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Decoding basal multipotency for histological transformation in lung cancer patients

Award Number: R01CA312002
ORGANIZATION: NATIONAL CANCER INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 08/01/2026
PERIOD OF PERFORMANCE END DATE: 07/31/2031

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Decoding basal multipotency for histological transformation in lung cancer patients - PROJECT SUMMARY Histological transformation (HT) is an emerging mechanism of acquired resistance across malignancies. In lung cancer, adenocarcinoma (ADC) can transform to small cell/neuroendocrine (NE) or squamous (SCC) histology as an escape from targeted therapies. We and others have observed that tumor cells often adopt a basal-like state prior to HT. Endogenous basal cells are a major cell type of origin for de novo small cell and SCC lung cancer, supporting the role of a multipotent basal-like precursor to HT. In prior work, we identified JAK/STAT inflammation as a tumor-intrinsic gene program driving a shift to the basal state in prostate cancer organoids prior to NE transformation and showed that JAK/STAT pathway inhibition reversed the basal state and restored sensitivity to androgen inhibition. We hypothesize that the basal state is a universal precursor across HT in lung cancer that may serve as a prognostic and predictive biomarker as well as therapeutic target to reverse or prevent HT. We will leverage advanced technologies in single-cell (sc-seq), cell-free sequencing (cf-seq), and spatial imaging that can model gene regulatory networks (GRNs) and tumor microenvironment (TME) factors driving plasticity, providing resolution beyond that of prior studies of the bulk tumor. In Aim 1, we will identify transcriptional & epigenetic changes driving precursor basal & terminal small cell lung cancer (SCLC) vs SCC HT. We will use single-nucleus (sn)RNA/ATAC-seq on previously collected patient tumors with ADC-to-SCLC & ADC-to-SCC HT to identify gene programs associated with early basal & terminal HT states. Our computational tools can 1) identify recurrent GRN changes along the transition to basal & terminal SCLC vs SCC states and 2) quantify plasticity to detect cell populations poised for transitions and enriched for gene programs initiating these transitions. We will validate drivers of basal & terminal SCLC vs SCC states using genetic & drug studies in cell lines & patient-derived xenografts. We will use H3K4me3 & H3K27ac cfChIP-seq on plasma from EGFR/TP53/RB1-mutant ADC patients at high risk of HT to confirm transcriptional and epigenetic basal features in transformed vs not yet transformed samples. In Aim 2, we will characterize inflammatory cues mediating the basal precursor & terminal SCLC vs SCC HT. We will integrate Xenium spatial imaging (489 RNA markers at single-cell resolution) with matched scRNA-seq (whole transcriptome) on matched tumors with ADC-to-SCLC & ADC-to-SCC HT to 1) capture differential compositional TME changes and 2) develop machine learning methods to infer tumor-immune ligand-receptor interactions driving the basal state and terminal SCLC vs SCC HT. We will validate findings with genetic and drug studies of co-cultured tumor and immune cells from syngeneic mice and orthotopic transplant of tumor cell lines. This proposal will develop computational tools using sc-seq and cf-seq to interrogate epigenetic and TME cues that converge on a basal precursor state during early HT, with potential to identify biomarkers for prognostic stratification and early drug targets to intercept, constrain, or even reverse plasticity.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $752,280 )
2026	2026	SLOAN-KETTERING INSTITUTE FOR CANCER RESEARCH	1275 YORK AVE	NEW YORK	NY	10065	NEW YORK	USA	Cancer Biology Research	000	1	7/30/2026	NEW	$752,280
														Subtotal = $752,280

Grand Total All Awards = $752,280

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Decoding basal multipotency for histological transformation in lung cancer patients

Award Number: R01CA312002

ORGANIZATION: NATIONAL CANCER INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 08/01/2026

PERIOD OF PERFORMANCE END DATE: 07/31/2031

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