Identification of a tumor microenvironment-related seven-gene signature for predicting prognosis in bladder cancer

Zhi, Wang; Tu, Lei; Chen, Minfeng; Tong, Shiyu

doi:10.1186/s12885-021-08447-7

Cited by 22 publications

(13 citation statements)

References 41 publications

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“…We compared the prediction models of our eight-gene signature with other models to demonstrate the predictive performance of our model, including models of the identified 3-gene ( 25 ), 5-gene ( 26 ), and 7-gene signature ( 27 ). We also computed RS for every sample by multivariate Cox regression analysis.…”

Section: Resultsmentioning

confidence: 99%

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Identification of a Novel Tumor Microenvironment Prognostic Signature for Bladder Urothelial Carcinoma

Pei

Liu

et al. 2022

Front. Oncol.

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BackgroundThe tumor microenvironment (TME) regulates the proliferation and metastasis of solid tumors and the effectiveness of immunotherapy against them. We investigated the prognostic role of TME-related genes based on transcriptomic data of bladder urothelial carcinoma (BLCA) and formulated a prediction model of TME-related signatures.MethodsMolecular subtypes were identified using the non-negative matrix factorization (NMF) algorithm based on TME-related genes from the TCGA database. TME-related genes with prognostic significance were screened with univariate Cox regression analysis and lasso regression. Nomogram was developed based on risk genes. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used for inner and outer validation of the model. Risk scores (RS) of patients were calculated and divided into high-risk group (HRG) and low-risk group (LRG) to compare the differences in clinical characteristics and PD-L1 treatment responsiveness between HRG and LRG.ResultsWe identified two molecular subtypes (C1 and C2) according to the NMF algorithm. There were significant differences in overall survival (OS) (p<0.05), progression-free survival (PFS) (p<0.05), and immune cell infiltration between the two subtypes. A total of eight TME-associated genes (CABP4, ZNF432, BLOC1S3, CXCL11, ANO9, OAS1, FBN2, CEMIP) with independent prognostic significance were screened to build prognostic risk models. Age (p<0.001), grade (p<0.001), and RS (p<0.001) were independent predictors of survival in BLCA patients. The developed RS nomogram was able to predict the prognosis of BLCA patients at 1, 3, and 5 years more potentially than the models of other investigators according to ROC and DCA. RS showed significantly higher values (p = 0.047) in patients with stable disease (SD)/progressive disease (PD) compared to patients with complete response (CR)/partial response (PR).ConclusionsWe successfully clustered and constructed predictive models for TME-associated genes and helped guide immunotherapy strategies.

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Section: Resultsmentioning

confidence: 99%

“…The ROC and DCA proved that they can exactly assess the outcome of patients. When we compared our nomogram with three other predictive genes signatures by Wang et al ( 27 ), Zhou et al ( 25 ), and Li et al ( 26 ). Our nomogram showed the highest C-index.…”

Section: Discussionmentioning

confidence: 99%

Identification of a Novel Tumor Microenvironment Prognostic Signature for Bladder Urothelial Carcinoma

Pei

Liu

et al. 2022

Front. Oncol.

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“…Genetic biomarkers would be viable to represent heterogeneity among BC, thus predicting the sensitivity of urothelial neoplasms tissues toward platinum. Previous studies have reported several prognostic gene signatures that are related to tumor microenvironment, immune cell in ltrating, unfolded protein response, and so on [39][40][41] . But signature that is associated with platinum-based chemotherapy resistance has not been recorded yet.…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of a Novel Prognostic Model Based on Platinum Resistance-Related Genes in Bladder Cancer

Hao

Wang

2022

Preprint

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Background: Bladder cancer (BC) is a heterogeneous disease with high recurrence rate. The depth of response to platinum-based chemotherapeutic agents in urothelial neoplasm tissues varies greatly. Biomarkers that have practical value in prognosis stratification and early determination of therapeutic effect are increasingly needed. Our study aimed to select a set of BC-related genes involved in both platinum resistance and survival, then use these genes to establish the prognostic model.Methods: Platinum resistance-related DEGs and tumorigenesis-related DEGs were identified. Among the intersection of them, 10 most predictive genes were acquired through Cox, lasso, and stepwise regressions followed by building a risk score model with their regression coefficients. Survival analysis and ROC plot were used to evaluate the predictive accuracy of our model. Combined with age and TMN stages, a nomogram was generated to create a graphical representation of survival rates at 1-, 3-, 5-, and 8-year in BC patients. The prognostic performance of risk score was also validated in three independent BC datasets including cisplatin-treated patients and a gastric cancer cohort with platinum-based chemotherapy. The potential mechanism of the gene-based model was explored by enrichment analysis.Results: PPP2R2B, TSPAN7, ATAD3C, SYT15, SAPCD1, AKR1B1, TCHH, AKAP12, AGLN3, and IGF2 were selected for our prognostic model. Patients in high- and low-risk groups exhibited a significant survival difference (HR = 2.7, p < 0.0001). The prognostic nomogram of predicting 3-year OS for BC patients could yield an AUC of 0.819. In the external validation dataset, the risk score also has a robust predictive ability. Conclusion: A prognostic model derived from platinum resistance-related genes was constructed, we confirmed its value in predicting platinum-based chemotherapy benefits and overall survival for BC patients. The model might assist in therapeutic decisions for bladder malignancy.Subjects: Urology, Oncology, Bioinformatics, Molecular Biology.

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“…In recent years, with the development of tumor immunology and the introduction of immunosuppressive agents in cancer treatment, the treatment of bladder cancer is expected to progress [8]. A large number of studies has analyzed the immune characteristics of BLCA patients from the perspective of immune infiltration [9][10][11]. However, there are still few studies on exploring new potential prognostic and immunotherapeutic biomarkers of BLCA with respect to tumor immune interaction.…”

Section: Introductionmentioning

confidence: 99%

Construction and validation of a gene signature related to bladder urothelial carcinoma based on immune gene analysis

2022

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Background This study developed a gene signature associated with a malignant and common tumor of the urinary system, the Bladder Urothelial Carcinoma (BLCA). Methods The Cancer Genome Atlas (TCGA) database was searched to obtain 414 BLCA samples and the expression spectra of 19 normal samples. Single-sample Gene Set Enrichment Analysis (ssGSEA) was conducted to determine the enrichment levels in the BLCA samples of the 29 immune genes. Unsupervised hierarchical clustering, gene set enrichment analysis (GSEA), single-factor Cox analysis, least absolute shrinkage and selection operator (LASSO) regression models, and GEO queues were used to determine the BLCA immune gene subtype, analyze the biological pathway differences between immune gene subtypes, determine the characteristic genes of BLCA associated with prognosis, identify the BLCA-related genes, and verify the gene signature, respectively. Results We identified two immune gene subtypes (immunity_L and immunity_H). The latter was significantly related to receptors, JAK STAT signaling pathways, leukocyte interleukin 6 generation, and cell membrane signal receptor complexes. Four characteristic genes (RBP1, OAS1, LRP1, and AGER) were identified and constituted the gene signature. Significant survival advantages, higher mutation frequency, and superior immunotherapy were observed in the low-risk group patients. The gene signature had good predictive ability. The results of the validation group were consistent with TCGA queue results. Conclusions We constructed a 4-gene signature that helps monitor BLCA occurrence and prognosis, providing an important basis for developing personalized BLCA immunotherapy.

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Identification of a tumor microenvironment-related seven-gene signature for predicting prognosis in bladder cancer

Cited by 22 publications

References 41 publications

Identification of a Novel Tumor Microenvironment Prognostic Signature for Bladder Urothelial Carcinoma

Identification of a Novel Tumor Microenvironment Prognostic Signature for Bladder Urothelial Carcinoma

Identification and Validation of a Novel Prognostic Model Based on Platinum Resistance-Related Genes in Bladder Cancer

Construction and validation of a gene signature related to bladder urothelial carcinoma based on immune gene analysis

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