scholarly journals Differentially Expressed Apoptotic Genes in Early Stage Lung Adenocarcinoma Predicted by Expression Profiling

2003 ◽  
Vol 2 (5) ◽  
pp. 566-571 ◽  
Author(s):  
Sunil Singhal ◽  
Kunjlata M. Amin ◽  
Robert Kruklitis ◽  
M. Blair Marshall ◽  
John C. Kucharczuk ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Expression Profiling ◽  
Early Stage ◽  
Differentially Expressed ◽  
Apoptotic Genes

scholarly journals Alterations in Cell Cycle Genes in Early Stage Lung Adenocarcinoma Identified by Expression Profiling

2003 ◽  
Vol 2 (3) ◽  
pp. 291-298 ◽  
Author(s):  
Sunil Singhal ◽  
Kunjilata Amin ◽  
Robert Kruklitis ◽  
Peter DeLong ◽  
Michael E. Friscia ◽  
...  
Keyword(s):  
Cell Cycle ◽  
Lung Adenocarcinoma ◽  
Expression Profiling ◽  
Early Stage ◽  
Cell Cycle Genes

Abstract 2357: Gene expression profiling robustly predicts the outcome of patients diagnosed with early stage lung adenocarcinoma

2014 ◽  
Author(s):  
Yann Gaston-Mathé ◽  
CHARLES FERTE ◽  
benoit gauthier ◽  
mathilde bateson ◽  
david planchard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Early Stage

Oncogenic activation of the HRR pathway drives RAD54L expression in early stage lung adenocarcinoma.

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. e20037-e20037
Author(s):  
Shaopeng Zheng ◽  
Jin Xia ◽  
Yunfang Yu ◽  
Fanjun Zeng ◽  
Luyu Huang ◽  
...  
Keyword(s):  
Dna Damage ◽  
Survival Rate ◽  
Lung Adenocarcinoma ◽  
Early Stage ◽  
Enrichment Analysis ◽  
Tumor Stage ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Dna Damage And Repair ◽  
T1 Stage

e20037 Background: In recent years, there has been a better understanding of ways to use DNA damage and repair (DDR) mechanisms to improve overall sensitivity and/or overcome resistance to traditional DNA damage treatments. The DDR network is quite complex and highly dynamic with as many as 450 proteins integral to the DNA repair. The current study is to identify the key dysregulated genes and its related pathways especially DDR pathways in early progression of lung adenocarcinoma. Methods: TCGA dataset of lung adenocarcinoma (LUAD) including 59 healthy lung tissues and 517 tumor tissues was utilized to detect the differentially expressed mRNAs and lncRNAs. Gene ontology (GO) analysis was conducted with DAVID, while Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of differentially expressed genes was performed using gene set enrichment analysis (GSEA) methods. Results: 41 lncRNAs and 2,047 mRNAs were screened out to be differentially expressed in LUAD. Besides, 38 lncRNAs and 1,801 mRNAs were found to be differentially expressed in T1 stage LUAD. The homologous recombination repair (HRR) pathway was found to be significantly up-regulated in LUAD, with four genes in this pathway up-regulated. In these genes of HRR pathway, PPP4R4 and RAD54L were recognized to be significantly differential expressed in T1 stage, compared with T2 stage and T3 stage, which were putative biomarkers of early stage LUAD. The survival analysis revealed that the expression of RAD54L was significantly related to the survival rate of patients with tumor of T1 stage. Conclusions: HRR pathway was up-regulated in lung adenocarcinoma, in which the expression of PPP4R4 and RAD54L were found to be tumor stage specific and RAD54L was related with survival rate of T1 stage patients. This study provided a further insight into the mechanism of the progression in early stage lung adenocarcinoma.

scholarly journals Analysis of Circulating microRNA Signatures and Preeclampsia Development

Cells ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1003
Author(s):  
Margarita L. Martinez-Fierro ◽  
Idalia Garza-Veloz
Keyword(s):  
Pregnant Women ◽  
Expression Profiling ◽  
Gene Prediction ◽  
Microrna Expression ◽  
Differentially Expressed ◽  
Control Group ◽  
Case Group ◽  
Circulating Microrna ◽  
Activated T Cells ◽  
Serum Microrna

microRNAs are important regulators of cell processes and have been proposed as potential preeclampsia biomarkers. We evaluated serum microRNA expression profiling to identify microRNAs involved in preeclampsia development. Serum microRNA expression profiling was evaluated at 12, 16, and 20 weeks of gestation (WG), and at the time of preeclampsia diagnosis. Two groups were evaluated using TaqMan low-density array plates: a control group with 18 normotensive pregnant women and a case group with 16 patients who developed preeclampsia during the follow-up period. Fifty-three circulating microRNAs were differentially expressed between groups (p < 0.05). Compared with controls, hsa-miR-628-3p showed the highest relative quantity values (at 12 WG = 7.7 and at 20 WG = 3.45) and the hsa-miRs -151a-3p and -573 remained differentially expressed from 16 to 20 WG (p < 0.05). Signaling pathways including cancer-related, axon guidance, Neurotrophin, GnRH, VEGF, and B/T cell receptor, were most commonly altered. Further target gene prediction revealed that nuclear factor of activated T-cells 5 gene was included among the transcriptional targets of preeclampsia-modulated microRNAs. Specific microRNAs including hsa-miRs -628-3p, -151a-3p, and -573 were differentially expressed in serum of pregnant women before they developed preeclampsia compared with controls and their participation in the preeclampsia development should be considered.

scholarly journals DeepRePath: Identifying the Prognostic Features of Early-Stage Lung Adenocarcinoma Using Multi-Scale Pathology Images and Deep Convolutional Neural Networks

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3308
Author(s):  
Won Sang Shim ◽  
Kwangil Yim ◽  
Tae-Jung Kim ◽  
Yeoun Eun Sung ◽  
Gyeongyun Lee ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Early Stage ◽  
External Validation ◽  
Area Under The Curve ◽  
The Cancer Genome Atlas ◽  
Deep Convolutional Neural Networks ◽  
Prognostic Features ◽  
Multi Scale ◽  
Model Based ◽  
Number Of Patients

The prognosis of patients with lung adenocarcinoma (LUAD), especially early-stage LUAD, is dependent on clinicopathological features. However, its predictive utility is limited. In this study, we developed and trained a DeepRePath model based on a deep convolutional neural network (CNN) using multi-scale pathology images to predict the prognosis of patients with early-stage LUAD. DeepRePath was pre-trained with 1067 hematoxylin and eosin-stained whole-slide images of LUAD from the Cancer Genome Atlas. DeepRePath was further trained and validated using two separate CNNs and multi-scale pathology images of 393 resected lung cancer specimens from patients with stage I and II LUAD. Of the 393 patients, 95 patients developed recurrence after surgical resection. The DeepRePath model showed average area under the curve (AUC) scores of 0.77 and 0.76 in cohort I and cohort II (external validation set), respectively. Owing to low performance, DeepRePath cannot be used as an automated tool in a clinical setting. When gradient-weighted class activation mapping was used, DeepRePath indicated the association between atypical nuclei, discohesive tumor cells, and tumor necrosis in pathology images showing recurrence. Despite the limitations associated with a relatively small number of patients, the DeepRePath model based on CNNs with transfer learning could predict recurrence after the curative resection of early-stage LUAD using multi-scale pathology images.

scholarly journals A circular RNAs dataset landscape reveals potential signatures for the detection and prognosis of early-stage lung adenocarcinoma

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhiying Chen ◽  
Jiahui Wei ◽  
Min Li ◽  
Yongjuan Zhao
Keyword(s):  
Functional Analysis ◽  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Target Genes ◽  
Interaction Analysis ◽  
Early Stage ◽  
Gene Interaction ◽  
Gene Expression Omnibus ◽  
Circular Rnas ◽  
Cerna Network

Abstract Background This study aimed to identify potential circular ribonucleic acid (circRNA) signatures involved in the pathogenesis of early-stage lung adenocarcinoma (LAC). Methods The circRNA sequencing dataset of early-stage LAC was downloaded from the Gene Expression Omnibus database. First, the differentially expressed circRNAs (DEcircRNAs) between tumour and non-tumour tissues were screened. Then, the corresponding miRNAs and their target genes were predicted. In addition, prognosis-related genes were identified using survival analysis and further used to build a network of competitive endogenous RNAs (ceRNAs; DEcircRNA–miRNA–mRNA). Finally, the functional analysis and drug–gene interaction analysis of mRNAs in the ceRNA network was performed. Results A total of 35 DEcircRNAs (30 up-regulated and 5 down-regulated circRNAs) were identified. Moreover, 135 DEcircRNA–miRNA and 674 miRNA–mRNA pairs were predicted. The survival analysis of these target mRNAs revealed that 60 genes were significantly associated with survival outcomes in early-stage LAC. Of these, high levels of PSMA 5 and low levels of NAMPT, CPT 2 and TNFSF11 exhibited favourable prognoses. In addition, the DEcircRNA–miRNA–mRNA network was constructed, containing 5 miRNA–circRNA (hsa_circ_0092283/hsa-miR-762/hsa-miR-4685-5p; hsa_circ_0070610/hsa-let-7a-2-3p/hsa-miR-3622a-3p; hsa_circ_0062682/hsa-miR-4268) and 60 miRNA–mRNA pairs. Functional analysis of the genes in the ceRNA network showed that they were primarily enriched in the Wnt signalling pathway. Moreover, PSMA 5, NAMPT, CPT 2 and TNFSF11 had strong correlations with different drugs. Conclusion Three circRNAs (hsa_circ_0062682, hsa_circ_0092283 and hsa_circ_0070610) might be potential novel targets for the diagnosis of early-stage LAC.

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