Search

PDF file - 40K, Unsupervised hierarchical clustering of gene expression data from endometrial carcinoma. The pStathmin(S38) high cases are significantly overrepresented in two of the clusters with aggressive tumors.

Purpose:Amplification of PIK3CA, encoding the PI3K catalytic subunit alpha, is common in uterine corpus endometrial carcinoma (UCEC) and linked to an aggressive phenotype. However, it is unclear whether PIK3CA amplification acts via PI3K activation. We investigated the association between PIK3CA amplification, markers of PI3K activity, and prognosis in a large cohort of UCEC specimens.Experimental Design:UCECs from 591 clinically annotated patients including 83 tumors with matching metastasis (n = 188) were analyzed by FISH to determine PIK3CA copy-number status. These data were integrated with mRNA and protein expression and clinicopathologic data. Results were verified in The Cancer Genome Atlas dataset.Results:PIK3CA amplifications were associated with disease-specific mortality and with other markers of aggressive disease. PIK3CA amplifications were also associated with other amplifications characteristic of the serous-like somatic copy-number alteration (SCNA)–high subgroup of UCEC. Tumors with PIK3CA amplification also demonstrated an increase in phospho-p70S6K but had decreased levels of activated phospho-AKT1-3 as assessed by Reverse Phase Protein Arrays and an mRNA signature of MTOR inhibition.Conclusions:PIK3CA amplification is a strong prognostic marker and a potential marker for the aggressive SCNA-high subgroup of UCEC. Although PIK3CA amplification associates with some surrogate measures of increased PI3K activity, markers for AKT1-3 and MTOR signaling are decreased, suggesting that this signaling is not a predominant pathway to promote cancer growth of aggressive serous-like UCEC. Moreover, these associations may reflect features of the SCNA-high subgroup of UCEC rather than effects of PIK3CA amplification itself.

PDF file - 50K, Primary investigation series. Cox's proportional hazard regression model used to estimate the prognostic value of pStathmin(S38) in endometrial carcinomas, in relation to histopathologic variables and Stathmin.

Correlation between copy number status determined by FISH and microarrays.

Links to supplementary video clips (VCS1+VCS2) and description of supplementary optical datasets (ODS1+ODS2)

PDF file - 84K, Gene Set Enrichment Analysis (www.broadinstitute.org/gsea/msigdb). Gene sets (GO categories, computational gene sets and curated gene sets) within FDR

PDF file - 50K, Validations series. Cox's proportional hazard regression model used to estimate the prognostic value of pStathmin(S38) in endometrial carcinomas, in relation to histopathologic variables and Stathmin.

Purpose: High Stathmin expression has recently been associated with clinical progress in endometrial cancers. Stathmin protein activity is modulated by phosphorylation, and the Serine38 site is one of four Stathmin phospho-sites. The presence and significance of pStathmin(S38) is largely unknown in human cancers, and we here examined the associations between this marker and tumor cell proliferation, clinicopathologic phenotype, and survival impact in endometrial cancer. A relationship with possible treatment targets was explored by integrated analysis of transcriptional alterations.Experimental Design: Primary endometrial cancers from two independent patient series (n = 518/n = 286) were analyzed. Biomarkers were assessed by immunohistochemistry, FISH, flow cytometry, DNA oligonucleotide microarray, single-nucleotide polymorphism array, and Sanger sequencing, and related to clinicopathologic annotations and follow-up information.Results: High pStathmin(S38) level was associated with poor prognosis, independent of other features, and correlated to increased tumor cell proliferation as well as high Stathmin levels. On the basis of transcriptional differences between high/low pStathmin(S38) tumors, phosphoinositide 3-kinase (PI3K)/mTOR/HSP90 were suggested as possible targets in pStathmin(S38)-high cases. High pStathmin(S38) was associated with several PI3K pathway alterations: amplification of the 3q26 region, increased PIK3CA copy number (FISH) and a PI3K activation score (all P < 0.05).Conclusions: High pStathmin(S38) is a novel biomarker of increased tumor cell proliferation and impaired prognosis as reported here for independent cohorts of endometrial cancer and not previously shown in human cancer. Our data support a rationale for further studies exploring effects of drugs inhibiting the PI3K signaling pathway in pStathmin(S38)-high endometrial cancer, including a potential value of pStathmin(S38) in predicting response to PI3K/mTOR/HSP90 inhibitors. Clin Cancer Res; 19(9); 2331–41. ©2013 AACR.

Supplementary Tables

The arsenic speciation, the abundance of arsenite-oxidizing bacteria, and microbial community structures in the groundwater, surface water, and soil from a gold mining area were explored using the PHREEQC model, cloning-ddPCR of the aioA gene, and high-throughput sequencing of the 16S rRNA gene, respectively. The analysis of the aioA gene showed that arsenite-oxidizing bacteria retrieved from groundwater, surface water, and soil were associated with Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria. In groundwaters from the mining area, there were relatively high ratios of aioA/total 16S rRNA gene copies and the dominance of As5+, which suggested the presence and activity of arsenite-oxidizing bacteria. Metagenomic analysis revealed that the majority of the soil and surface water microbiomes were Proteobacteria, Actinobacteria, Bacteroidetes, and Chloroflexi, whereas the groundwater microbiomes were dominated exclusively by Betaproteobacteria and Alphaproteobacteria. Geochemical factors influencing the microbial structure in the groundwater were As, residence time, and groundwater flowrate, while those showing a positive correlation to the microbial structure in the surface water were TOC, ORP, and DO. This study provides insights into the groundwater, surface water, and soil microbiomes from a gold mine and expands the current understanding of the diversity and abundance of arsenite-oxidizing bacteria, playing a vital role in global As cycling.

The advent of next-generation sequencing (NGS) allows to study living organisms by reading genetic materials in a high-throughput manner. The technology has opened up a field of microbial research in several areas such as medicine, agriculture, energy, and environment, to study a whole microbial community in an environment of interest without culturing. Bioinformatics analysis is a need in order to characterize and analyze microbiota in the studied samples. In this tutorial, we will give an overview of microbiome analysis based on high-throughput 16S rRNA genes sequencing, a commonly-used target sequence to classify bacteria and archaea. With biological and technology backgrounds, microbiome data from short-read sequencing platform will be elucidated followed by all important computational steps for microbiome analysis. The steps include data preprocessing, amplicon sequence variant analysis, taxonomy assignment, data normalization, and diversity analyses. Practical concepts and codes for the microbiome analysis will be demonstrated step by step providing a basic guideline for beginner.

Background: Despite successful implementation of drugs targeting the human epidermal growth factor receptor 2 (HER2) receptor in breast and gastric cancers, the potential of HER2 as a therapeutic target in other cancers has been less studied, including endometrial cancer. We investigated expression levels of HER2 (ERBB2) in a large cohort of endometrial cancer lesions, also including complex atypical hyperplasia and metastatic lesions. Methods: 67 precursor lesions, 790 primary endometrial cancers and 383 metastatic lesions were investigated for HER2 expression in relation to clinicopathologic features and outcome. Protein levels were assessed by immunohistochemistry (using the HercepTest and staining index (SI) criteria), mRNA levels by microarrays and amplification status by chromogenic in situ hybridisation. Results: High HER2 protein levels were significantly associated with features of aggressive disease and increased mRNA ERBB2 levels. HER2 expression defined by the SI proved to be a better predictor of survival compared with the HercepTest. A discordant HER2 expression pattern between paired primary and metastatic lesions was detected, revealing substantial reduction in HER2 expression from primary to metastatic disease. Conclusions: Loss of HER2 expression is common in metastatic endometrial cancer lesions and assessment of HER2 levels in the metastatic lesions may be important to define the potential benefit of anti-HER2 treatments in endometrial cancer patients. publishedVersion

Colorectal adenomas are precursor lesions of colorectal adenocarcinoma. The transition from adenoma to carcinoma in patients with colorectal cancer (CRC) has been associated with an accumulation of genetic aberrations. However, criteria that can screen adenoma progression to adenocarcinoma are still lacking. This present study is the first attempt to identify genetic aberrations, such as the somatic mutations, copy number variations (CNVs), and high-frequency mutated genes, found in Thai patients. In this study, we identified the genomic abnormality of two sample groups. In the first group, five cases matched normal-colorectal adenoma-colorectal adenocarcinoma. In the second group, six cases matched normal-colorectal adenomas. For both groups, whole-exome sequencing was performed. We compared the genetic aberration of the two sample groups. In both normal tissues compared with colorectal adenoma and colorectal adenocarcinoma analyses, somatic mutations were observed in the tumor suppressor gene APC (Adenomatous polyposis coli) in eight out of ten patients. In the group of normal tissue comparison with colorectal adenoma tissue, somatic mutations were also detected in Catenin Beta 1 (CTNNB1), Family With Sequence Similarity 123B (FAM123B), F-Box And WD Repeat Domain Containing 7 (FBXW7), Sex-Determining Region Y-Box 9 (SOX9), Low-Density Lipoprotein Receptor-Related Protein 5 (LRP5), Frizzled Class Receptor 10 (FZD10), and AT-Rich Interaction Domain 1A (ARID1A) genes, which are involved in the Wingless-related integration site (Wnt) signaling pathway. In the normal tissue comparison with colorectal adenocarcinoma tissue, Kirsten retrovirus-associated DNA sequences (KRAS), Tumor Protein 53 (TP53), and Ataxia-Telangiectasia Mutated (ATM) genes are found in the receptor tyrosine kinase-RAS (RTK–RAS) signaling pathway and p53 signaling pathway, respectively. These results suggest that APC and TP53 may act as a potential screening marker for colorectal adenoma and early-stage CRC. This preliminary study may help identify patients with adenoma and early-stage CRC and may aid in establishing prevention and surveillance strategies to reduce the incidence of CRC.

The microbiomes of deep and shallow aquifers located in an agricultural area, impacted by an old tin mine, were explored to understand spatial variation in microbial community structures and identify environmental factors influencing microbial distribution patterns through the analysis of 16S rRNA and aioA genes. Although Proteobacteria, Cyanobacteria, Actinobacteria, Patescibacteria, Bacteroidetes, and Epsilonbacteraeota were widespread across the analyzed aquifers, the dominant taxa found in each aquifer were unique. The co-dominance of Burkholderiaceae and Gallionellaceae potentially controlled arsenic immobilization in the aquifers. Analysis of the aioA gene suggested that arsenite-oxidizing bacteria phylogenetically associated with Alpha-, Beta-, and Gamma proteobacteria were present at low abundance (0.85 to 37.13%) and were more prevalent in shallow aquifers and surface water. The concentrations of dissolved oxygen and total phosphorus significantly governed the microbiomes analyzed in this study, while the combination of NO3--N concentration and oxidation-reduction potential significantly influenced the diversity and abundance of arsenite-oxidizing bacteria in the aquifers. The knowledge of microbial community structures and functions in relation to deep and shallow aquifers is required for further development of sustainable aquifer management.

// Karen Klepsland Mauland 1, 2 , Elisabeth Wik 3, 4, * , Erling A. Hoivik 1, 2, * , Kanthida Kusonmano 2, 5, 6 , Mari Kylleso Halle 1, 2 , Anna Berg 1, 2 , Hans Kristian Haugland 4 , Anne Margrete Oyan 1, 7 , Karl-Henning Kalland 1, 7 , Ingunn Marie Stefansson 4 , Lars A. Akslen 3, 4 , Camilla Krakstad 1, 8 , Jone Trovik 1, 2 , Henrica Maria Johanna Werner 1, 2 and Helga Birgitte Salvesen 1, 2, ** 1 Center for Cancer Biomarkers CCBIO, Department of Clinical Science (K2), University of Bergen, Bergen, Norway 2 Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway 3 Center for Cancer Biomarkers CCBIO, Department of Clinical Medicine (K1), Section for Pathology, University of Bergen, Bergen, Norway 4 Department of Pathology, Haukeland University Hospital, Bergen, Norway 5 Computational Biology Unit, University of Bergen, Bergen, Norway 6 Bioinformatics and Systems Biology Program, School of Bioresources and Technology, King Mongkut’s University of Technology Thonburi, Bangkhuntien, Bangkok, Thailand 7 Department of Microbiology, Haukeland University Hospital, Bergen, Norway 8 Center for Cancer Biomarkers CCBIO, Department of Biomedicine, University of Bergen, Bergen, Norway * These authors have contributed equally to this work ** Deceased Correspondence to: Karen Klepsland Mauland, email: Karen.Mauland@uib.no Keywords: endometrial cancer, DNA ploidy, prognosis, transcriptional alterations, chromosome 15q Received: October 06, 2016 Accepted: November 23, 2016 Published: December 25, 2016 ABSTRACT Aneuploidy is a widely studied prognostic marker in endometrial cancer (EC), however, not implemented in clinical decision-making. It lacks validation in large prospective patient cohorts adjusted for currently standard applied prognostic markers, including estrogen/progesterone receptor status (ER/PR). Also, little is known about aneuploidy-related transcriptional alterations, relevant for understanding its role in EC biology, and as therapeutic target. We included 825 EC patients with available ploidy status and comprehensive clinicopathologic characterization to analyze ploidy as a prognostic marker. For 144 patients, gene expression data were available to explore aneuploidy-related transcriptional alterations. Aneuploidy was associated with high age, FIGO stage and grade, non-endometrioid histology, ER/PR negativity, and poor survival (p-values

Recent studies have detailed the genomic landscape of primary endometrial cancers, but the evolution of these cancers into metastases has not been characterized. We performed whole-exome sequencing of 98 tumor biopsies including complex atypical hyperplasias, primary tumors and paired abdominopelvic metastases to survey the evolutionary landscape of endometrial cancer. We expanded and reanalyzed The Cancer Genome Atlas (TCGA) data, identifying new recurrent alterations in primary tumors, including mutations in the estrogen receptor cofactor gene NRIP1 in 12% of patients. We found that likely driver events were present in both primary and metastatic tissue samples, with notable exceptions such as ARID1A mutations. Phylogenetic analyses indicated that the sampled metastases typically arose from a common ancestral subclone that was not detected in the primary tumor biopsy. These data demonstrate extensive genetic heterogeneity in endometrial cancers and relative homogeneity across metastatic sites.

Purpose: Amplification of PIK3CA, encoding the PI3K catalytic subunit alpha, is common in uterine corpus endometrial carcinoma (UCEC) and linked to an aggressive phenotype. However, it is unclear whether PIK3CA amplification acts via PI3K activation. We investigated the association between PIK3CA amplification, markers of PI3K activity, and prognosis in a large cohort of UCEC specimens. Experimental Design: UCECs from 591 clinically annotated patients including 83 tumors with matching metastasis (n = 188) were analyzed by FISH to determine PIK3CA copy-number status. These data were integrated with mRNA and protein expression and clinicopathologic data. Results were verified in The Cancer Genome Atlas dataset. Results: PIK3CA amplifications were associated with disease-specific mortality and with other markers of aggressive disease. PIK3CA amplifications were also associated with other amplifications characteristic of the serous-like somatic copy-number alteration (SCNA)–high subgroup of UCEC. Tumors with PIK3CA amplification also demonstrated an increase in phospho-p70S6K but had decreased levels of activated phospho-AKT1-3 as assessed by Reverse Phase Protein Arrays and an mRNA signature of MTOR inhibition. Conclusions: PIK3CA amplification is a strong prognostic marker and a potential marker for the aggressive SCNA-high subgroup of UCEC. Although PIK3CA amplification associates with some surrogate measures of increased PI3K activity, markers for AKT1-3 and MTOR signaling are decreased, suggesting that this signaling is not a predominant pathway to promote cancer growth of aggressive serous-like UCEC. Moreover, these associations may reflect features of the SCNA-high subgroup of UCEC rather than effects of PIK3CA amplification itself.

We have identified nine highly connected and differentially expressed gene subnetworks between aggressive primary tumors and metastatic lesions in endometrial carcinomas. We implemented a novel pipeline combining gene set and network approaches, which here allows integration of protein-protein interactions and gene expression data. The resulting subnetworks are significantly associated with disease progression across tumor stages from complex atypical hyperplasia, primary tumors to metastatic lesions. The nine subnetworks include genes related to metastasizing features such as epithelial-mesenchymal transition (EMT), hypoxia and cell proliferation. TCF4 and TWIST2 were found as central genes in the subnetwork related to EMT. Two of the identified subnetworks display statistically significant association to patient survival, which were further supported by an independent validation in the data from The Cancer Genome Atlas data collection. The first subnetwork contains genes related to cell proliferation and cell cycle, while the second contains genes involved in hypoxia such as HIF1A and EGLN3. Our findings provide a promising context to elucidate the biological mechanisms of metastasis, suggest potential prognostic markers and further identify therapeutic targets. The pipeline R source code is freely available, including permutation tests to assess statistical significance of the identified subnetworks.

// Ingunn M. Stefansson 1,2,* , Maria Raeder 1,3,* , Elisabeth Wik 1,2 , Monica Mannelqvist 1,2 , Kanthida Kusonmano 1,3 , Goril Knutsvik 1,2 , Ingfrid Haldorsen 4,5 , Jone Trovik 1,3 , Anne M. Oyan 1,6 , Karl-H. Kalland 1,6 , Anne Cathrine Staff 7 , Helga B. Salvesen 1,3 and Lars A. Akslen 1,2 1 Centre for Cancer Biomarkers CCBIO, Department of Clinical Medicine, Section for Pathology, University of Bergen, Bergen, Norway 2 Department of Pathology, Haukeland University Hospital, Bergen, Norway 3 Department of Obstetrics and Gynaecology, Haukeland University Hospital, Bergen, Norway 4 Department of Radiology, Haukeland University Hospital, Postbox, Bergen, Norway 5 Section for Radiology, University of Bergen, Bergen, Norway 6 Department of Microbiology, Haukeland University Hospital, Bergen, Norway 7 Department of Obstetrics and Gynaecology, Women and Children’s Division, Oslo University Hospital, University of Oslo, Norway * These authors contributed equally to this work Correspondence to: Lars A. Akslen, email: // Keywords : angiogenesis, endometrial cancer, gene expression signature, prognosis Received : January 19, 2015 Accepted : February 17, 2015 Published : March 10, 2015 Abstract Background: Angiogenesis is a hallmark of cancer. The aim of this study was to explore whether microvessel proliferation is associated with gene expression profiles or copy number alterations in endometrial cancer. Methods: A prospective series of endometrial carcinomas was studied for angiogenesis markers, gene expression profiles, and gene copy number data. For validation, an independent series of endometrial carcinomas as well as an external cohort of endometrial cancer patients were examined by gene expression microarrays. Results: Increased microvessel proliferation (MVP) was associated with aggressive tumor features and reduced survival, and a 32-gene expression signature was found to separate tumors with high versus low MVP. An increased 32-gene signature score was confirmed to associate with high-grade tumor features and reduced survival by independent cohorts. Copy number studies revealed that amplification of the 6p21 region was significantly associated with MVP, a high 32-gene score, as well as reduced survival. Conclusion: Increased MVP was significantly associated with aggressive endometrial cancer and reduced survival. Integrated analyses demonstrated significant associations between increased vascular proliferation, amplification of the 6p21 region, VEGF-A mRNA expression, and the 32-gene angiogenesis signature. Our findings indicate amplification of 6p21 as a possible driver of tumor vascular proliferation in endometrial cancer.

Mutations of the phosphoinositide-3-kinase (PI3K) catalytic subunit alpha gene (PIK3CA) are frequent in endometrial cancer. We sequenced exon9 and exon20 of PIK3CA in 280 primary endometrial cancers to assess the relationship with clinicopathologic variables, patient survival and associations with PIK3CA mRNA and phospho-AKT1 by gene expression and protein data, respectively. While PIK3CA mutations generally had no impact on survival, and were not associated with clinicopathological variables, patients with exon9 charge-changing mutations, providing a positive charge at the substituted amino acid residue, were associated with poor survival (p = 0.018). Furthermore, we characterized PIK3CA mutations in the metastatic setting, including 32 patients with matched primary tumors and metastases, and found a high level of concordance (85.7%; 6 out of 7 patients), suggesting limited heterogeneity. PIK3CA mRNA levels were increased in metastases compared to the primary tumors (p = 0.031), independent of PIK3CA mutation status, which rather associated with reduced PIK3CA mRNA expression. PIK3CA mutated tumors expressed higher p-AKT/AKT protein levels, both within primary (p PIK3CA mutations, an aspect that should be considered when designing PIK3 pathway targeting strategies in endometrial cancer.

Background Cervical cancer is a major health problem worldwide. Identification of effective clinicopathologic and molecular markers is vital to improve treatment stratification. Objectives The purpose of this study was to validate a set of well-defined clinicopathologic features in a large population-based, prospectively collected cervical cancer cohort to support their use in the clinic. Further, we explored p53 and human epidermal growth factor receptor 2 as potential prognostic markers in cervical cancer. Study Design Tissue was collected from 401 patients with cervical cancer. Clinical data that included follow-up evaluations were collected from patient journals. Histopathologic data were evaluated and revised by an expert pathologist. The prognostic impact of selected clinicopathologic variables was analyzed in the whole cohort. Tissue microarrays were prepared from 292 carcinomas, and p53 and human epidermal growth factor receptor 2 protein levels were evaluated by immunohistochemistry. Fresh frozen samples from overlapping cervical carcinomas previously were subjected to human papilloma virus typing (n=94), whole exome (n=100) and RNA (n=79) sequencing; the results were available for our analyses. Results Among the clinicopathologic variables, vascular space invasion, histologic type, and tumor size were verified as strong independent prognostic markers. High p53 protein levels were associated significantly with markers for aggressive phenotype and survival, also in multivariate survival analysis, but did not reflect TP53 mutational status. High human epidermal growth factor receptor 2 protein levels were identified in 21% of all tumors. ERBB2 amplification was associated with poor outcome ( P =.003); human epidermal growth factor receptor 2 protein level was not. Conclusions Our findings support that the Federation Internationale de Gynecologie et d'Obstetrique s guidelines should include vascular space invasion and tumor size 2–4 cm and that careful selection of histologic type is essential for stratification of patient risk groups. High p53 levels independently predict poor survival yet do not reflect mutational status in cervical cancer. Amplified ERBB2 significantly links to poor survival, while HercepTest does not. With optimal stratification, human epidermal growth factor receptor 2–based therapy may improve cervical cancer treatment.

Obesity is linked to increased incidence of endometrioid endometrial cancer (EEC) and complex atypical hyperplasia (CAH). We here explore pattern and sequence of molecular alterations characterizing endometrial carcinogenesis in general and related to body mass index (BMI), to improve diagnostic stratification and treatment strategies. We performed molecular characterization of 729 prospectively collected EEC and CAH. Candidate biomarkers were identified in frozen samples by whole-exome and Sanger sequencing, oligonucleotide gene expression and Reverse Phase Protein Arrays (investigation cohort) and further explored in formalin fixed tissues by immunohistochemistry and Fluorescent in Situ Hybridization (validation cohort). We here demonstrate that PIK3CA mutations, PTEN loss, PI3K and KRAS activation are early events in endometrial carcinogenesis. Molecular changes related to KRAS activation and inflammation are more common in obese CAH patients, suggesting different prevention and systemic treatment strategies in obese and non-obese patients. We also found that oncoprotein Stathmin might improve preoperative diagnostic distinction between premalignant and malignant endometrial lesions.

Background: Recent identification of a specific role of HSF1 in cancer progression has led to new relevance of HSF1 as both a prognostic and a predictive marker. The role of HSF1 in endometrial cancer has so far been unexplored. Methods: A total of 823 lesions from endometrial carcinoma precursors, primary tumours and metastases were prospectively collected and explored for HSF1 protein expression in relation to established markers for aggressive disease and survival. Transcriptional alterations related to HSF1 protein level were investigated by microarray analysis for 224 freshly frozen samples in parallel. Results: High expression of HSF1 protein in endometrial carcinoma is significantly associated with aggressive disease and poor survival (all P-values ⩽0.02), also among ERα-positive patients presumed to have good prognosis. The HSF1-related gene signatures increase during disease progression and were also found to have prognostic value. Gene expression analyses identified HSP90 inhibition as a potential novel therapeutic approach for cases with high protein expression of HSF1. Conclusions: We demonstrate for the first time in endometrial cancer that high expression of HSF1 and measures for transcriptional activation of HSF1 associate with poor outcome and disease progression. The HSP90 inhibitors are suggested as new targeted therapeutics for patients with high HSF1 levels in tumour in particular.

Cancers arise through accumulating genetic and epigenetic alterations, considered relevant for phenotype and approaches to targeting new therapies. We investigated a unique collection of endometrial cancer precursor samples and clinically annotated primary and metastatic lesions for two evolutionary and functionally related transcription factors, CCCTC-binding factor (zinc finger protein) (CTCF) and its paralogue CTCF-like factor, also denoted Brother of the Regulator of Imprinted Sites (CTCFL/BORIS). CTCF, a chromatin modeling- and transcription factor, is normally expressed in a ubiquitous fashion, while CTCFL/BORIS is restricted to the testis. In cancer, CTCF is thought to be a tumor suppressor, while CTCFL/BORIS has been suggested as an oncogene. CTCF mutations were identified in 13 %, with CTCF hotspot frameshift mutations at p.T204, all observed solely in the endometrioid subtype, but with no association with outcome. Interestingly, CTCFL/BORIS was amongst the top ranked genes differentially expressed between endometrioid and non-endometrioid tumors, and increasing mRNA level of CTCFL/BORIS was highly significantly associated with poor survival. As aberrant CTCFL/BORIS expression might relate to loss of methylation, we explored methylation status in clinical samples from complex atypical hyperplasia, through primary tumors to metastatic lesions, demonstrating a pattern of DNA methylation loss during disease development and progression in line with the increase in CTCFL/BORIS mRNA expression observed. Thus, CTCF and CTCFL/BORIS are found to diverge in the different subtypes of endometrial cancer, with CTCFL/BORIS activation through demethylation from precursors to metastatic lesions. We thus propose, CTCFL/BORIS as an Epi-driver gene in endometrial cancer, suggesting a potential for future vaccine development.

Cancer remains a fundamental burden to public health despite substantial efforts aimed at developing effective chemotherapeutics and significant advances in chemotherapeutic regimens. The major challenge in anti-cancer drug design is to selectively target cancer cells with high specificity. Research into treating malignancies by targeting altered metabolism in cancer cells is supported by computational approaches, which can take a leading role in identifying candidate targets for anti-cancer therapy as well as assist in the discovery and optimisation of anti-cancer agents. Natural products appear to have privileged structures for anti-cancer drug development and the bulk of this particularly valuable chemical space still remains to be explored. In this review we aim to provide a comprehensive overview of current strategies for computer-guided anti-cancer drug development. We start with a discussion of state-of-the art bioinformatics methods applied to the identification of novel anti-cancer targets, including machine learning techniques, the Connectivity Map and biological network analysis. This is followed by an extensive survey of molecular modelling and cheminformatics techniques employed to develop agents targeting proteins involved in the glycolytic, lipid, NAD+, mitochondrial (TCA cycle), amino acid and nucleic acid metabolism of cancer cells. A dedicated section highlights the most promising strategies to develop anti-cancer therapeutics from natural products and the role of metabolism and some of the many targets which are under investigation are reviewed. Recent success stories are reported for all the areas covered in this review. We conclude with a brief summary of the most interesting strategies identified and with an outlook on future directions in anti-cancer drug development.

Following the availability of high-throughput technologies, vast amounts of biological data have been generated. Gene expression is one example of the popular data that has been utilized for studying cellular systems in the transcriptional level. Several bioinformatics approaches have been developed to analyze such data. A typical expression analysis identifies a ranked list of individual significant differentially expressed genes between two conditions of interest. However, it has been accepted that biomolecules in a living organism are working together and interacting with each other. Study through network analysis could be complementary to typical expression analysis and provides more contexts to understanding the biological systems. Conversely, expression data could provide clues to functional links between biomolecules in biological networks. In this chapter, bioinformatics approaches to analyze expression data in network levels including basic concepts of network biology are described. Different concepts to integrate expression data with interactome data and example studies are explained.

Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

Following the availability of high-throughput technologies, vast amounts of biological data have been generated. Gene expression is one example of the popular data that has been utilized for studying cellular systems in the transcriptional level. Several bioinformatics approaches have been developed to analyze such data. A typical expression analysis identifies a ranked list of individual significant differentially expressed genes between two conditions of interest. However, it has been accepted that biomolecules in a living organism are working together and interacting with each other. Study through network analysis could be complementary to typical expression analysis and provides more contexts to understanding the biological systems. Conversely, expression data could provide clues to functional links between biomolecules in biological networks. In this chapter, bioinformatics approaches to analyze expression data in network levels including basic concepts of network biology are described. Different concepts to integrate expression data with interactome data and example studies are explained.

Background: Three quarter of endometrial carcinomas are treated at early stage. Still, 15 to 20% of these patients experience recurrence, with little effect from systemic therapies. Homo sapiens v-Ki-ras2 Kirsten rat sarcoma viral oncogenes homologue (KRAS) mutations have been reported to have an important role in tumorigenesis for human cancers, but there is limited knowledge regarding clinical relevance of KRAS status in endometrial carcinomas. Methods: We have performed a comprehensive and integrated characterisation of genome-wide expression related to KRAS mutations and copy-number alterations in primary- and metastatic endometrial carcinoma lesions in relation to clinical and histopathological data. A primary investigation set and clinical validation set was applied, consisting of 414 primary tumours and 61 metastatic lesions totally. Results: Amplification and gain of KRAS present in 3% of the primary lesions and 18% of metastatic lesions correlated significantly with poor outcome, high International Federation of Gynaecology and Obstetrics stage, non-endometrioid subtype, high grade, aneuploidy, receptor loss and high KRAS mRNA levels, also found to be associated with aggressive phenotype. In contrast, KRAS mutations were present in 14.7% of primary lesions with no increase in metastatic lesions, and did not influence outcome, but was significantly associated with endometrioid subtype, low grade and obesity. Conclusion: These results support that KRAS amplification and KRAS mRNA expression, both increasing from primary to metastatic lesions, are relevant for endometrial carcinoma disease progression.

Cancer is ranked as one of the top killers in all human diseases and continues to have a devastating effect on the population around the globe. Current research efforts are aiming to accelerate our understanding of the molecular basis of cancer and develop effective means for cancer diagnostics, treatment and prognosis. An altered pattern of epigenetic modifications, most importantly DNA methylation events, plays a critical role in tumorigenesis through regulating oncogene activation, tumor suppressor gene silencing and chromosomal instability. To study interplay of DNA methylation, gene expression and cancer, we developed a publicly accessible database for human DNA Methylation and Cancer (MethyCancer, http://methycancer.genomics.org.cn). MethyCancer hosts both highly integrated data of DNA methylation, cancer-related gene, mutation and cancer information from public resources, and the CpG Island (CGI) clones derived from our large-scale sequencing. Interconnections between different data types were analyzed and presented. Furthermore, a powerful search tool is developed to provide user-friendly access to all the data and data connections. A graphical MethyView shows DNA methylation in context of genomics and genetics data facilitating the research in cancer to understand genetic and epigenetic mechanisms that make dramatic changes in gene expression of tumor cells.

We have explored the potential for clinical implementation of ATAD2 as a biomarker for aggressive endometrial cancer by investigating to what extent immunohistochemical (IHC) staining for ATAD2 is feasible, reflects clinical phenotype and molecular subgroups of endometrial carcinomas. Increased expression of the ATAD2 gene has been implicated in cancer development and progression in a number of tissues, but few studies have investigated ATAD2 expression using IHC. Here we show that high ATAD2 protein expression is significantly associated with established clinical-pathological variables for aggressive endometrial cancer, also in the subset of estrogen receptor α (ERα) positive tumors. Protein and mRNA expression of ATAD2 were highly correlated (P < 0.001), suggesting that IHC staining may represent a more clinically applicable measure of ATAD2 level in routinely collected formalin fixed paraffin embedded specimens. Gene expression alterations in samples with high ATAD2 expression revealed upregulation of several cancer-related genes (B-MYB, CDCs, E2Fs) and gene sets that previously have been linked to aggressive disease and potential for new targeting therapies. Our results support that IHC staining for ATAD2 may be a clinically applicable biomarker reflecting clinical phenotype and targetable alterations in endometrial carcinomas to be further explored in controlled clinical trials. publishedVersion

In endometrial cancer loss of progesterone receptor (PR, gene name PGR) is associated with aggressive disease and altered response to hormonal treatment. The aim of this study was to investigate changes in PR expression level with disease progression, and explore whether differences in gene expression according to PR status can be linked to processes involved in cancer development elucidating new therapeutic opportunities.686 primary endometrial cancers and 171 metastatic lesions were investigated for PR expression in relation to clinical and histopathological data. Protein levels were investigated by immunohistochemistry and reverse phase protein array, and mRNA levels by DNA oligonucleotide microarray.PR protein level was significantly associated with PGR mRNA expression (P0.001) and patient survival (P0.001). Loss of PR increased with disease progression, with 23% of the primary tumours and 76% of metastases demonstrating PR loss. Using a cell cycle progression signature score, PR loss was associated with increased proliferation for both oestrogen receptor (ER) positive and negative tumours. Through a Connectivity Map search, CDK inhibitors and other drugs with anti-proliferative effects were suggested in particular for treatment of patients with loss of PR.Loss of PR in endometrial cancer is associated with increased proliferation, poor survival, and increases from primary to metastatic lesions. Based on expression profiles, CDK inhibitors may have activity in PR negative tumours, supporting further testing in clinical trials for patients with systemic endometrial cancer dependent on PR status.

Background: The transcription factor Forkhead box A1 (FOXA1) is suggested to be important in hormone dependent cancers, although with little data for endometrial cancer. We investigated expression levels of FOXA1 in primary and metastatic endometrial cancer in relation to clinical phenotype, and transcriptional alterations related to FOXA1 status. Methods: Protein expression of FOXA1 was explored by immunohistochemistry in 529 primary and 199 metastatic endometrial carcinoma lesions. mRNA levels from corresponding 158 fresh frozen primary and 42 metastatic lesions were analyzed using Agilent Microarrays (44k) in parallel. Results: Low FOXA1 protein expression in primary tumors significantly correlated with low FOXA1 mRNA, high age, non-endometrioid histology, high grade, loss of ERα and PR and poor survival (all p-values

Our previously reported 29-gene expression signature identified an aggressive subgroup of endometrial cancer patients with PI3K activation. We here wanted to validate these findings by independent patient series.The 29-gene expression signature was assessed in fresh frozen tumor tissue from 280 primary endometrial carcinomas (three independent cohorts), 19 metastatic lesions and in 333 primary endometrial carcinomas using TCGA data, and expression was related to clinico-pathologic features and survival. The 29-gene signature was assessed by real-time quantitative PCR, DNA oligonucleotide microarrays, or RNA sequencing. PI3K alterations were assessed by immunohistochemistry, DNA microarrays, DNA sequencing, SNP arrays or fluorescence in situ hybridization. A panel of markers of epithelial-mesenchymal transition (EMT) was also correlated to the 29-gene signature score.High 29-gene Endometrial Carcinoma Recurrence Score (ECARS) values consistently validated to identify patients with aggressive clinico-pathologic phenotype and reduced survival. Within the presumed favorable subgroups of low grade, endometrioid tumors confined to the uterus, high ECARS still predicted a poor prognosis. The score was higher in metastatic compared to primary lesions (P0.001) and was significantly associated with potential measures of PI3K activation, markers of EMT and vascular invasion as an indicator of metastatic spread (all P0.001).ECARS validates to identify aggressive endometrial carcinomas in multiple, independent patients cohorts. The higher signature score in metastatic compared to primary lesions, and the potential link to PI3K activation and EMT, support further studies of ECARS in relation to response to PI3K and EMT inhibitors in clinical trials of metastatic endometrial carcinoma.

Purpose: High Stathmin expression has recently been associated with clinical progress in endometrial cancers. Stathmin protein activity is modulated by phosphorylation, and the Serine38 site is one of four Stathmin phospho-sites. The presence and significance of pStathmin(S38) is largely unknown in human cancers, and we here examined the associations between this marker and tumor cell proliferation, clinicopathologic phenotype, and survival impact in endometrial cancer. A relationship with possible treatment targets was explored by integrated analysis of transcriptional alterations. Experimental Design: Primary endometrial cancers from two independent patient series (n = 518/n = 286) were analyzed. Biomarkers were assessed by immunohistochemistry, FISH, flow cytometry, DNA oligonucleotide microarray, single-nucleotide polymorphism array, and Sanger sequencing, and related to clinicopathologic annotations and follow-up information. Results: High pStathmin(S38) level was associated with poor prognosis, independent of other features, and correlated to increased tumor cell proliferation as well as high Stathmin levels. On the basis of transcriptional differences between high/low pStathmin(S38) tumors, phosphoinositide 3-kinase (PI3K)/mTOR/HSP90 were suggested as possible targets in pStathmin(S38)-high cases. High pStathmin(S38) was associated with several PI3K pathway alterations: amplification of the 3q26 region, increased PIK3CA copy number (FISH) and a PI3K activation score (all P < 0.05). Conclusions: High pStathmin(S38) is a novel biomarker of increased tumor cell proliferation and impaired prognosis as reported here for independent cohorts of endometrial cancer and not previously shown in human cancer. Our data support a rationale for further studies exploring effects of drugs inhibiting the PI3K signaling pathway in pStathmin(S38)-high endometrial cancer, including a potential value of pStathmin(S38) in predicting response to PI3K/mTOR/HSP90 inhibitors. Clin Cancer Res; 19(9); 2331–41. ©2013 AACR.

ARID1A (AT-rich interactive domain 1A) has recently been identified as a tumor suppressor gene in various, predominantly gynecological cancers. We wanted to investigate the distribution of ARID1A in endometrial hyperplasia, carcinomas and metastatic lesions to elucidate the timing of expression loss of its protein ARID1A in the course of endometrial cancer carcinogenesis. In addition, we wanted to assess the relationship between the loss of ARID1A and clinicopathological variables in endometrial cancer in general and the endometrioid subtype in particular. We analyzed a prospectively collected series of 535 primary endometrial cancers, 77 metastatic lesions, as well as 38 retrospectively collected endometrial hyperplasias with evaluable immunohistochemical staining for ARID1A. Fresh frozen tissue was available for mRNA microarray analysis in 122 primary tumors in parallel. Loss of ARID1A protein expression was noted in none of the hyperplasias without atypia, 16% of hyperplasias with atypia, 19% of primary endometrioid tumors and 28% of metastatic lesions. Loss of ARID1A in primary tumor was significantly associated with endometrioid grade 1 or 2 and clear-cell histology, diploid tumor cells, younger patient age and deeper myometrial infiltration, but not survival. ARID1A RNA expression was significantly correlated with ARID1A protein loss. Thus, loss of ARID1A appears to be an early event in the carcinogenesis of endometrioid uterine carcinomas and the association with deep myometrial infiltration may suggest an importance for invasiveness.

A pooling design can be used as a powerful strategy to compensate for limited amounts of samples or high biological variation. In this paper, we perform a comparative study to model and quantify the effects of virtual pooling on the performance of the widely applied classifiers, support vector machines (SVMs), random forest (RF),k-nearest neighbors (k-NN), penalized logistic regression (PLR), and prediction analysis for microarrays (PAMs). We evaluate a variety of experimental designs using mock omics datasets with varying levels of pool sizes and considering effects from feature selection. Our results show that feature selection significantly improves classifier performance for non-pooled and pooled data. All investigated classifiers yield lower misclassification rates with smaller pool sizes. RF mainly outperforms other investigated algorithms, while accuracy levels are comparable among all the remaining ones. Guidelines are derived to identify an optimal pooling scheme for obtaining adequate predictive power and, hence, to motivate a study design that meets best experimental objectives and budgetary conditions, including time constraints.