# Immunogenomic analytical approaches for research and clinical applications

> **NIH NIH R50** · DANA-FARBER CANCER INST · 2020 · $265,958

## Abstract

Project Summary
One of the critical steps to developing curative and tumor-specific immunotherapies is the
identification and selection of antigens with tumor-restricted expression in order to avoid
undesirable immune responses against normal tissues. Proteins with tumor-specific mutations
have the potential to be the most restricted of all tumor antigens. However, the comprehensive
identification of such `neoantigens' has only become feasible recently using next-generation
massively parallel sequencing technologies, providing unprecedented genetic information about
cancer cells. We have previously developed computational workflows to identify neoantigens
arising from somatic missense mutations, insertions or deletions. The current project seeks to
develop neoantigen prediction pipelines to discover cancer neoantigens deriving from
transcriptome data, such as those arising from intra- or inter-chromosomal gene-fusions; or from
splicing alterations, generated from mutation in cis-acting regulatory sequences, or from
mutations in splicing factors themselves that can create multiple tumor-restricted transcripts.
The current project also seeks to expand our previously developed toolkit for characterization of
class I HLA genes to accommodate other immune-related polymorphic loci in the genome,
particularly class II HLA genes, as well as a tool for inferring allele specific copy number
variation in HLA genes. A new initiative in the Dr. Catherine Wu's lab focuses on development
of a novel experimental method for isolating paired CDR3-Vα and -Vβ chain information from
single T cells which would enable correspondence of specific TCRs that detect specific known
peptide-HLA complexes of interest. As part of this project, we therefore propose creation of
pipelines for deconvoluting single-cell T cell repertoire data. Finally, we propose to investigate
the clonal evolutionary dynamics of tumor and immune components in chronic lymphocytic
leukemia by developing single-cell sequencing workflows for studying transcriptional changes
over time or in response to treatment.

## Key facts

- **NIH application ID:** 9982849
- **Project number:** 5R50CA211482-05
- **Recipient organization:** DANA-FARBER CANCER INST
- **Principal Investigator:** Sachet Ashok Shukla
- **Activity code:** R50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $265,958
- **Award type:** 5
- **Project period:** 2016-09-19 → 2021-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9982849

## Citation

> US National Institutes of Health, RePORTER application 9982849, Immunogenomic analytical approaches for research and clinical applications (5R50CA211482-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9982849. Licensed CC0.

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