Project description:RRBS data from TRACERx non-small cell lung cancer (NSCLC) tumours and matched normal adjacent tissue.
TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).
Project description:TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).
Project description:TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).
Project description:Whole exome sequencing of tumors and paired adjacent uninvolved tissues from 222 early stage NSCLC patients, in order to identify genomic drivers present in early-stage non-small cell lung cancer and determine the overall tumor mutational burden in early-stage non-small cell lung cancer.
Project description:Plasma samples from 100 early stage (I to IIIA) non–small-cell lung cancer (NSCLC) patients and 100 non-cancer controls were screened for 754 circulating microRNAs via qRT-PCR, using TaqMan MicroRNA Arrays. Our objective was to identify a panel of circulating microRNAs in plasma that will contribute to early detection of lung cancer.
Project description:TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).
This study looks at multi-region RRBS data from the TRACERx cohort selected for quantity of material available and high tumour purity
Project description:Lung cancer is the second most commonly diagnosed cancer and the leading cause of cancer death worldwide, of which approximately 85% are non-small cell lung cancer (NSCLC). The overall survival (OS) of patients with advanced NSCLC was significantly prolonged with immune checkpoint inhibitors (ICIs) targeting the programmed cell death-1 (PD-1) and programmed death-ligand 1 (PD-L1) axis. For early-stage lung cancer, the 5-year survival rate for patients ranges from 80% in stage IA to 41% in stage IIIA, and many cases relapse after surgical resection. Currently, multiple clinical trials have manifested the encouraging efficacy of neoadjuvant immunotherapy in stage I-IIIA resectable NSCLC. However, the effect of immunotherapy in ultra early-stage NSCLC patients with micro-invasive or even pre-invasive lesions remains unclear. In this study, we aimed to evaluate the activity and safety of sintilimab on high-risk ground glass opacity lesions in multiple primary lung cancer patients.
Project description:TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). This study looks at the multi-region RNAseq data from the TRACERx100 cohort with high enough quality RNA available. There is RNAseq data from 164 regions (64 patients).
Project description:Aberrant serum N-glycan profiles have been observed in multiple cancers including non-small-cell lung cancer (NSCLC), yet the potential of N-glycans in the early diagnosis of NSCLC remains to be determined. Here, serum N-glycan profiles of 275 NSCLC patients and 309 healthy controls were characterized by MALDI-TOF-MS. The levels of serum N-glycans and N-glycosylation patterns were compared between NSCLC and control groups. In addition, a panel of N-glycan biomarkers for NSCLC diagnosis was established and validated using machine learning algorithms. As a result, a total of 54 N-glycan structures were identified in human serum. Compared with healthy controls, 29 serum N-glycans were up- or down-regulated in NSCLC patients. N-glycan abundance in different histological types or clinical stages of NSCLC presented differentiated changes. Furthermore, an optimal biomarker panel of 8 N-glycans was constructed based on logistic regression, with an AUC of 0.86 in the validation set. Notably, this model also showed a desirable capacity in distinguishing early-stage patients from healthy controls (AUC = 0.88). In conclusion, our work highlights the abnormal N-glycan profiles in NSCLC and provides supports for the promising potential of N-glycan panels in clinical NSCLC detection.
Project description:Anti-programmed death-1 (PD-1) treatment for advanced non-small-cell lung cancer (NSCLC) has improved the survival of patients. However, a significant percentage of patients do not respond. We examined the use of DNA methylation profiles to determine the efficacy of anti-PD-1 treatment in stage IV NSCLC patients.
