BackgroundSpy1 is a novel 'cyclin-like' activator of the G1/S transition capable of enhancing cell proliferation as well as inhibiting apoptosis. Spy1 protein levels are tightly regulated during normal mammary development and forced overexpression in mammary mouse models accelerates mammary tumorigenesis.MethodsUsing human tissue samples, cell culture models and in vivo analysis we study the implications of Spy1 as a mediator of mammary transformation and breast cancer proliferation.ResultsWe demonstrate that this protein can facilitate transformation in a manner dependent upon the activation of the G2/M Cdk, Cdk1, and the subsequent inhibition of the anti-apoptotic regulator FOXO1. Importantly, we show for the first time that enhanced levels of Spy1 protein are found in a large number of human breast cancers and that knockdown of Spy1 impairs breast cancer cell proliferation.ConclusionsCollectively, this work supports that Spy1 is a unique activator of Cdk1 in breast cancer cells and may represent a valuable drug target and/or a prognostic marker for subsets of breast cancers.

BackgroundThe newly discovered metastasis-associated in colon cancer-1 (MACC1) gene is a key regulator of the HGF/MET pathway. Deregulation of HGF/MET signaling is reported as a prognostic marker for tumorigenesis, early stage invasion, and metastasis. High expression levels of MACC1 have been associated with colon cancer metastasis and reduced survival. Potential links between the genetic diversity of the MACC1 locus and overall survival are unknown. We therefore investigated the association between MACC1 tagging single nucleotide polymorphisms (SNPs) and overall survival in a large cohort of colorectal cancer patients.MethodsThe study included 318 subjects with histopathologically proven colorectal cancer at the Academic Teaching Hospital Feldkirch, Austria. Survival data were provided by the federal agency for statistics in Austria. Genomic DNA was isolated from formalin-fixed paraffin-embedded specimens; six tagging SNPs (rs1990172, rs3114446, rs10275612, rs3095007, rs3095009, and rs7780032), capturing most of the common variants of the MACC1 locus, were genotyped by SNaPshot assays.ResultsOver a mean follow up period of 5.3 (± 1.0) years, 94 deaths were recorded. Carriers of the G-allele of SNP rs1990172 showed a significantly decreased overall survival (additive HR = 1.38 [1.05-1.82]; p = 0.023). Multivariate analysis adjusted for age and UICC tumor stage confirmed this result (HR = 1.49 [1.12-1.98]; p = 0.007). Other investigated genetic variants of the MACC1 gene were not significantly associated with overall survival (p-values > 0.05).ConclusionsFor the first time, our study investigated the influence of MACC1 tagging polymorphisms on overall survival suggesting SNP rs1990172 as a predictor for reduced overall survival in colorectal cancer patients. Further studies will be required to validate our findings.

BackgroundThe prognosis of human glioma is poor, and the highly invasive nature of the disease represents a major impediment to current therapeutic modalities. The oncoprotein B-cell-specific Moloney murine leukemia virus integration site 1 protein (Bmi-1) has been linked to the development and progression of glioma; however, the biological role of Bmi-1 in the invasion of glioma remains unclear.MethodsA172 and LN229 glioma cells were engineered to overexpress Bmi-1 via stable transfection or to be silenced for Bmi-1 expression using RNA interfering method. Migration and invasiveness of the engineered cells were assessed using wound healing assay, Transwell migration assay, Transwell matrix penetration assay and 3-D spheroid invasion assay. MMP-9 expression and activity were measured using real-time PCR, ELISA and the gelatin zymography methods. Expression of NF-kappaB target genes was quantified using real-time PCR. NF-kappaB transcriptional activity was assessed using an NF-kappaB luciferase reporter system. Expression of Bmi-1 and MMP-9 in clinical specimens was analyzed using immunohistochemical assay.ResultsEctopic overexpression of Bmi-1 dramatically increased, whereas knockdown of endogenous Bmi-1 reduced, the invasiveness and migration of glioma cells. NF-kappaB transcriptional activity and MMP-9 expression and activity were significantly increased in Bmi-1-overexpressing but reduced in Bmi-1-silenced cells. The reporter luciferase activity driven by MMP-9 promoter in Bmi-1-overexpressing cells was dependent on the presence of a functional NF-kappaB binding site, and blockade of NF-kappaB signaling inhibited the upregulation of MMP-9 in Bmi-1 overexpressing cells. Furthermore, expression of Bmi-1 correlated with NF-kappaB nuclear translocation as well as MMP-9 expression in clinical glioma samples.ConclusionsBmi-1 may play an important role in the development of aggressive phenotype of glioma via activating the NF-kappaB/MMP-9 pathway and therefore might represent a novel therapeutic target for glioma.

BackgroundTo evaluate the feasibility of image-guided radiotherapy based on helical Tomotherapy to spare the contralateral parotid gland in head and neck cancer patients with unilateral or no neck node metastases.MethodsA retrospective review of 52 patients undergoing radiotherapy for head and neck cancers with image guidance based on daily megavoltage CT imaging with helical tomotherapy was performed.ResultsMean contralateral parotid dose and the volume of the contralateral parotid receiving 40 Gy or more were compared between radiotherapy plans with significant constraint (SC) of less than 20 Gy on parotid dose (23 patients) and the conventional constraint (CC) of 26 Gy (29 patients). All patients had PTV coverage of at least 95% to the contralateral elective neck nodes. Mean contralateral parotid dose was, respectively, 14.1 Gy and 24.7 Gy for the SC and CC plans (p < 0.0001). The volume of contralateral parotid receiving 40 Gy or more was respectively 5.3% and 18.2% (p < 0.0001)ConclusionTomotherapy for head and neck cancer minimized radiotherapy dose to the contralateral parotid gland in patients undergoing elective node irradiation without sacrificing target coverage.

BackgroundHealth-related quality of life (HRQOL) assessment is a key component of clinical oncology trials. However, few breast cancer trials comparing adjuvant conventional radiotherapy (CR) and hypofractionated tomotherapy (TT) have investigated HRQOL. We compared HRQOL in stage I-II breast cancer patients who were randomized to receive either CR or TT. Tomotherapy uses an integrated computed tomography scanner to improve treatment accuracy, aiming to reduce the adverse effects of radiotherapy.MethodsA total of 121 stage I–II breast cancer patients who had undergone breast conserving surgery (BCS) or mastectomy (MA) were randomly assigned to receive either CR or TT. CR patients received 25 × 2 Gy over 5 weeks, and BCS patients also received a sequential boost of 8 × 2 Gy over 2 weeks. TT patients received 15 × 2.8 Gy over 3 weeks, and BCS patients also received a simultaneous integrated boost of 15 × 0.6 Gy over 3 weeks. Patients completed the EORTC QLQ-C30 and BR23 questionnaires. The mean score (± standard error) was calculated at baseline, the end of radiotherapy, and at 3 months and 1, 2, and 3 years post-radiotherapy. Data were analyzed by the 'intention-to-treat' principle.ResultsOn the last day of radiotherapy, patients in both treatment arms had decreased global health status and functioning scores; increased fatigue (clinically meaningful in both treatment arms), nausea and vomiting, and constipation; decreased arm symptoms; clinically meaningful increased breast symptoms in CR patients and systemic side effects in TT patients; and slightly decreased body image and future perspective.At 3 months post-radiotherapy, TT patients had a clinically significant increase in role- and social-functioning scores and a clinically significant decrease in fatigue. The post-radiotherapy physical-, cognitive- and emotional-functioning scores improved faster in TT patients than CR patients. TT patients also had a better long-term recovery from fatigue than CR patients. ANOVA with the Bonferroni correction did not show any significant differences between groups in HRQOL scores.ConclusionsTT patients had a better improvement in global health status and role- and cognitive-functioning, and a faster recovery from fatigue, than CR patients. These results suggest that a shorter fractionation schedule may reduce the adverse effects of treatment.

BackgroundMalignancies arising in the large bowel cause the second largest number of deaths from cancer in the Western World. Despite progresses made during the last decades, colorectal cancer remains one of the most frequent and deadly neoplasias in the western countries.MethodsA genomic study of human colorectal cancer has been carried out on a total of 31 tumoral samples, corresponding to different stages of the disease, and 33 non-tumoral samples. The study was carried out by hybridisation of the tumour samples against a reference pool of non-tumoral samples using Agilent Human 1A 60-mer oligo microarrays. The results obtained were validated by qRT-PCR. In the subsequent bioinformatics analysis, gene networks by means of Bayesian classifiers, variable selection and bootstrap resampling were built. The consensus among all the induced models produced a hierarchy of dependences and, thus, of variables.ResultsAfter an exhaustive process of pre-processing to ensure data quality--lost values imputation, probes quality, data smoothing and intraclass variability filtering--the final dataset comprised a total of 8, 104 probes. Next, a supervised classification approach and data analysis was carried out to obtain the most relevant genes. Two of them are directly involved in cancer progression and in particular in colorectal cancer. Finally, a supervised classifier was induced to classify new unseen samples.ConclusionsWe have developed a tentative model for the diagnosis of colorectal cancer based on a biomarker panel. Our results indicate that the gene profile described herein can discriminate between non-cancerous and cancerous samples with 94.45% accuracy using different supervised classifiers (AUC values in the range of 0.997 and 0.955).