Comparison of gene expression profiling of human lung at four developmental stages and lung adenocarcioma
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE43767 | GEO | 2014/08/25
SECONDARY ACCESSION(S): PRJNA187366
REPOSITORIES: GEO
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Project description:It is gradually becoming a new aspect in research to search and explore embryo development for malignant information hidden in tumor cells. In this study, the gene expression profiles for human lungs at four developmental stages and lung adenocarcinoma (ADC) were depicted, respectively. The molecular dynamics was compared for development and lung ADC, and it was proposed that primary lung ADC may hijack part of the molecular mechanisms of lung development to down-regulate homeostasis-associated genes and up-regulate stemness-associated genes; and it was revealed that the genes with monotonely decreasing expression trend during lung development process are enriched with lung ADC prognostic information. The study material for developing lung consisted of 29 cases of therapeutic or spontaneous abortion. The samples included whole embryos aged 3 to 5 weeks post ovulation (n = 10, named WholeE), lungs at 6 to 8 postovulatory weeks (PWs) (n = 10, named EarlyL) and lungs at 16 to 24 PWs (n = 9, named MiddleL). WholeE and EarlyL samples were carefully obtained from medical waste with the guidance of a Nikon stereo microscope SMZ1500 (Japan). MiddleL were collected when autopsies were performed. Embryo/Fetuses with known or suspected genetic disorders were excluded. Uninvolved peripheral lung tissue from adults (named MatureL) was obtained from fifteen patients operated on for benign lung diseases. 69 Lung ADC samples used for expression profiling analysis were obtained from patients. All these samples were examined with Agilent Whole Human Genome 4×44k microarray.
2014-08-25 | E-GEOD-43767 | biostudies-arrayexpress
Project description:Our group previously reported the gene expression profiles of four stages of human lung development, and the expression of one group of genes (PTN1 genes) steadily decreased during lung development, the data included four stages of human lung development and 69 lung adenocarcinoma (ADC) samples, and their gene expression profile data are available in the GEO (GSE43767). Our group has already performed another study with 69 lung squamous cell carcinoma (SCC) tissues, the gene expression profile data are available in the Gene Expression Omnibus (GSE67061). In the present study, we performed the whole genome gene expression mircroarray of 60 paracancerous tissues of human lung squamous cell carcinoma, we aim to show expression characteristics of PTN1 genes during the four lung developmental stages and in lung ADC, lung SCC and paracancerous samples. We examined the prognostic value of the PTN1 genes in five independent lung adenocarcinoma (ADC) and five squamous cell carcinoma (SCC) microarray datasets and revealed that the expression of PTN1 genes was associated with survival in lung ADC patients but had no prognostic value for lung SCC.
2017-07-15 | GSE101420 | GEO
Project description:Background: The development of a more refined prognostic methodology for early non-small cell lung cancer (NSCLC) is an unmet clinical need. An accurate prognostic tool might help to select patients at early stages for adjuvant therapies. Results: A new integrated bioinformatics searching strategy, that combines gene copy number alterations and expression, together with clinical parameters was applied to derive two prognostic genomic signatures. The proposed methodology combines data from patients with and without clinical data with a priori information on the ability of a gene to be a prognostic marker. Two initial candidate sets of 513 and 150 genes for lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively, were generated by identifying genes which have both: a) significant correlation between copy number and gene expression, and b) significant prognostic value at the gene expression level in external databases. From these candidates, two panels of 7 (ADC) and 5 (SCC) genes were further identified via semi-supervised learning. These panels, together with clinical data (stage, age and sex), were used to construct the ADC and SCC hazard scores combining clinical and genomic data. The signatures were validated in two independent datasets (n=73 for ADC, n=97 for SCC), confirming that the prognostic value of both clinical-genomic models is robust, statistically significant (P=0.008 for ADC and P=0.019 for SCC) and outperforms both the clinical models (P=0.060 for ADC and P=0.121 for SCC) and the genomic models applied separately (P=0.350 for ADC and P=0.269 for SCC). Conclusion: The present work provides a methodology to generate a robust signature using copy number data that can be potentially used to any cancer. Using it, we found new prognostic scores based on DNA s that, jointly with clinical information, are able to predict overall survival (OS) in patients with early-stage ADC and SCC.
2015-08-20 | GSE72194 | GEO
Project description:Background: The development of a more refined prognostic methodology for early non-small cell lung cancer (NSCLC) is an unmet clinical need. An accurate prognostic tool might help to select patients at early stages for adjuvant therapies. Results: A new integrated bioinformatics searching strategy, that combines gene copy number alterations and expression, together with clinical parameters was applied to derive two prognostic genomic signatures. The proposed methodology combines data from patients with and without clinical data with a priori information on the ability of a gene to be a prognostic marker. Two initial candidate sets of 513 and 150 genes for lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively, were generated by identifying genes which have both: a) significant correlation between copy number and gene expression, and b) significant prognostic value at the gene expression level in external databases. From these candidates, two panels of 7 (ADC) and 5 (SCC) genes were further identified via semi-supervised learning. These panels, together with clinical data (stage, age and sex), were used to construct the ADC and SCC hazard scores combining clinical and genomic data. The signatures were validated in two independent datasets (n=73 for ADC, n=97 for SCC), confirming that the prognostic value of both clinical-genomic models is robust, statistically significant (P=0.008 for ADC and P=0.019 for SCC) and outperforms both the clinical models (P=0.060 for ADC and P=0.121 for SCC) and the genomic models applied separately (P=0.350 for ADC and P=0.269 for SCC). Conclusion: The present work provides a methodology to generate a robust signature using copy number data that can be potentially used to any cancer. Using it, we found new prognostic scores based on DNA s that, jointly with clinical information, are able to predict overall survival (OS) in patients with early-stage ADC and SCC.
2015-08-20 | GSE72192 | GEO
Project description:Background: A gel-free proteomic approach was utilized to perform in-depth tissue protein profiling of lung adenocarcinoma (ADC) and normal lung tissues from early and advanced stages of the disease. The long-term goal of this study is to generate a large-scale, label-free proteomic data set from histologically well-classified lung ADC that can be used to increase further our understanding of disease progression and aid in identifying novel biomarkers. Methods and Results: Cases of early-stage (I-II) and advanced-stage (III-IV) lung ADCs were selected and paired with normal lung tissues from 22 patients. The histologically and clinically stratified human primary lung adenocarcinomas were analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS). From the analysis of ADC and normal specimens, 5,933 protein groups were identified. To examine the protein expression profile of ADC, a peak area-based quantitation method was used. In early- and advanced-stage ADC, 33 and 39 proteins were differentially-expressed respectively between normal and tumor tissue (adjusted p-value < 0.01, fold change ≥ 4). For early- and advanced stage ADC tumors compared to normal patient-matched tissue, 11 and 22 proteins and 23 and 16 proteins were identified as down- and up-regulated, respectively. In silico functional analysis of the up-regulated proteins in both tumor groups revealed that most of the enriched pathways are involved in mRNA metabolism. Furthermore, the most over-represented pathways in the proteins that were unique to ADC are related to mRNA metabolic processes. Conclusions: Further analysis of these data may provide an insight into the molecular pathways involved in disease etiology and may lead to the identification of biomarker candidates and potential targets for therapy. Our study provides potential diagnostic biomarkers for lung ADC and novel stage-specific drug targets for rational intervention.
2021-09-09 | PXD019259 | Pride
Project description:Identification of genes up-regulated in ALK-positive and EGFR/KRAS/ALK-negative lung adenocarcinomas. To elucidate molecular characteristics of lung adenocarcinomas (ADCs) with ALK mutations and those without EGFR, KRAS and ALK mutations, 226 primary lung ADCs of pathological stage I-II, examined for the status of EGFR, KRAS and ALK mutations, were subjected to genome-wide expression profiling, and genes up-regulated in lung ADCs with ALK mutations and those without EGFR, KRAS and ALK mutations were identified. One hundred and seventy-four genes, including ALK, were selected as being up-regulated specifically in 79 lung ADCs without EGFR and KRAS mutations. These 79 cases were divided into: 11 cases of ALK-positive ADCs, 36 cases of group A triple-negative ADCs, and 32 cases of group B triple-negative ADCs, by unsupervised clustering according to the expression of the 174 genes. In ALK-positive ADCs, 30 genes, including ALK itself and GRIN2A, were significantly overexpressed. Group A triple-negative ADC cases showed significantly worse prognoses for relapse and death than ADC cases with EGFR, KRAS or ALK mutations and group B triple-negative ADC cases. Nine genes were identified as being significantly up-regulated in group A triple-negative ADC cases and critical for predicting their prognosis. The nine genes included DEPDC1, which had been identified as a candidate diagnostic and therapeutic target in bladder and breast cancers. Genes discriminating this group of ADCs will be useful for selection of patients who will benefit from adjuvant chemotherapy after surgical resection of stage I-II triple-negative ADCs and also informative for the development of molecular targeting therapies for these patients. Expression profiles in of 226 lung adenocarcinomas (127 with EGFR mutation, 20 with KRAS mutation, 11 with EML4-ALK fusion and 68 triple negative cases).
2011-11-01 | E-GEOD-31210 | biostudies-arrayexpress
Project description:Distinct lung stem cells give rise to lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC). ΔNp63 guides development of these cells through regulation of terminal differentiation; however, its mechanistic role in lung cancer development has remained elusive. We utilized a ΔNp63-specific conditional knockout mouse model and found that ∆Np63 maintains lung ADC and SCC by keeping lung stem cells in quiescence. ChIP-seq analysis of lung basal cells and alveolar type 2 (AT2) cells lacking ∆Np63 revealed a robust loss of activating histone marks at super enhancers of cell identity genes defining a unifying oncogenic role for ∆Np63 in non-small cell lung cancer.
2021-12-23 | GSE131671 | GEO
Project description:Chinese lung ADC adjacent normal sample exon-level expression
2017-06-10 | GSE74116 | GEO
Project description:Background: Non-small cell lung cancers (NSCLCs) consist of adenocarcinoma (ADC), squamous cell carcinoma (SCC) and other types. Since most NSCLCs are now diagnosed from small biopsies or cytology materials, classification is not always accurate. This is a problem as many therapy regimens and clinical trials are histology-dependent. Specific Aim: To develop an RNA expression signature as an adjunct test for routine histo-pathological classification of NSCLCs. Methods: A microarray dataset of resected ADC and SCC cases was used as the learning set for an ADC-SCC signature. The Cancer Genome Atlas (TCGA) lung RNAseq dataset was used as a validation set. Another microarray dataset of ADCs and non-malignant lung was used as the learning set for a Tumor-Nonmalignant signature. The classifiers were selected as the most differentially expressed genes and sample classification was determined by a nearest distance approach. Results: We developed a 42-gene expression signature that contained many genes used in immunostains for NSCLC typing. Testing of the TCGA and other public datasets resulted in high accuracies (93-95%). We also observed that most non-malignant lung samples were classified as â??adenocarcinomasâ??, so we added 20 genes to differentiate tumor from non-malignant lung. Together, the 62-gene signature can discriminate ADC, SCC, and non-malignant lung. Additionally, a prediction score was derived that correlated both with histologic grading and survival. Summary and significance: Our histologic classifier provides a non-subjective method to aid in the pathological diagnosis of lung cancer and assist enrollment onto histology-based clinical trials 83 lung adenocarcinomas and 83 matched adjacent non-malignant lung were profiled on Illumina WG6-V3 expression arrays
2016-06-01 | E-GEOD-75037 | biostudies-arrayexpress
Project description:Here we describe novel murine models of pulmonary adenocarcinoma (ADC) and sarcomatoid carcinoma (PSC) driven by the loss of two tumor suppressors: deletion of Trp53 and Pten. Combined deletion of Pten and Trp53 in the lungs of adult conditional mice leads to the development of both ADC and PSC irrespective of the lung targeted cell type or naphthalene induced airway epithelial regeneration. Although this model shows long latency periods and incomplete penetrance for tumor development, it is the first PSC mouse model reported so far, and sheds light on the relationships between ADC and PSC and their cells of origin. Moreover, human ADC show strong transcriptomic similarities to mouse PSC, providing a link between these tumor types and human ADC. Ablation of Trp53 and Pten in pulmonary cells was achieved by intratracheal administration of purified Ad5-CMVcre or Ad5-K5cre (Du Page et al, 2009) to Trp53F/F; PtenF/F 8–10 week old mice. Mice were sacrificed at different time points after the Ad5-cre infection and tumors processed for whole transcriptome analysis. As control animals, Trp53F/F; PtenF/F littermates were used.
2022-08-17 | GSE199905 | GEO