Homo sapiens
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PROVIDER: PRJNA248876 | ENA |
REPOSITORIES: ENA
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Project description:In a stepwise approach, we evaluated available protocols before performing an analysis on circulating tumor cells of small cell lung cancer patients. We first compared 19 protocols on single MCF7 cells spiked miRExplore. Second, we analyzed MCF7 single cell equivalents of the eight best protocols. Third, we carried out single cell small RNA sequencing using the best performing protocol on 8 cell lines and 67 circulating tumor cells from seven small cell lung cancer patients.
2021-05-25 | GSE162514 | GEO
Project description:Tumor-initiating cells with reprogramming plasticity and/or de-differentiation attributes have been thought to initiate primary tumor development as well as to regenerate secondary tumors in metastatic organs; however, the molecular mechanisms are not fully understood. We previously found that breast tumor-initiating cell marker, CD44, directs multicellular aggregation and cluster formation of circulating tumor cells (CTCs), which further enhance stemness and survival of such cells, enabling metastatic colonization to the lungs. To further elucidate the molecular network underlying CTC cluster formation, we performed global proteomic profiling and discovered that the tetraspanin protein CD81, which is normally enriched in exosomes (small extracellular vesicles), is a new driver of cancer initiation and metastasis as a facilitator and target of CD44. Loss of CD81 compromises tumorigenicity and mammosphere formation of triple negative breast cancer (TNBC) cells. Assisted by machine learning-based algorithms and mutagenesis approach, we found that CD81 interacts with CD44 on the cellular membrane through their extracellular regions. Notably, genetic knockout of CD44 or CD81 results in loss of both CD81 and CD44 in secreted exosomes, a state which abolishes exosome-induced self-renewal of recipient cells, such as mammosphere formation. In addition, RNA sequencing analysis showed that CD81 knockdown up-regulates expression of a cell differentiation marker, SEMA7a, whose down-regulation partially rescues mammosphere formation inhibition by CD81 depletion. Clinically, CD81 expression was observed in >80% of CTCs and specifically enriched and co-expressed along with CD44 in clustered CTCs of breast cancer patients. Mimicing the phenotypes of CD44 deficiency, loss of CD81 also inhibited tumor cell aggregation and lung metastasis of TNBC in both human and mouse tumor models, supporting the clinical significance of CD81 in association with patient outcomes. Our study highlights a new driving role of CD81 in cancer exosome-induced stemness, clustered CTCs, and metastasis initiation of TNBC, reported for the first time to our knowledge.
2022-10-18 | PXD029529 | JPOST Repository
Project description:Early detection of small cell lung cancer crucially demands highly reliable markers. Growing evidence suggests that extracellular vesicles carry tumor cell-specific cargo suitable as protein markers in cancer. Therefore, we isolated plasma-derived exosomes from newly diagnosed small cell lung cancer patients and investigated proteome dynamics of these exosomes aiming at improving the detection of small cell lung cancer. A total of 1,016 proteins were initially identified. After data processing and statistical analysis, several proteins were found to be differentially expressed in comparing small cell lung cancer patients and healthy individuals, indicating that circulating exosomes may encompass specific proteins with potential diagnostic attributes for small cell lung cancer. Furthermore, our data may indicate a novel tumor-suppressing role of blood coagulation and involvement of complement activation in small cell lung cancer pathogenesis.
2022-04-04 | PXD028885 | Pride
Project description:Large numbers of cells are generally required for quantitative global proteome profiling due to the significant surface adsorption losses associated with sample processing. Such bulk measurement obscures important cell-to-cell variability (cell heterogeneity) and makes proteomic profiling impossible for rare cell populations (e.g., circulating tumor cells (CTCs)). Here we report a surfactant-assisted one-pot sample preparation coupled with mass spectrometry (MS) termed SOP-MS for label-free global single-cell proteomics. SOP-MS capitalizes on the combination of a MS-compatible nonionic surfactant, n-Dodecyl-β-D-maltoside, and hydrophobic surface-based low-bind tubes or multi-well plates for ‘all-in-one’ one-pot sample preparation. This ‘all-in-one’ method including elimination of all sample transfer steps maximally reduces surface adsorption losses for effective processing of single cells, thus significantly improving detection sensitivity for single-cell proteomics. This method allows convenient label-free quantification of hundreds of proteins from single human cells and ~1200 proteins from small tissue sections (close to ~20 cells). When applied to a patient CTC-derived xenograft (PCDX) model at the single-cell resolution, SOP-MS can reveal distinct protein signatures between primary tumor cells and early metastatic lung cells, which are related to the selection pressure of anti-tumor immunity during breast cancer metastasis. The approach paves the way for routine, precise, quantitative single-cell proteomics.
2021-03-11 | PXD022827 | panorama
Project description:The tumor microenvironment strongly influences cancer development, progression and metastasis. The role of carcinoma-associated fibroblasts (CAFs) in these processes and their clinical impact has not been studied systematically in non-small cell lung carcinoma (NSCLC). We established primary cultures of CAFs and matched normal fibroblasts (NFs) from 15 resected NSCLC. We demonstrate that CAFs have greater ability than NFs to enhance the tumorigenicity of lung cancer cell lines. Microarray gene expression analysis of the 15 matched CAF and NF cell lines identified 46 differentially expressed genes, encoding for proteins that are significantly enriched for extracellular proteins regulated by the TGF-beta signaling pathway. We have identified a subset of 11 genes that formed a prognostic gene expression signature, which was validated in multiple independent NSCLC microarray datasets. Functional annotation using protein-protein interaction analyses of these and published cancer stroma-associated gene expression changes revealed prominent involvement of the focal adhesion and MAPK signalling pathways. Fourteen (30%) of the 46 genes also were differentially expressed in laser-capture micro-dissected corresponding primary tumor stroma compared to the matched normal lung. Six of these 14 genes could be induced by TGF-beta1 in NF. The results establish the prognostic impact of CAF-associated gene expression changes in NSCLC patients. This SuperSeries is composed of the following subset Series: GSE22862: Prognostic Gene Expression Signature of Carcinoma Associated Fibroblasts in Non-Small Cell Lung Cancer [expression profiling_CAFs] GSE22863: Prognostic Gene Expression Signature of Carcinoma Associated Fibroblasts in Non-Small Cell Lung Cancer [expression profiling_NSCLC stroma] GSE27284: Prognostic Gene Expression Signature of Carcinoma Associated Fibroblasts in Non-Small Cell Lung Cancer [methylation profiling] GSE27289: Prognostic Gene Expression Signature of Carcinoma Associated Fibroblasts in Non-Small Cell Lung Cancer [genome variation profiling]
2011-04-08 | E-GEOD-22874 | biostudies-arrayexpress
Project description:Background: The identification of cancer driver genes from sequencing data has been crucial in deepening our understanding of tumor biology and expanding targeted therapy options. However, apart from the most commonly altered genes, the mechanisms underlying the contribution of other mutations to cancer acquisition remain understudied. Leveraging on our whole-exome sequencing of the largest Asian lung adenocarcinoma (LUAD) cohort (n=302), we now functionally assess the mechanistic role of a novel driver, PARP4. Methods: In vitro and in vivo tumorigenicity assays were used to study the functional effects of PARP4 loss and mutation in multiple lung cancer cell lines. Interactomics analysis by quantitative mass spectrometry was conducted to identify PARP4’s interaction partners. Transcriptomic data from cell lines and patient tumors were used to investigate splicing alterations. Results: PARP4 depletion or mutation (I1039T) promotes the tumorigenicity of KRAS- or EGFR-driven lung cancer cells. Disruption of the vault complex, with which PARP4 is commonly associated, did not alter tumorigenicity, indicating that PARP4’s tumor suppressive activity is mediated independently. The splicing regulator hnRNPM is a potentially novel PARP4 interaction partner, the loss of which likewise promotes tumor formation. hnRNPM loss results in splicing perturbations, with a propensity for dysregulated intronic splicing that was similarly observed in PARP4 knockdown cells and in LUAD cohort patients with PARP4 copy number loss. Conclusions: PARP4 is a novel modulator of lung adenocarcinoma, where its tumor suppressive activity is mediated not through the vault complex – unlike conventionally thought, but in association with its novel interaction partner hnRNPM, thus suggesting a role for splicing dysregulation in LUAD tumorigenesis.
2024-04-02 | PXD050844 | Pride
Project description:We have isolated Circulating Tumor Cells from four Small Cell Lung Cancer Patients at diagnosis and relapse using a two-step method developed in the laboratory. Subsequently, Whole-Exome sequencing was performed on these samples as well as on the corresponding biopsies.
2023-01-11 | E-MTAB-10766 | biostudies-arrayexpress
Project description:Lung cancers are a heterogeneous group of diseases with respect to biology and clinical behavior. So far, diagnosis and classification are based on histological morphology and immunohistological methods for discrimination between two main histologic groups: small cell lung cancer (SCLC) and non-small cell lung cancer which account for 20% and 80% of lung carcinomas, respectively. While SCLCs express properties of neuroendocrine cells, NSCLCs, which are divided into the three major subtypes adenocarcinoma, squamous cell carcinoma and dedifferentiated large cell carcinoma, show different characteristics such as the expression of certain keratins or production of mucin and lack neuroedocrine differentiation. The molecular pathogenesis of lung cancer involves the accumulation of genetic und epigenetic alterations including the activation of proto-oncogenes and inactivation of tumor suppressor genes which are different for lung cancer subgroups. The development of microarray technologies opened up the possibility to quantify the expression of a large number of genes simultaneously in a given sample. There are several recent reports on expression profiling on lung cancers but the analysis interpretation of the results might be difficult because of the heterogeneity of cellular components. A contamination of the tumor sample with normal epithelia, blood vessels, stromal cells, leucocytes and tumor necrosis may confound the true expression profile of the tumor. The use of laser capture microdissection (LCM) greatly improves the sample preparation for microarray expression analysis. Consequently, we used advanced technology including LCM and microarray analysis. In detail, we examined gene expression profiles of tumor cells from 29 previously untreated patients with lung cancer (10 adenocarcinomas (AC), 10 squamous cell carcinomas (SCC), 9 small cell lung cancer (SCLC)) in comparison to normal lung tissue (LT) of 5 control patients without tumor. Bronchoscopical biopsies from the primary lung tumor were taken before treatment. Biopsies were cut into 8µm sections and from each section cancer cells were isolated using laser capture microdissection in order to obtain pure samples of tumor cells. Total RNA was extracted, reversely transcribed, in-vitro transcribed, labelled and hybridized to the array. For expression analysis, microarrays covering 8793 defined genes (Human HG Focus Array, Affymetrix) were used. Following quality control, array data were normalized and analysed for significant differences using variance stabilizing transformation (VSN) and significance analysis of microarrays (SAM), respectively. Based on differentially expressed genes cancer samples could be clearly separated from non cancer samples using hierarchical clustering. Comparing AC, SCC and SCLC with normal lung tissue, we found 205, 335 and 404 genes, respectively, that were at least 2-fold differentially expressed with an estimated false discovery rate < 2.6%. Each histological subtype showed a distinct expression profile. Further, using a genetic programming approach we constructed a classificator to discriminate AC, SCC, NT and SCLC. To this end, the 50 genes with the greatest signal-to-noise ratio were selected to train the classificator. By leave-one-out cross validation all 34 samples were correctly classified in this training set. In order to validate the 50-gene-classificator on a test set, further 13 microdissected lung cancer samples were used and correctly classified in concordance to pathologic finding. In conclusion, the different lung cancer subtypes have distinct molecular phenotypes which reflect biological characteristics of the tumor cells and which might be the basis for development of targeted therapy. Moreover, gene expression profiling and genetic programming is a suitable tool for classification and discrimination of different histological subtypes in lung cancer in comparison to normal lung tissue. Experiment Overall Design: Comparison of gene expression profiles of normal lung tissues, adenocarcinomas, squamous cell carcinomas and small cell lung cancers.
2008-06-14 | E-GEOD-6044 | biostudies-arrayexpress
Project description:The target sequecing vcf data of tumor and curculating tumor DNA for non-small cell lung cancer patients.
2022-05-09 | PRJEB52694 | EVA
Project description:RNA of Small Cell Lung Cancer Circulating Tumour Cells Derived Explants
| PRJEB36164 | ENA