Active clinical trials for "Carcinoma, Non-Small-Cell Lung"

The purpose of this study is to assess the correlation of the predicted post-operative lung function with the observed post-operative lung function (FEV1 and DLCO) in patients who underwent surgical resection (FEV1 = Forced expiratory volume in 1-second. DLCO = Diffusion capacity for carbon monoxide. ppo = predicted postoperative.)and versus the gold standard QRRVP (Quantitative Radionuclide Study of Regional Lung Ventilation and Perfusion)

This study will examine, for the first time, the independent contribution of a patient's own genetic makeup to the development of post-radiation complications, permitting the future development of predictive tests to avoid radiation injury. To do this, the investigators will examine gene markers in a series of breast, prostate, brain and lung cancer survivors who have received conformal radiotherapy between 1996 and 2003 at the Cross Cancer Institute and Tom Baker Cancer Centre.

The association between cancer and thrombosis is well known and the occurrence of thrombotic complications is commonly associated with poor prognosis. The aim os this study is to determine the possible value of hypercoagulable parameters as prognostic parameters in advanced non-small cell lung carcinoma (NSCLC).

Circulating tumor DNA (ctDNA) is a promising biomarker for noninvasive assessment of cancer burden. In this study, PEAC (Personalized Analysis of Cancer) technology was performed to detect the driver gene mutations from plasma samples and matched tumor tissue samples were detected by NGS platform at baseline. Investigators also applied ctDNA dynamic monitoring using PEAC technology in early stage NSCLC patients with driver mutations positive at baseline, to evaluate the feasibility and their potential clinical application.

The goal of the project is to develop and validate the BioForte technology. Its main functionality should be to in silico determine candidates for novel microbiome-based therapeutics and diagnostics. Key challenge to be solved using the technology is to detect the differences in gut microbiome between oncology patients who respond to immunotherapies and the ones who do not respond to this treatment. This technology employs machine learning methods to replace the laboratory procedure for finding valuable genomic features. Such features can be crucial to identify differences between the two populations (e.g. responders vs non-responders) to target specific strains. The samples and data collected in this clinical study will be used for clinical validation of BioForte technology. For all patients treated with immunotherapy, stool collection will be performed per patient (one stool collection before setting up immunotherapy using anti-PD1 / anti-PDL1 and / or anti CTLA4 antibodies). Samples will be sequenced by long-read sequencing technology. In parallel, we will also collect samples of peripheral blood samples (PBMC) and biopsy (FFPE).

The purpose of this study is to assess whether the detection of circulating tumor cells (CTC) could be used as a tool to earlier diagnose, more accurately predict treatment response / failure and predict overall survival in non-small cell lung cancer (NSCLC) patients

Surgery may be the best treatment choice for early stage non-small cell lung cancer. And VATS major lung resection have been preferred as a standard radical procedure for early stage non-small cell lung cancer (NSCLC).This study aim to investigate the outcome of VATS major lung resection for lung cancer as a real-world study in china.

A 15-gene lung signature was created to identify predictive and prognostic biomarkers for Non-Small Cell Lung Cancer (NSCLC) patients. The 15-gene signature was validated using a microarray platform with fresh frozen tumor tissue to place NSCLC patients into high risk and low risk cohorts with significantly different survivals. Using fresh frozen tissue can be challenging, so this study attempts simplify the process by migrating the 15-gene signature from fresh frozen to two alternative tissue formats: Formalin Fixed Paraffin Embedded (FFPE) and RNAlater. The gene expressions of the different tissue formats will be compared to see if the fresh frozen tissue results are similar to the alternative tissue formats.

The purpose of this study is to learn whether our own made predictive algorithm can be used as a clinical practical decision support for patients with NSCLC spinal metastasis. The scoring system consists of the use of EGFR-TKI, KPS, Age, SCC, CA125 and smoking history. By predicting survival doctors could determine which patients are suitable for palliative therapy.

A multi-centre observational, non-interventional study is to dynamically monitor the changes of circulating tumor DNA (ctDNA) in late stage NSCLC patients under Gefitinib treatment.