Identification Of Molecular Differences Research Articles

Transcriptomic Analysis of Endometrium in Patients with Adenomyosis and Endometriosis

<h3>Study Objective</h3> to analyze specific gene expression patterns and signaling pathways activation level in endometrial samples of patients with adenomyosis and endometriosis. <h3>Design</h3> Retrospective cohort study. <h3>Setting</h3> University Clinic. <h3>Patients or Participants</h3> 50 women with endometriosis, 20 women with adenomyosis, 35 women with tubal factor infertility (control group). <h3>Interventions</h3> Laparoscopic excision of endometriotic foci and adenomyomas, hysteroscopy with endometrial sampling. RNA was isolated from all samples and stored in RNA Later. Following histologic analysis of all samples, RNA sequencing was performed using Illumina HiSeq 3000 equipment for single-end sequencing. We normalized all gene expression and pathway activation profiles of studied samples on endometrial samples of women from the control group, and then proceeded with identification of strongly differentially expressed genes and activated signaling pathways. <h3>Measurements and Main Results</h3> We performed transcriptomic analysis of 50 endometrial samples of patients with endometriosis, 20 endometrial samples of patients with adenomyosis, and 35 endometrial samples from patients of control group. Statistically significant difference in transcriptomic profiles of endometrium of women with endometriosis and adenomyosis was found. Top-10 most strongly similarly and differentially expressed genes and up- and down-activated signaling pathways were identified. <h3>Conclusion</h3> Our findings suggest that both adenomyosis and endometriosis are associated with specific molecular changes in endometrium. Such data could be potentially used for early diagnosis of adenomyosis, even when it is missed on ultrasonography. Moreover, identification of molecular differences between endometrium in adenomyosis and endometriosis can have important implications on understanding of the etiological aspects and can help in identifying novel drug targets.

P1457COMPARISON OF PEPTIDOMES BETWEEN URINE, PLASMA, AND HEMODIALYSIS FLUID INDICATES SELECTIVITY IN RENAL PEPTIDE PROCESSING

Abstract Background and Aims The physiological and related body fluids, urine, plasma and hemodialysis (HD) fluid spent dialysate (a mixture of technical HD fluid and patient´s ultrafiltrate) are rich biological sources of information especially in the context of kidney diseases. Of particular relevance are proteins and peptides, as they reflect essentially every biological process. Urine is produced as a result of glomerular plasma filtration and subsequent tubular reabsorption in the kidney. In analogy, HD spent dialysate is a result of ultrafiltration by an artificial kidney (dialysis membrane), but lacking tubular reabsorption and thereby accumulating in huge amounts of &amp;gt; 100 L per session comparable to primary urine. A recent study suggested that tubular reabsorption may be selective for specific proteins, and this process may represent a major difference between “natural” and artificial kidney. In this study, we aim at gaining insight into the composition of the peptidome/proteome in these body fluids of renal significance in a comprehensive analysis, in order to shed light on the relevant pathophysiological processes that take place in kidney, which may help developing better strategy in advanced-stage chronic kidney disease and detoxification in renal replacement therapies (RRT). Method We collected 15 plasma, 15 urine and 13 HD filtrate (spent dialysate during the first 30min of RRT) from age and sex matched subjects with stage 4 or above chronic kidney disease. Peptide identification and quantification were performed with capillary-electrophoresis coupled mass spectrometry and tandem mass spectrometry (CE-MS). The abundance, overlap and differences of the peptidome/proteome of the three body fluids were evaluated. Results We were able to detect 6281 urinary peptides, 1750 plasma peptides and 1728 peptides from spent dialysate. Of these we could identify 1764, 452 and 374 sequenced peptides, respectively Among them, there are 318 peptides detectable in both urine and spent dialysate, 307 detectable in both plasma and urine and only 191 detectable in both plasma and spent dialysate. Among the most abundant peptides in plasma were Thymosine-ß4 and fragments from hemoglobin, fibrinogen and collagen. In dialysate, the most abundant proteins detected in these patients were ß-2-microglobuline, Thymosine-ß4, and fragments from fibrinogen, while in urine fragments derived from collagen, albumin, and from alpha-1-antitrypsin were of the highest abundance. When investigating proteins/peptides found in at least 2 body fluids, a strong correlation in peptide abundance between urine and spent dialysate (P=4.2e-27, Rho=0.56), and a moderately strong correlation between HD fluid and plasma (P=3.7e-5, Rho=0.29) were detected. However, there is no significant correlation between peptide abundance in urine and plasma (P=0.22, Rho=0.07). Collagen peptides are the most abundant peptides in all three body fluids. Conclusion This dataset will serve as a valid basis to define the protein and peptide contents in blood, urine, and spent dialysate. The data show, as expected, substantial similarity between plasma and spent dialysate, but, surprisingly, very little similarity between urine and plasma. This further supports the hypothesis that tubular reabsorption may be selective for specific proteins and peptides, possibly excluding collagen-derived peptides. A more detailed investigation into the process and relevance of tubular reabsorption appears warranted in the light of the data. The fact that the samples investigated in this study are derived from advanced stage CKD patients must be taken into account, significant differences exist in comparison to urine produced by healthy kidney. The identification of molecular differences between urine and dialysate spent may present an opportunity to design future “biologically adapted” removal devices.

Comparison of molecular profile in triple-negative inflammatory and non-inflammatory breast cancer not of mesenchymal stem-like subtype

BackgroundInflammatory breast cancer (IBC) is an aggressive form of breast cancer. The triple-negative subtype of IBC (TN-IBC) is particularly aggressive. Identification of molecular differences between TN-IBC and TN-non-IBC may help clarify the unique clinical behaviors of TN-IBC. However, our previous study comparing gene expression between TN-IBC and TN-non-IBC did not identify any TN-IBC-specific molecular signature. Lehmann et al recently reported that the mesenchymal stem-like (MSL) TNBC subtype consisted of infiltrating tumor-associated stromal cells but not cancer cells. Therefore, we compared the gene expression profiles between TN-IBC and TN-non-IBC patient samples not of the MSL subtype.MethodsWe classified 88 TNBC samples from the World IBC Consortium into subtypes according to the Vanderbilt classification and Insight TNBCtype, removed samples of MSL and unstable subtype, and compared gene expression profiles between the remaining TN-IBC and TN-non-IBC samples.ResultsIn the Vanderbilt analysis, we identified 75 genes significantly differentially expressed between TN-IBC and TN-non-IBC at an FDR of 0.2. In the Insight TNBCtype analysis, we identified 81 genes significantly differentially expressed between TN-IBC and TN-non-IBC at an FDR of 0.4. In both analyses, the top canonical pathway was “Fc Receptor-mediated Phagocytosis in Macrophages and Monocytes”, and the top 10 differentially regulated genes included PADI3 and MCTP1, which were up-regulated, and CDC42EP3, SSR1, RSBN1, and ZC3H13, which were downregulated.ConclusionsOur data suggest that the activity of macrophages might be enhanced in TN-IBC compared with TN-non-IBC. Further clinical and preclinical studies are needed to determine the cross-talk between macrophages and IBC cells.

Endocervix microRNA expression in patients with deep endometriosis

The identification of molecular differences in eutopic endometrium of women with endometriosis is an important step toward understanding it pathogenesis and developing novel strategies for the treatment of associated infertility and pain. A number of differences in gene expression were found in patients with endometriosis. miRNA are small molecules and may act as post-transcriptional gene expression regulator. Many miRNAs are tissue specific and play a significant role in oncogenes, metastasis and tumor invasion.

Molecular profiling of patient-matched brain and extracranial melanoma metastases implicates the PI3K pathway as a therapeutic target.

An improved understanding of the molecular pathogenesis of brain metastases, one of the most common and devastating complications of advanced melanoma, may identify and prioritize rational therapeutic approaches for this disease. In particular, the identification of molecular differences between brain and extracranial metastases would support the need for the development of organ-specific therapeutic approaches. Hotspot mutations, copy number variations (CNV), global mRNA expression patterns, and quantitative analysis of protein expression and activation by reverse-phase protein array (RPPA) analysis were evaluated in pairs of melanoma brain metastases and extracranial metastases from patients who had undergone surgical resection for both types of tumors. The status of 154 previously reported hotspot mutations, including driver mutations in BRAF and NRAS, were concordant in all evaluable patient-matched pairs of tumors. Overall patterns of CNV, mRNA expression, and protein expression were largely similar between the paired samples for individual patients. However, brain metastases demonstrated increased expression of several activation-specific protein markers in the PI3K/AKT pathway compared with the extracranial metastases. These results add to the understanding of the molecular characteristics of melanoma brain metastases and support the rationale for additional testing of the PI3K/AKT pathway as a therapeutic target in these highly aggressive tumors.

Molecular Sex Differences in Human Serum

BackgroundSex is an important factor in the prevalence, incidence, progression, and response to treatment of many medical conditions, including autoimmune and cardiovascular diseases and psychiatric conditions. Identification of molecular differences between typical males and females can provide a valuable basis for exploring conditions differentially affected by sex.Methodology/Principal FindingsUsing multiplexed immunoassays, we analyzed 174 serum molecules in 9 independent cohorts of typical individuals, comprising 196 males and 196 females. Sex differences in analyte levels were quantified using a meta-analysis approach and put into biological context using k-means to generate clusters of analytes with distinct biological functions. Natural sex differences were established in these analyte groups and these were applied to illustrate sexually dimorphic analyte expression in a cohort of 22 males and 22 females with Asperger syndrome. Reproducible sex differences were found in the levels of 77 analytes in serum of typical controls, and these comprised clusters of molecules enriched with distinct biological functions. Analytes involved in fatty acid oxidation/hormone regulation, immune cell growth and activation, and cell death were found at higher levels in females, and analytes involved in immune cell chemotaxis and other indistinct functions were higher in males. Comparison of these naturally occurring sex differences against a cohort of people with Asperger syndrome indicated that a cluster of analytes that had functions related to fatty acid oxidation/hormone regulation was associated with sex and the occurrence of this condition.Conclusions/SignificanceSex-specific molecular differences were detected in serum of typical controls and these were reproducible across independent cohorts. This study extends current knowledge of sex differences in biological functions involved in metabolism and immune function. Deviations from typical sex differences were found in a cluster of molecules in Asperger syndrome. These findings illustrate the importance of investigating the influence of sex on medical conditions.

A Minimal Immunohistochemical Panel for Subtyping Poorly Differentiated Non-Small Cell Lung Carcinoma: A Tissue Microarray Study Simulating Small Biopsy Conditions

Purpose Given the emerging evidence for differential responses to new targeted therapies and the identification of molecular differences between specific subtypes of non-small cell lung carcinoma (NSCLC), there is an increased need for greater accuracy in subtyping NSCLC. In a substantial proportion of cases, standard morphology cannot specifically subtype the tumor, resulting in a final diagnosis of NSCLC-not otherwise specified. In this study, we added newly proposed markers (napsin A, desmocollin-3) to conventional markers (p63, thyroid transcription factor-1 [TTF-1], cytokeratin 5/6 [CK5/6], high molecular weight cytokeratin [HMWCK], cytokeratin 7 [CK7]) and evaluated for the minimal panel of immunohistochemical markers required for subtyping poorly differentiated (PD) NSCLC. Materials and Methods Resection specimens of 110 adenocarcinomas (ADCs) and 171 squamous cell carcinomas (SCCs) were collected and tissue microarrays were constructed to simulate small biopsy conditions. All specimens were stained with TTF-1, napsin A, CK7, p63, CK5/6, HMWCK, desmocollin-3 and mucicarmine. Results For 32 PD ADC, a combination of TTF-1 and napsin A increased sensitivity (81%). With regard to the 29 PD SCC, a combination of desmocollin-3 and p63 did not substantially increase diagnostic performance. Logistic regression analysis identified napsin A, p63 and TTF-1 as the optimal panel to separate PD ADC and PD SCC. Mucin stains for PD NSCLC increased accuracy rate (88%) for diagnosis of PD ADC. Conclusion We recommend a minimal panel of immunohistochemical and histochemical markers to include TTF-1, p63, napsin A and one of mucin stains for tumor subtyping of PD NSCLC in a small biopsy sample.

Differential Proteome Profiling of Eutopic Endometrium from Women with Endometriosis To Understand Etiology of Endometriosis

The identification of molecular differences in the endometrium of women with endometriosis is an important step toward understanding the pathogenesis of this condition and for developing novel strategies for the treatment of associated infertility and pain. In this study, we investigated protein expression analysis of eutopic endometrium from women with and without endometriosis. The proteomic analysis revealed molecular dysregulation of more than 70 proteins in the proliferative phase of eutopic endometrium in stage IV and secretory phase of stage II, III and IV endometriosis. Using mass spectrometry, 48 proteins spots which were consistently differentially expressed from stage II to IV endometriosis were identified. The differentially expressed proteins include structural proteins, proteins involved in stress response, protein-folding and protein-turnover, immunity, energy production, signal transduction, RNA biogenesis, protein biosynthesis, and nuclear proteins. Immunoblot and immunohistochemical analyses confirmed the observed changes in eight representative proteins. The present study provides identification of new players that have a potential role in the initiation and progression of endometriosis and also sets a framework for further investigations on mechanisms underlying the pathogenesis of endometriosis.

Gene Expression Analysis of Endometrium Reveals Progesterone Resistance and Candidate Susceptibility Genes in Women with Endometriosis

The identification of molecular differences in the endometrium of women with endometriosis is an important step toward understanding the pathogenesis of this condition and toward developing novel strategies for the treatment of associated infertility and pain. In this study, we conducted global gene expression analysis of endometrium from women with and without moderate/severe stage endometriosis and compared the gene expression signatures across various phases of the menstrual cycle. The transcriptome analysis revealed molecular dysregulation of the proliferative-to-secretory transition in endometrium of women with endometriosis. Paralleled gene expression analysis of endometrial specimens obtained during the early secretory phase demonstrated a signature of enhanced cellular survival and persistent expression of genes involved in DNA synthesis and cellular mitosis in the setting of endometriosis. Comparative gene expression analysis of progesterone-regulated genes in secretory phase endometrium confirmed the observation of attenuated progesterone response. Additionally, interesting candidate susceptibility genes were identified that may be associated with this disorder, including FOXO1A, MIG6, and CYP26A1. Collectively these findings provide a framework for further investigations on causality and mechanisms underlying attenuated progesterone response in endometrium of women with endometriosis.

Cancer: A Systems Biology disease

Cancer research has focused on the identification of molecular differences between cancerous and healthy cells. The emerging picture is overwhelmingly complex. Molecules out of many parallel signal transduction pathways are involved. Their activities appear to be controlled by multiple factors. The action of regulatory circuits, cross-talk between pathways and the non-linear reaction kinetics of biochemical processes complicate the understanding and prediction of the outcome of intracellular signaling. In addition, interactions between tumor and other cell types give rise to a complex supra-cellular communication network. If cancer is such a complex system, how can one ever predict the effect of a mutation in a particular gene on a functionality of the entire system? And, how should one go about identifying drug targets? Here, we argue that one aspect is to recognize, where the essence resides, i.e. recognize cancer as a Systems Biology disease. Then, more cancer biologists could become systems biologists aiming to provide answers to some of the above systemic questions. To this aim, they should integrate the available knowledge stemming from quantitative experimental results through mathematical models. Models that have contributed to the understanding of complex biological systems are discussed. We show that the architecture of a signaling network is important for determining the site at which an oncologist should intervene. Finally, we discuss the possibility of applying network-based drug design to cancer treatment and how rationalized therapies, such as the application of kinase inhibitors, may benefit from Systems Biology.