METHODS: RNA was isolated from peripheral whole blood samples (2 x 10 ml) collected from NPC patients/controls (EDTA vacutainer). Gene expression patterns from 99 samples (66 NPC; 33 controls) were assessed using the Affymetrix array. We also collected expression data from 447 patients with other cancers (201 patients) and non-cancer conditions (246 patients). Multivariate logistic regression analysis was used to obtain biomarker signatures differentiating NPC samples from controls and other diseases. Differences were also analysed within a subset (n=28) of a pre-intervention case cohort of patients whom we followed post-treatment.
RESULTS: A blood-based gene expression signature composed of three genes - LDLRAP1, PHF20, and LUC7L3 - is able to differentiate NPC from various other diseases and from unaffected controls with significant accuracy (area under the receiver operating characteristic curve of over 0.90). By subdividing our NPC cohort according to the degree of patient response to treatment we have been able to identify a blood gene signature that may be able to guide the selection of treatment.
CONCLUSION: We have identified a blood-based gene signature that accurately distinguished NPC patients from controls and from patients with other diseases. The genes in the signature, LDLRAP1, PHF20, and LUC7L3, are known to be involved in carcinoma of the head and neck, tumour-associated antigens, and/or cellular signalling. We have also identified blood-based biomarkers that are (potentially) able to predict those patients who are more likely to respond to treatment for NPC. These findings have significant clinical implications for optimizing NPC therapy.
AIM OF STUDY: The overall aim of this study was to investigate the gene expression profile of Ligno TG-K via de novo RNA-seq and pathway analysis. We also aimed to identify highly expressed genes encoding compounds that contribute to its cytotoxic and antioxidant properties, as well as perform a comparative transcriptomics analysis between Ligno TG-K and its sister species, L. rhinocerus TM02®.
MATERIALS AND METHODS: Total RNA from fresh 3-month-old cultivated L. tigris sclerotia (Ligno TG-K) was extracted and analyzed via de novo RNA sequencing. Expressed genes were analyzed using InterPro and NCBI-Nr databases for domain identification and homology search. Functional categorization based on gene functions and pathways was performed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Clusters of Orthologous Genes (COG) databases. Selected genes were subsequently subjected to phylogenetic analysis.
RESULTS: Our transcriptomics analysis of Ligno TG-K revealed that 68.06% of its genes are expressed in the sclerotium; 80.38% of these were coding transcripts. Our analysis identified highly expressed transcripts encoding proteins with prospective medicinal properties. These included serine proteases (FPKM = 7356.68), deoxyribonucleases (FPKM = 3777.98), lectins (FPKM = 3690.87), and fungal immunomodulatory proteins (FPKM = 2337.84), all of which have known associations with anticancer activities. Transcripts linked to proteins with antioxidant activities, such as superoxide dismutase (FPKM = 1161.69) and catalase (FPKM = 1905.83), were also highly expressed. Results of our sequence alignments revealed that these genes and their orthologs can be found in other mushrooms. They exhibit significant sequence similarities, suggesting possible parallels in their anticancer and antioxidant bioactivities.
CONCLUSION: This study is the first to provide a reference transcriptome profile of genes expressed in the sclerotia of L. tigris. The current study also presents distinct COG profiles of highly expressed genes in Ligno TG-K and L. rhinocerus TM02®, highlighting that any distinctions uncovered may be attributed to their interspecies variations and inherent characteristics that are unique to each species. Our findings suggest that Ligno TG-K contains bioactive compounds with prospective medicinal properties that warrant further investigations.
CLASSIFICATION: Systems biology and omics.
METHODS: In this study, the metabolic responses of C. glabrata under acetate growth condition was explored using high-throughput transcriptomic and proteomic approaches.
RESULTS: Collectively, a total of 1482 transcripts (26.96%) and 242 proteins (24.69%) were significantly up- or down-regulated. Both transcriptome and proteome data revealed that the regulation of alternative carbon metabolism in C. glabrata resembled other fungal pathogens such as Candida albicans and Cryptococcus neoformans, with up-regulation of many proteins and transcripts from the glyoxylate cycle and gluconeogenesis, namely isocitrate lyase (ICL1), malate synthase (MLS1), phosphoenolpyruvate carboxykinase (PCK1) and fructose 1,6-biphosphatase (FBP1). In the absence of glucose, C. glabrata shifted its metabolism from glucose catabolism to anabolism of glucose intermediates from the available carbon source. This observation essentially suggests that the glyoxylate cycle and gluconeogenesis are potentially critical for the survival of phagocytosed C. glabrata within the glucose-deficient macrophages.
CONCLUSION: Here, we presented the first global metabolic responses of C. glabrata to alternative carbon source using transcriptomic and proteomic approaches. These findings implicated that reprogramming of the alternative carbon metabolism during glucose deprivation could enhance the survival and persistence of C. glabrata within the host.
METHODS: We conducted transcriptome profiling on 32 colonic biopsies [11 long-duration UC, ≥20 years; and 21 short-duration UC, ≤5 years] using Affymetrix Human Transcriptome Array 2.0. Differentially expressed genes [fold change > 1.5, p < 0.05] and alternative splicing events [splicing index > 1.5, p < 0.05] were determined using the Transcriptome Analysis Console. KOBAS 3.0 and DAVID 6.8 were used for KEGG and GO analysis. Selected genes from microarray analysis were validated using qPCR.
RESULTS: There were 640 differentially expressed genes between both groups. The top ten upregulated genes were HMGCS2, UGT2A3 isoforms, B4GALNT2, MEP1B, GUCA2B, ADH1C, OTOP2, SLC9A3, and LYPD8; the top ten downregulated genes were PI3, DUOX2, VNN1, SLC6A14, GREM1, MMP1, CXCL1, TNIP3, TFF1, and LCN2. Among the 123 altered KEGG pathways, the most significant were metabolic pathways; fatty acid degradation; valine, leucine, and isoleucine degradation; the peroxisome proliferator-activated receptor signalling pathway; and bile secretion, which were previously linked with CAC. Analysis showed that 3560 genes exhibited differential alternative splicing between long- and short-duration UC. Among them, 374 were differentially expressed, underscoring the intrinsic relationship between altered gene expression and alternative splicing.
CONCLUSIONS: Long-duration UC patients have altered gene expressions, pathways, and alternative splicing events as compared with short-duration UC patients, and these could be further validated to improve our understanding of the pathogenesis of CAC.