DriverDBv4: a multi-omics integration database for cancer driver gene research.

Advancements in high-throughput technology offer researchers an extensive range of multi-omics data that provide deep insights into the complex landscape of cancer biology. However, traditional statistical models and databases are inadequate to interpret these high-dimensional data within a multi-omics framework. To address this limitation, we introduce DriverDBv4, an updated iteration of the DriverDB cancer driver gene database (http://driverdb.bioinfomics.org/). This updated version offers several significant enhancements: (i) an increase in the number of cohorts from 33 to 70, encompassing approximately 24 000 samples; (ii) inclusion of proteomics data, augmenting the existing types of omics data and thus expanding the analytical scope; (iii) implementation of multiple multi-omics algorithms for identification of cancer drivers; (iv) new visualization features designed to succinctly summarize high-context data and redesigned existing sections to accommodate the increased volume of datasets and (v) two new functions in Customized Analysis, specifically designed for multi-omics driver identification and subgroup expression analysis. DriverDBv4 facilitates comprehensive interpretation of multi-omics data across diverse cancer types, thereby enriching the understanding of cancer heterogeneity and aiding in the development of personalized clinical approaches. The database is designed to foster a more nuanced understanding of the multi-faceted nature of cancer.

LipidSig 2.0: integrating lipid characteristic insights into advanced lipidomics data analysis.

In the field of lipidomics, where the complexity of lipid structures and functions presents significant analytical challenges, LipidSig stands out as the first web-based platform providing integrated, comprehensive analysis for efficient data mining of lipidomic datasets. The upgraded LipidSig 2.0 (https://lipidsig.bioinfomics.org/) simplifies the process and empowers researchers to decipher the complex nature of lipids and link lipidomic data to specific characteristics and biological contexts. This tool markedly enhances the efficiency and depth of lipidomic research by autonomously identifying lipid species and assigning 29 comprehensive characteristics upon data entry. LipidSig 2.0 accommodates 24 data processing methods, streamlining diverse lipidomic datasets. The tool's expertise in automating intricate analytical processes, including data preprocessing, lipid ID annotation, differential expression, enrichment analysis, and network analysis, allows researchers to profoundly investigate lipid properties and their biological implications. Additional innovative features, such as the 'Network' function, offer a system biology perspective on lipid interactions, and the 'Multiple Group' analysis aids in examining complex experimental designs. With its comprehensive suite of features for analyzing and visualizing lipid properties, LipidSig 2.0 positions itself as an indispensable tool for advanced lipidomics research, paving the way for new insights into the role of lipids in cellular processes and disease development.

Diarylheptanoid 35d overcomes EGFR TKI resistance by inducing hsp70-mediated lysosomal degradation of EGFR in EGFR-mutant lung adenocarcinoma.

Epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma (LUAD) patients often respond to EGFR tyrosine kinase inhibitors (TKIs) initially but eventually develop resistance to TKIs. The switch of EGFR downstream signaling from TKI-sensitive to TKI-insensitive is a critical mechanism-driving resistance to TKIs. Identification of potential therapies to target EGFR effectively is a potential strategy to treat TKI-resistant LUADs. In this study, we developed a small molecule diarylheptanoid 35d, a curcumin derivative, that effectively suppressed EGFR protein expression, killed multiple TKI-resistant LUAD cells in vitro, and suppressed tumor growth of EGFR-mutant LUAD xenografts with variant TKI-resistant mechanisms including EGFR C797S mutations in vivo. Mechanically, 35d triggers heat shock protein 70-mediated lysosomal pathway through transcriptional activation of several components in the pathway, such as HSPA1B, to induce EGFR protein degradation. Interestingly, higher HSPA1B expression in LUAD tumors associated with longer survival of EGFR-mutant, TKI-treated patients, suggesting the role of HSPA1B on retarding TKI resistance and providing a rationale for combining 35d with EGFR TKIs. Our data showed that combination of 35d significantly inhibits tumor reprogression on osimertinib and prolongs mice survival. Overall, our results suggest 35d as a promising lead compound to suppress EGFR expression and provide important insights into the development of combination therapies for TKI-resistant LUADs, which could have translational potential for the treatment of this deadly disease.

Interplay between lncRNA RP11-367G18.1 variant 2 and YY1 plays a vital role in hypoxia-mediated gene expression and tumorigenesis.

BACKGROUND: The hypoxia-responsive long non-coding RNA, RP11-367G18.1, has recently been reported to induce histone 4 lysine 16 acetylation (H4K16Ac) through its variant 2; however, the underlying molecular mechanism remains poorly understood. METHODS: RNA pull-down assay and liquid chromatography-tandem mass spectrometry were performed to identify RP11-367G18.1 variant 2-binding partner. The molecular events were examined utilizing western blot analysis, real-time PCR, luciferase reporter assay, chromatin immunoprecipitation, and chromatin isolation by RNA purification assays. The migration, invasion, soft agar colony formation, and in vivo xenograft experiments were conducted to evaluate the impact of RP11-367G18.1 variant 2-YY1 complex on tumor progression. RESULTS: In this study, RNA sequencing data revealed that hypoxia and RP11-367G18.1 variant 2 co-regulated genes were enriched in tumor-related pathways. YY1 was identified as an RP11-367G18.1 variant 2-binding partner that activates the H4K16Ac mark. YY1 was upregulated under hypoxic conditions and served as a target gene for hypoxia-inducible factor-1α. RP11-367G18.1 variant 2 colocalized with YY1 and H4K16Ac in the nucleus under hypoxic conditions. Head and neck cancer tissues had higher levels of RP11-367G18.1 and YY1 which were associated with poor patient outcomes. RP11-367G18.1 variant 2-YY1 complex contributes to hypoxia-induced epithelial-mesenchymal transition, cell migration, invasion, and tumorigenicity. YY1 regulated hypoxia-induced genes dependent on RP11-367G18.1 variant 2. CONCLUSIONS: RP11-367G18.1 variant 2-YY1 complex mediates the tumor-promoting effects of hypoxia, suggesting that this complex can be targeted as a novel therapeutic strategy for cancer treatment.

Lipid metabolomic signature might predict subclinical atherosclerosis in patients with active rheumatoid arthritis.

OBJECTIVES: Although 1H-nuclear magnetic resonance (NMR)-based lipid/metabolomics has been used to detect atherosclerosis, data regarding lipid/metabolomic signature in rheumatoid arthritis (RA)-related atherosclerosis are scarce. We aimed to identify the distinct lipid/metabolomic profiling and develop a prediction score model for RA patients with subclinical atherosclerosis (SA). METHODS: Serum levels of lipid metabolites were determined using 1H-NMR-based lipid/metabolomics in 65 RA patients and 12 healthy controls (HCs). The occurrence of SA was defined as the presence of carotid plaques revealed in ultrasound images. RESULTS: Compared with HC, RA patients had significantly higher levels of phenylalanine and glycoprotein acetyls (GlycA) and lower levels of leucine and isoleucine. RA patients with SA had significantly higher levels of phenylalanine, creatinine, and glycolysis_total and lower levels of total lipid in HDL(HDL_L) than RA patients without SA. The Lasso logistic regression analysis revealed that age, creatinine, HDL_L, and glycolysis_total were significant predictors for the presence of SA. The prediction scoring algorithm was built as ( -0.657 + 0.011*Age + 0.004*Creatinine -0.120*HDL_L + 0.056*glycolysis-related measures), with AUC 0.90, sensitivity 83.3%, and specificity 87.2%. Serum phenylalanine levels were significantly decreased, and the levels of HDL_L and HDL_Particle were significantly increased in 20 RA patients, paralleling the decrease in disease activity score for 28-joints. CONCLUSIONS: With 1H-NMR-based lipid/metabolomics, distinct profiling of lipid metabolites was identified between RA patients and HC or between RA patients with and without SA. We further developed a scoring model based on lipid/metabolomics profiling for predicting RA-associated SA.

Luminescent Pt(II) Complexes Containing (1-Aza-15-crown-5)dithiocarbamate and (1-Aza-18-crown-6)dithiocarbamate: Mechanochromic and Solvent-Induced Luminescence.

The strong tendency to stack in the solid state and rich luminescence for the Pt(II) complexes makes them potential candidates as new mechanochromic materials and sensing applications. Six mononuclear complexes [Pt(ppy)(O4NCS2)] (1), [Pt(bpy)(O4NCS2)]ClO4 (2), [Pt(ppy)(O5NCS2)] (3), [Pt(phen)(O4NCS2)]ClO4·CH3OH (5a), [Pt(phen)(O4NCS2)]ClO4 (5b), and [Pt(phen)(O5NCS2)]ClO4 (6a), one dinuclear complex [Pt2(phen)2(NaO5NCS2)2(ClO4)3]ClO4 (6b), and one one-dimensional (1-D) coordination polymer {[Pt2(bpy)2(NaO5NCS2)2(ClO4)2](ClO4)2}n (4) were synthesized by reacting [Pt(ppy)Cl]2, Pt(bpy)Cl2, and Pt(phen)Cl2 (ppy = 2-phenylpyridine, bpy = 2,2'-bipyridine, and phen = 1,10-phenanthroline) with (1-aza-15-crown-5)dithiocarbamate (O4NCS2) or (1-aza-18-crown-6)dithiocarbamate (O5NCS2), respectively, which have been isolated and structurally characterized by X-ray diffraction. Neutral complexes 1 and 3 contain no intermolecular Pt(II)···Pt(II) contact, whereas cationic complexes 2, 5a, 5b, and 6a with ClO4- as counteranions show alternative intermolecular Pt(II)···Pt(II) contacts of 3.535/4.091, 3.480/5.001, 3.527/4.571, and 3.446/4.987 Å in the solid state, respectively. Interestingly, complex 4 forms a 1-D coordination polymer through coordination between the encapsulated Na+ ions inside the azacrown ether rings of O5NCS2 and ClO4- anions with respective intra- and intermolecular Pt(II)···Pt(II) contacts of 3.402 and 3.847 Å in crystal lattices, whereas a dinuclear complex 6b was surprisingly formed and also connected by the encapsulated Na+ ions and ClO4- anions with alternative intra- and intermolecular Pt(II)···Pt(II) contacts of 3.650 and 3.677/4.4.372 Å, respectively. Upon excitation, complexes 1 and 3 showed similar vibronic luminescence at 507, 534, and 502, 532 nm, respectively, and the other complexes 2 and 4-6 showed broad luminescence with maxima at 537-567 nm. The B3LYP/LanL2DZ calculation was carried out and used to clarify their excited-state properties. In addition, the powder samples for complexes 1-4 almost showed no energy shift for the luminescence and significantly those of complexes 5-6 exhibited the mechanochromic luminescence upon grinding. It is noted that complexes 5a and 6a only showed minor red shifts (i.e., from 544 to 556 nm for complex 5a and from 551 to 565 nm for complex 6a), whereas complex 6b exhibited a remarkable red shift from 558 to 603 nm upon grinding. Besides, their luminescence reversibility was also examined toward various solvents.

LipidSig: a web-based tool for lipidomic data analysis.

With the continuing rise of lipidomic studies, there is an urgent need for a useful and comprehensive tool to facilitate lipidomic data analysis. The most important features making lipids different from general metabolites are their various characteristics, including their lipid classes, double bonds, chain lengths, etc. Based on these characteristics, lipid species can be classified into different categories and, more interestingly, exert specific biological functions in a group. In an effort to simplify lipidomic analysis workflows and enhance the exploration of lipid characteristics, we have developed a highly flexible and user-friendly web server called LipidSig. It consists of five sections, namely, Profiling, Differential Expression, Correlation, Network and Machine Learning, and evaluates lipid effects on cellular or disease phenotypes. One of the specialties of LipidSig is the conversion between lipid species and characteristics according to a user-defined characteristics table. This function allows for efficient data mining for both individual lipids and subgroups of characteristics. To expand the server's practical utility, we also provide analyses focusing on fatty acid properties and multiple characteristics. In summary, LipidSig is expected to help users identify significant lipid-related features and to advance the field of lipid biology. The LipidSig webserver is freely available at http://chenglab.cmu.edu.tw/lipidsig.

Your height affects your health: genetic determinants and health-related outcomes in Taiwan.

BACKGROUND: Height is an important anthropometric measurement and is associated with many health-related outcomes. Genome-wide association studies (GWASs) have identified hundreds of genetic loci associated with height, mainly in individuals of European ancestry. METHODS: We performed genome-wide association analyses and replicated previously reported GWAS-determined single nucleotide polymorphisms (SNPs) in the Taiwanese Han population (Taiwan Biobank; n = 67,452). A genetic instrument composed of 251 SNPs was selected from our GWAS, based on height and replication results as the best-fit polygenic risk score (PRS), in accordance with the clumping and p-value threshold method. We also examined the association between genetically determined height (PRS251) and measured height (phenotype). We performed observational (phenotype) and genetic PRS251 association analyses of height and health-related outcomes. RESULTS: GWAS identified 6843 SNPs in 89 genomic regions with genome-wide significance, including 18 novel loci. These were the most strongly associated genetic loci (EFEMP1, DIS3L2, ZBTB38, LCORL, HMGA1, CS, and GDF5) previously reported to play a role in height. There was a positive association between PRS251 and measured height (p < 0.001). Of the 14 traits and 49 diseases analyzed, we observed significant associations of measured and genetically determined height with only eight traits (p < 0.05/[14 + 49]). Height was positively associated with body weight, waist circumference, and hip circumference but negatively associated with body mass index, waist-hip ratio, body fat, total cholesterol, and low-density lipoprotein cholesterol (p < 0.05/[14 + 49]). CONCLUSIONS: This study contributes to the understanding of the genetic features of height and health-related outcomes in individuals of Han Chinese ancestry in Taiwan.

TNFRSF13B is a potential contributor to prostate cancer.

BACKGROUND: Immunodeficiencies are genetic diseases known to predispose an individual to cancer owing to defective immunity towards malignant cells. However, the link between immunodeficiency and prostate cancer progression remains unclear. Therefore, the aim of this study was to evaluate the effects of common genetic variants among eight immunodeficiency pathway-related genes on disease recurrence in prostate cancer patients treated with radical prostatectomy. METHODS: Genetic and bioinformatic analyses on 19 haplotype-tagging single-nucleotide polymorphisms in eight immunodeficiency pathway-related genes were conducted in 458 patients with prostate cancer after receiving radical prostatectomy. Furthermore, the TNFRSF13B was knocked down in 22Rv1 and PC-3 human prostate cancer cell lines via transfecting short hairpin RNAs and cell proliferation and colony formation assays were performed. The molecular mechanisms underlying the effects of TNFRSF13B were further explored by microarray gene expression profiling. RESULTS: TNFRSF13B rs4792800 was found to be significantly associated with biochemical recurrence even after adjustment for clinical predictors and false discovery rate correction (adjusted hazard ratio 1.78, 95% confidence interval 1.16-2.71, p = 0.008), and the G allele was associated with higher TNFRSF13B expression (p = 0.038). Increased TNFRSF13B expression suggested poor prognosis in four independent prostate cancer datasets. Furthermore, silencing TNFRSF13B expression resulted in decreased colony formation of 22Rv1 and PC-3 cells through modulating the cell cycle and p53 signalling pathways. CONCLUSIONS: The present study suggests the potential role of immunodeficiency pathway-related genes, primarily TNFRSF13B, in prostate cancer progression.

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.

Evaluation Challenges for the Application of Extended Reality Devices in Medicine.

Augmented and virtual reality devices are being actively investigated and implemented for a wide range of medical uses. However, significant gaps in the evaluation of these medical devices and applications hinder their regulatory evaluation. Addressing these gaps is critical to demonstrating the devices' safety and effectiveness. We outline the key technical and clinical evaluation challenges discussed during the US Food and Drug Administration's public workshop, "Medical Extended Reality: Toward Best Evaluation Practices for Virtual and Augmented Reality in Medicine" and future directions for evaluation method development. Evaluation challenges were categorized into several key technical and clinical areas. Finally, we highlight current efforts in the standards communities and illustrate connections between the evaluation challenges and the intended uses of the medical extended reality (MXR) devices. Participants concluded that additional research is needed to assess the safety and effectiveness of MXR devices across the use cases.

Picky comprehensively detects high-resolution structural variants in nanopore long reads.

Acquired genomic structural variants (SVs) are major hallmarks of cancer genomes, but they are challenging to reconstruct from short-read sequencing data. Here we exploited the long reads of the nanopore platform using our customized pipeline, Picky ( https://github.com/TheJacksonLaboratory/Picky ), to reveal SVs of diverse architecture in a breast cancer model. We identified the full spectrum of SVs with superior specificity and sensitivity relative to short-read analyses, and uncovered repetitive DNA as the major source of variation. Examination of genome-wide breakpoints at nucleotide resolution uncovered micro-insertions as the common structural features associated with SVs. Breakpoint density across the genome is associated with the propensity for interchromosomal connectivity and was found to be enriched in promoters and transcribed regions of the genome. Furthermore, we observed an over-representation of reciprocal translocations from chromosomal double-crossovers through phased SVs. We demonstrate that Picky analysis is an effective tool for comprehensive detection of SVs in cancer genomes from long-read data.

Exosome-derived differentiation antagonizing non-protein coding RNA with risk of hepatitis C virus-related hepatocellular carcinoma recurrence.

BACKGROUND & AIMS: Differentiation antagonizing non-protein coding RNA is associated with various types of neoplasms. Hepatitis C virus-related hepatocellular carcinoma has a high risk of recurrence. Here we determined the role of differentiation antagonizing non-protein coding RNA in hepatitis C virus-related hepatocarcinogenesis and identified potential therapeutic targets and non-invasive prognostic markers for long-term outcome of hepatitis C virus-related hepatocellular carcinoma after surgical resection. METHODS: Differentiation antagonizing non-protein coding RNAs relevant to hepatitis C virus-related hepatocellular carcinoma were identified through comparative RNA-sequencing of tumour and adjacent non-tumour (ANT) tissues in a screening set, and were validated using real-time polymerase chain reaction. Target long non-coding RNAs (lncRNAs) in tissues and serum exosomes were used to predict the recurrence of hepatitis C virus-related hepatocellular carcinoma after curative surgical resection in a large application cohort from 2005 to 2012. RESULTS: We confirmed that differentiation antagonizing non-protein coding RNA was upregulated following hepatitis C virus infection and identified as the lncRNA most relevant to hepatitis C virus-related hepatocellular carcinoma in tumour tissues as compared to that in ANT tissues. In 183 hepatitis C virus-related hepatocellular carcinoma patients followed for 10 years after curative HCC resection, the expression level of circulating exosomal differentiation antagonizing non-protein coding RNA was positively associated with HCC recurrence and was the most predictive factor associated with HCC recurrence and mortality (hazard ratio/95% confidence intervals: 7.0/4.3-11.6 and 2.7/1.5-5.1 respectively). CONCLUSIONS: Differentiation antagonizing non-protein coding RNA is highly relevant to disease progression of hepatitis C virus-related hepatocellular carcinoma. Our finding indicated that circulating exosomal differentiation antagonizing non-protein coding RNA might serve as a non-invasive prognostic biomarker for hepatitis C virus-related hepatocellular carcinoma.

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.

Enzyme-Digested Peptides Derived from Lates calcarifer Enhance Wound Healing after Surgical Incision in a Murine Model.

Surgical wounds are common injuries of skin and tissues and usually become a clinical problem. Until now, various synthetic and natural peptides have been widely explored as potential drug candidates for wound healing. Inhibition of the TNF-α signaling pathway and promotion of angiogenesis are suggested to be involved in their effects. Angiogenesis at the wound site is one of the essential requisites for rapid healing. In the present study, a novel peptide extract derived from the natural source Lates calcarifer, commonly known as sea bass or barramundi, was evaluated for its wound healing property. The specific acidic and enzymatic approaches were employed for producing sea bass extract containing small size peptides (molecular weight ranging from 1 kD to 5 kD). The cytotoxicity of the extract was examined in HaCaT and NIH3T3. After this, the effects of enzyme digested peptide extracts of sea bass on wound healing in mice were investigated. The peptide extracts (660 and 1320 mg/kg/day) and control protein (1320 mg/kg/day) was orally given to the wounded mice, respectively, for 12 days. The surgical method was improved by implanting a silicone ring at the wound site. The ring avoided the contracting effect in murine wounds, making it more closely related to a clinical condition. The results showed promising improvement at the wound site in mice. Sea bass peptide extracts accelerated the wound healing process and enhanced the microvessel formation at the wound site. The remarkable effects of this novel sea bass peptide extract in healing traumatic injuries revealed a new option for developing wound management.

Color Rendering in Medical Extended-Reality Applications.

Cross-platform development of medical applications in extended-reality (XR) head-mounted displays (HMDs) often relies on game engines with rendering capabilities currently not standardized in the context of medical visualizations. Many aspects of the visualization pipeline including the characterization of color have yet to be consistently defined across rendering models and platforms. We examined the transfer of color properties from digital objects, through the rendering and image processing steps, to the RGB values sent to the display device. Five rendering pipeline configurations within the Unity engine were evaluated using 24 digital color patches. In the second experiment, the same configurations were evaluated with a tissue slide sample image. Measurements of the change in color associated with each configuration were characterized using the CIE 1976 color difference ([Formula: see text]). We found that the distribution of [Formula: see text] for the first experiment ranges from zero, as in the case using an Unlit Shader, to 25.97, as in the case using default configurations. The default Unity configuration consistently returned the highest [Formula: see text] across all 24 colors and also the largest range of color differences. In the second experiment, [Formula: see text]E ranged from 7.49 to 34.18. The Unlit configuration resulted in the highest [Formula: see text] in three of four selected pixels in the tissue sample image. Changes in color image properties associated with texture import settings were then evaluated in a third experiment using the TG18-QC test pattern. Differences in pixel values were found in all nine of the investigated texture import settings. The findings provide an initial characterization of color transfer and a basis for future work on standardization, consistency, and optimization of color in medical XR applications.

The Potential Role of Electronegative High-Density Lipoprotein H5 Subfraction in RA-Related Atherosclerosis.

Although the heterogeneity of high-density lipoprotein-cholesterol (HDL-c) composition is associated with atherosclerotic cardiovascular risk, the link between electronegative subfractions of HDL-c and atherosclerosis in rheumatoid arthritis (RA) remains unknown. We examined the association of the percentage of the most electronegative subfraction of HDL-c (H5%) and RA-related atherosclerosis. Using anion-exchange purification/fast-protein liquid chromatography, we demonstrated significantly higher H5% in patients (median, 7.2%) than HC (2.8%, p < 0.005). Multivariable regression analysis revealed H5% as a significant predictor for subclinical atherosclerosis. We subsequently explored atherogenic role of H5 using cell-based assay. The results showed significantly higher levels of IL-1ß and IL-8 mRNA in H5-treated (mean ± SD, 4.45 ± 1.22 folds, 6.02 ± 1.43-folds, respectively) than H1-treated monocytes (0.89 ± 0.18-folds, 1.03 ± 0.26-folds, respectively, both p < 0.001). In macrophages, H5 upregulated the mRNA and protein expression of IL-1ß and IL-8 in a dose-dependent manner, and their expression levels were significantly higher than H1-treated macrophages (all p < 0.001). H5 induced more foam cell formation compared with H1-treated macrophages (p < 0.005). In addition, H5 has significantly lower cholesterol efflux capacity than H1 (p < 0.005). The results of nanoLC-MS/MS approach reveal that the best discriminator between high-H5% and normal-H5% is Apo(a), the main constituent of Lp(a). Moreover, Lp(a) level is a significant predictor for high-H5%. These observations suggest that H5 is involved in RA-related atherosclerosis.

Identification of DNA Damage Repair-Associated Prognostic Biomarkers for Prostate Cancer Using Transcriptomic Data Analysis.

In the recent decade, the importance of DNA damage repair (DDR) and its clinical application have been firmly recognized in prostate cancer (PC). For example, olaparib was just approved in May 2020 to treat metastatic castration-resistant PC with homologous recombination repair-mutated genes; however, not all patients can benefit from olaparib, and the treatment response depends on patient-specific mutations. This highlights the need to understand the detailed DDR biology further and develop DDR-based biomarkers. In this study, we establish a four-gene panel of which the expression is significantly associated with overall survival (OS) and progression-free survival (PFS) in PC patients from the TCGA-PRAD database. This panel includes DNTT, EXO1, NEIL3, and EME2 genes. Patients with higher expression of the four identified genes have significantly worse OS and PFS. This significance also exists in a multivariate Cox regression model adjusting for age, PSA, TNM stages, and Gleason scores. Moreover, the expression of the four-gene panel is highly correlated with aggressiveness based on well-known PAM50 and PCS subtyping classifiers. Using publicly available databases, we successfully validate the four-gene panel as having the potential to serve as a prognostic and predictive biomarker for PC specifically based on DDR biology.

High Mobility Group Box 1 Promotes Lung Cancer Cell Migration and Motility via Regulation of Dynamin-Related Protein 1.

High mobility group box 1 (HMGB1) has been demonstrated to promote the migration and invasion of non-small cell lung cancer (NSCLC). However, the mechanism of action of HMGB1 in regulating tumor mobility remains unclear. Therefore, we aimed to investigate whether HMGB1 affects mitochondria distribution and regulates dynamin-related protein 1 (DRP1)-mediated lamellipodia/filopodia formation to promote NSCLC migration. The regulation of mitochondrial membrane tension, dynamics, polarization, fission process, and cytoskeletal rearrangements in lung cancer cells by HMGB1 was analyzed using confocal microscopy. The HMGB1-mediated regulation of DRP1 phosphorylation and colocalization was determined using immunostaining and co-immunoprecipitation assays. The tumorigenic potential of HMGB1 was assessed in vivo and further confirmed using NSCLC patient samples. Our results showed that HMGB1 increased the polarity and mobility of cells (mainly by regulating the cytoskeletal system actin and microtubule dynamics and distribution), promoted the formation of lamellipodia/filopodia, and enhanced the expression and phosphorylation of DRP1 in both the nucleus and cytoplasm. In addition, HMGB1 and DRP1 expressions were positively correlated and exhibited poor prognosis and survival in patients with lung cancer. Collectively, HMGB1 plays a key role in the formation of lamellipodia and filopodia by regulating cytoskeleton dynamics and DRP1 expression to promote lung cancer migration.

Targeting lipid droplet lysophosphatidylcholine for cisplatin chemotherapy.

This study aims to explore lipidic mechanism towards low-density lipoprotein receptor (LDLR)-mediated platinum chemotherapy resistance. By using the lipid profiling technology, LDLR knockdown was found to increase lysosomal lipids and decrease membranous lipid levels in EOC cells. LDLR knockdown also down-regulated ether-linked phosphatidylethanolamine (PE-O, lysosomes or peroxisomes) and up-regulated lysophosphatidylcholine [LPC, lipid droplet (LD)]. This implies that the manner of using Lands cycle (conversion of lysophospholipids) for LDs might affect cisplatin sensitivity. The bioinformatics analyses illustrated that LDLR-related lipid entry into LD, rather than an endogenous lipid resource (eg Kennedy pathway), controls the EOC prognosis of platinum chemotherapy patients. Moreover, LDLR knockdown increased the number of platinum-DNA adducts and reduced the LD platinum amount. By using a manufactured LPC-liposome-cisplatin (LLC) drug, the number of platinum-DNA adducts increased significantly in LLC-treated insensitive cells. Moreover, the cisplatin content in LDs increased upon LLC treatment. Furthermore, lipid profiles of 22 carcinoma cells with differential cisplatin sensitivity (9 sensitive vs 13 insensitive) were acquired. These profiles revealed low storage lipid levels in insensitive cells. This result recommends that LD lipidome might be a common pathway in multiple cancers for platinum sensitivity in EOC. Finally, LLC suppressed both cisplatin-insensitive human carcinoma cell training and testing sets. Thus, LDLR-platinum insensitivity can be due to a defective Lands cycle that hinders LPC production in LDs. Using lipidome assessment with the newly formulated LLC can be a promising cancer chemotherapy method.