Tumor Microenvironment Analysis Identified Subtypes Associated With the Prognosis and the Tumor Response to Immunotherapy in Bladder Cancer

What's new about the tumor microenvironment of urothelial carcinoma?

Urothelial carcinoma is a significant global health concern that accounts for a substantial part of cancer diagnoses and deaths worldwide. The tumor microenvironment is a complex ecosystem composed of stromal cells, soluble factors, and altered extracellular matrix, that mutually interact in a highly immunomodulated environment, with a prominent role in tumor development, progression, and treatment resistance. This article reviews the current state of knowledge of the different cell populations that compose the tumor microenvironment of urothelial carcinoma, its main functions, and distinct interactions with other cellular and non-cellular components, molecular alterations and aberrant signaling pathways already identified. It also focuses on the clinical implications of these findings, and its potential to translate into improved quality of life and overall survival. Determining new targets or defining prognostic signatures for urothelial carcinoma is an ongoing challenge that could be accelerated through a deeper understanding of the tumor microenvironment.

Tumor microenvironment characterization in colorectal cancer to identify prognostic and immunotherapy genes signature

BACKGROUND

The tumor microenvironment (TME) plays a crucial role in tumorigenesis, progression, and therapeutic response in many cancers. This study aimed to comprehensively investigate the role of TME in colorectal cancer (CRC) by generating a TMEscore based on gene expression.

METHODS

The TME patterns of CRC datasets were investigated, and the TMEscores were calculated. An unsupervised clustering method was used to divide samples into clusters. The associations between TMEscores and clinical features, prognosis, immune score, gene mutations, and immune checkpoint inhibitors were analyzed. A TME signature was constructed using the TMEscore-related genes. The results were validated using external and clinical cohorts.

RESULTS

The TME pattern landscape was for CRC was examined using 960 samples, and then the TMEscore pattern of CRC datasets was evaluated. Two TMEscore clusters were identified, and the high TMEscore cluster was associated with early-stage CRC and better prognosis in patients with CRC when compared with the low TMEscore clusters. The high TMEscore cluster indicated elevated tumor cell scores and tumor gene mutation burden, and decreased tumor purity, when compared with the low TMEscore cluster. Patients with high TMEscore were more likely to respond to immune checkpoint therapy than those with low TMEscore. A TME signature was constructed using the TMEscore-related genes superimposing the results of two machine learning methods (LASSO and XGBoost algorithms), and a TMEscore-related four-gene signature was established, which had a high predictive value for discriminating patients from different TMEscore clusters. The prognostic value of the TMEscore was validated in two independent cohorts, and the expression of TME signature genes was verified in four external cohorts and clinical samples.

CONCLUSION

Our study provides a comprehensive description of TME characteristics in CRC and demonstrates that the TMEscore is a reliable prognostic biomarker and predictive indicator for patients with CRC undergoing immunotherapy.

Immune-related gene risk score predicting the effect of immunotherapy and prognosis in bladder cancer patients

Background: Immune checkpoint inhibitor therapy has changed the treatment model of metastatic bladder cancer. However, only approximately 20% of patients benefit from this therapy, and robust biomarkers to predict the effect of immunotherapy are still lacking. In this study, we aimed to investigate whether immune-related genes could be indicators for the prognosis of bladder cancer patients and the effect of immunotherapy.

Methods: Based on bladder cancer dataset from the Cancer Genome Atlas (TCGA) and GSE48075, 22 immune microenvironment-related cells were identified by CIBERSORT. After performing a series of bioinformatic and machine learning approaches, we identified distinct tumor microenvironment clusters and three bladder cancer specific immune-related genes (EGFR, OAS1 and MST1R). Then, we constructed immune-related gene risk score (IRGRS) by using the Cox regression method and validated it with the IMvigor210 dataset.

Results: IRGRS-high patients had a worse overall survival than IRGRS-low patients, which was consistent with the result in the IMvigor210 dataset. Comprehensive analysis shows that patients with high IRGRS scores are mainly enriched in basal/squamous type (Ba/Sq), and tumor metabolism-related pathways are more Active, with higher TP53 and RB1 gene mutation rates, lower CD4+/CD8+ T cell infiltration, higher M0 macrophage infiltration, and lower immunotherapy efficacy. In contrast, Patients with low IRGRS scores are mainly enriched in the luminal papillary type (LumP), which is associated with the activation of IL-17 and TNF signaling pathways, higher mutation rates of FGFR3 and CDKN1A genes, higher CD4+/CD8+ T cell infiltration content, and The level of M0 macrophage infiltration was relatively low, and the immunotherapy was more probably effective.

Conclusion: Our study constructed an IRGRS for bladder cancer and clarified the immune and molecular characteristics of IRGRS-defined subgroups of bladder cancer to investigate the association between IRGRS and its potential implications for prognosis and immunotherapy.

Methionine enkephalin inhibited cervical carcinoma via apoptosis promotion and reduction of myeloid derived suppressor cell infiltrated in tumor

Immunotherapy for cervical carcinoma is becoming increasingly important recently. In these studies methionine enkephalin (menk) is shown to inhibit cervical tumor cell proliferation in vitro in association with an increase in the expression of apoptosis markers and mediators, including an increase in fas, caspase 8, and caspase 3 expression and intrinsic expression of the signaling pathway mediator bax. In vivo, tumor growth was restrained in mice xenotransplant model with typical pathological features of apoptosis. Furthermore, myeloid derived suppressor cells (MDSCs) had a significant decrease in circulation and in tumor site. In brief, these findings showed menk could inhibit tumor growth in vitro and in vivo, providing direction of further research and clinical application prospect.

Quantification of ferroptosis pattern in bladder carcinoma and its significance on immunotherapy

The role of ferroptosis in tumor development and therapy has been previously proved. Nonetheless, its potential role in tumor microenvironment (TME) and immunotherapy for bladder carcinoma remains unclear. Based on 38 ferroptosis-related genes, the characteristic of ferroptosis patterns and interactions with immune cell-infiltrating features in 2043 bladder cancer samples were systematically investigated. We further proposed the FerrScore to quantify the ferroptosis patterns for each patient. As results, three diverse ferroptosis patterns with distinct tumor-infiltrating immune cell features were established. By determination of ferroptosis patterns of each patient, we found that high FerrScore was related to lower proportion of luminal-papillary molecular subtype, more frequent TP53 mutations, activation of immunity and stroma, and lower 5-year survival. High FerrScore also seemed to be associated with decreased neoantigen load, tumor mutational burden and poorer response to anti-PD-L1/1 therapy. External verification in two immunotherapy cohorts showed FerrScore was an independent and effective prognostic factor for therapeutic effect and survival outcome. Overall, the present study indicated the ferroptosis strongly is closely correlated with TME diversity. Evaluation of the ferroptosis patterns may strengthen the cognition of TME immune cell infiltrations and guide more individualized immunotherapeutic strategies in bladder carcinoma.

Three Prognostic Biomarkers Correlate with Immune Checkpoint Blockade Response in Bladder Urothelial Carcinoma

Aim

We aim to develop a signature that could accurately predict prognosis and evaluate the response to immune checkpoint blockade (ICB) in bladder urothelial carcinoma (BLCA).

Methods

Based on comprehensive analysis of public database, we identified prognosis-related hub genes and investigated their predictive values for the ICB response in BLCA.

Results

Among 69 common DEGs, three genes (AURKA, BIRC5, and CKS1B) were associated with poor prognosis, and which were related to histological subtypes, TP53 mutation status, and the C2 (IFN-gamma dominant) subtype. Three genes and their related risk model can effectively predict the response of immunotherapy. Their related drugs were identified through analysis of drug bank database.

Conclusions

Three genes could predict prognosis and evaluate the response to ICB in BLCA.

Comprehensive Exploration of Tumor Microenvironment Modulation Based on the ESTIMATE Algorithm in Bladder Urothelial Carcinoma Microenvironment

Recently, the tumor microenvironment (TME) has been reported to be closely related to the tumor initiation, progression, and prognosis. Bladder urothelial carcinoma (BLCA), one of the most common subtypes of bladder cancer worldwide, has been associated with increased morbidity and mortality in the past decade. However, whether the TME status of BLCA contributes to the prediction of BLCA prognosis still remains uncertain. In this study, the ESTIMATE algorithms were used to estimate the division of immune and stromal components in 406 BLCA samples downloaded from The Cancer Genome Atlas database (TCGA). Based on the comparison between ESTIMATE scores, the differentially expressed genes (DEGs) were selected. Using the univariate Cox regression analysis, prognosis-related DEGs were further identified (p < 0.05). The LASSO regression analysis was then used to screen 11 genes that were highly related to the TME of BLCA to generate a novel prognostic gene signature. The following survival analyses showed that this signature could effectively predict the prognosis of BLCA. The clinical value of this signature was further verified in an external cohort obtained from the First Affiliated Hospital of Wenzhou Medical University (n = 120). Based on the stage-correlation analysis and differential expression analysis, IGF1 and MMP9 were identified as the hub genes in the signature. Additionally, using CIBERSORT algorithms, we found that both IGF1 and MMP9 were significantly associated with immune infiltration. Collectively, a novel TME-related prognostic signature contributes to accurately predict the prognosis of BLCA.

Multi-Omics Analysis of Novel Signature for Immunotherapy Response and Tumor Microenvironment Regulation Patterns in Urothelial Cancer

The tumor microenvironment (TME) is mainly composed of tumor cells, tumor-infiltrating immune cells, and stromal components. It plays an essential role in the prognosis and therapeutic response of patients. Nonetheless, the TME landscape of urothelial cancer (UC) has not been fully elucidated. In this study, we systematically analyzed several UC cohorts, and three types of TME patterns (stromal-activation subtype, immune-enriched subtype and immune-suppressive subtype) were defined. The tumor microenvironment signature (TMSig) was constructed by modified Lasso penalized regression. Patients were stratified into high- and low-TMSig score groups. The low-score group had a better prognosis (p < 0.0001), higher M1 macrophage infiltration (p < 0.01), better response to immunotherapy (p < 0.05), and more similar molecular characteristics to the luminal (differentiated) subtype. The accuracy of the TMSig for predicting the immunotherapy response was also verified in three independent cohorts. We highlighted that the TMSig is an effective predictor of patient prognosis and immunotherapy response. Quantitative evaluation of a single sample is valuable for us to combine histopathological and molecular characteristics to comprehensively evaluate the status of the patient. Targeted macrophage treatment has great potential for the individualized precision therapy of UC patients.

Evaluating prognostic value and relevant gene signatures of tumor microenvironment characterization in esophageal carcinoma

Background

Tumor microenvironment (TME) cells are an important part of tumor tissues. There is increasing evidence that the TME plays a vital role in tumor prognosis, and is associated with patient survival in various kinds of malignances. To date, very little research has been conducted on how to effectively use TME to better evaluate the prognosis of patients with esophageal carcinoma (EC). The concept of a "TME score" was introduced to better distinguish the prognosis of patients.

Methods

We employed bioinformatic methods to investigate the TME infiltration patterns of 160 patients with EC from the Cancer Genome Atlas (TCGA) cohort. TME clusters were identified using k-means clustering methods with 1,000 resampling times. The significance of the survival difference among patients belonging to different TME clusters was assessed by the log-rank test and Kaplan-Meier survival curves. Correlations between immune cell types and survival were calculated by a Cox regression, and the Pearson correlation coefficient (PCC) was used to measure the relationship among different immune cell types. We classified patient into 2 subtypes based on the optimal breakpoint of TME score determined by R package maxstat.

Results

Two TME phenotypes were defined based on the immune cell type fractions, and patients with a high TME score phenotype had a better prognosis than those with a low TME score phenotype. Kaplan-Meier analysis for differentially expressed micro ribonucleic acids (RNAs) and messenger RNAs also showed that different TME score subtypes were significantly associated with the prognosis of EC. Just as tumor mutational burden can predict the efficacy of immunotherapy, the TME score can predict the efficacy of immune checkpoint inhibitors (ICIs). The genomic alterations of 2 TME score subtypes of EC further revealed that genomic instability is prevalent in TMEs, and patients with a low TME score subtype have a more unstable chromosome status than those with a high subtype.

Conclusions

Thus, TME score is an emerging prognostic biomarker for predicting the efficacy of ICIs.