{"title":"使用质谱法鉴定结直肠癌中癌症相关蛋白。","authors":"Naoyuki Toyota, Ryo Konno, Shuhei Iwata, Shin Fujita, Yoshio Kodera, Rei Noguchi, Tadashi Kondo, Yusuke Kawashima, Yuki Yoshimatsu","doi":"10.3390/proteomes13030038","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide, with a multifactorial etiology involving genetic and environmental factors. Advanced proteomics offers valuable insights into the molecular mechanisms of cancer, identifying proteins that function as mediators in tumor biology.</p><p><strong>Methods: </strong>In this study, we used mass spectrometry-based data-independent acquisition (DIA) to analyze the proteomic landscape of CRC. We compared protein abundance in normal and tumor tissues from 16 patients with CRC to identify cancer-associated proteins and examine their roles in disease progression.</p><p><strong>Results: </strong>The analysis identified 10,329 proteins, including 531 cancer-associated proteins from the Catalogue Of Somatic Mutations In Cancer (COSMIC) database, and 48 proteins specifically linked to CRC. Notably, clusters of proteins showed consistent increases or decreases in abundance across disease stages, suggesting their roles in tumorigenesis and progression.</p><p><strong>Conclusions: </strong>Our findings suggest that proteome abundance trends may contribute to the identification of biomarker candidates and therapeutic targets in colorectal cancer. However, given the limited sample size and lack of subtype stratification, further studies using larger, statistically powered cohorts are warranted to establish clinical relevance. These proteins may provide insights into drug resistance and tumor heterogeneity. Limitations of the study include the inability to detect low-abundance proteins and reliance on protein abundance rather than functional activity. Future complementary approaches, such as affinity proteomics, are suggested to address these limitations.</p>","PeriodicalId":20877,"journal":{"name":"Proteomes","volume":"13 3","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12372073/pdf/","citationCount":"0","resultStr":"{\"title\":\"Identification of Cancer-Associated Proteins in Colorectal Cancer Using Mass Spectrometry.\",\"authors\":\"Naoyuki Toyota, Ryo Konno, Shuhei Iwata, Shin Fujita, Yoshio Kodera, Rei Noguchi, Tadashi Kondo, Yusuke Kawashima, Yuki Yoshimatsu\",\"doi\":\"10.3390/proteomes13030038\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide, with a multifactorial etiology involving genetic and environmental factors. Advanced proteomics offers valuable insights into the molecular mechanisms of cancer, identifying proteins that function as mediators in tumor biology.</p><p><strong>Methods: </strong>In this study, we used mass spectrometry-based data-independent acquisition (DIA) to analyze the proteomic landscape of CRC. We compared protein abundance in normal and tumor tissues from 16 patients with CRC to identify cancer-associated proteins and examine their roles in disease progression.</p><p><strong>Results: </strong>The analysis identified 10,329 proteins, including 531 cancer-associated proteins from the Catalogue Of Somatic Mutations In Cancer (COSMIC) database, and 48 proteins specifically linked to CRC. Notably, clusters of proteins showed consistent increases or decreases in abundance across disease stages, suggesting their roles in tumorigenesis and progression.</p><p><strong>Conclusions: </strong>Our findings suggest that proteome abundance trends may contribute to the identification of biomarker candidates and therapeutic targets in colorectal cancer. However, given the limited sample size and lack of subtype stratification, further studies using larger, statistically powered cohorts are warranted to establish clinical relevance. These proteins may provide insights into drug resistance and tumor heterogeneity. Limitations of the study include the inability to detect low-abundance proteins and reliance on protein abundance rather than functional activity. Future complementary approaches, such as affinity proteomics, are suggested to address these limitations.</p>\",\"PeriodicalId\":20877,\"journal\":{\"name\":\"Proteomes\",\"volume\":\"13 3\",\"pages\":\"\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2025-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12372073/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proteomes\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/proteomes13030038\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proteomes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/proteomes13030038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Identification of Cancer-Associated Proteins in Colorectal Cancer Using Mass Spectrometry.
Background: Colorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide, with a multifactorial etiology involving genetic and environmental factors. Advanced proteomics offers valuable insights into the molecular mechanisms of cancer, identifying proteins that function as mediators in tumor biology.
Methods: In this study, we used mass spectrometry-based data-independent acquisition (DIA) to analyze the proteomic landscape of CRC. We compared protein abundance in normal and tumor tissues from 16 patients with CRC to identify cancer-associated proteins and examine their roles in disease progression.
Results: The analysis identified 10,329 proteins, including 531 cancer-associated proteins from the Catalogue Of Somatic Mutations In Cancer (COSMIC) database, and 48 proteins specifically linked to CRC. Notably, clusters of proteins showed consistent increases or decreases in abundance across disease stages, suggesting their roles in tumorigenesis and progression.
Conclusions: Our findings suggest that proteome abundance trends may contribute to the identification of biomarker candidates and therapeutic targets in colorectal cancer. However, given the limited sample size and lack of subtype stratification, further studies using larger, statistically powered cohorts are warranted to establish clinical relevance. These proteins may provide insights into drug resistance and tumor heterogeneity. Limitations of the study include the inability to detect low-abundance proteins and reliance on protein abundance rather than functional activity. Future complementary approaches, such as affinity proteomics, are suggested to address these limitations.
ProteomesBiochemistry, Genetics and Molecular Biology-Clinical Biochemistry
CiteScore
6.50
自引率
3.00%
发文量
37
审稿时长
11 weeks
期刊介绍:
Proteomes (ISSN 2227-7382) is an open access, peer reviewed journal on all aspects of proteome science. Proteomes covers the multi-disciplinary topics of structural and functional biology, protein chemistry, cell biology, methodology used for protein analysis, including mass spectrometry, protein arrays, bioinformatics, HTS assays, etc. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. Therefore, there is no restriction on the length of papers. Scope: -whole proteome analysis of any organism -disease/pharmaceutical studies -comparative proteomics -protein-ligand/protein interactions -structure/functional proteomics -gene expression -methodology -bioinformatics -applications of proteomics