Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Relationship between the miRNA Profiles and Oncogene Mutations in Non-Smoker Lung Cancer. Relevance for Lung Cancer Personalized Screenings and Treatments

ABSTRACT: Oncogene mutations may be drivers of the carcinogenesis process. MicroRNA (miRNA) alterations may be adaptive or pathogenic and can have consequences only when mutation in the controlled oncogenes occurs. The aim of this research was to analyze the interplay between miRNA expression and oncogene mutation. A total of 2549 miRNAs were analyzed in cancer tissue—in surrounding normal lung tissue collected from 64 non-smoking patients and in blood plasma. Mutations in 92 hotspots of 22 oncogenes were tested in the lung cancer tissue. MicroRNA alterations were related to the mutations occurring in cancer patients. Conversely, the frequency of mutation occurrence was variable and spanned from the k-ras and p53 mutation detected in 30% of patients to 20% of patients in which no mutation was detected. The prediction of survival at a 3-year follow up did not occur for mutation analysis but was, conversely, well evident for miRNA analysis highlighting a pattern of miRNA distinguishing between survivors and death in patients 3 years before this clinical onset. A signature of six lung cancer specific miRNAs occurring both in the lungs and blood was identified. The obtained results provide evidence that the analysis of both miRNA and oncogene mutations was more informative than the oncogene mutation analysis currently performed in clinical practice.

ORGANISM(S): Homo sapiens

PROVIDER: GSE169587 | GEO | 2021/03/25

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Transcriptomic profiling identifies unique and shared functions of oncogenic KRAS and RIT1

Project description:Aberrant activation of RAS oncogenes is a prevalent event in lung adenocarcinoma, with somatic mutation of KRAS occurring in ~30% of tumors. Recently, we identified somatic mutation of the RAS-family GTPase RIT1 in lung adenocarcinoma, but relatively little is known about the biological pathways regulated by RIT1 and how these relate to the oncogenic KRAS network. Here we present (quantitative proteomic and) transcriptomic profiles from KRAS-mutant and RIT1-mutant isogenic lung epithelial cells and globally characterize the signaling networks regulated by each oncogene.

2020-03-06 | GSE146479 | GEO

Type I interferon signaling pathway enhances immune-checkpoint inhibition in KRAS mutant lung tumors [scRNA-seq]

Project description:Lung cancer is the leading cause of cancer mortality worldwide. KRAS oncogenes are responsible for at least a quarter of lung adenocarcinomas, the main subtype of lung cancer. After four decades of intense research, selective inhibitors of KRAS oncoproteins are finally reaching the clinic. Yet, their effect on overall survival is limited due to the rapid appearance of drug resistance, a likely consequence of the high intratumoral heterogeneity characteristic of these tumors. In this study, we have attempted to identify those functional alterations that result from KRAS oncoprotein expression during the earliest stages of tumor development. Such functional changes are likely to be maintained during the entire process of tumor progression regardless of additional co-occurring mutations. Single-cell RNA sequencing analysis of murine alveolar type 2 cells expressing a resident Kras oncogene revealed impairment of the type I interferon pathway, a feature maintained throughout tumor progression. This alteration was also present in advanced murine and human tumors harboring additional mutations in the p53 or LKB1 tumor suppressors. Restoration of type I interferon (IFN) signaling by IFN-beta or constitutive active stimulator of interferon genes (STING) expression had a profound influence on the tumor microenvironment, switching them from immunologically “cold” to immunologically “hot” tumors. Therefore, enhancement of the type I IFN pathway predisposes KRAS mutant lung tumors to immunotherapy treatments, regardless of co-occurring mutations in p53 or LKB1.

2024-08-12 | GSE274477 | GEO

Type I interferon signaling pathway enhances immune-checkpoint inhibition in KRAS mutant lung tumors [LCM]

2024-08-12 | GSE274351 | GEO

Type I interferon signaling pathway enhances immune-checkpoint inhibition in KRAS mutant lung tumors [cell lines]

2024-08-12 | GSE274352 | GEO

Fully accessible fitness landscape of oncogene negative lung adenocarcinoma

Project description:Multiple genetic mutations are needed for cancer to develop. This is even more pronounced in the case of oncogene negative cancer, where a single dominant oncogenic mutation that can start tumor growth is lacking and substituted by a combination of driver mutations. To shed light on how tumors can subsequently acquire these independent mutations and to test the predictability of cancer evolution, we have characterized the fitness landscapes of a triple-mutant oncogene negative genotype leading to potent lung adenocarcinoma formation. We found that, irrespective of the genetic background, landscapes are surprisingly accessible, where each additional mutation leads to growth advantage and hence prediction of the order of mutations in oncogene negative tumors cancer evolution is expected to be challenging.

2023-01-30 | GSE223678 | GEO

Integrative proteomic and transcriptomic profiling identifies unique and shared functions of oncogenic KRAS and RIT1

Project description:Lo A, Holmes K, Mundt F, Moorthi S, Fung I, Fereshetian S, Watson J, Carr SA, Mertins P, Berger A. Aberrant activation of RAS oncogenes is a prevalent event in lung adenocarcinoma, with somatic mutation of KRAS occurring in ~30% of tumors. Recently, we identified somatic mutation of the RAS-family GTPase RIT1 in lung adenocarcinoma, but relatively little is known about the biological pathways regulated by RIT1 and how these relate to the oncogenic KRAS network. Here we present quantitative proteomic and transcriptomic profiles from KRAS-mutant and RIT1-mutant isogenic lung epithelial cells and globally characterize the signaling networks regulated by each oncogene. We find that both mutant KRAS and mutant RIT1 promote S6 kinase, AKT, and RAF/MEK signaling, and promote epithelial-to-mesenchymal transition and immune evasion via HLA protein loss. However, KRAS and RIT1 diverge in regulation of phosphoproteins including EGFR, USO1, and AHNAK proteins. The majority of the proteome changes are related to altered transcriptional regulation, but a small subset of proteins are differentially regulated at the post-transcriptional level, including intermediate filament proteins, metallothioneins, and MHC Class I proteins, which are profoundly suppressed by oncogenic KRAS and RIT1 variants. These data provide the first global, unbiased characterization of oncogenic RIT1 network and identify the shared and divergent functions of oncogenic RIT1 and KRAS GTPases in lung cancer.

2020-04-03 | MSV000085225 | MassIVE

Sun2018 - Instantaneous mutation rate in cancer initiation and progression

Project description:Background Cancer is one of the leading causes for the morbidity and mortality worldwide. Although substantial studies have been conducted theoretically and experimentally in recent years, it is still a challenge to explore the mechanisms of cancer initiation and progression. The investigation for these problems is very important for the diagnosis of cancer diseases and development of treatment schemes. Results To accurately describe the process of cancer initiation, we propose a new concept of gene initial mutation rate based on our recently designed mathematical model using the non-constant mutation rate. Unlike the widely-used average gene mutation rate that depends on the number of mutations, the gene initial mutation rate can be used to describe the initiation process of a single patient. In addition, we propose the instantaneous tumour doubling time that is a continuous function of time based on the non-constant mutation rate. Our proposed concepts are supported by the clinic data of seven patients with advanced pancreatic cancer. The regression results suggest that, compared with the average mutation rate, the estimated initial mutation rate has a larger value of correlation coefficient with the patient survival time. We also provide the estimated tumour size of these seven patients over time. Conclusions The proposed concepts can be used to describe the cancer initiation and progression for different patients more accurately. Since a quantitative understanding of cancer progression is important for clinical treatment, our proposed model and calculated results may provide insights into the development of treatment schemes and also have other clinic implications.

2024-09-02 | BIOMD0000000915 | BioModels

Proteomics and phosphoproteomics on NB1 and IMR32 neuroblastoma cells stimulated with ALAKAL2

Project description:High-risk neuroblastoma (NB) is notoriously difficult to treat and is responsible for a disproportionate number of childhood deaths due to cancer. One long accepted indicator of high-risk NB and poor prognosis is amplification of the neural MYC (MYCN) oncogene, which is currently therapeutically intractable in this patient population. The identification of Anaplastic Lymphoma Kinase (ALK) as an oncogene in NB raised the possibility of using ALK tyrosine kinase inhibitors (TKIs) in the treatment of NB patients who harbor activating ALK mutations. The number of ALK-positive NB patients on primary diagnosis is in the range of 8-10%, a figure that increases substantially in the relapsed patient population. ALK signaling is activated by the ALKAL2 ligand located on the distal portion of chromosome 2, along with the ALK receptor and MYCN loci, in the ‘2p gain’ region that has been associated with NB. The question of whether dysregulation of ALK ligand may also play a role in NB has not been addressed, although notably, one of the first oncogenes described was the v-sis oncogene that shares more than 90% homology with the PDGF ligand. Therefore, we tested whether ALKAL ligand was able to potentiate NB progression in the absence of ALK mutation. We show here that overexpression of ALKAL2 is sufficient to drive rapid onset and penetrant Th-MYCN driven NB in the absence of ALK mutation, and that these tumours are sensitive to ALK TKI therapy. These results suggest that additional NB patients, such as those exhibiting 2p gain, may also benefit from ALK TKI based therapeutic intervention.

2020-11-25 | PXD021792 | Pride

Genomic profiling identifies TITF1 as a lineage-specific oncogene amplified in lung cancer

Project description:Lung cancer is a leading cause of cancer death, where the amplification of oncogenes contributes to tumorigenesis. Genomic profiling of 128 lung cancer cell lines and tumors revealed frequent focal DNA amplification at cytoband 14q13.3, a locus not amplified in other tumor types. The smallest region of recurrent amplification spanned the homeobox transcription factor TITF1 (also known as NKX2-1), previously linked to normal lung development and function. When amplified, TITF1 exhibited increased expression at both the RNA and protein level. siRNA-mediated knockdown of TITF1 in lung cancer cell lines with amplification led to reduced cell proliferation, manifested by both decreased cell-cycle progression and increased apoptosis. Our findings indicate that TITF1 amplification and overexpression contribute to lung cancer cell proliferation rates and survival, and implicate TITF1 as a lineage-specific oncogene in lung cancer. This SuperSeries is composed of the following subset Series: GSE9994: Genomic profiling identifies TITF1 as a lineage-specific oncogene amplified in lung cancer: Expression Arrays GSE10025: Genomic profiling identifies TITF1 as a lineage-specific oncogene amplified in lung cancer: aCGH Arrays Keywords: SuperSeries Refer to individual Series

2008-02-29 | E-GEOD-9995 | biostudies-arrayexpress

KRAS mutation-associated gene expression, p53 and STK11 mutations, proliferation and immune surveillance in lung adenocarcinoma

Project description:While mutations in the KRAS oncogene are amongst the most prevalent in human cancer, there are few successful treatments to target these tumors. It is also likely that heterogeneity in KRAS-mutant tumor biology significantly contributes to the response to therapy. We hypothesized that presence of commonly co-occurring mutations in STK11 and TP53 tumor suppressors may represent a significant source of heterogeneity in KRAS-mutant tumors. To address this, we utilized a large cohort of resected tumors from 442 lung adenocarcinoma patients with data including annotation of prevalent driver mutations (KRAS, EGFR) and tumor suppressor mutations (STK11 and TP53), microarray-based gene expression and clinical covariates including overall survival (OS). Specifically, we determined impact of STK11 and TP53 mutations on a new KRAS mutation-associated gene expression signature as well as previously defined signatures of tumor cell proliferation and immune surveillance responses. Interestingly, STK11, but not TP53 mutations, were associated with highly elevated expression of KRAS mutation-associated genes. Mutations in TP53 and STK11 also impacted tumor biology regardless of KRAS status, with TP53 strongly associated with enhanced proliferation and STK11 with suppression of immune surveillance. These findings illustrate the remarkably distinct ways through which tumor suppressor mutations may contribute to heterogeneity in KRAS-mutant tumor biology. In addition, these studies point to novel associations between gene mutations and immune surveillance that could impact the response to immunotherapy.

2015-10-21 | GSE72094 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data