# Statistical Methods For Quantitative Immunohistochemistry Biomarkers

> **NIH NIH R01** · THOMAS JEFFERSON UNIVERSITY · 2021 · $355,496

## Abstract

PROJECT SUMMARY
Immunohistochemistry (IHC) is widely used to classify cancer and guide clinical management of patients. A
major power of IHC is the detection of markers in the spatially resolved context of tumor tissue, including
cancerous and stromal elements, individual cell types, and subcellular compartments. Quantitative
Immunofluorescence (QIF) is used increasingly for IHC quantification of proteins that may serve as prognostic
biomarkers or targets for specific cancer therapies. A common application of QIF is simultaneous slide-based
analysis of certain protein expression using tissue microarrays (TMAs), which incorporate tumor tissues from
large cohorts of patients. This technology combined with machine readers allows for high-throughput molecular
profiling of tumor tissues and rapid development and validation of new prognostic and predictive cancer
biomarkers.
 The overall goal of our proposal is to develop an analytical framework of for discovery of new IHC
biomarkers to improve prognostication and drug response prediction. The new statistical methods will be
tailored to use the rich and untapped information on cell-level protein expression levels. Novel QIF IHC
biomarkers will be optimized as flexible indices based either on distribution functions of cell-level protein
expressions or on the spatial localization of the IHC signals viewed as marks of the spatial point pattern of
cancer cells. The proposed studies will yield broadly applicable methods for development of new biomarkers in
cancer. The improved biomarkers would support rational recruitment of patients at elevated risk of recurrence
into biomarker-driven clinical trials, with a potential to have major near-term impact on clinical research and
reduce mortality from cancer.

## Key facts

- **NIH application ID:** 10083722
- **Project number:** 5R01CA222847-03
- **Recipient organization:** THOMAS JEFFERSON UNIVERSITY
- **Principal Investigator:** Inna Chervoneva
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $355,496
- **Award type:** 5
- **Project period:** 2019-02-01 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10083722

## Citation

> US National Institutes of Health, RePORTER application 10083722, Statistical Methods For Quantitative Immunohistochemistry Biomarkers (5R01CA222847-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10083722. Licensed CC0.

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