Dataset Information

Proteomics of the Gastric cancer Response to Chemotherapy

ABSTRACT: Herein, we set out to investigate the responses to first-line therapies (DOS, XELOX, and anti-HER2-based therapies) for GC through a comprehensive proteomic analysis. We constructed a GC cohort that covered three clinical therapy subcohorts, including a DOS subcohort (44 patients treated with DOS therapy), an XELOX subcohort (70 patients treated with XELOX therapy) and a HER2 subcohort (71 patients who received anti-HER2-based therapy).

ORGANISM(S): Homo Sapiens

SUBMITTER: Chen Ding

PROVIDER: PXD024255 | iProX | Fri Sep 09 00:00:00 BST 2022

REPOSITORIES: iProX

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Publications

Proteomic characterization of gastric cancer response to chemotherapy and targeted therapy reveals new therapeutic strategies.

Li Yan Y Xu Chen C Wang Bing B Xu Fujiang F Ma Fahan F Qu Yuanyuan Y Jiang Dongxian D Li Kai K Feng Jinwen J Tian Sha S Wu Xiaohui X Wang Yunzhi Y Liu Yang Y Qin Zhaoyu Z Liu Yalan Y Qin Jing J Song Qi Q Zhang Xiaolei X Sujie Akesu A Huang Jie J Liu Tianshu T Shen Kuntang K Zhao Jian-Yuan JY Hou Yingyong Y Ding Chen C

Nature communications 20220929 1

Chemotherapy and targeted therapy are the major treatments for gastric cancer (GC), but drug resistance limits its effectiveness. Here, we profile the proteome of 206 tumor tissues from patients with GC undergoing either chemotherapy or anti-HER2-based therapy. Proteome-based classification reveals four subtypes (G-I-G-IV) related to different clinical and molecular features. MSI-sig high GC patients benefit from docetaxel combination treatment, accompanied by anticancer immune response. Further ...[more]

PMID: 36175412

Publication: 1/2

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Project description:Faratian2009 - Role of PTEN in Trastuzumab resistance This model is described in the article: Systems biology reveals new strategies for personalizing cancer medicine and confirms the role of PTEN in resistance to trastuzumab. Faratian D, Goltsov A, Lebedeva G, Sorokin A, Moodie S, Mullen P, Kay C, Um IH, Langdon S, Goryanin I, Harrison DJ. Cancer Res. 2009 Aug; 69(16): 6713-6720 Abstract: Resistance to targeted cancer therapies such as trastuzumab is a frequent clinical problem not solely because of insufficient expression of HER2 receptor but also because of the overriding activation states of cell signaling pathways. Systems biology approaches lend themselves to rapid in silico testing of factors, which may confer resistance to targeted therapies. Inthis study, we aimed to develop a new kinetic model that could be interrogated to predict resistance to receptor tyrosine kinase (RTK) inhibitor therapies and directly test predictions in vitro and in clinical samples. The new mathematical model included RTK inhibitor antibody binding, HER2/HER3 dimerization and inhibition, AKT/mitogen-activated protein kinase cross-talk, and the regulatory properties of PTEN. The model was parameterized using quantitative phosphoprotein expression data from cancer cell lines using reverse-phase protein microarrays. Quantitative PTEN protein expression was found to be the key determinant of resistance to anti-HER2 therapy in silico, which was predictive of unseen experiments in vitro using the PTEN inhibitor bp(V). When measured in cancer cell lines, PTEN expression predicts sensitivity to anti-HER2 therapy; furthermore, this quantitative measurement is more predictive of response (relative risk, 3.0; 95% confidence interval, 1.6-5.5; P < 0.0001) than other pathway components taken in isolation and when tested by multivariate analysis in a cohort of 122 breast cancers treated with trastuzumab. For the first time, a systems biology approach has successfully been used to stratify patients for personalized therapy in cancer and is further compelling evidence that PTEN, appropriately measured in the clinical setting, refines clinical decision making in patients treated with anti-HER2 therapies. This model is hosted on BioModels Database and identified by: BIOMD0000000424. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Dataset Information

Proteomics of the Gastric cancer Response to Chemotherapy

Publications

Proteomic characterization of gastric cancer response to chemotherapy and targeted therapy reveals new therapeutic strategies.

Similar Datasets

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