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      FSTL3 promotes tumor immune evasion and attenuates response to anti-PD1 therapy by stabilizing c-Myc in colorectal cancer

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          Abstract

          Programmed cell death 1 ligand 1 (PDL1)/programmed cell death 1 (PD1) blockade immunotherapy provides a prospective strategy for the treatment of colorectal cancer (CRC), but various constraints on the effectiveness of the treatment are still remaining. As reported in previous studies, follistatin-like 3 (FSTL3) could mediate inflammatory response in macrophages by induction lipid accumulation. Herein, we revealed that FSTL3 were overexpressed in malignant cells in the CRC microenvironment, notably, the expression level of FSTL3 was related to tumor immune evasion and the clinical efficacy of anti-PD1 therapy. Further studies determined that hypoxic tumor microenvironment induced the FSTL3 expression via HIF1α in CRC cells, FSTL3 could bind to the transcription factor c-Myc (354–406 amino acids) to suppress the latter’s ubiquitination and increase its stability, thereby to up-regulated the expression of PDL1 and indoleamine 2,3-dioxygenase 1 (IDO1). The results in the immunocompetent tumor models verified that FSLT3 knockout in tumor cells increased the proportion of CD8 + T cells in the tumor microenvironment, reduced the proportion of regulatory T cells (CD25 + Foxp3 +) and exhausted T cells (PD1 + CD8 +), and synergistically improved the anti-PD1 therapy efficacy. To sum up, FSTL3 enhanced c-Myc-mediated transcriptional regulation to promote immune evasion and attenuates response to anti-PD1 therapy in CRC, suggesting the potential of FSTL3 as a biomarker of immunotherapeutic efficacy as well as a novel immunotherapeutic target in CRC.

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            The Immune Landscape of Cancer

            We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes-wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant-characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.
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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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                Author and article information

                Contributors
                caohongy6167@163.com
                yma0917@163.com
                whj_888@sohu.com
                shulizhao79@163.com
                Journal
                Cell Death Dis
                Cell Death Dis
                Cell Death & Disease
                Nature Publishing Group UK (London )
                2041-4889
                1 February 2024
                1 February 2024
                February 2024
                : 15
                : 2
                : 107
                Affiliations
                [1 ]Department of general surgery, Nanjing First Hospital, Nanjing Medical University, ( https://ror.org/059gcgy73) Nanjing, Jiangsu China
                [2 ]General Clinical Research Center, Nanjing First Hospital, Nanjing Medical University, ( https://ror.org/059gcgy73) Nanjing, Jiangsu China
                [3 ]General Clinical Research Center, Nanjing First Hospital, China Pharmaceutical University, ( https://ror.org/01sfm2718) Nanjing, Jiangsu China
                [4 ]GRID grid.412676.0, ISNI 0000 0004 1799 0784, Hepatobiliary/Liver Transplantation Center, the First Affiliated Hospital of Nanjing Medical University, Key Laboratory of Living Donor Transplantation, Chinese Academy of Medical Sciences, ; Nanjing, Jiangsu China
                Author information
                http://orcid.org/0000-0002-8516-819X
                http://orcid.org/0000-0003-1188-991X
                http://orcid.org/0000-0002-3610-2418
                Article
                6469
                10.1038/s41419-024-06469-0
                10834545
                38302412
                0c7a7d98-6691-46a9-8cec-ecc4779698b5
                © The Author(s) 2024

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 September 2023
                : 8 January 2024
                : 12 January 2024
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 81872114
                Award ID: 82173205
                Award Recipient :
                Funded by: Key Research and Development Program of Jiangsu Province (Grant Reference Number: BE2019617)
                Categories
                Article
                Custom metadata
                © Associazione Differenziamento e Morte Cellulare ADMC 2024

                Cell biology
                cancer microenvironment,cancer immunotherapy,cancer therapeutic resistance
                Cell biology
                cancer microenvironment, cancer immunotherapy, cancer therapeutic resistance

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