A Novel TGF-β Risk Score Predicts the Clinical Outcomes and Tumour Microenvironment Phenotypes in Bladder Cancer

Predicting bladder cancer survival with high accuracy: insights from MAPK pathway-related genes

The mitogen-activated protein kinase (MAPK) pathway plays a critical role in tumor development and immunotherapy. Nevertheless, additional research is necessary to comprehend the relationship between the MAPK pathway and the prognosis of bladder cancer (BLCA), as well as its influence on the tumor immune microenvironment. To create prognostic models, we screened ten genes associated with the MAPK pathway using COX and least absolute shrinkage and selection operator (LASSO) regression analysis. These models were validated in the Genomic Data Commons (GEO) cohort and further examined for immune infiltration, somatic mutation, and drug sensitivity characteristics. Finally, the findings were validated using The Human Protein Atlas (HPA) database and through Quantitative Real-time PCR (qRT-PCR). Patients were classified into high-risk and low-risk groups based on the prognosis-related genes of the MAPK pathway. The high-risk group had poorer overall survival than the low-risk group and showed increased immune infiltration compared to the low-risk group. Additionally, the nomograms built using the risk scores and clinical factors exhibited high accuracy in predicting the survival of BLCA patients. The prognostic profiling of MAPK pathway-associated genes represents a potent clinical prediction tool, serving as the foundation for precise clinical treatment of BLCA.

Integrating novel immunotherapeutic approaches in organ-preserving therapies for bladder cancer

Bladder cancer (BC) is a prevalent malignancy with significant morbidity and mortality. Over the years, the landscape of bladder cancer treatment has witnessed notable advancements, particularly in the realm of immunotherapy. Immunotherapy has emerged as a promising adjunct to organ-preserving approaches, harnessing the immune system's potential to target and eliminate cancer cells. Organ preservation strategies offer viable alternatives to radical cystectomy to avoid the morbidities associated with radical surgery, as well as to respond to the needs of patients unfit for or who have refused surgery. However, the challenge lies in achieving durable disease control while minimizing treatment-related toxicities. This review highlights the significance of immune checkpoint inhibitors, such as anti-programmed cell death 1 (PD-1)/programmed cell death 1 ligand 1 (PD-L1) antibodies, in the treatment of localized bladder cancer. The clinical efficacy of immune checkpoint inhibitors, as both neoadjuvant and adjuvant therapies in combination with radiation or chemotherapy, is discussed. Moreover, the potential of immunotherapies beyond immune checkpoint inhibition, including combinations with bacillus Calmette-Guérin (BCG) instillations and/or investigational gene therapies, is explored. Furthermore, the predictive value of the tumour immune microenvironment for the success of these strategies is examined. Understanding the complex interplay between tumour immunity and therapeutic interventions can aid in identifying predictive biomarkers and tailoring personalized treatment strategies. Further research and clinical trials are warranted to optimize the use of immunotherapy in conjunction with organ-preserving therapies, potentially leading to enhanced patient outcomes and quality of life.

Predicting Survival Signature of Bladder Cancer Related to Cancer-Associated Fibroblast (CAF) Constructed by Intersecting Genes in TCGA and GEO

Bladder cancer was one of the most common carcinomas around the world. However, the mechanism of the disease still remained to be investigated. We expected to establish a prognostic survival model with 9 prognostic genes to predict overall survival (OS) in patients of bladder cancer. The gene expression data of bladder cancer were obtained from TCGA and GEO datasets. TCGA and GEO datasets were used for screening prognostic genes along with developing and validating a 9-gene prognostic survival model by method of weighted gene co-expression network analysis (WGCNA) and LASSO with Cox regression. The relative analysis of evaluate tumor burden mutation (TBM), GO, KEGG, chemotherapy drug and functional pathway were also performed based on CAF-related mRNAs. 151 Overlapping CAF-related genes were distinguished after intersecting differentially expressed genes from 945 genes in TCGA and 491 genes in GEO dataset. 9 Prognostic genes (MSRB2, AGMAT, KLF6, DDAH2, GADD45B, SERPINE2, STMN3, TEAD2, and COMP) were used for construction of prognostic model after LASSO with Cox regression. Receiver operating characteristic (ROC) curves showed a good survival prediction by this model. Functional analysis indicated chemokine, cytokine, ECM interaction, oxidative stress and apoptosis were highly appeared. Potential drugs targeted different CAF-related genes like vemurafenib, irofulven, ghiotepa, and idarubicin were found as well. We constructed a novel 9 CAF-related mRNAs prognostic model and explored the gene expression and potential functional information of related genes, which might be worthy of clinical application. In addition, potential chemotherapy drugs could provide useful insights into the potential clinical treatment of bladder cancer.

A novel oxidative stress-related genes signature associated with clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma

Background

Oxidative stress plays a significant role in the tumorigenesis and progression of tumors. We aimed to develop a prognostic signature using oxidative stress-related genes (ORGs) to predict clinical outcome and provide light on the immunotherapy responses of clear cell renal cell carcinoma (ccRCC).

Methods

The information of ccRCC patients were collected from the TCGA and the E-MTAB-1980 datasets. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) were conducted to screen out overall survival (OS)-related genes. Then, an ORGs risk signature was built by multivariate Cox regression analyses. The performance of the risk signature was evaluated with Kaplan-Meier (K-M) survival. The ssGSEA and CIBERSORT algorithms were performed to evaluate immune infiltration status. Finally, immunotherapy responses was analyzed based on expression of several immune checkpoints.

Results

A prognostic 9-gene signature with ABCB1, AGER, E2F1, FOXM1, HADH, ISG15, KCNMA1, PLG, and TEK. The patients in the high risk group had apparently poor survival (TCGA: p < 0.001; E-MTAB-1980: p < 0.001). The AUC of the signature was 0.81 at 1 year, 0.76 at 3 years, and 0.78 at 5 years in the TCGA, respectively, and was 0.8 at 1 year, 0.82 at 3 years, and 0.83 at 5 years in the E-MTAB-1980, respectively. Independent prognostic analysis proved the stable clinical prognostic value of the signature (TCGA cohort: HR = 1.188, 95% CI =1.142-1.236, p < 0.001; E-MTAB-1980 cohort: HR =1.877, 95% CI= 1.377-2.588, p < 0.001). Clinical features correlation analysis proved that patients in the high risk group were more likely to have a larger range of clinical tumor progression. The ssGSEA and CIBERSORT analysis indicated that immune infiltration status were significantly different between two risk groups. Finally, we found that patients in the high risk group tended to respond more actively to immunotherapy.

Conclusion

We developed a robust prognostic signature based on ORGs, which may contribute to predict survival and guide personalize immunotherapy of individuals with ccRCC.

TGF-β based risk model to predict the prognosis and immune features in glioblastoma

Background

Transforming growth factor-β (TGF-β) is a multifunctional cytokine with an important role in tissue development and tumorigenesis. TGF-β can inhibit the function of many immune cells, prevent T cells from penetrating into the tumor center, so that the tumor cells escape from immune surveillance and lead to low sensitivity to immunotherapy. However, its potential roles in predicting clinical prognosis and tumor microenvironment (TME) immune features need to be deeply investigated in glioblastoma (GBM).

Methods

The TCGA-GBM dataset was obtained from the Cancer Genome Atlas, and the validation dataset was downloaded from Gene Expression Omnibus. Firstly, differentially expressed TGF-β genes (DEGs) were screened between GBM and normal samples. Then, univariate and multivariate Cox analyses were used to identify prognostic genes and develop the TGF-β risk model. Subsequently, the roles of TGF-β risk score in predicting clinical prognosis and immune characteristics were investigated.

Results

The TGF-β risk score signature with an independent prognostic value was successfully developed. The TGF-β risk score was positively correlated with the infiltration levels of tumor-infiltrating immune cells, and the activities of anticancer immunity steps. In addition, the TGF-β risk score was positively related to the expression of immune checkpoints. Besides, the high score indicated higher sensitivity to immune checkpoint inhibitors.

Conclusions

We first developed and validated a TGF-β risk signature that could predict the clinical prognosis and TME immune features for GBM. In addition, the TGF-β signature could guide a more personalized therapeutic approach for GBM.

CD204⁺ tumor-associated macrophages are associated with clinical outcome in canine pulmonary adenocarcinoma and transitional cell carcinoma

Tumor-associated macrophages are abundant infiltrating cells in the tumor microenvironment (TME). Macrophages can be classified into several types of subsets based on their immune responses. Among those subsets, M2 macrophages contribute to anti-inflammatory responses and create an immunosuppressive environment that promotes tumor cell proliferation. In a previous study, human cancer patients with high M2 macrophages showed a worse prognosis for many types of tumors. However, studies examining the relationship between M2 macrophages and clinical outcomes in canine tumors are limited. In the previous human and canine studies, CD204 has been used as the marker for detecting M2 macrophages. Then we evaluated CD204+ and total macrophages infiltration and its association with clinical outcomes in canine solid tumors. In this study, we examined dogs with oral malignant melanoma (OMM), pulmonary adenocarcinoma (PA), hepatocellular carcinoma (HCC), and transitional cell carcinoma (TCC). Compared to healthy tissues, CD204+ and total macrophages were increased in OMM, PA, and TCC, but not in HCC. High CD204+ macrophage levels were significantly associated with lung metastasis in TCC (P = 0.030). Kaplan-Meier analysis revealed that high CD204+ macrophage levels were associated with shorter overall survival (OS) in canine patients with PA (P = 0.012) and TCC (P = 0.0053). These results suggest that CD204+ macrophages contribute to tumor progression and could be a prognostic factor in dogs with PA and TCC.

Comprehensive landscape of TGFβ-related signature in osteosarcoma for predicting prognosis, immune characteristics, and therapeutic response

Osteosarcoma (OS) is a highly heterogeneous malignant bone tumor, and its tendency to metastasize leads to a poor prognosis. TGFβ is an important regulator in the tumor microenvironment and is closely associated with the progression of various types of cancer. However, the role of TGFβ-related genes in OS is still unclear. In this study, we identified 82 TGFβ DEGs based on RNA-seq data from the TARGET and GETx databases and classified OS patients into two TGFβ subtypes. The KM curve showed that the Cluster 2 patients had a substantially poorer prognosis than the Cluster 1 patients. Subsequently, a novel TGFβ prognostic signatures (MYC and BMP8B) were developed based on the results of univariate, LASSO, and multifactorial Cox analyses. These signatures showed robust and reliable predictive performance for the prognosis of OS in the training and validation cohorts. To predict the three-year and five-year survival rate of OS, a nomogram that integrated clinical features and risk scores was also developed. The GSEA analysis showed that the different subgroups analyzed had distinct functions, particularly, the low-risk group was associated with high immune activity and a high infiltration abundance of CD8 T cells. Moreover, our results indicated that low-risk cases had higher sensitivity to immunotherapy, while high-risk cases were more sensitive to sorafenib and axitinib. scRNA-Seq analysis further revealed that MYC and BMP8B were strongly expressed mainly in tumor stromal cells. Finally, in this study, we confirmed the expression of MYC and BMP8B by performing qPCR, WB, and IHC analyses. To conclude, we developed and validated a TGFβ-related signature to accurately predict the prognosis of OS. Our findings might contribute to personalized treatment and making better clinical decisions for OS patients.

KRT13-expressing epithelial cell population predicts better response to chemotherapy and immunotherapy in bladder cancer: Comprehensive evidences based on BCa database

Neoadjuvant chemotherapy (NAC) prior to surgery and immune checkpoint therapy (ICT) has revolutionized bladder cancer (BCa) treatment. Patients likely to benefit from these therapies need to be accurately stratified; however, this remains a major clinical challenge. In the present study, single-cell RNA sequencing was used to evaluate the predictive ability of an epithelial cell population highly expressing keratin 13 (KRT13) to assess therapeutic response in BCa. The presence of KRT13-enriched tumors indicated favorable outcomes after NAC and superior response to ICT in patients with BCa. Furthermore, KRT13 population characteristics appeared to be closely related to changes in the immune microenvironment in the vicinity of this cell population. We constructed a prognostic model using an artificial neural network based on the gene signatures in the KRT13 population; the model demonstrated strong robustness and superiority. Additionally, a user-friendly and open-access web application named BCa database was developed for researchers to study BCa by mining the connective map database.

Cancer-associated Fibroblasts in Bladder Cancer: Origin, Biology, and Therapeutic Opportunities

CONTEXT

Bladder cancer (BLCA) is a highly prevalent tumour and a health problem worldwide, especially among men. Recent work has highlighted the relevance of the tumour microenvironment (TME) in cancer biology with translational implications. Cancer-associated fibroblasts (CAFs) are a prominent, heterogeneous population of cells in the TME. CAFs have been associated with tumour development, progression, and poor prognosis in several neoplasms. However, their role in BLCA has not yet been exploited deeply.

OBJECTIVE

To review the role of CAFs in BLCA biology and provide an understanding of CAF origin, subtypes, markers, and phenotypic and functional characteristics to improve patient management.

EVIDENCE ACQUISITION

A PubMed search was performed to review manuscripts published using the terms "cancer associated fibroblast" and "bladder cancer" or "urothelial cancer". All abstracts were reviewed, and the full content of all relevant manuscripts was analysed. In addition, selected manuscripts on CAFs in other tumours were considered.

EVIDENCE SYNTHESIS

CAFs have been studied less extensively in BLCA than in other tumours. Thanks to new techniques, such as single-cell RNA-seq and spatial transcriptomics, it is now possible to accurately map and molecularly define the phenotype of fibroblasts in normal bladder and BLCA. Bulk transcriptomic analyses have revealed the existence of subtypes among both non-muscle-invasive and muscle-invasive BLCA; these subtypes display distinct features regarding their CAF content. We provide a higher-resolution map of the phenotypic diversity of CAFs in these tumour subtypes. Preclinical studies and recent promising clinical trials leverage on this knowledge through the combined targeting of CAFs or their effectors and the immune microenvironment.

CONCLUSIONS

Current knowledge of BLCA CAFs and the TME is being increasingly applied to improve BLCA therapy. There is a need to acquire a deeper understanding of CAF biology in BLCA.

PATIENT SUMMARY

Tumour cells are surrounded by nontumoural cells that contribute to the determination of the behaviour of cancers. Among them are cancer-associated fibroblasts. The "neighbourhoods" established through these cellular interactions can now be studied with much greater resolution. Understanding these features of tumours will contribute to the designing of more effective therapies, especially in relationship to bladder cancer immunotherapy.

BCAT2 Shapes a Noninflamed Tumor Microenvironment and Induces Resistance to Anti-PD-1/PD-L1 Immunotherapy by Negatively Regulating Proinflammatory Chemokines and Anticancer Immunity

To improve response rate of monotherapy of immune checkpoint blockade (ICB), it is necessary to find an emerging target in combination therapy. Through analyzing tumor microenvironment (TME)-related indicators, it is validated that BCAT2 shapes a noninflamed TME in bladder cancer. The outcomes of multiomics indicate that BCAT2 has an inhibitory effect on cytotoxic lymphocyte recruitment by restraining activities of proinflammatory cytokine/chemokine-related pathways and T-cell-chemotaxis pathway. Immunoassays reveal that secretion of CD8⁺ T-cell-related chemokines keeps a robust negative correlation with BCAT2, generating a decreasing tendency of CD8⁺ T cells around BCAT2⁺ tumor cells from far to near. Cotreatment of BCAT2 deficiency and anti-PD-1 antibody has a synergistic effect in vivo, implying the potential of BCAT2 in combination therapy. Moreover, the value of BCAT2 in predicting efficacy of immunotherapy is validated in multiple immunotherapy cohorts. Together, as a key molecule in TME, BCAT2 is an emerging target in combination with ICB and a biomarker of guiding precision therapy.

Mutual regulation between glycosylation and transforming growth factor-β isoforms signaling pathway

Transforming growth factor-beta (TGF-β) superfamily members orchestrate a wide breadth of biological processes. Through Sma and Mad (Smad)-related dependent or noncanonical pathways, TGF-β members involve in the occurrence and development of many diseases such as cancers, fibrosis, autoimmune diseases, cardiovascular diseases and brain diseases. Glycosylation is one kind of the most common posttranslational modifications on proteins or lipids. Abnormal protein glycosylation can lead to protein malfunction and biological process disorder, thereby causing serious diseases. Previously, researchers commonly make comprehensive systematic overviews on the roles of TGF-β signaling in a specific disease or biological process. In recent years, more and more evidences associate glycosylation modification with TGF-β signaling pathway, and we can no longer disengage and ignore the roles of glycosylation from TGF-β signaling to make investigation. In this review, we provide an overview of current findings involved in glycosylation within TGF-βs and theirs receptors, and the interaction effects between glycosylation and TGF-β subfamily signaling, concluding that there is an intricate mutual regulation between glycosylation and TGF-β signaling, hoping to present the glycosylation regulatory patterns that concealed in TGF-βs signaling pathways.

Development of a TGF-β signaling-related genes signature to predict clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma

Background

Transforming growth factor (TGF)-β signaling is strongly related to the development and progression of tumor. We aimed to construct a prognostic gene signature based on TGF-β signaling-related genes for predicting clinical prognosis and immunotherapy responses of patients with clear cell renal cell carcinoma (ccRCC).

Methods

The gene expression profiles and corresponding clinical information of ccRCC were collected from the TCGA and the ArrayExpress (E-MTAB-1980) databases. LASSO, univariate and multivariate Cox regression analyses were conducted to construct a prognostic signature in the TCGA cohort. The E-MTAB-1980 cohort were used for validation. Kaplan-Meier (K-M) survival and time-dependent receiver operating characteristic (ROC) were conducted to assess effectiveness and reliability of the signature. The differences in gene enrichments, immune cell infiltration, and expression of immune checkpoints in ccRCC patients showing different risks were investigated.

Results

We constructed a seven gene (PML, CDKN2B, COL1A2, CHRDL1, HPGD, CGN and TGFBR3) signature, which divided the ccRCC patients into high risk group and low risk group. The K-M analysis indicated that patients in the high risk group had a significantly shorter overall survival (OS) time than that in the low risk group in the TCGA (p < 0.001) and E-MTAB-1980 (p = 0.012). The AUC of the signature reached 0.77 at 1 year, 0.7 at 3 years, and 0.71 at 5 years in the TCGA, respectively, and reached 0.69 at 1 year, 0.72 at 3 years, and 0.75 at 5 years in the E-MTAB-1980, respectively. Further analyses confirmed the risk score as an independent prognostic factor for ccRCC (p < 0.001). The results of ssGSEA that immune cell infiltration degree and the scores of immune-related functions were significantly increased in the high risk group. The CIBERSORT analysis indicated that the abundance of immune cell were significantly different between two risk groups. Furthermore, The risk score was positively related to the expression of PD-1, CTLA4 and LAG3.These results indicated that patients in the high risk group benefit more from immunotherapy.

Conclusion

We constructed a novel TGF-β signaling-related genes signature that could serve as an promising independent factor for predicting clinical prognosis and immunotherapy responses in ccRCC patients.

An IFN-γ-related signature predicts prognosis and immunotherapy response in bladder cancer: Results from real-world cohorts

Bladder cancer (BLCA) is featured with high incidence and mortality. Whether the IFN-γ signaling could be used as an immunotherapy determinant for BLCA has not been fully confirmed. In this study, the transcriptome data and clinical information of BLCA samples were collected from The Cancer Genome Atlas (TCGA). Besides, four immunotherapy cohorts including IMvigor210 cohort, Gide cohort, Van Allen cohort, and Lauss cohort were collected. The Xiangya real-world cohort was used for independent validation. An IFN-γ-related signature was developed and validated in BLCA for predicting prognosis, mutation, tumor microenvironment status, and immunotherapy response. This is the first study focusing on the comprehensive evaluation of predictive values on the IFN-γ-related signature in BLCA. The potential clinical application of the IFN-γ-related signature was expected to be further validated with more prospective clinical cohorts.

Molecular vasculogenic mimicry-Related signatures predict clinical outcomes and therapeutic responses in bladder cancer: Results from real-world cohorts

Bladder cancer (BLCA) is a heterogeneous disease, and there are many classical molecular subtypes that reflect tumor immune microenvironment (TME) heterogeneity but their clinical utility is limited and correct individual treatment and prognosis cannot be predicted based on them. To find reliable and effective biomarkers and tools for predicting patients' clinical responses to several therapies, we developed a new systemic indicator of molecular vasculogenic mimicry (VM)-related genes mediated by molecular subtypes based on the Xiangya cohort and additional external BLCA cohorts using a random forest algorithm. A correlation was then done between the VM_Score and classical molecular subtypes, clinical outcomes, immunophenotypes, and treatment options for BLCA. With the VM_Score, it is possible to predict classical molecular subtypes, immunophenotypes, prognosis, and therapeutic potential of BLCA with high accuracy. The VM_Scores of high levels indicate a more anticancer immune response but a worse prognosis due to a more basal and inflammatory phenotype. The VM_Score was also found associated with low sensitivity to antiangiogenic and targeted therapies targeting the FGFR3, β-catenin, and PPAR-γ pathways but with high sensitivity to cancer immunotherapy, neoadjuvant chemotherapy, and radiotherapy. A number of aspects of BLCA biology were reflected in the VM_Score, providing new insights into precision medicine. Additionally, the VM_Score may be used as an indicator of pan-cancer immunotherapy response and prognosis.

Identification of molecular subtypes based on liquid-liquid phase separation and cross-talk with immunological phenotype in bladder cancer

Background

Mounting evidence has demonstrated that an imbalance in liquid-liquid phase separation (LLPS) can induce alteration in the spatiotemporal coordination of biomolecular condensates, which plays a role in carcinogenesis and cachexia. However, the role of LLPS in the occurrence and progression of bladder cancer (BLCA) remains to be elucidated. Identifying the role of LLPS in carcinogenesis may aid in cancer therapeutics.

Methods

A total of 1,351 BLCA samples from six cohorts were retrieved from publicly available databases like The Cancer Genome Atlas, Gene Expression Omnibus, and ArrayExpress. The samples were divided into three distinct clusters, and their multi-dimensional heterogeneities were explored. The LLPS patterns of all patients were determined based on the LLPS-related risk score (LLPSRS), and its multifaceted landscape was depicted and experimentally validated at the multi-omics level. Finally, a cytotoxicity-related and LLPSRS-based classifier was established to predict the patient's response to immune checkpoint blockade (ICB) treatment.

Results

Three LLPS-related subtypes were identified and validated. The differences in prognosis, tumor microenvironment (TME) features, cancer hallmarks, and certain signatures of the three LLPS-related subtypes were validated. LLPSRS was calculated, which could be used as a prognostic biomarker. A close correlation was observed between clinicopathological features, genomic variations, biological mechanisms, immune infiltration in TME, chemosensitivity, and LLPSRS. Furthermore, our classifier could effectively predict immunotherapy response in patients with BLCA.

Conclusions

Our study identified a novel categorization of BLCA patients based on LLPS. The LLPSRS could predict the prognosis of patients and aid in designing personalized medicine. Further, our binary classifier could effectively predict patients' sensitivity to immunotherapy.

Exhaust the exhausters: Targeting regulatory T cells in the tumor microenvironment

The concept of cancer immunotherapy has gained immense momentum over the recent years. The advancements in checkpoint blockade have led to a notable progress in treating a plethora of cancer types. However, these approaches also appear to have stalled due to factors such as individuals' genetic make-up, resistant tumor sub-types and immune related adverse events (irAE). While the major focus of immunotherapies has largely been alleviating the cell-intrinsic defects of CD8⁺ T cells in the tumor microenvironment (TME), amending the relationship between tumor specific CD4⁺ T cells and CD8⁺ T cells has started driving attention as well. A major roadblock to improve the cross-talk between CD4⁺ T cells and CD8⁺ T cells is the immune suppressive action of tumor infiltrating T regulatory (Treg) cells. Despite their indispensable in protecting tissues against autoimmune threats, Tregs have also been under scrutiny for helping tumors thrive. This review addresses how Tregs establish themselves at the TME and suppress anti-tumor immunity. Particularly, we delve into factors that promote Treg migration into tumor tissue and discuss the unique cellular and humoral composition of TME that aids survival, differentiation and function of intratumoral Tregs. Furthermore, we summarize the potential suppression mechanisms used by intratumoral Tregs and discuss ways to target those to ultimately guide new immunotherapies.

Integrated Machine Learning and Single-Sample Gene Set Enrichment Analysis Identifies a TGF-Beta Signaling Pathway Derived Score in Headneck Squamous Cell Carcinoma

Background

The TGF-β signaling pathway is clinically predictive of pan-cancer. Nevertheless, its clinical prognosis and regulation of immune microenvironment (TME) characteristics as well as the prediction of immunotherapy efficacy need to be further elucidated in head and neck squamous cell carcinoma.

Method

At first, we summarized TGF-β related genes from previous published articles, used ssGSEA to establish the TGF-β risk score. Considering the complexity of its clinical application, we improved it with the LASSO-COX algorithm to construct the model. In addition, we explored the predictive efficacy of TGF-β risk score in the observation of TME phenotype and immunotherapy effect. Finally, the potency of TGF-β risk score in adjusting precise treatment of HNSC was evaluated.

Results

We systematically established TGF-β risk score with multi-level predictive ability. TGF-β risk score was employed to predict the tumor microenvironment status, which was negatively associated with NK cells but positively related to macrophages and fibroblasts. It reveals that patients with high TGF-β risk score predict “cold” TME status. In addition, higher risk scores indicate higher sensitivity to immunotherapy.

Conclusion

We first construct and validate TGF-β characteristics that can predict immune microenvironment phenotypes and immunotherapeutic effect in multiple datasets. Noteworthy, TGF-β risk score is helpful for individualized precise treatment of patients with the head and neck squamous cell carcinoma.

Robust pyroptosis risk score guides the treatment options and predicts the prognosis of bladder carcinoma

Background

Bladder carcinoma (BLCA) is a heterogeneous disease that makes it difficult to achieve proper individual treatment and predict prognosis. This study aimed to develop a risk score from a new perspective of pyroptosis and guide accurate treatment and prognosis prediction for BLCA.

Methods

The TCGA-BLCA cohort data were downloaded from The Cancer Genome Atlas database. Two external validation cohorts were collected from the Gene Expression Omnibus. Another independent validation cohort (the Xiangya cohort) was recruited from our hospital. The least absolute shrinkage and selector operation (LASSO) algorithm and Cox regression models were used to establish the pyroptosis risk score. Thereafter, we correlated the pyroptosis risk score with prognosis, tumor microenvironment (TME) immune hallmarks, and multiple treatments, including anticancer immunotherapy, chemotherapy, radiotherapy, and targeted therapy.

Results

The pyroptosis risk score was an independent prognostic predictor of BLCA. We found that the activities of multiple steps of the anticancer immune response cycle, such as the release of cancer cell antigens, CD8 T cell recruitment, and NK cell recruitment, were significantly higher in the high-risk score group than in the low-risk score group. In addition, the infiltration levels of the corresponding tumor-infiltrating immune cells (TIICs), such as CD8 T cells and NK cells, were positively correlated with the pyroptosis risk score. Thus, BLCA with a high-risk score may be associated with inflamed phenotypes. Simultaneously, the expression of multiple immune checkpoints (such as PD-L1, CTLA-4, and PD-1) and enrichment scores of gene signatures positively correlated with immunotherapy response were positively correlated with the pyroptosis risk score. Therefore, patients with a high pyroptosis risk score may be more sensitive to immunotherapy. In addition, patients with high pyroptosis risk scores may be more sensitive to chemotherapeutic drugs, such as cisplatin, docetaxel, and paclitaxel. In addition, the pyroptosis risk score accurately predicted the molecular subtypes of BLCA, which were cross-validated in several independent systems.

Conclusions

This study developed and validated a robust pyroptosis risk score that can predict the clinical outcomes and TME immune phenotypes of BLCA. In summary, the pyroptosis risk score helps drive precision therapy in patients with BLCA.

The Upregulation of Caffeic Acid Phenethyl Ester on Growth Differentiation Factor 15 Inhibits Transforming Growth Factor β/Smad Signaling in Bladder Carcinoma Cells

Growth differentiation factor 15 (GDF15) is known as a TGFβ-like cytokine acting on the TGFβ receptor to modulate target genes. GDF15 is regarded as a tumor suppressor gene in the human bladder and the caffeic acid phenethyl ester (CAPE) induces GDF15 expression to inhibit the tumor growth in vitro and in vivo. However, the interactions among GDF15, CAPE, and TGFβ/Smads signaling in the human bladder carcinoma cells remain unexplored. Results revealed that TGFβ downregulated the expression of GDF15 via the activation of Smad 2/3 and Smad 1/5. Induction of GDF15 on its downstream genes, NDRG1 and maspin, is dependent on the TGFβ/Smad pathways. Moreover, TGFβ blocked the CAPE-inducing expressions of GDF15, maspin, and NDRG1. Pretreatment of TGF receptor kinase inhibitor not only blocked the activation of TGFβ but also attenuated the activation of GDF15 on the expressions of maspin and NDRG1. The CAPE treatment attenuated the activation of TGFβ on cell proliferation and invasion. Our findings indicate that TGFβ downregulated the expressions of GDF15, maspin, and NDRG1 via TGFβ/Smad signaling. Whereas, CAPE acts as an antagonist on TGFβ/Smad signaling to block the effect of TGFβ on the GDF15 expression and cell proliferation and invasion in bladder carcinoma cells.

GATA3 Predicts the Tumor Microenvironment Phenotypes and Molecular Subtypes for Bladder Carcinoma

Aims

GATA3 is a key player in antitumor immunology, and continuous studies show that it might be a key biomarker for bladder cancer (BLCA). Thus, we lucubrate the immunological role of GATA3 in BLCA.

Main Methods

We initially used pan-cancer analysis to analyze the expression pattern and immunological function of GATA3 with data gathered from the TCGA (The Cancer Genome Atlas). Then, in the BLCA tumor microenvironment (TME), we comprehensively associated GATA3 with immunomodulators, cancer immune cycles, tumor-infiltrating immune cells (TIICs), immune checkpoints, and T-cell inflamed scores(TIS). The role of GATA3 in predicting BLCA molecular subtypes and responsiveness to various treatment regimens was also investigated. We confirmed our findings in an external cohort and the Xiangya-Pingkuang cohort to guarantee the correctness of our study.

Key Findings

GATA3 was preferentially expressed in the TME of numerous malignancies, including BLCA. High GATA3 expression was adversely connected with immunological aspects such as immunomodulators, cancer immune cycles, TIICs, immune checkpoints, and TIS in the BLCA TME. In addition, high GATA3 was more likely to be a luminal subtype, which meant it was less susceptible to cancer immunotherapy and neoadjuvant chemotherapy but more sensitive to targeted treatments.

Significance

GATA3 may aid in the precision treatment for BLCA because it can accurately predict the clinical outcomes and the TME characteristics of BLCA.