# Tech Core 2

> **NIH NIH U54** · JOHNS HOPKINS UNIVERSITY · 2024 · $526,720

## Abstract

Project Summary – Tech Core 2
Spatial tumor heterogeneity plays a critical role in multiple stages of cancer progression and metastasis including
the venous invasion that contributes to increased risk of cancer cell dissemination. This process involves spatially
distinct interaction between cancer cells and the surrounding microenvironment at multiple sites. In Tech1, PI
Wirtz will develop a new 3D multiscale tumor cell mapping method, CODA, which can create a 3D large-scale
tumor cell anatomy at single cell level via tissue histology image integration and trained deep-learning semantic
algorithms. What is highly desired to further add to this 3D tumor cell anatomic atlas is genome-wide molecular
information such as mRNAs and a large panel of proteins for unbiased discovery of cell subtype, state, and
interaction, and potentially to infer new mechanisms or targets for therapeutic intervention. TECH2 PI Fan
recently developed a novel technology called DBiT-seq for high-spatial-resolution multi-omics mapping via
deterministic barcoding in tissue at cellular level (~10µm), whole transcriptome scale (>22,000 genes), high
coverage (>2,000 genes per 10µm pixel), and multi-omics profiling (co-mapping of ~300 protein markers), which
can be readily applied to FFPE tissue sections and integrated with CODA. In Tech2, we propose the following
two aims: AIM 1. A high-throughput, low cost, high quality/coverage, multi-omic mapping method (DBiT-seq) with
full compatibility with human PFA and FFPE tissue samples. AIM 2. Integrating CODA and DBiT-seq for 3D
multi-omic tumor imaging. Successful completion of these two aims will lead to the first genome-wide multi-
omics 3D view of vascular or lymphovascular invasion of human tumors and a powerful technology platform for
the consortium to investigate spatial tissue heterogeneity in other human cancers.

## Key facts

- **NIH application ID:** 10747315
- **Project number:** 5U54CA268083-03
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Denis Wirtz
- **Activity code:** U54 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $526,720
- **Award type:** 5
- **Project period:** 2021-12-01 → 2026-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10747315

## Citation

> US National Institutes of Health, RePORTER application 10747315, Tech Core 2 (5U54CA268083-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10747315. Licensed CC0.

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