a key part in the diagnostic workup. Beyond mutational spectra (like Rat sarcoma [RAS] mutations or tumor mutational burden), the investigation of the immunological microenvironment has attracted more efforts. Especially as immunotherapies have changed the standard treatment for some solid tumors dramatically and have become an important part of routine oncology, also for gastrointestinal tumors. Still only a subgroup of patients benefits from immunotherapy in gastrointestinal tumors with prominent examples from colorectal, pancreatic or gastric cancer. Not only microsatellite instability as a marker for response to immunotherapy has shown its utility, there plenty of other approaches currently being investigated to better stratify and understand the microenvironment. But these insights have not translated into clinical utility. Reasons for this are limited technical capabilities for stratification and for coping with heterogeneity of tumor cells and the microenvironment as such. So the situation for gastrointestinal tumors has shown mainly progress for a subgroup of immunotherapy-receptive tumors (eg, microsatellite instability), but advances for the remaining majority have been in the area of stratification and combinatorial therapies, including approaches without chemotherapy. Molecular stratification (eg, B-Rapidly Accelerated Fibrosarcoma [BRAF] V600E mutation in colorectal cancer or NRG1 fusions in Kirsten-rat sarcoma (KRAS) Wild-Type Pancreatic Cancer) has clearly improved the possibilities for directed therapies, but there is a plethora of clinical situations where further developments are needed to improve patient care. Finding these areas and identifying the technical approach to unravel the complexities is the next decisive step. Here the recent advances are summarized and an outlook on possible diagnostic and treatment options in areas of unmet need is given with the context of new molecular imaging possibilities and cutting edge advances in nuclear medicine.

Occupancy and Fractal Dimension Analyses of the Spatial Distribution of Cytotoxic (CD8+) T Cells Infiltrating the Tumor Microenvironment in Triple Negative Breast Cancer

Favorable outcomes have been associated with high densities of tumor infiltrating lymphocytes (TILs) such as cytotoxic ([Formula: see text]) T cells. However, the clinical significance of the spatial distribution of TILs is less well understood. We have developed novel statistical techniques to characterize the spatial distribution of TILs at various length scales. These include a box counting method that we call “occupancy” and novel applications of fractal dimensions. We apply these techniques to the spatial distribution of [Formula: see text] T cells in the tumor microenvironment of tissue resected from 35 triple negative breast cancer patients. We find that there is a distinct difference in the spatial distribution of [Formula: see text] T cells between good clinical outcome (no recurrence within at least 5 years of diagnosis) and poor clinical outcome (recurrence within 3 years of diagnosis). The statistical significance of the difference between good and poor outcome in the occupancy, fractal dimension (FD), and FD difference of [Formula: see text] T cells is comparable to that of the [Formula: see text] T cell density. Even when we randomly exclude some of the cells so that the images have the same cell density, we still find that the fractal dimension at short length scales is correlated with cancer recurrence, implying that the actual spatial distribution of [Formula: see text] cells, and not just the [Formula: see text] cell density, is associated with clinical outcome. The occupancy and FD difference indicate that the [Formula: see text] T cells are more spatially dispersed in good outcome and more aggregated in poor outcome. We discuss possible interpretations.

Immunogradient Indicators for Antitumor Response Assessment by Automated Tumor-Stroma Interface Zone Detection

The distribution of tumor-infiltrating lymphocytes (TILs) within the tumor microenvironment provides strong prognostic value, which is increasingly important with the arrival of new immunotherapy modalities. Both visual and image analysis-based assays are developed to assess the immune contexture of the tumors. We propose an automated method based on grid subsampling of microscopy image analysis data to extract the tumor-stroma interface zone (IZ) of controlled width. The IZ is a ranking of tissue areas by their distance to the tumor edge, which is determined by a set of explicit rules. TIL density profiles across the IZ are used to compute a set of novel immunogradient indicators that reflect TIL gradient towards the tumor. We applied this method on CD8 immunohistochemistry images of surgically excised hormone receptor-positive breast and colorectal cancers to predict overall patient survival. In both cohorts, the immunogradient indicators enabled strong and independent prognostic stratification, outperforming clinical and pathologic variables. Patients with breast cancer with low immunogradient levels had a prominent decrease in survival probability 5 years after surgery. Our study provides proof of concept that data-driven, automated, operator-independent IZ sampling enables spatial immune response measurement in the tumor-host interaction frontline for prediction of disease outcomes.

A gene signature for immune subtyping of desert, excluded, and inflamed ovarian tumors

PROBLEM

The current tumor immunology paradigm emphasizes the role of the immune tumor microenvironment and distinguishes several histologically and transcriptionally different immune tumor subtypes. However, the experimental validation of such classification is so far limited to selected cancer types. Here, we aimed to explore the existence of inflamed, excluded, and desert immune subtypes in ovarian cancer, as well as investigate their association with the disease outcome.

METHOD OF STUDY

We used the publicly available ovarian cancer dataset from The Cancer Genome Atlas for developing subtype assignment algorithm, which was next verified in a cohort of 32 real-world patients of a known tumor subtype.

RESULTS

Using clinical and gene expression data of 489 ovarian cancer patients in the publicly available dataset, we identified three transcriptionally distinct clusters, representing inflamed, excluded, and desert subtypes. We developed a two-step subtyping algorithm with COL5A2 serving as a marker for separating excluded tumors, and CD2, TAP1, and ICOS for distinguishing between inflamed and desert tumors. The accuracy of gene expression-based subtyping algorithm in a real-world cohort was 75%. Additionally, we confirmed that patients bearing inflamed tumors are more likely to survive longer.

CONCLUSION

Our results highlight the presence of transcriptionally and histologically distinct immune subtypes among ovarian tumors and emphasize the potential benefit of immune subtyping as a clinical tool for treatment tailoring.

Regulatory T cells and cytotoxic T cells close to the epithelial-stromal interface are associated with a favorable prognosis

Cytotoxic T cells and regulatory T cells play a crucial role in the outcome of cancer patients. Besides the density of these cells, it was shown recently that the spatial distribution is equally important. Here, we specifically analyzed the spatial distribution of these T cell subtypes at the epithelial-stromal interface in a rectal cancer cohort and its relevance for prognosis. We studied a cohort of 191 patients with advanced rectal cancer treated by radiochemotherapy (RCT). Tissue microarrays were immunohistochemical double-stained by FoxP3+ and CD+. Cell densities were analyzed in the stromal and epithelial compartment. Additionally, an image analysis software calculated the distances of lymphocytes to the epithelial-stromal interface (ESI). CD8+ and FoxP3+ cell counts decreased clearly after RCT with the decrease of FoxP3+ being more pronounced than of CD8+ cells. In the invasive front, short distances of the ESI to CD8+ and to FoxP3+ cells were associated with improved overall survival. Cell counts in the stromal compartment had no influence on prognosis. No correlation between stromal and epithelial lymphocyte densities was observed. The distance of epithelial-stromal interface to CD8+ and FoxP3+ cells was more accurate in predicting prognosis in the stromal compartment of rectal cancer patients than mere cell counts and could thereby be means of better stratifying patients for therapy. This observation will have to be validated in future prospective studies with regard to other tumor entities and its implications for the responsiveness of tumors to new therapeutic modalities.

B Cells as Prognostic Biomarker After Surgery for Colorectal Liver Metastases

Background: The aim of this study was to identify more accurate variables to improve prognostication of individual patients with colorectal liver metastases (CRLM). Clinicopathological characteristics only partly explain the large range in survival rates. Methods: MessengerRNA expression profiles of resected CRLM of two patient groups were analysed by mRNA sequencing: poor survivors (death from recurrent disease <30 months after surgery) and good survivors (no recurrent disease >60 months after surgery). Tumour and adjacent liver parenchyma samples were analysed. Results: MessengerRNA expression profiling of the tumour samples identified 77 genes that were differentially expressed between the two survival groups at a False Discovery Rate (FDR) <0.1. In the adjacent liver parenchyma samples only one gene, MTRNR2L1, showed significantly higher expression in the good survivors. Pathway analysis showed higher expression of immune-related and stroma-related genes in tumour samples from good survivors. Expression data was then validated by immunohistochemistry in two cohorts comprising a total of 125 patients. Immunohistochemical markers that showed to be associated with good survival in the total cohort were: high K/L+ infiltration in tumour stroma [p = 0.029; OR 2.500 (95% CI 1.100-5.682)] and high CD79A+ infiltration in tumour stroma [p = 0.036; OR 2.428 (95%CI 1.062-5.552)]. Conclusions: A high stromal infiltration of CD79A+ B cells and K/L+ plasma cells might be favourable prognostic biomarkers after surgery for CRLM.

The InSituPlex® Staining Method for Multiplexed Immunofluorescence Cell Phenotyping and Spatial Profiling of Tumor FFPE Samples

Multiplexed immunohistochemistry (mIHC) enables the detection, quantification, and localization of many markers within cell or tissue samples, leading to a better understanding of the architecture of a disease at the cellular level. Current mIHC techniques involve long staining and assay times, require dedicated and/or captive instrumentation, and entail tedious assay optimization, hindering their establishment as routine methods. Here, we demonstrate the use of the InSituPlex^® method for spatial profiling of immuno-oncology targets in FFPE tumor tissue with the UltiMapper™ I/O PD-L1 multiplex assay. The panel consists of five protein markers to profile immune infiltration and PD-L1 expression and includes CD8, CD68, PD-L1, pan CK, and SOX10 markers. The assay shows benefits of high and low expression of markers, coexpression and colocalization of proteins in single cells, and completion of staining and image acquisition in 5.5 h. Through the combination of multiplexed characterization of protein expression in whole tissue sections, fast staining workflow, and compatibility with existing instrumentation, the InSituPlex method provides a robust modality for deep phenotyping of the tumor and its microenvironment.

Multiplexed immunohistochemistry for immune cell phenotyping, quantification and spatial distribution in situ

It is increasingly recognized that a deep characterization of the immune microenvironment is required for the identification of prognostic and predictive immune biomarkers. Recent advances in the field of tissue imaging resulted in the development of fluorescence multiplex IHC technologies enabling quantitative assessment of immune phenotypes and functional orientation of immune cells in a way similar to flow cytometry, while simultaneously providing tissue context and spatial distribution. Multiplex immunofluorescent technology to FFPE tumor tissue is applied to characterize immune infiltration and PD-L1 expression. A panel consists of five protein markers: CD8, CD68, PD-L1, CK, and SOX10. The assay workflow is fast, optimized and compatible with existing instrumentation. The resulting images can be analyzed with routinely used software for digital pathology enabling the quantification of dynamic range of expression, co-localization and co-expression of markers in the whole tissue. In this chapter, we provide the protocol for the use of the UltiMapper™ I/O PD-L1 multiplex assay, from the bench to the image analysis, as well as an overview of the current multiplex image analysis solutions. Such deep profiling could guide the development of strategies to better select immune checkpoint molecules and a better stratification of patients who will potentially benefit from immunotherapies.

Close proximity of immune and tumor cells underlies response to anti-PD-1 based therapies in metastatic melanoma patients

Immune checkpoint blockade has greatly improved the clinical outcomes of many patients with metastatic melanoma, however, almost half do not respond. Whether the interspatial distribution of immune and tumor cells predicts response to anti-PD-1-based therapies and patient outcomes in any cancer, including melanoma, is currently unknown. Here, we examined the spatial distribution of immune and tumor cells via multiplex immunofluorescence. Pre-treatment melanoma specimens from 27 patients (n = 18 responders; n = 9 non-responders) treated with anti-PD-1 monotherapy and 34 patients (n = 22 responders; n = 12 non-responders) treated with combined ipilimumab and anti-PD-1 immunotherapy were studied. Responders displayed significantly higher densities of CD8⁺ tumor-infiltrating lymphocytes within a 20 µM distance from a melanoma cell compared to non-responders in both anti-PD-1 alone (p = .0024) and combination-treated patients (p = .0096), that were associated with improved progression-free survival for both therapies (anti-PD-1 p = .0158; combination therapy p = .0088). In multivariate analysis, the best model for 12-month progression-free survival for anti-PD-1 monotherapy included PD-L1⁺ cells within proximity to tumor cells and intratumoral CD8⁺ density (AUC = 0.80), and for combination therapy included CD8⁺ cells in proximity to tumor cells, intratumoral PD-L1⁺ density and LDH (AUC = 0.85). Assessment of the spatial distribution of immune cells in relation to tumor cells provides insight into their role in modulating immune response and highlights their potential role as predictors of response to anti-PD-1 based therapies.

Circulating Tumor Cells as a Tool for Assessing Tumor Heterogeneity

Tumor heterogeneity is the major cause of failure in cancer prognosis and prediction. Accurately detecting heterogeneity for the development of biomarkers and the detection of the clones resistant to therapy is one of the main goals of contemporary medicine. Metastases belong to the natural history of cancer. The present review gives an overview on the origin of tumor heterogeneity. Recent progress has made it possible to isolate and characterize circulating tumor cells (CTCs), which are the drivers of the disease between the primary sites and metastatic foci. The most recent methods for characterizing CTCs are summarized and we discuss the power of CTC profiling for analyzing tumor heterogeneity in early and advanced diseases.

Automatic discovery of image-based signatures for ipilimumab response prediction in malignant melanoma

In the context of precision medicine with immunotherapies there is an increasing need for companion diagnostic tests to identify potential therapy responders and avoid treatment coming along with severe adverse events for non-responders. Here, we present a retrospective case study to discover image-based signatures for developing a potential companion diagnostic test for ipilimumab (IPI) in malignant melanoma. Signature discovery is based on digital pathology and fully automatic quantitative image analysis using virtual multiplexing as well as machine learning and deep learning on whole-slide images. We systematically correlated the patient outcome data with potentially relevant local image features using a Tissue Phenomics approach with a sound cross validation procedure for reliable performance evaluation. Besides uni-variate models we also studied combinations of signatures in several multi-variate models. The most robust and best performing model was a decision tree model based on relative densities of CD8+ tumor infiltrating lymphocytes in the intra-tumoral infiltration region. Our results are well in agreement with observations described in previously published studies regarding the predictive value of the immune contexture, and thus, provide predictive potential for future development of a companion diagnostic test.

Systematic Review of the Prognostic Role of the Immune System After Surgery of Colorectal Liver Metastases

Background: The current prognostication of patient survival after surgery for colorectal liver metastases is based on clinical characteristics, but low accuracy makes it difficult to guide treatment for the individual patient. Rapidly evolving technologies have led to the expectation that biomarkers will be able to outperform the current clinical scoring systems and provide more effective personalised treatment. Two main topics prevail in cancer treatment, namely the role of the immune system and the prediction and prognostication by application of high-throughput methodology. The aim of this review is to examine the evidence for prognostic immunological and molecular markers studied in tumour tissue obtained at surgical resection for colorectal liver metastases.

Methods: First we analysed immunophenotypical protein markers, that are mainly studied by immunohistochemistry. Second, we review molecular markers by analysing high-throughput studies on tumour mRNA and microRNA expression.

Results: CD3, CD4, and CD8 are the most frequently studied protein markers. High intra-tumoural CD3+ T cell infiltration and low CXCR4 expression have the best association with favourable patient survival. Studies that analysed microRNA or mRNA expression data showed very little overlap in prognostic genes.

Conclusions: Patient prognostication after surgery for colorectal liver metastases by analysing the immune system remains difficult. Current data are based on diverse and heterogeneous patient populations which prohibits drawing firm conclusions.

Strategies and Techniques for NK Cell Phenotyping

Therapies based on activating the immune system, that is, immunotherapy, are now widely implemented in clinical praxis in patients with advanced cancer. Although cancer immunotherapy can result in long-lasting clinical responses, the majority of patients do not respond or develop resistance. Furthermore, cancer immunotherapy is being increasingly combined with other forms of immunotherapy or conventional cancer therapies. It is therefore much needed to identify biomarkers that can precisely classify what patients will benefit from the treatment without any major adverse events and to further develop the efficacy of cancer immunotherapy. While much attention has been focused on monitoring T cell responses in cancer immunotherapy, recent reports have shown that NK cells also play a major role in the response to cancer immunotherapy. The gold standard for immunoprofiling of NK cells is flow cytometry, but other technologies have emerged and include mass cytometry, multiplex immunohistochemistry, and single-cell RNA-sequencing. In this chapter we provide a detailed protocol to profile NK cells using flow cytometry, and a brief introduction to other techniques.

Radiation combined with macrophage depletion promotes adaptive immunity and potentiates checkpoint blockade

Emerging evidence suggests a role for radiation in eliciting anti-tumour immunity. We aimed to investigate the role of macrophages in modulating the immune response to radiation. Irradiation to murine tumours generated from colorectal (MC38) and pancreatic (KPC) cell lines induced colony-stimulating factor 1 (CSF-1). Coincident with the elevation in CSF-1, macrophages increased in tumours, peaking 5 days following irradiation. These tumour-associated macrophages (TAMs) were skewed towards an immunosuppressive phenotype. Macrophage depletion via anti-CSF (aCSF) reduced macrophage numbers, yet only achieved tumour growth delay when combined with radiation. The tumour growth delay from aCSF after radiation was abrogated by depletion of CD8 T cells. There was enhanced recognition of tumour cell antigens by T cells isolated from irradiated tumours, consistent with increased antigen priming. The addition of anti-PD-L1 (aPD-L1) resulted in improved tumour suppression and even regression in some tumours. In summary, we show that adaptive immunity induced by radiation is limited by the recruitment of highly immunosuppressive macrophages. Macrophage depletion partly reduced immunosuppression, but additional treatment with anti-PD-L1 was required to achieve tumour regression.

Multiparametric analysis of colorectal cancer immune responses

Colorectal cancer (CRC) is a heterogeneous disease, with a diverse and plastic immune cell infiltrate. These immune cells play an important role in regulating tumour growth - progression or elimination. Some populations of cells have a strong correlation with disease-free survival, making them useful prognostic markers. In particular, the infiltrate of CD3+ and CD8+ T cells into CRC tumours has been validated worldwide as a valuable indicator of patient prognosis. However, the heterogeneity of the immune response, both between patients with tumours of different molecular subtypes, and within the tumour itself, necessitates the use of multiparametric analysis in the investigation of tumour-specific immune responses. This review will outline the multiparametric analysis techniques that have been developed and applied to studying the role of immune cells in the tumour, with a focus on colorectal cancer. Because much of the data in this disease relates to T cell subsets and heterogeneity, we have used T cell populations as examples throughout. Flow and mass cytometry give a detailed representation of the cells within the tumour in a single-cell suspension on a per-cell basis. Imaging technologies, such as imaging mass cytometry, are used to investigate increasing numbers of markers whilst retaining the spatial and structural information of the tumour section and the infiltrating immune cells. Together, the analyses of multiple immune parameters can provide valuable information to guide clinical decision-making in CRC.

Depleted polymorphonuclear leukocytes in human metastatic liver reflect an altered immune microenvironment associated with recurrent metastasis

BACKGROUND

Hepatic immunity, normally protective against neoplasia, is subverted in colorectal liver metastasis (CRLM). Here, we compare the inflammatory microenvironment of CRLM-bearing liver tissue to donor liver.

METHODS

Twenty-five patients undergoing resection for CRLM were recruited, 13 of whom developed intrahepatic recurrence within 18 months. Biopsies were obtained from tumour and normal liver tissue adjacent to and distal from, the tumour. Donor liver biopsies were obtained during transplantation. Biopsies were cultured and conditioned media (CM) screened for 102 inflammatory mediators. Twelve of these were validated by Luminex assay. Transwell assays measured cancer cell chemotaxis. Polymorphonuclear leukocytes (PMN) and lymphocytes were quantified in H&E sections.

RESULTS

Fewer periportal tissue-resident PMN were present in metastatic liver compared to donor liver. Patients with the fewest PMN in liver tissue distal to their tumour had a shorter time to intrahepatic recurrence (P < 0.001). IL-6, CXCL1, CXCL5, G-CSF, GM-CSF, VEGF, LIF, and CCL3 were higher in liver-bearing CRLM compared to donor tissue. Consequently, cancer cells migrated equally towards CM of all regions of metastatic liver but not towards donor liver CM.

CONCLUSIONS

The local inflammatory environment may affect both immune cell infiltration and cancer cell migration contributing to recurrence following resection for CRLM.

Genomics and emerging biomarkers for immunotherapy of colorectal cancer

Colorectal cancer (CRC) is a common and lethal disease with a high therapeutic need. For most patients with metastatic CRC, chemotherapy is the only viable option. Currently, immunotherapy is restricted to the particular genetic subgroup of mismatch-repair deficient (MMRd)/microsatellite instable (MSI) CRC. Anti-PD1 therapy was recently FDA-approved as a second-line treatment in this subgroup. However, in a metastatic setting, these MMRd/MSI tumors are vastly outnumbered by mismatch-repair proficient (MMRp)/microsatellite stable (MSS) tumors. These MMRp/MSS tumors do not meaningfully respond to any traditional immunotherapy approach including checkpoint blockade, adoptive cell transfer and vaccination. This resistance to immunotherapy is due to a complex tumor microenvironment that counteracts antitumor immunity through a combination of poorly antigenic tumor cells and an immunosuppressive tumor microenvironment. To find ways of overcoming immunotherapy resistance in the majority of CRC patients, it is necessary to analyze the immunological makeup in an in-depth and personalized way and in the context of their tumor genetic makeup. Flexible, biomarker-guided early-phase immunotherapy trials are needed to optimize this workflow. In this review, we detail key mechanisms for immune evasion and emerging immune biomarkers for personalized immunotherapy in CRC. Also, we present a template for biomarker-guided clinical trials that are needed to move new immunotherapy approaches closer to clinical application.

Multispectral imaging for quantitative and compartment-specific immune infiltrates reveals distinct immune profiles that classify lung cancer patients

Semiquantitative assessment of immune markers by immunohistochemistry (IHC) has significant limitations for describing the diversity of the immune response in cancer. Therefore, we evaluated a fluorescence-based multiplexed immunohistochemical method in combination with a multispectral imaging system to quantify immune infiltrates in situ in the environment of non-small-cell lung cancer (NSCLC). A tissue microarray including 57 NSCLC cases was stained with antibodies against CD8, CD20, CD4, FOXP3, CD45RO, and pan-cytokeratin, and immune cells were quantified in epithelial and stromal compartments. The results were compared with those of conventional IHC, and related to corresponding RNA-sequencing (RNAseq) expression values. We found a strong correlation between the visual and digital quantification of lymphocytes for CD45RO (correlation coefficient: r = 0.52), FOXP3 (r = 0.87), CD4 (r = 0.79), CD20 (r = 0.81) and CD8 (r = 0.90) cells. The correlation with RNAseq data for digital quantification (0.35-0.65) was comparable to or better than that for visual quantification (0.38-0.58). Combination of the signals of the five immune markers enabled further subpopulations of lymphocytes to be identified and localized. The specific pattern of immune cell infiltration based either on the spatial distribution (distance between regulatory CD8⁺ T and cancer cells) or the relationships of lymphocyte subclasses with each other (e.g. cytotoxic/regulatory cell ratio) were associated with patient prognosis. In conclusion, the fluorescence multiplexed immunohistochemical method, based on only one tissue section, provided reliable quantification and localization of immune cells in cancer tissue. The application of this technique to clinical biopsies can provide a basic characterization of immune infiltrates to guide clinical decisions in the era of immunotherapy. Copyright © 2017 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.