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Yu D, Chen C, Sun L, Wu S, Tang X, Mei L, Lei C, Wang D, Wang X, Cheng L, Li S. KRT13-expressing epithelial cell population predicts better response to chemotherapy and immunotherapy in bladder cancer: Comprehensive evidences based on BCa database. Comput Biol Med 2023; 158:106795. [PMID: 36989746 DOI: 10.1016/j.compbiomed.2023.106795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 03/04/2023] [Accepted: 03/20/2023] [Indexed: 03/29/2023]
Abstract
Neoadjuvant chemotherapy (NAC) prior to surgery and immune checkpoint therapy (ICT) has revolutionized bladder cancer (BCa) treatment. Patients likely to benefit from these therapies need to be accurately stratified; however, this remains a major clinical challenge. In the present study, single-cell RNA sequencing was used to evaluate the predictive ability of an epithelial cell population highly expressing keratin 13 (KRT13) to assess therapeutic response in BCa. The presence of KRT13-enriched tumors indicated favorable outcomes after NAC and superior response to ICT in patients with BCa. Furthermore, KRT13 population characteristics appeared to be closely related to changes in the immune microenvironment in the vicinity of this cell population. We constructed a prognostic model using an artificial neural network based on the gene signatures in the KRT13 population; the model demonstrated strong robustness and superiority. Additionally, a user-friendly and open-access web application named BCa database was developed for researchers to study BCa by mining the connective map database.
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Jin K, He M, Chen B, Zhou X, Zhang C, Zhang Z, Hu D, Jiang Z, Wei Q, Qiu S, Yang L. A single-sample mRNA molecular classification of bladder cancer predicting prognosis and response to immunotherapy. Transl Androl Urol 2022; 11:943-958. [PMID: 35958899 PMCID: PMC9360513 DOI: 10.21037/tau-21-887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 05/18/2022] [Indexed: 11/12/2022] Open
Abstract
Background As an immunogenic cancer, crosstalk between cancer cells and immune cells has been gradually recognized in bladder cancer (BC). Several studies have emphasized the clinical significance of the molecular stratification of BC without highlighting the role of the immune microenvironment. Although immunotherapy acted as a prospective treatment, more precise molecular stratification should be established to select those sensitive to immunotherapy. Methods To select specific immune genes forming subtypes indicating disparate prognoses, we performed bioinformatic analysis using BC transcriptomic profiles from six published datasets, with 408 BC samples in The Cancer Genome Atlas (TCGA) database and 295 individuals in International Cancer Genome Consortium (ICGC) database. Survival analyses were conducted using Kaplan-Meier curves, while Kruskal-Wallis tests were applied to test the differences among groups. Except for unsupervised clustering based on the differential expression of genes, we additionally performed binomial logistic regression, focusing on the mRNA level of a single sample. Results Unsupervised clustering showed that 4 clusters captured the best segmentation. After validation with survival data and simplification using binomial logistic regression, we found that cluster B and cluster D showed worse survival outcomes (P=0.012). Considering the similar survival outcomes of these two clusters, we recombined and performed another survival analysis, which also showed significant survival differences (P=0.0041). Bonding with clinical data, a greater proportion of risk factors were assigned to the worse prognosis subtype, especially showing higher grades in the subtype (P<0.001). In addition, immune cell infiltration, single nucleotide polymorphism (SNP) and copy number variation (CNV) all showed differences between clusters, indicating changes in the immune microenvironment and mutation burden. Through phenotypical analysis, we found metabolism and proliferation phenotypes associated with the immune clusters and mutually exclusive in BC, of which proliferation contributed to worse outcomes. Using the tumor immune dysfunction and exclusion (TIDE) score, a worse immunotherapy benefit was predicted in clusters B&D, defined as the worse prognosis subtype. Conclusions With this novel clustering criterion based on immune-related genes, we provide a better understanding of the immune microenvironment, further guiding the use of immunotherapy.
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Affiliation(s)
- Kun Jin
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Mingjing He
- Department of Urology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Bo Chen
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Xianghong Zhou
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Chichen Zhang
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Zilong Zhang
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Dan Hu
- Department of Clinical Research Management, West China Hospital, Sichuan University, Chengdu, China
| | - Zhongyuan Jiang
- Department of Clinical Research Management, West China Hospital, Sichuan University, Chengdu, China
| | - Qiang Wei
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Shi Qiu
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China.,Center of Biomedical Big Data, West China Hospital, Sichuan University, Chengdu, China
| | - Lu Yang
- Department of Urology, Institute of Urology and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
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Identification of an immune gene-associated prognostic signature in patients with bladder cancer. Cancer Gene Ther 2022; 29:494-504. [PMID: 35169299 DOI: 10.1038/s41417-022-00438-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 11/19/2021] [Accepted: 02/01/2022] [Indexed: 02/02/2023]
Abstract
A deeper understanding of the interaction between tumor cell and the immune microenvironment in bladder cancer may help select predictive and prognostic biomarkers. The current study aims to construct a prognostic signature for bladder cancer by analysis of molecular characteristics, as well as tumor-immune interactions. RNA-sequencing and clinical information from bladder cancer patients were downloaded from the TCGA database. The single sample Gene Sets Enrichment Analysis (ssGSEA) and Cell type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) were employed to separate the samples into two clusters. Lasso Cox regression was performed to construct an immune gene signature for bladder cancer. The correlation between key target genes of immune checkpoint blockade and the prognostic signature was also analyzed. Dataset from Gene Expression Omnibus (GEO) was retrieved for validation. Two immunophenotypes and immunological characteristics were identified, and a 17-immune gene signature was constructed to provide an independent prognostic signature for bladder cancer. The signature was verified through external validation and correlated with genomic characteristics and clinicopathologic features. Finally, a nomogram was generated from the clinical characteristics and immune signature. Our study reveals a tumor-immune microenvironment signature useful for prognosis in bladder cancer. The results provide information on the potential development of treatment strategies for bladder cancer patients. Prospective studies are warranted to validate the prognostic capability of this model, but these data highlight the role of the microenvironment in the clinical outcome of patients.
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Dyugay IA, Lukyanov DK, Turchaninova MA, Serebrovskaya EO, Bryushkova EA, Zaretsky AR, Khalmurzaev O, Matveev VB, Shugay M, Shelyakin PV, Chudakov DM. Accounting for B-cell Behavior and Sampling Bias Predicts Anti-PD-L1 Response in Bladder Cancer. Cancer Immunol Res 2022; 10:343-353. [PMID: 35013004 PMCID: PMC9381118 DOI: 10.1158/2326-6066.cir-21-0489] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 08/18/2021] [Accepted: 01/06/2022] [Indexed: 01/07/2023]
Abstract
Cancer immunotherapy is predominantly based on T cell-centric approaches. At the same time, the adaptive immune response in the tumor environment also includes clonally produced immunoglobulins and clonal effector/memory B cells that participate in antigen-specific decisions through their interactions with T cells. Here, we investigated the role of infiltrating B cells in bladder cancer via patient dataset analysis of intratumoral immunoglobulin repertoires. We showed that the IgG1/IgA ratio is a prognostic indicator for several subtypes of bladder cancer and for the whole IMVigor210 anti-PD-L1 immunotherapy study cohort. A high IgG1/IgA ratio associated with the prominence of a cytotoxic gene signature, T-cell receptor signaling, and IL21-mediated signaling. Immunoglobulin repertoire analysis indicated that effector B-cell function, rather than clonally produced antibodies, was involved in antitumor responses. From the T-cell side, we normalized a cytotoxic signature against the extent of immune cell infiltration to neutralize the artificial sampling-based variability in immune gene expression. Resulting metrics reflected proportion of cytotoxic cells among tumor-infiltrating immune cells and improved prediction of anti-PD-L1 responses. At the same time, the IgG1/IgA ratio remained an independent prognostic factor. Integration of the B-cell, natural killer cell, and T-cell signatures allowed for the most accurate prediction of anti-PD-L1 therapy responses. On the basis of these findings, we developed a predictor called PRedIctive MolecUlar Signature (PRIMUS), which outperformed PD-L1 expression scores and known gene signatures. Overall, PRIMUS allows for reliable identification of responders among patients with muscle-invasive urothelial carcinoma, including the subcohort with the low-infiltrated "desert" tumor phenotype.
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Affiliation(s)
- Ilya A. Dyugay
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Daniil K. Lukyanov
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia
| | - Maria A. Turchaninova
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Ekaterina O. Serebrovskaya
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Ekaterina A. Bryushkova
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia.,Molecular Biology Department, Lomonosov Moscow State University, Moscow, Russia
| | - Andrew R. Zaretsky
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Oybek Khalmurzaev
- Department of Urology, Federal State Budgetary Institution “N.N. Blokhin National Medical Research Center of Oncology” of the Ministry of Health of the Russian Federation, Moscow, Russia
| | - Vsevolod B. Matveev
- Department of Urology, Federal State Budgetary Institution “N.N. Blokhin National Medical Research Center of Oncology” of the Ministry of Health of the Russian Federation, Moscow, Russia
| | - Mikhail Shugay
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Pavel V. Shelyakin
- Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Dmitriy M. Chudakov
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russia.,Genomics of Adaptive Immunity Department, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, Russia.,Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia.,Corresponding Author: Dmitriy M. Chudakov, Genomics of Adaptive Immunity, IBCH RAS, Miklukho-Maklaya, 16/10, Moscow 117997, Russia. Phone: 7 (495) 335-01-00; E-mail:
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Zhang X, Wang Z, Zeng Z, Shen N, Wang B, Zhang Y, Shen H, Lu W, Wei R, Ma W, Wang C. Bioinformatic analysis identifying FGF1 gene as a new prognostic indicator in clear cell Renal Cell Carcinoma. Cancer Cell Int 2021; 21:222. [PMID: 33865387 PMCID: PMC8052755 DOI: 10.1186/s12935-021-01917-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 04/07/2021] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Clear cell renal cell carcinoma (ccRCC) has been the commonest renal cell carcinoma (RCC). Although the disease classification, diagnosis and targeted therapy of RCC has been increasingly evolving attributing to the rapid development of current molecular pathology, the current clinical treatment situation is still challenging considering the comprehensive and progressively developing nature of malignant cancer. The study is to identify more potential responsible genes during the development of ccRCC using bioinformatic analysis, thus aiding more precise interpretation of the disease METHODS: Firstly, different cDNA expression profiles from Gene Expression Omnibus (GEO) online database were used to screen the abnormal differently expressed genes (DEGs) between ccRCC and normal renal tissues. Then, based on the protein-protein interaction network (PPI) of all DEGs, the module analysis was performed to scale down the potential genes, and further survival analysis assisted our proceeding to the next step for selecting a credible key gene. Thirdly, immunohistochemistry (IHC) and quantitative real-time PCR (QPCR) were conducted to validate the expression change of the key gene in ccRCC comparing to normal tissues, meanwhile the prognostic value was verified using TCGA clinical data. Lastly, the potential biological function of the gene and signaling mechanism of gene regulating ccRCC development was preliminary explored. RESULTS Four cDNA expression profiles were picked from GEO database based on the number of containing sample cases, and a total of 192 DEGs, including 39 up-regulated and 153 down-regulated genes were shared in four profiles. Based on the DEGs PPI network, four function modules were identified highlighting a FGF1 gene involving PI3K-AKT signaling pathway which was shared in 3/4 modules. Further, both the IHC performed with ccRCC tissue microarray which contained 104 local samples and QPCR conducted using 30 different samples confirmed that FGF1 was aberrant lost in ccRCC. And Kaplan-Meier overall survival analysis revealed that FGF1 gene loss was related to worse ccRCC patients survival. Lastly, the pathological clinical features of FGF1 gene and the probable biological functions and signaling pathways it involved were analyzed using TCGA clinical data. CONCLUSIONS Using bioinformatic analysis, we revealed that FGF1 expression was aberrant lost in ccRCC which statistical significantly correlated with patients overall survival, and the gene's clinical features and potential biological functions were also explored. However, more detailed experiments and clinical trials are needed to support its potential drug-target role in clinical medical use.
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Affiliation(s)
- Xiaoqin Zhang
- Department of Pathology, The Second Hospital of ShanXi Medical University, ShanXi Province, No.382 WuYi Road, Tai Yuan, 030000, China
| | - Ziyue Wang
- Department of Pathology, The Second Clinical Medical College of ShanXi Medical University, ShanXi Province, Tai Yuan, China
| | - Zixin Zeng
- Department of Pathology, The Second Clinical Medical College of ShanXi Medical University, ShanXi Province, Tai Yuan, China
| | - Ningning Shen
- Department of Pathology, The Second Hospital of ShanXi Medical University, ShanXi Province, No.382 WuYi Road, Tai Yuan, 030000, China
| | - Bin Wang
- Department of Pathology, The Second Clinical Medical College of ShanXi Medical University, ShanXi Province, Tai Yuan, China
| | - Yaping Zhang
- Department of Pathology, The Second Clinical Medical College of ShanXi Medical University, ShanXi Province, Tai Yuan, China
| | - Honghong Shen
- Department of Pathology, The Second Hospital of ShanXi Medical University, ShanXi Province, No.382 WuYi Road, Tai Yuan, 030000, China
| | - Wei Lu
- Department of Pathology, The Second Clinical Medical College of ShanXi Medical University, ShanXi Province, Tai Yuan, China
| | - Rong Wei
- Department of Pathology, The Second Hospital of ShanXi Medical University, ShanXi Province, No.382 WuYi Road, Tai Yuan, 030000, China
| | - Wenxia Ma
- Department of Pathology, The Second Hospital of ShanXi Medical University, ShanXi Province, No.382 WuYi Road, Tai Yuan, 030000, China.
| | - Chen Wang
- Department of Pathology, The Second Hospital of ShanXi Medical University, ShanXi Province, No.382 WuYi Road, Tai Yuan, 030000, China.
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Weng H, Yuan S, Huang Q, Zeng XT, Wang XH. STAT1 is a key gene in a gene regulatory network related to immune phenotypes in bladder cancer: An integrative analysis of multi-omics data. J Cell Mol Med 2021; 25:3258-3271. [PMID: 33608980 PMCID: PMC8034450 DOI: 10.1111/jcmm.16395] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 01/31/2021] [Accepted: 02/04/2021] [Indexed: 12/13/2022] Open
Abstract
The immunophenotype of bladder cancer plays a pivotal role in the prognosis of cancer, but the effect of different epigenetic factors on different immunophenotypes in bladder tumours remains unclear. This study used multi-omics data analysis to provide molecular basis support for different immune phenotypes. Unsupervised cluster analysis revealed distinct subclusters with higher (subcluster B2) or lower cytotoxic immune phenotypes (subcluster A1) related to PD-L1 and IFNG expression. Mutational landscape analyses showed that the mutation level of TP53 in subcluster B1 was highest than other subclusters, and subcluster B1 had a lower frequency of concurrent mutation than subcluster A2. A total of 2364 differentially expressed genes were identified between subclusters A2 and B1, and the main functions of the up-regulated genes in subcluster B1 were enriched in the activation of T cells and other related pathways. We found that STAT1 was a key gene in a gene regulatory network related to immune phenotypes in bladder cancer. Finally, we constructed a prognostic prediction model by LASSO Cox regression which could distinguish high-risk and low-risk cases significantly. In conclusion, the present study addressed a field synopsis between genetic and epigenetic events in immune phenotypes of bladder cancer.
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Affiliation(s)
- Hong Weng
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Wuhan University, Wuhan, China.,Institute of Urology, Wuhan University, Wuhan, China
| | - Shuai Yuan
- Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Wuhan University, Wuhan, China
| | - Qiao Huang
- Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Wuhan University, Wuhan, China
| | - Xian-Tao Zeng
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Wuhan University, Wuhan, China.,Institute of Urology, Wuhan University, Wuhan, China
| | - Xing-Huan Wang
- Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China.,Center for Evidence-Based and Translational Medicine, Wuhan University, Wuhan, China.,Institute of Urology, Wuhan University, Wuhan, China
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