Project description:Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer due to its rapid progression, marked potential for metastasis and the difficulty in diagnosis1-3. However, there are no effective liquid tests currently available for PDAC detection besides CA19-9. Here we introduce a noninvasive detection approach that employs machine learning plus untargeted and targeted serum lipidomics to establish an accurate method to detect PDAC.
Project description:Lipidomics, proteomics and metabolomics characterization of the ontogeny of lipid, protein and metabolite changes during normal postnatal lung development
Project description:In this study, we generated a quantitative lung tissue proteome dataset from lung adenocarcinoma and adjacent normal lung tissues by using iTRAQ labeling combined with 2D-LC-MS/MS. Based on pathway and network analyses, protein expression profiles released in the public Human Protein Atlas database, literature search and novelty, six candidates were selected for validation via immunohistochemistry staining and western blot. Additionally, the clinical and biological significance of two novel candidates, ERO1L and NARS, was further analyzed. Collectively, our results provide a useful biomarker dataset for lung adenocarcinoma diagnosis/prognosis and provide new insights into ERO1L- and NARS- mediated tumorigenesis.
Project description:In this study, we generated a quantitative lung tissue proteome dataset from lung adenocarcinoma and adjacent normal lung tissues by using iTRAQ labeling combined with 2D-LC-MS/MS. Based on pathway and network analyses, protein expression profiles released in the public Human Protein Atlas database, literature search and novelty, six candidates were selected for validation via immunohistochemistry staining and western blot. Additionally, the clinical and biological significance of two novel candidates, ERO1L and NARS, was further analyzed. Collectively, our results provide a useful biomarker dataset for lung adenocarcinoma diagnosis/prognosis and provide new insights into ERO1L- and NARS- mediated tumorigenesis.
Project description:Lung cancer is the leading cause of preventable death globally and is broadly classified into adenocarcinoma and squamous cell carcinoma depending upon cell type. In this study, we carried out mass spectrometry based quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissue by employing the isobaric tags for relative and absolute quantitation (iTRAQ) approach. Proteomic data was analyzed using SEQUEST search algorithm which resulted in identification of 25,998 peptides corresponding to 4,342 proteins of which 610 proteins were differentially expressed (≥ 2-fold) between adenocarcinoma and squamous cell carcinoma samples. These differentially expressed proteins were further classified by gene ontology for their localizations and biological processes. Pathway analysis of differentially expressed proteins revealed distinct alterations in networks and pathways in both adenocarcinoma and squamous cell carcinoma samples. In this study, we identified a subset of proteins that shows converse expression between lung adenocarcinoma and squamous cell carcinoma samples. Such proteins may serve as signature markers to distinguish between the two subtypes.
Project description:In the present study, we used a high-throughput small RNA deep sequencing followed by a systematic computational analysis to identify genome wide mutant p53R273H regulated miRNAs in both DNA damage dependent and independent context. Several miRNA-mRNA regulatory networks have been predicted that might contribute to mutant p53 GOF properties. Differentially regulated miRNA signature profile has been validated in the lung cancer patients harboring wildtype and mutant p53. We identified specific miRNA signatures for lymph node metastasis associated with p53 mutation in lung adenocarcinoma and also predicted the possible contribution of two mutant p53 regulated miRNAs in EMT process. Furthermore, this study identified a hitherto unknown miRNA in human which might act as one of the crucial downstream targets of GOF mutant p53 to confer oncogenic properties. Determination of mutant p53R273H regulated microRNAs H1299 cells.
Project description:We performed a pilot proteogenomic study to compare lung adenocarcinoma to lung squamous cell carcinoma using quantitative proteomics (6-plex TMT) combined with a customized Affymetrix GeneChip. Using MaxQuant software, we identified 51,001 unique peptides that mapped to 7,241 unique proteins and from these identified 6,373 genes with matching protein expression for further analysis. We found a minor correlation between gene expression and protein expression; both datasets were able to independently recapitulate known differences between the adenocarcinoma and squamous cell carcinoma subtypes. We found 565 proteins and 629 genes to be differentially expressed between adenocarcinoma and squamous cell carcinoma, with 113 of these consistently differentially expressed at both the gene and protein levels. We then compared our results to published adenocarcinoma versus squamous cell carcinoma proteomic data that we also processed with MaxQuant. We selected two proteins consistently overexpressed in squamous cell carcinoma in all studies, MCT1 (SLC16A1) and GLUT1 (SLC2A1), for further investigation. We found differential expression of these same proteins at the gene level in our study as well as in other public gene expression datasets. These findings combined with survival analysis of public datasets suggest that MCT1 and GLUT1 may be potential prognostic markers in adenocarcinoma and druggable targets in squamous cell carcinoma.
Project description:Kinase fusions are considered oncogenic drivers in numerous types of cancer. In lung adenocarcinoma 5-10% of patients harbor kinase fusions. The most frequently detected kinase fusion involves the Anaplastic Lymphoma Kinase (ALK) and Echinoderm Microtubule-associated protein-Like 4 (EML4). In addition, oncogenic kinase fusions involving the tyrosine kinases RET and ROS1 are found in smaller subsets of patients. In this study, we employed quantitative mass spectrometry-based phosphoproteomics to define the cellular tyrosine phosphorylation patterns induced by different oncogenic kinase fusions identified in patients with lung adenocarcinoma. We show that the cellular expression of the kinase fusions leads to widespread tyrosine phosphorylation. Direct comparison of different kinase fusions demonstrates that the kinase part and not the fusion partner primarily defines the phosphorylation pattern. The tyrosine phosphorylation patterns differed between ALK, ROS1 and RET fusions, suggesting that oncogenic signaling induced by these kinases involves the modulation of different cellular processes.
Project description:In order to determine whether dis-regulation of a genetic pathway could explain the increased apoptosis of parp-2-/- double positive thymocytes, the gene expression profiles in double positive thymocytes derived from wild-type and parp-2-/- mice were analysed using Affymetrix oligonucleotide chips (mouse genome 430 2.0).