The Transcriptomic Response of the Murine Thyroid Gland to Iodide Overload and the Role of the Nrf2 Antioxidant System.

Thyroid follicular cells have physiologically high levels of reactive oxygen species because oxidation of iodide is essential for the iodination of thyroglobulin (Tg) during thyroid hormone synthesis. Thyroid follicles (the functional units of the thyroid) also utilize incompletely understood autoregulatory mechanisms to defend against exposure to excess iodide. To date, no transcriptomic studies have investigated these phenomena in vivo. Nuclear erythroid factor 2 like 2 (Nrf2 or Nfe2l2) is a transcription factor that regulates the expression of numerous antioxidant and other cytoprotective genes. We showed previously that the Nrf2 pathway regulates the antioxidant defense of follicular cells, as well as Tg transcription and Tg iodination. We, thus, hypothesized that Nrf2 might be involved in the transcriptional response to iodide overload. C57BL6/J wild-type (WT) or Nrf2 knockout (KO) male mice were administered regular water or water supplemented with 0.05% sodium iodide for seven days. RNA from their thyroids was prepared for next-generation RNA sequencing (RNA-Seq). Gene expression changes were assessed and pathway analyses were performed on the sets of differentially expressed genes. Analysis of differentially expressed messenger RNAs (mRNAs) indicated that iodide overload upregulates inflammatory-, immune-, fibrosis- and oxidative stress-related pathways, including the Nrf2 pathway. Nrf2 KO mice showed a more pronounced inflammatory-autoimmune transcriptional response to iodide than WT mice. Compared to previously published datasets, the response patterns observed in WT mice had strong similarities with the patterns typical of Graves' disease and papillary thyroid carcinoma (PTC). Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) also responded to iodide overload, with the latter targeting mRNAs that participate mainly in inflammation pathways. Iodide overload induces the Nrf2 cytoprotective response and upregulates inflammatory, immune, and fibrosis pathways similar to autoimmune hyperthyroidism (Graves' disease) and PTC

Clusterin overexpression in mice exacerbates diabetic phenotypes but suppresses tumor progression in a mouse melanoma model

Clusterin (CLU) is an ATP-independent small heat shock protein-like chaperone, which functions both intra- and extra-cellularly. Consequently, it has been functionally involved in several physiological (including aging), as well as in pathological conditions and most age-related diseases, e.g., cancer, neurodegeneration, and metabolic syndrome. To address CLU function at an in vivo model we established CLU transgenic (Tg) mice bearing ubiquitous or pancreas-targeted CLU overexpression (OE). Our downstream analyses in established Tg lines showed that ubiquitous or pancreas-targeted CLU OE in mice affected antioxidant, proteostatic and metabolic pathways. Targeted OE of CLU in the pancreas, which also resulted in CLU upregulation in the liver likely via systemic effects, increased basal glucose levels in the circulation and exacerbated diabetic phenotypes. Furthermore, by establishing a syngeneic melanoma mouse tumor model we found that ubiquitous CLU OE suppressed melanoma cells growth, indicating a likely tumor suppressor function in early phases of tumorigenesis. Our observations provide in vivo evidence corroborating the notion that CLU is a potential modulator of metabolic and/or proteostatic pathways playing an important role in diabetes and tumorigenesis

Zinc and ageing: third Zincage conference

The importance of Zn for optimal functioning of the immune system and antioxidant stress response is well documented. Zn homeostasis influences development and function of immune cells, activity of stress-related and antioxidant proteins [metallothioneins (MT), chaperones, ApoJ, Poly(ADP-Ribose) polymerase-1 (PARP-1) and Methionione Sulfoxide Reductase (Msr), Superoxide Dismutase (SOD)], and helps to maintain genomic integrity and stability. During ageing, the intake of Zn decreases due to inadequate diet and/or intestinal malabsorption, contributing to frailty, general disability and increased incidence of age-related degenerative diseases (cancer, infections and atherosclerosis). Although many factors contributing to Zn deficiency have been identified, the biochemical markers of Zn deficiency as well as the possibility to achieve relevant health benefits through Zn supplementation in the elderly are still a matter for evaluation. Taking into account that Zn homeostasis is regulated by proteins and enzymes for which polymorphisms have been previously found to be associated with successful/unsuccessful ageing, genetic screening might be of added value in evaluating the individual response to Zn supplementation. Biochemical, immunological, dietary and genetic studies aimed at understanding the impact of Zn in healthy ageing, the effect of Zn supplementation in the elderly and finally formulating a rationale for the promotion of correct Zn supplementation were discussed at the international Zincage conference held in Ancona in January 2007

Gene expression profiling in sinonasal adenocarcinoma

<p>Abstract</p> <p>Background</p> <p>Sinonasal adenocarcinomas are uncommon tumors which develop in the ethmoid sinus after exposure to wood dust. Although the etiology of these tumors is well defined, very little is known about their molecular basis and no diagnostic tool exists for their early detection in high-risk workers.</p> <p>Methods</p> <p>To identify genes involved in this disease, we performed gene expression profiling using cancer-dedicated microarrays, on nine matched samples of sinonasal adenocarcinomas and non-tumor sinusal tissue. Microarray results were validated by quantitative RT-PCR and immunohistochemistry on two additional sets of tumors.</p> <p>Results</p> <p>Among the genes with significant differential expression we selected <it>LGALS4, ACS5, CLU, SRI and CCT5 </it>for further exploration. The overexpression of <it>LGALS4, ACS5, SRI</it>, <it>CCT5 </it>and the downregulation of <it>CLU </it>were confirmed by quantitative RT-PCR. Immunohistochemistry was performed for LGALS4 (Galectin 4), ACS5 (Acyl-CoA synthetase) and CLU (Clusterin) proteins: LGALS4 was highly up-regulated, particularly in the most differentiated tumors, while CLU was lost in all tumors. The expression of ACS5, was more heterogeneous and no correlation was observed with the tumor type.</p> <p>Conclusion</p> <p>Within our microarray study in sinonasal adenocarcinoma we identified two proteins, LGALS4 and CLU, that were significantly differentially expressed in tumors compared to normal tissue. A further evaluation on a new set of tissues, including precancerous stages and low grade tumors, is necessary to evaluate the possibility of using them as diagnostic markers.</p

Transcriptomic changes in human breast cancer progression as determined by serial analysis of gene expression

INTRODUCTION: Genomic and transcriptomic alterations affecting key cellular processes such us cell proliferation, differentiation and genomic stability are considered crucial for the development and progression of cancer. Most invasive breast carcinomas are known to derive from precursor in situ lesions. It is proposed that major global expression abnormalities occur in the transition from normal to premalignant stages and further progression to invasive stages. Serial analysis of gene expression (SAGE) was employed to generate a comprehensive global gene expression profile of the major changes occurring during breast cancer malignant evolution. METHODS: In the present study we combined various normal and tumor SAGE libraries available in the public domain with sets of breast cancer SAGE libraries recently generated and sequenced in our laboratory. A recently developed modified t test was used to detect the genes differentially expressed. RESULTS: We accumulated a total of approximately 1.7 million breast tissue-specific SAGE tags and monitored the behavior of more than 25,157 genes during early breast carcinogenesis. We detected 52 transcripts commonly deregulated across the board when comparing normal tissue with ductal carcinoma in situ, and 149 transcripts when comparing ductal carcinoma in situ with invasive ductal carcinoma (P < 0.01). CONCLUSION: A major novelty of our study was the use of a statistical method that correctly accounts for the intra-SAGE and inter-SAGE library sources of variation. The most useful result of applying this modified t statistics beta binomial test is the identification of genes and gene families commonly deregulated across samples within each specific stage in the transition from normal to preinvasive and invasive stages of breast cancer development. Most of the gene expression abnormalities detected at the in situ stage were related to specific genes in charge of regulating the proper homeostasis between cell death and cell proliferation. The comparison of in situ lesions with fully invasive lesions, a much more heterogeneous group, clearly identified as the most importantly deregulated group of transcripts those encoding for various families of proteins in charge of extracellular matrix remodeling, invasion and cell motility functions

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

Heat Shock Proteins and Amateur Chaperones in Amyloid-Beta Accumulation and Clearance in Alzheimer’s Disease

The pathologic lesions of Alzheimer’s disease (AD) are characterized by accumulation of protein aggregates consisting of intracellular or extracellular misfolded proteins. The amyloid-β (Aβ) protein accumulates extracellularly in senile plaques and cerebral amyloid angiopathy, whereas the hyperphosphorylated tau protein accumulates intracellularly as neurofibrillary tangles. “Professional chaperones”, such as the heat shock protein family, have a function in the prevention of protein misfolding and subsequent aggregation. “Amateur” chaperones, such as apolipoproteins and heparan sulfate proteoglycans, bind amyloidogenic proteins and may affect their aggregation process. Professional and amateur chaperones not only colocalize with the pathological lesions of AD, but may also be involved in conformational changes of Aβ, and in the clearance of Aβ from the brain via phagocytosis or active transport across the blood–brain barrier. Thus, both professional and amateur chaperones may be involved in the aggregation, accumulation, persistence, and clearance of Aβ and tau and in other Aβ-associated reactions such as inflammation associated with AD lesions, and may, therefore, serve as potential targets for therapeutic intervention

Cell cycle and aging, morphogenesis, and response to stimuli genes are individualized biomarkers of glioblastoma progression and survival

<p>Abstract</p> <p>Background</p> <p>Glioblastoma is a complex multifactorial disorder that has swift and devastating consequences. Few genes have been consistently identified as prognostic biomarkers of glioblastoma survival. The goal of this study was to identify general and clinical-dependent biomarker genes and biological processes of three complementary events: lifetime, overall and progression-free glioblastoma survival.</p> <p>Methods</p> <p>A novel analytical strategy was developed to identify general associations between the biomarkers and glioblastoma, and associations that depend on cohort groups, such as race, gender, and therapy. Gene network inference, cross-validation and functional analyses further supported the identified biomarkers.</p> <p>Results</p> <p>A total of 61, 47 and 60 gene expression profiles were significantly associated with lifetime, overall, and progression-free survival, respectively. The vast majority of these genes have been previously reported to be associated with glioblastoma (35, 24, and 35 genes, respectively) or with other cancers (10, 19, and 15 genes, respectively) and the rest (16, 4, and 10 genes, respectively) are novel associations. <it>Pik3r1</it>, <it>E2f3, Akr1c3</it>, <it>Csf1</it>, <it>Jag2</it>, <it>Plcg1</it>, <it>Rpl37a</it>, <it>Sod2</it>, <it>Topors</it>, <it>Hras</it>, <it>Mdm2, Camk2g</it>, <it>Fstl1</it>, <it>Il13ra1</it>, <it>Mtap </it>and <it>Tp53 </it>were associated with multiple survival events.</p> <p>Most genes (from 90 to 96%) were associated with survival in a general or cohort-independent manner and thus the same trend is observed across all clinical levels studied. The most extreme associations between profiles and survival were observed for <it>Syne1</it>, <it>Pdcd4</it>, <it>Ighg1</it>, <it>Tgfa</it>, <it>Pla2g7</it>, and <it>Paics</it>. Several genes were found to have a cohort-dependent association with survival and these associations are the basis for individualized prognostic and gene-based therapies. <it>C2</it>, <it>Egfr</it>, <it>Prkcb</it>, <it>Igf2bp3</it>, and <it>Gdf10 </it>had gender-dependent associations; <it>Sox10</it>, <it>Rps20</it>, <it>Rab31</it>, and <it>Vav3 </it>had race-dependent associations; <it>Chi3l1</it>, <it>Prkcb</it>, <it>Polr2d</it>, and <it>Apool </it>had therapy-dependent associations. Biological processes associated glioblastoma survival included morphogenesis, cell cycle, aging, response to stimuli, and programmed cell death.</p> <p>Conclusions</p> <p>Known biomarkers of glioblastoma survival were confirmed, and new general and clinical-dependent gene profiles were uncovered. The comparison of biomarkers across glioblastoma phases and functional analyses offered insights into the role of genes. These findings support the development of more accurate and personalized prognostic tools and gene-based therapies that improve the survival and quality of life of individuals afflicted by glioblastoma multiforme.</p