Project description:Lung cancer is the deadliest cancer worldwide. In this study, we obtained RNA-sequencing data from 61 lung cancer samples. We hope that this data can improve the understanding of this disease.
Project description:Lung cancer is the leading cause of cancer mortality and early detection is the key to improve survival. However, there are no reliable blood-based tests currently available for early-stage lung cancer diagnosis. Here, we performed single-cell RNA sequencing of early-stage lung cancer and found lipid metabolism was broadly dysregulated in different cell types and glycerophospholipid metabolism is the most significantly altered lipid metabolism-related pathway. Untargeted lipidomics were detected in an exploratory cohort of 311 participants. Through support vector machine algorithm-based and mass spectrum-based feature selection, we have identified nine lipids as the most important detection features and developed a LC-MS-based targeted assay utilizing multiple reaction monitoring. This target assay achieved 100.00% specificity on an independent validation cohort. In a hospital-based lung cancer screening cohort of 1036 participants examined by low dose CT and a prospective clinical cohort containing 109 participants, this assay reached over 90.00% sensitivity and 92.00% specificity. Accordingly, matrix-assisted laser desorption/ionization-mass spectrometry imaging assay confirmed the selected lipids were differentially expressed in early-stage lung cancer tissues in situ. Thus, this method, designated as Lung Cancer Artificial Intelligence Detector (LCAID), may be used for early detection of lung cancer or large-scale screening of high-risk populations in cancer prevention.
Project description:This study aims to identify the molecular function of LncPTEN1 in lung cancer and explore its associated proteins and pathways. Using RNA pulldown coupled with mass spectrometry, we investigated the protein interactions of LncPTEN1 in A549 lung cancer cells. The experiment included three biological replicates with samples 1, 2, 3 as control group and samples 4, 5, 6 as LncPTEN1 overexpression group. The study revealed potential binding partners including Vimentin and Trim16, providing insights into the regulatory mechanisms of LncPTEN1 in lung cancer metastasis.
