Soil Microbiomes and their Arsenic Functional Genes in Chronically High-Arsenic Contaminated Soils.

Microbial arsenic transformations play essential roles in controlling pollution and ameliorating risk. This study combined high-throughput sequencing and PCR-based approaches targeting both the 16 S rRNA and arsenic functional genes to investigate the temporal and spatial dynamics of the soil microbiomes impacted by high arsenic contamination (9.13 to 911.88 mg/kg) and to investigate the diversity and abundance of arsenic functional genes in soils influenced by an arsenic gradient. The results showed that the soil microbiomes were relatively consistent and mainly composed of Actinobacteria (uncultured Gaiellales and an unknown_67 - 14 bacterium), Proteobacteria, Firmicutes (particularly, Bacillus), Chloroflexi, and Acidobacteria (unknown_Subgroup_6). Although a range of arsenic functional genes (e.g., arsM, arsC, arrA, and aioA) were identified by shotgun metagenomics, only the arsM gene was detected by the PCR-based method. The relative abundance of the arsM gene accounted for 0.20%-1.57% of the total microbial abundance. Combining all analyses, arsenic methylation mediated by the arsM gene was proposed to be a key process involved in the arsenic biogeochemical cycle and mitigation of arsenic toxicity. This study advances our knowledge about arsenic mechanisms over the long-term in highly contaminated soils.

Arsenic speciation, the abundance of arsenite-oxidizing bacteria and microbial community structures in groundwater, surface water, and soil from a gold mine.

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.

HER2 expression patterns in paired primary and metastatic endometrial cancer lesions.

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.

Clinicopathologic and molecular markers in cervical carcinoma: a prospective cohort study.

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 Féderation Internationale de Gynécologie et d'Obstétrique 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.

Informatics for Metabolomics.

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.

Distinct gut microbiomes in Thai patients with colorectal polyps.

BACKGROUND: Colorectal polyps that develop via the conventional adenoma-carcinoma sequence [e.g., tubular adenoma (TA)] often progress to malignancy and are closely associated with changes in the composition of the gut microbiome. There is limited research concerning the microbial functions and gut microbiomes associated with colorectal polyps that arise through the serrated polyp pathway, such as hyperplastic polyps (HP). Exploration of microbiome alterations associated with HP and TA would improve the understanding of mechanisms by which specific microbes and their metabolic pathways contribute to colorectal carcinogenesis. AIM: To investigate gut microbiome signatures, microbial associations, and microbial functions in HP and TA patients. METHODS: Full-length 16S rRNA sequencing was used to characterize the gut microbiome in stool samples from control participants without polyps [control group (CT), n = 40], patients with HP (n = 52), and patients with TA (n = 60). Significant differences in gut microbiome composition and functional mechanisms were identified between the CT group and patients with HP or TA. Analytical techniques in this study included differential abundance analysis, co-occurrence network analysis, and differential pathway analysis. RESULTS: Colorectal cancer (CRC)-associated bacteria, including Streptococcus gallolyticus (S. gallolyticus), Bacteroides fragilis, and Clostridium symbiosum, were identified as characteristic microbial species in TA patients. Mediterraneibacter gnavus, associated with dysbiosis and gastrointestinal diseases, was significantly differentially abundant in the HP and TA groups. Functional pathway analysis revealed that HP patients exhibited enrichment in the sulfur oxidation pathway exclusively, whereas TA patients showed dominance in pathways related to secondary metabolite biosynthesis (e.g., mevalonate); S. gallolyticus was a major contributor. Co-occurrence network and dynamic network analyses revealed co-occurrence of dysbiosis-associated bacteria in HP patients, whereas TA patients exhibited co-occurrence of CRC-associated bacteria. Furthermore, the co-occurrence of SCFA-producing bacteria was lower in TA patients than HP patients. CONCLUSION: This study revealed distinct gut microbiome signatures associated with pathways of colorectal polyp development, providing insights concerning the roles of microbial species, functional pathways, and microbial interactions in colorectal carcinogenesis.

CAIM: Coverage-based Analysis for Identification of Microbiome.

Accurate taxonomic profiling of microbial taxa in a metagenomic sample is vital to gain insights into microbial ecology. Recent advancements in sequencing technologies have contributed tremendously toward understanding these microbes at species resolution through a whole shotgun metagenomic (WMS) approach. In this study, we developed a new bioinformatics tool, CAIM, for accurate taxonomic classification and quantification within both long- and short-read metagenomic samples using an alignment-based method. CAIM depends on two different containment techniques to identify species in metagenomic samples using their genome coverage information to filter out false positives rather than the traditional approach of relative abundance. In addition, we propose a nucleotide-count based abundance estimation, which yield lesser root mean square error than the traditional read-count approach. We evaluated the performance of CAIM on 28 metagenomic mock communities and 2 synthetic datasets by comparing it with other top-performing tools. CAIM maintained a consitently good performance across datasets in identifying microbial taxa and in estimating relative abundances than other tools. CAIM was then applied to a real dataset sequenced on both Nanopore (with and without amplification) and Illumina sequencing platforms and found high similality of taxonomic profiles between the sequencing platforms. Lastly, CAIM was applied to fecal shotgun metagenomic datasets of 232 colorectal cancer patients and 229 controls obtained from 4 different countries and primary 44 liver cancer patients and 76 controls. The predictive performance of models using the genome-coverage cutoff was better than those using the relative-abundance cutoffs in discriminating colorectal cancer and primary liver cancer patients from healthy controls with a highly confident species markers.

ARID1A loss is prevalent in endometrial hyperplasia with atypia and low-grade endometrioid carcinomas.

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.

Microbiome variations among age classes and diets of captive Asian elephants (Elephas maximus) in Thailand using full-length 16S rRNA nanopore sequencing.

Asian elephant (Elephas maximus) is the national symbol of Thailand and linked to Thai history and culture for centuries. The elephant welfare improvement is one of the major components to achieve sustainable captive management. Microbiome inhabiting digestive tracts have been shown with symbiotic relations to host health. This work provided high-resolution microbiome profiles of 32 captive elephants at a species level by utilizing full-length 16S rRNA gene nanopore sequencing. Eleven common uncultured bacterial species were found across elephants fed with solid food including uncultured bacterium Rikenellaceae RC9 gut group, Kiritimatiellae WCHB1-41, Phascolarctobacterium, Oscillospiraceae NK4A214 group, Christensenellaceae R-7 group, Oribacterium, Oscillospirales UCG-010, Lachnospiraceae, Bacteroidales F082, uncultured rumen Rikenellaceae RC9 gut group, and Lachnospiraceae AC2044 group. We observed microbiome shifts along the age classes of baby (0-2 years), juvenile (2-10 years), and adult (> 10 years). Interestingly, we found distinct microbiome profiles among adult elephants fed with a local palm, Caryota urens, as a supplement. Potential beneficial microbes have been revealed according to the age classes and feed diets. The retrieved microbiome data could be provided as good baseline microbial profiles for monitoring elephant health, suggesting further studies towards dietary selection suitable for each age class and the use of local supplementary diets.

Lipocalin 2 expression is associated with aggressive features of endometrial cancer.

BACKGROUND: Increased expression of lipocalin 2 (LCN2) has been observed in several cancers. The aim of the present study was to investigate LCN2 in endometrial cancer in relation to clinico-pathologic phenotype, angiogenesis, markers of epithelial-mesenchymal transition (EMT), and patient survival. METHODS: Immunohistochemical staining was performed using a human LCN2 antibody on a population-based series of endometrial cancer patients collected in Hordaland County (Norway) during 1981-1990 (n = 256). Patients were followed from the time of primary surgery until death or last follow-up in 2007. The median follow-up time for survivors was 17 years. Gene expression data from a prospectively collected endometrial cancer series (n = 76) and a publicly available endometrial cancer series (n = 111) was used for gene correlation studies. RESULTS: Expression of LCN2 protein, found in 49% of the cases, was associated with non-endometrioid histologic type (p = 0.001), nuclear grade 3 (p = 0.001), >50% solid tumor growth (p = 0.001), ER and PR negativity (p = 0.028 and 0.006), and positive EZH2 expression (p < 0.001). LCN2 expression was significantly associated with expression of VEGF-A (p = 0.021), although not with other angiogenesis markers examined (vascular proliferation index, glomeruloid microvascular proliferation, VEGF-C, VEGF-D or bFGF2 expression). Further, LCN2 was not associated with several EMT-related markers (E-cadherin, N-cadherin, P-cadherin, ß-catenin), nor with vascular invasion (tumor cells invading lymphatic or blood vessels). Notably, LCN2 was significantly associated with distant tumor recurrences, as well as with the S100A family of metastasis related genes. Patients with tumors showing no LCN2 expression had the best outcome with 81% 5-year survival, compared to 73% for intermediate and 38% for the small subgroup with strong LCN2 staining (p = 0.007). In multivariate analysis, LCN2 expression was an independent prognostic factor in addition to histologic grade and FIGO stage. CONCLUSION: Increased LCN2 expression is associated with aggressive features and poor prognosis in endometrial cancer.

Effects of pooling samples on the performance of classification algorithms: a comparative study.

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.

Comparative Metagenomics Reveals Microbial Signatures of Sugarcane Phyllosphere in Organic Management.

Converting conventional farms to organic systems to improve ecosystem health is an emerging trend in recent decades, yet little is explored to what extent and how this process drives the taxonomic diversity and functional capacity of above-ground microbes. This study was, therefore, conducted to investigate the effects of agricultural management, i.e., organic, transition, and conventional, on the structure and function of sugarcane phyllosphere microbial community using the shotgun metagenomics approach. Comparative metagenome analysis exhibited that farming practices strongly influenced taxonomic and functional diversities, as well as co-occurrence interactions of phyllosphere microbes. A complex microbial network with the highest connectivity was observed in organic farming, indicating strong resilient capabilities of its microbial community to cope with the dynamic environmental stressors. Organic farming also harbored genus Streptomyces as the potential keystone species and plant growth-promoting bacteria as microbial signatures, including Mesorhizobium loti, Bradyrhizobium sp. SG09, Lactobacillus plantarum, and Bacillus cellulosilyticus. Interestingly, numerous toxic compound-degrading species were specifically enriched in transition farming, which might suggest their essential roles in the transformation of conventional to organic farming. Moreover, conventional practice diminished the abundance of genes related to cell motility and energy metabolism of phyllosphere microbes, which could negatively contribute to lower microbial diversity in this habitat. Altogether, our results demonstrated the response of sugarcane-associated phyllosphere microbiota to specific agricultural managements that played vital roles in sustainable sugarcane production.

Microbial community structure in aquifers associated with arsenic: analysis of 16S rRNA and arsenite oxidase genes.

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.

MethyCancer: the database of human DNA methylation and cancer.

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.

Diverse Microbial Community Profiles of Propionate-Degrading Cultures Derived from Different Sludge Sources of Anaerobic Wastewater Treatment Plants.

Anaerobic digestion (AD) has been used for wastewater treatment and production of renewable energy or biogas. Propionate accumulation is one of the important problems leading to an unstable system and low methane production. Revealing propionate-degrading microbiome is necessary to gain a better knowledge for alleviation of the problem. Herein, we systematically investigated the propionate-degrading cultures enriched from various anaerobic sludge sources of agro-industrial wastewater treatment plants using 16S rRNA gene sequencing. Different microbial profiles were shown even though the methanogenic activities of all cultures were similar. Interestingly, non-classical propionate-degrading key players Smithella, Syntrophomonas, and Methanosaeta were observed as common prevalent taxa in our enriched cultures. Moreover, different hydrogenotrophic methanogens were found specifically to the different sludge sources. The enriched culture of high salinity sludge showed a distinct microbial profile compared to the others, containing mainly Thermovirga, Anaerolinaceae, Methanosaeta, Syntrophobactor, and Methanospirillum. Our microbiome analysis revealed different propionate-degrading community profiles via mainly the Smithella pathway and offers inside information for microbiome manipulation in AD systems to increase biogas production corresponding to their specific microbial communities.

Genetic Aberration Analysis in Thai Colorectal Adenoma and Early-Stage Adenocarcinoma Patients by Whole-Exome Sequencing.

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.

PIK3CA Amplification Associates with Aggressive Phenotype but Not Markers of AKT-MTOR Signaling in Endometrial Carcinoma.

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.

Identification of highly connected and differentially expressed gene subnetworks in metastasizing endometrial cancer.

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.

Gene Expression Analysis Through Network Biology: Bioinformatics Approaches.

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.

PIK3CA exon9 mutations associate with reduced survival, and are highly concordant between matching primary tumors and metastases 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 < 0.001) and metastatic lesion (p = 0.010). Our results support the notion that the PI3K signaling pathway might be activated, both dependent- and independently of PIK3CA mutations, an aspect that should be considered when designing PIK3 pathway targeting strategies in endometrial cancer.