MYC functions are specific in biological subtypes of breast cancer and confers resistance to endocrine therapy in luminal tumours.

BACKGROUND: MYC is amplified in approximately 15% of breast cancers (BCs) and is associated with poor outcome. c-MYC protein is multi-faceted and participates in many aspects of cellular function and is linked with therapeutic response in BCs. We hypothesised that the functional role of c-MYC differs between molecular subtypes of BCs. METHODS: We therefore investigated the correlation between c-MYC protein expression and other proteins involved in different cellular functions together with clinicopathological parameters, patients' outcome and treatments in a large early-stage molecularly characterised series of primary invasive BCs (n=1106) using immunohistochemistry. The METABRIC BC cohort (n=1980) was evaluated for MYC mRNA expression and a systems biology approach utilised to identify genes associated with MYC in the different BC molecular subtypes. RESULTS: High MYC and c-MYC expression was significantly associated with poor prognostic factors, including grade and basal-like BCs. In luminal A tumours, c-MYC was associated with ATM (P=0.005), Cyclin B1 (P=0.002), PIK3CA (P=0.009) and Ki67 (P<0.001). In contrast, in basal-like tumours, c-MYC showed positive association with Cyclin E (P=0.003) and p16 (P=0.042) expression only. c-MYC was an independent predictor of a shorter distant metastases-free survival in luminal A LN+ tumours treated with endocrine therapy (ET; P=0.013). In luminal tumours treated with ET, MYC mRNA expression was associated with BC-specific survival (P=0.001). In ER-positive tumours, MYC was associated with expression of translational genes while in ER-negative tumours it was associated with upregulation of glucose metabolism genes. CONCLUSIONS: c-MYC function is associated with specific molecular subtypes of BCs and its overexpression confers resistance to ET. The diverse mechanisms of c-MYC function in the different molecular classes of BCs warrants further investigation particularly as potential therapeutic targets

nm23-H1 expression and loss of heterozygosity in colon adenocarcinoma

Background: The discovery that genetic alterations in oncogenes and tumour suppressor genes accompany tumour formation in many human tumours has encouraged the search for genes that promote or suppress tumour spread and metastasis; nm23 is a promising candidate for a metastasis suppressing gene. Aims: To evaluate whether expression of nm23-H1 protein or loss of heterozygosity (LOH) of the nm23-H1 gene is associated with colon cancer progression. Materials/Methods: Paraffin wax embedded tissue sections were analysed immunohistochemically. DNA isolated from normal and tumour tissue was used for LOH analysis using a variable nucleotide tandem repeat (VNTR) marker located in the untranslated 5′ region of the nm23-H1 gene. RNA isolated from tumour and normal tissue was used for “real time” RT-PCR. Results: Of 102 adenocarcinomas examined, 58.8% stained weakly for nm23-H1 protein. There was a negative correlation between nm23-H1 positivity and tumour histological grade. In VNTR analysis, 70.2% of patients were informative and 27.4% of tumours had nm23-H1 LOH. There was a positive correlation between nm23-H1 LOH and both tumour histological grade and Dukes’s stage. Expression of nm23-H1 mRNA was increased in 22 of 30 colon tumours compared with normal tissue. No significant correlation was found between nm23-H1 mRNA expression and histological grade or Dukes’s stage of tumours. Conclusions: These findings suggest that nm23-H1 protein expression in early stages may have a role in suppressing metastasis in sporadic colon cancer, whereas at a later stage both reduced nm23-H1 protein expression and LOH of the nm23-H1 gene may play role in colon cancer progression and metastasis

Molecular genetic alterations of FHIT and p53 genes in benign and malignant thyroid gland lesions

Several oncogenes and tumor-suppressor genes are involved either as early or late event in thyroid gland carcinogenesis. Human FHIT (fragile histidine triad) gene is highly conserved gene whose loss of function may be important in the development and/or progression of various types of cancer. We undertook this study to analyze FHIT and p53 gene status in different benignant and malignant thyroid tumors. Status of these genes as well as intensity of apoptosis was analyzed in tumor tissues by molecular genetic methods, immunohistochemistry, and FACS-scan analysis. The majority of the malignant thyroid cancers displayed aberrant expression of FHIT gene, concominant with p53 gene inactivation. This is followed by low rate of apoptosis, which may be important in the development and/or progression of thyroid cancer. We found higher incidence of p53 mutation and aberrant processing of FHIT mRNA in malignant tumors (papillary, follicular, medullary and anaplastic carcinomas) and i! n those tumors with distant metastasis. The growth of p53(-)/FHIT- follicular carcinoma of human origin was much faster in nude mice than p53(+)/FHIT- follicular carcinoma, and mice had shorter survival rate. Our results show a correlation between aberrant FHIT and p53 expression, low rate of apoptosis, and malignancy. Concomitant aberration of FHIT gene and p53 could be responsible for development of highly malignant types of thyroid cancer and may be considered as a prognostic marker for these tumors

On indexing in the Web of Science and predicting journal impact factor

We discuss what document types account for the calculation of the journal impact factor (JIF) as published in the Journal Citation Reports (JCR). Based on a brief review of articles discussing how to predict JIFs and taking data differences between the Web of Science (WoS) and the JCR into account, we make our own predictions. Using data by cited-reference searching for Thomson Scientific’s WoS, we predict 2007 impact factors (IFs) for several journals, such as Nature, Science, Learned Publishing and some Library and Information Sciences journals. Based on our colleagues’ experiences we expect our predictions to be lower bounds for the official journal impact factors. We explain why it is useful to derive one’s own journal impact factor