Initial characterization of C16orf89, a novel thyroid-specific gene

Association of clinical parameters and polygenic risk scores for body mass index, schizophrenia, and diabetes with antipsychotic-induced weight gain

Antipsychotic-induced weight gain (AIWG) is a common adverse event in schizophrenia. Genome-wide association studies (GWAS) and polygenic risk scores (PRS) for other diseases or traits are recent approaches to disentangling the genetic architecture of AIWG. 200 patients with schizophrenia treated monotherapeutically with antipsychotics were included in this study. A multiple linear regression analysis with ten-fold crossvalidation was performed to predict the percentage weight change after five weeks of treatment. Independent variables were sex, age, body mass index (BMI) at baseline, medication-associated risk, and PRSs (BMI, schizophrenia, diabetes, and metabolic syndrome). An explorative GWAS analysis was performed on the same subjects and traits. PRSs for BMI (β = 3.78; p = 0.0041), schizophrenia (β = 5.38; p = 0.021) and diabetes type 2 (β = 13.4; p = 0.046) were significantly associated with AIWG. Other significant factors were sex, baseline BMI and medication. Compared to the model without genetic factors, the addition of PRSs for BMI, schizophrenia, and diabetes type 2 increased the goodness of fit by 6.5 %. The GWAS identified the association of three variants (rs10668573, rs10249381 and rs1988834) with AIWG at a genome-wide level of p < 1 · 10-6. Using PRS for schizophrenia, BMI, and diabetes type 2 increased the explained variation of predicted weight gain, compared to a model without PRSs. For more precise results, PRSs derived from other traits (ideally AIWG) should be investigated. Potential risk variants identified in our GWAS need to be further investigated and replicated in independent samples.

Network medicine approaches for identification of novel prognostic systems biomarkers and drug candidates for papillary thyroid carcinoma

Papillary thyroid carcinoma (PTC) is one of the most common endocrine carcinomas worldwide and the aetiology of this cancer is still not well understood. Therefore, it remains important to understand the disease mechanism and find prognostic biomarkers and/or drug candidates for PTC. Compared with approaches based on single-gene assessment, network medicine analysis offers great promise to address this need. Accordingly, in the present study, we performed differential co-expressed network analysis using five transcriptome datasets in patients with PTC and healthy controls. Following meta-analysis of the transcriptome datasets, we uncovered common differentially expressed genes (DEGs) for PTC and, using these genes as proxies, found a highly clustered differentially expressed co-expressed module: a 'PTC-module'. Using independent data, we demonstrated the high prognostic capacity of the PTC-module and designated this module as a prognostic systems biomarker. In addition, using the nodes of the PTC-module, we performed drug repurposing and text mining analyzes to identify novel drug candidates for the disease. We performed molecular docking simulations, and identified: 4-demethoxydaunorubicin hydrochloride, AS605240, BRD-A60245366, ER 27319 maleate, sinensetin, and TWS119 as novel drug candidates whose efficacy was also confirmed by in silico analyzes. Consequently, we have highlighted here the need for differential co-expression analysis to gain a systems-level understanding of a complex disease, and we provide candidate prognostic systems biomarker and novel drugs for PTC.

A Multiplex Thyroid-Specific Assay for Quantification of Circulating Thyroid Cell-Free RNA in Plasma of Thyroid Cancer Patients

Background

The standard of care for thyroid cancer management is thyroidectomy and adjuvant radioactive iodine (RAI). There is a paucity of clinical tool that quantifies residual thyroid volume reliably for precise adjuvant RAI dosing. Serum thyroglobulin (TG), tumour marker for thyroid cancer, takes 4 weeks for complete clearance due to its long half-life, and might be undetectable in 12% of structural disease patients. It detects recurrence with a sensitivity of 19-40%, mainly attributed to issue of TG antibody interference with TG immunometric assay. We hypothesise that the quantity of thyroid-specific cell-free RNA (cfRNA) is indicative of amount of thyroid tissues, and that during thyroid surgery, cfRNA levels decrease accordingly.

Methods

We identified 11 biologically significant and highly expressed thyroid-specific targets from Human Protein Atlas and literature. To assess for a fall in thyroid-specific cfRNA level, we recruited 16 patients undergoing thyroid surgery or RAI for malignant or benign thyroid disease, and tracked longitudinal trend of cfRNA. To assess the utility of cfRNA in detecting metastatic thyroid cancer, cfRNA of 11 patients at intermediate to high risk of recurrence was measured during surveillance and at time of clinical recurrence.

Results

The multiplex assay was capable of amplifying and quantifying multiple thyroid-specific genes in a single reaction. The selected targets were amplified successfully from RNA extracted directly from the thyroid (positive control), indicating that they were highly expressed within thyroid tissue. These cfRNAs were present in plasma, in amounts quantifiable using qRT-PCR. Four cfRNA transcripts (TPO, GFRA2, IVD, TG) fell post-treatment in more than 50% of cohort. The thyroid peroxidase (TPO) cfRNA fell post-therapy in 63% of cohort by 80%, as early as 1 day post-treatment, supporting the potential role as early indicator of remnant thyroid tissue volume. We demonstrated the clinical relevance of circulating TPO cfRNA by tracking temporal changes in setting of peri-treatment, recurrence, and TG Ab positive state.

Conclusion

Using a multiplex pre-amplification approach, the TPO cfRNA was a potential biomarker that can track residual thyroid mass. It can be further optimised for quantification of thyroid volume to guide RAI doses and for detection of thyroid cancer recurrence.

Mining the plasma-proteome associated genes in patients with gastro-esophageal cancers for biomarker discovery

Gastro-esophageal (GE) cancers are one of the major causes of cancer-related death in the world. There is a need for novel biomarkers in the management of GE cancers, to yield predictive response to the available therapies. Our study aims to identify leading genes that are differentially regulated in patients with these cancers. We explored the expression data for those genes whose protein products can be detected in the plasma using the Cancer Genome Atlas to identify leading genes that are differentially regulated in patients with GE cancers. Our work predicted several candidates as potential biomarkers for distinct stages of GE cancers, including previously identified CST1, INHBA, STMN1, whose expression correlated with cancer recurrence, or resistance to adjuvant therapies or surgery. To define the predictive accuracy of these genes as possible biomarkers, we constructed a co-expression network and performed complex network analysis to measure the importance of the genes in terms of a ratio of closeness centrality (RCC). Furthermore, to measure the significance of these differentially regulated genes, we constructed an SVM classifier using machine learning approach and verified these genes by using receiver operator characteristic (ROC) curve as an evaluation metric. The area under the curve measure was > 0.9 for both the overexpressed and downregulated genes suggesting the potential use and reliability of these candidates as biomarkers. In summary, we identified leading differentially expressed genes in GE cancers that can be detected in the plasma proteome. These genes have potential to become diagnostic and therapeutic biomarkers for early detection of cancer, recurrence following surgery and for development of targeted treatment.

A molecular view of the normal human thyroid structure and function reconstructed from its reference transcriptome map

BACKGROUND

The thyroid is the earliest endocrine structure to appear during human development, and thyroid hormones are necessary for proper organism development, in particular for the nervous system and heart, normal growth and skeletal maturation. To date a quantitative, validated transcriptional atlas of the whole normal human thyroid does not exist and the availability of a detailed expression map might be an excellent occasion to investigate the many features of the thyroid transcriptome.

RESULTS

We present a view at the molecular level of the normal human thyroid histology and physiology obtained by a systematic meta-analysis of all the available gene expression profiles for the whole organ. A quantitative transcriptome reference map was generated by using the TRAM (Transcriptome Mapper) software able to combine, normalize and integrate a total of 35 suitable datasets from different sources thus providing a typical reference expression value for each of the 27,275 known, mapped transcripts obtained. The experimental in vitro validation of data was performed by "Real-Time" reverse transcription polymerase chain reaction showing an excellent correlation coefficient (r = 0.93) with data obtained in silico.

CONCLUSIONS

Our study provides a quantitative global reference portrait of gene expression in the normal human thyroid and highlights differential expression between normal human thyroid and a pool of non-thyroid tissues useful for modeling correlations between thyroidal gene expression and specific thyroid functions and diseases. The experimental in vitro validation supports the possible usefulness of the human thyroid transcriptome map as a reference for molecular studies of the physiology and pathology of this organ.

Engineered insulin secretion from neuroendocrine cells isolated from human thyroid

BACKGROUND

Insulin-secreting beta-like cells are vulnerable to diabetic autoimmunity. We hypothesized that human thyroid neuroendocrine (NE) cells could be engineered to secrete human insulin, be glucose-responsive, and avoid autoimmunity.

METHODS

Collagenase-digested thyroid tissue was cultured and subjected to size-based fluorescence-activated cell sorting. Insulin secretion and storage in NE cells transduced with viral vectors carrying an insulin sequence was assessed by enzyme-linked immunosorbent assay (ELISA) and immunogold transmission electron microscopy (TEM). Baseline mRNA expression was assessed by Illumina expression array analysis. Transduction with retrovirus expressing transcription factors PDX1, NGN3, MAFA, or HNF6 altered mRNA expression in a custom polymerase chain reaction (PCR) array. Gastrin-releasing peptide (GRP) in conditioned medium and cell lysates was determined by reverse transcription (RT)-PCR, ELISA, and immunohistochemistry.

RESULTS

Isolation yielded an average of 2.2 × 10(6) cells/g thyroid tissue, which stained for calcitonin/calcitonin gene-related protein, expressed genes consistent with NE origins, and secreted GRP. Transduced cells secreted 56 % and retained 48 % of total insulin produced. Immunogold TEM revealed insulin in secretory vesicles. PDX1, NGN3, and MAFA overexpression increased expression of genes typical for hepatocytes and beta cells. Overexpression of HNF6 also increased the message of genes critical for glucose sensing.

CONCLUSIONS

Human thyroid NE cells can produce human insulin, fractions of which are both secreted and retained in secretory granules. Overexpression of HNF6, PDX1, or NGN3 enhances expression of both hepatocyte and beta cell typical mRNAs, including the message of proteins critical for glucose sensing. These data suggest that reimplantation of engineered autologous NE cells may develop as a viable treatment for diabetes mellitus type 1.

Increased glucocerebrosidase expression and activity in preeclamptic placenta

INTRODUCTION

Lysosomal glucosidase beta acid (GBA) deficiency is inherent to Gaucher disease, Parkinsonism and Lewy-body dementia. Increased GBA expression has never been associated with human disease. We describe increased GBA expression and activity in placenta from preeclamptic pregnancies.

METHODS

112 placenta biopsies were available for qPCR, analysis of GBA gene expression and activity. Microanalysis was performed on 20 placenta samples. Alternatively spliced placental GBA transcripts were cloned, expressed in HEK293 cells and analyzed by Western blot and activity assay.

RESULTS

GBA is expressed in the syncytiotrophoblast layer of human placenta already at 5 weeks of gestation. We identified five novel GBA transcripts in placenta that enzymatically inactive when expressed in HEK293 cells. Both GBA RNA expression and enzymatic activity are upregulated in preeclamptic placenta. Microarray analysis of 20 placenta tissues identified 158 genes co-regulating with GBA expression and gene enrichment analysis highlights lysosomal function. In our micro-array data GBA expression does not correlate with FLT1 expression, currently the most powerful marker for preeclampsia. There are 89 transcripts that are negatively correlated with GBA expression of which BMP4 and TFEB are interesting as they are essential to early placenta function.

DISCUSSION

Although very speculative, we hypothesize that increased GBA expression might relate to placentation through decreased BMP4 signaling or vascularization through downregulation of TFEB. Ceramide, the product of hydrolysis of glucosylceramide by GBA and involved in the regulation of cell differentiation, survival and apoptosis, is another putative candidate linking increased GBA activity to preeclampsia. Both pathways merit further investigation.

Association between gene expression profiles and clinical outcome of pemetrexed-based treatment in patients with advanced non-squamous non-small cell lung cancer: exploratory results from a phase II study

INTRODUCTION

We report exploratory gene-expression profiling data from a single-arm Phase-II-study in patients with non-squamous (ns)NSCLC treated with pemetrexed and cisplatin. Previously disclosed results indicated a significant association of low thymidylate-synthase (TS)-expression with longer progression-free and overall survival (PFS/OS).

METHODS

Treatment-naïve nsNSCLC patients (IIIB/IV) received 4 cycles of pemetrexed/cisplatin; non-progressing patients continued on pemetrexed-maintenance. Diagnostic tissue-samples were used to assess TS-expression by immunohistochemistry (IHC) and mRNA-expression array-profiling (1,030 lung cancer-specific genes). Cox proportional-hazard models were applied to explore the association between each gene and PFS/OS. Genes significantly correlated with PFS/OS were further correlated with TS-protein expression (Spearman-rank). Unsupervised clustering was applied to all evaluable samples (n = 51) for all 1,030 genes and an overlapping 870-gene subset associated with adenocarcinoma (ADC, n = 47).

RESULTS

51/70 tissue-samples (72.9%) were evaluable; 9 of 1,030 genes were significantly associated with PFS/OS (unadjusted p < 0.01, genes: Chromosome 16 open reading frame 89, napsin A, surfactant protein B, aquaporin 4, TRAF2- and Nck-interacting kinase, Lysophosphatidylcholine acyltransferase 1, Interleukin 1 receptor type II, NK2 homeobox 1, ABO glycosyl-transferase); expression for all except IL1R2 correlated negatively with nuclear TS-expression (statistically significant for 5/8 genes, unadjusted p<0.01). Cluster-analysis based on 1,030 genes revealed no clear trend regarding PFS/OS; the ADC-based cluster analysis identified 3 groups (n = 21/11/15) with median (95%CI) PFS of 8.1(6.9,NE)/2.4(1.2,NE)/4.4(1.2,NE) months and OS of 20.3(17.5,NE)/4.3(1.4,NE)/8.3(3.9,NE) months, respectively.

CONCLUSIONS

These exploratory gene-expression profiling results describe genes potentially linked to low TS-expression. Nine genes were significantly associated with PFS/OS but could not be differentiated as prognostic or predictive as this was a single-arm study. Although these hypotheses-generating results are interesting, they provide no evidence to change the current histology-based treatment approach with pemetrexed.

Proteomic analysis of podocyte exosome-enriched fraction from normal human urine

Urine results from a coordinated activity of glomerular and tubular compartments of the kidney. As a footprint of these cellular functional processes, urinary exosomes, and 40-80 nm membrane vesicles released after fusion with the plasma membrane into the extracellular environment by renal epithelial cells, are a source for identification of proteins and investigation of their role in the kidney. The aim of the present study was the identification of podocyte exosome proteins based on urine immunoabsorption using podocyte-specific CR1-immunocoated beads followed by proteomic analysis using LC MS/MS techniques. This methodology allowed the identification of 1195 proteins. By using a bioinformatic approach, 27 brain-expressed proteins were identified, in which 14 out of them were newly demonstrated to be expressed in the kidney at a mRNA level, and, one of them, the COMT protein, was demonstrated to be expressed in podocytes at a protein level. These results, attesting the reliability of the methodology to identify podocyte proteins, need now to be completed by further experiments to analyze more precisely their biological function(s) in the podocytes.

Expression of placental FLT1 transcript variants relates to both gestational hypertensive disease and fetal growth

The recent discovery of additional alternative spliced FLT1 transcripts encoding novel soluble (s)FLT1 protein isoforms complicates both the predictive value and functional implications of sFLT1 in preeclampsia. We investigated FLT1 expression levels and splicing patterns in placentas of normotensive and preeclamptic women, and established the tissue specificity of all FLT1 transcript variants. mRNA levels of sFLT1 splice variants were determined by real-time polymerase chain reaction in 21 normal human tissues and placental biopsies from 91 normotensive and 55 preeclamptic women. Cellular localization of placental FLT1 expression was established by RNA in situ hybridization. Of all tissues investigated, placenta has by far the highest FLT1 mRNA expression level, mainly localized in the syncytiotrophoblast layer. More than 80% of placental transcripts correspond to sFLT1_v2. Compared with normotensive placenta, preeclamptic placenta has ≈3-fold higher expression of all FLT1 transcript variants (P<0.001), with a slight shift in favor of sFLT1_v1. Although to a lesser degree, transcript levels are also increased in placenta from normotensive women that deliver a small for gestational age neonate. We conclude that sFLT isoform-specific assays could potentially improve the accuracy of current sFLT1 assays for the prediction of preeclampsia. However, placental FLT1 transcript levels are increased not only in preeclampsia but also in normotensive pregnancy with a small for gestational age fetus. This may indicate a common pathway involved in the development of both conditions but complicates the use of circulating sFLT1 protein levels for the prediction or diagnosis of preeclampsia alone.