Comprehensive FGFR3 alteration-related transcriptomic characterization is involved in immune infiltration and correlated with prognosis and immunotherapy response of bladder cancer.

Bladder cancer (BC) threatens the health of human beings worldwide because of its high recurrence rate and mortality. As an actionable biomarker, fibroblast growth factor receptor 3 (FGFR3) alterations have been revealed as a vital biomarker and associated with favorable outcomes in BC. However, the comprehensive relationship between the FGFR3 alteration associated gene expression profile and the prognosis of BC remains ambiguous. Genomic alteration profile, gene expression data, and related clinical information of BC patients were downloaded from The Cancer Genomics database (TCGA), as a training cohort. Subsequently, the Weighted Gene Co-expression Network Analysis (WGCNA) was conducted to identify the hub modules correlated with FGFR3 alteration. The univariate, multivariate, and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to obtain an FGFR3 alteration-related gene (FARG) prognostic signature and FARG-based nomogram. The receiver operating characteristic (ROC) curve analysis was used for evaluation of the ability of prognosis prediction. The FARG signature was validated in four independent datasets, namely, GSE13507, GSE31684, GSE32548, and GSE48075, from Gene Expression Omnibus (GEO). Then, clinical feature association analysis, functional enrichment, genomic alteration enrichment, and tumor environment analysis were conducted to reveal differential clinical and molecular characterizations in different risk groups. Lastly, the treatment response was evaluated in the immunotherapy-related dataset of the IMvigor210 cohort and the frontline chemotherapy dataset of GSE48276, and the chemo-drug sensitivity was estimated via Genomics of Drug Sensitivity in Cancer (GDSC). There were a total of eleven genes (CERCAM, TPST1, OSBPL10, EMP1, CYTH3, NCRNA00201, PCDH10, GAP43, COLQ, DGKB, and SETBP1) identified in the FARG signature, which divided BC patients from the TCGA cohort into high- and low-risk groups. The Kaplan-Meier curve analysis demonstrated that BC patients in the low-risk group have superior overall survival (OS) than those in the high-risk group (median OS: 27.06 months vs. 104.65 months, p < 0.0001). Moreover, the FARG signature not only showed a good performance in prognosis prediction, but also could distinguish patients with different neoplasm disease stages, notably whether patients presented with muscle invasive phenotype. Compared to clinicopathological features, the FARG signature was found to be the only independent prognostic factor, and subsequently, a FARG-based prognostic nomogram was constructed with better ability of prognosis prediction, indicated by area under ROC curve (AUC) values for 1-, 3-, and 5-year OS of 0.69, 0.71, and 0.79, respectively. Underlying the FARG signature, multiple kinds of metabolism- and immune-related signaling pathways were enriched. Genomic alteration enrichment further identified that FGFR3 alterations, especially c.746C>G (p.Ser249Cys), were more prevalent in the low-risk group. Additionally, FARG score was positively correlated with ESTIMATE and TIDE scores, and the low-risk group had abundant enrichment of plasma B cells, CD8+ T cells, CD4+ naive T cells, and helper follicular T cells, implying that patients in the low-risk group were likely to make significant responses to immunotherapy, which was further supported by the analysis in the IMvigor210 cohort as there was a significantly higher response rate among patients with lower FARG scores. The analysis of the GDSC database finally demonstrated that low-risk samples were more sensitive to methotrexate and tipifarnib, whereas those in the high-risk group had higher sensitivities in cisplatin, docetaxel, and paclitaxel, instead. The novel established FARG signature based on a comprehensive FGFR3 alteration-related transcriptomic profile performed well in prognosis prediction and was also correlated with immunotherapy and chemotherapy treatment responses, which had great potential in future clinical applications.

Xu T ，Xu W ，Zheng Y ，Li X ，Cai H ，Xu Z ，Zou Q ，Yu B ... -  《Frontiers in Immunology》

Integrative transcriptional characterization of cell cycle checkpoint genes promotes clinical management and precision medicine in bladder carcinoma.

The aberrant regulation of cell cycle is significantly correlated with cancer carcinogenesis and progression, in which cell cycle checkpoints control phase transitions, cell cycle entry, progression, and exit. However, the integrative role of cell cycle checkpoint-related genes (CRGs) in bladder carcinoma (BC) remains unknown. The transcriptomic data and clinical features of BC patients were downloaded from The Cancer Genome Atlas (TCGA), used to identify CRGs correlated with overall survival (OS) by univariate Cox regression analysis. Then, the multivariate and least absolute shrinkage and selection operator (LASSO) Cox regression analyses further developed a prognostic CRG signature, which was validated in three external datasets retrieved from Gene Expression Omnibus (GEO). The receiver operating characteristic curve (ROC) analysis was conducted for evaluating the performance of the CRG signature in prognosis prediction. RNA sequencing (RNA-Seq) was performed to explore the expression difference in the identified CRGs between tumor and normal tissue samples from 11 BC patients in the local cohort. Ultimately, genomic profiles and tumor microenvironment (TME), and the Genomics of Drug Sensitivity in Cancer (GDSC) were investigated to guide precision treatment for BC patients with different CRG features. The novel constructed 23-CRG prognostic signature could stratify BC patients into high-risk and low-risk groups with significantly different outcomes (median OS: 13.64 vs. 104.65 months). Notably, 19 CRGs were the first to be identified as being associated with BC progression. In three additional validation datasets (GSE13507, GSE31684, and GSE32548), higher CRG scores all indicated inferior survival, demonstrating the robust ability of the CRG signature in prognosis prediction. Moreover, the CRG signature as an independent prognostic factor had a robust and stable risk stratification for BC patients with different histological or clinical features. Then, a CRG signature-based nomogram with a better performance in prognostic prediction [concordance index (C-index): 0.76] was established. Functional enrichment analysis revealed that collagen-containing extracellular matrix (ECM), and ECM-related and MAPK signaling pathways were significantly associated with the signature. Further analysis showed that low-risk patients were characterized by particularly distinctive prevalence of FGFR3 (17.03% vs. 6.67%, p < 0.01) and POLE alterations (7.97% vs. 2.50%, p < 0.05), and enrichment of immune infiltrated cells (including CD8+ T cells, CD4+ naïve T cells, follicular helper T cells, Tregs, and myeloid dendritic cells). RNA-seq data in our local cohort supported the findings in the differentially expressed genes (DEGs) between tumor and normal tissue samples, and the difference in TME between high-risk and low-risk groups. Additionally, CRG signature score plus FGFR3 status divided BC patients into four molecular subtypes, with distinct prognosis, TME, and transcriptomic profiling of immune checkpoint genes. Of note, CRG signature score plus FGFR3 status could successfully distinguish BC patients who have a higher possibility of response to immunotherapy or chemotherapy drugs. The CRG signature is a potent prognostic model for BC patients, and in combination with FGFR3 alterations, it had more practical capacity in the prediction of chemotherapy and immunotherapy response, helping guide clinical decision-making.

Shi WW ，Guan JZ ，Long YP ，Song Q ，Xiong Q ，Qin BY ，Ma ZQ ，Hu Y ，Yang B ... -  《Frontiers in Oncology》

Identification of a Nuclear Mitochondrial-Related Multi-Genes Signature to Predict the Prognosis of Bladder Cancer.

Bladder cancer (BC) is one of the most prevalent urinary cancers, and its management is still a problem causing recurrence and progression, elevating mortality. We aimed at the nuclear mitochondria-related genes (MTRGs), collected from the MITOMAP: A Human Mitochondrial Genome Database. Meanwhile, the expression profiles and clinical information of BC were downloaded from the Cancer Genome Atlas (TCGA) as a training group. The univariate, multivariate, and the least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to construct a nuclear mitochondrial-related multi-genes signature and the prognostic nomogram. A total of 17 nuclear MTRGs were identified to be correlated with the overall survival (OS) of BC patients, and a nuclear MTRGs signature based on 16 genes expression was further determined by the LASSO Cox regression analysis. Based on a nuclear MTRGs scoring system, BC patients from the TCGA cohort were divided into high- and low- nuclear MTRGs score groups. Patients with a high nuclear MTRGs score exhibited a significantly poorer outcome (median OS: 92.90 vs 20.20 months, p<0.0001). The nuclear MTRGs signature was further verified in three independent datasets, namely, GSE13507, GSE31684, and GSE32548, from the Gene Expression Omnibus (GEO). The BC patients with a high nuclear MTRGs score had significantly worse survival (median OS in GSE13507: 31.52 vs 98.00 months, p<0.05; GSE31684: 32.85 months vs unreached, p<0.05; GSE32548: unreached vs unreached, p<0.05). Furthermore, muscle-invasive bladder cancer (MIBC) patients had a significantly higher nuclear MTRGs score (p<0.05) than non-muscle-invasive bladder cancer (NMIBC) patients. The integrated signature outperformed each involved MTRG. In addition, a nuclear MTRGs-based nomogram was constructed as a novel prediction prognosis model, whose AUC values for OS at 1, 3, 5 years were 0.76, 0.75, and 0.75, respectively, showing the prognostic nomogram had good and stable predicting ability. Enrichment analyses of the hallmark gene set and KEGG pathway revealed that the E2F targets, G2M checkpoint pathways, and cell cycle had influences on the survival of BC patients. Furthermore, the analysis of tumor microenvironment indicated more CD8+ T cells and higher immune score in patients with high nuclear MTRGs score, which might confer sensitivity to immune checkpoint inhibitors. Not only could the signature and prognostic nomogram predict the prognosis of BC, but it also had potential therapeutic guidance.

Jiang X ，Xia Y ，Meng H ，Liu Y ，Cui J ，Huang H ，Yin G ，Shi B ... -  《Frontiers in Oncology》

Mitochondrial-Related Transcriptome Feature Correlates with Prognosis, Vascular Invasion, Tumor Microenvironment, and Treatment Response in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the most common subtype of primary liver cancer, which was highly correlated with metabolic dysfunction. Nevertheless, the association between nuclear mitochondrial-related transcriptome and HCC remained unclear. A total of 147 nuclear mitochondrial-related genes (NMRGs) were downloaded from the MITOMAP: A Human Mitochondrial Genome Database. The training dataset was downloaded from The Cancer Genome Atlas (TCGA), while validation datasets were retrieved from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). The univariate and multivariate, and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were applied to construct a NMRG signature, and the value of area under receiver operating characteristic curve (AUC) was utilized to assess the signature and nomogram. Then, data from the Genomics of Drug Sensitivity in Cancer (GDSC) were used for the evaluation of chemotherapy response in HCC. Functional enrichment of differentially expressed genes (DEGs) between HCC and paired normal tissue samples demonstrated that mitochondrial dysfunction was significantly associated with HCC development. Survival analysis showed a total of 35 NMRGs were significantly correlated with overall survival (OS) of HCC, and the LASSO Cox regression analysis further identified a 25-NMRG signature and corresponding prognosis score based on their transcriptional profiling. HCC patients were divided into high- and low-risk groups according to the median prognosis score, and high-risk patients had significantly worse OS (median OS: 27.50 vs. 83.18 months, P < 0.0001). The AUC values for OS at 1, 3, and 5 years were 0.79, 0.77, and 0.77, respectively. The prognostic capacity of NMRG signature was verified in the GSE14520 dataset and ICGC-HCC cohort. Besides, the NMRG signature outperformed each NMRG and clinical features in prognosis prediction and could also differentiate whether patients presented with vascular invasions (VIs) or not. Subsequently, a prognostic nomogram (C-index: 0.753, 95% CI: 0.703~0.804) by the integration of age, tumor metastasis, and NMRG prognosis score was constructed with the AUC values for OS at 1, 3, and 5 years were 0.82, 0.81, and 0.82, respectively. Notably, significant enrichment of regulatory and follicular helper T cells in high-risk group indicated the potential treatment of immune checkpoint inhibitors for these patients. Interestingly, the NMRG signature could also identify the potential responders of sorafenib or transcatheter arterial chemoembolization (TACE) treatment. Additionally, HCC patients in high-risk group appeared to be more sensitive to cisplatin, vorinostat, and methotrexate, reversely, patients in low-risk group had significantly higher sensitivity to paclitaxel and bleomycin instead. In summary, the development of NMRG signature provided a more comprehensive understanding of mitochondrial dysfunction in HCC, helped predict prognosis and tumor microenvironment, and provided potential targeted therapies for HCC patients with different NMRG prognosis scores.

Wang Y ，Song F ，Zhang X ，Yang C ... -  《-》

Construction of a novel mRNA-signature prediction model for prognosis of bladder cancer based on a statistical analysis.

Bladder cancer (BC) is a common malignancy neoplasm diagnosed in advanced stages in most cases. It is crucial to screen ideal biomarkers and construct a more accurate prognostic model than conventional clinical parameters. The aim of this research was to develop and validate an mRNA-based signature for predicting the prognosis of patients with bladder cancer. The RNA-seq data was downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were screened in three datasets, and prognostic genes were identified from the training set of TCGA dataset. The common genes between DEGs and prognostic genes were narrowed down to six genes via Least Absolute Shrinkage and Selection Operator (LASSO) regression, and stepwise multivariate Cox regression. Then the gene-based risk score was calculated via Cox coefficient. Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier (KM) survival analysis were used to assess the prognostic power of risk score. Multivariate Cox regression analysis was applied to construct a nomogram. Decision curve analysis (DCA), calibration curves, and time-dependent ROC were performed to assess the nomogram. Finally, functional enrichment of candidate genes was conducted to explore the potential biological pathways of candidate genes. SORBS2, GPC2, SETBP1, FGF11, APOL1, and H1-2 were screened to be correlated with the prognosis of BC patients. A nomogram was constructed based on the risk score, pathological stage, and age. Then, the calibration plots for the 1-, 3-, 5-year OS were predicted well in entire TCGA-BLCA patients. Decision curve analysis (DCA) indicated that the clinical value of the nomogram was higher than the stage model and TNM model in predicting overall survival analysis. The time-dependent ROC curves indicated that the nomogram had higher predictive accuracy than the stage model and risk score model. The AUC of nomogram time-dependent ROC was 0.763, 0.805, and 0.806 for 1-year, 3-year, and 5-year, respectively. Functional enrichment analysis of candidate genes suggested several pathways and mechanisms related to cancer. In this research, we developed an mRNA-based signature that incorporated clinical prognostic parameters to predict BC patient prognosis well, which may provide a novel prognosis assessment tool for clinical practice and explore several potential novel biomarkers related to the prognosis of patients with BC.

Li J ，Cao J ，Li P ，Yao Z ，Deng R ，Ying L ，Tian J ... -  《BMC CANCER》