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Advancing and Validating Single-Cell Long-Read Sequencing for Broad Adoption in Cancer Molecular Profiling

Award Number: R33CA315144
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: 07/31/2029

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Advancing and Validating Single-Cell Long-Read Sequencing for Broad Adoption in Cancer Molecular Profiling - PROJECT SUMMARY/ABSTRACT The future of personalized cancer medicine requires going beyond detecting mutations and copy number changes to also considering downstream transcriptional and post-transcriptional processes that influence cellular cancer phenotypes. Alternative splicing is a key, final step in gene expression regulation prior to translation, dictating cellular function and plasticity through expression of diverse transcript and protein isoforms from a single gene. The genetic and epigenetic insults that accumulate in tumors are upstream of splicing, and therefore therapies based on splicing have the potential to more proximally and specifically influence cancer cell phenotype. Splicing dysregulation is a hallmark of cancer and a robust indicator of cancer risk and has been causally linked to tumorigenesis. However, how splicing contributes to tumor heterogeneity and impacts drug response and resistance remains understudied, which hinders exploiting splicing vulnerabilities for clinical benefit. This knowledge gap is a result of an important technical gap: the cancer research field lacks robust, validated tools for mapping and analyzing full-length spliced isoforms at the single-cell resolution in tumors. To meet this need, we will build and validate enhanced tools for single-cell long-read isoform transcriptomics (scLRseq) (Aim 1). We will address specific shortcomings of currently emerging scLR-seq approaches, including suboptimal read length/depth and the absence of bioinformatics pipelines customized for integrating single-cell and LR-seq data. We will rigorously validate our advanced scLR-seq platform using orthogonal methods, including fluorescent in situ hybridization and through comparison to bulk short- and long-read data from sorted cells. Next, we will demonstrate the robustness of scLR-seq in detecting intra-tumor splicing heterogeneity, and the broad applicability of scLR-seq across tumor types (Aim 2). We will apply scLR-seq in a patient-derived xenograft (PDX) model of breast cancer and cisplatin resistance which contains at least five clonal populations that are heterogeneous in their response to therapy and in spliced isoform content. We will use a PDX model because cancer arises within, and is shaped by, the whole organism; tumor progression and treatment response are systemic processes that in vitro systems cannot fully replicate. Thus, in vivo models are required for comprehensive validation of our platform. To demonstrate effectiveness of scLR-seq across tumor types, we will use patient’s lung and malignant peripheral sheath nerve tumors, selected for their divergent cell type lineages and compositions. We will define the splicing landscape in cancer cells, tumor-resident immune cells, cancerassociated fibroblasts, and circulating blood cells. Finally, we will develop open-access, web-based data sharing and visualization tools for single cell isoform expression (Aim 3). By bringing scLR-seq and its associated computational methods to technical and analytical maturity, we will encourage and facilitate broad adoption by the cancer research community. This project will accelerate translation of splicing biology into the clinic, advancing precision oncology through enabling new strategies for early detection, intervention, and prevention.


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 = $452,458 )
2026	2026	JACKSON LABORATORY	600 MAIN ST	BAR HARBOR	ME	04609	HANCOCK	USA	Cancer Biology Research	000	1	7/16/2026	NEW	$452,458
														Subtotal = $452,458

Grand Total All Awards = $452,458

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Advancing and Validating Single-Cell Long-Read Sequencing for Broad Adoption in Cancer Molecular Profiling

Award Number: R33CA315144

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: 07/31/2029

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