# Multiscale Computational Oncology Research Core

> **NIH NIH U54** · UNIVERSITY OF TX MD ANDERSON CAN CTR · 2022 · $245,497

## Abstract

MULTISCALE COMPUTATIONAL ONCOLOGY RESEARCH CORE (M-CORE) – Abstract
The Multiscale Computational Oncology Research Core (M-CORE) provides computational oncology
expertise from initial experimental design and power studies to ongoing data generation and analysis to data
deposition and sharing for single-cell and genomics data. Core Leader Dr. Fertig is a leader in single-cell multi-
omics for applications to cancer, with a particular focus on translational pancreatic cancer research applications.
The M-CORE will support high-throughput data analysis in all three Tri-State Pancreatic Adenocarcinoma TBEL
(Tri-PACT) Center Projects and Collaborative Projects. Methods will be applied to bridge spatial and temporal
scales to identify cell intrinsic mechanisms underlying pre-malignant lesions progression into invasive cancers.
These will be extended to analyze cell extrinsic, intercellular interactions that mediate malignancy development
and tumor initiation incorporating new three-dimensional imaging technologies from Tri-PACT. Many of these
methods were recently developed by the Core leader, and new algorithms will be developed specifically to meet
the TBEL needs and provide synergy across Projects. Research Projects will be testbeds for new single-cell
methods for dynamic spatial processes and novel imaging technologies, and computational Collaborative
Projects will benefit from M-CORE resources. Standardization in the Core will harmonize data to enable meta-
analyses between biological models and human precursor lesions, biological mechanisms from the Projects,
and novel mechanisms associated with precancer through cross-disease analysis in the broader TBEL
consortium in collaboration with the Coordinating and Data Management Center (CDMC). The Core Leader will
participate in all regular Center meetings and collaborate closely with the TBEL CDMC to ensure ample
computational resources for new research directions. The Core will partner with the TBEL CDMC to assist with
data standards and harmonization, data validation, data wrangling, and overall data deposition, data and
software sharing, and genomic data sharing. In summary, the M-CORE will support the overall TBEL research
objectives by providing computational methods to characterize the mechanisms of malignancy initiation and
progression into invasive tumors; to analyze spatial and temporal data to infer interactions and crosstalk between
pre-malignant cells with stromal cells, and other cells in the microenvironment; and to perform integrative
analyses to promote Tri-PACT and Consortium synergy by identifying shared mechanisms.

## Key facts

- **NIH application ID:** 10518940
- **Project number:** 1U54CA274371-01
- **Recipient organization:** UNIVERSITY OF TX MD ANDERSON CAN CTR
- **Principal Investigator:** Elana Fertig
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $245,497
- **Award type:** 1
- **Project period:** 2022-09-21 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10518940

## Citation

> US National Institutes of Health, RePORTER application 10518940, Multiscale Computational Oncology Research Core (1U54CA274371-01). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10518940. Licensed CC0.

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