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Development of a Flow Cytometry Assay to Predict Immune Checkpoint Blockade-Related Complications.

ABSTRACT: Treatment of advanced melanoma with combined immune checkpoint inhibitor (ICI) therapy is complicated in up to 50% of cases by immune-related adverse events (irAE) that commonly include hepatitis, colitis and skin reactions. We previously reported that pre-therapy expansion of cytomegalovirus (CMV)-reactive CD4⁺ effector memory T cells (T_EM) predicts ICI-related hepatitis in a subset of patients with Stage IV melanoma given αPD-1 and αCTLA-4. Here, we develop and validate a 10-color flow cytometry panel for reliably quantifying CD4⁺ T_EM cells and other biomarkers of irAE risk in peripheral blood samples. Compared to previous methods, our new panel performs equally well in measuring CD4⁺ T_EM cells (agreement = 98%) and is superior in resolving CD4⁺ CD197⁺ CD45RA^- central memory T cells (T_CM) from CD4⁺ CD197⁺ CD45RA⁺ naive T cells (T_naive). It also enables us to precisely quantify CD14⁺ monocytes (CV = 6.6%). Our new "monocyte and T cell" (MoT) assay predicts immune-related hepatitis with a positive predictive value (PPV) of 83% and negative predictive value (NPV) of 80%. Our essential improvements open the possibility of sharing our predictive methods with other clinical centers. Furthermore, condensing measurements of monocyte and memory T cell subsets into a single assay simplifies our workflows and facilitates computational analyses.

SUBMITTER: Schilling HL

PROVIDER: S-EPMC8637156 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundImmune checkpoint blockade (ICB) shows lasting benefits in advanced melanoma; however, not all patients respond to this treatment and many develop potentially life-threatening immune-related adverse events (irAEs). Identifying individuals who will develop irAEs is critical in order to improve the quality of care. Here, we prospectively demonstrate that the gut microbiome predicts irAEs in melanoma patients undergoing ICB.MethodsPre-, during, and post-treatment stool samples were collected from 27 patients with advanced stage melanoma treated with IPI (anti-CTLA-4) and NIVO (anti-PD1) ICB inhibitors at NYU Langone Health. We completed 16S rRNA gene amplicon sequencing, DNA deep shotgun metagenomic, and RNA-seq metatranscriptomic sequencing. The divisive amplicon denoising algorithm (DADA2) was used to process 16S data. Taxonomy for shotgun sequencing data was assigned using MetaPhlAn2, and gene pathways were assigned using HUMAnN 2.0. Compositionally aware differential expression analysis was performed using ANCOM. The Cox-proportional hazard model was used to assess the prospective role of the gut microbiome (GMB) in irAES, with adjustment for age, sex, BMI, immune ICB treatment type, and sequencing batch.ResultsTwo natural GMB clusters with distinct community compositions were identified from the analysis of 16S rRNA data (R2 = 0.16, p < 0.001). In Cox-proportional hazard modeling, these two clusters showed a near 7-fold differential risk for developing irAEs within 1 year of initiating treatment (HR = 6.89 [95% CI: 1.33-35.58]). Using shotgun metagenomics, we further identified 37 bacterial strains differentially expressed between the risk groups, with specific dominance of Bacteroides dorei within the high-risk GMB cluster and Bacteroides vulgatus in the low-risk cluster. The high-risk cluster also appeared to have elevated expression of several functional pathways, including those associated with adenosine metabolism (all FDR < 0.05). A sub-analysis of samples (n = 10 participants) at baseline and 6 and 12 weeks after the start of treatment revealed that the microbiome remained stable over the course of treatment (R2 = 0.88, p < 0.001).ConclusionsWe identified two distinct fecal bacterial community clusters which are associated differentially with irAEs in ICB-treated advanced melanoma patients.

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Development of a Flow Cytometry Assay to Predict Immune Checkpoint Blockade-Related Complications.

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