Transcriptomic Analyses Reveal Long Non-Coding RNA in Peripheral Blood Mononuclear Cells as a Novel Biomarker for Diagnosis and Prognosis of Hepatocellular Carcinoma.

Novel biomarkers are highly required for the diagnosis and predicting prognosis of hepatocellular carcinoma (HCC). In this study, we investigated the profiles of long non-coding RNAs (lncRNAs) obtained from the peripheral blood mononuclear cells (PBMCs) of patients with HCC and PBMCs from a co-culture model using transcriptomic analysis. The differentially expressed lncRNAs (DElncRNAs) were then characterized and integrated as cancer-induced lncRNAs. Among them, three up-regulating DElncRNAs including MIR4435-2HG, SNHG9 and lnc-LCP2-1 and one down-regulating, lnc-POLD3-2, were identified. The functional analysis showed that these enriched lncRNAs were mainly associated with carcinogenesis and immune responses. Following further validation in PBMCs samples (100 HBV-related HCC, 100 chronic hepatitis B and 100 healthy controls), MIR4435-2HG, lnc-POLD3-2 and their combination were revealed to be sensitive biomarkers in discriminating HCC from non-HCC (AUROC = 0.78, 0.80, and 0.87, respectively), particularly among individuals with normal serum alpha-fetoprotein levels. Additionally, high circulating SNHG9 expression was shown to be an independent prognostic factor of overall survival in patients with HCC. These results indicate that determining these lncRNAs in PBMCs could serve as novel diagnostic and prognostic biomarkers for HBV-related HCC.

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.

Identification and validation of circulating miRNAs as potential new biomarkers for severe liver disease in patients with leptospirosis.

BACKGROUND: Leptospirosis, a global zoonotic infectious disease, has various clinical manifestations ranging from mild self-limiting illness to life-threatening with multi-organ damage, including liver involvement. This study was aimed at identifying circulating microRNAs (miRNAs) as novel biomarkers for predicting severe liver involvement in patients with leptospirosis. METHODS: In a discovery set, 12 serum samples of patients with anicteric and icteric leptospirosis at initial clinical presentation were used for miRNA profiling by a NanoString nCounter miRNA assay. In a validated cohort, top candidate miRNAs were selected and further tested by qRT-PCR in serum samples of 81 and 16 individuals with anicteric and icteric leptospirosis, respectively. RESULTS: The discovery set identified 38 significantly differential expression miRNAs between the two groups. Among these, miR-601 and miR-630 were selected as the top two candidates significantly up-regulated expressed in the icteric group. The enriched KEGG pathway showed that these miRNAs were mainly involved in immune responses and inflammation. In the validated cohort, miR-601 and miR-630 levels were significantly higher in the icteric group compared with the anicteric group. Additionally, these two miRNAs displayed good predictors of subsequent acute liver failure with a high sensitivity of 100%. On regression analysis, elevated miR-601 and miR-630 expression were also predictive of multi-organ failures and poor overall survival. CONCLUSION: Our data indicated that miRNA expression profiles were significantly differentiated between the icteric and anicteric groups. Serum miR-601 and miR-630 at presentation could potentially serve as promising biomarkers for predicting subsequent acute liver failure and overall survival in patients with leptospirosis.

The expression of FLNA and CLU in PBMCs as a novel screening marker for hepatocellular carcinoma.

Early detection improves survival and increases curative probability in hepatocellular carcinoma (HCC). Peripheral blood mononuclear cells (PBMCs) can provide an inexpensive, less-invasive and highly accurate method. The objective of this study is to find the potential marker for HCC screening, utilizing gene expression of the PBMCs. Data from the NCBI GEO database of gene expression in HCC patients and healthy donor's PBMCs was collected. As a result, GSE 49515 and GSE 58208 were found. Using both, a statistical significance test was conducted in each gene expression of each data set which resulted in 187 genes. We randomized three selected genes (FLNA, CAP1, and CLU) from the significant p-value group (p-values < 0.001). Then, a total of 76 healthy donors, 153 HCC, 20 hepatic fibrosis, 20 non-alcoholic fatty liver were collected. Quantitative RT-PCR (qRT-PCR) was performed in cDNA from all blood samples from the qRT-PCR, The Cycle threshold (Ct) value of FLNA, CLU, CAP1 of HCC group (28.47 ± 4.43, 28.01 ± 3.75, 29.64 ± 3.90) were lower than healthy group (34.23 ± 3.54, 32.90 ± 4.15, 32.18 ± 5.02) (p-values < 0.0001). The accuracy, sensitivity and specificity of these genes as a screening tool were: FLNA (80.8%, 88.0%, 65.8%), CLU (63.4%, 93.3%, 31.3%), CAP1 (67.2%, 83.3%, 39.1%). The tests were performed in two and three gene combinations. Results demonstrated high accuracy of 86.2%, sensitivity of 85% and specificity of 88.4% in the FLNA and CLU combination. Furthermore, after analyzed using hepatic fibrosis and non-alcoholic fatty liver as a control, the FLNA and CLU combination is shown to have accuracy of 76.9%, sensitivity of 77.6% and specificity of 75%. Also, we founded that our gene combination performs better than the current gold standard for HCC screening. We concluded that FLNA and CLU combination have high potential for being HCC novel markers. Combined with current tumor markers, further research of the gene's expression might help identify more potential markers and improve diagnosis methods.

Cell-Free DNA Analysis by Whole-Exome Sequencing for Hepatocellular Carcinoma: A Pilot Study in Thailand.

Cell-free DNA (cfDNA) has been used as a non-invasive biomarker for detecting cancer-specific mutations. However, the mutational profile of cfDNA in Thai patients with hepatocellular carcinoma (HCC) has not been investigated. Here, we demonstrated the utility of using whole-exome sequencing (WES) of cfDNA to define the somatic mutation profiles of HCC in Thai patients. The comprehensive profile of cfDNA was determined with WES to identify variants in matched cfDNA and germline DNA from 30 HCC patients in Thailand who underwent nonoperative therapies. The level of cfDNA was higher in HCC patients compared with chronic hepatitis patients (p-value < 0.001). Single nucleotide variants were present in somatic genes in cfDNA, including in ZNF814 (27%), HRNR (20%), ZNF492 (20%), ADAMTS12 (17%), FLG (17%), OBSCN (17%), TP53 (17%), and TTN (17%). These same mutations were matched to HCC mutation data from The Cancer Genome Atlas (TCGA) and a previous Thai HCC study. The co-occurrence of HRNR and TTN mutations in cfDNA was associated with shorter overall survival in HCC patients (hazard ratio = 1.60, p-value = 0.0196). These findings indicate that the mutational profile of cfDNA accurately reflected that of HCC tissue and suggest that cfDNA could serve as a useful biomarker for diagnosis and prognosis in Thai HCC patients. In addition, we demonstrated the use of the pocket-sized sequencer of Oxford Nanopore Technology to detect copy-number variants in HCC tissues that could be applied for onsite clinical detection/monitoring of HCC.

Identification of BHLHE40 expression in peripheral blood mononuclear cells as a novel biomarker for diagnosis and prognosis of hepatocellular carcinoma.

Novel and sensitive biomarkers is highly required for early detection and predicting prognosis of hepatocellular carcinoma (HCC). Here, we investigated transcription profiles from peripheral blood mononuclear cells (PBMCs) of 8 patients with HCC and PBMCs from co-culture model with HCC using RNA-Sequencing. These transcription profiles were cross compared with published microarray datasets of PBMCs in HCC to identify differentially expressed genes (DEGs). A total of commonly identified of 24 DEGs among these data were proposed as cancer-induced genes in PBMCs, including 18 upregulated and 6 downregulated DEGs. The KEGG pathway showed that these enriched genes were mainly associated with immune responses. Five up-regulated candidate genes including BHLHE40, AREG, SOCS1, CCL5, and DDIT4 were selected and further validated in PBMCs of 100 patients with HBV-related HCC, 100 patients with chronic HBV infection and 100 healthy controls. Based on ROC analysis, BHLHE40 and DDIT4 displayed better diagnostic performance than alpha-fetoprotein (AFP) in discriminating HCC from controls. Additionally, BHLHE40 and DDIT4 had high sensitivity for detecting AFP-negative and early-stage HCC. BHLHE40 was also emerged as an independent prognostic factor of overall survival of HCC. Together, our study indicated that BHLHE40 in PBMCs could be a promising diagnostic and prognostic biomarker for HBV-related HCC.