Evidence map›Paper›PMID 37101287›Full record

ArticleProteome science2023

Proteomics profiling for the global and acetylated proteins of papillary thyroid cancers.

Wei Wei, Yuezhang Wu, Dong-Dong Chen, Yuntao Song, Guohui Xu, Qi Shi, Xiao-Ping Dong

Abstract read
In one paragraph

Article in Proteome science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Wei WeiKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Head and Neck Surgery Department, Peking University Cancer Hospital & Institute, Beijing, 100142, China.
Yuezhang WuState Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases (Zhejiang University), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Chang-Bai Rd 155, Beijing, 102206, China.
Dong-Dong ChenState Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases (Zhejiang University), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Chang-Bai Rd 155, Beijing, 102206, China.
Yuntao SongKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Head and Neck Surgery Department, Peking University Cancer Hospital & Institute, Beijing, 100142, China.
Guohui XuKey Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Head and Neck Surgery Department, Peking University Cancer Hospital & Institute, Beijing, 100142, China.
Qi ShiState Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases (Zhejiang University), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Chang-Bai Rd 155, Beijing, 102206, China. shiqi76@126.com.
Xiao-Ping DongState Key Laboratory for Infectious Disease Prevention and Control, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases (Zhejiang University), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Chang-Bai Rd 155, Beijing, 102206, China. dongxp238@sina.com.

Funding

Grant from the State Key Laboratory for Infectious Disease Prevention and Control, China CDC 2019SKLID501Grants from the State Key Laboratory for Infectious Disease Prevention and Control, China CDC 2019SKLID307Grants from the State Key Laboratory for Infectious Disease Prevention and Control, China CDC 2019SKLID603
6 · The paper itself

Abstract

backgroundPapillary thyroid carcinoma (PTC) is the most common endocrine malignancy cancer among the malignancies of thyroid. Despite of wide usages of proteomics in PTC, the profile of acetylated proteins in PTC remains unsettled, which is helpful for understanding the carcinogenesis mechanism and identifying useful biomarkers for PTC.

methodsThe surgically removed specimens of cancer tissues (Ca-T) and adjacent normal tissues (Ca-N) from 10 female patients pathological diagnosed as PTC (TNM stage III) were enrolled in the study. After preparing the pooled extracts of the whole proteins and the acetylated proteins from 10 cases, TMT labeling and LC/MS/MS methods were applied to the assays of global proteomics and acetylated proteomics separately. Bioinformatics analysis, including KEGG, gene ontology (GO) and hierarchical clustering were performed. Some differentially expressed proteins (DEPs) and differentially expressed acetylated proteins (DEAPs) were validated by individual Western blots.

resultsControlled with the normal tissues adjacent to the lesions, 147 out of 1923 identified proteins in tumor tissues were considered as DEPs in global proteomics, including 78 up-regulated and 69 down-regulated ones, while 57 out of 311 identified acetylated proteins in tumor tissues were DEAPs in acetylated proteomics, including 32 up-regulated and 25 down-regulated, respectively. The top 3 up- and down-regulated DEPs were fibronectin 1, KRT1B protein and chitinase-3-like protein 1, as well as keratin, type I cytoskeletal 16, A-gamma globin Osilo variant and Huntingtin interacting protein-1. The top 3 up- and down-regulated DEAPs were ribosomal protein L18a-like protein, alpha-1-acid glycoprotein 2 and eukaryotic peptide chain release factor GTP-binding subunit ERF3A, as well as trefoil factor 3, thyroglobulin and histone H2B. Functional GO annotation and KEGG pathway analysis based on the DEPs and DEAPs showed completely different changing pictures. Contrary to the top 10 up- and -down regulated DEPs, most of which were addressed in PTC and other types of carcinomas, changes of the majority DEAPs were not mentioned in the literatures.

conclusionsTaken the profiling of the global and acetylated proteomics together will provide more broad view of protein alterations on the carcinogenesis and new direction for selecting biomarker for diagnosis of PTC.

Indexed as

Acetylated proteinsKEGGPapillary thyroid cancerProteomicsTMT labeling

Identifiers

PMID37101287
PMCPMC10131382

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.