three-microRNA Signature Research Articles

A diagnostic circulating miRNA signature as orchestrator of cell invasion via TKS4/TKS5/EFHD2 modulation in human gliomas

BackgroundAltered microRNA profiles have been observed not only in tumour tissues but also in biofluids, where they circulate in a stable form thus representing interesting biomarker candidates. This study aimed to identify a microRNA signature as a non-invasive biomarker and to investigate its impact on glioma biology.MethodsMicroRNAs were selected using a global expression profile in preoperative serum samples from 37 glioma patients. Comparison between serum samples from age and gender-matched controls was performed by using the droplet digital PCR. The ROC curve and Kaplan-Meier survival analyses were used to evaluate the diagnostic/prognostic values. The functional role of the identified signature was assessed by gain/loss of function strategies in glioma cells.ResultsA three-microRNA signature (miR-1-3p/−26a-1-3p/−487b-3p) was differentially expressed in the serum of patients according to the isocitrate dehydrogenase (IDH) genes mutation status and correlated with both patient Overall and Progression Free Survival. The identified signature was also downregulated in the serum of patients compared to controls. Consistent with these results, the signature expression and release in the conditioned medium of glioma cells was lower in IDH-wild type cells compared to the mutated counterpart. Furthermore, in silico analysis of glioma datasets showed a consistent deregulation of the signature according to the IDH mutation status in glioma tumour tissues. Ectopic expression of the signature negatively affects several glioma functions. Notably, it impacts the glioma invasive phenotype by directly targeting the invadopodia-related proteins TKS4, TKS5 and EFHD2.ConclusionsWe identified a three microRNA signature as a promising complementary or even an independent non-invasive diagnostic/prognostic biomarker. The signature displays oncosuppressive functions in glioma cells and impacts on proteins crucial for migration and invasion, providing potential targets for therapeutic intervention.

Diagnostic implication of a circulating serum-based three-microRNA signature in hepatocellular carcinoma.

Owing to the diagnostic dilemma, the prognosis of hepatocellular carcinoma (HCC) remains impoverished, contributing to the globally high mortality rate. Currently, HCC diagnosis depends on the combination of imaging modalities and the measurement of serum alpha-fetoprotein (AFP) levels. Nevertheless, these conventional modalities exhibit poor performance in detecting HCC at early stages. Thus, there is a pressing need to identify novel circulating biomarkers to promote diagnostic accuracy and surveillance. Circulating miRNAs are emerging as promising diagnostic tools in screening various cancers, including HCC. However, because of heterogenous and, at times, contradictory reports, the universality of miRNAs in clinical settings remains elusive. Consequently, we proposed to explore the diagnostic potential of ten miRNAs selected on a candidate-based approach in HCC diagnosis. The expression of ten candidate miRNAs (Let-7a, miR-15a, miR-26a, miR-124, miR-126, miR-155, miR-219, miR-221, miR-222, and miR-340) was investigated in serum and tissue of 66 subjects, including 33 HCC patients and 33 healthy controls (HC), by rt-PCR. Receiver operating characteristic curve (ROC) analysis was used to determine the diagnostic accuracy of the prospective serum miRNA panel. To anticipate the potential biological roles of a three-miRNA signature, the target genes were evaluated using the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathway. The serum and tissue expression of miRNAs (Let-7a, miR-26a, miR-124, miR-155, miR-221, miR-222, and miR-340) were differentially expressed in HCC patients (p < 0.05). The ROC analysis revealed promising diagnostic performance of Let-7a (AUC = 0.801), miR-221 (AUC = 0.786), and miR-2 (AUC = 0.758) in discriminating HCC from HC. Furthermore, in a logistic regression equation, we identified a three-miRNA panel (Let-7a, miR-221, and miR-222; AUC = 0.932) with improved diagnostic efficiency in differentiating HCC from HC. Remarkably, the combination of AFP and a three-miRNA panel offered a higher accuracy of HCC diagnosis (AUC = 0.961) than AFP alone. The functional enrichment analysis demonstrated that target genes may contribute to pathways associated with HCC and cell-cycle regulation, indicating possible crosstalk of miRNAs with HCC development. To conclude, the combined classifier of a three-miRNA panel and AFP could be indispensable circulating biomarkers for HCC diagnosis. Furthermore, targeting predicted genes may provide new therapeutic clues for the treatment of aggressive HCC.

A novel three-microRNA signature for predicting survival in patients with nasopharyngeal carcinoma

Background/purposeNasopharyngeal carcinoma (NPC) is a malignant neoplasm of the head and neck. This study aims to use integrated bioinformatics technologies to develop a predictive miRNA-signature correlated with the prognosis of NPC. Materials and methodsInitially, the differentially expressed miRNAs (DEMs) in NPC were identified, and then DEMs related to the prognosis of NPC were further screened. Subsequently, the relatively important DEMs identified by random forest algorithm were used to construct a predictive signature by multivariate COX regression analysis. Moreover, PCA, Kaplan–Meier analysis, time-dependent ROC analysis, and univariate and multivariate COX regression analysis were performed to evaluate the ability of the signature in risk identification and prognosis prediction in NPC. ResultsHsa-miR-29c, hsa-miR-30e and hsa-miR-93 were selected from DEMs to construct a signature, and their abnormal expression was significantly associated with poor prognosis of NPC. The average AUC values of 1- to 5-year OS, DFS and DMFS predicted by the signature were all above 0.7, and showed better clinical independence than other indexes. In addition, 295 differentially expressed mRNAs could be used as potential target genes of the 3 DEMs. Among them, 56 differentially expressed mRNAs were related to PFS. GO and KEGG enrichment analysis indicated that the poor prognosis of NPC was related to the abnormality of chromosomes, cytokines, and chemokines. ConclusionWe constructed a three-miRNA signature with good independent performance in predicting the prognosis for NPC. This study may lay the foundation for exploring new therapeutic targets and improving survival outcomes in NPC patients.

Plasma microrna expression profile for reduced ejection fraction in dilated cardiomyopathy

The left ventricular (LV) ejection fraction (EF) is key to prognosis in dilated cardiomyopathy (DCM). Circulating microRNAs have emerged as reliable biomarkers for heart diseases, included DCM. Clinicians need improved tools for greater clarification of DCM EF categorization, to identify high-risk patients. Thus, we investigated whether microRNA profiles can categorize DCM patients based on their EF. 179-differentially expressed circulating microRNAs were screened in two groups: (1) non-idiopathic DCM; (2) idiopathic DCM. Then, 26 microRNAs were identified and validated in the plasma of ischemic-DCM (n = 60), idiopathic-DCM (n = 55) and healthy individuals (n = 44). We identified fourteen microRNAs associated with echocardiographic variables that differentiated idiopathic DCM according to the EF degree. A predictive model of a three-microRNA (miR-130b-3p, miR-150-5p and miR-210-3p) combined with clinical variables (left bundle branch block, left ventricle end-systolic dimension, lower systolic blood pressure and smoking habit) was obtained for idiopathic DCM with a severely reduced-EF. The receiver operating characteristic curve analysis supported the discriminative potential of the diagnosis. Bioinformatics analysis revealed that miR-150-5p and miR-210-3p target genes might interact with each other with a high connectivity degree. In conclusion, our results revealed a three-microRNA signature combined with clinical variables that highly discriminate idiopathic DCM categorization. This is a potential novel prognostic biomarker with high clinical value.

Construction and validation of a three-microRNA signature as prognostic biomarker in patients with hepatocellular carcinoma.

Hepatocellular carcinoma (HCC), a common type of primary liver cancer, is one of the most aggressive malignant tumors worldwide. Although overall survival (OS) rates for HCC has significantly improved in recent years, however, the exact predictive value of microRNA (miRNA) for the prognosis of HCC has not yet been recognized. Here, we aimed to identify potential prognostic miRNAs involved in HCC by bioinformatics analysis and validated expression levels through quantitative polymerase chain reaction (qPCR) and GEO database. The RNA expression profiles and corresponding clinical information of HCC were available from The Cancer Genome Atlas (TCGA) datasets. Differentially expression and standardization analysis of miRNAs, Kaplan-Meier curve and time dependent ROC curve were performed by using R tools. Differentially expressed miRNAs (DEmiRNAs) and clinical parameters involved in the OS of HCC were confirmed by Cox regression models. And functional enrichment analysis was used to establish functions of the targeted genes of DEmiRNAs. A total of 300 DEmiRNAs were significantly related with HCC, of which 40 were down-regulated and 260 were up-regulated. A total of 344 patients with DEmiRNAs, status, overall survival (OS) time were randomized into training group (172) and test group (172). Multivariate Cox regression analyses revealed that 3 miRNA (hsa-miR-139-3p, hsa-miR-760, hsa-miR-7-5p) had independent prognostic significance for the OS of HCC in both training and test group. Moreover, according to Kaplan Meier analysis, the OS of HCC patients with high-risk score was shorter in validation and entire series. The time dependent ROC curve demonstrated high accuracy of the signature for OS. Besides, target genes of three miRNAs were analyzed by functional enrichment analysis and 20 genes associated with OS were verified by using Kaplan-Meier method. Compared with normal and benign group, the relative expression level of hsa-miR-139-3p was significantly decreased, while hsa-miR-7-5p and hsa-miR-760 were distinctly increased in the plasma of HCC patients. The same results were observed in the independent cohort. Collectively, our research suggested that three-miRNA signature could serve as an independent prognostic indicator for HCC patients.

MicroRNA Signatures in Malignant Pleural Mesothelioma Effusions.

Malignant pleural mesothelioma (MPM) is an incurable cancer of the pleura that can be difficult to diagnose. Biomarkers for an easier and/or earlier diagnosis are needed. Approximately 90% of MPM patients develop a pleural effusion (PE). PEs are ideal sources of biomarkers as the fluid would almost always require drainage for diagnostic and/or therapeutic reasons. However, differentiating MPM PE from PE caused by other diseases can be challenging. MicroRNAs are popular biomarkers given their stable expression in tissue and fluid. MicroRNAs have been analysed in PE cytology samples for the diagnosis of MPM but have not been measured in frozen/fresh PE. We hypothesise that microRNAs expressed in PE are biomarkers for MPM. TaqMan OpenArray was used to analyse over 700 microRNAs in PE cells and supernatants from 26 MPMs and 21 other PE-causing diseases. In PE cells, combining miR-143, miR-210, and miR-200c could differentiate MPM with an area under the curve (AUC) of 0.92. The three-microRNA signature could also discriminate MPM from a further 40 adenocarcinomas with an AUC of 0.9887. These results suggest that the expression of miR-143, miR-210, and miR-200c in PE cells might provide a signature for diagnosing MPM.

Construction of prognostic microRNA signature for human invasive breast cancer by integrated analysis.

BackgroundDespite the advances in early detection and treatment methods, breast cancer still has a high mortality rate, even in those patients predicted to have a good prognosis. The purpose of this study is to identify a microRNA signature that could better predict prognosis in breast cancer and add new insights to the current classification criteria.Materials and methodsWe downloaded microRNA sequencing data along with corresponding clinicopathological data from The Cancer Genome Atlas (TCGA). Of 1,098 breast cancer patients identified, 253 patients with fully characterized microRNA profiles were selected for analysis. A three-microRNA signature was generated in the training set. Subsequently, the performance of the signature was confirmed in a validation set. After construction of the signature, we conducted additional experiments, including flow cytometry and the Cell Counting Kit-8 assay, to illustrate the correlation of this microRNA signature with breast cancer cell cycle, apoptosis, and proliferation.ResultsThree microRNAs (hsa-mir-31, hsa-mir-16-2, and hsa-mir-484) were identified to be significantly and independently correlated with patient prognosis, and performed with good stability. Our results suggest that higher expression of hsa-mir-484 indicated worse prognosis, while higher expression of hsa-mir-31 and hsa-mir-16-2 indicated better prognosis. Moreover, additional experiments confirmed that this microRNA signature was related to breast cancer cell cycle and proliferation.ConclusionOur results indicate a three-microRNA signature that can accurately predict the prognosis of breast cancer, especially in basal-like and hormone receptor-positive breast cancer subtypes. We recommend more aggressive therapy and more frequent follow-up for high-risk groups.

A three-microRNA signature predicts clinical outcome in breast cancer patients.

Breast invasive carcinoma (BRCA) is a complex polygenic disease characterized by molecular and histological heterogeneity. An effort is underway to explore and investigate multiple reliable prognostic markers to improve management of BRCA patients and provide novel therapeutic targets. The aim of the study is to identify the prognostic miRNA signature in BRCA patients. The miRNA-sequencing data and clinical information of BRCA patients were downloaded from The Cancer Genome Atlas (TCGA) database. A total of 106 differentially expressed miRNAs were identified between BRCA tissues and matched normal tissues, including 81 up-regulated miRNAs and 25 down-regulated miRNAs. Then, we established a set of three-miRNA signature that was significantly associated with BRCA patients' survival. Using the prognostic three-miRNA signature, we classified the BRCA patients into high-risk and low-risk groups. Multivariate Cox regression demonstrated that the prognostic power of the three-miRNA signature was independent of other clinical variables. Functional enrichment analysis suggested that three prognostic miRNAs may be involved in known BRCA-related KEGG pathways and biological processes. We demonstrated that three-miRNA signature could be a potential biomarker for predicting clinical outcomes for BRCA patients.

Three-microRNA signature identified by bioinformatics analysis predicts prognosis of gastric cancer patients.

AIMTo identify multiple microRNAs (miRNAs) for predicting the prognosis of gastric cancer (GC) patients by bioinformatics analysis.METHODSThe original microarray dataset GSE93415, which included 20 GC and 20 tumor adjacent normal gastric mucosal tissues, was downloaded from the Gene Expression Omnibus database and used for screening differentially expressed miRNAs (DEMs). The cut-off criteria were P < 0.05 and fold change > 2.0. In addition, we acquired the miRNA expression profiles and clinical information of 361 GC patients from The Cancer Genome Atlas database to assess the prognostic role of the DEMs. The target genes of miRNAs were predicted using TargetScan, miRDB, miRWalk, and DIANA, and then the common target genes were selected for functional enrichment analysis.RESULTSA total of 110 DEMs including 19 up-regulated and 91 down-regulated miRNAs were identified between 20 pairs of GC and tumor adjacent normal tissues, and the Kaplan-Meier survival analysis found that a three-miRNA signature (miR-145-3p, miR-125b-5p, and miR-99a-5p) had an obvious correlation with the survival of GC patients. Furthermore, univariate and multivariate Cox regression analyses indicated that the three-miRNA signature could be a significant prognostic marker in GC patients. The common target genes of the three miRNAs are added up to 108 and used for Gene Functional Enrichment analysis. Biological Process and Molecular Function analyses showed that the target genes are involved in cell recognition, gene silencing and nucleic acid binding, transcription factor activity, and transmembrane receptor activity. Cellular Component analysis revealed that the genes are portion of nucleus, chromatin silencing complex, and TORC1/2 complex. Biological Pathway analysis indicated that the genes participate in several cancer-related pathways, such as the focal adhesion, PI3K, and mTOR signaling pathways.CONCLUSIONThis study justified that a three-miRNA signature could play a role in predicting the survival of GC patients.

A Three-MicroRNA Signature as a Potential Biomarker for the Early Detection of Oral Cancer.

Oral squamous cell carcinoma (OSCC) is often diagnosed at a late stage and may be malignantly transformed from oral leukoplakia (OL). This study aimed to identify potential plasma microRNAs (miRNAs) for the early detection of oral cancer. Plasma from normal, OL, and OSCC patients were evaluated. Small RNA sequencing was used to screen the differently expressed miRNAs among the groups. Next, these miRNAs were validated with individual samples by quantitative real-time polymerase chain reaction (qRT-PCR) assays in the training phase (n = 72) and validation phase (n = 178). The possible physiological roles of the identified miRNAs were further investigated using bioinformatics analysis. Three miRNAs (miR-222-3p, miR-150-5p, and miR-423-5p) were identified as differentially expressed among groups; miR-222-3p and miR-423-5p negatively correlated with T stage, lymph node metastasis status, and clinical stage. A high diagnostic accuracy (Area under curve = 0.88) was demonstrated for discriminating OL from OSCC. Bioinformatics analysis reveals that miR-423-5p and miR-222-3p are significantly over-expressed in oral cancer tissues and involved in various cancer pathways. The three-plasma miRNA panel may be useful to monitor malignant progression from OL to OSCC and as potential biomarkers for early detection of oral cancer.

A three-microRNA signature for lung squamous cell carcinoma diagnosis in Chinese male patients.

Various studies have demonstrated the diagnostic value of microRNA (miRNA) for lung cancer, but miRNA signatures varied between different subtypes. Whether serum miRNAs could be used as biomarkers in lung squamous cell carcinoma (SCC) remains unknown. Using quantitative real-time polymerase chain reaction (qRT-PCR) based Exiqon panel, 38 differentially expressed miRNAs were identified from 3 male lung SCC pool samples and 1 normal control (NC) pool in the initial screening phase. After the training (24 SCC VS. 15 NCs), testing (44 SCC VS. 57 NCs) and external validation (34 SCC VS. 36 NCs VS. 10 pulmonary hamartoma) processes via qRT-PCR, we identified a three-miRNA panel ((miR-106a-5p, miR-20a-5p and miR-93-5p) to be a potential diagnostic marker for male lung SCC patients. The areas under the receiver operating characteristic (ROC) curve of the three-miRNA panel for the training, testing and validation phases were 0.969, 0.881 and 0.954 respectively. In addition, this signature could also differentiate lung SCC from pulmonary hamartoma (AUC=0.900). The 3 miRNAs were consistently up-regulated in lung SCC tissues (23 SCC VS. 23 NCs) and serum exosomes (17 SCC VS. 24 NCs). Moreover, expression of the 3 miRNAs was decreased in arterial serum (n = 3). In conclusion, we established a three-miRNA signature in the peripheral serum with considerable clinical value in the diagnosis of male lung SCC patients.

A three-microRNA signature identifies two subtypes of glioblastoma patients with different clinical outcomes.

Glioblastoma multiforme (GBM) is the most common and malignant primary brain tumor in adults, characterized by aggressive growth, limited response to therapy, and inexorable recurrence. Because of the extremely unfavorable prognosis of GBM, it is important to develop more effective diagnostic and therapeutic strategies based on biologically and clinically relevant patient stratification systems. Analyzing a collection of patient‐derived GBM stem‐like cells (GSCs) by gene expression profiling, nuclear magnetic resonance spectroscopy, and signal transduction pathway activation, we identified two GSC clusters characterized by different clinical features. Due to the widely documented role played by microRNAs (miRNAs) in the tumorigenesis process, in this study we explored whether these two GBM patient subtypes could also be discriminated by different miRNA signatures. Global miRNA expression pattern was analyzed by oblique principal component analysis and principal component analysis. By a combined inferential strategy on PCA results, we identified a reduced set of three miRNAs – miR‐23a, miR‐27a, and miR‐9* (miR‐9‐3p) – able to discriminate the proneural‐ and mesenchymal‐like GSC phenotypes as well as mesenchymal and proneural subtypes of primary GBM included in The Cancer Genome Atlas (TCGA) data set. Kaplan–Meier analysis showed a significant correlation between the selected miRNAs and overall survival in 429 GBM specimens from TCGA‐identifying patients who had an unfavorable outcome. The survival prognostic capability of the three‐miRNA signatures could have important implications for the understanding of the biology of GBM subtypes and could be useful in patient stratification to facilitate interpretation of results from clinical trials.

A three-microRNA signature as a diagnostic and prognostic marker in clear cell renal cancer: An In Silico analysis.

Accumulating evidence has demonstrated that some specific miRNAs were aberrantly expressed in renal clear cell carcinoma and participated in many biological processes. The aim of this study was to investigate a panel of miRNA signature for diagnosis and prognosis of renal clear cell carcinoma (KIRC). Here, we performed a comprehensive analysis for miRNA expression profiles and corresponding clinical information of 516 KIRC patients from The Cancer Genome Atlas (TCGA). In the study, a total of 63 differentially expressed miRNAs were identified, of which 34 were up-regulated and 29 were down-regulated. We constructed a panel of three-miRNA that were significantly associated with KIRC diagnosis and KIRC patients' prognosis. The three-miRNA signature reached a sensitivity of 98.3% and a specificity of 97.2% in the diagnosis of KIRC. Using the three-miRNA signature, we classified the KIRC patients into high-risk group and low-risk group. The Kaplan- Meier curves showed that KIRC patients with high risk scores had significantly worsen overall survival (OS) and disease free survival (DFS) than KIRC patients with low risk scores. In the univariate and multivariate Cox regression analysis, three-miRNA signature was an independent prognostic factor in OS. In conclusion, the three-miRNA signature could be used as a diagnostic and prognostic biomarker in KIRC, and therefore, may help to provide significant clinical implication for the treatment of KIRC.

GPD1L is down-regulated by a three-microRNA signature in pancreatic cancer

Background: The prognosis of pancreatic ductal adenocarcinoma (PDAC) is very poor and its underlying mechanism is far from clear. Many studies show that PDAC has distinct microRNA signatures, but their target genes remain largely unknown. Methods: Reproducible candidate microRNA signature of PDAC from three highly cited studies was measured in 20 pairs of PDAC tissues and adjacent normal tissues. The target genes of candidate microRNAs were predicted by miRDB and validated by quantitative real-time PCR, western blot and 3'UTR luciferase assay. The prognostic association of target gene was analyzed using PROGgeneV2 Database. The effects of target gene on tumor phenotypes were evaluated with MTT assay, clone formation assay and Annexin V-FITC apoptosis assay. Results: Among the 5-microRNA panel, an up-regulation of 3-microRNA signature (miR155, miR181a and miR221) was validated in PDAC samples. The prediction of miRDB showed that the 3-microRNA signature shared four target genes: CREBRF, GABRA1, GPD1L and REPS2. GPD1L was down-regulated in PDAC and associated with poorer prognosis in three independent datasets (GSE21501, GSE28735 and GSE71729). In two PDAC cell lines, the 3-microRNA signature inhibited GPD1L expression through binding its 3'UTR and GPD1L reduction promoted cell proliferation and clone formation, and inhibited apoptosis. Conclusions: GPD1L as a novel target gene for a 3-microRNA signature and GPD1L might be an important therapeutic target in PDAC.

GPD1L is down-regulated by a three-microRNA signature in pancreatic cancer

Background: The prognosis of pancreatic ductal adenocarcinoma (PDAC) is very poor and its underlying mechanism is far from clear. Many studies show that PDAC has distinct microRNA signatures, but their target genes remain largely unknown.

Abstract A1-55: Combination of a three-microRNA signature and TP53 genotype predicts responses to platinum-based doublet chemotherapy in patients with lung adenocarcinoma

Abstract Platinum-based doublet, i.e., a combination of a platinum agent and another agent, is a standard regimen to treat non-small cell lung cancer, since molecular target therapy using tyrosine kinase inhibitors is effective only in a subset of patients with tumors with druggable oncogene mutations. Therefore, to identify biomarkers that can discriminate responders who received platinum-based chemotherapy before treatment is important to improve the efficacy of chemotherapy for non-small cell lung cancer. We found that a SNP in TP53 tumor suppressor gene, TP53-Arg72Pro is associated with response to the platinum-based doublet therapy (Shiraishi et al, JCO, 2010). We recently assessed intra-tumor micro (mi)RNA expression as a biomarker for predicting responses to platinum-based chemotherapy in patients with recurrent lung adenocarcinoma. Microarray-based screening of 904 miRNAs followed by quantitative reverse transcription-PCR-based verification in 40 test cohort samples, including 16 (40.0%) responders, was performed to identify miRNAs that are differentially expressed in chemotherapy responders and non-responders. Differential expression was confirmed in a validation cohort (n = 63 samples), including 18 (28.6%) responders. A signature comprising three miRNAs (miR1290, miR196b, and miR135a*) enabled the prediction of a chemotherapeutic response (rather than progression-free and overall survival) with high accuracy in both the test and validation cohorts (82.5% and 77.8%). Examination of the latter was performed using miRNAs extracted from archived formalin-fixed paraffin-embedded tissues. Genotype data for the TP53-Arg72Pro polymorphism, which is associated with responses to platinum-based doublet chemotherapy, were subsequently incorporated into the prediction analysis. Finally, combining this miRNA signature with the TP53-Arg72Pro polymorphism genotype marginally improved the predictive power (Saito et al., Clin. Cancer Res. 2014). Citation Format: Kouya Shiraishi, Motonobu Saito, Takashi Kohno. Combination of a three-microRNA signature and TP53 genotype predicts responses to platinum-based doublet chemotherapy in patients with lung adenocarcinoma. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-55.

A three-microRNA signature predicts responses to platinum-based doublet chemotherapy in patients with lung adenocarcinoma.

To examine the clinical utility of intratumor microRNAs (miRNA) as a biomarker for predicting responses to platinum-based doublet chemotherapy in patients with recurring lung adenocarcinoma (LADC). The expression of miRNAs was examined in LADC tissues surgically resected from patients treated with platinum-based doublet chemotherapy at the time of LADC recurrence. Microarray-based screening of 904 miRNAs followed by quantitative reverse transcription-PCR-based verification in 40 test cohort samples, including 16 (40.0%) responders, was performed to identify miRNAs that are differentially expressed in chemotherapy responders and nonresponders. Differential expression was confirmed in a validation cohort (n = 63 samples), including 18 (28.6%) responders. An miRNA signature that predicted responses to platinum-based doublet chemotherapy was identified and its accuracy was examined by principal component and support vector machine analyses. Genotype data for the TP53-Arg72Pro polymorphism, which is associated with responses to platinum-based doublet chemotherapy, were subsequently incorporated into the prediction analysis. A signature comprising three miRNAs (miR1290, miR196b, and miR135a*) enabled the prediction of a chemotherapeutic response (rather than progression-free and overall survival) with high accuracy in both the test and validation cohorts (82.5% and 77.8%). Examination of the latter was performed using miRNAs extracted from archived formalin-fixed paraffin-embedded tissues. Combining this miRNA signature with the TP53-Arg72Pro polymorphism genotype marginally improved the predictive power. The three-miRNA signature in surgically resected primary LADC tissues may by clinically useful for predicting responsiveness to platinum-based doublet chemotherapy in patients with LADC recurrence.

A three-microRNA signature for predicting survival in pancreatic cancer

A three-microRNA signature for predicting survival in pancreatic cancer

Use of a three-microRNA signature to discriminate prognostic groups in early-stage NSCLC patients in the IFCT-0002 trial.

7007 Background: No survival differences was observed between any arms in the 528 early stage NSCLC randomized patients of the IFCT-0002 phase III trial comparing two chemotherapy timing, all pre- vs. peri-operative, and two regimens, CDDP-Gem vs. CBDCA-Pac (V. Westeel, ASCO 2009). We hypothesized that microRNA (miRNA) expression profile could discriminate prognostic groups in these patients. Methods: Total RNA was extracted from 277 paraffin-embedded surgical macrodissected specimens. Expression of 17 miRNAs was successfully analyzed by Taqman qRT-PCR in 276 (99%) samples. Multivariate analysis with Cox model for overall survival (OS) was validated with a two-step bootstrap resampling analysis. Results: Low miR210 (under median) miR21, and miR15a, (under first quartile) expression significantly predicted a better survival when adjusted for stage and number of administered cycles, the two clinical variables influencing OS in multivariate analysis. A model including the three miRNAs discriminates three prognostic groups: Group 1: patients with the three miRNAs under the defined cut-off (n=129), Group 2: among the remaining patients, patients with miR21 under Q1, independently of the status of the two other miRNAs (n=82), and Group 3: all remaining patients (n=65). In univariate analysis, Group 1 showed the best OS (> 83 months), Group 2 intermediate OS (66 months), and Group 3 the worse OS (36 months, p=0.001, log-rank test). Adjusted HRs for OS with Group 3 as reference were 0.445, 95%CI [0.290-0.682], p=0.0002 and 0.632, 95%CI [0.406-0.986], p=0.043 for Group 1 and 2, respectively. Harrell’s concordance index of 0.83, 95%CI [0.67-0.95] showed a good predictive accuracy. A first bootstrap with 300 random resampling showed the stability of the miR model which significantly predicted OS in 260 samples (86.7%). The reproducibility of the model was confirmed by a second similar bootstrap procedure, the c-indexes of the created models ranging from 0.74 to 0.85. Conclusions: A miRNA model associating mIR15a, mIR21, and mIR210, accurately discriminates three prognostic groups in early-stage NSCLC patients treated by perioperative chemotherapy.