# Algorithms to link signaling pathways with transcriptional programs for precision medicine

> **NIH NIH R00** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2020 · $239,732

## Abstract

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.

## Key facts

- **NIH application ID:** 9832181
- **Project number:** 5R00CA207871-04
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Hatice Ulku Osmanbeyoglu
- **Activity code:** R00 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $239,732
- **Award type:** 5
- **Project period:** 2016-07-06 → 2021-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9832181

## Citation

> US National Institutes of Health, RePORTER application 9832181, Algorithms to link signaling pathways with transcriptional programs for precision medicine (5R00CA207871-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9832181. Licensed CC0.

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