DriverDBv3: a multi-omics database for cancer driver gene research.

An integrative multi-omics database is needed urgently, because focusing only on analysis of one-dimensional data falls far short of providing an understanding of cancer. Previously, we presented DriverDB, a cancer driver gene database that applies published bioinformatics algorithms to identify driver genes/mutations. The updated DriverDBv3 database (http://ngs.ym.edu.tw/driverdb) is designed to interpret cancer omics' sophisticated information with concise data visualization. To offer diverse insights into molecular dysregulation/dysfunction events, we incorporated computational tools to define CNV and methylation drivers. Further, four new features, CNV, Methylation, Survival, and miRNA, allow users to explore the relations from two perspectives in the 'Cancer' and 'Gene' sections. The 'Survival' panel offers not only significant survival genes, but gene pairs synergistic effects determine. A fresh function, 'Survival Analysis' in 'Customized-analysis,' allows users to investigate the co-occurring events in user-defined gene(s) by mutation status or by expression in a specific patient group. Moreover, we redesigned the web interface and provided interactive figures to interpret cancer omics' sophisticated information, and also constructed a Summary panel in the 'Cancer' and 'Gene' sections to visualize the features on multi-omics levels concisely. DriverDBv3 seeks to improve the study of integrative cancer omics data by identifying driver genes and contributes to cancer biology.

DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies.

Although rapid progress has been made in computational approaches for prioritizing cancer driver genes, research is far from achieving the ultimate goal of discovering a complete catalog of genes truly associated with cancer. Driver gene lists predicted from these computational tools lack consistency and are prone to false positives. Here, we developed an approach (DriverML) integrating Rao's score test and supervised machine learning to identify cancer driver genes. The weight parameters in the score statistics quantified the functional impacts of mutations on the protein. To obtain optimized weight parameters, the score statistics of prior driver genes were maximized on pan-cancer training data. We conducted rigorous and unbiased benchmark analysis and comparisons of DriverML with 20 other existing tools in 31 independent datasets from The Cancer Genome Atlas (TCGA). Our comprehensive evaluations demonstrated that DriverML was robust and powerful among various datasets and outperformed the other tools with a better balance of precision and sensitivity. In vitro cell-based assays further proved the validity of the DriverML prediction of novel driver genes. In summary, DriverML uses an innovative, machine learning-based approach to prioritize cancer driver genes and provides dramatic improvements over currently existing methods. Its source code is available at https://github.com/HelloYiHan/DriverML.

Long noncoding RNA HOTAIR promotes invasion of breast cancer cells through chondroitin sulfotransferase CHST15.

The long noncoding RNA HOTAIR plays significant roles in promoting cancer metastasis. However, how it conveys an invasive advantage in cancer cells is not clear. Here we identify the chondroitin sulfotransferase CHST15 (GalNAc4S-6ST) as a novel HOX transcript antisense intergenic RNA (HOTAIR) target gene using RNA profiling and show that CHST15 is required for HOTAIR-mediated invasiveness in breast cancer cells. CHST15 catalyzes sulfation of the C6 hydroxyl group of the N-acetyl galactosamine 4-sulfate moiety in chondroitin sulfate to form the 4,6-disulfated chondroitin sulfate variant known as the CS-E isoform. We show that HOTAIR is necessary and sufficient for CHST15 transcript expression. Inhibition of CHST15 by RNA interference abolished cell invasion promoted by HOTAIR but not on HOTAIR-mediated migratory activity. Conversely, reconstitution of CHST15 expression rescued the invasive activity of HOTAIR-depleted cells. In corroboration with this mechanism, blocking cell surface chondroitin sulfate using a pan-CS antibody or an antibody specifically recognizes the CS-E isoform significantly suppressed HOTAIR-induced invasion. Inhibition of CHST15 compromised tumorigenesis and metastasis in orthotopic breast cancer xenograft models. Furthermore, the expression of HOTAIR closely correlated with the level of CHST15 protein in primary as well as metastatic tumor lesions. Our results demonstrate a novel mechanism underlying the function of HOTAIR in tumor progression through programming the context of cell surface glycosaminoglycans. Our results further establish that the invasive and migratory activities downstream of HOTAIR are distinctly regulated, whereby CHST15 preferentially controls the arm of invasiveness. Thus, the HOTAIR-CHST15 axis may provide a new avenue toward novel therapeutic strategies and prognosis biomarkers for advanced breast cancer.

YM500v3: a database for small RNA sequencing in human cancer research.

We previously presented the YM500 database, which contains >8000 small RNA sequencing (smRNA-seq) data sets and integrated analysis results for various cancer miRNome studies. In the updated YM500v3 database (http://ngs.ym.edu.tw/ym500/) presented herein, we not only focus on miRNAs but also on other functional small non-coding RNAs (sncRNAs), such as PIWI-interacting RNAs (piRNAs), tRNA-derived fragments (tRFs), small nuclear RNAs (snRNAs) and small nucleolar RNAs (snoRNAs). There is growing knowledge of the role of sncRNAs in gene regulation and tumorigenesis. We have also incorporated >10 000 cancer-related RNA-seq and >3000 more smRNA-seq data sets into the YM500v3 database. Furthermore, there are two main new sections, 'Survival' and 'Cancer', in this updated version. The 'Survival' section provides the survival analysis results in all cancer types or in a user-defined group of samples for a specific sncRNA. The 'Cancer' section provides the results of differential expression analyses, miRNA-gene interactions and cancer miRNA-related pathways. In the 'Expression' section, sncRNA expression profiles across cancer and sample types are newly provided. Cancer-related sncRNAs hold potential for both biotech applications and basic research.

SPECT/CT imaging for tracking subendothelial retention of electronegative low-density lipoprotein in vivo.

The fifth subfraction of low-density lipoprotein (L5 LDL) can be separated from human LDL using fast-protein liquid chromatography with an anion exchange column. L5 LDL induces vascular endothelial injury both in vitro and in vivo through the lectin-like oxidized LDL receptor-1 (LOX-1). However, no in vivo evidence shows the tendency of L5 LDL deposition on vascular endothelium and links to dysfunction. This study aimed to investigate L5 LDL retention in vivo using SPECT/CT imaging, with Iodine-131 (131I)-labeled and injected into six-month-old apolipoprotein E knockout (apoE-/-) mice through tail veins. Besides, we examined the biodistribution of L5 LDL in tissues and analyzed the intracellular trafficking in human aortic endothelial cells (HAoECs) by confocal microscopy. The impacts of L5 LDL on HAoECs were analyzed using electron microscopy for mitochondrial morphology and western blotting for signaling. Results showed 131I-labeled-L5 was preferentially deposited in the heart and vessels compared to L1 LDL. Furthermore, L5 LDL was co-localized with the mitochondria and associated with mitofusin (MFN1/2) and optic atrophy protein 1 (OPA1) downregulation, leading to mitochondrial fission. In summary, L5 LDL exhibits a propensity for subendothelial retention, thereby promoting endothelial dysfunction and the formation of atherosclerotic lesions.

Inconsistencies in the Methodological Framework Throughout Published Studies in High-Impact Orthopaedic Journals: A Systematic Review.

BACKGROUND: Both the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) and Consolidated Standards of Reporting Trials (CONSORT) guidelines recommend that clinical trials follow a study framework that aligns with their objective to test the relative efficacy or safety (equality) or effectiveness (superiority, noninferiority, or equivalence) between interventions. We conducted a systematic review to assess the proportion of studies that demonstrated inconsistency between the framing of their research question, sample size calculation, and conclusion and those that should have framed their research question differently based on the compared interventions. METHODS: We included studies from 5 high-impact-factor orthopaedic journals published in 2017 and 2019 that compared at least 2 interventions using patient-reported outcome measures. RESULTS: We included 228 studies. The sample size calculation was reported in 60.5% (n = 138) of studies. Of these, 52.2% (n = 72) were inconsistent between the framing of their research question, sample size calculation, and conclusion. The majority (n = 137) of sample size calculations were for equality, but 43.8% of these studies concluded superiority, noninferiority, or equivalence. Studies that framed their research question as equality (n = 186) should have been framed as superiority (n = 129), equivalence (n = 52), or noninferiority (n = 3). Only 2 studies correctly framed their research question as equality. CONCLUSIONS: Studies published in high-impact journals were inconsistent between the framing of their research question, sample size calculation, and conclusion. Authors may be misinterpreting research findings and making clinical recommendations solely based on p values. Researchers are encouraged to state and justify their methodological framework and choice of margin(s) in a publicly published protocol as they have implications for sample size and the applicability of conclusions. CLINICAL RELEVANCE: The results of clinical research must be interpreted using confidence intervals, with careful consideration as to how the confidence intervals relate to clinically meaningful differences in outcomes between treatments. The more typical practice of relying on p values leaves the clinician at high risk of erroneous interpretation, recommendation, and/or action.

miR-4759 suppresses breast cancer through immune checkpoint blockade.

Programmed cell death protein 1 (PD-1)/ programmed cell death protein ligand 1 (PD-L1) is the key immune checkpoint governing evasion of advanced cancer from immune surveillance. Immuno-oncology (IO) therapy targeting PD-1/PD-L1 with traditional antibodies is a promising approach to multiple cancer types but to which the response rate remains moderate in breast cancer, calling for the need of exploring alternative IO targeting approaches. A miRNA-gene network was integrated by a bioinformatics approach and corroborated with The Cancer Genome Atlas (TCGA) to screen miRNAs regulating immune checkpoint genes and associated with patient survival. Here we show the identification of a novel microRNA miR-4759 which repressed RNA expression of the PD-L1 gene. miR-4759 targeted the PD-L1 gene through two binding motifs in the 3' untranslated region (3'-UTR) of PD-L1. Reconstitution of miR-4759 inhibited PD-L1 expression and sensitized breast cancer cells to killing by immune cells. Treatment with miR-4759 suppressed tumor growth of orthotopic xenografts and promoted tumor infiltration of CD8+ T lymphocytes in immunocompetent mice. In contrast, miR-4759 had no effect to tumor growth in immunodeficient mice. In patients with breast cancer, expression of miR-4759 was preferentially downregulated in tumors compared to normal tissues and was associated with poor overall survival. Together, our results demonstrated miR-4759 as a novel non-coding RNA which promotes anti-tumor immunity of breast cancer.

Using bioinformatics approaches to identify survival-related oncomiRs as potential targets of miRNA-based treatments for lung adenocarcinoma.

Lung cancer is a major cause of cancer-associated deaths worldwide, and lung adenocarcinoma (LUAD) is the most common lung cancer subtype. Micro RNAs (miRNAs) regulate the pattern of gene expression in multiple cancer types and have been explored as potential drug development targets. To develop an oncomiR-based panel, we identified miRNA candidates that show differential expression patterns and are relevant to the worse 5-year overall survival outcomes in LUAD patient samples. We further evaluated various combinations of miRNA candidates for association with 5-year overall survival and identified a four-miRNA panel: miR-9-5p, miR-1246, miR-31-3p, and miR-3136-5p. The combination of these four miRNAs outperformed any single miRNA for predicting 5-year overall survival (hazard ratio [HR]: 3.47, log-rank p-value = 0.000271). Experiments were performed on lung cancer cell lines and animal models to validate the effects of these miRNAs. The results showed that singly transfected antagomiRs largely inhibited cell growth, migration, and invasion, and the combination of all four antagomiRs considerably reduced cell numbers, which is twice as effective as any single miRNA-targeted transfected. The in vivo studies revealed that antagomiR-mediated knockdown of all four miRNAs significantly reduced tumor growth and metastatic ability of lung cancer cells compared to the negative control group. The success of these in vivo and in vitro experiments suggested that these four identified oncomiRs may have therapeutic potential.

Interpreting Patient-Reported Outcome Measures in Orthopaedic Surgery: A Systematic Review.

BACKGROUND: The Consolidated Standards of Reporting Trials (CONSORT) Statement recommends that studies report results beyond p values and include treatment effect(s) and measures of precision (e.g., confidence intervals [CIs]) to facilitate the interpretation of results. The objective of this systematic review was to assess the reporting and interpretation of patient-reported outcome measure (PROM) results in clinical studies from high-impact orthopaedic journals, to determine the proportion of studies that (1) only reported a p value; (2) reported a treatment effect, CI, or minimal clinically important difference (MCID); and (3) offered an interpretation of the results beyond interpreting a p value. METHODS: We included studies from 5 high-impact-factor orthopaedic journals published in 2017 and 2019 that compared at least 2 intervention groups using PROMs. RESULTS: A total of 228 studies were analyzed, including 126 randomized controlled trials, 35 prospective cohort studies, 61 retrospective cohort studies, 1 mixed cohort study, and 5 case-control studies. Seventy-six percent of studies (174) reported p values exclusively to express and interpret between-group differences, and only 22.4% (51) reported a treatment effect (mean difference, mean change, or odds ratio) with 95% CI. Of the 54 studies reporting a treatment effect, 31 interpreted the results using an important threshold (MCID, margin, or Cohen d), but only 3 interpreted the CIs. We found an absolute improvement of 35.5% (95% CI, 20.8% to 48.4%) in the reporting of the MCID between 2017 and 2019. CONCLUSIONS: The majority of interventional studies reporting PROMs do not report CIs around between-group differences in outcome and do not define a clinically meaningful difference. A p value cannot effectively communicate the readiness for implementation in a clinical setting and may be misleading. Thus, reporting requirements should be expanded to require authors to define and provide a rationale for between-group clinically important difference thresholds, and study findings should be communicated by comparing CIs with these thresholds.

Systematic identification of clinically relevant miRNAs for potential miRNA-based therapy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD), the most common histological type of non-small cell lung cancer, is one of the most malignant and deadly diseases. Current treatments for advanced LUAD patients are far from ideal and require further improvements. Here, we utilized a systematic integrative analysis of LUAD microRNA sequencing (miRNA-seq) and RNA-seq data from The Cancer Genome Atlas (TCGA) to identify clinically relevant tumor suppressor miRNAs. Three miRNA candidates (miR-195-5p, miR-101-3p, and miR-338-5p) were identified based on their differential expressions, survival significance levels, correlations with targets, and an additive effect on survival among them. We further evaluated mimics of the three miRNAs to determine their therapeutic potential in inhibiting cancer progression. The results showed not only that each of the miRNA mimics alone but also the three miRNA mimics in combination were efficient at inhibiting tumor growth and progression with equal final concentrations, meaning that the three miRNA mimics in combination were more effective than the single miRNA mimics. Moreover, the combined miRNA mimics provided significant therapeutic effects in terms of reduced tumor volume and metastasis nodules in lung tumor animal models. Hence, our findings show the potential of using the three miRNAs in combination to treat LUAD patients with poor survival outcomes.

Identification of Cancer Driver Genes from a Custom Set of Next Generation Sequencing Data.

Next generation sequencing (NGS) has become the norm of cancer genomic researches. Large-scale cancer sequencing projects seek to comprehensively uncover mutated genes that confer a selective advantage for cancer cells. Numerous computational algorithms have been developed to find genes that drive cancer based on their patterns of mutation in a patient cohort. It has been noted that the distinct features of driver gene alterations in different subgroups are based on clinical characteristics. Previously, we have developed a database, DriverDB, to integrate all public cancer sequencing data and to identify cancer driver genes according to bioinformatics tools. In this chapter, we describe the use of the function "Meta-Analysis" in DriverDB that offers a list of clinical characteristics to define samples and provides a high degree of freedom for researchers to utilize the huge amounts of sequencing data. Moreover, researchers can use the "Gene" section to explore a single driver gene in all cancers by different kinds of aspects after identifying the specific driver genes by "Meta-Analysis." DriverDB is available at http://ngs.ym.edu.tw/driverdb/ .

Knockout of toll-like receptor impairs nerve regeneration after a crush injury.

BACKGROUND: Toll-like receptors (TLRs) are involved in the initiation of Schwann cell activation and subsequent recruitment of macrophages for clearance of degenerated myelin and neuronal debris after nerve injury. The present study was designed to investigate the regenerative outcome and expression of myelination-related factors in Tlr-knockout mice following a sciatic nerve crush injury. MATERIALS AND METHODS: A standard sciatic nerve crush injury, induced by applying constant pressure to the nerve with a No. 5 jeweler's forceps for 30 s, was performed in C57BL/6, Tlr2-/- , Tlr3-/- , Tlr4-/- , Tlr5-/- , and Tlr7-/- mice. Quantitative histomorphometric analysis of toluidine blue-stained nerve specimens and walking track analysis were performed to evaluate nerve regeneration outcomes. PCR Arrays were used to detect the expression of neurogenesis-related genes of dorsal root ganglia as well as of myelination-related genes of the distal nerve segments. RESULTS: Worse nerve regeneration after nerve crush injury was found in all Tlr-knockout mice than in C57BL/6 mice. Delayed expression of myelin genes and a different expression pattern of myelination-related neurotrophin genes and transcription factors were found in Tlr-knockout mice in comparison to C57BL/6 mice. In these TLR-mediated pathways, insulin-like growth factor 2 and brain-derived neurotrophic factor, as well as early growth response 2 and N-myc downstream-regulated gene 1, were significantly decreased in the early and late stages, respectively, of nerve regeneration after a crush injury. CONCLUSIONS: Knockout of Tlr genes decreases the expression of myelination-related factors and impairs nerve regeneration after a sciatic nerve crush injury.