Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA355234 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Expression of 752 microRNAs in 77 cases of stage I non-small cell lung cancer was examined using a locked nucleic acid microarray to quantify microRNA changes associated with recurrence of the disease after surgical resection.
2010-04-07 | E-TABM-727 | biostudies-arrayexpress
Project description:This dataset encompassing the profiles of 150 lung cancer tumors was developed to serve as test dataset in the SBV IMPROVER Diagnostic Signature Challenge (sbvimprover.com). The aim of this subchallenge was to verify that it is possible to extract a robust diagnostic signature from gene expression data that can identify stages of different types of lung cancer. Participants were asked to develop and submit a classifier that can stratify lung cancer patients in one of four groups M-bM-^@M-^S Stage 1 of Adenocarcinoma (AC Stage 1), Stage 2 of Adenocarcinoma (AC Stage 2), Stage 1 of Squamous cell carcinoma (SCC Stage 1) or Stage 2 of Squamous cell carcinoma (SCC Stage 2). The classifier could be built by using any publicly available gene expression data with related histopathological information and was tested on the independent dataset described here. 150 non-small cell lung cancer tumors (adenocarcinoma, AC and squamous cell carcinoma, SCC) of stages I and II were collected by surgical resection from patients who have provided consent. Adenosquamous and large cell tumor samples were excluded. The number of smokers and non-smokers was balanced: there were 41 AC1 (adenocarcinoma stage I), 36 AC2, 34 SCC1, and 39 SCC2 samples. Study pathologists at each of the seven sites (Lebanon, Republic of Moldova, Romania, Russian Federation, Ukraine, Vietnam and United States of America) reviewed both the tumor permanent sections and the frozen sections of the samples. Clinical information was also collected about tumor staging, history of prior cancers, lymph node involvement by lymph node sampling/dissection, smoking history, age, gender.
2013-10-18 | E-GEOD-43580 | biostudies-arrayexpress
Project description:Background:; One of the main fields of lung cancer research is identifying patients who are at high risk of post-resection recurrence. Individual recurrence risk evaluation by accurate but simple and reproducible method is needed for the clinical practice. Results:; The log-rank test and further selection by our criteria of assayability generated 87 genes from microarray data with significant level 5%. Of these, by PTQ-PCR, the expression of most significant 18 genes was obtained. Using these gene expression information and clinical parameters, by stepwise variable selection method, the recurrence prediction model, which composed of 6 genes (CALB1, MMP7, SLC1A7, GSTA1, CCL19, IFI44) and pStage and cell differentiation, were developed. Validation into the two independent cohorts showed good results of the proposed model (p=0.0314, 0.0305, respectively). The predicted median recurrence-free survival times for each patient were reflected real ones well. Conclusions:; Our method of individualized recurrence risk prediction is accurate, technically simple and reproducible to be used in clinical practice. Therefore, it would be useful in customizing the lung cancer management strategies. Experiment Overall Design: Methods: Experiment Overall Design: At first, we selected the statistically significant genes from the analysis of time-to-recurrence and censoring information from 138 whole-genome wide microarray data. Then, we further reduced the number of genes which could be reliably reproducible by RTQ-PCR. With these assayable genes and clinical parameters, construction of recurrence prediction model by Cox proportional hazard regression was done. After validation into two independent cohorts (n=59 and n=56), the model was transformed into recurrence prediction for the each patient.
2008-06-17 | E-GEOD-8894 | biostudies-arrayexpress
Project description:Samples were taken from colorectal cancers in surgically resected specimens in 36 colorectal cancer patients. The expression profiles were determined using Affymetrix Human Genome U133 Plus 2.0 arrays. Comparison between the sample groups allow to identify a set of discriminating genes that can be used for molecular markers for predicting recurrence. Keywords: repeat Thirty-six colorectal cancer patients who had undergone surgical resection of colorectal cancer were studied. In all patients, curative resection was performed and no patients had any distant metastasis at the time of operation (stage III patients). Among the 36 patients, 23 patients did not develop recurrence. On the other hand, 13 patients developed rucurrence such as liver metastases, lung metastases and distant lymph node metastases. The median follow up period was 4.5 years.
2010-08-31 | E-GEOD-4526 | biostudies-arrayexpress
Project description:Surgical resection is the major clinical intervention for Stage III colorectal cancer (CRC) currently. However, as much as 30.8% of the patients who had ever taken curative resection came out of recurrence eventually. Therefore, to facilitate formulating effective treatment plans, there is an intense demand for Stage III CRC post-surgical prognostic biomarkers. In this study, we identified total 146 differentially expressed proteins (DEPs) associated with poor prognosis in Stage III CRC patients with TMT-based quantitative mass spectrometry (MS). In these DEPs, the protein expression level of R-Ras and Transgelin were tested with immunohistochemistry (IHC) of 192 individual specimens. Further Kaplan-Meier analysis revealed that the level of R-Ras and Transgelin is associated with patients’ 5-year overall survival (OS) and disease-free survival (DFS) significantly, and multivariate Cox-regression analyses revealed that R-Ras and Transgelin are independent prognostic factors for OS and DFS respectively. In conclusion, our study presents that R-Ras and Transgelin are potential post-surgical prognostic biomarkers of Stage III CRC.
2016-06-20 | PXD002903 | Pride
Project description:The objective is to establish robust transcriptional regulation differences between squamous cell carcinoma (SCC) and adenocarcinoma (ADC) by studying miRNA and concurrent transcriptional profiles. This series represents the miRNA profiles only (not mRNA). The related mRNA data is in Series GSE42998. The present study was performed in 44 tumour samples following surgical resection for clinical early stage NSCLC (20 lung adenocarcinoma and 24 squamous cell lung cancer). Mature human miRNA expression was detected and quantified using the TaqMan® Low Density Arrays (TLDA). The Human MicroRNA Card Set v2.0 array is a two card set containing a total of 384 TaqMan® MicroRNA Assays per card to enable accurate quantification of 667 human microRNAs, all catalogued in the miRBase database.Expression of target miRNAs was normalized in relation to the expression of RNU48. Cycle threshold (Ct) values were calculated using the SDS software v.2.3 using automatic baseline settings and a threshold of 0.2. Relative quantification of miRNA expression was calculated by the 2−ΔCt method (Applied Biosystems user bulletin no. 2 (P/N 4303859)).
2013-04-15 | E-GEOD-43000 | biostudies-arrayexpress
Project description:Microscopic vascular invasion (VI) predicts recurrence and benefit from lobectomy in stage I lung adenocarcinoma (LUAD) but cannot be accurately predicted before surgery. Thus, biomarkers that identify this aggressive tumor subset are needed. Here, we show that VI in stage I LUAD is associated with reproducible gene expression programs detectable beyond the invasive focus. Using bulk RNA sequencing of 162 resected tumors and spatial transcriptomics in a subset, we identify and characterize a VI-associated gene signature. A predictor derived from this signature is associated with VI and recurrence in an independent validation cohort and is robust to intra-tumor heterogeneity in multiregional sampling data. In a cohort of pre-surgical biopsies, predictor scores correlate with matched resections and show promising discrimination of VI. These findings indicate that VI-associated transcriptional changes extend across the tumor and are detectable in limited biopsy material, supporting further validation for preoperative risk stratification in stage I LUAD.
2026-01-26 | GSE273528 | GEO
Project description:Microscopic vascular invasion (VI) predicts recurrence and benefit from lobectomy in stage I lung adenocarcinoma (LUAD) but cannot be accurately predicted before surgery. Thus, biomarkers that identify this aggressive tumor subset are needed. Here, we show that VI in stage I LUAD is associated with reproducible gene expression programs detectable beyond the invasive focus. Using bulk RNA sequencing of 162 resected tumors and spatial transcriptomics in a subset, we identify and characterize a VI-associated gene signature. A predictor derived from this signature is associated with VI and recurrence in an independent validation cohort and is robust to intra-tumor heterogeneity in multiregional sampling data. In a cohort of pre-surgical biopsies, predictor scores correlate with matched resections and show promising discrimination of VI. These findings indicate that VI-associated transcriptional changes extend across the tumor and are detectable in limited biopsy material, supporting further validation for preoperative risk stratification in stage I LUAD.
2026-01-26 | GSE273378 | GEO
Project description:Microscopic vascular invasion (VI) predicts recurrence and benefit from lobectomy in stage I lung adenocarcinoma (LUAD) but cannot be accurately predicted before surgery. Thus, biomarkers that identify this aggressive tumor subset are needed. Here, we show that VI in stage I LUAD is associated with reproducible gene expression programs detectable beyond the invasive focus. Using bulk RNA sequencing of 162 resected tumors and spatial transcriptomics in a subset, we identify and characterize a VI-associated gene signature. A predictor derived from this signature is associated with VI and recurrence in an independent validation cohort and is robust to intra-tumor heterogeneity in multiregional sampling data. In a cohort of pre-surgical biopsies, predictor scores correlate with matched resections and show promising discrimination of VI. These findings indicate that VI-associated transcriptional changes extend across the tumor and are detectable in limited biopsy material, supporting further validation for preoperative risk stratification in stage I LUAD.
2026-01-26 | GSE273377 | GEO
Project description:Microscopic vascular invasion (VI) predicts recurrence and benefit from lobectomy in stage I lung adenocarcinoma (LUAD) but cannot be accurately predicted before surgery. Thus, biomarkers that identify this aggressive tumor subset are needed. Here, we show that VI in stage I LUAD is associated with reproducible gene expression programs detectable beyond the invasive focus. Using bulk RNA sequencing of 162 resected tumors and spatial transcriptomics in a subset, we identify and characterize a VI-associated gene signature. A predictor derived from this signature is associated with VI and recurrence in an independent validation cohort and is robust to intra-tumor heterogeneity in multiregional sampling data. In a cohort of pre-surgical biopsies, predictor scores correlate with matched resections and show promising discrimination of VI. These findings indicate that VI-associated transcriptional changes extend across the tumor and are detectable in limited biopsy material, supporting further validation for preoperative risk stratification in stage I LUAD.
2026-01-26 | GSE298714 | GEO