# Lymphocyte and inflammatory cytokine markers of response in the first-in-human combination of anti-PD-1 mAb and IL-15/IL-15Ra complexes and investigation of mediators of anti-tumor immune responses > **NIH NIH R01** · MEDICAL UNIVERSITY OF SOUTH CAROLINA · 2022 · $389,857 ## Abstract Because PD-1 therapies only benefit approximately 1 in 5 patients with NSCLC, there is a great need to improve immunotherapy for this disease. A distinct form of immunotherapy, IL-2, can yield complete responses in melanoma and renal cell carcinoma. Use of IL-2 is limited due to common life-threatening toxicity. An alternative to IL-2 is IL-15/IL-15Rα complexes. ALT-803 is a clinical grade IL-15/IL-15Rα complex and powerful super-agonist for IL-15 responsive CD8+ lymphocytes and natural killer (NK) cells with dramatically improved safety compared with IL-2. Preclinical studies combining ALT-803 with anti-PD-1 mAb demonstrate remarkable anti-tumor efficacy associated with expansion of both CD8+ T cells and NK cells, and the production of inflammatory cytokines such as IL-6 and IFNγ. We have moved this therapy into the clinic with an investigator- initiated, first-in-human, phase Ib/II trial testing the clinical hypothesis that adding IL-15/IL-15Rα complexes (ALT- 803) to anti-PD1 mAb (nivolumab) is safe and efficacious in NSCLC (NCT02523469). To date 11 patients have been treated with three highly active dose levels (6, 10, 15 mcg/kg SC, 15 being the highest planned dose) with zero observed dose limiting toxicities (DLTs) and excellent activation of CD8+ T cells and NK cells and increases in serum IL-6 and IFNγ. The goal of this application is to determine the mechanistic basis and predictors of response for this promising combinatorial approach using our unique bank of trial-derived samples and a powerful preclinical lung tumor model. We hypothesize that the addition of IL-15/IL-15Rα complexes to anti-PD- 1 mAb augments anti-tumor efficacy through enhanced expansion and functional activation of tumor-reactive CD8+ lymphocytes and NK cells and that the induction of inflammatory cytokines such as IL-6 and IFNγ will be associated with anti-tumor efficacy. We further hypothesize enhanced anti-tumor efficacy will depend on effector lymphocytes (CD8+ and NK but not CD4+) and correlate with cytokines (IL-6 and IFNγ). Specific Aim 1: Using state-of-art mass cytometry we will perform the high-dimension characterization of both NK and CD8+ T cell compartments from longitudinal PBMC samples of up to 116 patients. We will perform TCR sequencing on expanded T cells to determine if they originate from tumor. We will also perform 65-plex serum cytokine/chemokine analysis of longitudinally acquired samples to identify novel serum biomarkers. We will associate changes in lymphocyte and serum cytokines/chemokines parameters with clinical response. Specific Aim 2: We will use our Lewis lung carcinoma (LLC) mouse model to inform our future clinical efforts with the combination of anti-PD-1 mAb and IL-15/sIL-15Rα complexes. First, we will identify cellular and molecular markers that correlate with treatment outcome using longitudinal analysis of responding and non-responding mice. Second we will validate critical pathways using antibody-mediated depletion of lymphocy... ## Key facts - **NIH application ID:** 10374802 - **Project number:** 5R01CA222817-04 - **Recipient organization:** MEDICAL UNIVERSITY OF SOUTH CAROLINA - **Principal Investigator:** MARK P RUBINSTEIN - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $389,857 - **Award type:** 5 - **Project period:** 2019-04-01 → 2024-03-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10374802 ## Citation > US National Institutes of Health, RePORTER application 10374802, Lymphocyte and inflammatory cytokine markers of response in the first-in-human combination of anti-PD-1 mAb and IL-15/IL-15Ra complexes and investigation of mediators of anti-tumor immune responses (5R01CA222817-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10374802. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*