Georgia Mitsa, Livia Florianova, Josiane Lafleur, Adriana Aguilar-Mahecha, Rene P Zahedi, Sonia V Del Rincon, Mark Basik, Christoph H Borchers, Gerald Batist
{"title":"Clinical Proteomics Reveals Vulnerabilities in Noninvasive Breast Ductal Carcinoma and Drives Personalized Treatment Strategies.","authors":"Georgia Mitsa, Livia Florianova, Josiane Lafleur, Adriana Aguilar-Mahecha, Rene P Zahedi, Sonia V Del Rincon, Mark Basik, Christoph H Borchers, Gerald Batist","doi":"10.1158/2767-9764.CRC-24-0287","DOIUrl":null,"url":null,"abstract":"<p><strong>Abstract: </strong>Ductal carcinoma in situ (DCIS) is the most common type (80%) of noninvasive breast lesions in women. The lack of validated prognostic markers, limited patient numbers, and variable tissue quality have a significant impact on the diagnosis, risk stratification, patient enrollment, and results of clinical studies. In this study, we performed label-free quantitative proteomics on 50 clinical formalin-fixed, paraffin-embedded biopsies, validating 22 putative biomarkers from independent genetic studies. Our comprehensive proteomic phenotyping reveals more than 380 differentially expressed proteins and metabolic vulnerabilities, which can inform new therapeutic strategies for DCIS and invasive ductal carcinoma. Due to the readily druggable nature of proteins and metabolic enzymes or metabolism inhibitors, this study is of high interest for clinical research and the pharmaceutical industry. To further evaluate our findings, and to promote the clinical translation of our study, we developed a highly multiplexed targeted proteomics assay for 90 proteins associated with cancer metabolism, RNA regulation, and signature cancer pathways, such as PI3K/AKT/mTOR and EGFR/RAS/RAF.</p><p><strong>Significance: </strong>This study provides real-world evidence for DCIS, a disease for which currently no molecular tools or biomarkers exist, and gives an unbiased, comprehensive, and deep proteomic profile, identifying >380 actionable targets.</p>","PeriodicalId":72516,"journal":{"name":"Cancer research communications","volume":" ","pages":"138-149"},"PeriodicalIF":2.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11755405/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer research communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1158/2767-9764.CRC-24-0287","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract: Ductal carcinoma in situ (DCIS) is the most common type (80%) of noninvasive breast lesions in women. The lack of validated prognostic markers, limited patient numbers, and variable tissue quality have a significant impact on the diagnosis, risk stratification, patient enrollment, and results of clinical studies. In this study, we performed label-free quantitative proteomics on 50 clinical formalin-fixed, paraffin-embedded biopsies, validating 22 putative biomarkers from independent genetic studies. Our comprehensive proteomic phenotyping reveals more than 380 differentially expressed proteins and metabolic vulnerabilities, which can inform new therapeutic strategies for DCIS and invasive ductal carcinoma. Due to the readily druggable nature of proteins and metabolic enzymes or metabolism inhibitors, this study is of high interest for clinical research and the pharmaceutical industry. To further evaluate our findings, and to promote the clinical translation of our study, we developed a highly multiplexed targeted proteomics assay for 90 proteins associated with cancer metabolism, RNA regulation, and signature cancer pathways, such as PI3K/AKT/mTOR and EGFR/RAS/RAF.
Significance: This study provides real-world evidence for DCIS, a disease for which currently no molecular tools or biomarkers exist, and gives an unbiased, comprehensive, and deep proteomic profile, identifying >380 actionable targets.