Immuno-Interface Score to Predict Outcome in Colorectal Cancer Independent of Microsatellite Instability Status

Clinical significance of combined tumour-infiltrating lymphocytes and microsatellite instability status in colorectal cancer: a systematic review and network meta-analysis

BACKGROUND

Microsatellite instability (MSI) status and tumour-infiltrating lymphocytes (TIL) are established prognostic factors in colorectal cancer. Previous studies evaluating the combination of TIL and MSI status identified distinct colorectal cancer subtypes with unique prognostic associations. However, these studies were often limited by sample size, particularly for MSI-high (MSI-H) tumours, and there is no comprehensive summary of the available evidence. We aimed to review the literature to compare the survival outcomes associated with the subtypes derived from the integrated MSI-TIL classification in patients with colorectal cancer.

METHODS

In this systematic review and network meta-analysis, we searched PubMed, Embase, Scopus, and the Cochrane Library without language restrictions, for articles published between Jan 1, 1990, and March 13, 2024. Patient cohorts comparing different combinations of TIL (high or low) and MSI status (MSI or microsatellite stable [MSS]) in patients with surgically resected colorectal cancer were included. Studies were excluded if they focused on neoadjuvant therapy or on other immune markers such as B cells or macrophages. Methodological quality assessment was done with the Newcastle-Ottawa scale; data appraisal and extraction was done independently by two reviewers. Summary estimates were extracted from published reports. The primary outcomes were overall survival, disease-free survival, and cancer-specific survival. A frequentist network meta-analysis was done to compare hazard ratios (HRs) and 95% CI for each outcome. The MSI-TIL subgroups were prognostically ranked based on P-score, bias, magnitude, and precision of associations with each outcome. The protocol is registered with PROSPERO (CRD42023461108).

FINDINGS

Of 302 studies initially identified, 21 studies (comprising 14 028 patients) were included in the systematic review and 19 (13 029 patients) in the meta-analysis. Nine studies were identified with a low risk of bias and the remaining ten had a moderate risk of bias. The MSI-TIL-high (MSI-TIL-H) subtype exhibited longer overall survival (HR 0·45, 95% CI 0·34-0·61; I2=77·7%), disease-free survival (0·43, 0·32-0·58; I2=61·6%), and cancer-specific survival (0·53, 0·43-0·66; I2=0%), followed by the MSS-TIL-H subtype for overall survival (HR 0·53, 0·41-0·69; I2=77·7%), disease-free survival (0·52, 0·41-0·64; I2=61·6%), and cancer-specific survival (0·55, 0·47-0·64; I2=0%) than did patients with MSS-TIL-low tumours (MSS-TIL-L). Patients with the MSI-TIL-L subtype had similar overall survival (0·88, 0·66-1·18; I2=77·7%) and disease-free survival (0·93, 0·69-1·26; I2=61·6%), but a modestly longer cancer-specific survival (0·72, 0·57-0·90; I2=0%) than did the MSS-TIL-L subtype. Results from the direct and indirect evidence were strongly congruous.

INTERPRETATION

The findings from this network meta-analysis suggest that better survival was only observed among patients with TIL-H colorectal cancer, regardless of MSI or MSS status. The integrated MSI-TIL classification should be further explored as a predictive tool for clinical decision-making in early-stage colorectal cancer.

FUNDING

German Research Council (HO 5117/2-2).

The prognostic effect of tumor-associated macrophages in stage I-III colorectal cancer depends on T cell infiltration

BACKGROUND

Tumor-associated macrophages (TAMs) are associated with unfavorable patient prognosis in many cancer types. However, TAMs are a heterogeneous cell population and subsets have been shown to activate tumor-infiltrating T cells and confer a good patient prognosis. Data on the prognostic value of TAMs in colorectal cancer are conflicting. We investigated the prognostic effect of TAMs in relation to tumor-infiltrating T cells in colorectal cancers.

METHODS

The TAM markers CD68 and CD163 were analyzed by multiplex fluorescence immunohistochemistry and digital image analysis on tissue microarrays of 1720 primary colorectal cancers. TAM density in the tumor stroma was scored in relation to T cell density (stromal CD3+ and epithelial CD8+ cells) and analyzed in Cox proportional hazards models of 5-year relapse-free survival. Multivariable survival models included clinicopathological factors, MSI status and BRAFV600E mutation status.

RESULTS

High TAM density was associated with a favorable 5-year relapse-free survival in a multivariable model of patients with stage I-III tumors (p = 0.004, hazard ratio 0.94, 95% confidence interval 0.90-0.98). However, the prognostic effect was dependent on tumoral T-cell density. High TAM density was associated with a good prognosis in patients who also had high T-cell levels in their tumors, while high TAM density was associated with poorer prognosis in patients with low T-cell levels (pinteraction = 0.0006). This prognostic heterogeneity was found for microsatellite stable tumors separately.

CONCLUSIONS

This study supported a phenotypic heterogeneity of TAMs in colorectal cancer, and showed that combined tumor immunophenotyping of multiple immune cell types improved the prediction of patient prognosis.

Tumor-draining lymph nodes: opportunities, challenges, and future directions in colorectal cancer immunotherapy

Tumor-draining lymph nodes (TDLNs) are potential immunotherapy targets that could expand the population of patients with colorectal cancer (CRC) who may benefit from immunotherapy. Currently, pathological detection of tumor cell infiltration limits the acquisition of immune information related to the resected lymph nodes. Understanding the immune function and metastatic risk of specific stages of lymph nodes can facilitate better discussions on the removal or preservation of lymph nodes, as well as the timing of immunotherapy. This review summarized the contribution of TDLNs to CRC responses to immune checkpoint blockade therapy, local immunotherapy, adoptive cell therapy, and cancer vaccines, and discussed the significance of these findings for the development of diagnostics based on TDLNs and the potential implications for guiding immunotherapy after a definitive diagnosis. Molecular pathology and immune spectrum diagnosis of TDLNs will promote significant advances in the selection of immunotherapy options and predicting treatment efficacy.

Identification of necroptosis-related lncRNAs for prognosis prediction and screening of potential drugs in patients with colorectal cancer

BACKGROUND

Tumor recurrence and metastasis lead to a poor prognosis in colorectal cancer (CRC). Necroptosis is closely related to the tumor microenvironment (TME) and affects tumor recurrence and metastasis. We aimed to stratify CRC patients according to necroptosis-related long noncoding RNAs (lncRNAs), which can be used to not only evaluate prognosis and improve precision medicine in clinical practice but also screen potential immunotherapy drugs.

AIM

To stratify CRC patients according to necroptosis-related lncRNAs (NRLs), which can be used to not only evaluate prognosis and improve precision medicine in clinical practice but also screen potential immunotherapy drugs.

METHODS

LncRNA expression profiles were collected from The Cancer Genome Atlas. NRLs were identified by coexpression analysis. Cox regression analysis identified a NRL signature. Then, the value of this signature was comprehensively and multidimensionally evaluated, and its reliability for CRC prognosis prediction was assessed with clinical CRC data and compared with that of six other lncRNA signatures. Gene set enrichment analysis, TME analysis and half-maximal inhibitory concentration (IC₅₀) prediction were also performed according to the risk score (RS) of the signature.

RESULTS

An 8-lncRNA signature significantly associated with overall survival (OS) was constructed, and its reliability was validated with clinical CRC data. Most of the areas under the receiver operating characteristic curves (AUCs) values for 1-, 3- and 5-year OS for this signature were higher than those for the other six lncRNA signatures. OS, disease-specific survival and the progression-free interval were all significantly poorer in the high-risk group. The RS of the signature showed good concordance with the predicted prognosis, with AUCs for 1-, 3- and 5-year OS of 0.79, 0.81 and 0.77, respectively. Additionally, the calibration plots for this signature combined with clinical factors showed that this combination could effectively improve the ability to predict OS. The RS was correlated with tumor stage, lymph node metastasis and distant metastasis. Most of the enriched Kyoto Encyclopedia of Genes and Genomes and Gene Ontology terms were tumor metastasis-related pathways in the high-risk group; these patients showed greater infiltration of immunosuppressive cells, such as cancer-associated fibroblasts, hematopoietic stem cells and M2 macrophages, but less infiltration of infiltrating antitumor effector immune cells, such as cluster of differentiation 8⁺ T cells and regulatory T cells (Tregs). We explored additional potential immune checkpoint genes and potential immunotherapeutic and chemotherapeutic drugs with relatively low IC₅₀ values.

CONCLUSION

We identified an NRL signature with strong fidelity that could stably predict prognosis and might be an indicator of the TME of CRC. Furthermore, additional potential immunotherapeutic and chemotherapeutic drugs were explored.

Multi-scale spatial modeling of immune cell distributions enables survival prediction in primary central nervous system lymphoma

To understand the clinical significance of the tumor microenvironment (TME), it is essential to study the interactions between malignant and non-malignant cells in clinical specimens. Here, we established a computational framework for a multiplex imaging system to comprehensively characterize spatial contexts of the TME at multiple scales, including close and long-distance spatial interactions between cell type pairs. We applied this framework to a total of 1,393 multiplex imaging data newly generated from 88 primary central nervous system lymphomas with complete follow-up data and identified significant prognostic subgroups mainly shaped by the spatial context. A supervised analysis confirmed a significant contribution of spatial context in predicting patient survival. In particular, we found an opposite prognostic value of macrophage infiltration depending on its proximity to specific cell types. Altogether, we provide a comprehensive framework to analyze spatial cellular interaction that can be broadly applied to other technologies and tumor contexts.

CD8+ Cell Density Gradient across the Tumor Epithelium-Stromal Interface of Non-Muscle Invasive Papillary Urothelial Carcinoma Predicts Recurrence-Free Survival after BCG Immunotherapy

BACKGROUND

Bacille Calmette-Guerin (BCG) immunotherapy is the first-line treatment in patients with high-risk non-muscle invasive papillary urothelial carcinoma (NMIPUC), the most common type of bladder cancer. The therapy outcomes are variable and may depend on the immune response within the tumor microenvironment. In our study, we explored the prognostic value of CD8+ cell density gradient indicators across the tumor epithelium-stroma interface of NMIPUC.

METHODS

Clinical and pathologic data were retrospectively collected from 157 NMIPUC patients treated with BCG immunotherapy after transurethral resection. Whole-slide digital image analysis of CD8 immunohistochemistry slides was used for tissue segmentation, CD8+ cell quantification, and the assessment of CD8+ cell densities within the epithelium-stroma interface. Subsequently, the gradient indicators (center of mass and immunodrop) were computed to represent the density gradient across the interface.

RESULTS

By univariable analysis of the clinicopathologic factors, including the history of previous NMIPUC, poor tumor differentiation, and pT1 stage, were associated with shorter RFS (p < 0.05). In CD8+ analyses, only the gradient indicators but not the absolute CD8+ densities were predictive for RFS (p < 0.05). The best-performing cross-validated model included previous episodes of NMIPUC (HR = 4.4492, p = 0.0063), poor differentiation (HR = 2.3672, p = 0.0457), and immunodrop (HR = 5.5072, p = 0.0455).

CONCLUSIONS

We found that gradient indicators of CD8+ cell densities across the tumor epithelium-stroma interface, along with routine clinical and pathology data, improve the prediction of RFS in NMIPUC.

Fucosylation of HLA-DRB1 regulates CD4+ T cell-mediated anti-melanoma immunity and enhances immunotherapy efficacy

Immunotherapy efficacy is limited in melanoma, and combinations of immunotherapies with other modalities have yielded limited improvements but also adverse events requiring cessation of treatment. In addition to ineffective patient stratification, efficacy is impaired by paucity of intratumoral immune cells (itICs); thus, effective strategies to safely increase itICs are needed. We report that dietary administration of L-fucose induces fucosylation and cell surface enrichment of the major histocompatibility complex (MHC)-II protein HLA-DRB1 in melanoma cells, triggering CD4+ T cell-mediated increases in itICs and anti-tumor immunity, enhancing immune checkpoint blockade responses. Melanoma fucosylation and fucosylated HLA-DRB1 associate with intratumoral T cell abundance and anti-programmed cell death protein 1 (PD1) responder status in patient melanoma specimens, suggesting the potential use of melanoma fucosylation as a strategy for stratifying patients for immunotherapies. Our findings demonstrate that fucosylation is a key mediator of anti-tumor immunity and, importantly, suggest that L-fucose is a powerful agent for safely increasing itICs and immunotherapy efficacy in melanoma.

Prognostic Value of CD8+ Lymphocytes in Hepatocellular Carcinoma and Perineoplastic Parenchyma Assessed by Interface Density Profiles in Liver Resection Samples

Hepatocellular carcinoma (HCC) often emerges in the setting of long-standing inflammatory liver disease. CD8 lymphocytes are involved in both the antitumoral response and hepatocyte damage in the remaining parenchyma. We investigated the dual role of CD8 lymphocytes by assessing density profiles at the interfaces of both HCC and perineoplastic liver parenchyma with surrounding stroma in whole-slide immunohistochemistry images of surgical resection samples. We applied a hexagonal grid-based digital image analysis method to sample the interface zones and compute the CD8 density profiles within them. The prognostic value of the indicators was explored in the context of clinicopathological, peripheral blood testing, and surgery data. Independent predictors of worse OS were a low standard deviation of CD8+ density along the tumor edge, high mean CD8+ density within the epithelial aspect of the perineoplastic liver-stroma interface, longer duration of surgery, a higher level of aspartate transaminase (AST), and a higher basophil count in the peripheral blood. A combined score, derived from these five independent predictors, enabled risk stratification of the patients into three prognostic categories with a 5-year OS probability of 76%, 40%, and 8%. Independent predictors of longer RFS were stage pT1, shorter duration of surgery, larger tumor size, wider tumor-free margin, and higher mean CD8+ density in the epithelial aspect of the tumor-stroma interface. We conclude that (1) our computational models reveal independent and opposite prognostic impacts of CD8+ cell densities at the interfaces of the malignant and non-malignant epithelium interfaces with the surrounding stroma; and (2) together with pathology, surgery, and laboratory data, comprehensive prognostic models can be constructed to predict patient outcomes after liver resection due to HCC.

The prognostic impact of tumor-infiltrating B lymphocytes in patients with solid malignancies: A systematic review and meta-analysis

This study reviewed the prognostic effect of tumor-infiltrating B lymphocytes (TIBLs) on solid malignancies, to determine the potential role of TIBLs in predicting cancer patient's prognosis and their response to immunotherapy. A total of 45 original papers involving 11,099 individual patients were included in this meta-analysis covering 7 kinds of cancer. The pooled results suggested that high levels of TIBLs were correlated with favorable OS in lung, esophageal, gastric, colorectal, liver, and breast cancer; improved RFS in lung cancer; and improved DFS in gastrointestinal neoplasms. Additionally, TIBLs were significantly correlated with negative lymphatic invasion in gastric cancer, small tumor size in hepatocellular carcinoma, and negative distant metastasis in colorectal cancer. Additionally, TIBLs were reported as a discriminative feature of patients treated with immunotherapy with improved survival. We concluded that TIBLs play a favorable prognostic role among the common solid malignancie, providing theoretical evidence for further prognosis prediction for solid tumors.

Tumor-Infiltrating Lymphocytes in Colorectal Cancer: The Fundamental Indication and Application on Immunotherapy

The clinical success of immunotherapy has revolutionized the treatment of cancer patients, bringing renewed attention to tumor-infiltrating lymphocytes (TILs) of various cancer types. Immune checkpoint blockade is effective in patients with mismatched repair defects and high microsatellite instability (dMMR-MSI-H) in metastatic colorectal cancer (CRC), leading the FDA to accelerate the approval of two programmed cell death 1 (PD-1) blocking antibodies, pembrolizumab and nivolumab, for treatment of dMMR-MSI-H cancers. In contrast, patients with proficient mismatch repair and low levels of microsatellite stability or microsatellite instability (pMMR-MSI-L/MSS) typically have low tumor-infiltrating lymphocytes and have shown unsatisfied responses to the immune checkpoint inhibitor. Different TILs environments reflect different responses to immunotherapy, highlighting the complexity of the underlying tumor-immune interaction. Profiling of TILs fundamental Indication would shed light on the mechanisms of cancer-immune evasion, thus providing opportunities for the development of novel therapeutic strategies. In this review, we summarize phenotypic diversities of TILs and their connections with prognosis in CRC and provide insights into the subsets-specific nature of TILs with different MSI status. We also discuss current clinical immunotherapy approaches based on TILs as well as promising directions for future expansion, and highlight existing clinical data supporting its use.

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.