MicroRNAs involved in the HMGA2 deregulation and its co-occurrence with MED12 mutation in uterine leiomyoma.

STUDY QUESTION: Can the mediator complex subunit 12 (MED12) mutation and high mobility group AT-hook 2 (HMGA2) overexpression co-occurrence be explained by the alternative mechanism of HMGA2 dysregulation in uterine leiomyomas (UL)? SUMMARY ANSWER: The co-occurrence of MED12 mutation and HMGA2 overexpression, and a negative correlation of five validated or predicted microRNAs that target HMGA2 were reported. WHAT IS KNOWN ALREADY: The recent stratification of UL, according to recurrent and mutually exclusive genomic alterations affecting HMGA2, MED12, fumarate hydratase (FH) and collagen type IV alpha 5-alpha 6 (COL4A5-COL4A6) pointed out the involvement of distinct molecular pathways. However, the mechanisms of regulation involving these drivers are poorly explored. STUDY DESIGN, SIZE, DURATION: A total of 78 UL and 34 adjacent normal myometrium (NM) tissues was collected from 56 patients who underwent hysterectomies at a single institution. The patients were treated at the Department of Gynecology and Obstetrics, School of Medicine, Sao Paulo State University, Botucatu, SP, Brazil, from October 1995 to February 2004. PARTICIPANTS/MATERIALS, SETTING, METHODS: Gene expression profiling was evaluated from fresh frozen tissues and compared with MED12 mutations at exon 2. In addition, RT-qPCR was applied to evaluate the expression levels of HMGA2 and their predictive miRNA regulators: hsa-let-7a, miR-26a, miR-26b, mir-93 and mir-106b. MAIN RESULTS AND THE ROLE OF CHANCE: An unsupervised hierarchical clustering analysis revealed two main clusters with one of them (26 of 42 UL) showing an enrichment of MED12 mutated cases (18 of 26 UL). Increased expression levels of HMGA2 were observed in both clusters, including cases with MED12 mutation (cluster 1:18 UL). A significant HMGA2 overexpression (P < 0.001) in UL in comparison with NM was found. Five miRNAs predicted to regulate HMGA2 were significantly downregulated (P < 0.001) and negatively correlated to HMGA2 expression levels (P < 0.05) in UL. LIMITATIONS REASONS FOR CAUTION: An in vivo functional study was not performed to validate the microRNAs and HMGA2 interaction due to technical limitations. WIDER IMPLICATIONS OF THE FINDINGS: HMGA2 overexpression was detected in a significant number of MED12 mutated ULs, suggesting that these alterations coexist. Furthermore, five miRNAs were described as potential regulators of HMGA2 expression in UL. LARGE-SCALE DATA: Data available in the Gene Expression Omnibus GSE42939. STUDY FUNDING AND COMPETING INTEREST(S): This study was supported by grants from Fundação de Amparo a Pesquisa do Estado de São Paulo (# 2008/58835-2) and Conselho Nacional de Pesquisa (# 485032/2007-4), Brazil. The authors declared having no conflicts of interest.

Oncogenic drivers in 11q13 associated with prognosis and response to therapy in advanced oropharyngeal carcinomas.

OBJECTIVES: To identify potential molecular drivers associated with prognosis and response to treatment in advanced oropharyngeal squamous cell carcinomas (OPSCC). MATERIALS AND METHODS: Thirty-three OPSCC biopsies from untreated Brazilian patients were evaluated for human papilloma virus genotyping, genome wide copy number alterations and gene expression profiling. Data were integrated using CONEXIC algorithm. Validation with TCGA dataset and confirmation by RT-qPCR of candidate genes were performed. RESULTS: High-risk HPV positive cases, detected in 55% of advanced OPSCC, were associated with better outcome. Losses of 8p11.23-p11.22, 14q11.1-q11.2 and 15q11.2, and gains of 11q13.2 and 11q13.2-q13.3 were detected as recurrent alterations. Gains of 3q26.31 and 11q13.2 and losses of 9p21.3 were exclusively detected in HPV-negative tumors. Two clusters of expression profiles were observed, being one composed mostly by HPV positive cases (83%). HPV-positive enriched cluster showed predominantly immune response-related pathways. Integrative analysis identified 10 modulators mapped in 11q13, which were frequently cancer-related. These 10 genes showed copy number gains, overexpression and an association with worse survival, further validated by TCGA database analyses. Overexpression of four genes (ORAOV1, CPT1A, SHANK2 and PPFIA1) evaluated by RT-qPCR confirmed their association with poor survival. Multivariate analysis showed that PPFIA1 overexpression and HPV status are independent prognostic markers. Moreover, SHANK2 overexpression was significantly associated with incomplete response to treatment. CONCLUSION: The integrative genomic and transcriptomic data revealed potential driver genes mapped in 11q13 associated with worse prognosis and response to treatment, giving fundamentals for the identification of novel therapeutic targets in OPSCC.

Gene trio signatures as molecular markers to predict response to doxorubicin cyclophosphamide neoadjuvant chemotherapy in breast cancerpatients

In breast cancer patients submitted to neoadjuvant chemotherapy (4 cycles of doxorubicin and cyclophosphamide, AC), expression of groups of three genes (gene trio signatures) could distinguish responsive from non-responsive tumors, as demonstrated by cDNA microarray profiling in a previous study by our group. In the current study, we determined if the expression of the same genes would retain the predictive strength, when analyzed by a more accessible technique (real-time RT-PCR). We evaluated 28 samples already analyzed by cDNA microarray, as a technical validation procedure, and 14 tumors, as an independent biological validation set. All patients received neoadjuvant chemotherapy (4 AC). Among five trio combinations previously identified, defined by nine genes individually investigated (BZRP, CLPTM1,MTSS1, NOTCH1, NUP210, PRSS11, RPL37A, SMYD2, and XLHSRF-1), the most accurate were established by RPL37A, XLHSRF-1based trios, with NOTCH1 or NUP210. Both trios correctly separated 86 percent of tumors (87 percent sensitivity and 80 percent specificity for predicting response), according to their response to chemotherapy (82 percent in a leave-one-out cross-validation method). Using the pre-established features obtained by linear discriminant analysis, 71 percent samples from the biological validation set were also correctly classified by both trios (72 percent sensitivity; 66 percent specificity). Furthermore, we explored other gene combinations to achieve a higher accuracy in the technical validation group (as a training set). A new trio, MTSS1, RPL37 and SMYD2, correctly classified 93 percent of samples from the technical validation group (95 percent sensitivity and 80 percent specificity; 86 percent accuracy by the cross-validation method) and 79 percent from the biological validation group (72 percent sensitivity and 100 percent specificity). Therefore, the combined expression of MTSS1, RPL37 and SMYD2, as evaluated by real-time RT-PCR, is a potential candidate to predict response to neoadjuvant doxorubicin and cyclophosphamide in breast cancer patients.

Gene trio signatures as molecular markers to predict response to doxorubicin cyclophosphamide neoadjuvant chemotherapy in breast cancer patients.

In breast cancer patients submitted to neoadjuvant chemotherapy (4 cycles of doxorubicin and cyclophosphamide, AC), expression of groups of three genes (gene trio signatures) could distinguish responsive from non-responsive tumors, as demonstrated by cDNA microarray profiling in a previous study by our group. In the current study, we determined if the expression of the same genes would retain the predictive strength, when analyzed by a more accessible technique (real-time RT-PCR). We evaluated 28 samples already analyzed by cDNA microarray, as a technical validation procedure, and 14 tumors, as an independent biological validation set. All patients received neoadjuvant chemotherapy (4 AC). Among five trio combinations previously identified, defined by nine genes individually investigated (BZRP, CLPTM1, MTSS1, NOTCH1, NUP210, PRSS11, RPL37A, SMYD2, and XLHSRF-1), the most accurate were established by RPL37A, XLHSRF-1 based trios, with NOTCH1 or NUP210. Both trios correctly separated 86% of tumors (87% sensitivity and 80% specificity for predicting response), according to their response to chemotherapy (82% in a leave-one-out cross-validation method). Using the pre-established features obtained by linear discriminant analysis, 71% samples from the biological validation set were also correctly classified by both trios (72% sensitivity; 66% specificity). Furthermore, we explored other gene combinations to achieve a higher accuracy in the technical validation group (as a training set). A new trio, MTSS1, RPL37 and SMYD2, correctly classified 93% of samples from the technical validation group (95% sensitivity and 80% specificity; 86% accuracy by the cross-validation method) and 79% from the biological validation group (72% sensitivity and 100% specificity). Therefore, the combined expression of MTSS1, RPL37 and SMYD2, as evaluated by real-time RT-PCR, is a potential candidate to predict response to neoadjuvant doxorubicin and cyclophosphamide in breast cancer patients.