Monochasma savatieri Franch. protects against acute lung injury via α7nAChR-TLR4/NF-κB p65 signaling pathway based on integrated pharmacology analysis.

ETHNOPHARMACOLOGICAL RELEVANCE: Acute lung injury (ALI) is a life-threatening condition with high morbidity and mortality, underscoring the urgent need for novel treatments. Monochasma savatieri Franch. (LRC) is commonly used clinically to treat wind-heat cold, bronchitis, acute pneumonia and acute gastroenteritis. However, its role in the treatment of ALI and its mechanism of action are still unclear. AIM OF THE STUDY: This study aimed to demonstrate the pharmacological effects and underlying mechanisms of LRC extract, and provide important therapeutic strategies and theoretical basis for ALI. MATERIALS AND METHODS: In this study, a research paradigm of integrated pharmacology combining histopathological analysis, network pharmacology, metabolomics, and biochemical assays was used to elucidate the mechanisms underlaying the effects of LRC extract on LPS-induced ALI in BALB/c mice. RESULTS: The research findings demonstrated that LRC extract significantly alleviated pathological damage in lung tissues and inhibited apoptosis in alveolar epithelial cells, and the main active components were luteolin, isoacteoside, and aucubin. Lung tissue metabolomic and immunohistochemical methods confirmed that LRC extract could restore metabolic disorders in ALI mice by correcting energy metabolism imbalance, activating cholinergic anti-inflammatory pathway (CAP), and inhibiting TLR4/NF-κB signaling pathway. CONCLUSIONS: This study showed that LRC extract inhibited the occurrence and development of ALI inflammation by promoting the synthesis of antioxidant metabolites, balancing energy metabolism, activating CAP and suppressing the α7nAChR-TLR4/NF-κB p65 signaling pathway. In addition, our study provided an innovative research model for exploring the effective ingredients and mechanisms of traditional Chinese medicine. To the best of our knowledge, this is the first report describing the protective effects of LRC extract in LPS-induced ALI mice.

Identification of memory B-cell-associated miRNA signature to establish a prognostic model in gastric adenocarcinoma.

BACKGROUND: Memory B cells and microRNAs (miRNAs) play important roles in the progression of gastric adenocarcinoma (GAC), also known as stomach adenocarcinoma (STAD). However, few studies have investigated the use of memory B-cell-associated miRNAs in predicting the prognosis of STAD. METHODS: We identified the marker genes of memory B cells by single-cell RNA sequencing (scRNA-seq) and identified the miRNAs associated with memory B cells by constructing an mRNA‒miRNA coexpression network. Then, univariate Cox, random survival forest (RSF), and stepwise multiple Cox regression (StepCox) algorithms were used to identify memory B-cell-associated miRNAs that were significantly related to overall survival (OS). A prognostic risk model was constructed and validated using these miRNAs, and patients were divided into a low-risk group and a high-risk group. In addition, the differences in clinicopathological features, tumour microenvironment, immune blocking therapy, and sensitivity to anticancer drugs in the two groups were analysed. RESULTS: Four memory B-cell-associated miRNAs (hsa-mir-145, hsa-mir-125b-2, hsa-mir-100, hsa-mir-221) with significant correlations to OS were identified and used to construct a prognostic model. Time-dependent receiver operating characteristic (ROC) curve analysis confirmed the feasibility of the model. Kaplan‒Meier (K‒M) survival curve analysis showed that the prognosis was poor in the high-risk group. Comprehensive analysis showed that patients in the high-risk group had higher immune scores, matrix scores, and immune cell infiltration and a poor immune response. In terms of drug screening, we predicted eight drugs with higher sensitivity in the high-risk group, of which CGP-60474 was associated with the greatest sensitivity. CONCLUSIONS: In summary, we identified memory B-cell-associated miRNA prognostic features and constructed a novel risk model for STAD based on scRNA-seq data and bulk RNA-seq data. Among patients in the high-risk group, STAD showed the highest sensitivity to CGP-60474. This study provides prognostic insights into individualized and precise treatment for STAD patients.

SSELM-neg: spherical search-based extreme learning machine for drug-target interaction prediction.

BACKGROUND: The experimental verification of a drug discovery process is expensive and time-consuming. Therefore, efficiently and effectively identifying drug-target interactions (DTIs) has been the focus of research. At present, many machine learning algorithms are used for predicting DTIs. The key idea is to train the classifier using an existing DTI to predict a new or unknown DTI. However, there are various challenges, such as class imbalance and the parameter optimization of many classifiers, that need to be solved before an optimal DTI model is developed. METHODS: In this study, we propose a framework called SSELM-neg for DTI prediction, in which we use a screening approach to choose high-quality negative samples and a spherical search approach to optimize the parameters of the extreme learning machine. RESULTS: The results demonstrated that the proposed technique outperformed other state-of-the-art methods in 10-fold cross-validation experiments in terms of the area under the receiver operating characteristic curve (0.986, 0.993, 0.988, and 0.969) and AUPR (0.982, 0.991, 0.982, and 0.946) for the enzyme dataset, G-protein coupled receptor dataset, ion channel dataset, and nuclear receptor dataset, respectively. CONCLUSION: The screening approach produced high-quality negative samples with the same number of positive samples, which solved the class imbalance problem. We optimized an extreme learning machine using a spherical search approach to identify DTIs. Therefore, our models performed better than other state-of-the-art methods.

Reciprocal positive regulation between BRD4 and YAP in GNAQ-mutant uveal melanoma cells confers sensitivity to BET inhibitors.

Uveal melanoma (UM) is the most common intraocular cancer in adults. UMs are usually initiated by a mutation in GNAQ or GNA11 (encoding Gq or G11, respectively), unlike cutaneous melanomas (CMs), which usually carry a BRAF or NRAS mutation. Currently, there are no clinically effective targeted therapies for UM carrying Gq/11 mutations. Here, we identified a causal link between Gq activating mutations and hypersensitivity to bromodomain and extra-terminal (BET) inhibitors. BET inhibitors transcriptionally repress YAP via BRD4 regardless of Gq mutation status, independently of Hippo core components LATS1/2. In contrast, YAP/TAZ downregulation reduces BRD4 transcription exclusively in Gq-mutant cells and LATS1/2 double knockout cells, both of which are featured by constitutively active YAP/TAZ. The transcriptional interdependency between BRD4 and YAP identified in Gq-mutated cells is responsible for the preferential inhibitory effect of BET inhibitors on the growth and dissemination of Gq-mutated UM cells compared to BRAF-mutated CM cells in both culture cells and animal models. Our findings suggest BRD4 as a viable therapeutic target for Gq-driven UMs that are addicted to unrestrained YAP function.

Identification of active compounds and molecular mechanisms of Dalbergia tsoi Merr.et Chun to accelerate wound healing.

As a traditional Chinese medicine, Dalbergia tsoi Merr.et Chun (JZX) has been used for the treatment of wounds since ancient times. However, the active compounds and molecular mechanisms of JZX in the acceleration of wound healing are still unknown. Herein, we explored the main active compounds and key molecular mechanisms by which JZX accelerates wound healing. The ethanol extract of JZX was subjected to UPLC-Q-Orbitrap HRMS analysis to identify the main compounds. The pharmacological effect of JZX on wound healing was evaluated using a mouse excision wound model. Network pharmacology was utilized to predict the effective compounds and related signal transduction pathways of JZX that were involved in accelerating wound healing. The predicted key signaling pathways were then validated by immunohistochemical analysis. Interactions between the active compounds and therapeutic targets were confirmed by molecular docking analysis. JZX accelerated wound healing, improved tissue quality, and inhibited inflammation and oxidative stress. Moreover, our results suggested that the active components of JZX, such as butin, eriodyctiol, and formononetin, are the key compounds that facilitate wound treatment. Our studies also indicated that JZX accelerated wound healing by regulating the PI3K/Akt signaling pathway and inducing the expression of TGF-ß1, FGF2, VEGFA, ECM1, and α-SMA at different stages of skin wound healing. The JZX extract accelerates wound healing by reducing inflammation and inhibiting oxidative stress, regulating the PI3K/Akt signaling pathway, and promoting the expression of growth factors, suggesting that JZX has potential clinical applicability in wound treatment.

PTEN loss confers sensitivity to rapalogs in clear cell renal cell carcinoma.

Rapalogs (everolimus and temsirolimus) are allosteric mTORC1 inhibitors and approved agents for advanced clear cell renal cell carcinoma (ccRCC), although only a subset of patients derive clinical benefit. Progress in genomic characterization has made it possible to generate comprehensive profiles of genetic alterations in ccRCC; however, the correlations between recurrent somatic mutations and rapalog efficacy remain unclear. Here, we demonstrate by using multiple patient-derived ccRCC cell lines that compared to PTEN-proficient cells, PTEN-deficient cells exhibit hypersensitivity to rapalogs. Rapalogs inhibit cell proliferation by inducing G0/G1 arrest without inducing apoptosis in PTEN-deficient ccRCC cell lines. Using isogenic cell lines generated by CRISPR/Cas9, we validate the correlation between PTEN loss and rapalog hypersensitivity. In contrast, deletion of VHL or chromatin-modifying genes (PBRM1, SETD2, BAP1, or KDM5C) fails to influence the cellular response to rapalogs. Our mechanistic study shows that ectopic expression of an activating mTOR mutant (C1483F) antagonizes PTEN-induced cell growth inhibition, while introduction of a resistant mTOR mutant (A2034V) enables PTEN-deficient ccRCC cells to escape the growth inhibitory effect of rapalogs, suggesting that PTEN loss generates vulnerability to mTOR inhibition. PTEN-deficient ccRCC cells are more sensitive to the inhibitory effects of temsirolimus on cell migration and tumor growth in zebrafish and xenograft mice, respectively. Of note, PTEN protein loss as detected by immunohistochemistry is much more frequent than mutations in the PTEN gene in ccRCC patients. Our study suggests that PTEN loss correlates with rapalog sensitivity and could be used as a marker for ccRCC patient selection for rapalog therapy.

BAP1 loss augments sensitivity to BET inhibitors in cancer cells.

The tumor suppressor gene BAP1 encodes a widely expressed deubiquitinase for histone H2A. Both hereditary and acquired mutations are associated with multiple cancer types, including cutaneous melanoma (CM), uveal melanoma (UM), and clear cell renal cell carcinoma (ccRCC). However, there is no personalized therapy for BAP1-mutant cancers. Here, we describe an epigenetic drug library screening to identify small molecules that exert selective cytotoxicity against BAP1 knockout CM cells over their isogenic parental cells. Hit characterization reveals that BAP1 loss renders cells more vulnerable to bromodomain and extraterminal (BET) inhibitor-induced transcriptional alterations, G1/G0 cell cycle arrest and apoptosis. The association of BAP1 loss with sensitivity to BET inhibitors is observed in multiple BAP1-deficient cancer cell lines generated by gene editing or derived from patient tumors as well as immunodeficient xenograft and immunocompetent allograft murine models. We demonstrate that BAP1 deubiquitinase activity reduces sensitivity to BET inhibitors. Concordantly, ectopic expression of RING1A or RING1B (H2AK119 E3 ubiquitin ligases) enhances sensitivity to BET inhibitors. The mechanistic study shows that the BET inhibitor OTX015 exerts a more potent suppressive effect on the transcription of various proliferation-related genes, especially MYC, in BAP1 knockout cells than in their isogenic parental cells, primarily by targeting BRD4. Furthermore, ectopic expression of Myc rescues the BET inhibitor-sensitizing effect induced by BAP1 loss. Our study reveals new approaches to specifically suppress BAP1-deficient cancers, including CM, UM, and ccRCC.

Co-occurrence of BAP1 and SF3B1 mutations in uveal melanoma induces cellular senescence.

Uveal melanoma (UM) is the most common intraocular tumor in adults. Recurrent mutations in BRCA1-associated protein 1 (BAP1) and splicing factor 3B subunit 1 (SF3B1) display a mutually exclusive pattern in UM, but the underlying mechanism is unknown. We show that combined BAP1 deficiency and SF3B1 hotspot mutation lead to senescence and growth arrest in human UM cells. Although p53 protein expression is induced, deletion of TP53 (encoding p53) only modestly rescues the observed senescent phenotype. UM cells with BAP1 loss or SF3B1 mutation are more sensitive to chemotherapeutic drugs compared with their isogenic parental cells. Transcriptome analysis shows that DNA-repair genes are downregulated upon co-occurrence of BAP1 deletion and SF3B1 mutation, thus leading to impaired DNA damage response and the induction of senescence. The co-occurrence of these two mutations reduces invasion of UM cells in zebrafish xenograft models and suppresses growth of melanoma xenografts in nude mice. Our findings provide a mechanistic explanation for the mutual exclusivity of BAP1 and SF3B1 mutations in human UM.

Systematic discovery of signaling pathways linking immune activation to schizophrenia.

Immune activation has been shown to play a critical role in the development of schizophrenia; however its underlying mechanism remains unknown. Our report demonstrates a high-quality protein interaction network for schizophrenia (SCZ Network), constructed using our "neighborhood walk" approach in combination with "random walk with restart". The spatiotemporal expression pattern of the genes in this disease network revealed two developmental stages sensitive to perturbation by immune activation: mid-to late gestation, and adolescence. Furthermore, we induced immune activation at these stages in mice, carried out transcriptome sequencing on the mouse brains, and illustrated clear potential molecular pathways and key regulators correlating maternal immune activation during gestation and an increased risk for schizophrenia after a second immune activation at puberty. This work provides not only valuable resources for the study on molecular mechanisms underlying schizophrenia, but also a systematic strategy for the discovery of molecular pathways of complex mental disorders.

Spliceosome-regulated RSRP1-dependent NF-κB activation promotes the glioblastoma mesenchymal phenotype.

BACKGROUND: The glioblastoma (GBM) mesenchymal (MES) phenotype, induced by NF-κB activation, is characterized by aggressive tumor progression and poor clinical outcomes. Our previous analysis indicated that MES GBM has a unique alternative splicing (AS) pattern; however, the underlying mechanism remains obscure. We aimed to reveal how splicing regulation contributes to MES phenotype promotion in GBM. METHODS: We screened novel candidate splicing factors that participate in NF-κB activation and MES phenotype promotion in GBM. In vitro and in vivo assays were used to explore the function of RSRP1 in MES GBM. RESULTS: Here, we identified that arginine/serine-rich protein 1 (RSRP1) promotes the MES phenotype by facilitating GBM cell invasion and apoptosis resistance. Proteomic, transcriptomic, and functional analyses confirmed that RSRP1 regulates AS in MES GBM through mediating spliceosome assembly. One RSRP1-regulated AS event resulted in skipping PARP6 exon 18 to form truncated, oncogenic PARP6-s. This isoform was unable to effectively suppress NF-κB. Cotreatment of cultured GBM cells and GBM tumor-bearing mice with spliceosome and NF-κB inhibitors exerted a synergistic effect on MES GBM growth. CONCLUSION: We identified a novel mechanism through which RSRP1-dependent splicing promotes the GBM MES phenotype. Targeting AS via RSRP1-related spliceosomal factors might constitute a promising treatment for GBM.

Distinct placental molecular processes associated with early-onset and late-onset preeclampsia.

Background: Patients with preeclampsia display a spectrum of onset time and severity of clinical presentation, yet the underlying molecular bases for the early-onset and late-onset clinical subtypes are not known. Although several transcriptome studies have been done on placentae from PE patients, only a small number of differentially expressed genes have been identified due to very small sample sizes and no distinguishing of clinical subtypes. Methods: We carried out RNA-seq on 65 high-quality placenta samples, including 33 from 30 patients and 32 from 30 control subjects, to search for dysregulated genes and the molecular network and pathways they are involved in. Results: We identified two functionally distinct sets of dysregulated genes in the two major subtypes: 2,977 differentially expressed genes in early-onset severe preeclampsia, which are enriched with metabolism-related pathways, notably transporter functions; and 375 differentially expressed genes in late-onset severe preeclampsia, which are enriched with immune-related pathways. We also identified some key transcription factors, which may drive the widespread gene dysregulation in both early-onset and late-onset patients. Conclusion: These results suggest that early-onset and late-onset severe preeclampsia have different molecular mechanisms, whereas the late-onset mild preeclampsia may have no placenta-specific causal factors. A few regulators may be the key drivers of the dysregulated molecular pathways.

Construction and Analysis of Survival-Associated Competing Endogenous RNA Network in Lung Adenocarcinoma.

Increasing evidence has shown that noncoding RNAs play significant roles in the initiation, progression, and metastasis of tumours via participating in competing endogenous RNA (ceRNA) networks. However, the survival-associated ceRNA in lung adenocarcinoma (LUAD) remains poorly understood. In this study, we aimed to investigate the regulatory mechanisms underlying ceRNA in LUAD to identify novel prognostic factors. mRNA, lncRNA, and miRNA sequencing data obtained from the GDC data portal were utilized to identify differentially expressed (DE) RNAs. Survival-related RNAs were recognized using univariate Kaplan-Meier survival analysis. We performed functional enrichment analysis of survival-related mRNAs using the clusterProfiler package of R and STRING. lncRNA-miRNA and miRNA-mRNA interactions were predicted based on miRcode, Starbase, and miRanda. Subsequently, the survival-associated ceRNA network was constructed for LUAD. Multivariate Cox regression analysis was used to identify prognostic factors. Finally, we acquired 15 DE miRNAs, 49 DE lncRNAs, and 843 DE mRNAs associated with significant overall survival. Functional enrichment analysis indicated that survival-related DE mRNAs were enriched in cell cycle. The survival-associated lncRNA-miRNA-mRNA ceRNA network was constructed using five miRNAs, 49 mRNAs, and 21 lncRNAs. Furthermore, seven hub RNAs (LINC01936, miR-20a-5p, miR-31-5p, TNS1, TGFBR2, SMAD7, and NEDD4L) were identified based on the ceRNA network. LINC01936 and miR-31-5p were found to be significant using the multifactorial Cox regression model. In conclusion, we successfully constructed a survival-related lncRNA-miRNA-mRNA ceRNA regulatory network in LUAD and identified seven hub RNAs, which provide novel insights into the regulatory molecular mechanisms associated with survival of LUAD, and identified two independent prognostic predictors for LUAD.

BAP1 deletion abrogates growth and metastasis of murine cutaneous melanoma.

Although germline mutations in BRCA-associated protein-1 (BAP1) predispose to cutaneous melanoma (CM), BAP1 is rarely mutated in primary CM outside the familial context. The role of BAP1 in the pathogenesis of CM remains obscure. Here, we discovered an unexpected role of BAP1 in suppressing CM growth and metastasis. BAP1 deletion by CRISPR-Cas9 system severely compromises colony-forming capability of murine CM cell line B16-F10 and human CM cell lines, SK-MEL-28 and A375. Furthermore, BAP1 loss abrogates tumor growth and lung metastasis in murine syngeneic tumor models. Deletion of BAP1 in B16-F10 cells leads to preferential downregulation of genes accompanied with increased H2A ubiquitination at lysine 119. Transcriptomic characterization of BAP1 deletion reveals multiple deregulated cellular functions including extracellular matrix-receptor interaction and MAPK signaling pathway which may contribute to BAP1's effect on metastasis and proliferation. Our findings indicate that BAP1 could be a potential therapeutic target for CM.

Preeclampsia-Associated lncRNA INHBA-AS1 Regulates the Proliferation, Invasion, and Migration of Placental Trophoblast Cells.

Preeclampsia is believed to be caused by impaired placentation with insufficient trophoblast invasion, leading to impaired uterine spiral artery remodeling and angiogenesis. However, the underlying molecular mechanism remains unknown. We recently carried out transcriptome profiling of placental long noncoding RNAs (lncRNAs) and identified 383 differentially expressed lncRNAs in early-onset severe preeclampsia. Here, we are reporting our identification of lncRNA INHBA-AS1 as a potential causal factor of preeclampsia and its downstream pathways that may be involved in placentation. We found that INHBA-AS1 was upregulated in patients and positively correlated with clinical severity. We systematically searched for potential INHBA-AS1-binding transcription factors and their targets in databases and found that the targets were enriched with differentially expressed genes in the placentae of patients. We further demonstrated that the lncRNA INHBA-AS1 inhibited the invasion and migration of trophoblast cells through restraining the transcription factor CENPB from binding to the promoter of TNF receptor-associated factor 1 (TRAF1). Therefore, we have identified the dysregulated pathway "INHBA-AS1-CENPB-TRAF1" as a contributor to the pathogenesis of preeclampsia through prohibiting the proliferation, invasion, and migration of trophoblasts during placentation.

Association of lncRNA SH3PXD2A-AS1 with preeclampsia and its function in invasion and migration of placental trophoblast cells.

Accumulating evidence suggests that the pathogenesis of preeclampsia involves poor placentation caused by insufficient trophoblast invasion and impaired uterine spiral artery remodeling, yet the underlying molecular mechanism remains unclear. We carried out transcriptome profiling on placentae from preeclamptic patients and normal subjects, and identified about four hundred long non-coding RNAs differentially expressed in placentae of patients with early-onset severe preeclampsia. Here, we report our identification of lncRNA SH3PXD2A-AS1 as a potential causal factor for this disease and its downstream pathways involved in placentation. We found that expression level of SH3PXD2A-AS1 in the placentae is positively correlated with clinical severity of the patients. We demonstrated that SH3PXD2A-AS1 inhibited invasion and migration through recruiting CCCTC-binding factor (CTCF) to the promoters of SH3PXD2A and CCR7 to inhibit their transcription. Therefore, we conclude that the upregulation of lncRNA SH3PXD2A-AS1 may contribute to the pathogenesis of preeclampsia through prohibiting trophoblast invasion during placentation.

Landscape of Dysregulated Placental RNA Editing Associated With Preeclampsia.

Dysregulated RNA editing is well documented in several diseases, such as cancer and neurodegenerative diseases. The extent to which RNA editing might be involved in diseases originated in the placenta remains unknown. Here, we have systematically profiled RNA editome on the placentae, 9 from patients with early-onset severe preeclampsia (EOSPE) and 32 from normal subjects, and a widespread RNA editing dysregulation in EOSPE has been identified. The mis-edited gene set is enriched with known preeclampsia-associated genes and differentially expressed genes in EOSPE. The RNA editing events at 2 microRNA binding sites in 3'-untranslated region of the LEP mRNA were generated, which could inhibit the microRNA-induced mRNA downregulation of LEP in placenta-derived cell line, consistent with the observation in the placentae of preeclampsia patients. These results demonstrate the association of dysregulated placental RNA editing with preeclampsia, and providing a resource for further study on the role of RNA editing in the pathogenesis of this disease.

Whole-Genome Promoter Profiling of Plasma DNA Exhibits Diagnostic Value for Placenta-Origin Pregnancy Complications.

Placenta-origin pregnancy complications, including preeclampsia (PE), gestational diabetes mellitus (GDM), fetal growth restriction (FGR), and macrosomia (MA) are common occurrences in pregnancy, resulting in significant morbidity and mortality for both mother and fetus. However, despite their frequency, there are no reliable methods for the early diagnosis of these complications. Since cfDNA is mainly derived from placental trophoblasts and maternal hematopoietic cells, it might have information for gene expression which can be used for disease prediction. Here, low coverage whole-genome sequencing on plasma DNA from 2,199 pregnancies is performed based on retrospective cohorts of 3,200 pregnant women. Read depth in the promoter regions is examined to define read-depth distribution patterns of promoters for pregnancy complications and controls. Using machine learning methods, classifiers for predicting pregnancy complications are developed. Using these classifiers, complications are successfully predicted with an accuracy of 80.3%, 78.9%, 72.1%, and 83.0% for MA, FGR, GDM, and PE, respectively. The findings suggest that promoter profiling of cfDNA may be used as a biological biomarker for predicting pregnancy complications at early gestational age.

Gene Selection for the Discrimination of Colorectal Cancer.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer worldwide. Cancer discrimination is a typical application of gene expression analysis using a microarray technique. However, microarray data suffer from the curse of dimensionality and usual imbalanced class distribution between the majority (tumor samples) and minority (normal samples) classes. Feature gene selection is necessary and important for cancer discrimination. OBJECTIVES: To select feature genes for the discrimination of CRC. METHODS: We improve the feature selection algorithm based on differential evolution, DEFSw by using RUSBoost classifier and weight accuracy instead of the common classifier and evaluation measure for selecting feature genes from imbalance data. We firstly extract differently expressed genes (DEGs) from the CRC dataset of the TCGA and then select the feature genes from the DEGs using the improved DEFSw algorithm. Finally, we validate the selected feature gene sets using independent datasets and retrieve the cancer related information for these genes based on text mining through the Coremine Medical online database. RESULTS: We select out 16 single-gene feature sets for colorectal cancer discrimination and 19 single-gene feature sets only for colon cancer discrimination. CONCLUSIONS: In summary, we find a series of high potential candidate biomarkers or signatures, which can discriminate either or both of colon cancer and rectal cancer with high sensitivity and specificity.

Classification of glioma based on prognostic alternative splicing.

BACKGROUND: Previously developed classifications of glioma have provided enormous advantages for the diagnosis and treatment of glioma. Although the role of alternative splicing (AS) in cancer, especially in glioma, has been validated, a comprehensive analysis of AS in glioma has not yet been conducted. In this study, we aimed at classifying glioma based on prognostic AS. METHODS: Using the TCGA glioblastoma (GBM) and low-grade glioma (LGG) datasets, we analyzed prognostic splicing events. Consensus clustering analysis was conducted to classified glioma samples and correlation analysis was conducted to characterize regulatory network of splicing factors and splicing events. RESULTS: We analyzed prognostic splicing events and proposed novel splicing classifications across pan-glioma samples (labeled pST1-7) and across GBM samples (labeled ST1-3). Distinct splicing profiles between GBM and LGG were observed, and the primary discriminator for the pan-glioma splicing classification was tumor grade. Subtype-specific splicing events were identified; one example is AS of zinc finger proteins, which is involved in glioma prognosis. Furthermore, correlation analysis of splicing factors and splicing events identified SNRPB and CELF2 as hub splicing factors that upregulated and downregulated oncogenic AS, respectively. CONCLUSION: A comprehensive analysis of AS in glioma was conducted in this study, shedding new light on glioma heterogeneity and providing new insights into glioma diagnosis and treatment.

An Integrated Approach for Identifying Molecular Subtypes in Human Colon Cancer Using Gene Expression Data.

Identifying molecular subtypes of colorectal cancer (CRC) may allow for more rational, patient-specific treatment. Various studies have identified molecular subtypes for CRC using gene expression data, but they are inconsistent and further research is necessary. From a methodological point of view, a progressive approach is needed to identify molecular subtypes in human colon cancer using gene expression data. We propose an approach to identify the molecular subtypes of colon cancer that integrates denoising by the Bayesian robust principal component analysis (BRPCA) algorithm, hierarchical clustering by the directed bubble hierarchical tree (DBHT) algorithm, and feature gene selection by an improved differential evolution based feature selection method (DEFSW) algorithm. In this approach, the normal samples being completely and exclusively clustered into one class is considered to be the standard of reasonable clustering subtypes, and the feature selection pays attention to imbalances of samples among subtypes. With this approach, we identified the molecular subtypes of colon cancer on the mRNA gene expression dataset of 153 colon cancer samples and 19 normal control samples of the Cancer Genome Atlas (TCGA) project. The colon cancer was clustered into 7 subtypes with 44 feature genes. Our approach could identify finer subtypes of colon cancer with fewer feature genes than the other two recent studies and exhibits a generic methodology that might be applied to identify the subtypes of other cancers.