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Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Expression Profile-Defined Classification of Lung Adenocarcinoma

ABSTRACT: Expression profiles of 18,175 unique genes and three major genetic changes, p53, EGFR and K-ras, were investigated in 149 patients with non-small cell lung cancer (NSCLC), including 90 patients with adenocarcinomas (AD) to determine their relationships with various clinicopathologic features and Gene Ontology (GO) terms. Keywords: Disease state analysis Expression profiles in 149 patients with NSCLC, 9 patients with SCLC and 5 for normal lung tissue.

ORGANISM(S): Homo sapiens

SUBMITTER: Takahashi Takashi

PROVIDER: E-GEOD-11969 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Expression profile-defined classification of lung adenocarcinoma shows close relationship with underlying major genetic changes and clinicopathologic behaviors.

Takeuchi Toshiyuki T Tomida Shuta S Yatabe Yasushi Y Kosaka Takayuki T Osada Hirotaka H Yanagisawa Kiyoshi K Mitsudomi Tetsuya T Takahashi Takashi T

Journal of clinical oncology : official journal of the American Society of Clinical Oncology 20060320 11

<h4>Purpose</h4>This study was conducted to gain insight into the relationship between expression profiles and underlying genetic changes, which are known to be important for the pathogenesis of lung cancers.<h4>Methods</h4>Expression profiles of 18,175 unique genes and three major targets for genetic changes, p53, epidermal growth factor receptor (EGFR), and K-ras, were investigated in 149 patients with non-small-cell lung cancer, including 90 patients with adenocarcinoma to determine their rel ...[more]

PMID: 16549822

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Expression Profile-Defined Classification of Lung Adenocarcinoma

Project description:Expression profiles of 18,175 unique genes and three major genetic changes, p53, EGFR and K-ras, were investigated in 149 patients with non-small cell lung cancer (NSCLC), including 90 patients with adenocarcinomas (AD) to determine their relationships with various clinicopathologic features and Gene Ontology (GO) terms. Keywords: Disease state analysis

2009-04-01 | GSE11969 | GEO

Selective Loss of RB in Resistant EGFR Mutant Lung Adenocarcinomas that Transform to SCLC [CGH]

Project description:The study was designed to identify the molecular changes that occur in EGFR mutant NSCLCs that become resistant to TKI by transforming to SCLC. Tyrosine kinase inhibitors (TKIs) are effective treatments for non-small cell lung cancers (NSCLCs) with epidermal growth factor receptor (EGFR) mutations. However, they do not lead to cures, and, on average, relapse occurs after one year of continuous treatment. In a subset of patients, a fundamental histological transformation from NSCLC to small cell lung cancer (SCLC) is observed in the resistant cancers, but the molecular changes associated with this transformation remain unknown. Analysis of a cohort of tumor samples and cell lines derived from resistant EGFR mutant patients with SCLC transformation revealed that RB is lost in 100% of these cases, but rarely in those that remain NSCLC. Global changes in gene expression, including increased neuroendocrine marker expression and absence of EGFR expression, are observed in cancers that transformed to SCLC. Consistent with their genetic and epigenetic similarities to classical SCLC, cell lines derived from resistant EGFR mutant SCLC biopsies are substantially more sensitive to ABT-263 treatment compared to those derived from resistant EGFR mutant NSCLCs. Together, these findings suggest that despite developing initially as EGFR mutant adenocarcinomas, this subset of resistant cancers ultimately take on many of the molecular and phenotypic characteristics of classical SCLC. Overall, we completed array CGH analysis on 4 tumor specimens from EGFR mutant, TKI-resistant patients. Three of these samples had transformed to SCLC and one remained NSCLC.

2015-01-30 | E-GEOD-64765 | biostudies-arrayexpress

Proteome of silenced minichromosome maintenance protein 2 with siRNA on non-small cell lung cancer H1299 cells

Project description:Lung cancer is the leading cause of cancer-related mortality. The two main lung cancer types are small cell lung cancer (SCLC) and non-SCLC (NSCLC), where NSCLC comprises about 80-85% of all lung cancer. Despite the introduction of improved treatments, the overall survival rate of lung cancer patients remains low. Further elucidation of the regulatory network perturbations between cancer-related genes and proteins is one promising route to alter this mortality trend. The deregulation of the DNA replication, cell cycle, proliferation and migration are the common factors that are involved in cancer development and progression, and therefore logical targets for analysis. Minichromosome maintenance 2(MCM2) is a DNA replication licensing factor, which belongs to the heterohexameric MCM2-7 complex. MCM2 has been proposed as an excellent proliferation marker in many types of cancer. Our study will establish a global functional distribution of identified proteins in silenced-MCM2 in H1299 NSCLC by the means of iTRAQ. Understanding the molecular basis of MCM2 in lung cancer cells enables us to discover alternative target for lung cancer therapy.

2018-10-26 | PXD003743 | Pride

Gene expression of samples derived from normal lung and patients with small cell lung cancer (SCLC) or non-small cell lung cancer (NSCLC)

Project description:Differences in gene expression profiles regarding the expression of genes encoding for proteins with G protein-coupled receptor (GPCR) activity between SCLC and NSCLC and normal lung samples was successfully examined. In the present study, 8 SCLC, 16 NSCLC and 14 normal lung RNA samples (human) had been purchased from OriGene Technologies. Gene expression analysis was performed using Affymetrix microarrays (Human Exon 1.0 ST Array).

2012-08-25 | E-GEOD-40275 | biostudies-arrayexpress

A plasma miRNA-based classifier for small cell lung cancer diagnosis [NanoString]

Project description:Objectives: Small cell lung cancer (SCLC) is characterized by poor prognosis and challenging diagnosis. Screening in high-risk smokers results in a reduction in lung cancer mortality, however, screening efforts are primarily focused on non-small cell lung cancer (NSCLC). SCLC diagnosis and surveillance remain significant challenges. The aberrant expression of circulating microRNAs (miRNAs/miRs) is reported in many tumors and can provide insights into the pathogenesis of tumor development and progression. Here, we conducted a comprehensive assessment of circulating miRNAs in SCLC with a goal of developing a miRNA-based biomarker classifier to assist in SCLC diagnoses. Materials and Methods: We profiled deregulated circulating cell-free miRNA in the plasma of SCLC patients. We tested selected miRs on a training cohort and created a classifier by integrating miRNA expression and patient clinical data. Finally, we applied the classifier on a validation dataset. Results: We determined that miR-375-3p can discriminate between SCLC and NSCLC patients, and between SCLC and Squamous Cell Carcinoma patients. Moreover, we found that a model comprising miR-375-3p, miR-320b, and miR-144-3p can be integrated with race and age to distinguish metastatic SCLC from a control group. Conclusion: This study proposes a miRNA-based biomarker classifier for SCLC that considers clinical demographics with specific cut offs to inform SCLC diagnosis.

2023-10-31 | GSE240758 | GEO

A plasma miRNA-based classifier for small cell lung cancer diagnosis [miRNA-Seq]

2023-10-31 | GSE240757 | GEO

Expression defined classification of subtypes of diffuse large B cell lymphoma

Project description:Diffuse large B-cell lymphoma (DLBCL) comprises molecularly distinct subgroups such as activated B-cell-like (ABC) and germinal center B-cell-like (GCB) DLBCLs. We previously reported that CD5(+) and CD5(-)CD10(+) DLBCL constitute clinically relevant subgroups. To determine whether these 2 subgroups are related to ABC and GCB DLBCLs, we analyzed the genomic imbalance of 99 cases (36 CD5(+), 19 CD5(-)CD10(+), and 44 CD5(-)CD10(-)) using array-based comparative genomic hybridization (CGH). Forty-six of these cases (22 CD5(+), 9 CD5(-)CD10(+), 1 CD5 (-), and 14 CD5(-)CD10(-)) were subsequently subjected to gene-expression profiling, resulting in their division into 28 ABC (19 CD5(+) and 9 CD5(-)CD10(-)) and 18 GCB (3 CD5(+), 7 CD5(-)CD10(+), and 8 CD5(-)CD10(-)) types. A comparison of genome profiles of distinct subgroups of DLBCL demonstrated that (1) ABC DLBCL is characterized by gain of 3q, 18q, and 19q and loss of 6q and 9p21, and GCB DLBCL is characterized by gain of 1q, 2p, 7q, and 12q; (2) the genomic imbalances characteristic of the CD5(+) and CD5(-)CD10(+) groups were similar to those of the ABC and GCB types, respectively. These findings suggest that CD5(+) and CD5(-)CD10(+) subgroups are included, respectively, in the ABC and GCB types. Finally, when searching for genomic imbalances that affect patients' prognosis, we found that 9p21 loss (p16(INK4a) locus) marks the most aggressive type of DLBCL. Expression profiles in 46 patients with DLBCL and 8 for normal lymph node biopsy samples.

2009-07-10 | E-GEOD-16920 | biostudies-arrayexpress

Molecular Classification and Prediction of Survival in Non-Small-Cell Lung Cancer

Project description:BACKGROUND: Global gene expression analysis provides a comprehensive molecular characterization of non-small cell lung cancer. The aim of this study was to evaluate the feasibility of integrating expression profiling into routine clinical work-up by including minute bronchoscopic biopsies and develop a robust prognostic gene expression signature METHODS: Tissue samples from a series of 41 chemotherapy-naïve non-small cell lung cancer patients and 15 control patients with inflammatory lung diseases were obtained during routine clinical work-up and gene expression profiles were gained using a highly sensitive oligonucleotide array platform (Novachip ; 34'207 transcripts). Gene expression signatures were analyzed by correlation with histological and clinical parameters and validated on independent published datasets and immunohistochemistry. RESULTS: Tumor tissue classification based on the gene expression results was strongly dependent on the proportion of tumor cells present in the biopsies and showed an overall sensitivity of 80% and specificity of 89%. For prognostication we developed a metagene consisting of 13 genes, which was validated on 4 independent published datasets. The robustness of this metagene has been demonstrated by a virtual independence from tumor cells present in the biopsies. Furthermore, vascular endothelial growth factor-beta, one of the key prognostic genes was validated by immunohistochemistry on 508 independent tumor samples. CONCLUSIONS: The proposed strategy of integrating functional genomics into routine clinical work-up allows molecular tumor classification and prediction of survival in patients with non-small cell lung cancer of all stages and is suitable for an integration in the daily clinical practice. Keywords: Gene expression profiling for disease state analysis in lung cancer patients 56 lung biopsies, 4 different Phenotypes: NSCLC-squa., NSCLC-NOS, NSCLC-Adeno, Ctr.-Infl.

2008-04-10 | E-GEOD-11117 | biostudies-arrayexpress

In-depth proteomic analyses reveal unique subtype-specific signatures in small cell lung cancer (part I: cell pellets)

Project description:Small-cell lung cancer (SCLC) represents about 13–15% of all lung cancers and with a five-year survival rate of less than 7%, it remains one of the most lethal forms of malignant diseases. It has a very aggressive course and is characterized by extensive chromosomal rearrangements, high mutation burden, and almost universal inactivation of the tumor suppressor genes TP53 and RB1. Therefore, the vast majority of SCLC patients are diagnosed with extensive-stage disease when surgery is not feasible and the treatment options are mostly limited to cytotoxic chemotherapy (CHT) and radiation. Importantly, targeted therapies for these patients have so far failed, and the success of immunotherapy in non-SCLC (NSCLC) has not been reflected in SCLC. Although SCLC has been formerly considered as a homogeneous disease with a single morphological type, recent advances in SCLC research have led to the development of subtype-specific classifications primarily based on neuroendocrine (NE) features and unique molecular profiles. Here, we investigate the general cell line characteristics on protein level, the relationship between the RNA-based classification and the protein expression profile, and the distinct biological processes specific for each subtype.

2022-10-14 | PXD029805 | Pride

In-depth proteomic analyses reveal unique subtype-specific signatures in small cell lung cancer (part II: cell media)

2022-10-14 | PXD029821 | Pride

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