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The most used methodologies for HPV genotyping in Tunisian studies are based on hybridization that are limited to a restricted number of HPV types and to a lack of specificity and sensitivity for same types. Recently, Next-Generation sequencing (NGS) technology has been efficiently used for HPV genotyping. In this work we designed and validated a sensitive genotyping method based on nested PCR followed by NGS. Eighty-six samples were tested for the validation of an HPV genotyping assay based on Nested-PCR followed by NGS. These include, 43 references plasmids and 43 positive HPV clinical cervical specimens previously evaluated with the conventional genotyping method: Reverse Line Hybridization (RLH). Results of genotyping using NGS were compared to those of RLH. The analytical sensitivity of the NGS assay was 1GE/μl per sample. The NGS allowed the detection of all HPV types presented in references plasmids. On the clinical samples, a total of 19 HPV types were detected versus 14 types using RLH. Besides the identification of more HPV types in multiple infection (6 types for NGS versus 4 for RLH), NGS allowed the identification of HPV types that were not detected by RLH. In addition, the NGS assay detected newly HPV types that were not described in Tunisia so far: HPV81, HPV43, HPV74, and HPV62. The high sensitivity and specificity of NGS for HPV genotyping in addition to the identification of new HPV types may justify the use of such technique to provide with high accuracy the profile of circulating types in epidemiological studies.

BackgroundA major challenge in oncology is the selection of the most effective chemotherapeutic agents for individual patients, while the administration of ineffective chemotherapy increases mortality and decreases quality of life in cancer patients. This emphasizes the need to evaluate every patient's probability of responding to each chemotherapeutic agent and limiting the agents used to those most likely to be effective.Methods and resultsUsing gene expression data on the NCI-60 and corresponding drug sensitivity, mRNA and microRNA profiles were developed representing sensitivity to individual chemotherapeutic agents. The mRNA signatures were tested in an independent cohort of 133 breast cancer patients treated with the TFAC (paclitaxel, 5-fluorouracil, adriamycin, and cyclophosphamide) chemotherapy regimen. To further dissect the biology of resistance, we applied signatures of oncogenic pathway activation and performed hierarchical clustering. We then used mRNA signatures of chemotherapy sensitivity to identify alternative therapeutics for patients resistant to TFAC. Profiles from mRNA and microRNA expression data represent distinct biologic mechanisms of resistance to common cytotoxic agents. The individual mRNA signatures were validated in an independent dataset of breast tumors (P = 0.002, NPV = 82%). When the accuracy of the signatures was analyzed based on molecular variables, the predictive ability was found to be greater in basal-like than non basal-like patients (P = 0.03 and P = 0.06). Samples from patients with co-activated Myc and E2F represented the cohort with the lowest percentage (8%) of responders. Using mRNA signatures of sensitivity to other cytotoxic agents, we predict that TFAC non-responders are more likely to be sensitive to docetaxel (P = 0.04), representing a viable alternative therapy.ConclusionsOur results suggest that the optimal strategy for chemotherapy sensitivity prediction integrates molecular variables such as ER and HER2 status with corresponding microRNA and mRNA expression profiles. Importantly, we also present evidence to support the concept that analysis of molecular variables can present a rational strategy to identifying alternative therapeutic opportunities.

textabstractPurpose. To define the biology driving the aggressive nature of breast cancer arising in young women. Experimental Design. Among 784 patients with early stage breast cancer, using prospectively-defined, age-specific cohorts (young ≤45 years; older ≥65 years), 411 eligible patients (n = 200≤545 years; n = 211≥65 years) with clinically-annotated Affymetrix microarray data were identified. GSEA, signatures of oncogenic pathway deregulation and predictors of chemotherapy sensitivity were evaluated within the two age-defined cohorts. Results. In comparing deregulation of oncogenic pathways between age groups, a higher probability of P13K (p = 0.006) and Myc (p = 0.03) pathway deregulation was observed in breast tumors arising in younger women. When evaluating unique patterns of pathway deregulation, a low probability of Src and E2F deregulation in tumors of younger women, concurrent with a higher probability of P13K, Myc, and β-catenin, conferred a worse prognosis (HR = 4.15). In contrast, a higher probability of Src and E2F pathway activation in tumors of older women, with concurrent low probability of P13K, Myc and β-catenin deregulation, was associated with poorer outcome (HR = 2.7). In multivariate analyses, genomic clusters of pathway deregulation illustrate prognostic value. Conclusion. Results demonstrate that breast cancer arising in young women represents a distinct biologic entity characterized by unique patterns of deregulated signaling pathways that are prognostic, independent of currently available clinico-pathologic variables. These results should enable refinement of targeted treatment strategies in this clinically challenging situation. Copyright.