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      The Potential Dual Role of H2.0-like Homeobox in the Tumorgenesis and Development of Colorectal Cancer and Its Prognostic Value

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          Abstract

          Background

          H2.0-like homeobox ( HLX) is highly expressed in several hematopoietic malignancies. However, the role of HLX in the carcinogenesis and progression of colorectal cancer (CRC) patients has rarely been reported.

          Methods

          In this study, the data were collected from The Cancer Genome Atlas and Gene Expression Omnibus databases. The diagnostic value of HLX was analyzed by the R package “pROC.” The overall survival was estimated using the “survival” and “survminer” packages. A nomogram was established to predict 1-, 3-, and 5-year overall survival of CRC patients. The CIBERSORT software was employed to calculate the relative proportions of 22 immune cells.

          Results

          HLX expression was downregulated in CRC patients. Remarkably, HLX expression was increased with stage (stage I–stage III) of CRC, and the CRC patients with high HLX expression exhibited a poor prognosis. The promoter methylation level of HLX was prominently increased in CRC samples compared to paracancerous samples. We also found that the six miRNAs target HLX genes, leading to its downregulation, and HLX expression had a negative correlation with its downstream target gene BRI3BP in both CRC and normal samples. Finally, we found that the 12 immune infiltrating cells were observably different between high and low HLX expression groups. The HLX had a significant positive correlation with 8 immune checkpoints (PD-1 (PDCD1), CTLA4, PDL-1 (CD274), PDL-2 (PDCD1LG2), CD80, CD86, LAG3, and TIGIT) expressions.

          Conclusion

          HLX probably played a carcinostasis role in the early stages of CRC but exhibited a cancer-promoting effect in the advanced stages. Meanwhile, HLX could serve as a reliable prognostic indicator for CRC.

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          Most cited references43

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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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            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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              Robust enumeration of cell subsets from tissue expression profiles

              We introduce CIBERSORT, a method for characterizing cell composition of complex tissues from their gene expression profiles. When applied to enumeration of hematopoietic subsets in RNA mixtures from fresh, frozen, and fixed tissues, including solid tumors, CIBERSORT outperformed other methods with respect to noise, unknown mixture content, and closely related cell types. CIBERSORT should enable large-scale analysis of RNA mixtures for cellular biomarkers and therapeutic targets (http://cibersort.stanford.edu).
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                Author and article information

                Contributors
                Journal
                Can J Gastroenterol Hepatol
                Can J Gastroenterol Hepatol
                CJGH
                Canadian Journal of Gastroenterology & Hepatology
                Hindawi
                2291-2789
                2291-2797
                2023
                9 September 2023
                : 2023
                : 5521544
                Affiliations
                1Department of Colorectal Surgery, Tianjin Union Medical Center, Hongqiao District, Tianjin 300121, China
                2Department of Cardiothoracic Surgery, Army Hospital of the 80th Group, Weicheng District, Weifang 261021, Shandong, China
                3Nankai University, No. 94 Weijin Road, Nankai District, Tianjin 300074, China
                Author notes

                Academic Editor: Antonio Giovanni Solimando

                Author information
                https://orcid.org/0000-0002-9433-9368
                Article
                10.1155/2023/5521544
                10505080
                37719132
                c147b962-98cc-4715-bc5a-060c92006741
                Copyright © 2023 Shuo Chen et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 March 2023
                : 16 August 2023
                : 29 August 2023
                Funding
                Funded by: Natural Science Foundation of Tianjin City
                Award ID: 20JCYBJC01230
                Categories
                Research Article

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