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      MTHFD2 is a potential oncogene for its strong association with poor prognosis and high level of immune infiltrates in urothelial carcinomas of bladder

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          Abstract

          Background

          The bifunctional methylenetetrahydrofolate dehydrogenase (NADP+ dependent) 2, methenyltetrahydrofolate cyclohydrolase ( MTHFD2) has been reported to play an oncogenic role in various types of cancers. However, the function of MTHFD2 in urothelial carcinomas of bladder (UCB) and its association with tumor immune infiltration remains unknown. We aim to examine the suitability of MTHFD2 to be a novel biomarker of bladder cancer and whether MTHFD2 is linked to immune infiltration.

          Methods

          RNA sequencing data and clinical information (bladder cancer samples: normal samples = 414: 19) were downloaded from The Cancer Genome Atlas official website. Western blot analysis was performed to detect MTHFD2 expression in human bladder cancer (BLCA) cells and normal urothelial cell line SV-HUC-1. Associations between MTHFD2 expression and clinicopathological features were analyzed using Mann Whitney U test or Kruskal-Wallis H test. The “survival” and “survminer” packages were utilized to plot Kaplan-Meier survival curves. Moreover, the gene set enrichment analysis (GSEA) was conducted using a clusterProfiler package. The correlation of MTHFD2 expression with immune infiltration level was estimated using the single sample GSEA (ssGSEA) algorithm. Furthermore, associations between MTHFD2 and immune checkpoint genes were evaluated using the correlation analysis .

          Results

          Transcriptome analysis manifested that MTHFD2 was highly expressed in UCB tissues than normal bladder tissues, which was further confirmed by western blot analysis in human BLCA cells and SV-HUC-1 cells. Moreover, MTHFD2 high expression was significantly associated with the advanced disease progression. Also, the high expression of MTHFD2 was correlated with poor prognosis, and MTHFD2 was considered as an independent prognostic factor for disease specific survival. Furthermore, a number of cancer-related pathways were enriched in MTHFD2 high group, including NF-κB activation, JAK/STAT, and cancer immunotherapy by PD1 blockade. Several immune checkpoint molecules were also strongly associated with MTHFD2 expression, including PDCD1, CD274, CTLA4, CD276, LAG3, HAVCR2, and TIGIT.

          Conclusions

          MTHFD2 expression was remarkably elevated in UCB, suggesting that MTHFD2 could be a promising biomarker for BLCA as well as novel target for anti-cancer immunotherapy since its close association with immune infiltration.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12885-022-09606-0.

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          Most cited references39

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          GSVA: gene set variation analysis for microarray and RNA-Seq data

          Background Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. Results To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. Conclusions GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.
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            TIMER2.0 for analysis of tumor-infiltrating immune cells

            Abstract Tumor progression and the efficacy of immunotherapy are strongly influenced by the composition and abundance of immune cells in the tumor microenvironment. Due to the limitations of direct measurement methods, computational algorithms are often used to infer immune cell composition from bulk tumor transcriptome profiles. These estimated tumor immune infiltrate populations have been associated with genomic and transcriptomic changes in the tumors, providing insight into tumor–immune interactions. However, such investigations on large-scale public data remain challenging. To lower the barriers for the analysis of complex tumor–immune interactions, we significantly improved our previous web platform TIMER. Instead of just using one algorithm, TIMER2.0 (http://timer.cistrome.org/) provides more robust estimation of immune infiltration levels for The Cancer Genome Atlas (TCGA) or user-provided tumor profiles using six state-of-the-art algorithms. TIMER2.0 provides four modules for investigating the associations between immune infiltrates and genetic or clinical features, and four modules for exploring cancer-related associations in the TCGA cohorts. Each module can generate a functional heatmap table, enabling the user to easily identify significant associations in multiple cancer types simultaneously. Overall, the TIMER2.0 web server provides comprehensive analysis and visualization functions of tumor infiltrating immune cells.
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              Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer.

              The complex interactions between tumors and their microenvironment remain to be elucidated. Combining large-scale approaches, we examined the spatio-temporal dynamics of 28 different immune cell types (immunome) infiltrating tumors. We found that the immune infiltrate composition changed at each tumor stage and that particular cells had a major impact on survival. Densities of T follicular helper (Tfh) cells and innate cells increased, whereas most T cell densities decreased along with tumor progression. The number of B cells, which are key players in the core immune network and are associated with prolonged survival, increased at a late stage and showed a dual effect on recurrence and tumor progression. The immune control relevance was demonstrated in three endoscopic orthotopic colon-cancer mouse models. Genomic instability of the chemokine CXCL13 was a mechanism associated with Tfh and B cell infiltration. CXCL13 and IL21 were pivotal factors for the Tfh/B cell axis correlating with survival. This integrative study reveals the immune landscape in human colorectal cancer and the major hallmarks of the microenvironment associated with tumor progression and recurrence. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Contributors
                cavinx@yeah.net
                Journal
                BMC Cancer
                BMC Cancer
                BMC Cancer
                BioMed Central (London )
                1471-2407
                17 May 2022
                17 May 2022
                2022
                : 22
                : 556
                Affiliations
                [1 ]GRID grid.411634.5, ISNI 0000 0004 0632 4559, Department of Urology, , Peking University People’s Hospital, ; 11 Xizhimen South Street, Xicheng District, Beijing, 100044 China
                [2 ]GRID grid.411634.5, ISNI 0000 0004 0632 4559, Peking University Applied Lithotripsy Institute, Peking University People’s Hospital, ; Beijing, 100034 China
                Article
                9606
                10.1186/s12885-022-09606-0
                9112551
                35581573
                a62a59c6-12d4-49b0-a2c4-3288c4cc23fa
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 9 September 2021
                : 25 April 2022
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Oncology & Radiotherapy
                urothelial carcinomas of bladder,mthfd2,the cancer genome atlas website,biomarker,immune infiltrates,prognosis

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