RNA-Seq of Circulating Tumor Cells in Stage II-III Breast Cancer
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PROVIDER: PRJNA438345 | ENA |
REPOSITORIES: ENA
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Project description:BACKGROUND: We characterized the whole transcriptome of circulating tumor cells (CTCs) in Stage II-III breast cancer to evaluate correlations with primary tumor biology. METHODS: CTCs were isolated from peripheral blood (PB) via immunomagnetic enrichment followed by fluorescence-activated cell sorting (IE-FACS). CTCs, PB and fresh tumors were profiled with RNA Seq. Formalin-fixed, paraffin-embedded (FFPE) tumors were subjected to RNA Seq and NanoString PAM50 assays with Risk of Recurrence (ROR) scores. RESULTS: CTCs were detected in 29/33 (88%) of patients. We selected 21 cases to attempt RNA Seq (median number of CTCs=9). 16 CTC samples yielded results that passed quality control metrics. These samples had a median of 4,311,255 uniquely mapped reads, less than PB or tumors. Intrinsic subtype predicted by comparing estrogen receptor (ER), progesterone receptor (PR) and HER2 versus PAM50 for FFPE tumors was 85% concordant. However, CTC RNA Seq subtype assessed by the PAM50 classification genes was highly discordant both with the subtype predicted by ER/PR/HER2 as well as by tumor PAM50. Two patients died of metastatic disease - both had high ROR scores and high CTC counts. We identified significant genes, canonical pathways, upstream regulators and molecular interaction networks comparing CTCs by various clinical factors. We identified a 75-gene signature with highest expression in CTCs and tumors taken together that was prognostic in The Cancer Genome Atlas and METABRIC datasets. CONCLUSION: It is feasible to use RNA Seq of CTCs in non-metastatic patients to discover novel tumor biology characteristics.
2019-02-04 | GSE111842 | GEO
Project description:Imaging technologies only detect progression after it has occurred, which may be well after tumor growth or disease progression has begun. In this work, we determined whether circulating tumor cell (CTC) quantification, PD-L1 expression on CTCs, or CTC gene expression can be used as a blood-based biomarker to predict patient outcomes in stage III NSCLC. The primary endpoint was disease progression, either locoregional, distant, or death. We used immunoaffinity graphene oxide (GO) chip to isolated CTCs from stage III NSCLC patients, and extracted bulk RNA materials from isolated CTC samples and conducted microarray gene expression profiling.
2024-01-18 | GSE249262 | GEO
Project description:Distant metastasis is the major causes of death in colorectal cancer (CRC) patients. In order to identify genes influencing the prognosis of patients with CRC, we compared gene expression in primary tumors with and without distant metastasis using an oligonucleotide microarray. We also examined the expression of the candidate gene in 100 CRC patients by quantitative real-time reverse transcription PCR and studied the relationship between its expression and the prognosis of patients with CRC. As a result, we identified MUC12 as a candidate gene involved in metastasis processes by microarray analysis. Quantitative real-time reverse transcription PCR showed that MUC12 expression was significantly lower in cancer tissues than in adjacent normal tissues (P < 0.001). In stage II and stage III CRC, patients with low expression showed worse disease-free survival (P = 0.038). Multivariate analysis disclosed that MUC12 expression status was an independent prognostic factor in stage II and stage III CRC (relative risk, 9.532; 95% confidence interval, 2.303-41.905; P = 0.002). This study revealed the prognostic value of MUC12 expression in CRC patients. Moreover, our result suggests MUC12 expression is a possible candidate gene for assessing postoperative adjuvant therapy for CRC patients.
2010-02-04 | GSE18105 | GEO
Project description:Colorectal cancer is one of the most common cancers in the world. Histological staging is efficient but combination with molecular markers may improve tumors classification. Gene expression profiles have been defined as prognosis predictors among stage II and III tumors but their implementation in medical practice remains controversial. Stage-II tumors have been recognized as a heterogeneous group and high-risk morphologic features have been retained as justifying adjuvant chemotherapy. We propose here the investigation of clinical features and expression profiles from stage II and stage III colon carcinomas without DNA mismatch repair defect. A series of 130 colon cancer samples was retained. Expression profiles were established on oligonucleotide microarrays and processed in the R/Bioconductor environment. Hierarchical then supervised analyses were successively performed applying the data-sampling approach. A molecular signature of seven genes was found to cluster stage III tumors with an adjusted p-values lower than 10^-10. A subgroup of stage-II tumors aggregated this cluster in both series. No correlation was found between with the disease severity but the function of the discriminating genes suggests that tumors have been classified according to their putative response to adjuvant targeted or classic therapies. Further pharmacogenetic studies might document this observation.
2012-05-11 | GSE37892 | GEO
Project description:Defining molecular features that can predict the response to chemotherapy for stage II-III colorectal cancer (CRC) patients remains challenging in cancer research. Most available clinical samples are Formalin-Fixed and Paraffin-Embedded (FFPE). Affymetrix GeneChip® Human Transcriptome Array 2.0 (HTA) is one platform marketed for high-throughput gene expression profiling for FFPE tissue samples. In this study, we analyzed the whole transcriptom gene expression of 156 CRC patient samples measured by this platform to identify biomarkers predicting the response to chemotherapy for stage II-III CRC patients.
2021-11-04 | GSE106584 | GEO
Project description:Purpose: A 128-gene signature has been proposed to predict poor outcomes in patients with stage II and III colorectal cancer. In the present study we aimed to validate this previously published 128-gene signature on external and independent data from patients with stage II and III colon cancer.
2011-09-01 | GSE31595 | GEO
Project description:Colorectal cancer is one of the most common cancers in the world. Histological staging is efficient but combination with molecular markers may improve tumors classification. Gene expression profiles have been defined as prognosis predictors among stage II and III tumors but their implementation in medical practice remains controversial. Stage-II tumors have been recognized as a heterogeneous group and high-risk morphologic features have been retained as justifying adjuvant chemotherapy. We propose here the investigation of clinical features and expression profiles from stage II and stage III colon carcinomas without DNA mismatch repair defect. A series of 130 colon cancer samples was retained. Expression profiles were established on oligonucleotide microarrays and processed in the R/Bioconductor environment. Hierarchical then supervised analyses were successively performed applying the data-sampling approach. A molecular signature of seven genes was found to cluster stage III tumors with an adjusted p-values lower than 10^-10. A subgroup of stage-II tumors aggregated this cluster in both series. No correlation was found between with the disease severity but the function of the discriminating genes suggests that tumors have been classified according to their putative response to adjuvant targeted or classic therapies. Further pharmacogenetic studies might document this observation. Expression profile of stage-II colon carcinomas distinguishes two patterns of tumors based on a 7-gene signature. One pattern is very similar to that of stage-III tumors and the corresponding tumors aggregate into a single cluster. Genes function suggests possible tumor determinism in drug response more than in prognosis evolution.
2012-05-10 | E-GEOD-37892 | biostudies-arrayexpress
Project description:Analyze differential expression between stage UICC II and UICC III colorectal cancer
2005-08-30 | E-MEXP-383 | biostudies-arrayexpress
Project description:Distant metastasis is the major causes of death in colorectal cancer (CRC) patients. In order to identify genes influencing the prognosis of patients with CRC, we compared gene expression in primary tumors with and without distant metastasis using an oligonucleotide microarray. We also examined the expression of the candidate gene in 100 CRC patients by quantitative real-time reverse transcription PCR and studied the relationship between its expression and the prognosis of patients with CRC. As a result, we identified MUC12 as a candidate gene involved in metastasis processes by microarray analysis. Quantitative real-time reverse transcription PCR showed that MUC12 expression was significantly lower in cancer tissues than in adjacent normal tissues (P < 0.001). In stage II and stage III CRC, patients with low expression showed worse disease-free survival (P = 0.038). Multivariate analysis disclosed that MUC12 expression status was an independent prognostic factor in stage II and stage III CRC (relative risk, 9.532; 95% confidence interval, 2.303-41.905; P = 0.002). This study revealed the prognostic value of MUC12 expression in CRC patients. Moreover, our result suggests MUC12 expression is a possible candidate gene for assessing postoperative adjuvant therapy for CRC patients. Total of 111 microarray datasets (77 for LCM samples, and 17 pairs for homogenized samples from tumor and adjacent tissues) were normalized using robust multi-array average (RMA) method under R 2.6.2 statistical software together with BioConductor package, as described previously. Then, the gene expression levels were log2-transformed, and 62 control probe sets were removed for further analysis. In order to identify a set of genes associated with development of metastatic recurrence, we performed Wilcoxon rank-sum test for gene expression differences of 54,613 probe sets between recurrence and non-recurrence groups. Similarly, Wilcoxon singed-rank test was conducted to select genes which showed significant expression difference between tumor and adjacent tissue. Then, we selected a set of genes that satisfied both of above two criteria.
2010-03-05 | E-GEOD-18105 | biostudies-arrayexpress
Project description:Background & Aims. The current staging system for colorectal cancer (CRC) based on TNM classification allows prediction of potential recurrence. However, it does not necessarily make reliable personalized prediction of prognosis. In this paper we describe combination of clinicopathological data and gene signature of dissected tumor specimen with stage II and III CRC patients would improve the situation.. Methods. A total of 1978 CRC were collected over 5 years, and then 371 stage II and 322 stage III of them with more than 45.9 months records were subjected to clinicopathological feature analyses. Out of this collection, 129 stage II and III CRC cases were selected for analyses of gene expression profiles with resected specimen. The gene signatures were analyzed by repeated random divisions of the samples into training and test sets to extract discriminator genes. After testing the applicability of this discriminator set, it was subjected to validation using a newly obtained set of 69 samples. Results. The pathological factors in solo or in combinations could not make personalized recurrence prediction, except for partial success with stage II patients. The gene signature, on the other hand, was capable of producing a set of discriminator genes, though the accuracy was yet to be improved. We observed that the best result was obtained when discriminators were selected from stage II CRC samples and used for prognosis of stage II CRC. When stage III cases were included in the process of discriminator extraction or in the process to validate samples, the results were poorer. Finally, we examined 31 independent stage II samples with a set of 30 such discriminators and were able to obtain results with 78 % accuracy, 90 % negative predictive value (NPV), and 55% positive predictive value (PPV). Conclusions. Independent clinicopathological variables were not able to predict prognosis of individual patient, unless the factors are combined. On the other hand, gene signatures allowed accurate prediction of prognosis for individuals, especially with stage II CRC, suggesting its potential use for selection of best treatment option for individual patients. The accuracy of discriminator prediction will be further improved when we take the evolution of CRC into consideration.
2009-07-02 | GSE12032 | GEO