Christopher C Jackson, Jia Jenny Liu, Howard Y Liu, Steven G Williams, Asim Anees, Zainab Noor, Natasha Lucas, Dylan Xavier, Peter G Hains, Daniel Bucio-Noble, Adel T Aref, Sandro V Porceddu, Rahul Ladwa, Joseph Whitfield, Roger R Reddel, Qing Zhong, Benedict J Panizza, Phillip J Robinson
{"title":"人乳头状瘤病毒相关口咽鳞状细胞癌的蛋白质组特征可预测高复发风险患者。","authors":"Christopher C Jackson, Jia Jenny Liu, Howard Y Liu, Steven G Williams, Asim Anees, Zainab Noor, Natasha Lucas, Dylan Xavier, Peter G Hains, Daniel Bucio-Noble, Adel T Aref, Sandro V Porceddu, Rahul Ladwa, Joseph Whitfield, Roger R Reddel, Qing Zhong, Benedict J Panizza, Phillip J Robinson","doi":"10.1158/2767-9764.CRC-23-0460","DOIUrl":null,"url":null,"abstract":"<p><strong>Significance: </strong>HPV+OPSCC incidence is increasing, with heterogeneous treatment outcomes despite favorable prognosis. Current de-escalation strategies show inferior results, highlighting the need for precise risk stratification. Using data-independent acquisition mass spectrometry proteomics, we identified a 26-peptide signature that stratifies patients into risk categories, potentially enabling personalized treatment decisions and optimal patient selection for de-escalation trials.</p>","PeriodicalId":72516,"journal":{"name":"Cancer research communications","volume":" ","pages":"580-593"},"PeriodicalIF":2.0000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11979894/pdf/","citationCount":"0","resultStr":"{\"title\":\"A Proteomic Signature for Human Papillomavirus-Associated Oropharyngeal Squamous Cell Carcinoma Predicts Patients at High Risk of Recurrence.\",\"authors\":\"Christopher C Jackson, Jia Jenny Liu, Howard Y Liu, Steven G Williams, Asim Anees, Zainab Noor, Natasha Lucas, Dylan Xavier, Peter G Hains, Daniel Bucio-Noble, Adel T Aref, Sandro V Porceddu, Rahul Ladwa, Joseph Whitfield, Roger R Reddel, Qing Zhong, Benedict J Panizza, Phillip J Robinson\",\"doi\":\"10.1158/2767-9764.CRC-23-0460\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Significance: </strong>HPV+OPSCC incidence is increasing, with heterogeneous treatment outcomes despite favorable prognosis. Current de-escalation strategies show inferior results, highlighting the need for precise risk stratification. Using data-independent acquisition mass spectrometry proteomics, we identified a 26-peptide signature that stratifies patients into risk categories, potentially enabling personalized treatment decisions and optimal patient selection for de-escalation trials.</p>\",\"PeriodicalId\":72516,\"journal\":{\"name\":\"Cancer research communications\",\"volume\":\" \",\"pages\":\"580-593\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11979894/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cancer research communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1158/2767-9764.CRC-23-0460\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cancer research communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1158/2767-9764.CRC-23-0460","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ONCOLOGY","Score":null,"Total":0}
A Proteomic Signature for Human Papillomavirus-Associated Oropharyngeal Squamous Cell Carcinoma Predicts Patients at High Risk of Recurrence.
Significance: HPV+OPSCC incidence is increasing, with heterogeneous treatment outcomes despite favorable prognosis. Current de-escalation strategies show inferior results, highlighting the need for precise risk stratification. Using data-independent acquisition mass spectrometry proteomics, we identified a 26-peptide signature that stratifies patients into risk categories, potentially enabling personalized treatment decisions and optimal patient selection for de-escalation trials.
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