R01CA285426
Project Grant
Overview
Grant Description
A network approach to interrogate cellular plasticity and drug resistance in cancer - abstract
We will address a critical problem in clinical oncology, namely how highly heterogeneous, drug resistant tumor cell populations develop, and how they can be targeted.
Most tumors develop resistance to almost every type of therapy, including targeted-, radiation-, chemo- or immunotherapy, ultimately leading to cancer deaths.
It is essential to develop novel methods to understand the processes leading to drug resistance under complex in vivo conditions where stromal and immune elements interact with malignant cells.
We will study squamous cell carcinomas (SCCs), a major contributor to human cancer burden and one of the most common solid tumor types that arise in a range of tissues including head and neck, lung, esophagus, bladder, and skin.
We will use a well-established multistage, carcinogen-induced, cutaneous SCC mouse model and credential its’ representation of human cancer drug resistance.
Mouse CSCCs display many genetic alterations seen in human SCCs, including mutation of RAS, PI3 kinase and NOTCH pathways.
The model also incorporates the critical role played by non-mutagenic tumor promoting factors as cancer drivers.
This proposal will build on our previous work, accessing our extensive in-house mouse tumor genomics and transcriptomics databases.
In Aim 1, we will use single cell analyses of primary papillomas, carcinomas and metastases induced by chemical carcinogenesis in situ and analyzed before and during chemo- or immunotherapies.
We will use our novel biocomputational metagene approach to identify rewiring of transcriptomic networks within single tumor cells after therapy.
Single cell analyses, namely scRNAseq, CyTOF, MIBI, and FISH, will be combined with our in- house developed analytical tools, to identify high plasticity state tumor cell populations enriched or depleted in response to therapy and their molecular and spatial relationship to other cells and structures within the tumor.
In Aim 2, we will test the fidelity of the chemical carcinogenesis model as a robust representation of human CSCC biology by undertaking longitudinal validation studies of fresh human CSCC tissue collected before and during chemo- or immuno-therapy and analyzed using the same technology.
In Aim 3, we will empirically test the function of candidate genes (metagene components) expressed in the high plasticity state, for their contribution to drug resistance.
CRISPRi/dCas9 and CRISPR/multiCas12a technology will be used to test gene activities during drug therapy by single or combinatorial gene knockdown in syngeneic tumor models in vivo.
Our strategy will credential the use of the skin chemical carcinogenesis system to model features of human cancer drug resistance.
The project is responsive to PAR-23-281, as it undertakes cross-species discovery of the molecular basis for development of drug resistant tumor cells.
The knowledge to be gained will contribute to discovery of biomarkers and therapeutic targets for this drug resistant cell population.
Our computational methodology and our extensive transcriptomic data from hundreds of tissue and tumor samples will be shared with the Oncology Models Forum NCIP Hub.
We will address a critical problem in clinical oncology, namely how highly heterogeneous, drug resistant tumor cell populations develop, and how they can be targeted.
Most tumors develop resistance to almost every type of therapy, including targeted-, radiation-, chemo- or immunotherapy, ultimately leading to cancer deaths.
It is essential to develop novel methods to understand the processes leading to drug resistance under complex in vivo conditions where stromal and immune elements interact with malignant cells.
We will study squamous cell carcinomas (SCCs), a major contributor to human cancer burden and one of the most common solid tumor types that arise in a range of tissues including head and neck, lung, esophagus, bladder, and skin.
We will use a well-established multistage, carcinogen-induced, cutaneous SCC mouse model and credential its’ representation of human cancer drug resistance.
Mouse CSCCs display many genetic alterations seen in human SCCs, including mutation of RAS, PI3 kinase and NOTCH pathways.
The model also incorporates the critical role played by non-mutagenic tumor promoting factors as cancer drivers.
This proposal will build on our previous work, accessing our extensive in-house mouse tumor genomics and transcriptomics databases.
In Aim 1, we will use single cell analyses of primary papillomas, carcinomas and metastases induced by chemical carcinogenesis in situ and analyzed before and during chemo- or immunotherapies.
We will use our novel biocomputational metagene approach to identify rewiring of transcriptomic networks within single tumor cells after therapy.
Single cell analyses, namely scRNAseq, CyTOF, MIBI, and FISH, will be combined with our in- house developed analytical tools, to identify high plasticity state tumor cell populations enriched or depleted in response to therapy and their molecular and spatial relationship to other cells and structures within the tumor.
In Aim 2, we will test the fidelity of the chemical carcinogenesis model as a robust representation of human CSCC biology by undertaking longitudinal validation studies of fresh human CSCC tissue collected before and during chemo- or immuno-therapy and analyzed using the same technology.
In Aim 3, we will empirically test the function of candidate genes (metagene components) expressed in the high plasticity state, for their contribution to drug resistance.
CRISPRi/dCas9 and CRISPR/multiCas12a technology will be used to test gene activities during drug therapy by single or combinatorial gene knockdown in syngeneic tumor models in vivo.
Our strategy will credential the use of the skin chemical carcinogenesis system to model features of human cancer drug resistance.
The project is responsive to PAR-23-281, as it undertakes cross-species discovery of the molecular basis for development of drug resistant tumor cells.
The knowledge to be gained will contribute to discovery of biomarkers and therapeutic targets for this drug resistant cell population.
Our computational methodology and our extensive transcriptomic data from hundreds of tissue and tumor samples will be shared with the Oncology Models Forum NCIP Hub.
Funding Goals
NOT APPLICABLE
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
San Francisco,
California
94143
United States
Geographic Scope
Single Zip Code
Related Opportunity
Analysis Notes
Amendment Since initial award the total obligations have increased 405% from $671,594 to $3,388,524.
San Francisco Regents Of The University Of California was awarded
Cancer Drug Resistance Network Analysis
Project Grant R01CA285426
worth $3,388,524
from National Cancer Institute in June 2024 with work to be completed primarily in San Francisco California United States.
The grant
has a duration of 5 years and
was awarded through assistance program 93.396 Cancer Biology Research.
The Project Grant was awarded through grant opportunity Research Projects to Enhance Applicability of Mammalian Models for Translational Research (R01 Clinical Trial Not Allowed).
Status
(Ongoing)
Last Modified 6/22/26
Period of Performance
6/15/24
Start Date
5/31/29
End Date
Funding Split
$3.4M
Federal Obligation
$0.0
Non-Federal Obligation
$3.4M
Total Obligated
Activity Timeline
Transaction History
Modifications to R01CA285426
Additional Detail
Award ID FAIN
R01CA285426
SAI Number
R01CA285426-2336840603
Award ID URI
SAI UNAVAILABLE
Awardee Classifications
Public/State Controlled Institution Of Higher Education
Awarding Office
75NC00 NIH National Cancer Institute
Funding Office
75NC00 NIH National Cancer Institute
Awardee UEI
KMH5K9V7S518
Awardee CAGE
4B560
Performance District
CA-11
Senators
Dianne Feinstein
Alejandro Padilla
Alejandro Padilla
Modified: 6/22/26