An immune cell infiltration-related gene signature predicts prognosis for bladder cancer

Clinical significance of KRT7 in bladder cancer prognosis

BACKGROUND

Typically, the overexpressed keratin 7 (KRT7) is considered a validated therapeutic target and prognosis marker in bladder cancer. However, the crucial roles of KRT7 in the clinical prognosis and immune microenvironment in bladder cancer remain unclear.

METHODS

Initially, the expression levels of KRT7 in public databases were analyzed that is,Tumor Immune Estimation Resource (TIMER) 2.0 and Gene Expression Profiling Interactive Analysis (GEPIA). Further, the clinical tissue samples from patients (n = 10 pairs) were collected to confirm the expression trends of KRT7 and detected by immunohistochemistry (IHC) analysis. Meanwhile, the relationship between KRT7 and the prognosis of bladder cancer patients was analyzed by Kaplan-Meier plotter estimation and Cox regression analysis. Finally, TIMER 2.0 and IHC staining analyses were performed to calculate the infiltration abundances of three kinds of immune cells in eligible bladder tumor samples.

RESULTS

The TIMER 2.0 and GEPIA datasets suggested the differences in the expression levels of KRT7 in tumors, in which KRT7 was significantly upregulated in bladder cancer. The KRT7 expression was closely associated with patients' gender, tumor histologic subtypes, T status, and American Joint Committee on Cancer stages. Notably, the increased KRT7 indicated poor overall survival and disease-free survival rates. Moreover, KRT7 expression could be responsible for immune infiltration in the cancer microenvironment of the bladder. Finally, the high expression level of KRT7 increased the presence of regulatory T cells (Tregs) but reduced the infiltration of CD8+ T and natural killer cells.

CONCLUSION

KRT7 as a biomarker potentiated the prediction of bladder cancer prognosis and the immune microenvironment.

Decreased TLR7 expression was associated with airway eosinophilic inflammation and lung function in asthma: evidence from machine learning approaches and experimental validation

BACKGROUND

Asthma is a global public health concern. The underlying pathogenetic mechanisms of asthma were poorly understood. This study aims to explore potential biomarkers associated with asthma and analyze the pathological role of immune cell infiltration in the disease.

METHODS

The gene expression profiles of induced sputum were obtained from Gene Expression Omnibus datasets (GSE76262 and GSE137268) and were combined for analysis. Toll-like receptor 7 (TLR7) was identified as the core gene by the intersection of two different machine learning algorithms, namely, least absolute shrinkage and selector operation (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE), and the top 10 core networks based on Cytohubba. CIBERSORT algorithm was used to analyze the difference of immune cell infiltration between asthma and healthy control groups. Finally, the expression level of TLR7 was validated in induced sputum samples of patients with asthma.

RESULTS

A total of 320 differential expression genes between the asthma and healthy control groups were screened, including 184 upregulated genes and 136 downregulated genes. TLR7 was identified as the core gene after combining the results of LASSO regression, SVM-RFE algorithm, and top 10 hub genes. Significant differences were observed in the distribution of 13 out of 22 infiltrating immune cells in asthma. TLR7 was found to be closely related to the level of several infiltrating immune cells. TLR7 mRNA levels were downregulated in asthmatic patients compared with healthy controls (p = 0.0049). The area under the curve of TLR7 for the diagnosis of asthma was 0.7674 (95% CI 0.631-0.904, p = 0.006). Moreover, TLR7 mRNA levels were negatively correlated with exhaled nitric oxide fraction (r = - 0.3268, p = 0.0347) and the percentage of peripheral blood eosinophils (%) (r = - 0.3472, p = 0.041), and positively correlated with forced expiratory volume in the first second (FEV1) (% predicted) (r = 0.3960, p = 0.0071) and FEV1/forced vital capacity (r = 0.3213, p = 0.0314) in asthmatic patients.

CONCLUSIONS

Decreased TLR7 in the induced sputum of eosinophilic asthmatic patients was involved in immune cell infiltration and airway inflammation, which may serve as a new biomarker for the diagnosis of eosinophilic asthma.

POLR3G promotes EMT via PI3K/AKT signaling pathway in bladder cancer

RNA Polymerase III Subunit G (POLR3G) promotes tumorigenesis, metastasis, cancer stemness, and chemoresistance of breast cancer and lung cancer; however, its biological function in bladder cancer (BLCA) remains unclear. Through bioinformatic analyses, we found that POLR3G expression was significantly elevated in BLCA tumor tissues and was associated with decreased survival. Multivariate Cox analysis indicated that POLR3G could serve as an independent prognostic risk factor. Our functional investigations revealed that POLR3G deficiency resulted in reduced migration and invasion of BLCA cells both in vitro and in vivo. Additionally, the expressions of EMT-related mesenchymal markers were also downregulated in POLR3G knockdown cells. Mechanistically, we showed that POLR3G could activate the PI3K/AKT signaling pathway. Inhibition of this pathway with LY294002 reduced the enhanced migration and invasion of BLCA cells induced by POLR3G overexpression, whereas the activation of this pathway using 740Y-P restored the abilities that were inhibited by POLR3G knockdown. Taken together, our findings suggested that POLR3G is a prognostic predictor for BLCA and promotes EMT of BLCA through activation of the PI3K/AKT signaling pathway.

Machine-learning based integrating bulk and single-cell RNA sequencing reveals the SLC38A5-CCL5 signaling as a promising target for clear cell renal cell carcinoma treatment

Cancer-associated fibroblasts paly critical roles in regulating cancer cell biological properties by intricate and dynamic communication networks. But the mechanism of CAFs in clear cell renal cell carcinoma (ccRCC) is not clear. In our study, we identified CAFs and malignant cells from the integrated scRNA-seq datasets and establish a CAF-derived communication signature based on the highly activated regulons ETS1 and MEF2C. We stratified the ccRCC TME into two molecular subtypes with distinct prognoses, immune cell infiltration landscapes, and immune-related characteristics. The model derived from signature demonstrated high accuracy and robustness in predicting prognosis and ICIs therapy responses. Subsequently, the SLC38A5 of the model was found upregulated in CAFs and was related to decreased survival probabilities, inflamed TME, and upregulated inhibitory checkpoints. SLC38A5 inhibition could attenuate the pro-tumoral abilities of CAFs in terms of proliferation, migration, and invasion. Mechanically, CCL5 could restore these properties induced by SLC38A5 inhibition. In conclusion, our communication signature and its derived model enabled a more precise selection of ccRCC patients who were potential beneficiaries of ICIs. Besides, the SLC38A5-CCL5 axis may serve as a promising target for ccRCC treatment.

Immune gene signatures as prognostic criteria for cancer patients

Recently, the possibility of using immune gene signatures (IGSs) has been considered as a novel prognostic tool for numerous cancer types. State-of-the-art methods of genomic, transcriptomic, and protein analysis have allowed the identification of a number of immune signatures correlated to disease outcome. The major adaptive and innate immune components are the T lymphocytes and macrophages, respectively. Herein, we collected essential data on IGSs consisting of subsets of T cells and tumor-associated macrophages and indicating cancer patient outcomes. We discuss factors that can introduce errors in the recognition of immune cell types and explain why the significance of immune signatures can be interpreted with uncertainty. The unidirectional functions of cell types should be entirely addressed in the signatures constructed by the combination of innate and adaptive immune cells. The state of the antitumor immune response is the key basis for IGSs and should be considered in gene signature construction. We also analyzed immune signatures for the prediction of immunotherapy response. Finally, we attempted to explain the present-day limitations in the use of immune signatures as robust criteria for prognosis.

Leveraging a disulfidptosis-based signature to improve the survival and drug sensitivity of bladder cancer patients

Background

Disulfidptosis is a recently discovered form of cell death. However, its biological mechanisms in bladder cancer (BCa) are yet to be understood.

Methods

Disulfidptosis-related clusters were identified by consensus clustering. A disulfidptosis-related gene (DRG) prognostic model was established and verified in various datasets. A series of experiments including qRT-PCR, immunoblotting, IHC, CCK-8, EdU, wound-healing, transwell, dual-luciferase reporter, and ChIP assays were used to study the biological functions.

Results

We identified two DRG clusters, which exhibited distinct clinicopathological features, prognosis, and tumor immune microenvironment (TIME) landscapes. A DRG prognostic model with ten features (DCBLD2, JAM3, CSPG4, SCEL, GOLGA8A, CNTN1, APLP1, PTPRR, POU5F1, CTSE) was established and verified in several external datasets in terms of prognosis and immunotherapy response prediction. BCa patients with high DRG scores may be characterized by declined survival, inflamed TIME, and elevated tumor mutation burden. Besides, the correlation between DRG score and immune checkpoint genes and chemoradiotherapy-related genes indicated the implication of the model in personalized therapy. Furthermore, random survival forest analysis was performed to select the top important features within the model: POU5F1 and CTSE. qRT-PCR, immunoblotting, and immunohistochemistry assays showed the enhanced expression of CTSE in BCa tumor tissues. A series of phenotypic assays revealed the oncogenetic roles of CTSE in BCa cells. Mechanically, POU5F1 can transactivate CTSE, promoting BCa cell proliferation and metastasis.

Conclusions

Our study highlighted the disulfidptosis in the regulation of tumor progression, sensitivity to therapy, and survival of BCa patients. POU5F1 and CTSE may be potential therapeutic targets for the clinical treatment of BCa.

Machine learning-based identification of tumor-infiltrating immune cell-associated model with appealing implications in improving prognosis and immunotherapy response in bladder cancer patients

Background

Immune cells are crucial components of the tumor microenvironment (TME) and regulate cancer cell development. Nevertheless, the clinical implications of immune cell infiltration-related mRNAs for bladder cancer (BCa) are still unclear.

Methods

A 10-fold cross-validation framework with 101 combinations of 10 machine-learning algorithms was employed to develop a consensus immune cell infiltration-related signature (IRS). The predictive performance of IRS in terms of prognosis and immunotherapy was comprehensively evaluated.

Results

The IRS demonstrated high accuracy and stable performance in prognosis prediction across multiple datasets including TCGA-BLCA, eight independent GEO datasets, our in-house cohort (PUMCH_Uro), and thirteen immune checkpoint inhibitors (ICIs) cohorts. Additionally, IRS was superior to traditional clinicopathological features (e.g., stage and grade) and 94 published signatures. Furthermore, IRS was an independent risk factor for overall survival in TCGA-BLCA and several GEO datasets, and for recurrence-free survival in PUMCH_Uro. In the PUMCH_Uro cohort, patients in the high-IRS group were characterized by upregulated CD8A and PD-L1 and TME of inflamed and immunosuppressive phenotypes. As predicted, these patients should benefit from ICI therapy and chemotherapy. Furthermore, in the ICI cohorts, the high-IRS group was related to a favorable prognosis and responders have dramatically higher IRS compared to non-responders.

Conclusions

Generally, these indicators suggested the promising application of IRS in urological practices for the early identification of high-risk patients and potential candidates for ICI application to prolong the survival of individual BCa patients.

BCG-Induced Tumor Immunity Requires Tumor-Intrinsic CIITA Independent of MHC-II

For decades, BCG immunotherapy has been the standard of care for non-muscle-invasive bladder cancer. Despite this clinical experience, the mechanism by which BCG stimulates tumor-eliminating immunity is unclear, and there is still a need for more accurate prediction of clinical outcomes in advance of treatment initiation. We have shown that BCG stimulates tumor-specific T-cell immunity that requires tumor cell expression of the IFNγ receptor (IFNGR); however, the downstream components of IFNGR signaling responsible for responsiveness to BCG are unknown. Here, we demonstrate that the IFNγ-driven, tumor cell intrinsic expression of the class II transactivator CIITA is required for activation of a tumor-specific CD4 T-cell response and BCG-induced tumor immunity. Despite the established role for CIITA in controlling MHC-II antigen presentation machinery, the requirement for CIITA is independent of MHC-II and associated genes. Rather, we find that CIITA is required for a broader tumor-intrinsic transcriptional program linked to critical pathways of tumor immunity via mechanisms that remain to be determined. Tumor cell intrinsic expression of CIITA is not required for a response to immunotherapy targeting programmed cell death protein 1 (PD-1), suggesting that different modalities of immunotherapy for bladder cancer could be employed based on tumor-intrinsic characteristics.

mRNA-miRNA bipartite networks reconstruction in different tissues of bladder cancer based on gene co-expression network analysis

Bladder cancer (BC) is one of the most important cancers worldwide, and if it is diagnosed early, its progression in humans can be prevented and long-term survival will be achieved accordingly. This study aimed to identify novel micro-RNA (miRNA) and gene-based biomarkers for diagnosing BC. The microarray dataset of BC tissues (GSE13507) listed in the GEO database was analyzed for this purpose. The gene expression data from three BC tissues including 165 primary bladder cancer (PBC), 58 normal looking-bladder mucosae surrounding cancer (NBMSC), and 23 recurrent non-muscle invasive tumor tissues (RNIT) were used to reconstruct gene co-expression networks. After preprocessing and normalization, deferentially expressed genes (DEGs) were obtained and used to construct the weighted gene co-expression network (WGCNA). Gene co-expression modules and low-preserved modules were extracted among BC tissues using network clustering. Next, the experimentally validated mRNA-miRNA interaction information were used to reconstruct three mRNA-miRNA bipartite networks. Reactome pathway database and Gene ontology (GO) was subsequently performed for the extracted genes of three bipartite networks and miRNAs, respectively. To further analyze the data, ten hub miRNAs (miRNAs with the highest degree) were selected in each bipartite network to reconstruct three bipartite subnetworks. Finally, the obtained biomarkers were comprehensively investigated and discussed in authentic studies. The obtained results from our study indicated a group of genes including PPARD, CST4, CSNK1E, PTPN14, ETV6, and ADRM1 as well as novel miRNAs (e.g., miR-16-5p, miR-335-5p, miR-124-3p, and let-7b-5p) which might be potentially associated with BC and could be a potential biomarker. Afterward, three drug-gene interaction networks were reconstructed to explore candidate drugs for the treatment of BC. The hub miRNAs in the mRNA-miRNA bipartite network played a fundamental role in BC progression; however, these findings need further investigation.