Metagenome analysis for immunotherapy-treated patients with NSCLC
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PROVIDER: PRJEB69295 | ENA |
REPOSITORIES: ENA
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Project description:BackgroundThe newest method of treatment for patients with NSCLC (non-small cell lung cancer) is immunotherapy directed at the immune checkpoints PD-1 (Programmed Cell Death 1) and PD-L1 (Programmed Cell Death Ligand 1). PD-L1 is the only validated predictor factor for immunotherapy efficacy, but it is imperfect. Some patients do not benefit from immunotherapy and may develop primary or secondary resistance. This study aimed to assess the intestinal resistome composition of non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors in the context of clinical features and potentially new prediction factors for assessing immunotherapy efficacy.MethodsThe study included 30 advanced NSCLC patients, 19 (57%) men and 11 (33%) women treated with first- or second-line immunotherapy (nivolumab, pembrolizumab or atezolizumab). We evaluated the patient's gut resistome composition using the high sensitivity of targeted metagenomics.ResultsStudies have shown that resistome richness is associated with clinical and demographic factors of NSCLC patients treated with immunotherapy. Smoking seems to be associated with an increased abundance of macrolides, lincosamides, streptogramins and vancomycin core resistome. The resistome of patients with progression disease appears to be more abundant and diverse, with significantly higher levels of genomic markers of resistance to lincosamides (lnuC). The resistance genes lnuC, msrD, ermG, aph(6), fosA were correlated with progression-free survival or/and overall survival, thus may be considered as factors potentially impacting the disease.ConclusionThe results indicate that the intestinal resistome of NSCLC patients with immune checkpoint inhibitors treatment differs depending on the response to immunotherapy, with several distinguished markers. Since it might impact treatment efficacy, it must be examined more deeply.
| S-EPMC11335565 | biostudies-literature
Project description:Metagenome data from soil samples were collected at 0 to 10cm deep from 2 avocado orchards in Channybearup, Western Australia, in 2024. Amplicon sequence variant (ASV) tables were constructed based on the DADA2 pipeline with default parameters.
2025-06-15 | GSE298403 | GEO
Project description:Tumor mutation burden estimated with whole exome sequencing of 43 NSCLC patient tumors treated with anti-PD-1 + anti-CTLA-4
2018-02-15 | PRJEB24995 | EVA
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
2025-02-18 | PXD042091 | Pride
Project description:Different types of therapy are currently being used to treat non-small cell lung cancer (NSCLC) depending on the stage of tumor and the presence of potentially druggable mutations. However, few biomarkers are available to guide clinicians in selecting the most effective therapy for all patients with various genetic backgrounds. To examine whether patients' mutation profiles are associated with the response to a specific treatment, we collected comprehensive clinical characteristics and sequencing data from 524 patients with stage III and IV NSCLC treated at Atrium Health Wake Forest Baptist. Overall survival based Cox-proportional hazard regression models were applied to identify mutations that were "beneficial" (HR < 1) or "detrimental" (HR > 1) for patients treated with chemotherapy (chemo), immune checkpoint inhibitor (ICI) and chemo+ICI combination therapy (Chemo+ICI) followed by the generation of mutation composite scores (MCS) for each treatment. We also found that MCS is highly treatment specific that MCS derived from one treatment group failed to predict the response in others. Receiver operating characteristics (ROC) analyses showed a superior predictive power of MCS compared to TMB and PD-L1 status for immune therapy-treated patients. Mutation interaction analysis also identified novel co-occurring and mutually exclusive mutations in each treatment group. Our work highlights how patients' sequencing data facilitates the clinical selection of optimized treatment strategies.
| S-EPMC10042886 | biostudies-literature
Project description:Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of lung cancer. However, their clinical benefit is limited to a minority of patients. To unravel immune-related factors that are predictive of sensitivity or resistance to immunotherapy, we performed a gene expression analysis by RNA-Seq using the Oncomine Immuno Response Assay (OIRRA) on a total of 33 advanced NSCLC patients treated with ICI evaluating the expression levels of 365 immune-related genes. We found four genes (CD1C, HLA-DPA1, MMP2, and TLR7) downregulated (p < 0.05) and two genes (IFNB1 and MKI67) upregulated (p < 0.05) in ICI-Responders compared to ICI-Non-Responders. The Bayesian enrichment computational analysis showed a more complex interaction network that involved 10 other genes (IFNA1, TLR4, CD40, TLR2, IL12A, IL12B, TLR9, CD1E, IFNG, and HLA-DPB1) correlated with different functional groups. Five main pathways were identified (FDR < 0.0001). High TLR7 expression levels were significantly associated with a lack of response to immunotherapy (p < 0.0001) and worse outcome in terms of both PFS (p < 0.001) and OS (p = 0.03). The multivariate analysis confirmed TLR7 RNA expression as an independent predictor for both poor PFS (HR = 2.97, 95% CI, 1.16-7.6, p = 0.023) and OS (HR = 2.2, 95% CI, 1-5.08, p = 0.049). In conclusion, a high TLR7 gene expression level was identified as an independent predictor for poor clinical benefits from ICI. These data could have important implications for the development of novel single/combinatorial strategies TLR-mediated for an efficient selection of "individualized" treatments for NSCLC in the era of immunotherapy.
| S-EPMC8303258 | biostudies-literature
Project description:Treatment with immunotherapy has made a significant impact in the outcomes for those individuals diagnosed with metastatic non-small cell lung cancer (NSCLC) and its use is currently an established treatment modality. In light of recent advances in immunotherapy, improved survival, particularly for patients with stage IV NSCLC, has been reported with durable and prolonged responses in a subset of patients. Immune check point inhibitors, which include nivolumab, pembrolizumab, and atezolizumab, are standard treatment options in the salvage setting. Nivolumab and atezolizumab are approved for patients regardless of programmed death-ligand 1 (PD-L1) expression, whereas pembrolizumab requires tumor PD-L1 expression at the cut-off ≥1%. In this review, we will outline the clinical development of immunotherapy in previously treated NSCLC, current challenges and discuss novel treatment strategies.
| S-EPMC5861264 | biostudies-literature
Project description:AimThe role of tumor burden (TB) for patients with non-small cell lung cancer (NSCLC) receiving immunotherapy is still unknown. The aim of this analysis was to analyze the prognostic value of TB in a real-world sample of advanced NSCLC patients.MethodsSixty-five consecutive patients with advanced NSCLC treated with immunotherapy as first or second line therapy were retrospectively analyzed between August 2015 and February 2018. TB was recorded at baseline considering sites and number of metastases, thoracic vs. extrathoracic disease, measurable disease (MD) vs. not-MD (NMD) and evaluating dimensional aspects as maximum lesion diameter (cut-off = 6.3 cm), sum of the 5 major lesions diameters (cut-off = 14.3 cm), and number of sites of metastases (cut-off > 4). All cut-offs were calculated by receiver operating characteristic curves. Median overall survival (OS) was estimated using Kaplan-Meier method. A Cox regression model was carried out for univariate and multivariate analyses.ResultsMedian age was 70 years and most patients (86.2%) had a good performance status (PS-Eastern Cooperative Oncology Group < 2). No significant difference in OS was noted between subgroups of patients according to TB. Bone metastases (BM) had a negative prognostic impact [median OS (mOS), 13.8 vs. 70.0 months, P = 0.0009; median progression free survival in the second line (mPFS2) 2.97 vs. 8.63 months; P = 0.0037]. Patients with NMD had a poorer prognosis (mOS, 15.9 months vs. not reached, P < 0.0001; mPFS2 3.8 vs. 12.2 months; P = 0.0199). Patients with disease limited to the thorax had a better prognosis compared to patients with involvement of extrathoracic sites (mOS, 70 vs. 17.3 months; P = 0.0136). Having more than 4 metastatic sites resulted as a negative prognostic factor (mOS, 15.9 vs. 25.2 months; P = 0.0106). At multivariate analysis, BM, NMD, extrathoracic disease and number of sites of metastases > 4 were negative prognostic factors (P < 0.0001).ConclusionsThis study underlines the negative prognostic impact of specific metastatic sites, presence of NMD and extrathoracic disease in advanced NSCLC patients treated with immunotherapy. However, TB does not appear to affect the outcome of these patients.
| S-EPMC9400786 | biostudies-literature
Project description:Approximately 40% of unselected non-small cell lung cancer (NSCLC) patients develop brain metastases (BMs) during their disease, with considerable morbidity and mortality. The management of BMs in patients with NSCLC is a clinical challenge and requires a multidisciplinary approach to gain effective intracranial disease control. Over the last decade, immune checkpoint inhibitors (ICIs) have emerged as a game-changer in the treatment landscape of advanced NSCLC, with significant improvements in survival outcomes, although patients with BMs are mostly underrepresented in randomized clinical trials. Moreover, the safety and activity of ICIs and radiotherapy combinations compared with single-agent or sequential modalities is still under evaluation to establish the optimal management of these patients. The aim of this review is to summarize the state-of-the-art of clinical evidence of ICIs intracranial activity and the main challenges of incorporating these agents in the treatment armamentarium of NSCLC patients with BMs.
| S-EPMC9267075 | biostudies-literature
Project description:BackgroundSeveral biomarkers have been separately described to select patients for immunotherapy (IO), but few studies integrate these markers. Di Maio, EPSILoN and the plasma microRNA signature classifier (MSC), are three different clinico, biochemical and molecular markers able to independently predict prognosis in non-small cell lung cancer (NSCLC).MethodsComplete data such as sex, histology, ECOG-PS, stage, smoking status, presence of liver metastasis, LDH and neutrophils-to-lymphocyte ratio were collected to generate Di Maio and EPSILoN. The MSC risk level was prospectively assessed in plasma samples collected at baseline IO. The 3 markers were integrated into the DEMo score system prospectively tested in a cohort of 200 advanced NSCLC patients treated with IO. Endpoints were overall survival (OS), progression-free survival (PFS) and overall response rate (ORR).ResultsDEMo separated patients in 7-risk groups whose median OS had a trend ranging from 29.7 to 1.5 months (P<0.0001). When comparing patients with the lowest (n=29) and the highest (n=35) DEMo scores ORR was 45% and 3%, respectively (P<0.0001). Considering the 53 PD-L1 ≥50% patients, DEMo identified a group of 13 (25%) patients who benefit less from IO in terms of both OS (HR: 8.81; 95% CI: 2.87-20.01) and PFS (HR: 6.82; 95% CI: 2.57-18.10). Twelve out of 111 (11%) patients who most benefit from IO according to OS (HR: 0.21; 95% CI: 0.07-0.62) and PFS (HR: 0.28; 95% CI: 0.12-0.65) were identified by DEMo in the PD-L1 <50% group.ConclusionsThe DEMo prognostic score system stratified NSCLC patients treated with IO better than each single marker. The proper use of DEMo according to PD-L1 could improve selection in IO regimens.
| S-EPMC7354114 | biostudies-literature