Project description:Immunotherapy has improved the prognosis of patients with advanced non-small cell lung
cancer (NSCLC), but only a small subset of patients achieved clinical benefit. The purpose of our study was to integrate multidimensional data using a machine learning method to predict the therapeutic efficacy of immune checkpoint inhibitors (ICIs) monotherapy in patients with advanced NSCLC.The authors retrospectively enrolled 112 patients with stage IIIB-IV NSCLC receiving ICIs monotherapy. The random forest (RF) algorithm was used to establish efficacy prediction models based on five different input datasets, including precontrast computed tomography (CT) radiomic data, postcontrast CT radiomic data, combination of the two CT radiomic data, clinical data, and a combination of radiomic and clinical data. The 5-fold cross-validation was used to train and test the random forest classifier. The performance of the models was assessed according to the area under the curve (AUC) in the receiver operating characteristic (ROC) curve. Among these models(RF MLP LR XGBoost), our reproduced onnx models have better performance, especially for random forest. The response variable with a value (1/0) indicates the (efficacy/inefficacy) of PD-1/PD-L1 monotherapy in patients with advanced NSCLC
2023-07-11 | BIOMD0000001074 | BioModels
Project description:Gut resistome of NSCLC patients treated with immunotherapy
Project description:Introduction: Immune checkpoint inhibitors(ICIs) targeting programmed cell death protein 1 (PD1) confer significant survival benefits to patients with non-small cell lung cancer (NSCLC). However, there remains a substantial unmet need to identify therapeutic approaches to overcome resistance and provide benefits to these patients. High-dose ascorbic acid (AA) acts synergistically with many standard anticancer treatments. However, little is known about the effect of high-dose AA on improving the efficacy of anti-PD1 inhibitors in NSCLC. This study aimed to elucidate the effects of high-dose AA on anti-PD1 immunotherapy in NSCLC. Methods: The combined effects of high-dose AA and anti-PD1 were investigated using a coculture model of H460 cells and CD8+ T cells and an LLC1 lung cancer syngeneic mouse model. To investigate the molecular mechanism, tumor tissues from mice were analyzed by comprehensive proteomic profiling using nano-LC-ESI-MS/MS. Results: Pretreatment with a high dose of AA led to enhanced the sensitivity to the cytotoxicity of CD8+ T cells derived from healthy donor for H460 cells. Additionally, the combination of anti-PD1 and high-dose AA significantly increased CD8+ T cell cytotoxicity in H460 cells. The combination of anti-PD1 and high-dose AA showed dramatic antitumor effects in a syngeneic mouse model of lung cancer by significantly reducing tumor growth and increasing CD8+ T cell-dependent cytotoxicity and macrophage activity. Comprehensive protein analysis confirmed that high-dose AA in anti-PD1-treated tumor tissues enhanced the antitumor effects by regulating various immune-related mechanisms, including the B cell and T cell receptor signaling pathways, Fc gamma R-mediated phagocytosis, and natural killer (NK) cell-mediated cytotoxicity. Discussion: Our results suggest that high-dose AA may be a promising adjuvant to potentiate the efficacy of anti-PD1 immunotherapy.
Project description:Anti-PD(L)1 with chemotherapy is a standard of care for non-small cell lung cancer (NSCLC), but a varying degree of response to the same regimen is observed in patients. The tumor immune microenvironment (TIME) plays a key role in response to immunotherapy, and the TIME heterogeneity in association with therapeutic outcome is incompletely understood. Here we prospectively applied single-cell RNA and TCR sequencing to characterize post-neoadjuvant chemo-immunotherapy treatment tumor samples of 234 NSCLC patients. Our study provides a fine-grained dissection of the TIME heterogeneity underlying response to chemo-immunotherapy in NSCLC, thus representing a valuable resource for improved management of NSCLC.
Project description:Ongoing immunomodulatory strategies in tumors characterized by an overall hot immune phenotype may improve prognosis of patients with non-small cell lung cancer (NSCLC). Our objective was to develop a reliable and stable scoring system for the identification of immunologically hot NSCLC and to evaluate its association with response to immunotherapies. A Hot Oral Tumor (HOT) score was developed using data from The Cancer Genome Atlas. HOT score was computed in 82 patients with NSCLC treated with second-line immunotherapy targeting PD-1/PD-L1. High HOT score was associated with a statistically significant improved clinical outcome.
Project description:Immunotherapy has improved survival rates in NSCLC patients, but identifying those who will respond to treatment remains a challenge. We performed a differential proteomic quantitative analysis based on SWATH–MS technology to analyse the proteome in blood samples collected from patients with advanced NSCLC prior to the start therapy and during the therapy
Project description:We launched an investigator-initiated, Simon’s two-stage design trial of neoadjuvant sintilimab combined with carboplatin and nab-paclitaxel (nab-PC) in early-stage EGFR-mutant NSCLC (Clinicaltrial.gov number NCT05244213). Here we report the first interim results of stage 1 cohort which met the overall primary endpoint in advance, and multi-omics profiling of neoadjuvant immunotherapy combination in early-stage EGFR-mutant patients. We performed in-depth single-cell RNA/TCR sequencing (scRNA/TCR-seq) of cells derived from 11 resected tumors as well as 34 tumors from real-world cohort which were all confirmed wild-type lung adenocarcinoma (LUAD) or adeno-squamous carcinoma (ASC) and received neoadjuvant immunochemotherapy as control. By associating the tumor microenvironment (TME) and with responses, we uncovered heterogeneous mechanisms of primary resistance, providing insights into further strategic developments of combination regimens to improve the clinical outcome of EGFR-mutant NSCLC patients.
Project description:Immunotherapy in immunologically active tumors may improve prognosis of non-small cell lung carcinomas (NSCLC). Our objective was to develop a reliable and stable scoring system for the identification of immunologically active HNSCC and to evaluate its association with response to immunotherapies. A Hot Oral Tumor (HOT) score was developed using data from The Cancer Genome Atlas in human-papillomavirus negative head and neck squamous cell carcinomas; it was computed in 92 patients with early stage NSCLC treated with surgery to evaluate the prognostic impact of the HOT score.