# Defining and targeting the lung cancer progenitor cell niche using a high-resolution, multi-omics approach

> **NIH NIH F30** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2021 · $45,636

## Abstract

Project Summary
Despite advances in treatment options, 5-year overall survival (OS) for non-small cell lung cancer 
(NSCLC) patients remains around 20% [1]. Subpopulations of tumor initiating cells (TICs) 
representing <1.5% of the overall tumor population exhibit the capacity for self-renewal, 
drug-resistance, and are believed to drive disease progression [2]. Although surface markers 
including CD133, CD44, CD166, and EPCAM have been proposed to isolate lung TICs, results are 
inconsistent. Micro-heterogeneity within the tumor microenvironment (TME) is believed to regulate 
balance between progenitor-like and differentiated tumor cell phenotypes, and consequently 
supports heterogeneous drug responses. This proposed research attempts to definitively 
characterize expression profiles of TICs, and study the relationship 
between the tumor micro-environment and TIC dynamics in the context of drug response, 
with the goal of identifying critical pathways that mediate transitions to a 
progenitor-like state. Aim 1 - Lineage tracing studies suggest that TICs exhibit clonal 
dominance in culture, whereby a small fraction of tumor cells tend to drive outgrowth of the 
overall population. Having already established a protocol using cell line models, I will transfect 
patient-derived NSCLC cells with RNA-expressed barcodes and analyze growing populations 
using serial passaging assays under normal and drug-treated conditions. Using 
transcriptional analysis of time-series single-cell RNA Sequencing (scRNA-Seq) data in 
combination with custom computational tools, I aim to identify gene expression profiles 
and surface markers unique to progenitor-like subclones that drive population growth under 
treatment selection pressure. Aim 2 - TICs are dependent on niche signalling from a heterogeneous 
tumor microenvironment (TME) to support the progenitor phenotype. We hypothesize that 
micro-heterogeneity within the TME regulates the ratio of progenitor-to-differentiated tumor cells 
and influences drug sensitivity. I will first develop an in-vitro spheroid culture 
platform combining clonally barcoded patient-derived tumor and stromal cells exposed to cytotoxic 
therapy, processing them with the 10X Genomics Spatial Transcriptomics platform. This data 
will enable assessment of essential TME crosstalk signalling and its impact on spatial cancer 
projenitor-like transcriptional signatures defined from Aim 1. We will confirm these insights 
by integrating scRNA-Seq and Spatial Transcriptomics data from naive and 
post-treatment patient-derived lung samples used for Aim 1 to characterize 
patient-specific TIC niches. Through the robust profiling of the TIC transcriptional 
profile and its associated microenvironment using multimodal sequencing approaches, we hope to 
potentially identify new targets or prognostic biomarkers to aid in the treatment of NSCLC.

## Key facts

- **NIH application ID:** 10315427
- **Project number:** 1F30CA265288-01
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Daniel Charytonowicz
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $45,636
- **Award type:** 1
- **Project period:** 2021-09-07 → 2025-09-06

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10315427

## Citation

> US National Institutes of Health, RePORTER application 10315427, Defining and targeting the lung cancer progenitor cell niche using a high-resolution, multi-omics approach (1F30CA265288-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10315427. Licensed CC0.

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