The Immunoscore in Localized Urothelial Carcinoma Treated with Neoadjuvant Chemotherapy: Clinical Significance for Pathologic Responses and Overall Survival

Gastric cancer immune microenvironment score predicts neoadjuvant chemotherapy efficacy and prognosis

The efficacy of neoadjuvant chemotherapy (NACT) in patients with advanced gastric cancer (GC) varies greatly. Thus, we aimed to verify the predictive value of tumor-infiltrating immune cells (TIICs) on the treatment response to NACT and the prognosis of patients with advanced GC, and to explore the impact of NACT on the tumor immune microenvironment (TIME). Paired tumor tissues (pre- and post-NACT) from patients with advanced GC were collected for this study. TIICs were assessed using immunohistochemistry staining and analyzed using logistic regression to establish an immune microenvironment score for GC (ISGC score) and predict NACT efficacy. Kaplan-Meier curves were used to evaluate the survival outcome of patients. The results showed that TIME was dramatically heterogeneous between NACT response and nonresponse patients. In the validation cohort, the ISGC score demonstrated good predictive performance for treatment response to NACT. Moreover, high ISGC indicated better long-term survival in patients with advanced GC. Furthermore, tumor-infiltrated T cells (CD3+ and CD8+) and CD11c+ macrophages were significantly increased in the response group, while CD163+ macrophages and FOXP3+ Treg cells were decreased after NACT. However, opposite results were exhibited in the nonresponse group. Finally, we found that the percentage of programmed cell death ligand 1 (PD-L1)-positive tumors was 31% (32/104) pre-NACT and 49% (51/104) post-NACT, and almost all patients with elevated PD-L1 were in the NACT response group. The ISGC model accurately predicted NACT efficacy and classified patients with GC into different survival groups. NACT regulates the TIME in GC, which may provide strategies for personalized immunotherapy.

Principles of risk assessment in colon cancer: immunity is key

In clinical practice, the administration of adjuvant chemotherapy (ACT) following tumor surgical resection raises a critical dilemma for stage II colon cancer (CC) patients. The prognostic features used to identify high-risk CC patients rely on the pathological assessment of tumor cells. Currently, these factors are considered for stratifying patients who may benefit from ACT at early CC stages. However, the extent to which these factors predict clinical outcomes (i.e. recurrence, survival) remains highly controversial, also uncertainty persists regarding patients' response to treatment, necessitating further investigation. Therefore, an imperious need is to explore novel biomarkers that can reliably stratify patients at risk, to optimize adjuvant treatment decisions. Recently, we evaluated the prognostic and predictive value of Immunoscore (IS), an immune digital-pathology assay, in stage II CC patients. IS emerged as the sole significant parameter for predicting disease-free survival (DFS) in high-risk patients. Moreover, IS effectively stratified patients who would benefit most from ACT based on their risk of recurrence, thus predicting their outcomes. Notably, our findings revealed that digital IS outperformed the visual quantitative assessment of the immune response conducted by expert pathologists. The latest edition of the WHO classification for digestive tumor has introduced the evaluation of the immune response, as assessed by IS, as desirable and essential diagnostic criterion. This supports the revision of current cancer guidelines and strongly recommends the implementation of IS into clinical practice as a patient stratification tool, to guide CC treatment decisions. This approach may provide appropriate personalized therapeutic decisions that could critically impact early-stage CC patient care.

Digital Pathology for Better Clinical Practice

(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution whole-slide images (WSI) of tissue specimens in a digital format. By integrating cutting-edge imaging technology with advanced software, DP promises to enhance clinical practice in numerous ways. DP not only improves quality assurance and standardization but also allows remote collaboration among experts for a more accurate diagnosis. Artificial intelligence (AI) in pathology significantly improves cancer diagnosis, classification, and prognosis by automating various tasks. It also enhances the spatial analysis of tumor microenvironment (TME) and enables the discovery of new biomarkers, advancing their translation for therapeutic applications. (3) Results: The AI-driven immune assays, Immunoscore (IS) and Immunoscore-Immune Checkpoint (IS-IC), have emerged as powerful tools for improving cancer diagnosis, prognosis, and treatment selection by assessing the tumor immune contexture in cancer patients. Digital IS quantitative assessment performed on hematoxylin-eosin (H&E) and CD3+/CD8+ stained slides from colon cancer patients has proven to be more reproducible, concordant, and reliable than expert pathologists' evaluation of immune response. Outperforming traditional staging systems, IS demonstrated robust potential to enhance treatment efficiency in clinical practice, ultimately advancing cancer patient care. Certainly, addressing the challenges DP has encountered is essential to ensure its successful integration into clinical guidelines and its implementation into clinical use. (4) Conclusion: The ongoing progress in DP holds the potential to revolutionize pathology practices, emphasizing the need to incorporate powerful AI technologies, including IS, into clinical settings to enhance personalized cancer therapy.

Spatial Immunephenotypes of Distant Metastases but not Matched Primary Urothelial Carcinomas Predict Response to Immune Checkpoint Inhibition

BACKGROUND

The value of programmed cell death ligand-1 (PD-L1) to predict durable responses to immune checkpoint inhibitors (ICIs) in metastatic urothelial carcinoma (mUC) is inconsistent. We hypothesize that the use of archived primary tumor material (PRIM) for PD-L1 testing in clinical trials not properly reflecting the metastatic disease status (MET) contributes to this clinical issue.

OBJECTIVE

To analyze the predictive and prognostic value of PD-L1, spatial immunephenotypes, and major histocompatibility complex class I (MHC-I) determined in patient-matched PRIM/MET.

DESIGN, SETTING, AND PARTICIPANTS

PD-L1, spatial immunephenotypes, and MHC-I were examined in 154 mUC patients with at least one available pretreatment MET (138 patient-matched PRIM/MET pairs).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

PD-L1, spatial immunephenotype, and MHC-I status of (patient-matched PRIM and) pretreatment MET were correlated with chemotherapy and ICI response and outcomes.

RESULTS AND LIMITATIONS

Discordance rates in patient-matched PRIM/MET were 25/30%, 36%, and 49% for PD-L1 (CPS10/IC5%), immunephenotypes, and MHC-I (loss vs preserved), respectively. Correlations with chemotherapy and ICI responses were observed for immunephenotypes and MHC-I status determined in MET (not for PD-L1 alone), but not in PRIM. In case of ICIs, patients with cytotoxic tumor immune microenvironment (TIME) showed durable responses with disease control rates of 90% and a hazard ratio for disease progression/death of 0.05 (95% confidence interval: 0.01-0.65) versus patients with immunedepleted MET (disease control rate 29%). MET MHC-I status added an incremental value to predict durable ICI responses. Limitations include the partly retrospective design and the lack of MET multisampling on individual patient level.

CONCLUSIONS

The TIME is subject to substantial dynamics during metastatic evolution. MET immunephenotypes and MHC-I statuses show promising potential to predict chemotherapy and durable ICI responses, while the PRIM TIME does not. Thus, future clinical trials should rather rely on pretreatment MET biopsies reflecting the current immunological disease state than on PRIM.

PATIENT SUMMARY

Prediction of chemotherapy and responses to immune checkpoint inhibitors might be possible using representative pretreatment metastatic biopsies.

Predicting Complete Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer

Muscle-invasive bladder cancer is a life-threatening disease best managed with multimodal therapy. Neoadjuvant chemotherapy prior to cystectomy significantly improves survival with the greatest benefit noted in patients with a complete pathologic response noted at cystectomy. While radical cystectomy is currently an important part of the treatment plan, surgical morbidity remains high. Accurate prediction of complete responses to chemotherapy would enable avoiding the morbidity of radical cystectomy. Multiple clinical, pathologic, molecular, and radiographic predictors have been evaluated. Clinical and standard pathologic findings have not been found to be accurate predictors of complete response. To date, tumor genomic findings have been the most promising and have led to multiple clinical trials to evaluate if bladder preservation is possible in select patients. Radiomics has shown initial promise with larger validation series needed. These predictors can be further characterized as treatment specific and non-treatment specific. With the potential changing landscape of neoadjuvant therapy prior to radical cystectomy and the limitations of individual predictors of a complete response, a panel of several biomarkers may enhance patient selection for bladder preservation. The aim of this review is to summarize predictors of complete response to neoadjuvant chemotherapy.

Modified immunoscore improves the prediction of progression-free survival in patients with non-muscle-invasive bladder cancer: A digital pathology study

Tumour-infiltrating lymphocytes (TIL), known to be of prognostic value in various solid tumours, have been in the focus of research in the last years. TIL are often quantified via IMMUNOSCORE ® (IS), a scoring system based on TIL cell densities. Recent studies were able to replicate these findings for muscle-invasive bladder cancer (MIBC), however data regarding non-muscle-invasive bladder cancer (NMIBC) are scarce. This study aimed to evaluate the value of a modified Immunoscore (mIS) as a predictive marker for NMIBC prognosis using tissue-micro-arrays (TMAs). We analysed two TMAs containing 316 samples from 158 patients with NMIBC, stained for CD3, CD8, CD45RO and FOXP3. Stained TIL were captured by digital pathology, cumulated, averaged, and reported as density (stained cells per mm²). The mIS was then constructed based on density of all four immune-cell types. Clinical, pathological and follow-up data were collected retrospectively. Univariable and multivariable cox regression analysis was performed to assess the potential value of mIS as a predictor for progression free survival (PFS) and recurrence-free-survival (RFS). Patients within "European Organisation for Research and Treatment of Cancer" (EORTC) risk groups were further substratified in high mIS and low mIS subgroups. Finally log-rank test was used to compare the different survival curves. The median age in our cohort was 68 years (Interquartile Range (IQR): 60 - 76), and 117 (74%) patients were male. A total of 26 patients (16.5%) were classified as EORTC low risk, 45 (28.5%) as intermediate risk and 87 (55.1%) as high risk. Patients in the EORTC high risk group with low mIS showed a shorter PFS in comparison to high mIS (HR 2.9, CI 0.79 - 11.0, p=0.082). In contrast, no predictive potential regarding PFS was observed in intermediate or low risk groups. Furthermore, mIS was not able to predict RFS in any EORTC risk group. mIS could be utilized to predict prognosis more accurately in high-risk patients with NMIBC by identifying those with higher or lower risk of progression. Therefore, mIS could be used to allocate these highrisk patients to more streamlined follow-up or more aggressive treatment strategies.

Molecular Subtypes as a Basis for Stratified Use of Neoadjuvant Chemotherapy for Muscle-Invasive Bladder Cancer-A Narrative Review

There are no established biomarkers to guide patient selection for neoadjuvant chemotherapy prior to radical cystectomy for muscle-invasive bladder cancer. Recent studies suggest that molecular subtype classification holds promise for predicting chemotherapy response and/or survival benefit in this setting. Here, we summarize and discuss the scientific literature examining transcriptomic or panel-based molecular subtyping applied to neoadjuvant chemotherapy-treated patient cohorts. We find that there is not sufficient evidence to conclude that the basal subtype of muscle-invasive bladder cancer responds well to chemotherapy, since only a minority of studies support this conclusion. More evidence indicates that luminal-like subtypes may have the most improved outcomes after neoadjuvant chemotherapy. There are also conflicting data concerning the association between biopsy stromal content and response. Subtypes indicative of high stromal infiltration responded well in some studies and poorly in others. Uncertainties when interpreting the current literature include a lack of reporting both response and survival outcomes and the inherent risk of bias in retrospective study designs. Taken together, available studies suggest a role for molecular subtyping in stratifying patients for receiving neoadjuvant chemotherapy. The precise classification system that best captures such a predictive effect, and the exact subtypes for which other treatment options are more beneficial remains to be established, preferably in prospective studies.

Immune Score Predicts Outcomes of Gastric Cancer Patients Treated with Adjuvant Chemoradiotherapy

Background

Substantial evidence has demonstrated that tumor-infiltrating lymphocytes (TILs) are correlated with patient prognosis. The TIL-based immune score (IS) affects prognosis in various cancers, but its prognostic impact in gastric cancer (GC) patients treated with adjuvant chemoradiotherapy remains unclear.

Methods

A total of 101 GC patients who received chemoradiotherapy after gastrectomy were retrospectively analyzed in this study. Immunohistochemistry staining for CD3+ and CD8+ T-cell counts in both tumor center (CT) and invasive margin (IM) regions was built into the IS. Patients were then divided into three groups based on their differential IS levels. The correlation between IS and clinical parameters was analyzed. The prognostic impact of IS and clinical parameters was evaluated using Kaplan-Meier analysis and Cox proportional hazard regression analysis. Receiver operating characteristic (ROC) curves were plotted to compare the area under the curve (AUC) of IS with other clinical parameters. Nomograms for disease-free survival (DFS) and overall survival (OS) prediction were constructed based on the identified parameters.

Results

Finally, 20 (19.8%), 57 (56.4%), and 24 (23.8%) GC patients were identified with low, intermediate, and high IS levels, respectively. GC patients with higher IS levels exhibited better DFS (p < 0.001) and OS (p < 0.001). IS was an independent prognostic factor for both DFS (p < 0.001) and OS (p < 0.001) in multivariate analysis. IS presented a better predictive ability than the traditional pathological tumor-node-metastasis (pTNM) staging system (AUC: 0.801 vs. 0.677 and 0.800 vs. 0.660, respectively) with respect to both DFS and OS. The C-index of the nomograms for DFS and OS prediction was 0.737 and 0.774, respectively.

Conclusions

IS is a strong predictive factor for both DFS and OS in GC patients treated with adjuvant chemoradiotherapy, which may complement the traditional pTNM staging system.

Cancer Immunotherapy with Immune Checkpoint Inhibitors-Biomarkers of Response and Toxicity; Current Limitations and Future Promise

Immune checkpoint inhibitors are monoclonal antibodies that are used to treat over one in three cancer patients. While they have changed the natural history of disease, prolonging life and preserving quality of life, they are highly active in less than 40% of patients, even in the most responsive malignancies such as melanoma, and cause significant autoimmune side effects. Licenced biomarkers include tumour Programmed Death Ligand 1 expression by immunohistochemistry, microsatellite instability, and tumour mutational burden, none of which are particularly sensitive or specific. Emerging tumour and immune tissue biomarkers such as novel immunohistochemistry scores, tumour, stromal and immune cell gene expression profiling, and liquid biomarkers such as systemic inflammatory markers, kynurenine/tryptophan ratio, circulating immune cells, cytokines and DNA are discussed in this review. We also examine the influence of the faecal microbiome on treatment outcome and its use as a biomarker of response and toxicity.

Avelumab maintenance in advanced urothelial carcinoma: biomarker analysis of the phase 3 JAVELIN Bladder 100 trial

In a recent phase 3 randomized trial of 700 patients with advanced urothelial cancer (JAVELIN Bladder 100; NCT02603432 ), avelumab/best supportive care (BSC) significantly prolonged overall survival relative to BSC alone as maintenance therapy after first-line chemotherapy. Exploratory biomarker analyses were performed to identify biological pathways that might affect survival benefit. Tumor molecular profiling by immunohistochemistry, whole-exome sequencing and whole-transcriptome sequencing revealed that avelumab survival benefit was positively associated with PD-L1 expression by tumor cells, tumor mutational burden, APOBEC mutation signatures, expression of genes underlying innate and adaptive immune activity and the number of alleles encoding high-affinity variants of activating Fcγ receptors. Pathways connected to tissue growth and angiogenesis might have been associated with reduced survival benefit. Individual biomarkers did not comprehensively identify patients who could benefit from therapy; however, multi-parameter models incorporating genomic alteration, immune responses and tumor growth showed promising predictive utility. These results characterize the complex biologic pathways underlying survival benefit from immune checkpoint inhibition in advanced urothelial cancer and suggest that multiple biomarkers might be needed to identify patients who would benefit from treatment.

Fundamental and Essential Knowledge for Pathologists Engaged in the Research and Practice of Immune Checkpoint Inhibitor-Based Cancer Immunotherapy

Extensive research over 100 years has demonstrated that tumors can be eliminated by the autologous immune system. Without doubt, immunotherapy is now a standard treatment along with surgery, chemotherapy, and radiotherapy; however, the field of cancer immunotherapy is continuing to develop. The current challenges for the use of immunotherapy are to enhance its clinical efficacy, reduce side effects, and develop predictive biomarkers. Given that histopathological analysis provides molecular and morphological information on humans in vivo, its importance will continue to grow. This review article outlines the basic knowledge that is essential for the research and daily practice of immune checkpoint inhibitor-based cancer immunotherapy from the perspective of histopathology.

Precision immunity: Immunoscore and neoadjuvant treatment in bladder cancer

This review details the clinical utility of Immunoscore, measuring the immune response to cancer within the tumor microenvironment, in bladder cancer. Immunoscore was recently introduced into ESMO Clinical Practice Guidelines for gastrointestinal cancer and into the WHO classification of the Digestive System Tumors. In muscle-invasive bladder cancer (MIBC), the standard-of-care treatment is neo-adjuvant chemotherapy and cystectomy. However, only 50% of the patients are still alive at 5 years. The degree of histologic response positively correlated with Immunoscore and patients at lower risk of relapse or death were associated with a high-Immunoscore. Immunoscore is also predicting response to neoadjuvant chemotherapy-based treatment in several indications. This paves the way for the use of Immunoscore in clinical practice not only in gastrointestinal tumors but also in bladder cancer, and beyond.