# Advancing technologies for the collection and analysis of high dimensional immunoprofiles and tumor images

> **NIH NIH R50** · HARVARD MEDICAL SCHOOL · 2024 · $174,710

## Abstract

SUMMARY-ABSTRACT
 The overall goal of this proposal is to use highly multiplexed, high-resolution imaging of
tissues and tumors to deeply characterize the microenvironments of diverse solid tumors being
studied by NCI-funded collaborators at the Harvard Laboratory of Systems Pharmacology
(LSP), Dana Farber/Harvard Cancer Center and four other NCI cancer centers. The PI of this
proposal, Research Specialist Jerry Lin PhD, invented tissue-based cyclic immunofluorescence
(CyCIF) in 2018 and has made it the leading public domain (license-free) method for performing
high-plex tissue analysis. He has adapted the method to high resolution 3D imaging of selected
fields of view (~103 cells using deconvolution microscopy) as well as rapid analysis of whole
slides (~106 cells) at lower resolution. As developed CyCIF can collect data from 20-60 protein
markers from a single specimen making it possible to identify cell types and states in a
preserved tissue environment. It can also image structures as small as immune synapses
allowing cell-cell interactions to be analyzed at a functional level. Dr. Lin’s work directly supports
research by 18 NCI-funded laboratories and the CyCIF protocols he has published are used by
multiple other labs working independent of the HMS team. Dr. Lin also performs his own
research as part of a Human Tumor Atlas Network Trans Network Project that conceived and
now leads. These activities have resulted in 20 collaborative publications over the past three
years including several in high impact journals with Dr. Lin as first or co-first author.
 As part of this R50 proposal Dr Lin will engage in three primary activities. First, he will
continue to collaborate with research groups to acquire CyCIF data at different stages before
and after treatment. This is will make it possible to identify molecular and morphological features
associated with disease initiation, progression, and therapeutic response. Second, he will
continue to improve the CyCIF method and integrate it with other methods for spatial
interrogation of human and murine tumors (e.g. transcript profiling and imaging mass
spectrometry). Dr. Lin will also continue to lead an HTAN TNP designed to compare spatial
profiling methods across technologies and performance sites. This research has already led to
unexpected insights into adequately powering spatial profiles as well as the relative merits of
whole-slide 2D and 3D imaging. Third, he will continue to develop and validate new approaches
to tissue imaging, particularly those that are applicable to digital pathology workflows in the
setting of clinical trials and patient diagnosis. This builds on the proven ability of CyCIF to collect
high quality data from the formaldehyde-fixed paraffin embedded (FFPE) specimens routinely
acquired for patient diagnosis and staging (including core biopsies and fine needle aspirates).
This combination of collaborative and original research and technology development is
expected to have a h...

## Key facts

- **NIH application ID:** 10916286
- **Project number:** 5R50CA274277-03
- **Recipient organization:** HARVARD MEDICAL SCHOOL
- **Principal Investigator:** Jia-Ren Lin
- **Activity code:** R50 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $174,710
- **Award type:** 5
- **Project period:** 2022-09-20 → 2027-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10916286

## Citation

> US National Institutes of Health, RePORTER application 10916286, Advancing technologies for the collection and analysis of high dimensional immunoprofiles and tumor images (5R50CA274277-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10916286. Licensed CC0.

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