Search results for "Key genes"

showing 5 items of 5 documents

R-Score: A New Parameter to Assess the Quality of Variants’ Calls Assessed by NGS Using Liquid Biopsies

2021

Next-generation sequencing (NGS) has enabled a deeper knowledge of the molecular landscape in non-small cell lung cancer (NSCLC), identifying a growing number of targetable molecular alterations in key genes. However, NGS profiling of liquid biopsies risk for false positive and false negative calls and parameters assessing the quality of NGS calls remains lacking. In this study, we have evaluated the positive percent agreement (PPA) between NGS and digital PCR calls when assessing EGFR mutation status using 85 plasma samples from 82 EGFR-positive NSCLC patients. According to our data, variant allele fraction (VAF) was significantly lower in discordant calls and the median of the absolute va…

Oncologymedicine.medical_specialtyKey genesQH301-705.5BiologyGeneral Biochemistry Genetics and Molecular BiologyArticle03 medical and health sciences0302 clinical medicineInternal medicinemedicineDigital polymerase chain reactionBiology (General)Liquid biopsy030304 developmental biology0303 health sciencesGeneral Immunology and MicrobiologyPlasma samplesliquid biopsyvariant callingVariant allelectDNArespiratory systemfiltering3. Good healthEgfr mutation030220 oncology & carcinogenesisNGSVAFNon small cellLinear correlationGeneral Agricultural and Biological SciencesBiology
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Targeting breast cancer initiating cells: advances in breast cancer research and therapy

2014

Over the past 10 years there have been significant advances in our understanding of breast cancer and the important roles that breast cancer initiating cells (CICs) play in the development and resistance of breast cancer. Breast CICs endowed with self-renewing and tumor-initiating capacities are believed to be responsible for the relapses which often occur after various breast cancer therapies. In this review, we will summarize some of the key developments in breast CICs which will include discussion of some of the key genes implicated: estrogen receptor (. ER), HER2, BRCA1, TP53, PIK3CA, RB, P16INK1 and various miRs as well some drugs which are showing promise in targeting CICs. In additio…

OncologyCancer Researchmedicine.medical_specialtyKey genesmedicine.medical_treatmentEstrogen receptorAntineoplastic AgentsBreast NeoplasmsMiRCancer stem cells; ER; HER2; Hormonal therapy; MiRs; Targeted therapy; Therapy resistanceTargeted therapyMiRsTargeted therapyBreast cancerCancer stem cellInternal medicineHER2GeneticsmedicineHumansTreatment resistanceskin and connective tissue diseasesMolecular Biologybusiness.industryCancer stem cellsTherapy resistanceProteinsmedicine.diseaseClinical researchERNeoplastic Stem CellsMolecular MedicineHormonal therapyFemalebusinessHormonal therapyCancer stem cells HER2 ER miRs Targeted therapy Hormonal therapy Therapy resistance
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Combined omics approaches reveal distinct responses between light and heavy rare earth elements in Saccharomyces cerevisiae

2022

International audience; The rapid development of green energy sources and new medical technologies contributes to the increased exploitation of rare earth elements (REEs). They can be subdivided into light (LREEs) and heavy (HREEs) REEs. Mining, industrial processing, and end-use practices of REEs has led to elevated environmental concentrations and raises concerns about their toxicity to organisms and their impact on ecosystems. REE toxicity has been reported, but its precise underlying molecular effects have not been well described. Here, transcriptomic and proteomic approaches were combined to decipher the molecular responses of the model organism Saccharomyces cerevisiae to La (LREE) an…

Environmental EngineeringlanthanumKey genesHealth Toxicology and Mutagenesis[SDV]Life Sciences [q-bio]ved/biology.organism_classification_rank.speciesSaccharomyces cerevisiaeRare earthSaccharomyces cerevisiaeComputational biology010501 environmental sciences01 natural sciencesMiningTranscriptome03 medical and health sciencesHuman healthtranscriptomicsproteomicsLanthanidesHumansEnvironmental ChemistryModel organismWaste Management and DisposalEcosystem030304 developmental biology0105 earth and related environmental sciences0303 health sciencesbiologyved/biologyChemistryytterbiumbiology.organism_classificationPollutionREEs13. Climate action[SDE]Environmental Sciencescell wallMetals Rare EarthSignalling pathways
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SF3B1 modulators affect key genes in metastasis and drug influx: a new approach to fight pancreatic cancer chemoresistance.

2021

Aim: Because mutations of splicing factor 3B subunit-1 (SF3B1) have been identified in 4% of pancreatic ductal adenocarcinoma (PDAC) patients, we investigated the activity of new potential inhibitors of SF3B1 in combination with gemcitabine, one of the standard drugs, in PDAC cell lines. Methods: One imidazo[2,1-b][1,3,4]thiadiazole derivative (IS1) and three indole derivatives (IS2, IS3 and IS4), selected by virtual screening from an in-house library, were evaluated by the sulforhodamine-B and wound healing assay for their cytotoxic and antimigratory activity in the PDAC cells SUIT-2, Hs766t and Panc05.04, the latter harbouring the SF3B1 mutations. The effects on the splicing pattern of pr…

DrugPancreatic ductal adenocarcinomaKey genesbusiness.industrymedia_common.quotation_subjectPancreatic ductal adenocarcinoma gemcitabine indole derivatives anti-proliferative activity antimigratory activity SF3B1 RON hENT1Affect (psychology)medicine.diseaseGemcitabineMetastasisPancreatic cancerCancer researchmedicinebusinessmedia_commonmedicine.drugCancer drug resistance (Alhambra, Calif.)
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Ranking Series of Cancer-Related Gene Expression Data by Means of the Superposing Significant Interaction Rules Method

2020

The Superposing Significant Interaction Rules (SSIR) method is a combinatorial procedure that deals with symbolic descriptors of samples. It is able to rank the series of samples when those items are classified into two classes. The method selects preferential descriptors and, with them, generates rules that make up the rank by means of a simple voting procedure. Here, two application examples are provided. In both cases, binary or multilevel strings encoding gene expressions are considered as descriptors. It is shown how the SSIR procedure is useful for ranking the series of patient transcription data to diagnose two types of cancer (leukemia and prostate cancer) obtaining Area Under Recei…

Male0301 basic medicineKey genesComputer sciencelcsh:QR1-502Binary numberBiochemistrylcsh:MicrobiologyArticlePattern Recognition AutomatedStructure-Activity Relationship03 medical and health sciencesBig data0302 clinical medicinerankingData MiningHumanscancergene expressionsRelated geneCàncerMolecular BiologyOligonucleotide Array Sequence AnalysisCancerPròstata -- CàncerLeukemiaReceiver operating characteristicbusiness.industryGene Expression ProfilingleukemiaProstatic NeoplasmsLeucèmiaDades massivesPattern recognitionprostate cancerExpressió gènicaSSIR method030104 developmental biologyROC Curvemultilevel fingerprintsExpression dataData Interpretation Statistical030220 oncology & carcinogenesisProstate -- CancerArtificial intelligenceGene expressionbusinessAlgorithms
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