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      Omics-wide quantitative B-cell infiltration analyses identify GPR18 for human cancer prognosis with superiority over CD20

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          Abstract

          Tumor-infiltrating B lymphocyte (TIL-B), and TIL-B-related biomarkers have clinical prognostic values for human cancers. CD20 (encoded by MS4A1) is a widely used TIL-B biomarker. Using TCGA-quantitative multiomics datasets, we first cross-compare prognostic powers of intratumoral CD20 protein, mRNA and TIL-B levels in pan-cancers. Here, we show that MS4A1 and TIL-B are consistently prognostic in 5 cancers (head and neck, lung, cervical, kidney and low-grade glioma), while unexpectedly, CD20 protein levels lack quantitative correlations with MS4A1/TIL-B levels and demonstrate limited prognosticity. Subsequent bioinformatics discovery for TIL-B prognostic gene identifies a single gene, GPR18 with stand-alone prognosticity across 9 cancers (superior over CD20), with further validations in multiple non-TCGA cohorts. GPR18' s immune signature denotes major B-cell-T-cell interactions, with its intratumoral expression strongly tied to a “T-cell active”, likely cytolytic, status across human cancers, suggesting its functional link to cytolytic T-cell activity in cancer. GPR18 merits biological and clinical utility assessments over CD20.

          Abstract

          Yuchen Liu et al. show that GPR18 serves as a superior prognostic marker across nine cancers over CD20 by TIL-B omics analyses. GPR18 expressions in tumors are strongly correlated with major T-cell functionality scores, suggesting its functional link to cytolytic T-cell activity in cancer.

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          The head and neck cancer immune landscape and its immunotherapeutic implications.

          Recent clinical trials have demonstrated a clear survival advantage in advanced head and neck squamous cell carcinoma (HNSCC) patients treated with immune checkpoint blockade. These emerging results reveal that HNSCC is one of the most promising frontiers for immunotherapy research. However, further progress in head and neck immuno-oncology will require a detailed understanding of the immune infiltrative landscape found in these tumors. We leveraged transcriptome data from 280 tumors profiled by The Cancer Genome Atlas (TCGA) to comprehensively characterize the immune landscape of HNSCC in order to develop a rationale for immunotherapeutic strategies in HNSCC and guide clinical investigation. We find that both HPV(+) and HPV(-) HNSCC tumors are among the most highly immune-infiltrated cancer types. Strikingly, HNSCC had the highest median Treg/CD8(+) T cell ratio and the highest levels of CD56(dim) NK cell infiltration, in our pan-cancer analysis of the most immune-infiltrated tumors. CD8(+) T cell infiltration and CD56(dim) NK cell infiltration each correlated with superior survival in HNSCC. Tumors harboring genetic smoking signatures had lower immune infiltration and were associated with poorer survival, suggesting these patients may benefit from immune agonist therapy. These findings illuminate the immune landscape of HPV(+) and HPV(-) HNSCC. Additionally, this landscape provides a potentially novel rationale for investigation of agents targeting modulators of Tregs (e.g., CTLA-4, GITR, ICOS, IDO, and VEGFA) and NK cells (e.g., KIR, TIGIT, and 4-1BB) as adjuncts to anti-PD-1 in the treatment of advanced HNSCC.
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            Biomarker discovery in non-small cell lung cancer: integrating gene expression profiling, meta-analysis, and tissue microarray validation.

            Global gene expression profiling has been widely used in lung cancer research to identify clinically relevant molecular subtypes as well as to predict prognosis and therapy response. So far, the value of these multigene signatures in clinical practice is unclear, and the biologic importance of individual genes is difficult to assess, as the published signatures virtually do not overlap. Here, we describe a novel single institute cohort, including 196 non-small lung cancers (NSCLC) with clinical information and long-term follow-up. Gene expression array data were used as a training set to screen for single genes with prognostic impact. The top 450 probe sets identified using a univariate Cox regression model (significance level P < 0.01) were tested in a meta-analysis including five publicly available independent lung cancer cohorts (n = 860). The meta-analysis revealed 14 genes that were significantly associated with survival (P < 0.001) with a false discovery rate <1%. The prognostic impact of one of these genes, the cell adhesion molecule 1 (CADM1), was confirmed by use of immunohistochemistry on tissue microarrays from 2 independent NSCLC cohorts, altogether including 617 NSCLC samples. Low CADM1 protein expression was significantly associated with shorter survival, with particular influence in the adenocarcinoma patient subgroup. Using a novel NSCLC cohort together with a meta-analysis validation approach, we have identified a set of single genes with independent prognostic impact. One of these genes, CADM1, was further established as an immunohistochemical marker with a potential application in clinical diagnostics.
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              Systematic Analysis of Immune Infiltrates in High-Grade Serous Ovarian Cancer Reveals CD20, FoxP3 and TIA-1 as Positive Prognostic Factors

              Background Tumor-infiltrating T cells are associated with survival in epithelial ovarian cancer (EOC), but their functional status is poorly understood, especially relative to the different risk categories and histological subtypes of EOC. Methodology/Principal Findings Tissue microarrays containing high-grade serous, endometrioid, mucinous and clear cell tumors were analyzed immunohistochemically for the presence of lymphocytes, dendritic cells, neutrophils, macrophages, MHC class I and II, and various markers of activation and inflammation. In high-grade serous tumors from optimally debulked patients, positive associations were seen between intraepithelial cells expressing CD3, CD4, CD8, CD45RO, CD25, TIA-1, Granzyme B, FoxP3, CD20, and CD68, as well as expression of MHC class I and II by tumor cells. Disease-specific survival was positively associated with the markers CD8, CD3, FoxP3, TIA-1, CD20, MHC class I and class II. In other histological subtypes, immune infiltrates were less prevalent, and the only markers associated with survival were MHC class II (positive association in endometrioid cases) and myeloperoxidase (negative association in clear cell cases). Conclusions/Significance Host immune responses to EOC vary widely according to histological subtype and the extent of residual disease. TIA-1, FoxP3 and CD20 emerge as new positive prognostic factors in high-grade serous EOC from optimally debulked patients.
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                Author and article information

                Contributors
                vlui002@cuhk.edu.hk
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                12 May 2020
                12 May 2020
                2020
                : 3
                : 234
                Affiliations
                [1 ]School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR
                [2 ]Department of Anatomical and Cellular Pathology and State Key Laboratory of Translational Oncology, The Chinese University of Hong Kong, Hong Kong, Hong Kong SAR
                Article
                964
                10.1038/s42003-020-0964-7
                7217858
                32398659
                67dcdc6d-deb1-43bc-b0de-2c1cab4a682a
                © The Author(s) 2020

                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
                : 21 November 2019
                : 20 April 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/100007420, Lee Hysan Foundation (LHF);
                Award ID: CA11281
                Award ID: CA11286
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100002920, Research Grants Council, University Grants Committee (RGC, UGC);
                Award ID: #1416857
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100005847, Food and Health Bureau of the Government of the Hong Kong Special Administrative Region | Health and Medical Research Fund (HMRF);
                Award ID: HMRF#15160691
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100010428, Innovation and Technology Fund (ITF);
                Award ID: UIM/329
                Award Recipient :
                Funded by: Research Impact Fund, Hong Kong government (#R4017-18)
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                data mining,high-throughput screening
                data mining, high-throughput screening

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