Absence of annexin I expression in B-cell non-Hodgkin's lymphomas and cell lines

BACKGROUND: Annexin I, one of the 20 members of the annexin family of calcium and phospholipid-binding proteins, has been implicated in diverse biological processes including signal transduction, mediation of apoptosis and immunosuppression. Previous studies have shown increased annexin I expression in pancreatic and breast cancers, while it is absent in prostate and esophageal cancers. RESULTS: Data presented here show that annexin I mRNA and protein are undetectable in 10 out of 12 B-cell lymphoma cell lines examined. Southern blot analysis indicates that the annexin I gene is intact in B-cell lymphoma cell lines. Aberrant methylation was examined as a cause for lack of annexin I expression by treating cells 5-Aza-2-deoxycytidine. Reexpression of annexin I was observed after prolonged treatment with the demethylating agent indicating methylation may be one of the mechanisms of annexin I silencing. Treatment of Raji and OMA-BL-1 cells with lipopolysaccharide, an inflammation inducer, and with hydrogen peroxide, a promoter of oxidative stress, also failed to induce annexin I expression. Annexin I expression was examined in primary lymphoma tissues by immunohistochemistry and presence of annexin I in a subset of normal B-cells and absence of annexin I expression in the lymphoma tissues were observed. These results show that annexin I is expressed in normal B-cells, and its expression is lost in all primary B-cell lymphomas and 10 of 12 B-cell lymphoma cell lines. CONCLUSIONS: Our results suggest that, similar to prostate and esophageal cancers, annexin I may be an endogenous suppressor of cancer development, and loss of annexin I may contribute to B-cell lymphoma development

CIP2A expression predicts recurrences of tamoxifen-treated breast cancer

CIP2A is emerging as an oncoprotein overexpressed commonly across many tumours and generally correlated with higher tumour grade and therapeutic resistance. CIP2A drives an oncogenic potential through inhibiting protein phosphatase 2A, stabilizing MYC, and promoting epithelial-to-mesenchymal transition, although further biological mechanisms for CIP2A are yet to be defined. CIP2A protein expression was studied by immunohistochemistry in oestrogen receptor–positive primary breast cancers (n = 250) obtained from the Leeds Tissue Bank. In total, 51 cases presented with a relapse or metastasis during adjuvant treatment with tamoxifen and were regarded as tamoxifen resistant. CIP2A expression was scored separately for cytoplasmic, nuclear, or membranous staining, and scores were tested for statistically significant relationships with clinicopathological features. Membranous CIP2A was preferentially expressed in cases who experienced a recurrence during tamoxifen treatment thus predicting a worse overall survival (log rank = 8.357, p = 0.004) and disease-free survival (log rank = 21.766, p < 0.001). Cox multivariate analysis indicates that it is an independent prognostic indicator for overall survival (hazard ratio = 4.310, p = 0.013) and disease-free survival (hazard ratio = 5.449, p = 0.002). In this study, we propose the assessment of membranous CIP2A expression as a potential novel prognostic and predictive indicator for tamoxifen resistance and recurrence within oestrogen receptor–positive breast cancer

‘1-8 interferon inducible gene family': putative colon carcinoma-associated antigens

Db−/−xβ2 microglobulin (β2m) null mice transgenic for a chimeric HLA-A2.1/Db-β2m single chain (HHD mice) are an effective biological tool to evaluate the antitumour cytotoxic T-lymphocyte response of known major histocompatibility-restricted peptide tumour-associated antigens, and to screen for putative unknown novel peptides. We utilised HHD lymphocytes to identify immunodominant epitopes of colon carcinoma overexpressed genes. We screened with HHD-derived lymphocytes over 500 HLA-A2.1-restricted peptides derived from colon carcinoma overexpressed genes. This procedure culminated in the identification of seven immunogenic peptides, three of these were derived from the ‘human 1-8D gene from interferon inducible gene' (1-8D). The 1-8D gene was shown to be overexpressed in fresh tumour samples. The three 1-8D peptides were both antigenic and immunogenic in the HHD mice. The peptides induce cytotoxic T lymphocytes that were able to kill a colon carcinoma cell line HCT/HHD, in vitro and retard its growth in vivo. One of the peptides shared by all the 1-8 gene family primed efficiently normal human cytotoxic T lymphocyte precursors. These results highlight the 1-8D gene and its homologues as putative immunodominant tumour-associated antigens of colon carcinoma

Gut Microbiota, Probiotics and Diabetes

Diabetes is a condition of multifactorial origin, involving several molecular mechanisms related to the intestinal microbiota for its development. In type 2 diabetes, receptor activation and recognition by microorganisms from the intestinal lumen may trigger inflammatory responses, inducing the phosphorylation of serine residues in insulin receptor substrate-1, reducing insulin sensitivity. In type 1 diabetes, the lowered expression of adhesion proteins within the intestinal epithelium favours a greater immune response that may result in destruction of pancreatic β cells by CD8+ T-lymphocytes, and increased expression of interleukin-17, related to autoimmunity. Research in animal models and humans has hypothesized whether the administration of probiotics may improve the prognosis of diabetes through modulation of gut microbiota. We have shown in this review that a large body of evidence suggests probiotics reduce the inflammatory response and oxidative stress, as well as increase the expression of adhesion proteins within the intestinal epithelium, reducing intestinal permeability. Such effects increase insulin sensitivity and reduce autoimmune response. However, further investigations are required to clarify whether the administration of probiotics can be efficiently used for the prevention and management of diabetes

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases