Array CGH analysis of 56 primary gastric cancers for elucidating prognostic biomarkers
ABSTRACT: Array CGH analysis was done with 56 primary gastric cancers to elucidate prognostic biomarkers on the BAC basis. Using the extracted genomic DNA from 56 primary gastric cancers, array CGH was done to elucidate the prognostic biomarkers.
Unlike the case with some other solid tumors, whole genome array screening has not revealed prognostic genetic aberrations in primary gastric cancer. Comparative genomic hybridization (CGH) using bacterial artificial chromosome (BAC) arrays for 56 primary gastric cancers resulted in identification of four prognostic loci in this study: 6q21 (harboring FOXO3A; previously FKHRL1), 9q32 (UGCG), 17q21.1 approximately q21.2 (CASC3), and 17q21.32 (HOXB3 through HOXB9). If any one of these four loci wa ...[more]
Project description:This SuperSeries is composed of the following subset Series: GSE10128: Genomic copy number alterations as predictive markers of systemic recurrence in breast cancer GSE10129: Genomic copy number alterations as predictive markers of neoadjuvant chemotherapy response in breast cancer Refer to individual Series
Project description:Array CGH containing 4,044 human bacterial artificial chromosome clones was used to assess different copy number changes between chemotherapy responsive and non-resposive breast cancer tissues. Array CGH containing 4,044 human bacterial artificial chromosome clones was used to assess different copy number changes between chemotherapy responsive and non-resposive breast cancer tissues.
Project description:Array CGH containing 4,044 human bacterial artificial chromosome clones was used to assess copy number changes in 31 pairs of clinicopathologically well matched recurred / nonrecurred breast cancer tissues. Array CGH containing 4,044 human bacterial artificial chromosome clones was used to assess copy number changes in 31 pairs of clinicopathologically well matched recurred / nonrecurred breast cancer tissues.
Project description:Background: Neoadjuvant chemoradiotherapy (NCRT) is the treatment of choice in advanced rectal cancer, even though there are many patients who will not benefit from it. There are still no effective methods for predicting which patients will respond or not. The present study aimed to define the genomic profile of rectal tumors and to identify alterations that are predictive of response in order to optimize therapeutic strategies. Methods: Forty-eight candidates for NCRT were recruited and their pretherapy biopsies analyzed by array Comparative Genomic Hybridization (aCGH). Pathologic response was evaluated by tumor regression grade (TRG).Results: Both Smoothing and Hidden Markov Model (HMM) approaches identified similar alterations, with a prevalence of DNA gains. Non responsive patients had a different alteration profile from responsive ones, with a higher number of genome changes mainly located on 2q21, 7q21, 7q36, 13q12, 13q32-34, 16p13, 17p12 chromosomal regions. Conclusion: This exploratory study suggests that an in depth characterization of chromosomal alterations by aCGH would provide useful predictive information about response to NCRT and help to optimize therapy in rectal cancer patients. 48 samples included in the study were analyzed on whole genome BAC arrays with the aim to characterize genomic alterations and correlate them with the tumor response to therapy. The case series was composed by 15%,81% and 4% of uT2, uT3 and uT4 tumors, respectively. At the diagnosis 56% of patients had uN0 tumors and 44% uN+. 30%,13%, 23% and 34% of patients reached/mantained respectively ypT0, ypT1, ypT2 and ypT3. With regard to response to NCRT, according to TRG criteria proposed by Dworak, two group were defined: non responders (TRG0-2= 56%) and responders (TRG3-4=44%). Clinical and pathological parameters: uT: pre-therapy stage determined by ultrasounds techniques uN: pre-therapy lymph node status determined by ultrasounds techniques ypT: pathologic stage after a neoadjuvant treatment ypN: pathologic lymph node status after a neoadjuvant treatment
Project description:We analyzed DNA copy number alterations in 64 human gastric cancer samples and 8 gastric cancer cell lines using bacterial artificial chromosome (BAC) arrays based comparative genomic hybridisation (aCGH). Gastric cancer tumor tissue samples and cell lines vs normal blood samples
Project description:The lncRNA expression profiles in three pairs of hTERT-positive gastric cancer tissue sand hTERT-negative para-cancerous tissues. The para-cancerous tissue is at least 5cm away from the cancer tissue. The expression of hTERT of identified by immunohistochemistry before RNA extraction for lncRNA assay. LncRNAs/mRNAs in 3 gastric cancer tissue and 3 paired para-cancerous tissue (Control) by microarray using Arraystar Human LncRNA Microarray v2.0
Project description:Array CGH analysis was done with 56 primary gastric cancers to elucidate prognostic biomarkers on the BAC basis. Overall design: Using the extracted genomic DNA from 56 primary gastric cancers, array CGH was done to elucidate the prognostic biomarkers.
Project description:Promoter hypermethylation occurs in human gastric cancers, but whether the deregulated genes contribute to the multi-step Helicobacter pylori (H pylori)-induced gastric carcinogenesis remains unclear. We used Microarray-based Methylation Assessment of Single Samples (MMASS) to identify differential methylated genes in 10 human gastric cancer tissues. Two-condition experiment, gastric cancers from patients (n = 5 per group) who survived 5 years or more (long-term survivors group) and who died of disease prior to 5 years (short-term survivors group)
Project description:Purpose: Our study aimed to disclose the specific gene expression profile representing peritoneal relapses inherent in primary gastric cancers and to identify patients at high risk of peritoneal relapse in a prospective study on the basis of the molecular prediction. Experimental Design: RNA samples from 141 primary gastric cancer tissues after curative surgery were profiled using oligonucleotide microarrays covering 30,000 human probes. Firstly we constructed molecular prediction system and validated the robustness and prognostic validity of the analysis by 500 times multiple random sampling in 56 retrospective set consisting of 38 relapse free and 18 peritoneal relapse patients. Secondly we applied this prediction to 85 prospective set to assess the predictive accuracy and prognostic validity. Results: In retrospective phase, 500 times multiple random sampling analysis yielded 68% predictive accuracy in average and 22 gene expression profile associated with peritoneal relapse was identified. This prediction could identify significantly poor prognostic patients. In prospective phase, the molecular prediction yielded 76.9% overall accuracy. Kaplan–Meier analysis with peritoneal relapse free survival showed a significant difference between ‘good signature group’ and ‘poor signature group’ (Log-rank p=0.0017). Multivariate analysis by Cox regression hazards model revealed that the molecular prediction was the only independent peritoneal relapse prognostic factor. Conclusions: Gene expression profile inherent in primary gastric cancer tissues can be useful to predict peritoneal relapse prospectively after curative surgery and individualize postoperative management to improve the prognosis of advanced gastric cancers. Of 141 samples, 56 represented the retrospective phase and 85 represented the prospective phase.