A novel model for predicting prognosis and response to immunotherapy in nasopharyngeal carcinoma patients.

Blood-based biomarkers of immune checkpoint inhibitors (ICIs) response in patients with nasopharyngeal carcinoma (NPC) are lacking, so it is necessary to identify biomarkers to select NPC patients who will benefit most or least from ICIs. The absolute values of lymphocyte subpopulations, biochemical indexes, and blood routine tests were determined before ICIs-based treatments in the training cohort (n = 130). Then, the least absolute shrinkage and selection operator (Lasso) Cox regression analysis was developed to construct a prediction model. The performances of the prediction model were compared to TNM stage, treatment, and Epstein-Barr virus (EBV) DNA using the concordance index (C-index). Progression-free survival (PFS) was estimated by Kaplan-Meier (K-M) survival curve. Other 63 patients were used for validation cohort. The novel model composed of histologic subtypes, CD19+ B cells, natural killer (NK) cells, regulatory T cells, red blood cells (RBC), AST/ALT ratio (SLR), apolipoprotein B (Apo B), and lactic dehydrogenase (LDH). The C-index of this model was 0.784 in the training cohort and 0.735 in the validation cohort. K-M survival curve showed patients with high-risk scores had shorter PFS compared to the low-risk groups. For predicting immune therapy responses, the receiver operating characteristic (ROC), decision curve analysis (DCA), net reclassifcation improvement index (NRI) and integrated discrimination improvement index (IDI) of this model showed better predictive ability compared to EBV DNA. In this study, we constructed a novel model for prognostic prediction and immunotherapeutic response prediction in NPC patients, which may provide clinical assistance in selecting those patients who are likely to gain long-lasting clinical benefits to anti-PD-1 therapy.

Multiple TMA-aided CRISPR/Cas13a platform for highly sensitive detection of IL-15 to predict immunotherapeutic response in nasopharyngeal carcinoma.

BACKGROUND: Immune checkpoint inhibitors (ICIs)-based treatments have been recommended as the first line for refractory recurrent and/or metastatic nasopharyngeal carcinoma (NPC) patients, yet responses vary, and predictive biomarkers are urgently needed. We selected serum interleukin-15 (sIL-15) out of four interleukins as a candidate biomarker, while most patients' sIL-15 levels were too low to be detected by conventional methods, so it was necessary to construct a highly sensitive method to detect sIL-15 in order to select NPC patients who would benefit most or least from ICIs. METHODS: Combining a primer exchange reaction (PER), transcription-mediated amplification (TMA), and a immuno-PER-TMA-CRISPR/Cas13a system, we developed a novel multiple signal amplification platform with a detection limit of 32 fg/mL, making it 153-fold more sensitive than ELISA. RESULTS: This platform demonstrated high specificity, repeatability, and versatility. When applied to two independent cohorts of 130 NPC sera, the predictive value of sIL-15 was accurate in both cohorts (area under the curve: training, 0.882; validation, 0.898). Additionally, lower sIL-15 levels were correlated with poorer progression-free survival (training, HR: 0.080, p<0.0001; validation, HR: 0.053, p<0.0001). CONCLUSION: This work proposes a simple and sensitive approach for sIL-15 detection to provide insights for personalized immunotherapy of NPC patients.