CD4+T and CD8+T Cells in Uterus Exhibit Both Selective Dysfunction and Residency Signatures.

Unlike T cells in other tissues, uterine T cells must balance strong immune defense against pathogens with tolerance to semiallogeneic fetus. Our previous study fully elucidated the characteristics of γδT cells in nonpregnant uterus and the mechanism modulated by estrogen. However, comprehensive knowledge of the immunological properties of αßT (including CD4+T cells and CD8+T) cells in nonpregnancy uterus has not been acquired. In this study, we fully compared the immunological properties of αßT cells between uterus and blood using mouse and human sample. It showed that most of CD4+T cells and CD8+T cells in murine uterus and human endometrium were tissue resident memory T cells which highly expressed tissue residence markers CD69 and/or CD103. In addition, both CD4+T cells and CD8+T cells in uterus highly expressed inhibitory molecular PD-1 and cytokine IFN-γ. Uterine CD4+T cells highly expressed IL-17 and modulated by transcription factor pSTAT3. Moreover, we compared the similarities and differences between human and murine uterine T cell phenotype. Together, uterine CD4+T cells and CD8+ cells exhibited a unique mixed signature of T cell dysfunction, activation, and effector function which enabled them to balance strong immune defense against pathogens with tolerance to fetus. Our study fully elucidated the unique immunologic properties of uterine CD4+T and CD8+T cells and provided a base for further investigation of functions.

Discovery of novel nucleoside derivatives as selective lysine acetyltransferase p300 inhibitors for cancer therapy.

P300 and CBP are two closely related histone acetyltransferases that are important transcriptional coactivators of many cellular processes. Inhibition of the transcriptional regulator p300/CBP is a promising therapeutic approach in oncology. However, there are no reported single selective p300 or CBP inhibitors to date. In this study, we designed and optimized a series of lysine acetyltransferase p300 selective inhibitors bearing a nucleoside scaffold. Most compounds showed excellent inhibitory activity against p300 with IC50 ranging from 0.18 to 9.90 µM, except for J16, J29, J40, and J48. None of the compounds showed inhibitory activity against CBP (inhibition rate < 50 % at 10 µM). Then the cytotoxicity of the compounds against a series of cancer cells were evaluated. Compounds J31 and J32 showed excellent proliferation inhibitory activity on cancer cells T47D and H520 with desirable selectivity profile of p300 over CBP. These compounds could be promising lead compounds for the development of novel epigenetic inhibitors as antitumor agents.

Transcriptome analysis unveils the mechanisms of lipid metabolism response to grayanotoxin I stress in Spodoptera litura.

Background: Spodoptera litura (tobacco caterpillar, S. litura) is a pest of great economic importance due to being a polyphagous and world-distributed agricultural pest. However, agricultural practices involving chemical pesticides have caused resistance, resurgence, and residue problems, highlighting the need for new, environmentally friendly methods to control the spread of S. litura. Aim: This study aimed to investigate the gut poisoning of grayanotoxin I, an active compound found in Pieris japonica, on S. litura, and to explore the underlying mechanisms of these effects. Methods: S. litura was cultivated in a laboratory setting, and their survival rate, growth and development, and pupation time were recorded after grayanotoxin I treatment. RNA-Seq was utilized to screen for differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to determine the functions of these DEGs. ELISA was employed to analyze the levels of lipase, 3-hydroxyacyl-CoA dehydrogenase (HOAD), and acetyl-CoA carboxylase (ACC). Hematoxylin and Eosin (H & E) staining was used to detect the development of the fat body. Results: Grayanotoxin I treatment significantly suppressed the survival rate, growth and development, and pupation of S. litura. RNA-Seq analysis revealed 285 DEGs after grayanotoxin I exposure, with over 16 genes related to lipid metabolism. These 285 DEGs were enriched in the categories of cuticle development, larvae longevity, fat digestion and absorption. Grayanotoxin I treatment also inhibited the levels of FFA, lipase, and HOAD in the hemolymph of S. litura. Conclusion: The results of this study demonstrated that grayanotoxin I inhibited the growth and development of S. litura. The mechanisms might, at least partly, be related to the interference of lipid synthesis, lipolysis, and fat body development. These findings provide valuable insights into a new, environmentally-friendly plant-derived insecticide, grayanotoxin I, to control the spread of S. litura.

The obesogenic side of Genistein.

Genistein (GN) has been highly recommended for its medicinal properties like anticancer, antidiabetic, antihyperlipidemic, antiviral, and antioxidant activities among others. Recently, scientists realized that Genistein is an endocrine disruptor. It is an obesogen that interferes with the endocrine system causing obesity through many mechanisms like inducing adipocyte differentiation, lipid accumulation, and transformation of some stem cells into adipocytes (bone marrow mesenchymal stem cells for example) in vitro. Animal studies show that GN upregulates genes associated with adipogenesis like CCAAT/enhancer binding protein alpha (Cebpα), CCAAT/enhancer binding protein beta (Cebpß), and PPARγ. In silico studies reveal a strong binding affinity for estrogen receptors. All these findings were contingent on concentration and tissues. It is beyond dispute that obesity is one of the most frustrating medical conditions under the sun. The pathophysiology of this disease was first attributed to a high-calorie diet and lack of physical activity. However, studies proved that these two factors are not enough to account for obesity in both children and adults. This mini review highlights how Genistein interaction with the peroxisome proliferator-activated receptor gamma protein can cause obesity.

Cryopreservation of bioflavonoid-rich plant sources and bioflavonoid-microcapsules: emerging technologies for preserving bioactivity and enhancing nutraceutical applications.

Bioflavonoids are natural polyphenolic secondary metabolites that are medicinal. These compounds possess antitumor, cardioprotective, anti-inflammatory, antimicrobial, antiviral, and anti-psoriasis properties to mention a few. Plant species that contain bioflavonoids should be preserved as such. Also, the bioactivity of the bioflavonoids as neutraceutical compounds is compromised following extraction due to their sensitivity to environmental factors like light, pH, and temperature. In other words, the bioflavonoids' shelf-life is affected. Scientists noticed that bioflavonoids have low solubility properties, poor absorption, and low bioavailability following consumption. Researchers came up with methods to encapsulate bioflavonoids in order to circumvent the challenges above and also to mask the unpleasant order these chemicals may have. Besides, scientists cryopreserve plant species that contain bioflavonoids. In this review, we discuss cryopreservation and bioflavonoid microencapsulation focusing mainly on vitrification, slow freezing, and freeze-drying microencapsulation techniques. In addition, we highlight bioflavonoid extraction techniques, medicinal properties, challenges, and future perspectives of cryopreservation and microencapsulation of bioflavonoids. Regardless of the uniqueness of cryopreservation and microencapsulation as methods to preserve bioflavonoid sources and bioflavonoids' bioactivity, there are challenges reported. Freeze-drying technology is costly. Cryoprotectants damage the integrity of plant cells, to say the least. Researchers are working very hard to overcome these challenges. Encapsulating bioflavonoids via coaxial electrospray and then cryopreserving the micro/nanocapsules produced can be very interesting.

A cross-cohort computational framework to trace tumor tissue-of-origin based on RNA sequencing.

Carcinoma of unknown primary (CUP) is a type of metastatic cancer with tissue-of-origin (TOO) unidentifiable by traditional methods. CUP patients typically have poor prognosis but therapy targeting the original cancer tissue can significantly improve patients' prognosis. Thus, it's critical to develop accurate computational methods to infer cancer TOO. While qPCR or microarray-based methods are effective in inferring TOO for most cancer types, the overall prediction accuracy is yet to be improved. In this study, we propose a cross-cohort computational framework to trace TOO of 32 cancer types based on RNA sequencing (RNA-seq). Specifically, we employed logistic regression models to select 80 genes for each cancer type to create a combined 1356-gene set, based on transcriptomic data from 9911 tissue samples covering the 32 cancer types with known TOO from the Cancer Genome Atlas (TCGA). The selected genes are enriched in both tissue-specific and tissue-general functions. The cross-validation accuracy of our framework reaches 97.50% across all cancer types. Furthermore, we tested the performance of our model on the TCGA metastatic dataset and International Cancer Genome Consortium (ICGC) dataset, achieving an accuracy of 91.09% and 82.67%, respectively, despite the differences in experiment procedures and pipelines. In conclusion, we developed an accurate yet robust computational framework for identifying TOO, which holds promise for clinical applications. Our code is available at http://github.com/wangbo00129/classifybysklearn .

Effects of Litsea cubeba essential oil on growth performance, blood antioxidation, immune function, apparent digestibility of nutrients, and fecal microflora of pigs.

The purpose of this experiment was to investigate the effects of Litsea cubeba essential oil (LCO) on the growth performance, blood antioxidation, immune function, apparent digestibility of nutrients, and fecal microflora in fattening pigs. A total of 120 pigs were randomly assigned to five groups, with six replicate pens per treatment and four pigs per pen, and they were fed basal diet, chlortetracycline (CTC), and low-, medium-, and high-concentration LCO. The results of the study showed that compared with the control treatment and CTC addition treatment of the basic diet, the catalase level in the serum of the pigs treated with 500 mg/kg LCO in the diet of finishing pigs was significantly increased (p < 0.05). The apparent digestibility of crude protein, crude ash, and calcium in pigs with different levels of LCO was significantly increased compared with the control treatments fed the basal diet (p < 0.05). In addition, compared with the control treatment fed the basal diet and the treatment with CTC, the apparent digestibility of ether extract in pigs treated with medium-dose LCO was significantly increased (p < 0.05), and the apparent digestibility of pigs was significantly increased after the addition of low-dose LCO (p < 0.05). Among the genera, the percentage abundance of SMB53 (p < 0.05) was decreased in the feces of the CTC group when compared to that in the medium-LCO group. At the same time, the relative abundance of L7A_E11 was markedly decreased in the feces of the control and medium- and high-concentration LCO group than that in the CTC group (p < 0.05). In conclusion, adding the level of 250 mg/kg LCO in the diet of pig could improve the growth performance and blood physiological and biochemical indicators of pigs, improve the antioxidant level of body and the efficiency of digestion and absorption of nutrients, and show the potential to replace CTC.

Antitumor Activity of s-Triazine Derivatives: A Systematic Review.

1,3,5-triazine derivatives, also called s-triazines, are a series of containing-nitrogen heterocyclic compounds that play an important role in anticancer drug design and development. To date, three s-triazine derivatives, including altretamine, gedatolisib, and enasidenib, have already been approved for refractory ovarian cancer, metastatic breast cancer, and leukemia therapy, respectively, demonstrating that the s-triazine core is a useful scaffold for the discovery of novel anticancer drugs. In this review, we mainly focus on s-triazines targeting topoisomerases, tyrosine kinases, phosphoinositide 3-kinases, NADP+-dependent isocitrate dehydrogenases, and cyclin-dependent kinases in diverse signaling pathways, which have been extensively studied. The medicinal chemistry of s-triazine derivatives as anticancer agents was summarized, including discovery, structure optimization, and biological applications. This review will provide a reference to inspire new and original discoveries.

LncRNA FAS-AS1 upregulated by its genetic variation rs6586163 promotes cell apoptosis in nasopharyngeal carcinoma through regulating mitochondria function and Fas splicing.

Nasopharyngeal carcinoma (NPC) is a common head and neck malignant with a high incidence in Southern China. Genetic aberrations play a vital role in the pathogenesis, progression and prognosis of NPC. In the present study, we elucidated the underlying mechanism of FAS-AS1 and its genetic variation rs6586163 in NPC. We demonstrated that FAS-AS1 rs6586163 variant genotype carriers were associated with lower risk of NPC (CC vs. AA, OR = 0.645, P = 0.006) and better overall survival (AC + CC vs. AA, HR = 0.667, P = 0.030). Mechanically, rs6586163 increased the transcriptional activity of FAS-AS1 and contributed to ectopic overexpression of FAS-AS1 in NPC. rs6586163 also exhibited an eQTL trait and the genes affected by rs6586163 were enriched in apoptosis related signaling pathway. FAS-AS1 was downregulated in NPC tissues and over-expression of FAS-AS1 was associated with early clinical stage and better short-term treatment efficacy for NPC patients. Overexpression of FAS-AS1 inhibited NPC cell viability and promoted cell apoptosis. GSEA analysis of RNA-seq data suggested FAS-AS1 participate in mitochondria regulation and mRNA alternative splicing. Transmission electron microscopic examination verified that the mitochondria was swelled, the mitochondrial cristae was fragmented or disappeared, and their structures were destroyed in FAS-AS1 overexpressed cells. Furthermore, we identified HSP90AA1, CS, BCL2L1, SOD2 and PPARGC1A as the top 5 hub genes of FAS-AS1 regulated genes involved in mitochondria function. We also proved FAS-AS1 could affect Fas splicing isoform sFas/mFas expression ratio, and apoptotic protein expression, thus leading to increased apoptosis. Our study provided the first evidence that FAS-AS1 and its genetic polymorphism rs6586163 triggered apoptosis in NPC, which might have a potential as new biomarkers for NPC susceptibility and prognosis.

The ferroptosis signature predicts the prognosis and immune microenvironment of nasopharyngeal carcinoma.

Nasopharyngeal carcinoma (NPC) is a cancer with a high metastatic rate and poor prognosis. Growing studies suggest that ferroptosis take part in the development of tumours. At the same time, the connection between ferroptosis-related genes (FRGs) and the prognosis of NPC remains unclear. In this study, we explored the dysregulated FRGs between normal control and tumour samples of NPC. Firstly, 14 of 36 differentially expressed FRGs were identified in NPC tissues compared to normal tissues, among which ABCC1, GLS2, CS and HMGCR were associated with poor prognosis for patients. The four ferroptosis genes were used for consensus cluster analysis and two risk-related FRGs (ABCC1 and GLS2) were used in a risk model. The ROC curve revealed the good predictive performance of this risk signature. Multivariate analysis revealed that risk score and intratumoral TILs were independent risk factors linked to prognosis. Additionally, our results suggested that the risk signature was attached to the immune microenvironment. Moreover, the NPC patients with high risk were sensitive to chemotherapeutic drugs including axitinib, docetaxel, embelin, epothilone.B, parthenolide, thapsigargin, tipifarnib, vinorelbine. Finally, the expression of ABCC1 and GLS2 was validated in NPC tissues using immunohistochemistry. Together, these results revealed ferroptosis may be a potential biomarker in NPC and representing a promising future direction in prognosis and therapeutic strategy for the treatment of NPC.

MNNMDA: Predicting human microbe-disease association via a method to minimize matrix nuclear norm.

Identifying the potential associations between microbes and diseases is the first step for revealing the pathological mechanisms of microbe-associated diseases. However, traditional culture-based microbial experiments are expensive and time-consuming. Thus, it is critical to prioritize disease-associated microbes by computational methods for further experimental validation. In this study, we proposed a novel method called MNNMDA, to predict microbe-disease associations (MDAs) by applying a Matrix Nuclear Norm method into known microbe and disease data. Specifically, we first calculated Gaussian interaction profile kernel similarity and functional similarity for diseases and microbes. Then we constructed a heterogeneous information network by combining the integrated disease similarity network, the integrated microbe similarity network and the known microbe-disease bipartite network. Finally, we formulated the microbe-disease association prediction problem as a low-rank matrix completion problem, which was solved by minimizing the nuclear norm of a matrix with a few regularization terms. We tested the performances of MNNMDA in three datasets including HMDAD, Disbiome, and Combined Data with small, medium and large sizes respectively. We also compared MNNMDA with 5 state-of-the-art methods including KATZHMDA, LRLSHMDA, NTSHMDA, GATMDA, and KGNMDA, respectively. MNNMDA achieved area under the ROC curves (AUROC) of 0.9536 and 0.9364 respectively on HDMAD and Disbiome, better than the AUCs of compared methods under the 5-fold cross-validation for all microbe-disease associations. It also obtained a relatively good performance with AUROC 0.8858 in the combined data. In addition, MNNMDA was also better than other methods in area under precision and recall curve (AUPR) under the 5-fold cross-validation for all associations, and in both AUROC and AUPR under the 5-fold cross-validation for diseases and the 5-fold cross-validation for microbes. Finally, the case studies on colon cancer and inflammatory bowel disease (IBD) also validated the effectiveness of MNNMDA. In conclusion, MNNMDA is an effective method in predicting microbe-disease associations. Availability: The codes and data for this paper are freely available at Github https://github.com/Haiyan-Liu666/MNNMDA.

Endocrine and metabolic factors and the risk of idiopathic pulmonary fibrosis: a Mendelian randomization study.

Background: Previous observational studies have investigated the association between endocrine and metabolic factors and idiopathic pulmonary fibrosis (IPF), yet have produced inconsistent results. Therefore, it is imperative to employ the Mendelian randomization (MR) analysis method to conduct a more comprehensive investigation into the impact of endocrine and metabolic factors on IPF. Methods: The instrumental variables (IVs) for 53 endocrine and metabolic factors were sourced from publicly accessible genome-wide association study (GWAS) databases, with GWAS summary statistics pertaining to IPF employed as the dependent variables. Causal inference analysis encompassed the utilization of three methods: inverse-variance weighted (IVW), weighted median (WM), and MR-Egger. Sensitivity analysis incorporated the implementation of MR-PRESSO and leave-one-out techniques to identify potential pleiotropy and outliers. The presence of horizontal pleiotropy and heterogeneity was evaluated through the MR-Egger intercept and Cochran's Q statistic, respectively. Results: The IVW method results reveal correlations between 11 traits and IPF. After correcting for multiple comparisons, seven traits remain statistically significant. These factors include: "Weight" (OR= 1.44; 95% CI: 1.16, 1.78; P=8.71×10-4), "Body mass index (BMI)" (OR= 1.35; 95% CI: 1.13, 1.62; P=1×10-3), "Whole body fat mass" (OR= 1.40; 95% CI: 1.14, 1.74; P=1.72×10-3), "Waist circumference (WC)" (OR= 1.54; 95% CI: 1.16, 2.05; P=3.08×10-3), "Trunk fat mass (TFM)" (OR=1.35; 95% CI: 1.10,1.65; P=3.45×10-3), "Body fat percentage (BFP)" (OR= 1.55; 95% CI: 1.15,2.08; P=3.86×10-3), "Apoliprotein B (ApoB)" (OR= 0.78; 95% CI: 0.65,0.93; P=5.47×10-3). Additionally, the sensitivity analysis results confirmed the reliability of the MR results. Conclusion: The present study identified causal relationships between seven traits and IPF. Specifically, ApoB exhibited a negative impact on IPF, while the remaining six factors demonstrated a positive impact. These findings offer novel insights into the underlying etiopathological mechanisms associated with IPF.

Linc00312 Single Nucleotide Polymorphism as Biomarker for Chemoradiotherapy Induced Hematotoxicity in Nasopharyngeal Carcinoma Patients.

Background: Linc00312 is downregulated in nasopharyngeal carcinoma (NPC) and associates with poor treatment efficacy. Genetic variations are the main cause of individual differences in treatment response. The objective of this study is to explore the relationship between genetic variations of linc00312 and the risk of chemoradiotherapy induced toxic reactions in NPC patients. Methods: We used a bioinformatics approach to select 3 single nucleotide polymorphisms (SNPs) with regulatory feature in linc00312 (rs12497104, rs15734, and rs164966). 505 NPC patients receiving chemoradiotherapy with complete follow-up data were recruited. Genotyping was carried out by MassARRAY iPLEX platform. Univariate logistic and multivariate logistic regression were used to analyze the risk factors responsible for toxic reactions of NPC patients. Results: Our result demonstrated that linc00312 rs15734 (G > A) was significantly associated with severe leukopenia in NPC patients underwent chemoradiotherapy (AA vs. GG, OR = 3.145, P = 0.029). In addition, the risk of severe leukopenia was remarkably increased to 5.635 times (P = 0.034) in female with rs15734 AA genotype compared to male with rs15734 GG genotype. Moreover, patients with rs12497104 (G > A) AA genotype showed a 67.5% lower risk of thrombocytopenia than those with GG genotype (P = 0.030). Remarkably, the younger patients (age < 47) with rs12497104 AA genotype displayed a 90% decreased risk of thrombocytopenia compared with older patients (age ≥ 47) carrying rs12497104 GG genotype (P = 0.030). Conclusions: Genetic variations of linc00312 affect the risk of chemoradiotherapy induced hematotoxicity in nasopharyngeal carcinoma patients and may serve as biomarkers for personalized medicine.

DL-3-n-butylphthalide (NBP) alleviates poststroke cognitive impairment (PSCI) by suppressing neuroinflammation and oxidative stress.

Currently, the recovery of cognitive function has become an essential part of stroke rehabilitation. DL-3-n-butylphthalide (NBP) is a neuroprotective reagent and has been used in stroke treatment. Clinical studies have confirmed that NBP can achieve better cognitive outcomes in ischemic stroke patients than in healthy controls. In this study, we aimed to investigate the influences of NBP on cognitive function in an ischemic reperfusion (I/R) rat model. Our results showed that NBP profoundly decreased neurological scores, reduced cerebral infarct areas and enhanced cerebral blood flow (CBF). NBP potently alleviated poststroke cognitive impairment (PSCI) including depression-like behavior and learning, memory and social cognition impairments, in I/R rats. NBP distinctly suppressed the activation of microglia and astrocytes and improved neuron viability in the ischemic brain. NBP inhibited the expression of inflammatory cytokines, including interleukin-6 (IL-6), interleukin-1ß (IL-1ß) and tumor necrosis factor-α (TNF-α), by targeting the nuclear factor kappa B/inducible nitric oxide synthase (NF-κB/iNOS) pathway and decreased cerebral oxidative stress factors, including reactive oxygen species (ROS) and malondialdehyde (MDA), by targeting the kelch like ECH associated protein 1/nuclear factor-erythroid 2 p45-related factor 2 (Keap1/Nrf2) pathway in the ischemic brain. The current study revealed that NBP treatment improved neurological function and ameliorated cognitive impairment in I/R rats, possibly by synergistically suppressing inflammation and oxidative stress.

Evaluating Cancer-Related Biomarkers Based on Pathological Images: A Systematic Review.

Many diseases are accompanied by changes in certain biochemical indicators called biomarkers in cells or tissues. A variety of biomarkers, including proteins, nucleic acids, antibodies, and peptides, have been identified. Tumor biomarkers have been widely used in cancer risk assessment, early screening, diagnosis, prognosis, treatment, and progression monitoring. For example, the number of circulating tumor cell (CTC) is a prognostic indicator of breast cancer overall survival, and tumor mutation burden (TMB) can be used to predict the efficacy of immune checkpoint inhibitors. Currently, clinical methods such as polymerase chain reaction (PCR) and next generation sequencing (NGS) are mainly adopted to evaluate these biomarkers, which are time-consuming and expansive. Pathological image analysis is an essential tool in medical research, disease diagnosis and treatment, functioning by extracting important physiological and pathological information or knowledge from medical images. Recently, deep learning-based analysis on pathological images and morphology to predict tumor biomarkers has attracted great attention from both medical image and machine learning communities, as this combination not only reduces the burden on pathologists but also saves high costs and time. Therefore, it is necessary to summarize the current process of processing pathological images and key steps and methods used in each process, including: (1) pre-processing of pathological images, (2) image segmentation, (3) feature extraction, and (4) feature model construction. This will help people choose better and more appropriate medical image processing methods when predicting tumor biomarkers.

Evaluation of the MGISEQ-2000 Sequencing Platform for Illumina Target Capture Sequencing Libraries.

Illumina is the leading sequencing platform in the next-generation sequencing (NGS) market globally. In recent years, MGI Tech has presented a series of new sequencers, including DNBSEQ-T7, MGISEQ-2000 and MGISEQ-200. As a complex application of NGS, cancer-detecting panels pose increasing demands for the high accuracy and sensitivity of sequencing and data analysis. In this study, we used the same capture DNA libraries constructed based on the Illumina protocol to evaluate the performance of the Illumina Nextseq500 and MGISEQ-2000 sequencing platforms. We found that the two platforms had high consistency in the results of hotspot mutation analysis; more importantly, we found that there was a significant loss of fragments in the 101-133 bp size range on the MGISEQ-2000 sequencing platform for Illumina libraries, but not for the capture DNA libraries prepared based on the MGISEQ protocol. This phenomenon may indicate fragment selection or low fragment ligation efficiency during the DNA circularization step, which is a unique step of the MGISEQ-2000 sequence platform. In conclusion, these different sequencing libraries and corresponding sequencing platforms are compatible with each other, but protocol and platform selection need to be carefully evaluated in combination with research purpose.

Identifying Breast Cancer-Related Genes Based on a Novel Computational Framework Involving KEGG Pathways and PPI Network Modularity.

Complex diseases, such as breast cancer, are often caused by mutations of multiple functional genes. Identifying disease-related genes is a critical and challenging task for unveiling the biological mechanisms behind these diseases. In this study, we develop a novel computational framework to analyze the network properties of the known breast cancer-associated genes, based on which we develop a random-walk-with-restart (RCRWR) algorithm to predict novel disease genes. Specifically, we first curated a set of breast cancer-associated genes from the Genome-Wide Association Studies catalog and Online Mendelian Inheritance in Man database and then studied the distribution of these genes on an integrated protein-protein interaction (PPI) network. We found that the breast cancer-associated genes are significantly closer to each other than random, which confirms the modularity property of disease genes in a PPI network as revealed by previous studies. We then retrieved PPI subnetworks spanning top breast cancer-associated KEGG pathways and found that the distribution of these genes on the subnetworks are non-random, suggesting that these KEGG pathways are activated non-uniformly. Taking advantage of the non-random distribution of breast cancer-associated genes, we developed an improved RCRWR algorithm to predict novel cancer genes, which integrates network reconstruction based on local random walk dynamics and subnetworks spanning KEGG pathways. Compared with the disease gene prediction without using the information from the KEGG pathways, this method has a better prediction performance on inferring breast cancer-associated genes, and the top predicted genes are better enriched on known breast cancer-associated gene ontologies. Finally, we performed a literature search on top predicted novel genes and found that most of them are supported by at least wet-lab experiments on cell lines. In summary, we propose a robust computational framework to prioritize novel breast cancer-associated genes, which could be used for further in vitro and in vivo experimental validation.

Genetic Polymorphisms of Long Non-coding RNA Linc00312 Are Associated With Susceptibility and Predict Poor Survival of Nasopharyngeal Carcinoma.

BACKGROUND: Linc00312 is dysregulated in nasopharyngeal carcinoma (NPC) and participates in the initiation and progression of NPC. Our previous studies suggested that linc00312 was able to enhance the sensitivity of NPC cells to irradiation and NPC patients with higher expression of linc00312 was associated with better short-term curative effect and overall survival. The single nucleotide polymorphisms (SNPs) of lncRNAs may influence the disease course and outcome by affecting the expression, secondary structure or function of lncRNAs. However, the role of SNPs in linc00312 on the occurrence and survival of NPC remains unknown. METHODS: We recruited 684 NPC patients and 823 healthy controls to evaluate the association between linc00312 SNPs and NPC susceptibility by using multivariate logistic regression analysis. Kaplan-Meier analysis and Cox proportional hazards regression were applied to assess the effect of linc00312 SNPs on the survival of NPC patients. The relative expression of linc00312 in NPC tissues was determined by real-time PCR. The interaction between linc00312 and mir-411-3p was explored by luciferase reporter assay. In silico prediction of the changes on linc00312 folding structure was conducted by RNAfold WebServer. RESULT: We demonstrated that rs12497104 (G > A) GA genotype carriers had a higher risk than others for suffering from NPC (GA vs GG, OR = 1.437, P = 0.003). Besides, patients with rs12497104 AA genotype showed a poorer overall survival in contrast to GG genotype (AA vs GG, HR = 2.117, P = 0.011). In addition, the heterozygous carriers of rs15734 (G > A) and rs164966 (A > G) were correlated with decreased risk of NPC (GA vs GG, OR = 0.778, P = 0.031; GA vs AA, OR = 0.781, P = 0.033, respectively). We found that the three SNPs might influence the expression of linc00312 in a genotype specific feature. The local centroid secondary structure as well as the minimum free energy of linc00312 were changed following the candidate SNPs alterations. Besides, we revealed that the G to A alteration at rs12497104 disrupted the binding between mir-411-3p and linc00312. CONCLUSION: Our results indicated genetic polymorphisms of linc00312 might serve as potential biomarkers for NPC carcinogenesis and prognosis.

A Review of Current In Silico Methods for Repositioning Drugs and Chemical Compounds.

Drug repositioning is a new way of applying the existing therapeutics to new disease indications. Due to the exorbitant cost and high failure rate in developing new drugs, the continued use of existing drugs for treatment, especially anti-tumor drugs, has become a widespread practice. With the assistance of high-throughput sequencing techniques, many efficient methods have been proposed and applied in drug repositioning and individualized tumor treatment. Current computational methods for repositioning drugs and chemical compounds can be divided into four categories: (i) feature-based methods, (ii) matrix decomposition-based methods, (iii) network-based methods, and (iv) reverse transcriptome-based methods. In this article, we comprehensively review the widely used methods in the above four categories. Finally, we summarize the advantages and disadvantages of these methods and indicate future directions for more sensitive computational drug repositioning methods and individualized tumor treatment, which are critical for further experimental validation.

A Neural Network Framework for Predicting the Tissue-of-Origin of 15 Common Cancer Types Based on RNA-Seq Data.

Sequencing-based identification of tumor tissue-of-origin (TOO) is critical for patients with cancer of unknown primary lesions. Even if the TOO of a tumor can be diagnosed by clinicopathological observation, reevaluations by computational methods can help avoid misdiagnosis. In this study, we developed a neural network (NN) framework using the expression of a 150-gene panel to infer the tumor TOO for 15 common solid tumor cancer types, including lung, breast, liver, colorectal, gastroesophageal, ovarian, cervical, endometrial, pancreatic, bladder, head and neck, thyroid, prostate, kidney, and brain cancers. To begin with, we downloaded the RNA-Seq data of 7,460 primary tumor samples across the above mentioned 15 cancer types, with each type of cancer having between 142 and 1,052 samples, from the cancer genome atlas. Then, we performed feature selection by the Pearson correlation method and performed a 150-gene panel analysis; the genes were significantly enriched in the GO:2001242 Regulation of intrinsic apoptotic signaling pathway and the GO:0009755 Hormone-mediated signaling pathway and other similar functions. Next, we developed a novel NN model using the 150 genes to predict tumor TOO for the 15 cancer types. The average prediction sensitivity and precision of the framework are 93.36 and 94.07%, respectively, for the 7,460 tumor samples based on the 10-fold cross-validation; however, the prediction sensitivity and precision for a few specific cancers, like prostate cancer, reached 100%. We also tested the trained model on a 20-sample independent dataset with metastatic tumor, and achieved an 80% accuracy. In summary, we present here a highly accurate method to infer tumor TOO, which has potential clinical implementation.