# Evolutionary Heterogeneity of High Grade Glioma

> **NIH NIH K00** · SLOAN-KETTERING INST CAN RESEARCH · 2021 · $100,662

## Abstract

PROJECT SUMMARY/ABSTRACT
Cancer is the result of an orchestrated set of genomic alterations that conspire to drive
uncontrolled cell growth. Dissecting temporal and spatial association of these alterations into
varying time points will provide milestones into initiation, progression, metastasis and/or
resistance to certain therapeutic regimens. Elucidating these milestones could provide invaluable
biomarkers in the context of different stages for treatments and would help to tailor personalized
therapies based on genomic information. We will develop a model to infer a possible ordering of
alterations from longitudinal, multi-region, transcriptomic and single cell data by first discerning
the totality of significant alterations and most likely contributors to progression using a rigorous
genomic approach. Next we will infer potential evolutionary moves of each patient using
sequential samples with a statistical approach rooted in evolutionary biology. Third we will
construct an evolutionary network for the cohort of patients that will delineate and order significant
routes of genomic alteration.

## Key facts

- **NIH application ID:** 10249322
- **Project number:** 5K00CA212478-06
- **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH
- **Principal Investigator:** Erik Ladewig
- **Activity code:** K00 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $100,662
- **Award type:** 5
- **Project period:** 2018-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10249322

## Citation

> US National Institutes of Health, RePORTER application 10249322, Evolutionary Heterogeneity of High Grade Glioma (5K00CA212478-06). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10249322. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*