• Chronic diseases
• Glycolipid metabolism
• Oxidative stress
• Targeted therapy
• Vanin1

• Humans
• Cysteamine/metabolism
• Oxidative Stress
• Pantothenic Acid/metabolism
• Chronic Disease
• Disease Progression
• Amidohydrolases/metabolism
• GPI-Linked Proteins/metabolism

• Chromatography, Liquid/methods
• Colorectal Neoplasms/diagnosis
• Double-Blind Method
• Humans
• Mass Spectrometry/methods
• Phosphopeptides/chemistry
• Silicon Dioxide

• National Key Research and Development Program of China
• Natural Science Foundation of Beijing Municipality
• National Natural Science Foundation of China

• atractylenolide
• sepsis
• forkhead box protein o1
• lung injury
• mice

• Amidohydrolases/antagonists & inhibitors
• Animals
• Apoptosis
• Forkhead Box Protein O1/antagonists & inhibitors
• GPI-Linked Proteins/antagonists & inhibitors
• Lactones
• Lung Injury
• Mice
• Sepsis/complications
• Sepsis/drug therapy
• Sesquiterpenes/pharmacology

• Biomarker
• Colon cancer
• Colorectal cancer
• Drug repositioning
• Omics
• Systems biology

• Chimeric rna
• benchmarking
• datasets
• fusion transcript
• software tools

Gene fusions and their products (RNA and protein) have been traditionally recognized as unique features of cancer cells and are used as ideal biomarkers and drug targets for multiple cancer types. However, recent studies have demonstrated that chimeric RNAs generated by intergenic alternative splicing can also be found in normal cells and tissues. In this study, we aim to identify chimeric RNAs in different non-neoplastic cell lines and investigate the landscape and expression of these novel candidate chimeric RNAs. To do so, we used HEK-293T, HUVEC, and LO2 cell lines as models, performed paired-end RNA sequencing, and conducted analyses for chimeric RNA profiles. Several filtering criteria were applied, and the landscape of chimeric RNAs was characterized at multiple levels and from various angles. Further, we experimentally validated 17 chimeric RNAs from different classifications. Finally, we examined a number of validated chimeric RNAs in different cancer and non-cancer cells, including blood from healthy donors, and demonstrated their ubiquitous expression pattern.

• chimeric RNA
• fusion transcript
• gene fusion

Chimeric RNAs and their encoded proteins have been traditionally viewed as unique features of neoplasia, and have been used as biomarkers and therapeutic targets for multiple cancers. Recent studies have demonstrated that chimeric RNAs also exist in non-cancerous cells and tissues, although large-scale, genome-wide studies of chimeric RNAs in non-diseased tissues have been scarce. Here, we explored the landscape of chimeric RNAs in 9495 non-diseased human tissue samples of 53 different tissues from the GTEx project. Further, we established means for classifying chimeric RNAs, and observed enrichment for particular classifications as more stringent filters are applied. We experimentally validated a subset of chimeric RNAs from each classification and demonstrated functional relevance of two chimeric RNAs in non-cancerous cells. Importantly, our list of chimeric RNAs in non-diseased tissues overlaps with some entries in several cancer fusion databases, raising concerns for some annotations. The data from this study provides a large repository of chimeric RNAs present in non-diseased tissues, which can be used as a control dataset to facilitate the identification of true cancer-specific chimeras.

• Chimeric/fusion protein identification
• In silico peptide digestion
• Proteomics

• Algorithms
• Amino Acid Sequence
• Computational Biology/methods
• Databases, Protein
• Gene Fusion
• Humans
• Peptides/genetics
• Peptides/metabolism
• Proteome
• Proteomics/methods
• Proteomics/standards
• Software

This study was designed to identify novel fusion transcripts (FTs) and their functional significance in colorectal cancer (CRC) lines.

We performed paired-end RNA sequencing of 28 CRC cell lines. FT candidates were identified using TopHat-fusion, ChimeraScan, and FusionMap tools and further experimental validation was conducted through reverse transcription-polymerase chain reaction and Sanger sequencing. FT was depleted in human CRC line and the effects on cell proliferation, cell migration, and cell invasion were analyzed.

One thousand three hundred eighty FT candidates were detected through bioinformatics filtering. We selected six candidate FTs, including four inter-chromosomal and two intrachromosomal FTs and each FT was found in at least one of the 28 cell lines. Moreover, when we tested 19 pairs of CRC tumor and adjacent normal tissue samples, NFATC3–PLA2G15 FT was found in two. Knockdown of NFATC3–PLA2G15 using siRNA reduced mRNA expression of epithelial–mesenchymal transition (EMT) markers such as vimentin, twist, and fibronectin and increased mesenchymal–epithelial transition markers of E-cadherin, claudin-1, and FOXC2 in colo-320 cell line harboring NFATC3–PLA2G15 FT. The NFATC3–PLA2G15 knockdown also inhibited invasion, colony formation capacity, and cell proliferation.

These results suggest that that NFATC3–PLA2G15 FTs may contribute to tumor progression by enhancing invasion by EMT and proliferation.

• Colorectal neoplasms
• Fusion transcript
• NFATC3
• PLA2G15
• RNA-sequencing

• Colon
• Colon cancer
• High throughput
• Next generation sequencing
• RNA sequencing
• Transcriptome

• Biomarkers, Tumor/genetics
• Colitis, Ulcerative/diagnosis
• Colitis, Ulcerative/genetics
• Colonic Diseases/diagnosis
• Colonic Diseases/genetics
• Colonic Diseases/therapy
• Colorectal Neoplasms/diagnosis
• Colorectal Neoplasms/genetics
• Crohn Disease/diagnosis
• Crohn Disease/genetics
• Genetic Markers
• Genetic Predisposition to Disease
• High-Throughput Nucleotide Sequencing
• Humans
• Irritable Bowel Syndrome/diagnosis
• Irritable Bowel Syndrome/genetics
• Phenotype
• Predictive Value of Tests
• Prognosis
• RNA/genetics
• RNA, Neoplasm/genetics
• Risk Factors
• Sequence Analysis, RNA/methods

With an annual estimated incidence of 1.4 million, and a five-year survival rate of 60%, colorectal cancer (CRC) is a major clinical burden. To identify novel RNA variants in CRC, we analyzed exon-level microarray expression data from a cohort of 202 CRCs. We nominated 25 genes with increased expression of their 3′ parts in at least one cancer sample each. To efficiently investigate underlying transcript structures, we developed an approach using rapid amplification of cDNA ends followed by high throughput sequencing (RACE-seq). RACE products from the targeted genes in 23 CRC samples were pooled together and sequenced. We identified VWA2-TCF7L2, DHX35-BPIFA2 and CASZ1-MASP2 as private fusion events, and novel transcript structures for 17 of the 23 other candidate genes. The high-throughput approach facilitated identification of CRC specific RNA variants. These include a recurrent read-through fusion transcript between KLK8 and KLK7, and a splice variant of S100A2. Both of these were overrepresented in CRC tissue and cell lines from external RNA-seq datasets.

• RACE-seq
• colorectal cancer
• fusion genes
• splicing
• transcript variants

The present study aimed to identify specific microRNAs (miRs) and their predicted target genes to clarify the molecular mechanisms of colorectal cancer (CRC). An miR expression profile (array ID, GSE39833), which consisted of 88 CRC samples with various tumor-necrosis-metastasis stages and 11 healthy controls, was downloaded from the Gene Expression Omnibus database. Subsequently, the differentially expressed miRs and their target genes were screened. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways of target genes were analyzed using the Database for Annotation Visualization and Integrated Discovery. A protein-protein interaction (PPI) network of the target genes was constructed using the Search Tool for the Retrieval of Interacting Genes database. The present study identified a total of 18 differentially expressed miRs (upregulated, 8; downregulated, 10) in the sera of the CRC patients compared with the healthy controls. Of these, 3 upregulated (let-7b, miR-1290 and miR-126) and 2 downregulated (miR-16 and miR-760) differentially expressed miRs and their target genes, including cyclin D1 (CCND1), v-myc avian myelocytomatosis viral oncogene homolog (MYC), phosphoinositide-3-kinase, regulatory subunit 2 (beta) (PIK3R2) and SMAD family member 3 (SMAD3), were significantly enriched in the CRC developmental pathway. All these target genes had higher node degrees in the PPI network. In conclusion, let-7b, miR-1290, miR-126, miR-16 and miR-760 and their target genes, CCND1, MYC, PIK3R2 and SMAD3, may be important in the molecular mechanisms for the progression of CRC.

• colorectal cancer
• microRNAs
• pathway analysis
• protein-protein interaction network analysis
• target genes

Outlier genes with marked overexpression in subsets of cancers like ERBB2 have potential for the identification of gene classifiers and therapeutic targets for the appropriate subpopulation. In this study, using the cancer outlier profile analysis strategy, we identified WNT1-inducible-signaling pathway protein 3 (WISP3) as an outlier gene that is highly expressed in a subset of colorectal cancers (CRCs) from The Cancer Genome Atlas dataset. A meta-cancer outlier profile analysis and immunohistochemistry experiment to validate the outlier expression model of WISP3 in CRC was then performed. Our immunohistochemical results indicated that WISP3 was more frequently seen in the small tumors, and there was a significant association between its overexpression with a good prognosis. Furthermore, in the multivariable model, WISP3 outlier expression retained significance for overall survival. In summary, in this study, we identified an outlier gene WISP3 overexpressed in a subset of CRC having less aggressive characteristics and a better prognosis. We suggest WISP3 may provide more accurate and precise information regarding CRC population classification.

• WISP3
• microarray
• outlier
• prognosis
• subtype

AIM: To screening key genes related to hepatocellular carcinoma (HCC) metastasis by high-throughput transcriptomics sequencing and serum proteomics.

METHODS: Differentially expressed genes between liver cancer cells Smmc-7721 and normal liver cells L-02 were analyzed by Ion Proton™ high-throughput sequencing. Bioinformatics methods were used to perform GO annotation, clustering and enrichment analysis. Ten serum samples from HCC patients and 10 normal serum samples were recruited to detect the differential protein expression by isobaric tags for relative and absolute quantitation (iTRAQ) and matrix-assisted laser desorption/ionization tandem time of flight mass spectrometry (MALDI-TOF/MS). The transcriptomics data and serum proteomics data were analyzed together to screen key genes related to HCC metastasis. Then, a screened key gene was verified by immunohistochemistry in 76 HCC and adjacent tissues.

RESULTS: A total of 618 differentially expressed genes (DEGs) in liver cancer cells were identified by transcriptome sequencing, and the gene functions were enriched in 14 terms, including metastasis process, transcription and REDOX process, among which metastasis process owned the most DEGs [15.05% (93/618)]. The proteomics data showed that a total of 69 differentially expressed proteins in HCC were detected, including 33 up-regulated and 36 down-regulated ones. Combination analysis found three common factors in transcriptomics and proteomics, among which heat shock protein 90 AA1 (HSP90AA1) was up-regulated in HCC and presented the most significant ratio. According to the immunohistochemical results, the strongly positive rates of HSP90α in HCC with portal vein metastasis and without were 66.7% (16/24) and 25% (13/52), respectively (P < 0.005). HSP90α was overexpressed in HCC with portal vein metastasis.

CONCLUSION: Transcriptomics and proteomics analysis revealed that HSP90AA1 might be a key gene related to HCC metastasis.

• Hepatocellular carcinoma
• Serum Proteomics
• Transcriptome sequencing
• HSP90AA1
• Metastasis