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      Multimodal metagenomic analysis reveals microbial single nucleotide variants as superior biomarkers for early detection of colorectal cancer

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          ABSTRACT

          Microbial signatures show remarkable potentials in predicting colorectal cancer (CRC). This study aimed to evaluate the diagnostic powers of multimodal microbial signatures, multi-kingdom species, genes, and single-nucleotide variants (SNVs) for detecting precancerous adenomas. We performed cross-cohort analyses on whole metagenome sequencing data of 750 samples via xMarkerFinder to identify adenoma-associated microbial multimodal signatures. Our data revealed that fungal species outperformed species from other kingdoms with an area under the ROC curve (AUC) of 0.71 in distinguishing adenomas from controls. The microbial SNVs, including dark SNVs with synonymous mutations, displayed the strongest diagnostic capability with an AUC value of 0.89, sensitivity of 0.79, specificity of 0.85, and Matthews correlation coefficient (MCC) of 0.74. SNV biomarkers also exhibited outstanding performances in three independent validation cohorts (AUCs = 0.83, 0.82, 0.76; sensitivity = 1.0, 0.72, 0.93; specificity = 0.67, 0.81, 0.67, MCCs = 0.69, 0.83, 0.72) with high disease specificity for adenoma. In further support of the above results, functional analyses revealed more frequent inter-kingdom associations between bacteria and fungi, and abnormalities in quorum sensing, purine and butanoate metabolism in adenoma, which were validated in a newly recruited cohort via qRT-PCR. Therefore, these data extend our understanding of adenoma-associated multimodal alterations in the gut microbiome and provide a rationale of microbial SNVs for the early detection of 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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            Fast gapped-read alignment with Bowtie 2.

            As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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              Improved metagenomic analysis with Kraken 2

              Although Kraken’s k-mer-based approach provides a fast taxonomic classification of metagenomic sequence data, its large memory requirements can be limiting for some applications. Kraken 2 improves upon Kraken 1 by reducing memory usage by 85%, allowing greater amounts of reference genomic data to be used, while maintaining high accuracy and increasing speed fivefold. Kraken 2 also introduces a translated search mode, providing increased sensitivity in viral metagenomics analysis.
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                Author and article information

                Journal
                Gut Microbes
                Gut Microbes
                Gut Microbes
                Taylor & Francis
                1949-0976
                1949-0984
                27 August 2023
                2023
                27 August 2023
                : 15
                : 2
                : 2245562
                Affiliations
                [a ]Department of Gastroenterology, the Shanghai Tenth People’s Hospital, School of Medicine, School of Life Sciences and Technology, Tongji University; , Shanghai, P. R. China
                [b ]Guangdong Institute of Gastroenterology; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases; Biomedical Innovation Center, Sun Yat-Sen University; , Guangzhou, P. R. China
                [c ]Department of General Surgery, The Sixth Affiliated Hospital of Sun Yat-Sen University; , Guangzhou, P. R. China
                [d ]National Clinical Research Center for Child Health, the Children’s Hospital, Zhejiang University School of Medicine; , Hangzhou, P. R. China
                [e ]Center for IBD Research, Department of Gastroenterology, the Shanghai Tenth People’s Hospital, School of Medicine, Tongji University; , Shanghai, P. R. China
                [f ]Research Institute, GloriousMed Clinical Laboratory Co, Ltd; , Shanghai, P. R. China
                Author notes
                CONTACT Lixin Zhu zhulx6@ 123456mail.sysu.edu.cn Department of General Surgery, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, P. R. China
                Zhanju Liu liuzhanju88@ 123456126.com Center for IBD Research, Department of Gastroenterology, The Shanghai Tenth People’s Hospital, School of Medicine, Tongji University; , Shanghai 200072, P. R. China
                Ruixin Zhu rxzhu@ 123456tongji.edu.cn Department of Gastroenterology, The Shanghai Tenth People’s Hospital, School of Medicine, School of Life Sciences and Technology, Tongji University; , Shanghai 200072, P. R. China
                Na Jiao jiaona@ 123456zju.edu.cn National Clinical Research Center for Child Health, the Children’s Hospital, Zhejiang University School of Medicine; , Hangzhou, Zhejiang 310058, P. R. China
                [#]

                Wenxing Gao and Xiang Gao contributed equally.

                [*]

                These authors jointly supervised this work.

                Author information
                https://orcid.org/0000-0002-1740-8227
                https://orcid.org/0000-0001-7904-1769
                https://orcid.org/0000-0002-4383-2849
                https://orcid.org/0000-0002-5070-6453
                https://orcid.org/0000-0003-3976-6313
                Article
                2245562
                10.1080/19490976.2023.2245562
                10464540
                37635357
                8107494f-52ee-46b5-924b-8f119f517dae
                © 2023 The Author(s). Published with license by Taylor & Francis Group, LLC.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

                History
                Page count
                Figures: 6, References: 57, Pages: 1
                Categories
                Research Article
                Research Paper

                Microbiology & Virology
                colorectal cancer,precancerous adenoma,early detection,noninvasive,microbial multimodal biomarkers,single-nucleotide variant,synonymous mutation

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