Intrinsic subtypes in Ethiopian breast cancer patient.

PURPOSE: The recent development of multi-gene assays for gene expression profiling has contributed significantly to the understanding of the clinically and biologically heterogeneous breast cancer (BC) disease. PAM50 is one of these assays used to stratify BC patients and individualize treatment. The present study was conducted to characterize PAM50-based intrinsic subtypes among Ethiopian BC patients. PATIENTS AND METHODS: Formalin-fixed paraffin-embedded tissues were collected from 334 BC patients who attended five different Ethiopian health facilities. All samples were assessed using the PAM50 algorithm for intrinsic subtyping. RESULTS: The tumor samples were classified into PAM50 intrinsic subtypes as follows: 104 samples (31.1%) were luminal A, 91 samples (27.2%) were luminal B, 62 samples (18.6%) were HER2-enriched and 77 samples (23.1%) were basal-like. The intrinsic subtypes were found to be associated with clinical and histopathological parameters such as steroid hormone receptor status, HER2 status, Ki-67 proliferation index and tumor differentiation, but not with age, tumor size or histological type. An immunohistochemistry-based classification of tumors (IHC groups) was found to correlate with intrinsic subtypes. CONCLUSION: The distribution of the intrinsic subtypes confirms previous immunohistochemistry-based studies from Ethiopia showing potentially endocrine-sensitive tumors in more than half of the patients. Health workers in primary or secondary level health care facilities can be trained to offer endocrine therapy to improve breast cancer care. Additionally, the findings indicate that PAM50-based classification offers a robust method for the molecular classification of tumors in the Ethiopian context.

Relationship of micro-RNA, mRNA and eIF Expression in Tamoxifen-Adapted MCF-7 Breast Cancer Cells: Impact of miR-1972 on Gene Expression, Proliferation and Migration.

BACKGROUND: Tamoxifen-adapted MCF-7-Tam cells represent an in-vitro model for acquired tamoxifen resistance, which is still a problem in clinics. We here investigated the correlation of microRNA-, mRNA- and eukaryotic initiation factors (eIFs) expression in this model. METHODS: MicroRNA- and gene expression were analyzed by nCounter and qRT-PCR technology; eIFs by Western blotting. Protein translation mode was determined using a reporter gene assay. Cells were transfected with a miR-1972-mimic. RESULTS: miR-181b-5p,-3p and miR-455-5p were up-, miR-375, and miR-1972 down-regulated and are significant in survival analysis. About 5% of the predicted target genes were significantly altered. Pathway enrichment analysis suggested a contribution of the FoxO1 pathway. The ratio of polio-IRES driven to cap-dependent protein translation shifted towards cap-dependent initiation. Protein expression of eIF2A, -4G, -4H and -6 decreased, whereas eIF3H was higher in MCF-7-Tam. Significant correlations between tamoxifen-regulated miRNAs and eIFs were found in representative breast cancer cell lines. Transfection with a miR-1972-mimic reverses tamoxifen-induced expression for a subset of genes and increased proliferation in MCF-7, but reduced proliferation in MCF-7-Tam, especially in the presence of 4OH-tamoxifen. Migration was inhibited in MCF-7-Tam cells. Translation mode remained unaffected. CONCLUSIONS: miR-1972 contributes to the orchestration of gene-expression and physiological consequences of tamoxifen adaption.

Identifying High-Risk Triple-Negative Breast Cancer Patients by Molecular Subtyping.

INTRODUCTION: Triple-negative breast cancer (TNBC) is considered the most aggressive type of breast cancer (BC) with limited options for therapy. TNBC is a heterogeneous disease and tumors have been classified into TNBC subtypes using gene expression profiling to distinguish basal-like 1, basal-like 2, immunomodulatory, mesenchymal, mesenchymal stem-like, luminal androgen receptor (LAR), and one nonclassifiable group (called unstable). OBJECTIVES: The aim of this study was to verify the clinical relevance of molecular subtyping of TNBCs to improve the individual indication of systemic therapy. PATIENTS AND METHODS: Molecular subtyping was performed in 124 (82%) of 152 TNBC tumors that were obtained from a prospective, multicenter cohort including 1,270 histopathologically confirmed invasive, nonmetastatic BCs (NCT01592825). Treatment was guideline-based. TNBC subtypes were correlated with recurrence-free interval (RFI) and overall survival (OS) after 5 years of observation. RESULTS: Using PAM50 analysis, 87% of the tumors were typed as basal with an inferior clinical outcome compared to patients with nonbasal tumors. Using the TNBCtype-6 classifier, we identified 23 (15%) of TNBCs as LAR subtype. After standard adjuvant or neoadjuvant chemotherapy, patients with LAR subtype showed the most events for 5-year RFI (66.7 vs. 80.6%) and the poorest probability of 5-year OS (60.0 vs. 84.4%) compared to patients with non-LAR disease (RFI: adjusted hazard ratio [aHR] = 1.87, 95% confidence interval [CI] 0.69-5.05, p = 0.211; OS: aHR = 2.74, 95% CI 1.06-7.10, p = 0.037). CONCLUSION: Molecular analysis and subtyping of TNBC may be relevant to identify patients with LAR subtype. These cancers seem to be less sensitive to conventional chemotherapy, and new treatment options, including androgen receptor-blocking agents and immune checkpoint inhibitors, have to be explored.

Causes and Consequences of A Glutamine Induced Normoxic HIF1 Activity for the Tumor Metabolism.

The transcription factor hypoxia-inducible factor 1 (HIF1) is the crucial regulator of genes that are involved in metabolism under hypoxic conditions, but information regarding the transcriptional activity of HIF1 in normoxic metabolism is limited. Different tumor cells were treated under normoxic and hypoxic conditions with various drugs that affect cellular metabolism. HIF1α was silenced by siRNA in normoxic/hypoxic tumor cells, before RNA sequencing and bioinformatics analyses were performed while using the breast cancer cell line MDA-MB-231 as a model. Differentially expressed genes were further analyzed and validated by qPCR, while the activity of the metabolites was determined by enzyme assays. Under normoxic conditions, HIF1 activity was significantly increased by (i) glutamine metabolism, which was associated with the release of ammonium, and it was decreased by (ii) acetylation via acetyl CoA synthetase (ACSS2) or ATP citrate lyase (ACLY), respectively, and (iii) the presence of L-ascorbic acid, citrate, or acetyl-CoA. Interestingly, acetylsalicylic acid, ibuprofen, L-ascorbic acid, and citrate each significantly destabilized HIF1α only under normoxia. The results from the deep sequence analyses indicated that, in HIF1-siRNA silenced MDA-MB-231 cells, 231 genes under normoxia and 1384 genes under hypoxia were transcriptionally significant deregulated in a HIF1-dependent manner. Focusing on glycolysis genes, it was confirmed that HIF1 significantly regulated six normoxic and 16 hypoxic glycolysis-associated gene transcripts. However, the results from the targeted metabolome analyses revealed that HIF1 activity affected neither the consumption of glucose nor the release of ammonium or lactate; however, it significantly inhibited the release of the amino acid alanine. This study comprehensively investigated, for the first time, how normoxic HIF1 is stabilized, and it analyzed the possible function of normoxic HIF1 in the transcriptome and metabolic processes of tumor cells in a breast cancer cell model. Furthermore, these data imply that HIF1 compensates for the metabolic outcomes of glutaminolysis and, subsequently, the Warburg effect might be a direct consequence of the altered amino acid metabolism in tumor cells.

RNA-Seq analysis of soft rush (Juncus effusus): transcriptome sequencing, de novo assembly, annotation, and polymorphism identification.

BACKGROUND: Juncus effusus L. (family: Juncaceae; order: Poales) is a helophytic rush growing in temperate damp or wet terrestrial habitats and is of almost cosmopolitan distribution. The species has been studied intensively with respect to its interaction with co-occurring plants as well as microbes being involved in major biogeochemical cycles. J. effusus has biotechnological value as component of Constructed Wetlands where the plant has been employed in phytoremediation of contaminated water. Its genome has not been sequenced. RESULTS: In this study we carried out functional annotation and polymorphism analysis of de novo assembled RNA-Seq data from 18 genotypes using 249 million paired-end Illumina HiSeq reads and 2.8 million 454 Titanium reads. The assembly comprised 158,591 contigs with a mean contig length of 780 bp. The assembly was annotated using the dammit! annotation pipeline, which queries the databases OrthoDB, Pfam-A, Rfam, and runs BUSCO (Benchmarking Single-Copy Ortholog genes). In total, 111,567 contigs (70.3%) were annotated with functional descriptions, assigned gene ontology terms, and conserved protein domains, which resulted in 30,932 non-redundant gene sequences. Results of BUSCO and KEGG pathway analyses were similar for J. effusus as for the well-studied members of the Poales, Oryza sativa and Sorghum bicolor. A total of 566,433 polymorphisms were identified in transcribed regions with an average frequency of 1 polymorphism in every 171 bases. CONCLUSIONS: The transcriptome assembly was of high quality and genome coverage was sufficient for global analyses. This annotated knowledge resource can be utilized for future gene expression analysis, genomic feature comparisons, genotyping, primer design, and functional genomics in J. effusus.

Comparison of the oral microbiome of patients with generalized aggressive periodontitis and periodontitis-free subjects.

OBJECTIVE: The primary objectives of the study were to assess differences in complex subgingival bacterial composition between periodontitis-free persons and patients with generalized aggressive periodontitis (gAgP). BACKGROUND: The composition of the oral microbiota plays an important role for both oral and systemic diseases. However, the complex nature of the oral microbiome and its homeostasis is still poorly understood. MATERIAL AND METHODS: We compared the microbiome of 13 periodontitis-free persons to 13 patients with gAgP. The 16S rRNA genes were amplified, targeting the V3/V4 region using the MiSeq platform. RESULTS: In total, 1713 different bacterial species were mapped according to the Greengenes database. Using the Shannon index, no significant differences in alpha diversity were found between the two study groups. In principal component and linear discriminant analyses, disease-specific differences in beta diversity of the microbiome composition were evaluated. Bacteroidetes, Spirochaetes, and Synergistetes were more abundant in gAgP whereas Proteobacteria, Firmicutes, and Actinobacteria were associated with a healthy periodontium. At the bacterial species level, we showed that Porphyromonas gingivalis is the strongest indicator of gAgP. Treponema denticola and Tanerella forsythia of the "red complex" as well as Filifactor alocis were among the ten best biomarkers for gAgP. CONCLUSIONS: These results broaden our knowledge of disease-specific differences in the microbial community associated with generalized AgP. A more complex view of the composition of the oral microbiome describes the etiology of generalized AgP in more detail. These results could help to individually adapt periodontal therapy in these patients.

Time resolved gene expression analysis during tamoxifen adaption of MCF-7 cells identifies long non-coding RNAs with prognostic impact.

Acquired tamoxifen resistance is a persistent problem for the treatment of estrogen receptor positive, premenopausal breast cancer patients and predictive biomarkers are still elusive. We here analyzed gene expression changes in a cellular model to identify early and late changes upon tamoxifen exposure and thereby novel prognostic biomarkers. Estrogen receptor positive MCF-7 cells were incubated with 4OH-tamoxifen (10 nM) and gene expression analyzed by array hybridization during 12 weeks. Array results were confirmed by nCounter- and qRT-PCR technique. Pathway enrichment analysis revealed that early responses concerned mainly amine synthesis and NRF2-related signaling and evolved into a stable gene expression pattern within 4 weeks characterized by changes in glucuronidation-, estrogen metabolism-, nuclear receptor- and interferon signaling pathways. As a large number of long non coding RNAs was subject to regulation, we investigated 5 of these (linc01213, linc00632 linc0992, LOC101929547 and XR_133213) in more detail. From these, only linc01213 was upregulated but all were less abundant in estrogen-receptor negative cell lines (MDA-MB 231, SKBR-3 and UACC3199). In a web-based survival analysis linc01213 and linc00632 turned out to have prognostic impact. Linc01213 was investigated further by plasmid-mediated over-expression as well as siRNA down-regulation in MCF-7 cells. Nevertheless, this had no effect on proliferation or expression of tamoxifen regulated genes, but migration was increased. In conclusion, the cellular model identified a set of lincRNAs with prognostic relevance for breast cancer. One of these, linc01213 although regulated by 4OH-tamoxifen, is not a central regulator of tamoxifen adaption, but interferes with the regulation of migration.

Highly parallel assays of tissue-specific enhancers in whole Drosophila embryos.

Transcriptional enhancers are a primary mechanism by which tissue-specific gene expression is achieved. Despite the importance of these regulatory elements in development, responses to environmental stresses and disease, testing enhancer activity in animals remains tedious, with a minority of enhancers having been characterized. Here we describe 'enhancer-FACS-seq' (eFS) for highly parallel identification of active, tissue-specific enhancers in Drosophila melanogaster embryos. Analysis of enhancers identified by eFS as being active in mesodermal tissues revealed enriched DNA binding site motifs of known and putative, previously uncharacterized mesodermal transcription factors. Naive Bayes classifiers using transcription factor binding site motifs accurately predicted mesodermal enhancer activity. Application of eFS to other cell types and organisms should accelerate the cataloging of enhancers and understanding how transcriptional regulation is encoded in them.