Development of prognostic signature based on immune-related genes in muscle-invasive bladder cancer: bioinformatics analysis of TCGA database

Unveiling the role of RAC3 in the growth and invasion of cisplatin-resistant bladder cancer cells

Bladder cancer is one of the most prevalent cancers worldwide, and its morbidity and mortality rates have been increasing over the years. However, how RAC family small GTPase 3 (RAC3) affects the proliferation, migration and invasion of cisplatin-resistant bladder cancer cells remains unclear. Bioinformatics techniques were used to investigate the expression of RAC3 in bladder cancer tissues. Influences of RAC3 in the grade, stage, distant metastasis, and survival rate of bladder cancer were also examined. Analysis of the relationship between RAC3 expression and the immune microenvironment (TIME), genomic mutations, and stemness index. In normal bladder cancer cells (T24, 5637, and BIU-87) and cisplatin-resistant bladder cancer cells (BIU-87-DDP), the expression of RAC3 was detected separately with Western blotting. Plasmid transfection was used to overexpress or silence the expression of RAC3 in bladder cancer cells resistant to cisplatin (BIU-87-DDP). By adding activators and inhibitors, the activities of the JNK/MAPK signalling pathway were altered. Cell viability, invasion, and its level of apoptosis were measured in vitro using CCK-8, transwell, and flow cytometry. The bioinformatics analyses found RAC3 levels were elevated in bladder cancer tissues and were associated with a poor prognosis in bladder cancer. RAC3 in BIU-87-DDP cells expressed a higher level than normal bladder cancer cells. RAC3 overexpression promoted BIU-87-DDP proliferation. The growth of BIU-87-DDP cells slowed after the knockdown of RAC3, and RAC3 may have had an impact on the activation of the JNK/MAPK pathway.

Exploring the impact of PDGFD in osteosarcoma metastasis through single-cell sequencing analysis

PURPOSE

The overall survival rate for metastatic osteosarcoma hovers around 20%. Responses to second-line chemotherapy, targeted therapies, and immunotherapies have demonstrated limited efficacy in metastatic osteosarcoma. Our objective is to validate differentially expressed genes and signaling pathways between non-metastatic and metastatic osteosarcoma, employing single-cell RNA sequencing (scRNA-seq) and additional functional investigations. We aim to enhance comprehension of metastatic mechanisms and potentially unveil a therapeutic target.

METHODS

scRNA-seq was performed on two primary osteosarcoma lesions (1 non-metastatic and 1 metastatic). Seurat package facilitated dimensionality reduction and cluster identification. Copy number variation (CNV) was predicted using InferCNV. CellChat characterized ligand-receptor-based intercellular communication networks. Differentially expressed genes underwent GO function enrichment analysis and GSEA. Validation was achieved through the GSE152048 dataset, which identified PDGFD-PDGFRB as a common ligand-receptor pair with significant contribution. Immunohistochemistry assessed PDGFD and PDGFRB expression, while multicolor immunofluorescence and flow cytometry provided insight into spatial relationships and the tumor immune microenvironment. Kaplan-Meier survival analysis compared metastasis-free survival and overall survival between high and low levels of PDGFD and PDGFRB. Manipulation of PDGFD expression in primary osteosarcoma cells examined invasion abilities and related markers.

RESULTS

Ten clusters encompassing osteoblasts, osteoclasts, osteocytes, fibroblasts, pericytes, endothelial cells, myeloid cells, T cells, B cells, and proliferating cells were identified. Osteoblasts, osteoclasts, and osteocytes exhibited heightened CNV levels. Ligand-receptor-based communication networks exposed significant fibroblast crosstalk with other cell types, and the PDGF signaling pathway was activated in non-metastatic osteosarcoma primary lesion. These results were corroborated by the GSE152048 dataset, confirming the prominence of PDGFD-PDGFRB as a common ligand-receptor pair. Immunohistochemistry demonstrated considerably greater PDGFD expression in non-metastatic osteosarcoma tissues and organoids, correlating with extended metastasis-free and overall survival. PDGFRB expression showed no significant variation between non-metastatic and metastatic osteosarcoma, nor strong correlations with survival times. Multicolor immunofluorescence suggested co-localization of PDGFD with PDGFRB. Flow cytometry unveiled a highly immunosuppressive microenvironment in metastatic osteosarcoma. Manipulating PDGFD expression demonstrated altered invasive abilities and marker expressions in primary osteosarcoma cells from both non-metastatic and metastatic lesions.

CONCLUSIONS

scRNA-seq illuminated the activation of the PDGF signaling pathway in primary lesion of non-metastatic osteosarcoma. PDGFD displayed an inhibitory effect on osteosarcoma metastasis, likely through the suppression of the EMT signaling pathway.

Development of a Novel Prognostic Model for Esophageal Squamous Cell Carcinoma: Insights into Immune Cell Interactions and Drug Sensitivity

Esophageal squamous cell carcinoma (ESCC) presents a five-year survival rate below 20%, underscoring the need for improved prognostic markers. Our study analyzed ESCC-specific datasets to identify consistently differentially expressed genes. A Venn analysis followed by gene network interactions revealed 23 key genes, from which we built a prognostic model using the COX algorithm (p = 0.000245, 3-year AUC = 0.967). This model stratifies patients into risk groups, with high-risk individuals showing worse outcomes and lower chemotherapy sensitivity. Moreover, a link between risk scores and M2 macrophage infiltration, as well as significant correlations with immune checkpoint genes (e.g., SIGLEC15, PDCD1LG2, and HVCR2), was discovered. High-risk patients had lower Tumor Immune Dysfunction and Exclusion (TIDE) values, suggesting potential responsiveness to immune checkpoint blockade (ICB) therapy. Our efficient 23-gene prognostic model for ESCC indicates a dual utility in assessing prognosis and guiding therapeutic decisions, particularly in the context of ICB therapy for high-risk patients.

ALYREF m5C RNA methylation reader predicts bladder cancer prognosis by regulating the tumor immune microenvironment

BACKGROUND

5-Methylcytidine (m5C) methylation is a recently emerging epigenetic modification that is closely related to tumor proliferation, occurrence, and metastasis. This study aimed to investigate the clinicopathological characteristics and prognostic value of m5C regulators in bladder cancer (BLCA), and their correlation with the tumor immune microenvironment.

METHODS

Thirteen m5C RNA methylation regulators were analyzed using RNA-sequencing and corresponding clinical information obtained from the TCGA database. The Cluster Profiler package was used to analyze the gene ontology function of potential targets and enriched the Kyoto Encyclopedia of Genes and Genomes pathway. Kaplan-Meier survival analysis was used to compare survival differences using the log-rank test and univariate Cox proportional hazards regression. The correlation between signature prognostic m5C regulators and various immune cells was analyzed. Univariate and multivariate Cox regression analyses identified independence of the ALYREF gene signature.

RESULTS

Nine out of the 13 m5C RNA methylation regulators were differentially expressed in BLCA and normal samples and were co-expressed. These 9 regulators were associated with clinicopathological tumor characteristics, particularly high or low tumor risk, pT or pTNM stage, and migration. Consensus clustering analysis divides the BLCA samples into 4 clusters. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment annotation and gene ontology function analysis identified 273 upregulated and 594 downregulated genes in BLCA. Notably, only ALYREF was significantly correlated with OS (P < .05). ALYREF exhibited significant infiltration levels in macrophage cells. Therefore, we constructed a nomogram for ALYREF as an independent prognostic factor. Additionally, we observed that both the mRNA and protein levels of ALYREF were upregulated, and immunofluorescence showed that ALYREF was mainly distributed in nuclear speckles. ALYREF overexpression was significantly associated with poor OS.

CONCLUSION

Our findings demonstrated the potential of ALYREF to predict clinical prognostic risks in BLCA patients and regulate the tumor immune microenvironment. As such, ALYREF may serve as a novel prognostic indicator in BLCA patients.

circRNA TATA-box binding protein associated factor 15 acts as an oncogene to facilitate bladder cancer progression through targeting miR-502-5p/high mobility group box 3

Circular RNAs (circRNAs) are key in regulating bladder cancer progression. This study explored the effects of circRNA TATA-box binding protein associated factor 15 (circTAF15) on bladder cancer progression. We enrolled 80 bladder cancer patients to examine the relationship between circTAF15 expression and clinical features. The function of circTAF15 on bladder cancer cell viability, proliferation, migration, invasion, and glycolysis was monitored by cell counting kit-8 assay, 5-Ethynyl-2'-deoxyuridine experiment, Transwell experiment, and glycolysis analysis. Dual luciferase reporter gene assay, RNA pull-down assay, and RNA immunoprecipitation assay were used to verify the binding between circTAF15 and miR-502-5p or between miR-502-5p and high mobility group box 3 (HMGB3). circTAF15 effect on in vivo growth of bladder cancer was investigated by xenograft tumor experiment. Quantitative real-time polymerase chain reaction, Western blot, and immunohistochemistry were implemented to investigate the expression levels of genes. circTAF15 was upregulated in bladder cancer patients, associated with unfavorable outcomes. circTAF15 knockdown attenuated bladder cancer cell viability, proliferation, migration, invasion, epithelial-mesenchymal transition, and glycolysis. circTAF15 suppressed miR-502-5p expression, and miR-502-5p inhibited HMGB3 expression. Low miR-502-5p expression was associated with unfavorable outcomes in bladder cancer patients. miR-502-5p silencing and HMGB3 overexpression counteracted the inhibition of circTAF15 knockdown on the malignant phenotype of bladder cancer cells. circTAF15 knockdown attenuated the in vivo growth of bladder cancer cells. circTAF15 enhanced the progression of bladder cancer through upregulating HMGB3 via suppressing miR-502-5p. circTAF15 may be a novel target to treat bladder cancer in the future.

Development of a prognostic signature for immune-associated genes in bladder cancer and exploring potential drug findings

BACKGROUND

Bladder cancer, predominantly affecting men, is a prevalent malignancy of the urinary system. Although platinum-based chemotherapy has demonstrated certain enhancements in overall survival when compared to surgery alone, the efficacy of treatments is impeded by the unfavorable side effects of conventional chemotherapy medications. Nonetheless, immunotherapy exhibits potential in the treatment of bladder cancer.

METHODS

To create an immune-associated prognostic signature for bladder cancer, bioinformatics analyses were performed utilizing The Cancer Genome Atlas (TCGA) database in this study. By identifying differential gene expressions between the high-risk and low-risk groups, a potential therapeutic drug was predicted using the Connectivity Map database. Subsequently, the impact of this drug on the growth of T24 cells was validated through MTT assay and 3D cell culture techniques.

RESULTS

The signature included 1 immune-associated LncRNA (NR2F1-AS1) and 16 immune-associated mRNAs (DEFB133, RBP7, PDGFRA, CGB3, PDGFD, SCG2, ADCYAP1R1, OPRL1, PGR, PSMD1, TANK, PRDX1, ADIPOR2, S100A8, AHNAK, EGFR). Based on the assessment of risk scores, the patients were classified into cohorts of low-risk and high-risk individuals. The cohort with low risk demonstrated a considerably higher likelihood of survival in comparison to the group with high risk. Furthermore, variations in immune infiltration were noted among the two categories. Cephaeline, a possible medication, was discovered by analyzing variations in gene expression. It exhibited promise in suppressing the viability and growth of T24 bladder cancer cells.

CONCLUSION

The novel predictive pattern allows for efficient categorization of patients with bladder cancer, enabling focused and rigorous treatment for those expected to have a worse prognosis. The discovery of a possible curative medication establishes a basis for forthcoming immunotherapy trials in bladder cancer.

Early diagnosis and prognostic potential of RAC3 in bladder tumor

BACKGROUND AND PURPOSE

Bladder tumors are among the most prevalent malignancies in the urinary system, and RAC3 has been linked to various types of cancer. This article seeks to explore the potential of RAC3 as both an early diagnostic marker for bladder tumors and a novel therapeutic target.

METHODS/PATIENTS

The expression of RAC3 in bladder tissue was detected using immunohistochemical staining. Additionally, the protein expression of RAC3 was measured and quantified through enzyme-linked immunosorbent assay (ELISA). Subsequently, the correlation between the expression level of RAC3 and bladder tumors was investigated through multifactorial analysis and survival analysis.

RESULTS

Our findings revealed that RAC3 expression was upregulated in bladder tumor tissues. Moreover, we observed higher levels of RAC3 expression in the serum and urine of patients with bladder tumors compared to those with non-bladder tumors. Additionally, we identified a significant positive correlation between RAC3 expression levels and the stage, degree of differentiation, and infiltration of bladder tumors. Importantly, high RAC3 expression emerged as an influential factor in the poor prognosis of bladder tumors, as patients with high RAC3 expression exhibited a lower overall survival rate than those with low RAC3 expression.

CONCLUSION

Based on our results, RAC3 shows promise as both a marker for early diagnosis of bladder tumors and a potential therapeutic target.

Integration of multi-omics and clinical treatment data reveals bladder cancer therapeutic vulnerability gene combinations and prognostic risks

Background

Bladder cancer (BCa) is a common malignancy of the urinary tract. Due to the high heterogeneity of BCa, patients have poor prognosis and treatment outcomes. Immunotherapy has changed the clinical treatment landscape for many advanced malignancies, opening new avenues for the precise treatment of malignancies. However, effective predictors and models to guide clinical treatment and predict immunotherapeutic outcomes are still lacking.

Methods

We downloaded BCa sample data from The Cancer Genome Atlas to identify anti-PD-L1 immunotherapy-related genes through an immunotherapy dataset and used machine learning algorithms to build a new PD-L1 multidimensional regulatory index (PMRI) based on these genes. PMRI-related column-line graphs were constructed to provide quantitative tools for clinical practice. We analyzed the clinical characteristics, tumor immune microenvironment, chemotherapy response, and immunotherapy response of patients based on PMRI system. Further, we performed function validation of classical PMRI genes and their correlation with PD-L1 in BCa cells and screening of potential small-molecule drugs targeting PMRI core target proteins through molecular docking.

Results

PMRI, which consists of four anti-PD-L1 immunotherapy-associated genes (IGF2BP3, P4HB, RAC3, and CLK2), is a reliable predictor of survival in patients with BCa and has been validated using multiple external datasets. We found higher levels of immune cell infiltration and better responses to immunotherapy and cisplatin chemotherapy in the high PMRI group than in the low PMRI group, which can also be used to predict immune efficacy in a variety of solid tumors other than BCa. Knockdown of IGF2BP3 inhibited BCa cell proliferation and migration, and IGF2BP3 was positively correlated with PD-L1 expression. We performed molecular docking prediction for each of the core proteins comprising PMRI and identified 16 small-molecule drugs with the highest affinity to the target proteins.

Conclusions

Our PD-L1 multidimensional expression regulation model based on anti-PD-L1 immunotherapy-related genes can accurately assess the prognosis of patients with BCa and identify patient populations that will benefit from immunotherapy, providing a new tool for the clinical management of intermediate and advanced BCa.

Deciphering the significance of anoikis in bladder cancer and systematic analysis of S100A7 as a potential therapeutic target

BACKGROUND

Bladder cancer is an epidemic and life-threating urologic carcinoma. Anoikis is a unusual type of programmed cell death which plays a vital role in tumor survival, invasion and metastasis. Nevertheless, the relationship between anoikis and bladder cancer has not been understood thoroughly.

METHODS

We downloaded the transcriptome and clinical information of BLCA patients from TCGA and GEO databases. Then, we analyzed different expression of anoikis-related genes and established a prognostic model based on TCGA database by univariate Cox regression, lasso regression, and multivariate Cox regression. Then the Kaplan-Meier survival analysis and receiver operating characteristic (ROC) curves were performed. GEO database was used for external validation. BLCA patients in TCGA database were divided into two subgroups by non-negative matrix factorization (NMF) classification. Survival analysis, different gene expression, immune cell infiltration and drug sensitivity were calculated. Finally, we verified the function of S100A7 in two BLCA cell lines.

RESULTS

We developed a prognostic risk model based on three anoikis-related genes including TPM1, RAC3 and S100A7. The overall survival of BLCA patients in low-risk groups was significantly better than high-risk groups in training sets, test sets and external validation sets. Subsequently, the checkpoint and immune cell infiltration had significant difference between two groups. Then we identified two subtypes (CA and CB) through NMF analysis and found CA had better OS and PFS than CB. Besides, the accuracy of risk model was verified by ROC analysis. Finally, we identified that knocking down S100A7 gene expression restrained the proliferation and invasion of bladder cancer cells.

CONCLUSION

We established and validated a bladder cancer prognostic model consisting of three genes, which can effectively evaluate the prognosis of bladder cancer patients. Additionally, through cellular experiments, we demonstrated the significant role of S100A7 in the metastasis and invasion of bladder cancer, suggesting its potential as a novel target for future treatments.

A risk model based on lncRNA-miRNA-mRNA gene signature for predicting prognosis of patients with bladder cancer

OBJECTIVES

We aimed to analyze lncRNAs, miRNAs, and mRNA expression profiles of bladder cancer (BC) patients, thereby establishing a gene signature-based risk model for predicting prognosis of patients with BC.

METHODS

We downloaded the expression data of lncRNAs, miRNAs and mRNA from The Cancer Genome Atlas (TCGA) as training cohort including 19 healthy control samples and 401 BC samples. The differentially expressed RNAs (DERs) were screened using limma package, and the competing endogenous RNAs (ceRNA) regulatory network was constructed and visualized by the cytoscape. Candidate DERs were screened to construct the risk score model and nomogram for predicting the overall survival (OS) time and prognosis of BC patients. The prognostic value was verified using a validation cohort in GSE13507.

RESULTS

Based on 13 selected. lncRNAs, miRNAs and mRNA screened using L1-penalized algorithm, BC patients were classified into two groups: high-risk group (including 201 patients ) and low risk group (including 200 patients). The high-risk group's OS time ( hazard ratio [HR], 2.160; 95% CI, 1.586 to 2.942; P= 5.678e-07) was poorer than that of low-risk groups' (HR, 1.675; 95% CI, 1.037 to 2.713; P= 3.393 e-02) in the training cohort. The area under curve (AUC) for training and validation datasets were 0.852. Younger patients (age ⩽ 60 years) had an improved OS than the patients with advanced age (age > 60 years) (HR 1.033, 95% CI 1.017 to 1.049; p= 2.544E-05). We built a predictive model based on the TCGA cohort by using nomograms, including clinicopathological factors such as age, recurrence rate, and prognostic score.

CONCLUSIONS

The risk model based on 13 DERs patterns could well predict the prognosis for patients with BC.

TGF-β-regulated different iron metabolism processes in the development and cisplatin resistance of ovarian cancer

The impact of different iron metabolism processes (DIMP) on ovarian cancer remains unclear. In this study, we employed various gene chips and databases to investigate the role of DIMP in the initiation and development of ovarian cancer. cBioPortal was used to determine mutations in DIMP-associated genes in ovarian cancer. Kaplan-Meier plotter was used to examine the influence of DIMP on the prognosis of ovarian cancer. By analyzing 1669 serous ovarian cancer cases, we identified a range of mutations in iron metabolism genes, notably in those coding for the transferrin receptor (19%), melanotransferrin (19%), and ceruloplasmin (10%) in the iron import process, and glucose-6-phosphate isomerase (9%), hepcidin antimicrobial peptide (9%), metal regulatory transcription factor 1 (8%), and bone morphogenetic protein 6 (8%) in the iron regulation process. Compared to the unaltered group, the group with gene alterations exhibited a higher tumor mutation burden count (43 vs. 54) and more advanced histologic grade (78.19% vs. 87.90%). Compared to the normal ovarian counterparts, a reduction in expression was observed in 9 out of the 14 genes involved in iron utilization and 4 out of the 5 genes involved in iron export in ovarian cancer; in contrast, an increase in expression was observed in 2 out of the 3 genes involved in iron storage in ovarian cancer. Furthermore, in cisplatin-resistant cells compared to cisplatin-sensitive ones, the expression of all genes in iron storage and 13 out of 14 genes in iron import was decreased, while that of 8 out of the 10 genes in iron utilization was increased. In addition, survival curve analysis indicated that a higher expression in the majority of genes in the iron import process (12/21), or a reduced expression in most genes in the iron export process (4/5) correlated with poor progression-free survival. Additionally, TGF-β could regulate the expression of most iron metabolism-associated genes; particularly, expression of genes involved in the iron storage process (2/2) was inhibited after TGF-β1 or TGF-β2 treatment. In conclusion, DIMP plays multifaceted roles in the initiation, chemo-resistance, and prognosis of ovarian cancer. Therapeutically targeting DIMP may pave the way for more tailored treatment approaches for ovarian cancer.

Prognostic related gene index for predicting survival and immunotherapeutic effect of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common malignant liver tumor. It is an aggressive disease with high mortality rate. In this study, we investigated a new prognosis-related gene index (PRGI) that can predict the survival and efficacy of immunotherapy in patients with HCC. RNA-seq data and clinical data of HCC samples were obtained from the cancer genome atlas and ICGC databases. Prognosis-related genes were obtained using log-rank tests and univariate Cox proportional hazards regression. Univariate and multivariate analyses were performed on the overall survival rate of patients with prognosis-related genes and multiple clinicopathological factors, and a nomogram was constructed. A PRGI was then constructed based on least absolute shrinkage and selection operator or multivariate Cox Iterative Regression. The possible correlation between PRGI and immune cell infiltration or immunotherapy efficacy was discussed. Eight genes were identified to construct the PRGI. PRGI can predict the infiltration of immune cells into the tumor microenvironment of HCC and the response to immunotherapy. PRGI can accurately predict the survival rate of patients with HCC, reflect the immune microenvironment, and predict the efficacy of immunotherapy.

Role of the membrane-spanning 4A gene family in lung adenocarcinoma

Lung adenocarcinoma, which is the second most prevalent cancer in the world, has a poor prognosis and a low 5-year survival rate. The MS4A protein family is crucial to disease development and progression, particularly for cancers, allergies, metabolic disorders, autoimmune diseases, infections, and neurodegenerative disorders. However, its involvement in lung adenocarcinoma remains unclear. In this study, we found that 11 MS4A family genes were upregulated or downregulated in lung adenocarcinoma. Furthermore, we described the genetic variation landscape of the MS4A family in lung adenocarcinoma. Notably, through functional enrichment analysis, we discovered that the MS4A family is involved in the immune response regulatory signaling pathway and the immune response regulatory cell surface receptor signaling pathway. According to the Kaplan-Meier curve, patients with lung adenocarcinoma having poor expression of MS4A2, MS4A7, MS4A14, and MS4A15 had a low overall survival rate. These four prognostic genes are substantially associated with immune-infiltrating cells, and a prognosis model incorporating them may more accurately predict the overall survival rate of patients with lung adenocarcinoma than current models. The findings of this study may offer creative suggestions and recommendations for the identification and management of lung adenocarcinoma.

Screening of immunotherapy-related genes in bladder cancer based on GEO datasets

Background

As one of the most prevalent genitourinary cancers, bladder cancer (BLCA) is associated with high morbidity and mortality. Currently, limited indicators are available for early detection and diagnosis of bladder cancer, and there is a lack of specific biomarkers for evaluating the prognosis of BLCA patients. This study aims to identify critical genes that affect bladder cancer immunity to improve the diagnosis and prognosis of bladder cancer and to identify new biomarkers and targets for immunotherapy.

Methods

Two GEO datasets were used to screen differentially expressed genes (DEGs). The STRING database was used to construct a protein-protein interaction network of DEGs, and plug-in APP CytoHubba in Cytoscape was used to identify critical genes in the network. GO and KEGG analyses explored the functions and pathways of differential gene enrichment. We used GEPIA to validate the expression of differential genes, their impact on patient survival, and their relationship to clinicopathological parameters. Additionally, hub genes were verified using qRT-PCR and Western blotting. Immune infiltration analysis and multiple immunohistochemistry reveal the impact of Hub genes on the tumor microenvironment.

Result

We screened out 259 differential genes, and identified 10 key hub genes by the degree algorithm. Four genes (ACTA2, FLNA, TAGLN, and TPM1) were associated with overall or disease-free survival in BLCA patients and were significantly associated with clinical parameters. We experimentally confirmed that the mRNA and protein levels of these four genes were significantly decreased in bladder cancer cells. Immunoassays revealed that these four genes affect immune cell infiltration in the tumor microenvironment; they increased the polarization of M2 macrophages.

Conclusion

These four genes affect the tumor microenvironment of bladder cancer, provide a new direction for tumor immunotherapy, and have significant potential in the diagnosis and prognosis of bladder cancer.

A novel immune score model predicting the prognosis and immunotherapy response of breast cancer

Breast cancer (BC) is one of the most common malignancies. However, the existing pathological grading system cannot accurately and effectively predict the survival rate and immune checkpoint treatment response of BC patients. In this study, based on The Cancer Genome Atlas (TCGA) database, a total of 7 immune-related genes (IRGs) were screened out to construct a prognostic model. Subsequently, the clinical prognosis, pathological characteristics, cancer-immunity cycle, tumour immune dysfunction and exclusion (TIDE) score, and immune checkpoint inhibitor (ICI) response were compared between the high- and low-risk groups. In addition, we determined the potential regulatory effect of NPR3 on BC cell proliferation, migration, and apoptosis. The model consisting of 7 IRGs was an independent prognostic factor. Patients with lower risk scores exhibited longer survival times. Moreover, the expression of NPR3 was increased but the expression of PD-1, PD-L1, and CTLA-4 was decreased in the high-risk group compared to the low-risk group. In addition, compared with si-NC, si-NPR3 suppressed proliferation and migration but promoted apoptosis in both MDA-MB-231 and MCF-7 cells. This study presents a model for predicting survival outcomes and provides a strategy to guide effective personalized immunotherapy in BC patients.

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.

Clinical significance and integrative analysis of the cuproptosis-associated genes in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSC) is a kind of malignant tumor originating from the oropharynx, larynx, nasopharynx and oral cavity. The incidence of HNSC is increasing and it is the sixth malignant tumor in the world at present. "Cuprotosis" is a novel cuper-dependent cell death mode that is closely related to mitochondrial respiration. Tumorigenesis is closely related to the dysregulation of cell death. However, the relationship between cuprotosis and HNSC remains unclear. Here, we investigated the association between 10 cuprotosis-associated genes (CAGs) and HNSC using multi-omics public data. We found that CAGs had abnormal expression and significant genetic changes in HNSC, especially CDKN2A with 54% mutation rate. Expression of CAGs significantly correlates with the prognosis of HNSC patients. Moreover, the CAGs expression is correlated with the immune checkpoints expression and immune cells infiltration. These CAGs expression was associated with multiple drugs sensitivity of cancer cells, such as cisplatin and docetaxel. These findings indicate that CAGs are likely to serve an essential role in the diagnosis, prognosis, immunotherapy and drug therapy prediction of HNSC.

PDGF-D-induced immunoproteasome activation and cell-cell interactions

Platelet-derived growth factor-D (PDGF-D) is abundantly expressed in ocular diseases. Yet, it remains unknown whether and how PDGF-D affects ocular cells or cell-cell interactions in the eye. In this study, using single-cell RNA sequencing (scRNA-seq) and a mouse model of PDGF-D overexpression in retinal pigment epithelial (RPE) cells, we found that PDGF-D overexpression markedly upregulated the key immunoproteasome genes, leading to increased antigen processing/presentation capacity of RPE cells. Also, more than 6.5-fold ligand-receptor pairs were found in the PDGF-D overexpressing RPE-choroid tissues, suggesting markedly increased cell-cell interactions. Moreover, in the PDGF-D-overexpressing tissues, a unique cell population with a transcriptomic profile of both stromal cells and antigen-presenting RPE cells was detected, suggesting PDGF-D-induced epithelial-mesenchymal transition of RPE cells. Importantly, administration of ONX-0914, an immunoproteasome inhibitor, suppressed choroidal neovascularization (CNV) in a mouse CNV model in vivo. Together, we show that overexpression of PDGF-D increased pro-angiogenic immunoproteasome activities, and inhibiting immunoproteasome pathway may have therapeutic value for the treatment of neovascular diseases.

Comprehensive analysis of the prognosis and immune infiltrates for the BET protein family reveals the significance of BRD4 in glioblastoma multiforme

Background: Glioblastoma multiforme (GBM) is the most common and invasive primary central nervous system tumor. The prognosis after surgery, radiation and chemotherapy is very poor. Bromodomain (BRD) proteins have been identified in oncogenic rearrangements, and play a key role in the development of multiple cancers. However, the relationship between BET proteins and prognosis of GBM are still worth exploring, and the distinct functions of BET proteins and tumor immunology in GBM have not been fully elucidated. Therefore, it is particularly important to develop effective biomarkers to predict the prognosis of GBM patients. Methods: Metascape, David, Kaplan-Meier Plotter, Oncomine, GEPIA, TCGA, TIMER, and LinkedOmics databases were used to assess the expression and prognosis for BET proteins in GBM. ROC analysis of risk model was established to identify the correlation between BET genes and overall survival in GBM patients. TIMER and GEPIA databases were used to comprehensively investigate the correlation between BET genes and tumor immune infiltration cells. Moreover, the image of immunohistochemistry staining of BET proteins in normal tissue and tumor tissue were retrived from the HPA database. In addition, differential analysis and pathway enrichment analysis of BRD4 gene expression profile were also carried out. Finally, immune-fluorescence and Western blot were used to clarify the expression of BRD4 in GBM cells. Results: Bioinformatics analysis showed that the expression levels of BET genes in GBM may play an important role in oncogenesis. Specifically, bioinformatic and immunohistochemistry analysis showed that BRD4 protein was more highly expressed in tumor tissues than that in normal tissues. The high expression of BRD4 was associated with poor prognosis in GBM. The expression of BET genes were closely related to the immune checkpoint in GBM. The correlation effect of BRD4 was significantly higher than other BET genes, which represented negative correlation with immune checkpoint. The expression of BRD4 was positively associated with tumor purity, and negatively associated with immune infiltration abundance of macrophage, neutrophil and CD8⁺ T-cell, respectively. Cox analysis showed that the model had good survival prediction and prognosis discrimination ability. In addition, the expression levels of BRD4 protein was significantly higher in U-251 MG cells than that in normal cells, which was consistent with the results of bioinformatics data. Conclusion: This study implied that BRD4 could be hopeful prognostic biomarker in GBM. The increased expression of BRD4 may act as a molecular marker to identify GBM patients with high-risk subgroups. BRD4 may be a valuable prognostic biomarker, and a potential target of precision therapy against GBM.

A risk score for the prognosis prediction of the muscle-invasive bladder cancer patients who received gemcitabine plus cisplatin chemotherapy

To develop an individualized gene-based risk score to predict the prognosis of muscle-invasive bladder cancer (MIBC) patients who received GC regimens. We downloaded transcriptome profiling data and clinical information from the Cancer Genome Atlas (TCGA) database. We identified 1854 survival-associated genes and then constructed the risk score based on six special genes selected from the survival-associated genes. We divided patients into high-risk and low-risk groups according to the median risk score. High-risk patients have significantly poorer overall survival than low-risk patients (log-rank test chi-square = 38.08, p = 7e-10, C-index = 0.785, se = 0.032). The risk score was evaluated by Kaplan-Meier survival curve, time-dependent ROC curves, and C-index. Multivariate Cox regression and nomogram suggested that the risk score was an independent prognostic indicator. Gene set enrichment analysis indicated that the survival-associated genes were significantly enriched in immune-related terms. Among six special genes, CHPF2, TRAV26-2, and BTF3P12 were found to be immune-related genes. In conclusion, our risk score provided an indicator to predict the prognosis of MIBC patients who received GC regimens and potential immunotherapeutic targets for MIBC.

Construction of cuproptosis-related gene signature to predict the prognosis and immunotherapy efficacy of patients with bladder cancer through bioinformatics analysis and experimental validation

Background: A new form of cell death, copper-dependent cell death (termed cuproptosis), was illustrated in a recent scientific study. However, the biological function or prognostic value of cuproptosis regulators in bladder cancer (BLCA) remains unknown. Materials and Methods: Sequencing data obtained from BLCA samples in TCGA and GEO databases were preprocessed for analysis. Biological function and immune cell infiltration levels evaluated by gene set variation analysis (GSVA) were employed to calculate enrichment scores. Iteration least absolute shrinkage and selection operator (LASSO) and COX regression model were employed to select feature genes and construct a novel cuproptosis-related (CR) score signature. The genomics of drug sensitivity in cancer (GDSC) and tumor immune dysfunction and exclusion (TIDE) analysis were used to predict the chemotherapy and immunotherapy efficacy for BLCA patients. The relative expression of the genes involved in the signature was also verified by real-time quantitative PCR (qRT-PCR) in cell lines and tissues. Results: Expression abundance and the prognostic value of cuproptosis regulators proved that cuproptosis might play a vital part in the carcinogenesis of BLCA. GSVA revealed that cuproptosis regulators might be associated with metabolism and metastasis-related pathways such as TGF-β, protein secretion, oxidative Phosphorylation, MYC targets, MTORC1, and adipogenesis pathways. CR scores could predict the prognosis and evaluate the chemotherapy and immunotherapy efficacies of BLCA. CR scores were positively correlated with EMT, MYC, MTORC1, HEDGEHOG, and E2F signaling pathways; meanwhile, they were negatively correlated with several immune cell infiltration levels such as CD8⁺ T cells, γδT cells, and activated dendritic cells. Several GEO datasets were used to validate the power of prognostic prediction, and a nomogram was also established for clinical use. The expressions of DDX10, RBM34, and RPL17 were significantly higher in BLCA cell lines and tissues in comparison with those in the corresponding normal controls. Conclusion: Cuproptosis might play an essential role in the progression of BLCA. CR scores could be helpful in the investigation of prognostic prediction and therapeutic efficacy and could make contributions to further studies in BLCA.

Novel T-cell signature based on cell pair algorithm predicts survival and immunotherapy response for patients with bladder urothelial carcinoma

Background

T-cell–T-cell interactions play important roles in the regulation of T-cells’ cytotoxic function, further impacting the anti-tumor efficacy of immunotherapy. There is a lack of comprehensive studies of T-cell types in bladder urothelial carcinoma (BLCA) and T-cell-related signatures for predicting prognosis and monitoring immunotherapy efficacy.

Methods

More than 3,400 BLCA patients were collected and used in the present study. The ssGSEA algorithm was applied to calculate the infiltration level of 19 T-cell types. A cell pair algorithm was applied to construct a T-cell-related prognostic index (TCRPI). Survival analysis was performed to measure the survival difference across TCRPI-risk groups. Spearman’s correlation analysis was used for relevance assessment. The Wilcox test was used to measure the expression level difference.

Results

Nineteen T-cell types were collected; 171 T-cell pairs (TCPs) were established, of which 26 were picked out by the least absolute shrinkage and selection operator (LASSO) analysis. Based on these TCPs, the TCRPI was constructed and validated to play crucial roles in survival stratification and the dynamic monitoring of immunotherapy effects. We also explored several candidate drugs targeting TCRPI. A composite TCRPI and clinical prognostic index (CTCPI) was then constructed, which achieved a more accurate estimation of BLCA’s survival and was therefore a better choice for prognosis prediction in BLCA.

Conclusions

All in all, we constructed and validated TCRPI based on cell pair algorithms in this study, which might put forward some new insights to increase the survival estimation and clinical response to immune therapy for individual BLCA patients and contribute to the personalized precision immunotherapy strategy of BLCA.

Distinct immune and inflammatory response patterns contribute to the identification of poor prognosis and advanced clinical characters in bladder cancer patients

Due to the molecular heterogeneity, most bladder cancer (BLCA) patients show no pathological responses to immunotherapy and chemotherapy yet suffer from their toxicity. This study identified and validated three distinct and stable molecular clusters of BLCA in cross-platform databases based on personalized immune and inflammatory characteristics. H&E-stained histopathology images confirmed the distinct infiltration of immune and inflammatory cells among clusters. Cluster-A was characterized by a favorable prognosis and low immune and inflammatory infiltration but showed the highest abundance of prognosis-related favorable immune cell and inflammatory activity. Cluster-B featured the worst prognosis and high immune infiltration, but numerous unfavorable immune cells exist. Cluster-C had a favorable prognosis and the highest immune and inflammatory infiltration. Based on machine learning, a highly precise predictive model (immune and inflammatory responses signature, IIRS), including FN1, IL10, MYC, CD247, and TLR2, was developed and validated to identify the high IIRS-score group that had a poor prognosis and advanced clinical characteristics. Compared to other published models, IIRS showed the highest AUC in 5 years of overall survival (OS) and a favorable predictive value in predicting 1- and 3- year OS. Moreover, IIRS showed an excellent performance in predicting immunotherapy and chemotherapy's response. According to immunohistochemistry and qRT-PCR, IIRS genes were differentially expressed between tumor tissues with corresponding normal or adjacent tissues. Finally, immunohistochemical and H&E-stained analyses were performed on the bladder tissues of 13 BLCA patients to further demonstrate that the IIRS score is a valid substitute for IIR patterns and can contribute to identifying patients with poor clinical and histopathology characteristics. In conclusion, we established a novel IIRS depicting an IIR pattern that could independently predict OS and acts as a highly precise predictive biomarker for advanced clinical characters and the responses to immunotherapy and chemotherapy.

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

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

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

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

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

Identification of tumor microenvironment-related signature for predicting prognosis and immunotherapy response in patients with bladder cancer

The tumor microenvironment (TME) not only provides fertile soil for tumor growth and development but also widely involves immune evasion as well as the resistance towards therapeutic response. Accumulating interest has been attracted from the biological function of TME to its effects on patient outcomes and treatment efficacy. However, the relationship between the TME-related gene expression profiles and the prognosis of bladder cancer (BLCA) remains unclear. The TME-related genes expression data of BLCA were collected from The Cancer Genome Atlas (TCGA) database. NFM algorithm was used to identify the distinct molecular pattern based on the significantly different TME-related genes. LASSO regression and Cox regression analyses were conducted to identify TME-related gene markers related to the prognosis of BLCA and to establish a prognostic model. The predictive efficacy of the risk model was verified through integrated bioinformatics analyses. Herein, 10 TME-related genes (PFKFB4, P4HB, OR2B6, OCIAD2, OAS1, KCNJ15, AHNAK, RAC3, EMP1, and PRKY) were identified to construct the prognostic model. The established risk scores were able to predict outcomes at 1, 3, and 5 years with greater accuracy than previously known models. Moreover, the risk score was closely associated with immune cell infiltration and the immunoregulatory genes including T cell exhaustion markers. Notably, the predictive power of the model in immunotherapy sensitivity was verified when it was applied to patients with metastatic urothelial carcinoma (mUC) undergoing immunotherapy. In conclusion, TME risk score can function as an independent prognostic biomarker and a predictor for evaluating immunotherapy response in BLCA patients, which provides recommendations for improving patients’ response to immunotherapy and promoting personalized tumor immunotherapy in the future.

HYAL3 as a potential novel marker of BLCA patient prognosis

BACKGROUND

It has been previously demonstrated that hyaluronan (HA) potentially regulates the initiation and propagation of bladder cancer (BLCA). HYAL3 encodes hyaluronidase and is a potential therapeutic target for BLCA. We aimed to explore the role that HYAL3 plays in BLCA pathogenesis.

METHODS

HYAL3 expression in BLCA specimens was analyzed using The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) cohort as well as confirmed in cell lines and The Human Protein Atlas. Then, associations between HYAL3 expression and clinicopathological data were analyzed using survival curves and receiver-operating characteristic (ROC) curves. The functions of HYAL3 were further dissected using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and the protein-protein interaction network. Finally, we harnessed the Tumor IMmune Estimation Resource and Gene Expression Profiling Interactive Analysis to obtain correlations between HYAL3 expression, infiltrating immunocytes, and the corresponding immune marker sets.

RESULTS

HYAL3 expression varied greatly between many types of cancers. In addition, a higher HYAL3 expression level predicted a poor overall survival (OS) in both TCGA-BLCA and GEO gene chips (P < 0.05). HYAL3 also exhibited an acceptable diagnostic ability for the pathological stage of BLCA (area under the receiver-operating characteristic curve = 0.769). Furthermore, HYAL3 acted as an independent prognostic factor in BLCA patients and correlated with the infiltration of various types of immunocytes, including B cells, CD8⁺ T cells, cytotoxic cells, T follicular helper cells, and T helper (Th) 2 cells.

CONCLUSION

HYAL3 might serve as a potential biomarker for predicting poor OS in BLCA patients and correlated with immunocyte infiltration in BLCA.

Hypomethylated gene RAC3 induces cell proliferation and invasion by increasing FASN expression in endometrial cancer

BACKGROUND

Endometrial cancer (EC) is one of the most prevalent gynecological cancers with a 5-year survival rate of 20-60%. Feasible prognostic molecular biomarkers of EC are necessary for accurate prediction of EC prognosis.

METHODS

RAC3 is a member of the Rho GTPases. Public databases including Gene Expression Profiling Interactive Analysis (GEPIA2), Tumor Immune Estimation Resource (TIMER), LinkedOmics, Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), TISIDB and cBioPortal were employed to analyze the differential expression, clinicopathologic characteristics, functional networks, immune cell infiltrates and genetic alteration of RAC3 in EC patients.

RESULTS

RAC3 expression was elevated in EC patients analyzed by TIMER and GEPIA. Overexpression of RAC3 was obviously correlated with clinical stage, histological type, histological grade and DNA hypomethylation. Patients with high RAC3 expression displayed poor overall survival. Functional enrichment analysis showed that RAC3 was involved in translational initiation, DNA replication and mRNA processing. RAC3 expression was negatively associated with infiltrating levels of B cells, CD8+ T cells, macrophages and dendritic cells in EC. Experiments in vitro showed that RAC3 was upregulated in EC tissues and cell lines, and RAC3 induced cell proliferation and invasion by increasing fatty acid synthase (FASN) expression.

CONCLUSION

High expression of RAC3iscorrelated with poor prognosis and low infiltration of immune cells in EC. RAC3 promotes cell proliferation and invasion via FASN. These results demonstrate thatRAC3 functions as an EC oncogene and reveal its underlying mechanism in EC progression, suggesting that RAC3 may serve as a potential therapeutic target in EC.

Comprehensive Analysis of the Expression and Prognostic Value of LMAN2 in HER2+ Breast Cancer

Lectin, Mannose Binding 2 (LMAN2) encodes a type I transmembrane lectin that shuttles between the plasma membrane, the Golgi apparatus, and the endoplasmic reticulum. However, its expression, prognosis, and function in invasive breast carcinoma remain unknown. Nine databases were consulted to evaluate LMAN2 expression and prognosis in breast cancer. The possible function of LMAN2 in breast cancer was investigated in the Human Cell Landscape (HCL) database, Gene Regulatory Network database (GRNdb), and CancerSEA database. Moreover, N6-methyladenosine (m6A) modifications were analyzed using the RMBase v2.0 and M6A2Target databases. Seven databases were then used to analyze the potential action mechanisms of LMAN2. Our findings suggest that LMAN2, which is expressed at a high level in breast cancer, is linked to an unfavorable prognosis. Therefore, LMAN2 has the potential to be utilized as a treatment target in breast cancer. Furthermore, the single-cell analysis illustrated that LMAN2 expression had a positive link to breast cancer stemness, proliferation, metastasis, and differentiation. Moreover, m6A modifications were found in the LMAN2 gene. Consequently, modifications to m6A methylation may influence LMAN2 expression, which is associated with the homologous recombination (HR) in its DNA damage repair pathway .

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

Aim

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

Methods

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

Results

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

Conclusions

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

Comprehensive analysis of expression signature and immune microenvironment signature of biomarker Endothelin Receptor Type A in stomach adenocarcinoma

Background: EDNRA (Endothelin Receptor Type A) is closely associated with tumor progression in many tumor types. However, the functional mechanism of EDNRA in stomach adenocarcinoma (STAD) remains to be elucidated.

Methods: ENDRA expression levels in STAD were assessed. A Receiver Operating Characteristic (ROC) curve was constructed to measure the diagnostic value of EDNRA. The correlation between ENDRA expression levels and patient clinical-pathological characteristics was analyzed. The survival and prognostic significance were validated using Kaplan-Meier and Cox regression and confirmed by the immunohistochemistry cohorts. Differentially expressed genes of EDNRA in STAD were determined, and EDNRA related functional enrichment and biological pathways involved in STAD were obtained by Gene-Set Enrichment Analysis (GSEA). The correlation between EDNRA expression in STAD and immune cell infiltration was assessed using the CIBERSORT and Spearman correlation analysis, and the correlation between EDNRA and TMB, MSI, IC50, and immune checkpoints was examined.

Results: EDNRA expression was significantly higher in STAD than in normal tissues (P < 0.001) and associated with worse overall survival (OS). EDNRA expression was significantly associated with T stage, histological type, histologic grade, and TP53 status. Cox regression analysis revealed that primary therapy outcome, age, tumor status, and EDNRA were independent prognostic factors for OS. Multivariate analysis revealed that EDNRA expression, tumor status, age, and primary therapy outcome influenced patient prognosis. GSEA was significantly enriched in several pathways and biological processes, which include Immunoregulatory, Hedgehog, WNT, PI3K-AKT.NK cells, Tem, macrophages, and mast cells were substantially positively correlated with EDNRA expression in the STAD microenvironment. Notably, high EDNRA expression may promote M2 macrophages to block PD-1-mediated immunotherapy and induce immunosuppression. In addition, patients with high expression of EDNRA might be resistant to the treatment of several anti-tumor drugs.

Conclusion: Our results suggest that EDNRA was closely related to clinicopathologic characteristics, poor prognosis, and promoted macrophage differentiation and synergistic role in immunosuppression.

circ-0007707/miR-429/PDGFD Pathway Regulates the Progression of Gastric Cancer by Modulating the Immune-Gene Signature

Background

Immunotherapy is an important treatment modality for gastric cancer, therefore, it is crucial to understand the regulators of the tumor microenvironment in gastric cancer. Numerous studies have shown that noncoding RNAs have a critical status in the tumor progression, and the influence of competing endogenous RNA (ceRNA) networks on gastric adenocarcinoma has been widely discussed over the years, but the connection between ceRNA networks and the immune microenvironment of cancer is unclear. This study was aimed at exploring how ceRNA networks influence the prognosis of patients with gastric cancer by modulating the tumor microenvironment.

Methods

The Gene Expression Omnibus was analyzed to obtain differential expression matrixes of the noncoding RNAs (circular RNAs (circRNAs), microRNAs (miRNAs)), and mRNAs. The Circular RNA Interactome web tool and TargetScan were applied to determine the miRNA binding sites of the circRNAs and miRNA target genes. The Cancer Genome Atlas provided prognostic genes for gastric cancer, and Cytoscape created the ceRNA networks. Real-time quantitative reverse transcription polymerase chain reaction and western blot assay were adopted to find out how the ceRNA network regulates the expression of the hub gene. Additionally, the TISIDB and TIMER databases were used to assess the link between the hub gene and immunotherapy, with TISIDB providing the immune genes that are coexpressed with the hub gene. Furthermore, the immune-gene signature was constructed by using Cox regression analysis. Moreover, the nomogram, which could predict the prognostic role of gastric cancer patients was created on the basis of the immune-gene signature.

Results

In gastric cancer, the circ-0007707/miR-429/PDGFD pathway had a differential expression. The results demonstrated that the pathway could regulate the progression and immune microenvironment of gastric cancer by modulating the immune-gene signature, which included two immune genes (TAB1 and CXCR4). Moreover, the low-risk group patients had better survival.

Conclusion

The circ-0007707/miR-429/PDGFD pathway may play a regulatory role in the progression and prognosis of gastric cancer by interfering with the tumor microenvironment, and the PDGFD-related immune-gene signature could be considered a moderator of prognostic factor for gastric cancer and to guide immunotherapy programs.

Development and verification of a hypoxia- and immune-associated prognosis signature for esophageal squamous cell carcinoma

BACKGROUND

Esophageal cancer is one of the most common gastrointestinal malignancies worldwide, with high morbidity and mortality in China. The clinical importance of the interaction between hypoxia and immune status in the tumor microenvironment has been established in esophageal squamous cell carcinoma (ESCC). This study aims to develop a new hypoxia- and immune-based gene signature to predict the survival of ESCC patients.

METHODS

The RNA-sequencing and clinical data of 173 cases of ESCC and 271 normal tissues were obtained from The Cancer Genome Atlas (TCGA) data portal and the Genotype-Tissue Expression (GTEx) database. Hypoxia-related genes (HRGs) and immune-related genes (IRGs) were retrieved from publicly shared data. Differentially expressed gene (DEG) analyses were carried out by the DESeq2 method using the edgeR package in R. Based on the intersection of the DEGs and HRGs/IRGs, differentially expressed HRGs (DEHRGs) and differentially expressed IRGs (DEIRGs) were obtained. DEHRGs and DEIRGs associated with prognosis were evaluated using univariate Cox proportional hazards analysis. A prognostic risk score model was constructed according to the genes acquired through Cox regression. Univariate analysis and Cox proportional hazards analysis were used to determine the independent prognostic factors related to prognosis. A nomogram was developed to predict the 1-, 2-, and 3-year overall survival (OS) probability.

RESULTS

A total of 73 intersecting genes were obtained as DEHRGs and a total of 548 intersecting genes were obtained as DEIRGs. The risk score was established using 8 genes (FABP7, TLR1, SYTL1, APLN, OSM, EGFR, IL17RD, MYH9) acquired from univariate Cox analysis. Based on this 8-gene-based risk score, a risk prognosis classifier was constructed to classify the samples into high- and low-risk groups according to the median risk score. The nomogram model was constructed to predict the OS of ESCC patients.

CONCLUSIONS

The hypoxia- and immune-based gene signature might serve as a prognostic classifier for clinical decision-making regarding individualized management, follow-up plans, and treatment strategies for ESCC patients.

A novel immune-related gene signature predicting survival in sarcoma patients

Sarcomas are a heterogeneous group of rare mesenchymal tumors. The migration of immune cells into these tumors and the prognostic impact of tumor-specific factors determining their interaction with these tumors remain poorly understood. The current risk stratification system is insufficient to provide a precise survival prediction and treatment response. Thus, valid prognostic models are needed to guide treatment. This study analyzed the gene expression and outcome of 980 sarcoma patients from seven public datasets. The abundance of immune cells and the response to immunotherapy was calculated. Immune-related genes (IRGs) were screened through a weighted gene co-expression network analysis (WGCNA). A least absolute shrinkage and selection operator (LASSO) Cox regression was used to establish a powerful IRG signature predicting prognosis. The identified IRG signature incorporated 14 genes and identified high-risk patients in sarcoma cohorts. The 14-IRG signature was identified as an independent risk factor for overall and disease-free survival. Moreover, the IRG signature acted as a potential indicator for immunotherapy. The nomogram based on the risk score was built to provide a more accurate survival prediction. The decision tree with IRG risk score discriminated risk subgroups powerfully. This proposed IRG signature is a robust biomarker to predict outcomes and treatment responses in sarcoma patients.

Prognostic signature of esophageal adenocarcinoma based on pyroptosis-related genes

Background

The role of pyroptosis-related genes (PRGs) in esophageal adenocarcinoma (EAC) remains unknown.

Methods

In this study, the first PRGs prognostic signature (PPS) of EAC was constructed based on the results of multivariate stepwise Cox regression analysis. Based on 1,047 samples of EAC and normal esophagus (NE), differentially expressed PRGs were selected for the establishment of the PPS. The discrimination effect of this PPS was detected by receiver operating characteristic curves, and the prognosis value of this PPS was determined through Cox regression analysis and Kaplan-Meier curves. Net benefits of the EAC patients from the nomogram (constructed based on the PPS and some clinical parameters) were assessed via decision curve analysis. The potential molecular mechanism of the PPS in EAC was explored via gene set enrichment analysis. The ability of PPS to distinguish EAC and NE was evaluated based on the results of summary receiver operating characteristic curves.

Results

The significant prognostic value of PPS can be observed at all of the training cohort, test cohort, and validation cohort, such as its independent risk role in the prognosis of the EAC patients (hazard ratio > 0; 95% CI not including 0). The positive net benefits of the nomogram for the EAC patients can be detected via decision curve analysis, and the potential molecular mechanism of the PPS in EAC is likely related to cell pyroptosis. Last, some of the PRGs (particularly CASP5) included in this PPS specifically support its feasibility for identifying EAC (area under the curves > 0.7).

Conclusions

The construction of this PPS in EAC enhances the present understanding of the relationship between PRGs and EAC, thus representing a novel approach to the clinical identification and management of EAC based on PRGs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01196-x.