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      Alterations of thyroid microbiota across different thyroid microhabitats in patients with thyroid carcinoma


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          In recent years, the incidence rate of Thyroid carcinoma (TC) has been increasing worldwide. Thus, research on factors of TC carcinogenesis may promote TC prevention and decrease the incidence rate. There are several studies targeting the correlation between gut microbiota and thyroid disease. Carcinogenesis of several malignancies is influenced by microbiota. However, thyroid microbiome of TC has not been revealed. This study investigated thyroid microbiota in different TC microhabitats.


          We performed 16s rRNA gene sequencing using tumor tissues and matched peritumor tissues from 30 patients with TC to characterize thyroid microbiota.


          The richness and diversity of thyroid microbiota were lower in TC tumor samples than in matched peritumor tissues. At the genus level, the core microbiota of thyroid included Sphingomonas, Comamonas, Acinetobacter, Pseudomonas, Microvirgula, and Soonwooa. The abundance of Sphingomonas and Aeromonas was significantly increased in tumor tissues, while the abundance of Comamonas, Acinetobacter, and Peptostreptococcus was significantly enhanced in peritumor tissues. The combination of Comamonas and Sphingomonas could discriminate tumor samples from peritumor samples with an area under the curve (AUC) of 0.981 (95% confidence interval [CI] 0.949–1.000). The abundance of Sphingomonas was significantly higher in N1 stage than in N0 stage. Sphingomonas could distinguish between N0 and N1 stage with an AUC of 0.964 (95% CI 0.907–1.000).


          The microbial diversity and composition were significantly different between peritumor and tumor microhabitats from patients with TC, which may eventually affect TC carcinogenesis and progression. The combination of Comamonas and Sphingomonas could serve as a powerful biomarker for discrimination between tumor and peritumor tissues. Furthermore, the higher abundance of Sphingomonas was correlated with lymph node metastasis, indicating that the abundance of Sphingomonas may indicate a poor prognosis for TC patients, and Sphingomonas may play a role in promoting TC progression.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12967-021-03167-9.

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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            UPARSE: highly accurate OTU sequences from microbial amplicon reads.

            Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.
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              UCHIME improves sensitivity and speed of chimera detection

              Motivation: Chimeric DNA sequences often form during polymerase chain reaction amplification, especially when sequencing single regions (e.g. 16S rRNA or fungal Internal Transcribed Spacer) to assess diversity or compare populations. Undetected chimeras may be misinterpreted as novel species, causing inflated estimates of diversity and spurious inferences of differences between populations. Detection and removal of chimeras is therefore of critical importance in such experiments. Results: We describe UCHIME, a new program that detects chimeric sequences with two or more segments. UCHIME either uses a database of chimera-free sequences or detects chimeras de novo by exploiting abundance data. UCHIME has better sensitivity than ChimeraSlayer (previously the most sensitive database method), especially with short, noisy sequences. In testing on artificial bacterial communities with known composition, UCHIME de novo sensitivity is shown to be comparable to Perseus. UCHIME is >100× faster than Perseus and >1000× faster than ChimeraSlayer. Contact: robert@drive5.com Availability: Source, binaries and data: http://drive5.com/uchime. Supplementary information: Supplementary data are available at Bioinformatics online.

                Author and article information

                J Transl Med
                J Transl Med
                Journal of Translational Medicine
                BioMed Central (London )
                30 November 2021
                30 November 2021
                : 19
                : 488
                [1 ]GRID grid.412604.5, ISNI 0000 0004 1758 4073, Jiangxi Otorhinolaryngology Head and Neck Surgery Institute, Department of Otorhinolaryngology Head and Neck Surgery, , The First Affiliated Hospital of Nanchang University, ; Nanchang, China
                [2 ]GRID grid.13402.34, ISNI 0000 0004 1759 700X, Department of Surgical Oncology, The First Affiliated Hospital, School of Medicine, , Zhejiang University, ; Hangzhou, China
                [3 ]GRID grid.415002.2, ISNI 0000 0004 1757 8108, Department of Otolaryngology Head and Neck Surgery, , Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, ; Nanchang, China
                [4 ]GRID grid.412604.5, ISNI 0000 0004 1758 4073, Department of General Surgery, , The First Affiliated Hospital of Nanchang University, ; Nanchang, China
                [5 ]GRID grid.469636.8, Pathology Department, , Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, ; Linhai, China
                Author information
                © The Author(s) 2021

                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.

                : 12 October 2021
                : 23 November 2021
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 82160527
                Award ID: 81860182
                Award ID: 81772853
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100004479, Natural Science Foundation of Jiangxi Province;
                Award ID: 20181BAB205036
                Award Recipient :
                Funded by: Project of the Regional Diagnosis and Treatment Center of the Health Planning Committee
                Award ID: JBZX-201903
                Award Recipient :
                Funded by: Science and Technology Department of Jiangxi Province
                Award ID: 20203BBGL73201
                Award Recipient :
                Funded by: Health Commission of Jiangxi Province
                Award ID: 202130016
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100010248, Zhejiang Province Public Welfare Technology Application Research Project;
                Award ID: No. LGF20H160023
                Award Recipient :
                Funded by: Medical Health Science and Technology Project of Zhejiang Province
                Award ID: No. 2018273130
                Award Recipient :
                Funded by: The First Affiliated Hospital of Nanchang University
                Award ID: No. YFYPY202002
                Award Recipient :
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                © The Author(s) 2021

                thyroid cancer,microbiome,lymph node metastasis,biomarker,sphingomonas
                thyroid cancer, microbiome, lymph node metastasis, biomarker, sphingomonas


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