# Optimization of peripheral blood mononuclear cell (PBMC) processing for robust downstream functional immune cell analysis and correlation with therapeutic efficacy

> **NIH NIH U01** · UNIVERSITY OF CINCINNATI · 2022 · $353,556

## Abstract

There is an increasing dependence on sophisticated biomarker development to allow prediction of
therapeutic response as well as detection of potential underlying drug targets for novel therapeutics. A frequent
limitation for solid tumors is that standard tissue biopsies are not always feasible, safe or easily repeated during
treatment. Optimal sample acquisition, processing, and final validation are critical for any biomarker, regardless
of source. Moreover, with the advent of immunotherapy, repeated sampling has become even more critical
to understand the tumor and systemic immune response to better predict response and prevent resistance.
Accordingly, there is an urgent need to develop reliable and valid alternatives to tissue biopsies. Peripheral
blood is easy and safe to obtain and is more readily obtainable before, during, and after treatment. Peripheral
blood mononuclear cells (PBMCs) can be isolated from standard whole blood and subsequent isolation and
analysis of protein, DNA and RNA has the potential to serve as a surrogate for tissue response to anti-cancer
therapy. However, analysis of immune functions more reflective of the systemic and tumor immune response to
immunotherapy, using PBMCs, requires unusually rigorous processing techniques. We have found, for
example, that reproducible viability of fresh samples is important for functional responses including cellular
cytotoxicity and chemotaxis. However, fresh processing with subsequent analysis often requires flexible staffing
and constant instrumentation availability due the unpredictable timing of patient sample collection. Furthermore,
requiring immediate analysis may preclude the benefits of batching samples. The central hypothesis of this
proposal is that optimizing PBMC processing will allow for delayed and more comprehensive, reproducible
functional analyses that reflect the patient immune and tumor status permitting clinical treatment decisions
without the requirement of a tissue biopsy.
 The hypothesis will be tested by first determining the optimal collection, processing and storage
conditions that maximize long-term viability and sustain intact downstream meaningful functional immune
analyses even when performed in a delayed batch manner. Second, we will determine if the reproducible PBMC
functional outcomes serve as a surrogates to tumor infiltrating immune cell function and therapeutic efficacy.
 This approach will allow the advancement of peripheral blood biospecimens to reflect underlying
mechanisms of tumor behavior previously relegated to the invasive tissue biopsy. In addition, we will have
established conditions for processing PBMCs that allow for reproducible collection of viable cells that maintain
functional capacity upon storage, from which meaningful functional assays can be performed by different
facilities. The fundamental knowledge obtained from this proposal will facilitate the development of suitable
correlative PBMC analyses for future clinical trials al...

## Key facts

- **NIH application ID:** 10370587
- **Project number:** 1U01CA267985-01
- **Recipient organization:** UNIVERSITY OF CINCINNATI
- **Principal Investigator:** Kelsey Dillehay McKillip
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $353,556
- **Award type:** 1
- **Project period:** 2022-02-15 → 2027-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10370587

## Citation

> US National Institutes of Health, RePORTER application 10370587, Optimization of peripheral blood mononuclear cell (PBMC) processing for robust downstream functional immune cell analysis and correlation with therapeutic efficacy (1U01CA267985-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10370587. Licensed CC0.

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