Tumor Immune Cell Biomarkers Predict Response to First-Line Nivolumab in Kidney Cancer

Why This Study Matters

Anti-PD-1-based regimens are now the standard of care for previously untreated metastatic clear-cell renal cell carcinoma (mccRCC), yet clinicians have no validated biomarker to identify — before treatment even starts — which patients are likely to respond to PD-1 blockade. This correlative analysis of the HCRN GU16-260 trial, a single-arm, open-label phase 2 study of first-line nivolumab monotherapy, tested whether four components of the tumor immune microenvironment previously linked to response in previously treated mccRCC would hold up when nivolumab is used first-line.

Study Design

This report is a retrospective correlative biomarker analysis, not a new clinical trial readout: investigators re-examined archival, pretreatment tumor samples from patients already enrolled in HCRN GU16-260 Cohort A, all of whom received first-line nivolumab monotherapy (non-responders could receive salvage nivolumab plus ipilimumab in Cohort B, per the parent trial design). Multiplex immunofluorescence was used to quantify four immune features in pretreatment tumor tissue: non-exhausted CD8+ effector T cells, PD-1+ regulatory T cells, tertiary lymphoid structures, and CD163+ tumor-associated macrophages. Of the 128 patients enrolled in Cohort A, the number with evaluable pretreatment samples is reported inconsistently in the source: the abstract cites 72 patients with evaluable samples overall, while the results text cites 78 patients with multiplex immunofluorescence performed and per-biomarker evaluable counts ranging from 66 to 72 depending on tissue quality. Both figures are reported here exactly as they appear in the source.

Patient Population

Patients were treatment-naive individuals with metastatic clear-cell RCC enrolled in HCRN GU16-260 Cohort A. Objective response rate (ORR) was defined per RECIST 1.1 as complete or partial response, and progression-free survival (PFS) was measured from nivolumab initiation to documented progression or death. Patients with and without evaluable multiplex immunofluorescence data were similar in gender, ECOG performance status, sarcomatoid features, and IMDC risk category, though the included biomarker subset had numerically higher ORR and better PFS than those excluded — a possible selection bias the authors acknowledge directly.

Key Findings

Primary Findings: Four Biomarkers, Four Different Signals

Non-exhausted CD8+ T cells. Density of CD8+PD-1+TIM-3−LAG-3− tumor-infiltrating lymphocytes — T cells that express PD-1 but not the additional exhaustion markers TIM-3 or LAG-3 — was associated with improved ORR (OR 1.54, 95% CI 1.10–2.16, one-sided P=0.017) and PFS (HR 0.79, 95% CI 0.67–0.95, one-sided P=0.016) as a continuous variable. Using an exploratory cutoff optimized for ORR, the 61 of 67 evaluable patients with high density of these cells had an ORR of 44.3% versus 0% in the low-density group (one-sided P=0.039), and median PFS of 10.9 months versus 4.2 months (one-sided P=0.016). This is the third independent clinical trial cohort in which this research group has linked this T-cell phenotype to nivolumab response — the earlier two cohorts involved previously treated patients, making this first-line confirmation notable.

Tertiary lymphoid structures. Densities of both total and peritumoral TLS were associated with increased ORR (OR 1.18, 95% CI 1.02–1.37 for total TLS; OR 1.10, 95% CI 1.02–1.18 for peritumoral TLS) and longer PFS (HR 0.92, 95% CI 0.85–0.99 for total TLS, one-sided P=0.038; HR 0.94, 95% CI 0.90–0.98 for peritumoral TLS, one-sided P=0.010). By ORR-optimized cutoff, the 37 of 71 patients with high total TLS density had an ORR of 54.1% versus 23.5% (one-sided P=0.008) and median PFS of 13.7 months versus 6.8 months (one-sided P=0.046).

It is worth noting that, unlike other components of the immune microenvironment that need to be interrogated by molecular analyses, TLS can potentially be studied by histopathological examination of tissue slides stained with hematoxylin and eosin.
— Discussion, El Ahmar, Paul, Simsek, et al., Clinical Cancer Research, 2026

CD163+ tumor-associated macrophages. Density of CD163+ tumor-associated macrophages (TAMs) — typically viewed as pro-tumorigenic — was associated with increased ORR (OR 2.21, 95% CI 1.33–3.69, two-sided P=0.002) and longer PFS (HR 0.77, 95% CI 0.61–0.97, two-sided P=0.029). By ORR-optimized cutoff, the 34 of 67 patients with high CD163+ TAM density had an ORR of 64.7% versus 15.2% (two-sided P<0.001) and median PFS of 16.6 months versus 5.5 months (two-sided P=0.009). The authors speculate this apparent paradox may reflect PD-1 blockade reprogramming TAMs from a pro-tumorigenic to an anti-tumorigenic state, rather than TAM density itself being protective — a hypothesis supported by spatial analysis showing that terminally exhausted CD8+ T cells were significantly enriched near CD163+ TAMs compared to non-proximal tumor regions (median density 123.3 per mm² versus 37.2 per mm², two-sided P<0.001).

PD-1+ regulatory T cells. As a continuous variable, the percentage of PD-1+ regulatory T cells was not significantly associated with ORR (OR 0.72, one-sided P=0.420) or PFS (HR 2.52, one-sided P=0.179), though the PFS association trended in the expected direction. Using an ORR-optimized cutoff, the 8 of 70 patients with high PD-1+ Treg percentage had lower ORR (12.5% versus 43.6%, one-sided P=0.093) and notably shorter median PFS (3.4 months versus 10.9 months, one-sided P<0.001).

Combining Biomarkers Sharpens Risk Stratification

Because the four biomarkers were not strongly correlated with one another, the authors tested whether combining them could stratify outcomes better than any single marker alone. These are exploratory, biomarker-defined patient subgroups within the correlative analysis, not conventional demographic or clinical subgroup analyses.

All three combined-biomarker analyses reached statistical significance for both ORR and PFS (two-sided P<0.001 for ORR in each; PFS P=0.008, P<0.001, and P=0.002, respectively). The individual markers showed only weak-to-moderate correlation with each other (Spearman's r ranging from −0.011 to 0.469), which the authors interpret as evidence that these are independent biological determinants of response rather than redundant readouts of general inflammation.

Safety Profile

Not specified in this source. This article is a retrospective correlative biomarker analysis of archival tumor tissue and does not itself report treatment-related adverse events for nivolumab. Toxicity data for the HCRN GU16-260 Cohort A population was reported separately in the trial's primary clinical outcomes paper, published in the Journal of Clinical Oncology and cited within this article as a separate reference; it is not reproduced in the source used for this article. Readers seeking safety and tolerability data should consult that primary trial report directly.

Interpretation and Broader Context

Taken together, these findings reinforce a growing view that no single biomarker will adequately predict response to PD-1 blockade in mccRCC, but that a small panel of complementary immune features — capturing effector T-cell exhaustion state, lymphoid organization, macrophage phenotype, and regulatory T-cell activity — may meaningfully stratify patients. The authors note this validates the non-exhausted CD8+ T-cell biomarker across three independent clinical trial cohorts and confirms the PD-1+ Treg resistance signal first identified in the CheckMate-025 trial.

The authors are careful to flag limitations: this is a retrospective analysis of a prospective trial's archival samples, restricted to primary tumor tissue that may not fully represent metastatic lesion biology, and the analyzed subset had numerically better outcomes than patients excluded for lack of evaluable tissue — raising the possibility of selection bias. The findings have not yet been prospectively validated and are described by the authors as exploratory.

Should these efforts prove successful, the next critical steps will include establishing the assay or assays in a CLIA-certified laboratory and performing clinical validation through prospective clinical trials.
— Discussion, El Ahmar, Paul, Simsek, et al., Clinical Cancer Research, 2026

The authors state that candidate biomarkers are currently being evaluated in patients treated with FDA-approved anti-PD-(L)1-based combination regimens within phase 3 clinical trials, with plans to move toward CLIA-certified assay development and prospective clinical validation if those efforts succeed.