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A circulating risk score, based on combination of exo-miR130a-3p and fibrinopeptide A, as predictive biomarker of relapse in early stage non-small cell lung cancer patients [Nanostring]

ABSTRACT: A circulating risk score, based on combination of exo-miR130a-3p and fibrinopeptide A, as predictive biomarker of relapse in early stage non-small cell lung cancer patients [Nanostring]

PROVIDER: PRJNA817571 | ENA |

REPOSITORIES: ENA

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A circulating risk score, based on combination of exo-miR130a-3p and fibrinopeptide A, as predictive biomarker of relapse in early stage non-small cell lung cancer patients [Nanostring]

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 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.

2022-05-01 | GSE198957 | GEO

A circulating risk score, based on combination of exo-miR130a-3p and fibrinopeptide A, as predictive biomarker of relapse in early stage non-small cell lung cancer patients [miRNA]

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.

2022-05-01 | GSE198958 | GEO

A circulating risk score, based on combination of exo-miR130a-3p and fibrinopeptide A, as predictive biomarker of relapse in early stage non-small cell lung cancer patients.

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

A circulating risk score, based on combination of exo-miR130a-3p and fibrinopeptide A, as predictive biomarker of relapse in early stage non-small cell lung cancer patients

Project description:A circulating risk score, based on combination of exo-miR130a-3p and fibrinopeptide A, as predictive biomarker of relapse in early stage non-small cell lung cancer patients

| PRJNA817569 | ENA

A circulating risk score, based on combination of exo-miR130a-3p and fibrinopeptide A, as predictive biomarker of relapse in early stage non-small cell lung cancer patients [miRNA]

Project description:A circulating risk score, based on combination of exo-miR130a-3p and fibrinopeptide A, as predictive biomarker of relapse in early stage non-small cell lung cancer patients [miRNA]

| PRJNA817572 | ENA

A 17-Gene Stemness Score for Rapid Identification of High-Risk AML Patients [NanoString]

Project description:In AML, most patients are initiated on standard chemotherapy and afterwards assigned to a post-remission strategy based on genetically-defined risk categories. However, outcomes remain heterogeneous, indicating the need for novel biomarker tests that can rapidly and accurately identify high-risk patients, allowing better stratification of both induction and post-remission therapy. As patient outcomes are linked to leukemia stem cell (LSC) properties that confer therapy resistance and drive relapse, LSC-based biomarkers may be highly informative. We tested 227 CD34/CD38 cell fractions from 78 AML patients for LSC activity in xenotransplantation assays. Comparison of microarray-based gene expression (GE) profiles between 138 LSC+ and 89 LSC? fractions identified 104 differentially-expressed LSC-specific genes. To obtain prognostic signatures, we performed statistical regression analysis of LSC GE against patient outcome using a training cohort of 495 AML patients treated with curative intent. A score calculated as the weighted sum of expression of 17 LSC signature genes (LSC17) was strongly associated with survival in 4 independent datasets (716 AML cases) spanning all risk categories in multi-variate analysis; an optimized 3-gene sub-score (LSC3) was prognostic in favorable risk subsets. These scores were robust across GE technology platforms, including the clinically serviceable NanoString system (LSC17: HR=2.73, P<0.0001; LSC3: HR=6.3, P<0.02). The LSC17 and LSC3 scores provide rapid and accurate identification of high-risk patients for whom conventional chemotherapy is non-curative. These scores will enable evaluation in clinical trials of whether such patients may benefit from novel and/or more intensified therapies during induction or in the post-remission setting.

2016-12-02 | GSE76004 | GEO

A Circulating Risk Score, Based on Combined Expression of Exo-miR-130a-3p and Fibrinopeptide A, as Predictive Biomarker of Relapse in Resectable Non-Small Cell Lung Cancer Patients.

Project description:To date, the 5-year overall survival rate of 60% for early-stage non-small cell lung cancer (NSCLC) is still unsatisfactory. Therefore, reliable prognostic factors are needed. Growing evidence shows that cancer progression may depend on an interconnection between cancer cells and the surrounding tumor microenvironment; hence, circulating molecules may represent promising markers of cancer recurrence. In order to identify a prognostic score, we performed in-depth high-throughput analyses of plasma circulating markers, including exosomal microRNAs (Exo-miR) and peptides, in 67 radically resected NSCLCs. The miRnome profile selected the Exo-miR-130a-3p as the most overexpressed in relapsed patients. Peptidome analysis identified four progressively more degraded forms of fibrinopeptide A (FpA), which were depleted in progressing patients. Notably, stepwise Cox regression analysis selected Exo-miR-130a-3p and the greatest FpA (2-16) to build a score predictive of recurrence, where high-risk patients had 18 months of median disease-free survival. Moreover, in vitro transfections showed that higher levels of miR-130a-3p lead to a deregulation of pathways involved in metastasis and angiogenesis, including the coagulation process and metalloprotease increase which might be linked to FpA reduction. In conclusion, by integrating circulating markers, the identified risk score may help clinicians predict early-stage NSCLC patients who are more likely to relapse after primary surgery.

| S-EPMC9317031 | biostudies-literature

A circulating risk score, based on combination of exo-miR130a-3p and fibrinopeptide A, as predictive biomarker of relapse in early stage non-small cell lung cancer patients

Project description:This SuperSeries is composed of the SubSeries listed below.

2022-05-01 | GSE198959 | GEO

Predictive computational obesity risk framework through integration of gene expression profiles and genetic risk score.

Project description:We aimed to predict obesity risk with genetic data, specifically, obesity-associated gene expression profiles. Genetic risk score was computed. The genetic risk score was significantly correlated with BMI when an optimization algorithm was used. Linear regression and built support vector machine models predicted obesity risk using gene expression profiles and the genetic risk score with a new mathematical method.

2018-01-25 | GSE109597 | GEO

Differentiation Score and Intrinsic Subtype Predict Breast Cancer Organ of Relapse

Project description:The ability to predict metastatic potential is of clinical and biological importance. Numerous metastasis/relapse predictors exist for breast cancer patients; however, what is less well established is whether predicting metastasis to specific organs sites is feasible. In this study we sought to determine: 1) the degree to which gene signatures vary across tumors and their metastases, 2) if genomic intrinsic subtypes associate with particular organs of relapse, and 3) if other genomic signatures can predict spread to specific organs. Using a gene expression microarray data set of >1000 breast tumors and metastases, we observed that >90% of 298 gene signatures were similarly expressed between matched pairs of breast tumors and metastases; those most altered were reflective of cell types including fibroblasts and immune cells. Significant associations were identified between tumor subtypes and organ of first relapse. Among these, HER2-enriched tumors were significantly associated with liver, and Basal-like and Claudin-low tumors with brain and lung. Correspondingly, previously published brain and lung metastasis signatures, along with embryonic stem cell and tumor initiating cell signatures, were also associated with Basal-like and Claudin-low subtypes. These signatures strongly correlated with low Differentiation Scores (DS) and, to a lesser extent, high proliferation. Interestingly, within Basal-like and Claudin-low tumors, low DS further predicted for brain and lung metastases. In total, intrinsic subtype and DS provide clinically useful information that identifies the distant organ sites that should be most closely monitored for signs of disease recurrence. 414 samples profiled on Agilent microarrays.

2011-06-20 | E-GEOD-26338 | biostudies-arrayexpress

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