An Invasive Gene Expression Signature in Pancreas Cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Rogers Annamarie
PROVIDER: S-ECPF-GEOD-22973 | biostudies-other |
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Gene expression profiling has demonstrated clinical utility as a predictive tool in clinical oncology. We have identified genes associated with invasion of pancreatic cancer, and with potential for identifying early recurrence. We used Affymetrix Human U133 Plus 2.0 microarrays to identifiy specific predictive profiles in pancreatic cancer, and the evolution of gene expression. We identified distinct classes of up-regulated genes during this process.
2011-01-01 | GSE22973 | GEO
Project description:Gene expression profiling has demonstrated clinical utility as a predictive tool in clinical oncology. We have identified genes associated with invasion of pancreatic cancer, and with potential for identifying early recurrence. We used Affymetrix Human U133 Plus 2.0 microarrays to identify specific predictive profiles in pancreatic cancer, and the evolution of gene expression. We identified distinct classes of up-regulated genes during this process. Primary and metastatic pancreatic cancer cell lines (BxPC-3 and AsPC-1), were stimulated with with phorbol-12-myristate 13-acetate (PMA), a known inducer of invasion. Affymetrix gene expression microarray analysis was performed, comparing PMA stimulated BxPC-3 and AsPC-1 gene expression to unstimulated controls, and also PMA stimulated BxPC-3 verses stimulated AsPC-1 cell lines. Differential gene expression was identified using ArrayAssist bioinformatics software. Gene expression changes were confirmed using quantitative reverse transcription polymerase chain reaction (qRT-PCR) (Assays-on-demand, Taqman, ABI systems). Pathway Assist and GOstat were used to identify pathway and gene ontology changes.
2011-01-01 | E-GEOD-22973 | biostudies-arrayexpress
Project description:BackgroundWe are investigating the molecular basis of melanoma by defining genomic characteristics that correlate with tumour phenotype in a novel panel of metastatic melanoma cell lines. The aim of this study is to identify new prognostic markers and therapeutic targets that might aid clinical cancer diagnosis and management.Principal findingsGlobal transcript profiling identified a signature featuring decreased expression of developmental and lineage specification genes including MITF, EDNRB, DCT, and TYR, and increased expression of genes involved in interaction with the extracellular environment, such as PLAUR, VCAN, and HIF1a. Migration assays showed that the gene signature correlated with the invasive potential of the cell lines, and external validation by using publicly available data indicated that tumours with the invasive gene signature were less melanocytic and may be more aggressive. The invasion signature could be detected in both primary and metastatic tumours suggesting that gene expression conferring increased invasive potential in melanoma may occur independently of tumour stage.ConclusionsOur data supports the hypothesis that differential developmental gene expression may drive invasive potential in metastatic melanoma, and that melanoma heterogeneity may be explained by the differing capacity of melanoma cells to both withstand decreased expression of lineage specification genes and to respond to the tumour microenvironment. The invasion signature may provide new possibilities for predicting which primary tumours are more likely to metastasize, and which metastatic tumours might show a more aggressive clinical course.
| S-EPMC2794539 | biostudies-literature
Project description:The molecular pathology of intraductal papillary mucinous neoplasms (IPMNs) of the pancreas has not been well characterized, and there are no reliable markers to predict the presence of an associated invasive carcinoma in IPMNs. Using oligonucleotide microarrays, we performed a large-scale gene expression profiling of 12 IPMNs with or without an associated invasive carcinoma. A subset of genes identified was validated for the gene expression patterns in a large panel of IPMNs by reverse-transcription polymerase chain reaction and/or immunohistochemistry. A total of 673 transcripts were identified as expressed at significantly higher levels (P < 0.05 and at fivefold or greater) in IPMNs relative to normal pancreatic ductal epithelial samples. Of interest, many of the genes identified as overexpressed in IPMNs have also been previously reported to be highly expressed in infiltrating ductal adenocarcinoma of the pancreas. By analyzing genes overexpressed selectively in IPMNs with an associated invasive carcinoma (n = 7), we also identified a panel of genes potentially associated with the invasive phenotype of the neoplasms. Immunohistochemical validation revealed that claudin 4, CXCR4, S100A4, and mesothelin were expressed at significantly high frequency in invasive IPMNs than in noninvasive IPMNs. Notably, the expression of at least two of the four proteins was observed in 73% of 22 invasive IPMNs but in none of 16 noninvasive IPMNs (P < 0.0001). Our findings suggest that preoperative assessment of gene expression profiles may be able to differentiate invasive from noninvasive IPMNs.
| S-EPMC1613263 | biostudies-literature
Project description:BackgroundInteractions between cancer cells and surrounding cancer-associated fibroblasts (CAFs) play an important role in cancer progression. Invasive ductal carcinoma (IDC) of the pancreas is characterized by abundant fibrous connective tissue called desmoplasia. Podoplanin (PDPN) is a lymphatic vessel marker (D2-40), and expression of PDPN by stromal CAFs has been reported to be a prognostic indicator in various types of cancer.MethodsExpression of PDPN in pancreatic IDCs was assessed by immunohistochemical examination in 105 patients who underwent pancreatic resection. Primary CAFs were established from pancreatic cancer tissue obtained by surgery. Quantitative reverse transcription-polymerase chain reaction and flow cytometric analysis were performed to investigate PDPN expression in CAFs. We sorted CAFs according to PDPN expression, and analyzed the functional differences between PDPN+?CAFs and PDPN- CAFs using indirect co-culture with pancreatic cancer cell lines. We also investigated the culture conditions to regulate PDPN expression in CAFs.ResultsPDPN expression in stromal fibroblasts was associated with lymphatic vessel invasion (P?=?0.0461), vascular invasion (P?=?0.0101), tumor size ? 3 cm (P?=?0.0038), histological grade (P?=?0.0344), Union for International Cancer Control classification T stage (P?=?0.029), and shorter survival time (P?<?0.0001). Primary CAFs showed heterogeneous PDPN expression in vitro. Moreover, migration and invasion of pancreatic cancer cell lines (PANC-1 and SUIT-2) were associated with PDPN expression in CAFs (P?<?0.01) and expression of CD10, matrix metalloproteinase (MMP) 2, and MMP3. In cultured CAFs, PDPN positivity changed over time under several conditions including co-culture with cancer cells, different culture media, and addition of growth factor.ConclusionsPDPN-expressing CAFs enhance the progression of pancreatic IDC, and a high ratio of PDPN-expressing CAFs is an independent predictor of poor outcome. Understanding the regulation of the tumor microenvironment is an important step towards developing new therapeutic strategies.
| S-EPMC3916072 | biostudies-literature
Project description:There are no reliable criteria to handle disease progression of muscle invasive bladder cancer (MIBC), which strongly influences patient survival. Therefore, an accurate predicting method to identify progressive MIBC patients is greatly needed. The aim of this study was to identify a genetic signature associated with disease progression in MIBC. To address this issue, we analyzed three independent cohorts (a training set, test set 1 and test set 2) comprising a total of 128 MIBC patients. Microarray gene expression profiling, including gene network analysis, was performed in the training set to identify a gene expression signature associated with disease progression. The prognostic value of the signature was validated in test set 1 and test set 2 by microarray and real-time reverse transcriptase polymerase chain reaction (RT-PCR), respectively. The determination of gene expression patterns by microarray data analysis identified 1,320 genes associated with disease progression. Gene network analysis of the 1,320 genes suggested that IL1B, S100A8, S100A9 and EGFR were important mediators of MIBC progression. We validated this putative four-gene signature in two independent cohorts (log-rank test, P < 0.05 each, respectively) and estimated the predictive value of the signature by multivariate Cox regression analysis (hazard ratio [HR], 6.24; 95% confidence interval [CI], 1.58-24.61; P = 0.009). Finally, signature-based stratification demonstrated that the four-gene signature was an independent predictor of MIBC progression. In conclusion, a molecular signature defined by four genes represents a promising diagnostic tool for the identification of MIBC patients at high risk of progression.
| S-EPMC3105150 | biostudies-literature
Project description:BackgroundIn recent years, immune-associated genes (IAGs) have been documented as having critical roles in the occurrence and progression of muscle-invasive bladder cancer (MIBC). Novel immune-related biomarkers and a robust prognostic signature for MIBC patients are still limited. The study is aimed at developing an IAG-based signature to predict the prognosis of MIBC patients.MethodsIn the present study, we identified differentially expressed IAGs in MIBC by using transcriptomics data from The Cancer Genome Atlas (TCGA) database and proteomics data from our samples. We further constructed an IAG-based signature and evaluated its prognostic and predictive value by survival analysis and nomogram. Tumor Immune Estimation Resource (TIMER) was applied to explore the correlation between the IAG-based signature and immune cell infiltration in the microenvironment of MIBC.ResultsA total of 22 differentially expressed IAGs were identified, and 2 IAGs (NR2F6 and AHNAK) were used to establish a prognostic signature. Subsequently, survival analysis showed that high-risk scores were significantly correlated with poor overall survival (OS), progression-free survival (PFS), and disease-free survival (DFS) of MIBC patients. A prognostic nomogram was constructed by integrating clinical factors with the IAG-based signature risk score. In addition, the IAG-based signature risk score was positively associated with the infiltration of macrophages and dendritic cells in MIBC.ConclusionsWe constructed and verified a novel IAG-based signature, which could predict the prognosis of MIBC and might reflect the status of the immune microenvironment of MIBC. Further studies in more independent clinical cohorts and further experimental exploration of the prognostic IAG-based signature are still needed.
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Project description:Breast cancer biomarkers that can precisely predict the risk of progression of non-invasive ductal carcinoma in situ (DCIS) lesions to invasive disease are lacking. The identification of molecular alterations that occur during the invasion process is crucial for the discovery of drivers of transition to invasive disease and, consequently, biomarkers with clinical utility. In this study, we explored differences in gene expression in mammary epithelial cells before and after the morphological manifestation of invasion, i.e., early and late stages, respectively. In the early stage, epithelial cells were captured from both pre-invasive lesions with distinct malignant potential [pure DCIS as well as the in situ component that co-exists with invasive breast carcinoma lesions (DCIS-IBC)]; in the late stage, epithelial cells were captured from the two distinct morphological components of the same sample (in situ and invasive components). Candidate genes were identified using cDNA microarray and rapid subtractive hybridization (RaSH) cDNA libraries and validated by RT-qPCR assay using new samples from each group. These analyses revealed 26 genes, including 20 from the early and 6 from the late stage. The expression profile based on the 20 genes, marked by a preferential decrease in expression level towards invasive phenotype, discriminated the majority of DCIS samples. Thus, this study revealed a gene expression signature with the potential to predict DCIS progression and, consequently, provides opportunities to tailor treatments for DCIS patients.
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Project description:Despite continual efforts to develop a prognostic model of gastric cancer by using clinical and pathologic parameters, a clinical test that can discriminate patients with good outcomes from those with poor outcomes after gastric cancer surgery has not been established. We aim to develop practical biomarker-based risk score that can predict relapse of gastric cancer after surgical treatment.Microarray technologies were used to generate and analyze gene expression profiling data from 65 gastric cancer patients to identify biomarker genes associated with relapse. The association of expression patterns of identified genes with relapse and overall survival was validated in independent gastric cancer patients.We uncovered two subgroups of gastric cancer that were strongly associated with the prognosis. For the easy translation of our findings into practice, we developed a scoring system based on the expression of six genes that predicted the likelihood of relapse after curative resection. In multivariate analysis, the risk score was an independent predictor of relapse in a cohort of 96 patients. We were able to validate the robustness of the six-gene signature in an additional independent cohort.The risk score derived from the six-gene set successfully prognosticated the relapse of gastric cancer patients after gastrectomy.
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