Objective: Oncogenic human papillomaviruses (HPVs) are the etiological agents of cervical cancer. Different cofactors might be needed for malignant transformation, but they still remain elusive. Methods: To delineate the role of Chlamydia trachomatis (CT) and herpes simplex virus type 2 (HSV2) in HPV-positive cervical intraepithelial neoplasia (CIN) lesions and cervical carcinoma a series of 149 cervical cancer and CIN biopsies were analyzed for CT and HSV2 DNA by PCR, and HPV genotyped by InnoLipa. Monitoring of aberrations in key intracellular pathways due to CT/HSV2 and HPV co-expression were analyzed with 13 biomarkers. Results: Of the 149 samples tested, 136 were HPV DNA positive; 32/136 contained also CT DNA and 29 HSV2 DNA. Detection of CT was significantly (p = 0.0001) related to multiple-type HPV infections, while HSV2 was of borderline significance (p = 0.053). Of the 13 biomarkers tested, cytoplasmic and nuclear NF-ĸB and VEGF-C were significantly increased in CT+/HPV+ lesions; p = 0.023, p = 0.045, and p = 0.020 as well as survivin, p = 0.026. Survivin was the only marker that was overexpressed also in HSV2+/HPV+ lesions, p = 0.027. Conclusions: CT infection favors the entry and persistence of multiple HR-HPV types, which leads to viral integration, inhibition of apoptosis, overexpression of E6/E7 oncogenes and cell transformation.

Background. Although Papanicolaou cytology represents the most effective technique to prevent and detect precancerous conditions of the uterine cervix, its false‐negative yield is still a reason of concern among pathologists and gynecologists. Methods. Because histologic control is one of the best ways to assess the accuracy of cytology diagnosis, the authors have investigated 1000 women who had cervical smears and tissue sampling obtained during the same colposcopic evaluation between 1987 and 1990. Results. Out of 1000 cases (average age, 34.6 years; range, 14–80 years), 918 had adequate, 62 had less than optimal, and 10 had unsatisfactory samples. Cytology unsatisfactory and less than optimal cases as well as inadequate histology cases have been disregarded from all calculations. After histologic comparison, confirmed negatives were 622 of 918 (67.8%). Cytologic diagnoses of cervical intra‐epithelial neoplasia (CIN) I were 96, of CIN II were 44, of CIN III, inclusive of carcinoma in situ, were 39, and of invasive carcinoma were 2. Atypical cases were 56. The overall sensitivity was 76.3%, with group sensitivity rates increasing directly with CIN grade. Positive predictive value was 80.2%. Specificity was 93.0%, and negative predictive value was 91.3%. False‐negatives were 59 of 681 (8.7%), basically due to sampling errors. Among true‐positives, there was 1 category discrepancy in 30 cases (mostly undercalled or overcalled CIN II) and 2 category discrepancies in 4 cases. Conclusions. Cervical cytology has an overall accuracy close to that reported in studies employing indirect control methods, such as patient follow‐up. Higher sensitivity rates emerged for CIN II, CIN III, and cervical carcinoma. Our figures of sensitivity and specificity may represent a useful reference source for future studies dealing with quality control in cervical cytopathology.

High- and low-grade cervical lesions were analyzed for the presence of polyomavirus (PYV) and human papillomavirus (HPV) sequences. In precancerous cervical lesions, the overall prevalence of PYV sequences was 44% (41/93). Specifically, among the PYV-positive samples, 83% (34/41) tested positive for BK polyomavirus (BKV) sequences, whereas 17% (7/41) were positive for JC-virus. None of the samples were positive for simian virus 40. The presence of BKV DNA in high-grade squamous intraepithelial lesions was confirmed by in situ PCR. BKV sequences were detected more frequently in high-grade squamous intraepithelial lesions, together with the genotype HPV-16. The association of BKV with precancerous cervical lesions suggests that this polyomavirus participates with HPV-16 in the cell transformation process. Alternatively, BKV might multiply better in HPV-16-positive cells from precancerous cervical lesions than in HPV-16-negative cells.

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Molecular tests predicting the outcome of breast cancer patients based on gene expression levels can be used to assist in making treatment decisions after consideration of conventional markers. In this study we identified a subset of 20 mRNA differentially regulated in breast cancer analyzing several publicly available array gene expression data using R/Bioconductor package. Using RTqPCR we evaluate 261 consecutive invasive breast cancer cases not selected for age, adjuvant treatment, nodal and estrogen receptor status from paraffin embedded sections. The biological samples dataset was split into a training (137 cases) and a validation set (124 cases). The gene signature was developed on the training set and a multivariate stepwise Cox analysis selected five genes independently associated with DFS: FGF18 (HR = 1.13, p = 0.05), BCL2 (HR = 0.57, p = 0.001), PRC1 (HR = 1.51, p = 0.001), MMP9 (HR = 1.11, p = 0.08), SERF1a (HR = 0.83, p = 0.007). These five genes were combined into a linear score (signature) weighted according to the coefficients of the Cox model, as: 0.125FGF18 − 0.560BCL2 + 0.409PRC1 + 0.104MMP9 − 0.188SERF1A (HR = 2.7, 95% CI = 1.9–4.0, p < 0.001). The signature was then evaluated on the validation set assessing the discrimination ability by a Kaplan Meier analysis, using the same cut offs classifying patients at low, intermediate or high risk of disease relapse as defined on the training set (p < 0.001). Our signature, after a further clinical validation, could be proposed as prognostic signature for disease free survival in breast cancer patients where the indication for adjuvant chemotherapy added to endocrine treatment is uncertain.