Ontology highlight
ABSTRACT:
PROVIDER: PRJNA740302 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14893100.fastq.gz | Fastqsanger.gz | |||
| SRR14893101.fastq.gz | Fastqsanger.gz | |||
| SRR14893102.fastq.gz | Fastqsanger.gz | |||
| SRR14893103_1.fastq.gz | Fastqsanger.gz | |||
| SRR14893103_2.fastq.gz | Fastqsanger.gz |
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Project description:The epigenome of plasma cell-free DNA (cfDNA) has demonstrated promise as both a prognostic and predictive cancer biomarker in liquid biopsies. Currently, it remains unknown whether and why cfDNA 5-hydroxymethylcytosine (5hmC) can identify disease state for non-small cell lung cancer (NSCLC). We profiled 5-hydroxymethylomes using the plasma cfDNA of 302 EGFR-mutant NSCLC patients with different disease states. We found NSCLCs were epigenetically heterogeneous among individuals, especially for cfDNA 5hmC on gene EGFR. The diversity of age, sex, race, smoking status, EGFR-mutation of patients increased the epigenetic heterogeneity of NSCLC, however, only smoking status shaped disease state-associated cfDNA 5hmC. More importantly, disease state-dependent and patients’ characteristics-independent cfDNA 5hmC can be linked to lung function and regulatory elements in human lung cells. Interestingly, although 5-hydroxymethylome heterogeneity of plasma cfDNA among NSCLC patients were detected substantially, cfDNA-5hmC-based machine learning model can accurately predict different disease state in NSCLC.
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Project description:Background: Current histopathological methods are inadequate for predicting outcome and recurrence in patients with non-small cell lung carcinoma (NSCLC) after surgery. In this study, we investigated the use of gene expression signatures to predict outcome and metastasis in lung cancer patients. Methods: Gene expression was studied by microarray and the real-time reverse transcriptase polymerase chain reaction (RT-PCR) in normal and lung tumor tissue of 188 NSCLC patients who underwent surgical resection. The 5 cancer-related genes and 1 reference gene expression levels measureed by real-time RT-PCR were used in a prospectively defined algorithm to determine the risk for each patient. Finally, we used an independent cohort to verify the 5 gene-based predictive model derived from decision tree analysis. Results: The 5 gene-based decision tree model was able to predict the prognosis. The recurrence rate at 36 months was 53% in the low-risk group versus 83% in the high-risk group (P=0.002). The 5 gene-based model could also predict overall survival (P<0.001). In multivariate analysis, the decision tree model predicted that high-low dichotomy and stage were both significant for recurrence. In addition, it could also predict metastasis and survival of NSCLC patients within the stage I-II subgroups. A similar result was found using an independent cohort of NSCLC patients. The high-risk patients had a significantly poorer overall survival than the low-risk patients (P=0.005). We also found distinct gene signatures which could distinguish between NSCLC, and normal tissue and histology subtypes. Conclusions: A gene expression signature can predict metastasis and survival of NSCLC patients. Keywords: Survival and metastasis analysis
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Project description:Early-stage epithelial ovarian cancer (eEOC) patients have a generally favorable prognosis but heterogeneous behavior at recurrence. Accurate prediction of the risk of relapse is still a major concern, essentially to avoid overtreatment. We have identified a robust miRNA-based signature named MiROvaR able to predict early disease recurrence in case materials of mostly advanced-stage EOC patients. We challenged MiROvaR in the eEOC sub-setting (stage IA-IIB) and it proved to accurately classify eEOC patients according to their risk of relapse.
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Project description:To date, the 5-year overall survival of early-stage non-small cell lung cancer (NSCLC) is still unsatisfactory at 59.8%. Therefore, reliable prognostic factors are needed. Growing evidence shows that cancer progression may depend on a double interconnection between cancer cells and the surrounding tumor microenvironment; hence, circulating molecules may represent promising markers of cancer recurrence. Here, we performed in-depth analysis of circolome-derived markers, including Exo-miRnome and peptidome in 67 radically resected NSCLCs, to identify a prognostic score. The miRnome profile selected exo-miR130a-3p as the most overexpressed in patients with relapse. Peptidome analysis identified 4 progressively more degraded forms of fibrinopeptide A (fpA) in progressing patients. Notably, the combination of exo-miR130a-3p and the greatest fpA (2-16) built a score where high-risk patients had 24 months of disease-free survival. Moreover, in vitro transfections showed that higher levels of exo-miR-130a-3p lead to a deregulation of some pathways involved in metastasis, in angiogenesis, such as in coagulation which could be linked to the FpA reduction. In conclusion, the identified risk score integrating circulating markers can help clinicians predict early-stage NSCLC patients who are more likely to relapse after initial surgery.
2022-03-16 | MSV000089072 | MassIVE
Project description:To date, the 5-year overall survival of early stage non-small cell lung cancer (NSCLC) is still unsatisfactory at 59.8%. Therefore, reliable prognostic factors are needed. Growing evidence shows that cancer progression may depend on a double interconnection between cancer cells and the surrounding tumor microenvironment, and circulating molecules may represent promising markers of cancer recurrence. Here, we performed in-depth analysis of circolome-derived markers, including Exo-miRnome and peptidome in 67 radically resected NSCLCs, to identify a prognostic score. The miRnome profile selected exo-miR130a-3p as the most overexpressed in patients with relapse. Peptidome analysis identified 4 fibrinopeptide A (fpA), which were depleted in progressing patients. Notably, the combination of exo-miR130a-3p and the greatest fpA (2-16) built a score where high-risk patients had 24 months of disease-free survival. Moreover, in vitro transfections showed that higher levels of exo-miR-130a-3p lead to a deregulation of some pathways involved in metastasis, in angiogenesis, such as in coagulation. In conclusion, the identified risk score integrating circulating markers can help clinicians predict early-stage NSCLC patients who are more likely to relapse after initial surgery.
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Project description:Background Despite improvement in diagnostic and therapeutic techniques, a significant percentage of patients with early stage laryngeal cancer still recur after treatment. Gene expression models prognostic of recurrence risk could suggest which patients with early stage laryngeal cancer would be more appropriate for testing adjuvant strategies. Patients and Methods Expression profiling using whole genome DASL arrays was performed on 56 formalin-fixed paraffin-embedded tumor samples of patients with early stage laryngeal cancer, treated with surgery or radiation therapy. We split the samples into a training set and a validation set. Using the supervised principal components survival analysis in the first cohort, we identified multiple gene expression profiles that predict the risk of recurrence. These profiles were then validated in the second independent cohort. Results Gene models comprising different number of genes (40-100) identified a subgroup of patients who were at high risk of recurrence. Of these, the best prognostic model distinguished between a high- and a low-risk group (median DFS: 92 and 123 months, log rank p<0.005, permutation p<0.05), Hazard Ratio (HR): 8.51 (95% CI, 1.01 to 71.77; p<0.05). These models performed similarly in the independent cohort of our study (median DFS: 38 vs 161 months, log rank p=0.018), HR=5.19 (95% CI, 1.14 to 23.57; p<0.05). Conclusions We have identified gene expression prognostic models which can refine the estimation of a patient’s risk of recurrence. These findings, if further validated, should aid in patient stratification for testing adjuvant treatment strategies. 56 patients with early stage laryngeal cancer were included in this study.
2011-11-26 | E-GEOD-25727 | biostudies-arrayexpress
Project description:Postoperative recurrence is the main cause of poor prognosis in early stage lung adenocarcinoma (LUAD). Factors that can predict recurrence risk are critically needed.we designed a screening procedure based on gene profile data.The differentially expressed genes (DEGs) between patients with recurrence-free survival (RFS)<1 year and RFS>3 years were found.Cox proportional hazards model, IHC and Kaplan-Meier survival analysis were preformed to validate these biomarkers in TCGA and Daping validation sets.
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