MicroRNA signature predict chemotherapy response in patients with advanced colorectal cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE48664 | GEO | 2014/08/12
SECONDARY ACCESSION(S): PRJNA210969
REPOSITORIES: GEO
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Project description:The aim of our study was to evaluate the ability of miRNA expression patterns to predict chemotherapy response in a cohort of 39 patients with metastatic colorectal carcinoma To define miRNA signature, samples were obtained from tumor tissue samples of 39 patients . Patients were divided into responders or non-responders according to tresponse treatment with a chemotherapy regimen that included fluoropyrimidines and either oxaliplatin or irinotecan .Tumor response was evaluated by conventional methods according to the standard RECIST 1.0 criteria: a complete response (CR) was defined as the disappearance of all measurable and evaluable evidence of disease; a partial response (PR) was defined as a > 30% decrease in the sum of the longest diameters of target lesions; stable disease (SD) was considered if the tumor burden decreased less than 30% or increased less than 20%; and progressive disease (PD) was indicated by a >20% increase in the sum of the longest diameters of target lesions or the appearance of any new lesion. Patients were classified according to best response to chemotherapy in two groups: those that achieved an objective response (Responders [R]: CR + PR) and those that did not (Non-responders [NR]: SD + PD). 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 MammU6. 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)).
2014-08-12 | E-GEOD-48664 | biostudies-arrayexpress
Project description:The aim of our study was to identify a microRNA signature to predict the recurrence in stage II & III CRC patients who were treated with FOLFOX-based adjuvant chemotherapy after curative resection of tumors. We performed small RNA sequencing in 71 FFPE surgical specimens, and discovered differentially expressed microRNAs in patients who developed recurrence. Thereafter, selected microRNA biomarkers were validated in independent cohort using qRT-PCR assay.
2022-11-16 | GSE217978 | GEO
Project description:We performed a prospective cohort study in patients with advanced CRC to identify a miRNA signature that could predict the benefit of receiving first-line chemotherapy for these patients.
2017-12-16 | GSE108153 | GEO
Project description:Gene expression signature can be used to predict treatment efficacy in various types of tumour. We aim to identify a gene expression signature to predict efficacy of induction chemotherapy (IC) in patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC).
2021-04-14 | GSE132112 | GEO
Project description:To measure global gene expression in primary advanced colorectal cancer patients who have undergone fluorouracil, leucovorin and oxaliplatin (FOLFOX4) chemotherapy and screen valuable biomarkers to predict the effects of chemotherapy Samples from primary advanced colorectal cancer patients were collected. The effects of chemotherapy were evaluated, and patients were divided into an experimental group and a control group.
2015-12-31 | GSE69657 | GEO
Project description:To measure global gene expression in primary metastatic colorectal cancer patients who have undergone fluorouracil, leucovorin and oxaliplatin (FOLFOX) chemotherapy and screen valuable biomarkers to predict the effects of chemotherapy. Samples from primary metastatic colorectal cancer patients were collected. The effects of chemotherapy were evaluated.
2020-01-28 | GSE138912 | GEO
Project description:To measure global gene expression in primary advanced colorectal cancer patients who have undergone fluorouracil, leucovorin and oxaliplatin (FOLFOX4) chemotherapy and screen valuable biomarkers to predict the effects of chemotherapy Samples from primary advanced colorectal cancer patients were collected. The effects of chemotherapy were evaluated, and patients were divided into an experimental group and a control group. All patients underwent standard FOLFOX4 regimen chemotherapy in four cycles after signing the chemotherapy agreement; subsequently, they were evaluated in accordance with the Response Evaluation Criteria In Solid Tumors (RECIST).Each samplewas collected immediately following resection. Each sample was divided in half: one half was fixed in formalin and embedded in paraffin; the other half floated in ice-cold phosphate-buffered saline and was stored in liquid nitrogen until total RNA extraction. CEL files available for only 16/30 samples. Remaining CEL files have been lost.
2015-12-31 | E-GEOD-69657 | biostudies-arrayexpress
Project description:In patients with advanced colorectal cancer, leucovorin, fluorouracil, and irinotecan (FOLFIRI) is considered as one of the reference first-line treatments. However, only about half of treated patients respond to this regimen, and there is no clinically useful marker that predicts response. A major clinical challenge is to identify the subset of patients who could benefit from this chemotherapy. We aimed to identify a gene expression profile in primary colon cancer tissue that could predict chemotherapy response. Patients and Methods:- Tumor colon samples from 21 patients with advanced colorectal cancer were analyzed for gene expression profiling using Human Genome GeneChip arrays U133. At the end of the first-line treatment, the best observed response, according to WHO criteria, was used to define the responders and nonresponders. Discriminatory genes were first selected by the significance analysis of microarrays algorithm and the area under the receiver operating characteristic curve. A predictor classifier was then constructed using support vector machines. Finally, leave-one-out cross validation was used to estimate the performance and the accuracy of the output class prediction rule. Results:- We determined a set of 14 predictor genes of response to FOLFIRI. Nine of nine responders (100% specificity) and 11 of 12 nonresponders (92% sensitivity) were classified correctly, for an overall accuracy of 95%. Conclusion:- After validation in an independent cohort of patients, our gene signature could be used as a decision tool to assist oncologists in selecting colorectal cancer patients who could benefit from FOLFIRI chemotherapy, both in the adjuvant and the first-line metastatic setting.
2014-10-06 | GSE62080 | GEO
Project description:In patients with advanced colorectal cancer, leucovorin, fluorouracil, and irinotecan (FOLFIRI) is considered as one of the reference first-line treatments. However, only about half of treated patients respond to this regimen, and there is no clinically useful marker that predicts response. A major clinical challenge is to identify the subset of patients who could benefit from this chemotherapy. We aimed to identify a gene expression profile in primary colon cancer tissue that could predict chemotherapy response. Patients and Methods:- Tumor colon samples from 21 patients with advanced colorectal cancer were analyzed for gene expression profiling using Human Genome GeneChip arrays U133. At the end of the first-line treatment, the best observed response, according to WHO criteria, was used to define the responders and nonresponders. Discriminatory genes were first selected by the significance analysis of microarrays algorithm and the area under the receiver operating characteristic curve. A predictor classifier was then constructed using support vector machines. Finally, leave-one-out cross validation was used to estimate the performance and the accuracy of the output class prediction rule. Results:- We determined a set of 14 predictor genes of response to FOLFIRI. Nine of nine responders (100% specificity) and 11 of 12 nonresponders (92% sensitivity) were classified correctly, for an overall accuracy of 95%. Conclusion:- After validation in an independent cohort of patients, our gene signature could be used as a decision tool to assist oncologists in selecting colorectal cancer patients who could benefit from FOLFIRI chemotherapy, both in the adjuvant and the first-line metastatic setting. All tissue samples were maintained at −180°C (liquid nitrogen) until RNA extraction and were weighed before homogenization. Tissue samples were then disrupted directly into a lysis buffer using Mixer Mill MM 300 (Qiagen, Valencia, CA). Total RNA was isolated from tissue lysates using the RNeasy Mini Kit (Qiagen), and additional DNAse digestion was performed on all samples during the extraction process (RNase-Free DNase Set Protocol for DNase treatment on RNeasy Mini Spin Columns; Qiagen). After each extraction, a small fraction of the total RNA preparation was taken to determine the quality of the sample and the yield of total RNA. Controls analyses were performed by UV spectroscopy and analysis of total RNA profile using the Agilent RNA 6000 Nano LabChip Kit with the Agilent 2100 Bioanalyser (Agilent Technologies, Palo Alto, CA) to determine RNA purity, quantity, and integrity.
2014-10-06 | E-GEOD-62080 | biostudies-arrayexpress
Project description:Background: Colorectal cancer is the third most common and the fourth most lethal cancer in the world. In the majority of cases, patients are diagnosed at an advanced stage or even metastatic, thus explaining the high mortality. The standard protocol for treating patients with locally advanced non-metastatic colorectal cancer (CRC) is neoadjuvant radio-chemotherapy (NRCT) with 5-fluorouracil (5-FU), but the resistance rate to this treatment remains high with approximately 30% of non-responders. The lack of evidence available in clinical practice to predict NRCT resistance to 5-FU and to guide clinical practice therefore encourages the search for biomarkers of this resistance. Methods: From twenty-three formalin-fixed paraffin-embedded (FFPE) biopsies performed before NRCT with 5-FU of locally advanced non-metastatic CRC patients, we extracted and analysed the tumor proteome of these patients. From clinical data, we were able to classify the twenty-two patients in our cohort into three treatment response groups: non-responders (NR), partial responders (PR) and total responders (TR), and to compare the proteomes of these different groups. Results: We have highlighted 384 differentially expressed proteins between NR and PR, 248 between NR and TR and 417 between PR and TR. Among these proteins, we have identified many differentially expressed proteins identified as having a role in cancer (IFIT1, FASTKD2, PIP4K2B, ARID1B, SLC25A33: overexpressed in TR; CALD1, CPA3, B3GALT5, CD177, RIPK1: overexpressed in NR). We have also identified that DPYD, the main degradation enzyme of 5-FU, was overexpressed in NR, as well as several ribosomal and mitochondrial proteins also overexpressed in NR. Conclusions: From these retrospective study, we implemented a protein extraction protocol from FFPE biopsy to highlight protein differences between different response groups to RCTN with 5-FU in patients with locally advanced non-metastatic CRC. These results will pave the way for a larger cohort for better sensitivity and specificity of the signature to guide decisions in the choice of treatment.
2018-06-25 | PXD008440 | Pride