Algorithms to link signaling pathways with transcriptional programs for precision medicine

将信号通路与精准医学转录程序联系起来的算法

• 批准号: 10319970
• 负责人: Hatice Ulku Osmanbeyoglu
• 金额: $ 24.9万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-06 至 2023-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10319970
• 关键词: Address; Affinity; Algorithms; Award; Basic Science; Binding; Cancer Biology; Cancer Patient; Cancer cell line; Cell Line; Clinic; Clinical; Clinical Trials Design; Communication; Computer Models; DNA Sequence Alteration; Data; Data Set; Development; Diagnosis; Drug resistance; Enhancers; Epigenetic Process; Event; Foundations; Gene Expression; Gene Expression Profile; Genes; Genetic; Genetic Transcription; Genome; Goals; Growth Factor Receptors; Hand; Laboratories; Lead; Leadership; Learning; Link; Malignant Neoplasms; Measures; Mentorship; Messenger RNA; Methodology; Methods; Modeling; Monoclonal Antibodies; Mutation; Oncogenic; Outcome; Patient-Focused Outcomes; Pharmaceutical Preparations; Phase; Predictive Factor; Protein Array; Proteins; Proteomics; Research; Research Project Grants; Role; Scientist; Signal Pathway; Signal Transduction; Signal Transduction Inhibitor; Signal Transduction Pathway; Signaling Protein; Statistical Models; Training; Translating; Tumor Biology; anticancer research; base; cancer cell; cancer genomics; cancer type; career development; comparative; drug response prediction; drug sensitivity; epigenomics; experience; functional genomics; genomic aberrations; genomic data; insight; learning strategy; mRNA Expression; multi-task learning; novel; patient prognosis; personalized approach; personalized cancer therapy; personalized medicine; phosphoproteomics; precision medicine; predictive modeling; predictive signature; programs; protein expression; regression algorithm; response; skills; small molecule inhibitor; targeted treatment; transcription factor; transcriptomics; tumor

Project Summary/Abstract Cancers arise through the accumulation of genetic and epigenetic alterations that often target signal transduction pathways, leading to dysregulation of downstream transcriptional effectors and widespread gene expression changes. Since many targeted therapies are small molecule inhibitors of signal transduction proteins or monoclonal antibodies against growth factor receptors, deciphering the signaling pathways that are deregulated in a given tumor in order to personalize therapy is a major goal of cancer genomics. The aim of this project is to develop algorithmic approaches linking signaling to transcriptional response for precision medicine. During the K99 phase of the award, I will develop statistical modeling approaches to integrate publicly available transcriptomic, proteomic and genomic data across tumor types with epigenomic data in appropriate cell lines in order to study altered transcriptional programs and signaling pathways in cancer. With these methods in hand, during the R00 phase I will study the impact of common and cancer-specific transcription factor and signaling regulators on clinical outcome and drug response. We expect that our results will lead to new insights in cancer biology and furthermore assist in the design of clinical trials that match actionable oncogenic signatures with personalized therapies. I propose a training plan under the mentorship of a broad, interdisciplinary team of clinicians, scientists, and computational biologists with extensive combined experience in all aspects of the proposed research project. This focused research mentorship, together with frequent presentation of results and informal interactions, will help me develop the communication and leadership skills vital for my transition to independence. In the long term, this training will prepare me to lead a laboratory that centers on developing statistical and computational approaches for precision medicine to bridge the gap between basic science and the clinic.

项目总结/文摘

项目成果

Isolated BAP1 Genomic Alteration in Malignant Pleural Mesothelioma Predicts Distinct Immunogenicity with Implications for Immunotherapeutic Response.

• DOI: 10.3390/cancers14225626
• 发表时间: 2022-11-16
• 期刊: Cancers
• 影响因子: 5.2

The SWI/SNF Protein PBRM1 Restrains VHL-Loss-Driven Clear Cell Renal Cell Carcinoma.

• DOI: 10.1016/j.celrep.2017.02.074
• 发表时间: 2017-03-21
• 期刊: Cell reports
• 影响因子: 8.8
• 作者: Nargund AM;Pham CG;Dong Y;Wang PI;Osmangeyoglu HU;Xie Y;Aras O;Han S;Oyama T;Takeda S;Ray CE;Dong Z;Berge M;Hakimi AA;Monette S;Lekaye CL;Koutcher JA;Leslie CS;Creighton CJ;Weinhold N;Lee W;Tickoo SK;Wang Z;Cheng EH;Hsieh JJ
• 通讯作者: Hsieh JJ

Ets transcription factor GABP controls T cell homeostasis and immunity.

• DOI: 10.1038/s41467-017-01020-6
• 发表时间: 2017-10-20
• 期刊: Nature communications
• 影响因子: 16.6
• 作者: Luo CT;Osmanbeyoglu HU;Do MH;Bivona MR;Toure A;Kang D;Xie Y;Leslie CS;Li MO
• 通讯作者: Li MO

Chromatin accessibility landscape and active transcription factors in primary human invasive lobular and ductal breast carcinomas.

• DOI: 10.1186/s13058-022-01550-y
• 发表时间: 2022-07-29
• 期刊: Breast cancer research : BCR

Single-cell analysis reveals the stromal dynamics and tumor-specific characteristics in the microenvironment of ovarian cancer.

• DOI: 10.1038/s42003-023-05733-x
• 发表时间: 2024-01-05
• 期刊: COMMUNICATIONS BIOLOGY
• 影响因子: 5.9
• 作者: Zhang, Linan;Cascio, Sandra;Mellors, John W.;Buckanovich, Ronald J.;Osmanbeyoglu, Hatice Ulku
• 通讯作者: Osmanbeyoglu, Hatice Ulku