High throughput screening to generate and investigate cancer driver mutations in hepatocellular carcinoma

Active Project Grant Awarded Last action

Award ID
F30CA306325
Recipient
Awarding agency
Obligated
$72,162

Award facts

Assistance listing
93.398 Cancer Research Manpower
Completion date 0% complete
Originally
Place of performance
Worcester, MA 01655, USA

Award details come from USAspending.gov.

Description

As the agency reported it.

Abstract
Cancer remains a leading cause of death in the united states and globally. Understanding the genetic mutations that drive cancer can help inform diagnosis, prognosis, and treatment options. Cancer driver mutations are thought to cause tumor formation and malignancy by leading to abnormal and uncontrolled cellular growth. To date, thousands of cancer driver mutations have been identified in hundreds of genes. Experimental models that precisely install cancer driver mutations are essential for investigating the mechanisms that underlie cancer. Crispr-based prime editing offers a comprehensive way to generate a diverse array of cancer driver mutations, including substitutions, insertions, deletions, or combinations. In prime editing, a prime editing guide RNA (PEGRNA) guides mutant CAS9 to nick one strand of the genome target site and serves as a template for reverse transcriptase (fused to CAS9) to copy new information into the genome. However, designing and validating effective pegrnas is expensive and time-consuming. Preliminary experiments using a high- throughput screening approach based on next generation sequencing identified pegrnas that guide efficient editing. This screen enabled simultaneous testing of thousands of PEGRNA designs for their ability to edit frequent mutations in hepatocellular carcinoma (HCC), the most prevalent form of primary liver cancer. This project aims to use these PEGRNA constructs to further characterize HCC mutations and to generate a mouse model of HCC. Aim 1 will characterize the cellular and molecular effects of HCC driver mutations. Utilizing a library of the highest efficacy pegrnas from the preliminary screen, a secondary screen will be performed to identify mutations that confer a growth advantage in transformed primary human hepatocyte cell lines. Cellular fitness results from this screen will be validated using a competition assay. Cellular and molecular phenotypes of mutations that promote fitness will then be characterized. Colony formation assays will determine the ability of cells with cancer driver mutations to expand into a clonal population. RNA sequencing will reveal transcriptional profiles associated with the cancer mutation. Aim 2 will model HCC driver mutations in vivo. Prime editing will be used to install cancer mutations in transformed primary human hepatocytes, and cells will be orthotopically implanted into the livers of immune-deficient mice via intrahepatic injection. After a period of growth, tumor formation and the histopathology and gene expression signatures of the tumors will be analyzed. This study will be piloted with pegrnas (identified from the preliminary screen) that generated an activating mutation in the conserved gene NOTCH1. In vivo models of cancer driver mutations will be used to assess how tumors respond to treatment with first-line therapies for HCC. Successful completion of this project will generate a system to characterize HCC driver mutations at the cellular level and in tumors, informing potential treatment approaches based on the genetic profiles of cancer.

Transactions

Action Obligated Date
Amendment $36,081
Original award $0

Quick answers

Who received award F30CA306325?

F30CA306325 was awarded to University Of Massachusetts Medical School by National Cancer Institute (National Institutes of Health) on February 15, 2027.

How much is award F30CA306325 worth?

$72,162 has been obligated on F30CA306325.

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