Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA140947 | ENA |
REPOSITORIES: ENA
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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:We performed lung ADC and SCC transcriptome profiling from KRasG12D; Fbw7f/f murine lung tumors by RNA-seq and compared them with a consensus lung SCC signature using data from two different SCC models (Lkb1f/f; Ptenf/f, Cancer Cell 2014 and LSL-Sox2; Ptenf/f; Cdkn2abf/f, Cancer Cell 2016) that has been validated in human lung SCC
2019-01-08 | GSE123716 | GEO
Project description:Adenosquamous lung tumors may result from cellular plasticity. We demonstrate lineage switching of KRAS+ lung adenocarcinomas (ADC) to squamous cell carcinoma (SCC) through deletion of Lkb1 (Stk11) in autochthonous and transplant models. Chromatin analysis reveals loss of H3K27me3 and gain of H3K27ac and H3K4me3 at squamous lineage genes, included Sox2, ΔNp63 and Ngfr. SCC lesions have higher levels of the H3K27 methyltransferase EZH2 than the ADC lesions, but there is a clear lack of the essential Polycomb Repressive Complex 2 (PRC2) subunit EED in the SCC lesions.
2017-02-02 | GSE94365 | 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: 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: 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: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:Lung squamous cell carcinoma (SCC) is a deadly disease for which current treatments are inadequate. We demonstrate that bi-allelic inactivation of Lkb1 and Pten in the mouse lung led to SCC that recapitulated the histology, gene expression and microenvironment found in human disease. Lkb1/Pten-null (LP) tumors expressed the squamous markers Krt5, p63 and Sox2, and transcriptionally resembled the basal subtype of human SCC. In contrast to mouse adenocarcinomas, the LP tumors contained immune populations enriched for tumor-associated neutrophils. Sca1+/Ngfr+ fractions were enriched for tumor propagating cells (TPCs) that could serially transplant the disease in orthotopic assays. TPCs in the LP model and Ngfr+ cells in human SCCs highly expressed Pdl1, suggesting a novel mechanism of immune escape for TPCs. We used microarrays to detail the gene expression profles among lung SCC tumor epitheial cell, lung ADC tumor epithelia cell and normal epithelial cells. Kras tumor stroma cells and LP tumor stroma cells were sorted by FACS, the cells were gated as EpCAM-/CD45+/CD31+
2014-01-24 | E-GEOD-54352 | biostudies-arrayexpress
Project description:Lung squamous cell carcinoma (SCC) is a deadly disease for which current treatments are inadequate. We demonstrate that bi-allelic inactivation of Lkb1 and Pten in the mouse lung led to SCC that recapitulated the histology, gene expression and microenvironment found in human disease. Lkb1/Pten-null (LP) tumors expressed the squamous markers Krt5, p63 and Sox2, and transcriptionally resembled the basal subtype of human SCC. In contrast to mouse adenocarcinomas, the LP tumors contained immune populations enriched for tumor-associated neutrophils. Sca1+/Ngfr+ fractions were enriched for tumor propagating cells (TPCs) that could serially transplant the disease in orthotopic assays. TPCs in the LP model and Ngfr+ cells in human SCCs highly expressed Pdl1, suggesting a novel mechanism of immune escape for TPCs. We used microarrays to detail the gene expression profles among lung SCC tumor epitheial cell, lung ADC tumor epithelia cell and normal epithelial cells. Normal EpCAM+, Kras tumor EpCAM+ and LP tumor EpCAM+ were sorted by FACS, the cells were gating as EpCAM+/CD45-/CD31-
2014-01-24 | E-GEOD-54351 | biostudies-arrayexpress
Project description:Although adenocarcinoma of the cervix (ADC) exhibits a more malignant phenotype and poorer prognosis than squamous cell carcinoma (SCC), they are treated identically. This clinical dilemma calls for deeper investigation into differences between SCC and ADC. We studied 3 human papillomavirus (HPV)-positive SCC, 3 HPV-associated (HPVA) and 2 non-HPV-associated (NHPVA) ADC samples with single-cell RNA and T cell receptor sequencing plus 3D organoid verification. Notably, we revealed the malignant origin of epithelial cells characterized by stemness and poor differentiation and the potential mechanism of HPVA and NHPVA oncogenesis, deciphering differences between SCC and ADC. Additionally, we discovered the key role of tip cells in sprouting angiogenesis, the protumoral effects of cancer-associated fibroblasts and the functional dysregulation of T lymphocytes. We highlighted tumor microenvironment differences between different histologic subtypes through cellular interaction analysis. Importantly, we discovered novel precise treatment strategies specifically for HPV-positive SCC, HPVA and NHPVA-ADC, providing tremendous clinical value.
2023-12-01 | GSE197461 | GEO