Transgelin-2, a novel cancer stem cell-related biomarker, is a diagnostic and therapeutic target for biliary tract cancer.

BACKGROUND: Biliary tract cancer (BTC) is a relatively rare but aggressive gastrointestinal cancer with a high mortality rate. Cancer stem cell (CSC) populations play crucial roles in tumor biology and are responsible for the low response to anti-cancer treatment and the high recurrence rate. This study investigated the role of Transgelin-2 (TAGLN2), overexpressed in CSC in BTC cells, and analyzed its expression in patient tissues and serum to identify potential new targets for BTC. METHODS: TAGLN2 expression was suppressed by small-interfering or short hairpin RNAs, and its effects on tumor biology were assessed in several BTC cell lines. Furthermore, the effects of TAGLN2 silencing on gemcitabine-resistant BTC cells, differentially expressed genes, proteins, and sensitivity to therapeutics or radiation were assessed. TAGLN2 expression was also assessed using western blotting and immunohistochemistry in samples obtained from patients with BTC to validate its clinical application. RESULTS: Suppression of TAGLN2 in BTC cell lines decreased cell proliferation, migration, invasion, and tumor size, in addition to a reduction in CSC features, including clonogenicity, radioresistance, and chemoresistance. TAGLN2 was highly expressed in BTC tissues, especially in cancer-associated fibroblasts in the stroma. Patients with a low stromal immunohistochemical index had prolonged disease-free survival compared to those with a high stromal immunohistochemical index (11.5 vs. 7.4 months, P = 0.013). TAGLN2 expression was higher in the plasma of patients with BTC than that in those with benign diseases. TAGLN2 had a higher area under the curve (0.901) than CA19-9, a validated tumor biomarker (0.799; P < 0.001). CONCLUSION: TAGLN2 plays a critical role in promoting BTC cell growth and motility and is involved in regulating BTC stemness. Silencing TAGLN2 expression enhanced cell sensitivity to radiation and chemotherapeutic drugs. The expression of TAGLN2 in patient tissue and plasma suggests its potential to serve as a secretory biomarker for BTC. Overall, targeting TAGLN2 could be an appropriate therapeutic strategy against advanced cancer following chemotherapy failure.

Transcriptome-wide analysis reveals GYG2 as a mitochondria-related aging biomarker in human subcutaneous adipose tissue.

Subcutaneous adipose tissue (SAT), a vital energy reservoir and endocrine organ for maintaining systemic glucose, lipid, and energy homeostasis, undergoes significant changes with age. However, among the existing aging-related markers, only few genes are associated with SAT aging. In this study, weighted gene co-expression network analysis was used on a transcriptome of SAT obtained from the Genotype-Tissue Expression portal to identify biologically relevant, SAT-specific, and age-related marker genes. We found modules that exhibited significant changes with age and identified GYG2 as a novel key aging associated gene. The link between GYG2 and mitochondrial function as well as brown/beige adipocytes was supported using additional bioinformatics and experimental analyses. Additionally, we identified PPARG as the transcription factor of GYG2 expression. The newly discovered GYG2 marker can be used to not only determine the age of SAT but also uncover new mechanisms underlying SAT aging.

Nasal Transcriptome and Epigenome Analysis Identifies the Pathogenic Features of Aspirin-Exacerbated Respiratory Disease.

Dysregulation of the arachidonic acid metabolic pathway is the most widely known pathomechanism of aspirin-exacerbated respiratory disease (AERD). This study aimed to perform integrative analysis of transcriptomic and epigenomic profiling with network analysis to determine the novel pathogenic features of AERD. Ten patients with asthma including 5 patients with AERD and another 5 patients with aspirin tolerant asthma (ATA) were enrolled. Nasal scraping was performed and nasal mucosa was used in omics profiling. Peripheral eosinophil counts, sputum eosinophil counts, fractional exhaled nitric oxide levels, and pulmonary function test results were evaluated. Differentially expressed genes (DEGs), differentially methylated probes (DMPs) and differentially correlated genes (DCGs) between patients with AERD and those with ATA were analyzed. Network analysis using ingenuity pathway analysis (IPA) was performed to determine the gene connection network and signaling pathways. In total, 1,736 DEGs, 1,401 DMPs, and 19 pairs for DCGs were identified. Among DCGs, genes related to vesicle transport (e.g., RAB3B and STX2) and sphingolipid dysregulation (e.g., SMPD3) were found to be hypo-methylated and up-regulated in AERD. Using the canonical pathway analysis of IPA with 78 asthma-related DEGs, signaling pathways of T helper cell differentiation/activation and Fcε receptor I were generated. Up-regulation of RORγt and FcER1A were noted in AERD. Gene expression levels of RAB3B, SYNE1, STX2, SMPD3 and RORγt were significantly associated with sputum eosinophil counts. Quantitative real-time polymerase chain reaction was performed and mRNA expression levels of STX2, SMPD3, RORγt, and FcER1A were significantly higher in AERD compared to ATA. Distinct pathogenic features were identified by using integrative multi-omics data analysis in patients with AERD.

RiceNet v2: an improved network prioritization server for rice genes.

Rice is the most important staple food crop and a model grass for studies of bioenergy crops. We previously published a genome-scale functional network server called RiceNet, constructed by integrating diverse genomics data and demonstrated the use of the network in genetic dissection of rice biotic stress responses and its usefulness for other grass species. Since the initial construction of the network, there has been a significant increase in the amount of publicly available rice genomics data. Here, we present an updated network prioritization server for Oryza sativa ssp. japonica, RiceNet v2 (http://www.inetbio.org/ricenet), which provides a network of 25 765 genes (70.1% of the coding genome) and 1 775 000 co-functional links. Ricenet v2 also provides two complementary methods for network prioritization based on: (i) network direct neighborhood and (ii) context-associated hubs. RiceNet v2 can use genes of the related subspecies O. sativa ssp. indica and the reference plant Arabidopsis for versatility in generating hypotheses. We demonstrate that RiceNet v2 effectively identifies candidate genes involved in rice root/shoot development and defense responses, demonstrating its usefulness for the grass research community.

Interaction specificity and coexpression of rice NPR1 homologs 1 and 3 (NH1 and NH3), TGA transcription factors and Negative Regulator of Resistance (NRR) proteins.

BACKGROUND: The nonexpressor of pathogenesis-related genes 1, NPR1 (also known as NIM1 and SAI1), is a key regulator of SA-mediated systemic acquired resistance (SAR) in Arabidopsis. In rice, the NPR1 homolog 1 (NH1) interacts with TGA transcriptional regulators and the Negative Regulator of Resistance (NRR) protein to modulate the SAR response. Though five NPR1 homologs (NHs) have been identified in rice, only NH1 and NH3 enhance immunity when overexpressed. To understand why NH1 and NH3, but not NH2, NH4, or NH5, contribute to the rice immune response, we screened TGA transcription factors and NRR-like proteins for interactions specific to NH1 and NH3. We also examined their co-expression patterns using publicly available microarray data. RESULTS: We tested five NHs, four NRR homologs (RHs), and 13 rice TGA proteins for pair-wise protein interactions using yeast two-hybrid (Y2H) and split YFP assays. A survey of 331 inter-family interactions revealed a broad, complex protein interaction network. To investigate preferred interaction partners when all three families of proteins were present, we performed a bridged split YFP assay employing YFPN-fused TGA, YFPC-fused RH, and NH proteins without YFP fusions. We found 64 tertiary interactions mediated by NH family members among the 120 sets we examined. In the yeast two-hybrid assay, each NH protein was capable of interacting with most TGA and RH proteins. In the split YFP assay, NH1 was the most prevalent interactor of TGA and RH proteins, NH3 ranked the second, and NH4 ranked the third. Based on their interaction with TGA proteins, NH proteins can be divided into two subfamilies: NH1, NH2, and NH3 in one family and NH4 and NH5 in the other.In addition to evidence of overlap in interaction partners, co-expression analyses of microarray data suggest a correlation between NH1 and NH3 expression patterns, supporting their common role in rice immunity. However, NH3 is very tightly co-expressed with RH1 and RH2, while NH1 is strongly, inversely co-expressed with RH proteins, representing a difference between NH1 and NH3 expression patterns. CONCLUSIONS: Our genome-wide surveys reveal that each rice NH protein can partner with many rice TGA and RH proteins and that each NH protein prefers specific interaction partners. NH1 and NH3 are capable of interacting strongly with most rice TGA and RH proteins, whereas NH2, NH4, and NH5 have weaker, limited interaction with TGA and RH proteins in rice cells. We have identified rTGA2.1, rTGA2.2, rTGA2.3, rLG2, TGAL2 and TGAL4 proteins as the preferred partners of NH1 and NH3, but not NH2, NH4, or NH5. These TGA proteins may play an important role in NH1- and NH3-mediated immune responses. In contrast, NH4 and NH5 preferentially interact with TGAL5, TGAL7, TGAL8 and TGAL9, which are predicted to be involved in plant development.

Three Novel Rice Genes Closely Related to the Arabidopsis IRX9, IRX9L, and IRX14 Genes and Their Roles in Xylan Biosynthesis.

Xylan is the second most abundant polysaccharide on Earth, and represents a major component of both dicot wood and the cell walls of grasses. Much knowledge has been gained from studies of xylan biosynthesis in the model plant, Arabidopsis. In particular, the irregular xylem (irx) mutants, named for their collapsed xylem cells, have been essential in gaining a greater understanding of the genes involved in xylan biosynthesis. In contrast, xylan biosynthesis in grass cell walls is poorly understood. We identified three rice genes Os07g49370 (OsIRX9), Os01g48440 (OsIRX9L), and Os06g47340 (OsIRX14), from glycosyltransferase family 43 as putative orthologs to the putative ß-1,4-xylan backbone elongating Arabidopsis IRX9, IRX9L, and IRX14 genes, respectively. We demonstrate that the over-expression of the closely related rice genes, in full or partly complement the two well-characterized Arabidopsis irregular xylem (irx) mutants: irx9 and irx14. Complementation was assessed by measuring dwarfed phenotypes, irregular xylem cells in stem cross sections, xylose content of stems, xylosyltransferase (XylT) activity of stems, and stem strength. The expression of OsIRX9 in the irx9 mutant resulted in XylT activity of stems that was over double that of wild type plants, and the stem strength of this line increased to 124% above that of wild type. Taken together, our results suggest that OsIRX9/OsIRX9L, and OsIRX14, have similar functions to the Arabidopsis IRX9 and IRX14 genes, respectively. Furthermore, our expression data indicate that OsIRX9 and OsIRX9L may function in building the xylan backbone in the secondary and primary cell walls, respectively. Our results provide insight into xylan biosynthesis in rice and how expression of a xylan synthesis gene may be modified to increase stem strength.

Genetic dissection of the biotic stress response using a genome-scale gene network for rice.

Rice is a staple food for one-half the world's population and a model for other monocotyledonous species. Thus, efficient approaches for identifying key genes controlling simple or complex traits in rice have important biological, agricultural, and economic consequences. Here, we report on the construction of RiceNet, an experimentally tested genome-scale gene network for a monocotyledonous species. Many different datasets, derived from five different organisms including plants, animals, yeast, and humans, were evaluated, and 24 of the most useful were integrated into a statistical framework that allowed for the prediction of functional linkages between pairs of genes. Genes could be linked to traits by using guilt-by-association, predicting gene attributes on the basis of network neighbors. We applied RiceNet to an important agronomic trait, the biotic stress response. Using network guilt-by-association followed by focused protein-protein interaction assays, we identified and validated, in planta, two positive regulators, LOC_Os01g70580 (now Regulator of XA21; ROX1) and LOC_Os02g21510 (ROX2), and one negative regulator, LOC_Os06g12530 (ROX3). These proteins control resistance mediated by rice XA21, a pattern recognition receptor. We also showed that RiceNet can accurately predict gene function in another major monocotyledonous crop species, maize. RiceNet thus enables the identification of genes regulating important crop traits, facilitating engineering of pathways critical to crop productivity.

Differentially expressed microRNAs in pancreatic cancer stem cells.

OBJECTIVE: The objective of this study was to analyze and identify pancreatic cancer stem cell-specific microRNAs (miRNAs) and messenger RNAs (mRNAs) to investigate their correlations to cancer stem cell biology. METHODS: We used sphere cultivation methods to enrich the stem cell population and analyzed overall miRNA and mRNA expressions using microarray analysis. RESULTS: Differentially expressed miRNAs including miR-99a, miR-100, miR-125b, miR-192, and miR-429 were detected in pancreatic cancer stem cells. Furthermore, examining both profiles, we obtained 210 miRNAs and 258 stem cell-associated mRNAs that were differentially expressed in the pancreatic cancer stem cells. These miRNAs and mRNAs were further investigated using cross-correlation analysis, which yielded 6 groups of miRNAs and 3 groups of mRNAs. The number of miRNA clusters and mRNA clusters showed high correlation based on microarray result. CONCLUSIONS: Differentially expressed miRNAs in pancreatic cancer stem cells provide insights into possible linkages between clusters of miRNAs and clusters of stem cell-associated mRNAs in cancer stem cells and have broad implications in our understanding of cancer stem cells and cancer stem cell-targeted cancer therapy.