Yongchao Dou, Lizabeth Katsnelson, Marina A Gritsenko, Yingwei Hu, Boris Reva, Runyu Hong, Yi-Ting Wang, Iga Kolodziejczak, Rita Jui-Hsien Lu, Chia-Feng Tsai, Wen Bu, Wenke Liu, Xiaofang Guo, Eunkyung An, Rebecca C Arend, Jasmin Bavarva, Lijun Chen, Rosalie K Chu, Andrzej Czekański, Teresa Davoli, Elizabeth G Demicco, Deborah DeLair, Kelly Devereaux, Saravana M Dhanasekaran, Peter Dottino, Bailee Dover, Thomas L Fillmore, McKenzie Foxall, Catherine E Hermann, Tara Hiltke, Galen Hostetter, Marcin Jędryka, Scott D Jewell, Isabelle Johnson, Andrea G Kahn, Amy T Ku, Chandan Kumar-Sinha, Paweł Kurzawa, Alexander J Lazar, Rossana Lazcano, Jonathan T Lei, Yi Li, Yuxing Liao, Tung-Shing M Lih, Tai-Tu Lin, John A Martignetti, Ramya P Masand, Rafał Matkowski, Wilson McKerrow, Mehdi Mesri, Matthew E Monroe, Jamie Moon, Ronald J Moore, Michael D Nestor, Chelsea Newton, Tatiana Omelchenko, Gilbert S Omenn, Samuel H Payne, Vladislav A Petyuk, Ana I Robles, Henry Rodriguez, Kelly V Ruggles, Dmitry Rykunov, Sara R Savage, Athena A Schepmoes, Tujin Shi, Zhiao Shi, Jimin Tan, Mason Taylor, Mathangi Thiagarajan, Joshua M Wang, Karl K Weitz, Bo Wen, C M Williams, Yige Wu, Matthew A Wyczalkowski, Xinpei Yi, Xu Zhang, Rui Zhao, David Mutch, Arul M Chinnaiyan, Richard D Smith, Alexey I Nesvizhskii, Pei Wang, Maciej Wiznerowicz, Li Ding, D R Mani, Hui Zhang, Matthew L Anderson, Karin D Rodland, Bing Zhang, Tao Liu, David Fenyö
{"title":"蛋白质组学研究提示子宫内膜癌的药物途径。","authors":"Yongchao Dou, Lizabeth Katsnelson, Marina A Gritsenko, Yingwei Hu, Boris Reva, Runyu Hong, Yi-Ting Wang, Iga Kolodziejczak, Rita Jui-Hsien Lu, Chia-Feng Tsai, Wen Bu, Wenke Liu, Xiaofang Guo, Eunkyung An, Rebecca C Arend, Jasmin Bavarva, Lijun Chen, Rosalie K Chu, Andrzej Czekański, Teresa Davoli, Elizabeth G Demicco, Deborah DeLair, Kelly Devereaux, Saravana M Dhanasekaran, Peter Dottino, Bailee Dover, Thomas L Fillmore, McKenzie Foxall, Catherine E Hermann, Tara Hiltke, Galen Hostetter, Marcin Jędryka, Scott D Jewell, Isabelle Johnson, Andrea G Kahn, Amy T Ku, Chandan Kumar-Sinha, Paweł Kurzawa, Alexander J Lazar, Rossana Lazcano, Jonathan T Lei, Yi Li, Yuxing Liao, Tung-Shing M Lih, Tai-Tu Lin, John A Martignetti, Ramya P Masand, Rafał Matkowski, Wilson McKerrow, Mehdi Mesri, Matthew E Monroe, Jamie Moon, Ronald J Moore, Michael D Nestor, Chelsea Newton, Tatiana Omelchenko, Gilbert S Omenn, Samuel H Payne, Vladislav A Petyuk, Ana I Robles, Henry Rodriguez, Kelly V Ruggles, Dmitry Rykunov, Sara R Savage, Athena A Schepmoes, Tujin Shi, Zhiao Shi, Jimin Tan, Mason Taylor, Mathangi Thiagarajan, Joshua M Wang, Karl K Weitz, Bo Wen, C M Williams, Yige Wu, Matthew A Wyczalkowski, Xinpei Yi, Xu Zhang, Rui Zhao, David Mutch, Arul M Chinnaiyan, Richard D Smith, Alexey I Nesvizhskii, Pei Wang, Maciej Wiznerowicz, Li Ding, D R Mani, Hui Zhang, Matthew L Anderson, Karin D Rodland, Bing Zhang, Tao Liu, David Fenyö","doi":"10.1016/j.ccell.2023.07.007","DOIUrl":null,"url":null,"abstract":"<p><p>We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.</p>","PeriodicalId":9670,"journal":{"name":"Cancer Cell","volume":"41 9","pages":"1586-1605.e15"},"PeriodicalIF":44.5000,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10631452/pdf/","citationCount":"0","resultStr":"{\"title\":\"Proteogenomic insights suggest druggable pathways in endometrial carcinoma.\",\"authors\":\"Yongchao Dou, Lizabeth Katsnelson, Marina A Gritsenko, Yingwei Hu, Boris Reva, Runyu Hong, Yi-Ting Wang, Iga Kolodziejczak, Rita Jui-Hsien Lu, Chia-Feng Tsai, Wen Bu, Wenke Liu, Xiaofang Guo, Eunkyung An, Rebecca C Arend, Jasmin Bavarva, Lijun Chen, Rosalie K Chu, Andrzej Czekański, Teresa Davoli, Elizabeth G Demicco, Deborah DeLair, Kelly Devereaux, Saravana M Dhanasekaran, Peter Dottino, Bailee Dover, Thomas L Fillmore, McKenzie Foxall, Catherine E Hermann, Tara Hiltke, Galen Hostetter, Marcin Jędryka, Scott D Jewell, Isabelle Johnson, Andrea G Kahn, Amy T Ku, Chandan Kumar-Sinha, Paweł Kurzawa, Alexander J Lazar, Rossana Lazcano, Jonathan T Lei, Yi Li, Yuxing Liao, Tung-Shing M Lih, Tai-Tu Lin, John A Martignetti, Ramya P Masand, Rafał Matkowski, Wilson McKerrow, Mehdi Mesri, Matthew E Monroe, Jamie Moon, Ronald J Moore, Michael D Nestor, Chelsea Newton, Tatiana Omelchenko, Gilbert S Omenn, Samuel H Payne, Vladislav A Petyuk, Ana I Robles, Henry Rodriguez, Kelly V Ruggles, Dmitry Rykunov, Sara R Savage, Athena A Schepmoes, Tujin Shi, Zhiao Shi, Jimin Tan, Mason Taylor, Mathangi Thiagarajan, Joshua M Wang, Karl K Weitz, Bo Wen, C M Williams, Yige Wu, Matthew A Wyczalkowski, Xinpei Yi, Xu Zhang, Rui Zhao, David Mutch, Arul M Chinnaiyan, Richard D Smith, Alexey I Nesvizhskii, Pei Wang, Maciej Wiznerowicz, Li Ding, D R Mani, Hui Zhang, Matthew L Anderson, Karin D Rodland, Bing Zhang, Tao Liu, David Fenyö\",\"doi\":\"10.1016/j.ccell.2023.07.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. 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Proteogenomic insights suggest druggable pathways in endometrial carcinoma.
We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.
期刊介绍：
Cancer Cell is a journal that focuses on promoting major advances in cancer research and oncology. The primary criteria for considering manuscripts are as follows:
Major advances: Manuscripts should provide significant advancements in answering important questions related to naturally occurring cancers.
Translational research: The journal welcomes translational research, which involves the application of basic scientific findings to human health and clinical practice.
Clinical investigations: Cancer Cell is interested in publishing clinical investigations that contribute to establishing new paradigms in the treatment, diagnosis, or prevention of cancers.
Insights into cancer biology: The journal values clinical investigations that provide important insights into cancer biology beyond what has been revealed by preclinical studies.
Mechanism-based proof-of-principle studies: Cancer Cell encourages the publication of mechanism-based proof-of-principle clinical studies, which demonstrate the feasibility of a specific therapeutic approach or diagnostic test.
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