A Robust Hypoxia Risk Score Predicts the Clinical Outcomes and Tumor Microenvironment Immune Characters in Bladder Cancer

Comprehensive analysis and prognostic assessment of senescence-associated genes in bladder cancer

BACKGROUND

The prevalence and mortality of bladder cancer (BLCA) present a significant medical challenge. While the function of senescence-related genes in tumor development is recognized, their prognostic significance in BLCA has not been thoroughly explored.

METHODS

BLCA transcriptome datasets were sourced from the TCGA and GEO repositories. Gene groupings were determined through differential gene expression and non-negative matrix factorization (NMF) methodologies. Key senescence-linked genes were isolated using singular and multivariate Cox regression analyses, combined with lasso regression. Validation was undertaken with GEO database information. Predictive models, or nomograms, were developed by merging risk metrics with clinical records, and their efficacy was gauged using ROC curve methodologies. The immune response's dependency on the risk metric was assessed through the immune phenomenon score (IPS). Additionally, we estimated IC50 metrics for potential chemotherapeutic agents.

RESULTS

Reviewing 406 neoplastic and 19 standard tissue specimens from the TCGA repository facilitated the bifurcation of subjects into two unique clusters (C1 and C2) according to senescence-related gene expression. After a stringent statistical evaluation, a set of ten pivotal genes was discerned and applied for risk stratification. Validity tests for the devised nomograms in forecasting 1, 3, and 5-year survival probabilities for BLCA patients were executed via ROC and calibration plots. IC50 estimations highlighted a heightened responsiveness in the low-risk category to agents like cisplatin, cyclopamine, and sorafenib.

CONCLUSIONS

In summation, our research emphasizes the prospective utility of risk assessments rooted in senescence-related gene signatures for enhancing BLCA clinical oversight.

Urinary IL-6 and IL-8 as predictive markers in bladder urothelial carcinoma: A pilot study

BACKGROUND

Cytokines are known to be a key a factor in numerous malignancies and to exert an important regulatory role in the tumor microenvironment. Interest has grown in understanding how cytokines modulate the tumor microenvironment and which cytokines may serve as markers of the tumor process; however, a complete picture of the cytokine landscape in bladder cancer remains unclear.

METHODS

Fresh urine specimens with sufficient volume were collected at random intervals. The urine concentrations of IL-8 (CXCL8), CCL18, and CXCL9 were determined using the standard commercially available enzyme immunoassay. The urine concentrations of IL-6 were determined using the high sensitivity enzyme immunoassay kit. Urinary cytokine concentrations were normalized with urinary creatinine concentrations.

RESULTS

Significantly elevated concentrations of IL-6 and IL-8 were detected in the urine from patients with urothelial carcinoma on follow-up compared to patients with benign follow-up. The presence of both IL-6 and IL-8 in the urine samples from the high grade urothelial carcinoma (HGUC) cohort revealed a clear discrimination when compared to samples from patients with benign follow-up. The presence of the combination of both IL-6 and IL-8 had a sensitivity of 90.0% and a specificity of 81.25%. Similar data were obtained when receiver operating characteristic analysis was performed on both IL-6 and IL-8 concentrations in the urine from patients with HGUC vs. the hematuria cohort.

CONCLUSIONS

The presence of IL-6 and IL-8 in urine specimens may have predictive value for urothelial carcinoma. However, a large longitudinal study is required to statistically eliminate confounding factors and support this theory.

NAD+ associated genes as potential biomarkers for predicting the prognosis of gastric cancer

Nicotinamide adenine dinucleotide (NAD+) plays an essential role in cellular metabolism, mitochondrial homeostasis, inflammation, and senescence. However, the role of NAD+-regulated genes, including coding and long non-coding genes in cancer development is poorly understood. We constructed a prediction model based on the expression level of NAD+ metabolism-related genes (NMRGs). Furthermore, we validated the expression of NMRGs in gastric cancer (GC) tissues and cell lines; additionally, β-nicotinamide mononucleotide (NMN), a precursor of NAD+, was used to treat the GC cell lines to analyze its effects on the expression level of NMRGs lncRNAs and cellular proliferation, cell cycle, apoptosis, and senescence-associated secretory phenotype (SASP). A total of 13 NMRGs-related lncRNAs were selected to construct prognostic risk signatures, and patients with high-risk scores had a poor prognosis. Some immune checkpoint genes were upregulated in the high-risk group. In addition, cell cycle, epigenetics, and senescence were significantly downregulated in the high-risk group. Notably, we found that the levels of immune cell infiltration, including CD8 T cells, CD4 naïve T cells, CD4 memory-activated T cells, B memory cells, and naïve B cells, were significantly associated with risk scores. Furthermore, the treatment of NMN showed increased proliferation of AGS and MKN45 cells. In addition, the expression of SASP factors (IL6, IL8, IL10, TGF-β, and TNF-α) was significantly decreased after NMN treatment. We conclude that the lncRNAs associated with NAD+ metabolism can potentially be used as biomarkers for predicting clinical outcomes of GC patients.

BLCA prognostic model creation and validation based on immune gene-metabolic gene combination

BACKGROUND

Bladder cancer (BLCA) is a prevalent urinary system malignancy. Understanding the interplay of immunological and metabolic genes in BLCA is crucial for prognosis and treatment.

METHODS

Immune/metabolism genes were extracted, their expression profiles analyzed. NMF clustering found prognostic genes. Immunocyte infiltration and tumor microenvironment were examined. Risk prognostic signature using Cox/LASSO methods was developed. Immunological Microenvironment and functional enrichment analysis explored. Immunotherapy response and somatic mutations evaluated. RT-qPCR validated gene expression.

RESULTS

We investigated these genes in 614 BLCA samples, identifying relevant prognostic genes. We developed a predictive feature and signature comprising 7 genes (POLE2, AHNAK, SHMT2, NR2F1, TFRC, OAS1, CHKB). This immune and metabolism-related gene (IMRG) signature showed superior predictive performance across multiple datasets and was independent of clinical indicators. Immunotherapy response and immune cell infiltration correlated with the risk score. Functional enrichment analysis revealed distinct biological pathways between low- and high-risk groups. The signature demonstrated higher prediction accuracy than other signatures. qRT-PCR confirmed differential gene expression and immunotherapy response.

CONCLUSIONS

The model in our work is a novel assessment tool to measure immunotherapy's effectiveness and anticipate BLCA patients' prognosis, offering new avenues for immunological biomarkers and targeted treatments.

Oct4 and Hypoxia Dual-Regulated Oncolytic Adenovirus Armed with shRNA-Targeting Dendritic Cell Immunoreceptor Exerts Potent Antitumor Activity against Bladder Cancer

Immunotherapy has emerged as a promising modality for cancer treatment. Dendritic cell immunoreceptor (DCIR), a C-type lectin receptor, is expressed mainly by dendritic cells (DCs) and mediates inhibitory intracellular signaling. Inhibition of DCIR activation may enhance antitumor activity. DCIR is encoded by CLEC4A in humans and by Clec4a2 in mice. Gene gun-mediated delivery of short hairpin RNA (shRNA) targeting Clec4a2 into mice bearing bladder tumors reduces DCIR expression in DCs, inhibiting tumor growth and inducing CD8+ T cell immune responses. Various oncolytic adenoviruses have been developed in clinical trials. Previously, we have developed Ad.LCY, an oncolytic adenovirus regulated by Oct4 and hypoxia, and demonstrated its antitumor efficacy. Here, we generated a Clec4a2 shRNA-expressing oncolytic adenovirus derived from Ad.LCY, designated Ad.shDCIR, aimed at inducing more robust antitumor immune responses. Our results show that treatment with Ad.shDCIR reduced Clec4a expression in DCs in cell culture. Furthermore, Ad.shDCIR exerted cytolytic effects solely on MBT-2 bladder cancer cells but not on normal NIH 3T3 mouse fibroblasts, confirming the tumor selectivity of Ad.shDCIR. Compared to Ad.LCY, Ad.shDCIR induced higher cytotoxic T lymphocyte (CTL) activity in MBT-2 tumor-bearing immunocompetent mice. In addition, Ad.shDCIR and Ad.LCY exhibited similar antitumor effects on inhibiting tumor growth. Notably, Ad.shDCIR was superior to Ad.LCY in prolonging the survival of tumor-bearing mice. In conclusion, Ad.shDCIR may be further explored as a combination therapy of virotherapy and immunotherapy for bladder cancer and likely other types of cancer.

Therapeutic potential of vasculogenic mimicry in urological tumors

Angiogenesis is an essential process in the growth and metastasis of cancer cells, which can be hampered by an anti-angiogenesis mechanism, thereby delaying the progression of tumors. However, the benefit of this treatment modality could be restricted, as most patients tend to develop acquired resistance during treatment. Vasculogenic mimicry (VM) is regarded as a critical alternative mechanism of tumor angiogenesis, where studies have demonstrated that patients with tumors supplemented with VM generally have a shorter survival period and a poorer prognosis. Inhibiting VM may be an effective therapeutic strategy to prevent cancer progression, which could prove helpful in impeding the limitations of lone use of anti-angiogenic therapy when performed concurrently with other anti-tumor therapies. This review summarizes the mechanism of VM signaling pathways in urological tumors, i.e., prostate cancer, clear cell renal cell carcinoma, and bladder cancer. Furthermore, it also summarizes the potential of VM as a therapeutic strategy for urological tumors.

Development and validation of prognostic index based on purine metabolism genes in patients with bladder cancer

Background

Bladder cancer (BLCA) is a prevalent malignancy affecting the urinary system and is associated with significant morbidity and mortality worldwide. Dysregulation of tumor metabolic pathways is closely linked to the initiation and proliferation of BLCA. Tumor cells exhibit distinct metabolic activities compared to normal cells, and the purine metabolism pathway, responsible for providing essential components for DNA and RNA synthesis, is believed to play a crucial role. However, the precise involvement of Purine Metabolism Genes (PMGs) in the defense mechanism against BLCA remains elusive.

Methods

The integration of BLCA samples from the TCGA and GEO datasets facilitated the quantitative evaluation of PMGs, offering potential insights into their predictive capabilities. Leveraging the wealth of information encompassing mRNAsi, gene mutations, CNV, TMB, and clinical features within these datasets further enriched the analysis, augmenting its robustness and reliability. Through the utilization of Lasso regression, a prediction model was developed, enabling accurate prognostic assessments within the context of BLCA. Additionally, co-expression analysis shed light on the complex relationship between gene expression patterns and PMGs, unraveling their functional relevance and potential implications in BLCA.

Results

PMGs exhibited increased expression levels in the high-risk cohort of BLCA patients, even in the absence of other clinical indicators, suggesting their potential as prognostic markers. GSEA revealed enrichment of immunological and tumor-related pathways specifically in the high-risk group. Furthermore, notable differences were observed in immune function and m6a gene expression between the low- and high-risk groups. Several genes, including CLDN6, CES1, SOST, SPRR2A, MYBPH, CGB5, and KRT1, were found to potentially participate in the oncogenic processes underlying BLCA. Additionally, CRTAC1 was identified as potential tumor suppressor genes. Significant discrepancies in immunological function and m6a gene expression were observed between the two risk groups, further highlighting the distinct molecular characteristics associated with different prognostic outcomes. Notably, strong correlations were observed among the prognostic model, CNVs, SNPs, and drug sensitivity profiles.

Conclusion

PMGs have been implicated in the etiology and progression of bladder cancer (BLCA). Prognostic models corresponding to this malignancy aid in the accurate prediction of patient outcomes. Notably, exploring the potential therapeutic targets within the tumor microenvironment (TME) such as PMGs and immune cell infiltration holds promise for effective BLCA management, albeit necessitating further research. Moreover, the identification of a gene signature associated with purine Metabolism presents a credible and alternative approach for predicting BLCA, signifying a burgeoning avenue for targeted therapeutic investigations in the field of BLCA.

ACSM6 overexpression indicates a non-inflammatory tumor microenvironment and predicts treatment response in bladder cancer: results from multiple real-world cohorts

Background: ACSMs play critical roles in lipid metabolism; however, their immunological function within the tumor microenvironment (TME) remains unclear, especially that of ACSM6. In this study, we investigate the latent effect of ACSM6 on bladder cancer (BLCA). Methods: Several real-world cohorts, including the Xiangya (in-house), The Cancer Genome Atlas (TCGA-BLCA), and IMvigor210 cohorts, with TCGA-BLCA cohort serving as the discovery cohort were compared. We investigated the potential immunological effects of ACSM6 in regulating the BLCA tumor microenvironment by analyzing its correlation with immunomodulators, anti-cancer immune cycles, immune checkpoints, tumor-infiltrating immune cells, and the T-cell inflamed score (TIS). Additionally, we assessed the precision of ACSM6 in predicting BLCA molecular subtypes and responses to several treatments using ROC analysis. To ensure the robustness of our findings, all results were confirmed in two independent external cohorts: the IMvigor210 and Xiangya cohorts. Results: ACSM6 expression was markedly upregulated in BLCA. Our analysis suggests that ACSM6 might have significant impact to promote the formation of a non-inflamed tumor microenvironment because of its negative correlation with immunomodulators, anticancer immune cycles, immune checkpoints, tumor-infiltrating immune cells, and the T-cell inflamed score (TIS). Additionally, high ACSM6 expression levels in BLCA may predict the luminal subtype, which is typically associated with resistance to chemotherapy, neoadjuvant chemotherapy, and radiotherapy. These findings were consistent across both the IMvigor210 and Xiangya cohorts. Conclusion: ACSM6 has the potential to serve as a valuable predictor of the tumor microenvironment phenotypes and treatment outcomes in BLCA, thereby contributing to more precise treatment.

Single-cell RNA sequencing revealed subclonal heterogeneity and gene signatures of gemcitabine sensitivity in pancreatic cancer

Introduction: Resistance to gemcitabine is common and critically limits its therapeutic efficacy in pancreatic ductal adenocarcinoma (PDAC). Methods: We constructed 17 patient-derived xenograft (PDX) models from PDAC patient samples and identified the most notable responder to gemcitabine by screening the PDX sets in vivo. To analyze tumor evolution and microenvironmental changes pre- and post-chemotherapy, single-cell RNA sequencing (scRNA-seq) was performed. Results: ScRNA-seq revealed that gemcitabine promoted the expansion of subclones associated with drug resistance and recruited macrophages related to tumor progression and metastasis. We further investigated the particular drug-resistant subclone and established a gemcitabine sensitivity gene panel (GSGP) (SLC46A1, PCSK1N, KRT7, CAV2, and LDHA), dividing PDAC patients into two groups to predict the overall survival (OS) in The Cancer Genome Atlas (TCGA) training dataset. The signature was successfully validated in three independent datasets. We also found that 5-GSGP predicted the sensitivity to gemcitabine in PDAC patients in the TCGA training dataset who were treated with gemcitabine. Discussion and conclusion: Our study provides new insight into the natural selection of tumor cell subclones and remodeling of tumor microenvironment (TME) cells induced by gemcitabine. We revealed a specific drug resistance subclone, and based on the characteristics of this subclone, we constructed a GSGP that can robustly predict gemcitabine sensitivity and prognosis in pancreatic cancer, which provides a theoretical basis for individualized clinical treatment.

Hypoxia Is Associated with Increased Immune Infiltrates and Both Anti-Tumour and Immune Suppressive Signalling in Muscle-Invasive Bladder Cancer

Hypoxia and a suppressive tumour microenvironment (TME) are both independent negative prognostic factors for muscle-invasive bladder cancer (MIBC) that contribute to treatment resistance. Hypoxia has been shown to induce an immune suppressive TME by recruiting myeloid cells that inhibit anti-tumour T cell responses. Recent transcriptomic analyses show hypoxia increases suppressive and anti-tumour immune signalling and infiltrates in bladder cancer. This study sought to investigate the relationship between hypoxia-inducible factor (HIF)-1 and -2, hypoxia, and immune signalling and infiltrates in MIBC. ChIP-seq was performed to identify HIF1α, HIF2α, and HIF1β binding in the genome of the MIBC cell line T24 cultured in 1% and 0.1% oxygen for 24 h. Microarray data from four MIBC cell lines (T24, J82, UMUC3, and HT1376) cultured under 1%, 0.2%, and 0.1% oxygen for 24 h were used. Differences in the immune contexture between high- and low-hypoxia tumours were investigated using in silico analyses of two bladder cancer cohorts (BCON and TCGA) filtered to only include MIBC cases. GO and GSEA were used with the R packages "limma" and "fgsea". Immune deconvolution was performed using ImSig and TIMER algorithms. RStudio was used for all analyses. Under hypoxia, HIF1α and HIF2α bound to ~11.5-13.5% and ~4.5-7.5% of immune-related genes, respectively (1-0.1% O₂). HIF1α and HIF2α both bound to genes associated with T cell activation and differentiation signalling pathways. HIF1α and HIF2α had distinct roles in immune-related signalling. HIF1 was associated with interferon production specifically, whilst HIF2 was associated with generic cytokine signalling as well as humoral and toll-like receptor immune responses. Neutrophil and myeloid cell signalling was enriched under hypoxia, alongside hallmark pathways associated with Tregs and macrophages. High-hypoxia MIBC tumours had increased expression of both suppressive and anti-tumour immune gene signatures and were associated with increased immune infiltrates. Overall, hypoxia is associated with increased inflammation for both suppressive and anti-tumour-related immune signalling and immune infiltrates, as seen in vitro and in situ using MIBC patient tumours.

A Comprehensive Pan-Cancer Analysis of the Regulation and Prognostic Effect of Coat Complex Subunit Zeta 1

The Coatomer protein complex Zeta 1 (COPZ1) has been reported to play an essential role in maintaining the survival of some types of tumors. In this study, we sought to explore the molecular characteristics of COPZ1 and its clinical prognostic value through a pan-cancers bioinformatic analysis. We found that COPZ1 was extremely prevalent in a variety of cancer types, and high expression of COPZ1 was linked to poor overall survival in many cancers, while low expression in LAML and PADC was correlated with tumorigenesis. Besides, the CRISPR Achilles' knockout analysis revealed that COPZ1 was vital for many tumor cells' survival. We further demonstrated that the high expression level of COPZ1 in tumors was regulated in multi-aspects, including abnormal CNV, DNA-methylation, transcription factor and microRNAs. As for the functional exploration of COPZ1, we found a positive relationship between COPZ1's expression and stemness and hypoxia signature, especially the contribution of COPZ1 on EMT ability in SARC. GSEA analysis revealed that COPZ1 was associated with many immune response pathways. Further investigation demonstrated that COPZ expression was negatively correlated with immune score and stromal score, and low expression of COPZ1 has been associated to more antitumor immune cell infiltration and pro-inflammatory cytokines. The further analysis of COPZ1 expression and anti-inflammatory M2 cells showed a consistent result. Finally, we verified the expression of COPZ1 in HCC cells, and proved its ability of sustaining tumor growth and invasion with biological experiments. Our study provides a multi-dimensional pan-cancer analysis of COPZ and demonstrates that COPZ1 can serve as both a prospective target for the treatment of cancer and a prognostic marker for a variety of cancer types.

Expression pattern, tumor immune landscape, and prognostic value of N7‑methylguanosine regulators in bladder urothelial carcinoma

N7-Methylguanosine (m7G) modification is important in post-transcriptional regulation. dysregulation of m7G RNA modification has been reported to be markedly associated with cancer. However, its importance in bladder urothelial carcinoma (BLCA) remains poorly characterized. The present study systematically analyzed mRNA gene expression data and clinical information from The Cancer Genome Atlas and further constructed robust risk signatures for the four regulators of m7G RNA modification (nudix hydrolase 11, gem nuclear organelle-associated protein 5, eukaryotic translation initiation factor 3 subunit D and cytoplasmic FMR1 interacting protein 1). The differential expression and cell function of m7G-related genes in bladder cancer cells were verified by reverse transcription-quantitative PCR, Cell Counting Kit-8 and colony formation assays. The four-gene-based model could accurately predict the prognosis of BLCA. Nomogram-based clinical decisions had a higher net benefit compared with that of individual predictors. Through immune infiltration analysis, it was found that immune cell infiltration affected the prognosis of patients with BLCA. Finally, the present study identified potential therapeutics that differ between high and low-risk groups based on four genes. In summary, the current findings revealed an essential role for m7G RNA modification regulators in BLCA, and developed risk signatures as promising prognostic markers in patients with BLCA.

Necroptosis-Related LncRNA Signatures for Prognostic Prediction in Uterine Corpora Endometrial Cancer

Necroptosis is one of the common modes of apoptosis, and it has an intrinsic association with cancer prognosis. However, the role of the necroptosis-related long non-coding RNA LncRNA (NRLncRNAs) in uterine corpora endometrial cancer (UCEC) has not yet been fully elucidated at present. Therefore, the present study is designed to investigate the potential prognostic value of necroptosis-related LncRNAs in UCEC. In the present study, the expression profiles and clinical data of UCEC patients were downloaded from TCGA database to identify the differentially expressed NRLncRNAs associated with overall survival. A LncRNA risk model was constructed via Cox regression analysis, and its prognostic value was evaluated. We have also further evaluated the relationships between the LncRNA features and the related cellular function, related pathways, immune status, and immune checkpoints m6A-related genes. Seven signatures, including PCAT19, CDKN2B-AS1, LINC01936, LINC02178, BMPR1B-DT, LINC00237, and TRPM2-AS, were established to assess the overall survival (OS) of the UCEC in the present study. Survival analysis and ROC curves indicated that the correlated signature has good predictable performance. The normogram could accurately predict the overall survival of the patients with an excellent clinical practical value. Enrichment analysis of gene sets indicated that risk signals were enriched in several immune-related pathways. In addition, the risk characteristics were significantly correlated with immune cells, immune function, immune cell infiltration, immune checkpoints, and some m6A-related genes. This study has identified seven necroptosis-related LncRNA signatures for the first time, providing a valuable basis for a more accurate prognostic prediction of UCEC.

Novel hypoxia-related gene signature for predicting prognoses that correlate with the tumor immune microenvironment in NSCLC

Background: Intratumoral hypoxia is widely associated with the development of malignancy, treatment resistance, and worse prognoses. The global influence of hypoxia-related genes (HRGs) on prognostic significance, tumor microenvironment characteristics, and therapeutic response is unclear in patients with non-small cell lung cancer (NSCLC). Method: RNA-seq and clinical data for NSCLC patients were derived from The Cancer Genome Atlas (TCGA) database, and a group of HRGs was obtained from the MSigDB. The differentially expressed HRGs were determined using the limma package; prognostic HRGs were identified via univariate Cox regression. Using the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression, an optimized prognostic model consisting of nine HRGs was constructed. The prognostic model's capacity was evaluated by Kaplan‒Meier survival curve analysis and receiver operating characteristic (ROC) curve analysis in the TCGA (training set) and GEO (validation set) cohorts. Moreover, a potential biological pathway and immune infiltration differences were explained. Results: A prognostic model containing nine HRGs (STC2, ALDOA, MIF, LDHA, EXT1, PGM2, ENO3, INHA, and RORA) was developed. NSCLC patients were separated into two risk categories according to the risk score generated by the hypoxia model. The model-based risk score had better predictive power than the clinicopathological method. Patients in the high-risk category had poor recurrence-free survival in the TCGA (HR: 1.426; 95% CI: 0.997-2.042; p = 0.046) and GEO (HR: 2.4; 95% CI: 1.7-3.2; p < 0.0001) cohorts. The overall survival of the high-risk category was also inferior to that of the low-risk category in the TCGA (HR: 1.8; 95% CI: 1.5-2.2; p < 0.0001) and GEO (HR: 1.8; 95% CI: 1.4-2.3; p < 0.0001) cohorts. Additionally, we discovered a notable distinction in the enrichment of immune-related pathways, immune cell abundance, and immune checkpoint gene expression between the two subcategories. Conclusion: The proposed 9-HRG signature is a promising indicator for predicting NSCLC patient prognosis and may be potentially applicable in checkpoint therapy efficiency prediction.

The Role of the Hypoxia-Related Unfolded Protein Response (UPR) in the Tumor Microenvironment

Despite our understanding of the unfolded protein response (UPR) pathways, the crosstalk between the UPR and the complex signaling networks that different cancers utilize for cell survival remains to be, in most cases, a difficult research barrier. A major problem is the constant variability of different cancer types and the different stages of cancer as well as the complexity of the tumor microenvironments (TME). This complexity often leads to apparently contradictory results. Furthermore, the majority of the studies that have been conducted have utilized two-dimensional in vitro cultures of cancer cells that were exposed to continuous hypoxia, and this approach may not mimic the dynamic and cyclic conditions that are found in solid tumors. Here, we discuss the role of intermittent hypoxia, one of inducers of the UPR in the cellular component of TME, and the way in which intermittent hypoxia induces high levels of reactive oxygen species, the activation of the UPR, and the way in which cancer cells modulate the UPR to aid in their survival. Although the past decade has resulted in defining the complex, novel non-coding RNA-based regulatory networks that modulate the means by which hypoxia influences the UPR, we are now just to beginning to understand some of the connections between hypoxia, the UPR, and the TME.

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.

G-Protein Subunit Gamma 4 as a Potential Biomarker for Predicting the Response of Chemotherapy and Immunotherapy in Bladder Cancer

Background: GNG4, a member of the G-protein γ family, is a marker of poor overall survival (OS) rates in some malignancies. However, the potential role of GNG4 in bladder cancer (BLCA) is unknown. It is also unclear whether GNG4 may be utilized as a marker to guide chemotherapy or immunotherapy. Methods: Single-cell RNA sequencing data were used to explore the expression of GNG4 in tumor microenvironment of BLCA. Bulk RNA sequencing data from TCGA were used to evaluate the relationship between GNG4 expression and biological features, such as immune cell infiltrations and gene mutations. The associations between GNG4 expression and survival in BLCA patients under or not under immunotherapy were evaluated using seven BLCA cohorts. Results: GNG4 was specifically expressed in exhausted CD4⁺ T cells. And the high expression of the GNG4 was associated with high level of immune cell infiltration. The high-GNG4-expression group displayed a better response to immunotherapy, whereas patients in the low-GNG4-expression group often benefited from chemotherapy. Moreover, the high-GNG4 group was more similar to the basal group, whereas the low-GNG4 group was similar to the luminal group. Conclusions: GNG4 may be a potential biomarker for the prediction of the response to therapy in BLCA. Higher GNG4 expression can be used as a predictor of response to immunotherapy, and lower GNG4 expression can be used as a predictor of response to chemotherapy.

Fatty Acid Synthase Is the Key Regulator of Fatty Acid Metabolism and Is Related to Immunotherapy in Bladder Cancer

Fatty acid metabolism (FAM) genes are potentially useful for predicting prognosis and immunotherapy response in bladder cancer (BC). To examine this, we constructed a prognostic model and identified key FAM genes in BC. Using transcriptional expression profiles and clinical data of BC patients from public datasets and Changhai (CH) hospital, we built and validated a risk-score model based on 13 prognostic FAM genes. Differential gene expression identified fatty acid synthase (FASN) as central to fatty acid metabolism in BC. FASN was differentially expressed between normal and tumor tissue, and was related to survival. In the CH dataset, FASN independently predicted muscle-invasive BC. FASN differential expression was significantly related to immune-cell infiltration and patients with low FASN expression responded better to immune checkpoint inhibitor (ICI) treatment. SREBF1 was predicted as the most significant transcription factor for FASN. Competing endogenous RNA network analysis suggested that lncRNA AC107027.3 may upregulate FASN by competitively binding miR-27A-3p, thereby regulating the immunotherapy response in BC. Dasatinib and temsirolimus are potential FASN-targeting drugs. Our model efficiently predicted prognosis in BC. FASN is central to fatty acid metabolism, and a potential indicator and regulator of ICI treatment.

The Effect of Hypoxia and Hypoxia-Associated Pathways in the Regulation of Antitumor Response: Friends or Foes?

Hypoxia is an environmental stressor that is instigated by low oxygen availability. It fuels the progression of solid tumors by driving tumor plasticity, heterogeneity, stemness and genomic instability. Hypoxia metabolically reprograms the tumor microenvironment (TME), adding insult to injury to the acidic, nutrient deprived and poorly vascularized conditions that act to dampen immune cell function. Through its impact on key cancer hallmarks and by creating a physical barrier conducive to tumor survival, hypoxia modulates tumor cell escape from the mounted immune response. The tumor cell-immune cell crosstalk in the context of a hypoxic TME tips the balance towards a cold and immunosuppressed microenvironment that is resistant to immune checkpoint inhibitors (ICI). Nonetheless, evidence is emerging that could make hypoxia an asset for improving response to ICI. Tackling the tumor immune contexture has taken on an in silico, digitalized approach with an increasing number of studies applying bioinformatics to deconvolute the cellular and non-cellular elements of the TME. Such approaches have additionally been combined with signature-based proxies of hypoxia to further dissect the turbulent hypoxia-immune relationship. In this review we will be highlighting the mechanisms by which hypoxia impacts immune cell functions and how that could translate to predicting response to immunotherapy in an era of machine learning and computational biology.

TNF Family-Based Signature Predicts Prognosis, Tumor Microenvironment, and Molecular Subtypes in Bladder Carcinoma

Background: Tumor necrosis factor (TNF) family members play vital roles in cancer development and antitumor immune responses. However, the expression patterns, prognostic values, and immunological characteristics of TNF members in bladder carcinoma (BLCA) remain unclear.

Methods: The training cohort, TCGA-BLCA, was downloaded from The Cancer Genome Atlas; another two Gene Expression Omnibus datasets (GSE13507 and GSE32894) and the Xiangya cohort (RNA-sequencing cohort collected from our hospital) were used as the external validation cohort. The least absolute shrinkage and selection operator (LASSO) algorithm and cross-validation were used to screen variables. Cox regression model and random survival forest (RSF) were used to develop the risk score, respectively. Then, we systematically correlated the TNF risk score with the tumor microenvironment (TME) cell infiltration, molecular subtypes of BLCA, and the potential value for predicting the efficacy of immunotherapy.

Results: We developed two TNF-based patterns, named TNF cluster 1 and TNF cluster 2. TNF cluster 1 exhibited poorer survival outcome and an inflamed TME characteristic compared with TNF cluster 2. We then filtered out 196 differentially expressed genes between the two TNF clusters and applied the LASSO algorithm and cross-validation to screen out 22 genes to build the risk score. For risk score, we found that RSF exhibited higher efficacy than the Cox regression model, and we chose the risk score developed by RSF for the following analysis. BLCA patients in the higher risk score group showed significantly poorer survival outcomes. Moreover, these results could be validated in the external validation cohorts, including the GSE13507, GSE32894, and Xiangya cohorts. Then, we systematically correlated the risk score with TME cell infiltration and found that it was positively correlated with the infiltration of a majority of immune cells. Also, a higher risk score indicated a basal subtype of BLCA. Notably, the relationship between risk score, TME cell infiltration, and molecular subtypes could be validated in the Xiangya cohort.

Conclusion: We developed and validated a robust TNF-based risk score, which could predict prognostic outcomes, TME, and molecular subtypes of BLCA. However, the value of risk score predicting the efficacy of immunotherapy needs further research.

A Novel Assessment Model Based on Molecular Subtypes of Hypoxia-Related LncRNAs for Prognosis of Bladder Cancer

Hypoxia is a common feature in various tumors that regulates aggressiveness. Previous studies have demonstrated that some dysregulated long non-coding RNAs (lncRNAs) are correlated with tumor progression, including bladder cancer (BCa). However, the prognostic effect of hypoxia-related lncRNAs (HRLs) and their clinical relevance, as well as their regulatory effect on the tumor immune microenvironment, are largely unknown in BCa. A co-expression analysis between hypoxia genes and lncRNA expression, which was downloaded from the TCGA database, was performed to identify HRLs. Univariate Cox regression analysis was performed to select the most desirable lncRNAs for molecular subtype, and further LASSO analysis was performed to develop a prognostic model. This molecular subtype based on four HRLs (AC104653, AL136084, AL139393, and LINC00892) showed good performance in the tumor microenvironment and tumor mutation burden. The prognostic risk model suggested better performance in predicting BCa patients' prognosis and obtained a close correlation with clinicopathologic features. Furthermore, four of five first-line clinical chemotherapies showed different sensitivities to this model, and nine immune checkpoints showed different expression in the molecular subtypes or the risk model. In conclusion, this study indicates that this molecular subtype and risk model based on HRLs may be useful in improving the prognostic prediction of BCa patients with different clinical situations and may help to find a useful target for tumor therapy.

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

Background

The TGF-β pathway plays critical roles in numerous malignancies. Nevertheless, its potential role in prognosis prediction and regulating tumour microenvironment (TME) characteristics require further elucidation in bladder cancer (BLCA).

Methods

TGF-β-related genes were comprehensively summarized from several databases. The TCGA-BLCA cohort (training cohort) was downloaded from the Cancer Genome Atlas, and the independent validation cohorts were gathered from Xiangya Hospital (Xinagya cohort) and Gene Expression Omnibus. Initially, we identified differentially expressed TGF-β genes (DEGs) between cancer and normal tissues. Subsequently, univariate Cox analysis was applied to identify prognostic DEGs, which were further used to develop the TGF-β risk score by performing LASSO and multivariate Cox analyses. Then, we studied the role of the TGF-β risk score in predicting prognosis and the TME phenotypes. In addition, the role of the TGF-β risk score in guiding precision treatments for BLCA has also been assessed.

Results

We successfully constructed a TGF-β risk score with an independent prognostic prediction value. A high TGF-β risk score indicated an inflamed TME, which was supported by the positive relationships between the risk score, enrichment scores of anticancer immunity steps, and the infiltration levels of tumour-infiltrating immune cells. In addition, the risk score positively correlated with the expression of several immune checkpoints and the T cell inflamed score. Consistently, the risk score was positively related to the enrichment scores of most immunotherapy-positive pathways. In addition, the sensitivities of six common chemotherapeutic drugs were positively associated with the risk score. Furthermore, higher risk score indicated higher sensitivity to radiotherapy and EGFR-targeted therapy. On the contrary, patients with low-risk scores were more sensitive to targeted therapies, including the blockade of FGFR3 and WNT-β-catenin networks.

Conclusions

We first constructed and validated a TGF-β signature that could predict the prognosis and TME phenotypes for BLCA. More importantly, the TGF-β risk score could aid in individual precision treatment for BLCA.