Mapping knowledge landscapes and emerging trends of the biomarkers in melanoma: a bibliometric analysis from 2004 to 2022.

Background: Melanoma is a skin tumor with a high mortality rate, and early diagnosis and effective treatment are the key to reduce its mortality rate. Therefore, more and more attention has been paid for biomarker identification for early diagnosis, prognosis prediction and prognosis evaluation of melanoma. However, there is still a lack of a report that comprehensively and objectively evaluates the research status of melanoma biomarkers. Therefore, this study aims to intuitively analyze the research status and trend of melanoma biomarkers through the methods of bibliometrics and knowledge graph. Objective: This study uses bibliometrics to analyze research in biomarkers in melanoma, summarize the field's history and current status of research, and predict future research directions. Method: Articles and Reviews related to melanoma biomarkers were retrieved by using Web of Science core collection subject search. Bibliometric analysis was performed in Excel 365, CiteSpace, VOSviewer and Bibliometrix (R-Tool of R-Studio). Result: A total of 5584 documents from 2004 to 2022 were included in the bibliometric analysis. The results show that the number of publications and the frequency of citations in this field are increasing year by year, and the frequency of citations has increased rapidly after 2018. The United States is the most productive and influential country in this field, with the largest number of publications and institutions with high citation frequency. Caroline Robert, F. Stephen Hodi, Suzanne L. Topalian and others are authoritative authors in this field, and The New England Journal of Medicine, Journal of Clinical Oncology and Clinical Cancer Research are the most authoritative journals in this field. Biomarkers related to the diagnosis, treatment and prognosis of melanoma are hot topics and cutting-edge hotspots in this field. Conclusion: For the first time, this study used the bibliometric method to visualize the research in the field of melanoma biomarkers, revealing the trends and frontiers of melanoma biomarkers research, which provides a useful reference for scholars to find key research issues and partners.

Gene expression variability across cells and species shapes the relationship between renal resident macrophages and infiltrated macrophages.

BACKGROUND: Two main subclasses of macrophages are found in almost all solid tissues: embryo-derived resident tissue macrophages and bone marrow-derived infiltrated macrophages. These macrophage subtypes show transcriptional and functional divergence, and the programs that have shaped the evolution of renal macrophages and related signaling pathways remain poorly understood. To clarify these processes, we performed data analysis based on single-cell transcriptional profiling of renal tissue-resident and infiltrated macrophages in human, mouse and rat. RESULTS: In this study, we (i) characterized the transcriptional divergence among species and (ii) illustrated variability in expression among cells of each subtype and (iii) compared the gene regulation network and (iv) ligand-receptor pairs in human and mouse. Using single-cell transcriptomics, we mapped the promoter architecture during homeostasis. CONCLUSIONS: Transcriptionally divergent genes, such as the differentially TF-encoding genes expressed in resident and infiltrated macrophages across the three species, vary among cells and include distinct promoter structures. The gene regulatory network in infiltrated macrophages shows comparatively better species-wide consistency than resident macrophages. The conserved transcriptional gene regulatory network in infiltrated macrophages among species is uniquely enriched in pathways related to kinases, and TFs associated with largely conserved regulons among species are uniquely enriched in kinase-related pathways.

SMPD1 expression profile and mutation landscape help decipher genotype-phenotype association and precision diagnosis for acid sphingomyelinase deficiency.

BACKGROUND: Acid sphingomyelinase deficiency (ASMD) disorder, also known as Niemann-Pick disease (NPD) is a rare genetic disease caused by mutations in SMPD1 gene, which encodes sphingomyelin phosphodiesterase (ASM). Except for liver and spleen enlargement and lung disease, two subtypes (Type A and B) of NDP have different onset times, survival times, ASM activities, and neurological abnormalities. To comprehensively explore NPD's genotype-phenotype association and pathophysiological characteristics, we collected 144 NPD cases with strict quality control through literature mining. RESULTS: The difference in ASM activity can differentiate NPD type A from other subtypes, with the ratio of ASM activity to the reference values being lower in type A (threshold 0.045 (4.45%)). Severe variations, such as deletion and insertion, can cause complete loss of ASM function, leading to type A, whereas relatively mild missense mutations generally result in type B. Among reported mutations, the p.Arg3AlafsX76 mutation is highly prevalent in the Chinese population, and the p.R608del mutation is common in Mediterranean countries. The expression profiles of SMPD1 from GTEx and single-cell RNA sequencing data of multiple fetal tissues showed that high expressions of SMPD1 can be observed in the liver, spleen, and brain tissues of adults and hepatoblasts, hematopoietic stem cells, STC2_TLX1-positive cells, mesothelial cells of the spleen, vascular endothelial cells of the cerebellum and the cerebrum of fetuses, indicating that SMPD1 dysfunction is highly likely to have a significant effect on the function of those cell types during development and the clinicians need pay attention to these organs or tissues as well during diagnosis. In addition, we also predicted 21 new pathogenic mutations in the SMPD1 gene that potentially cause the NPD, signifying that more rare cases will be detected with those mutations in SMPD1. Finally, we also analysed the function of the NPD type A cells following the extracellular milieu. CONCLUSIONS: Our study is the first to elucidate the effects of SMPD1 mutation on cell types and at the tissue level, which provides new insights into the genotype-phenotype association and can help in the precise diagnosis of NPD.

Prognostic value of PNN in prostate cancer and its correlation with therapeutic significance.

Prostate cancer (PCa) is the most common malignancy. New biomarkers are in demand to facilitate the management. The role of the pinin protein (encoded by PNN gene) in PCa has not been thoroughly explored yet. Using The Cancer Genome Atlas (TCGA-PCa) dataset validated with Gene Expression Omnibus (GEO) and protein expression data retrieved from the Human Protein Atlas, the prognostic and diagnostic values of PNN were studied. Highly co-expressed genes with PNN (HCEG) were constructed for pathway enrichment analysis and drug prediction. A prognostic signature based on methylation status using HCEG was constructed. Gene set enrichment analysis (GSEA) and the TISIDB database were utilised to analyse the associations between PNN and tumour-infiltrating immune cells. The upregulated PNN expression in PCa at both transcription and protein levels suggests its potential as an independent prognostic factor of PCa. Analyses of the PNN's co-expression network indicated that PNN plays a role in RNA splicing and spliceosomes. The prognostic methylation signature demonstrated good performance for progression-free survival. Finally, our results showed that the PNN gene was involved in splicing-related pathways in PCa and identified as a potential biomarker for PCa.

Transcriptome sequencing of hepatocellular carcinoma uncovers multiple types of dysregulated ncRNAs.

Transcriptome profiling of hepatocellular carcinoma (HCC) by next-generation sequencing (NGS) technology has been broadly performed by previous studies, which facilitate our understanding of the molecular mechanisms of HCC formation, progression, and metastasis. However, few studies jointly analyze multiple types of noncoding RNAs (ncRNAs), including long noncoding RNAs (lncRNAs), circular RNAs (circRNAs), and micro-RNAs (miRNAs), and further uncover their implications in HCC. In this study, we observed that the circRNA cZRANB1 and lncRNA DUXAP10 were not only significantly upregulated in tumor tissues, but also higher expressed in blood exosomes of HCC as compared with healthy donors. From the analysis of subclass-associated dysregulated ncRNAs, we observed that DLX6-AS1, an antisense RNA of DLX6, and the sense gene DLX6 were highly expressed in S1, a subclass with a more invasive/disseminative phenotype. High correlation between DLX6-AS1 and DLX6 suggested that DLX6-AS1 may function via promoting the transcription of DLX6. Integrative analysis uncovers circRNA-miRNA, lncRNA-miRNA, and competing endogenous RNA networks (ceRNAs). Specifically, cZRANB1, LINC00501, CTD-2008L17.2, and SLC7A11-AS1 may function as ceRNAs that regulate mRNAs by competing the shared miRNAs. Further prognostic analysis demonstrated that the dysregulated ncRNAs had the potential to predict HCC patients' overall survival. In summary, we identified some novel circRNAs and miRNAs, and dysregulated ncRNAs that could participate in HCC tumorigenesis and progression by inducing transcription of their neighboring genes, increasing their derived miRNAs, or acting as miRNA sponges. Moreover, our systematic analysis provides not only rich data resources for related researchers, but also new insights into the molecular basis of how different ncRNAs coordinately or antagonistically participate in the pathogenesis process of diseases.

ToPP: Tumor online prognostic analysis platform for prognostic feature selection and clinical patient subgroup selection.

Patients with cancer with different molecular characterization and subtypes result in different response to anticancer therapeutics and survival. To identify features that are associated with prognosis is essential to precision medicine by providing clues for target identification, drug discovery. Here, we developed a tumor online prognostic analysis platform (ToPP) which integrated eight multi-omics features and clinical data from 68 cancer projects. It provides multiple approaches for customized prognostic studies, including 1) Prognostic analysis based on multi-omics features and clinical characteristics; 2) Automatic construction of prognostic model; 3) Pancancer prognostic analysis in multi-omics data; 4) Explore the impact of different levels of feature combinations on patient prognosis; 5) More sophisticated prognostic analysis according to regulatory network. ToPP provides a comprehensive source and easy-to-use interface for tumor prognosis research, with one-stop service of multi-omics, subtyping, and online prognostic modeling. The web server is freely available at http://www.biostatistics.online/topp/index.php.

Computational identification of new potential transcriptional partners of ERRα in breast cancer cells: specific partners for specific targets.

Estrogen related receptors are orphan members of the nuclear receptor superfamily acting as transcription factors (TFs). In contrast to classical nuclear receptors, the activities of the ERRs are not controlled by a natural ligand. Regulation of their activities thus relies on availability of transcriptional co-regulators. In this paper, we focus on ERRα, whose involvement in cancer progression has been broadly demonstrated. We propose a new approach to identify potential co-activators, starting from previously identified ERRα-activated genes in a breast cancer (BC) cell line. Considering mRNA gene expression from two sets of human BC cells as major endpoint, we used sparse partial least squares modeling to uncover new transcriptional regulators associated with ERRα. Among them, DDX21, MYBBP1A, NFKB1, and SETD7 are functionally relevant in MDA-MB-231 cells, specifically activating the expression of subsets of ERRα-activated genes. We studied SET7 in more details and showed its co-localization with ERRα and its ERRα-dependent transcriptional and phenotypic effects. Our results thus demonstrate the ability of a modeling approach to identify new transcriptional partners from gene expression. Finally, experimental results show that ERRα cooperates with distinct co-regulators to control the expression of distinct sets of target genes, thus reinforcing the combinatorial specificity of transcription.

Whole genome and exome sequencing identify NDUFV2 mutations as a new cause of progressive cavitating leukoencephalopathy.

BACKGROUND: Progressive cavitating leukoencephalopathy (PCL) is thought to result from mutations in nuclear genes affecting mitochondrial function and energy metabolism. To date, mutations in two subunits of complex I, NDUFS1 and NDUFV1, have been reported to be related to PCL. METHODS: Patients underwent clinical examinations, brain MRI, skin biopsy and muscle biopsy. Whole-genome or whole-exome sequencing was performed on the index patients from two unrelated families with PCL. The effects of the mutations were examined through complementation of the NDUFV2 mutation by cDNA expression. RESULTS: The common clinical features of the patients in this study were recurring episodes of acute or subacute developmental regression that appeared in the first years of life, followed by gradual remissions and prolonged periods of stability. MRI showed leukoencephalopathy with multiple cavities. Three novel NDUFV2 missense mutations were identified in these families. Complex I deficiency was confirmed in affected individuals' fibroblasts and a muscle biopsy. Functional and structural analyses revealed that these mutations affect the structural stability and function of the NDUFV2 protein, indicating that defective NDUFV2 function is responsible for the phenotypes in these individuals. CONCLUSIONS: Here, we report the clinical presentations, neuroimaging and molecular and functional analyses of novel mutations in NDUFV2 in two sibling pairs of two Chinese families presenting with PCL. We hereby expand the knowledge on the clinical phenotypes associated with mutations in NDUFV2 and the genotypes causative for PCL.

A Novel Risk-Score Model With Eight MiRNA Signatures for Overall Survival of Patients With Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer with heterogeneous outcomes and diverse therapeutic responses. To classify patients into different groups and facilitate the suitable therapeutic strategy, we first selected eight microRNA (miRNA) signatures in The Cancer Genome Atlas (TCGA)-LUAD cohort based on multi-strategy combination, including differential expression analysis, regulatory relationship, univariate survival analysis, importance clustering, and multivariate combinations analysis. Using the eight miRNA signatures, we further built novel risk scores based on the predefined cutoff and beta coefficients and divided the patients into high-risk and low-risk groups with significantly different overall survival time (p-value < 2 e-16). The risk-score model was confirmed with an independent dataset (p-value = 4.71 e-4). We also observed that the risk scores of early-stage patients were significantly lower than those of late-stage patients. Moreover, our model can also provide new insights into the current clinical staging system and can be regarded as an alternative system for patient stratification. This model unified the variable value as the beta coefficient facilitating the integration of biomarkers obtained from different omics data.

A Novel Germline Compound Heterozygous Mutation of BRCA2 Gene Associated With Familial Peripheral Neuroblastic Tumors in Two Siblings.

OBJECTIVES: To investigate the genetic variants that are responsible for peripheral neuroblastic tumors (PNTs) oncogenesis in one family case. MATERIALS AND METHODS: One family was recruited, including the healthy parents, sister affected by neuroblastoma (NB), and brother who suffered from ganglioneuroma (GN). Whole-genome sequencing (WGS) of germline DNA from all the family members and RNA-seq of tumor RNA from the siblings were performed. Mutants were validated by Sanger sequencing and co-IP was performed to assess the impact of the mutant on chemosensitivity in the SH-SY5Y cell line. RESULTS: A novel compound heterozygous mutation of BRCA2 was locked as the cause of carcinogenesis. One allele was BRCA2-S871X (stop-gain) from the siblings' mother, the other was BRCA2-N372H (missense) from their father. This novel compound heterozygous mutations of the BRCA2 gene associated with PNTs by disordering DNA damage and response (DDR) signal pathway. Moreover, chemosensitivity was reduced in the NB cell line due to the BRCA2-N372H mutant. CONCLUSION: In summary, these results revealed a novel germline compound heterozygous mutation of the BRCA2 gene associated with familial PNTs.

Proteomics provides individualized options of precision medicine for patients with gastric cancer.

While precision medicine driven by genome sequencing has revolutionized cancer care, such as lung cancer, its impact on gastric cancer (GC) has been minimal. GC patients are routinely treated with chemotherapy, but only a fraction of them receive the clinical benefit. There is an urgent need to develop biomarkers or algorithms to select chemo-sensitive patients or apply targeted therapy. Here, we carried out retrospective analyses of 1,020 formalin-fixed, paraffin-embedded GC surgical resection samples from 5 hospitals and developed a mass spectrometry-based workflow for proteomic subtyping of GC. We identified two proteomic subtypes: the chemo-sensitive group (CSG) and the chemo-insensitive group (CIG) in the discovery set. The 5-year overall survival of CSG was significantly improved in patients who had received adjuvant chemotherapy after surgery compared with those who received surgery only (64.2% vs. 49.6%; Cox P-value=0.002), whereas no such improvement was observed in CIG (50.0% vs. 58.6%; Cox P-value=0.495). We validated these results in an independent validation set. Further, differential proteome analysis uncovered 9 FDA-approved drugs that may be applicable for targeted therapy of GC. A prospective study is warranted to test these findings for future GC patient care.

Biochemical features and mutations of key proteins in SARS-CoV-2 and their impacts on RNA therapeutics.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic. Three viral proteins, the spike protein (S) for attachment of virus to host cells, 3-chymotrypsin-like cysteine protease (Mpro) for digestion of viral polyproteins to functional proteins, and RNA-dependent-RNA-polymerase (RdRp) for RNA synthesis are the most critical proteins for virus infection and replication, rendering them the most important drug targets for both antibody and chemical drugs. Due to its low-fidelity polymerase, the virus is subject to frequent mutations. To date, the sequence data from tens of thousands of virus isolates have revealed hundreds of mutations. Although most mutations have a minimum consequence, a small number of non-synonymous mutations may alter the virulence and antigenicity of the mutants. To evaluate the effects of viral mutations on drug safety and efficacy, we reviewed the biochemical features of the three main proteins and their potentials as drug targets, and analyzed the mutation profiles and their impacts on RNA therapeutics. We believe that monitoring and predicting mutation-introduced protein conformational changes in the three key viral proteins and evaluating their binding affinities and enzymatic activities with the U.S. Food and Drug Administration (FDA) regulated drugs by using computational modeling and machine learning processes can provide valuable information for the consideration of drug efficacy and drug safety for drug developers and drug reviewers. Finally, we propose an interactive database for drug developers and reviewers to use in evaluating the safety and efficacy of U.S. FDA regulated drugs with regard to viral mutations.

Perturbation of Specific Signaling Pathways Is Involved in Initiation of Mouse Liver Fibrosis.

BACKGROUND AND AIMS: To identify the regulatory role of protein phosphatase 2A (PP2A) in the development of liver disease, we generated a mouse model with hepatocyte-specific deletion of Ppp2r1a gene (encoding PP2A Aα subunit). APPROACH AND RESULTS: Homozygote (HO) mice and matched wild-type littermates were investigated at 3, 6, 9, 12, 15, and 18 months of age. Pathological examination showed that PP2A Aα deficiency in hepatocytes resulted in progressive liver fibrosis phenotype from 9 months of age. No hepatocyte death was observed in HO mice. However, perturbation of pathways including epidermal growth factor receptor 1 (EGFR1), amino acid metabolism, and translation factors as well as leptin and adiponectin led to pronounced hepatic fibrosis. In vitro studies demonstrated the involvement of specific B subunit complexes in the regulation of EGFR1 signaling pathway and cross talk between defected hepatocytes and stimulation of interstitial hyperplasia. It is noteworthy that HO mice failed to develop hepatocellular carcinoma for as long as 22 months of age. We further demonstrate that PP2A Aß-containing holoenzymes played a critical role in preventing hepatocyte apoptosis and antagonizing tumorigenesis through specific pathways on Aα loss. Furthermore, PP2A Aα and Aß were functionally distinct, and the Aß isoform failed to substitute for Aα in the development of inflammation and liver fibrosis. CONCLUSIONS: These observations identify pathways that contribute to the pathogenesis of liver fibrosis and provide putative therapeutic targets for its treatment.

Comprehensive Characterization of Circular RNAs in Neuroblastoma Cell Lines.

Neuroblastoma (NB) is a rare type of cancer but frequently occurred in children. However, it is still unclear whether circular RNAs (circRNAs) play key roles in NB tumorigenesis or progression. In this study, we identified 39,022 circRNAs across the 39 neuroblastoma and 2 normal cell lines. With the gene and circRNA expression data, we classified the NB cell lines, identified and characterized the functional circRNAs in the 3 NB classes. Specifically, 29 circRNAs were found to be dysregulated in the NB classes. Notably, 7 circRNAs located within MYCN-amplified regions were upregulated in cell lines with the high activities of MYC targets and MYCN amplification, and were highly correlated with expression of their parental gene, NBAS. Subsequently, we constructed ceRNA networks for the functional circRNAs. Specifically, hsa_circ_0005379 was identified as a critical regulator in the ceRNA networks because of targeting 13 genes, which formed a complex competing endogenous RNA (ceRNA) network. Moreover, hsa_circ_0002343, which was connected with few genes, might regulate the PI3K/Akt/mTOR signaling via RAC1. Furthermore, 3 genes, including NOTCH2, SERPINH1, and LAMC1, involved in epithelial mesenchymal transition (EMT) were observed to connect with hsa_circ_0001361, suggesting that this circRNA was closely associated with EMT. Consequently, 7 genes, such as DAD1, PPIA, NOTCH2, PGK1, BUB1, EIF2S1, and TCF7L2, were found to be closely associated with both event-free survival (EFS) and overall survival (OS). In conclusion, the present study identified functional circRNAs and predicted their functionality in neuroblastoma cell lines, which not only improved the understanding of circRNAs in neuroblastoma, but also provided the evidences for the related researchers.

Genotype-phenotype correlations of Berardinelli-Seip congenital lipodystrophy and novel candidate genes prediction.

BACKGROUND: Berardinelli-Seip congenital lipodystrophy (BSCL) is a heterogeneous autosomal recessive disorder characterized by an almost total lack of adipose tissue in the body. Mutations in the AGPAT2, BSCL2, CAV1 and PTRF genes define I-IV subtype of BSLC respectively and clinical data indicate that new causative genes remain to be discovered. Here, we retrieved 341 cases from 60 BSCL-related studies worldwide and aimed to explore genotype-phenotype correlations based on mutations of AGPAT2 and BSCL2 genes from 251 cases. We also inferred new candidate genes for BSCL through protein-protein interaction and phenotype-similarity. RESULTS: Analysis results show that BSCL type II with earlier age of onset of diabetes mellitus, higher risk to suffer from premature death and mental retardation, is a more severe disorder than BSCL type I, but BSCL type I patients are more likely to have bone cysts. In BSCL type I, females are at higher risk of developing diabetes mellitus and acanthosis nigricans than males, while in BSCL type II, males suffer from diabetes mellitus earlier than females. In addition, some significant correlations among BSCL-related phenotypes were identified. New candidate genes prediction through protein-protein interaction and phenotype-similarity was conducted and we found that CAV3, EBP, SNAP29, HK1, CHRM3, OBSL1 and DNAJC13 genes could be the pathogenic factors for BSCL. Particularly, CAV3 and EBP could be high-priority candidate genes contributing to pathogenesis of BSCL. CONCLUSIONS: Our study largely enhances the current knowledge of phenotypic and genotypic heterogeneity of BSCL and promotes the more comprehensive understanding of pathogenic mechanisms for BSCL.

UHRF2 promotes intestinal tumorigenesis through stabilization of TCF4 mediated Wnt/ß-catenin signaling.

Intestinal tumors mainly originate from transformed crypt stem cells supported by Wnt signaling, which functions through downstream critical factors enriched in the intestinal stem/progenitor compartment. Here, we show Uhrf2 is predominantly expressed in intestinal crypts and adenomas in mice and is transcriptionally regulated by Wnt signaling. Upregulated UHRF2 correlates with poor prognosis in colorectal cancer patients. Although loss of Uhrf2 did not affect intestinal homeostasis and regeneration, tumor initiation and progression were inhibited, leading to a markedly prolonged life span in Uhrf2 null mice on an ApcMin background. Uhrf2 deficiency also strongly reduced primary tumor organoid formation suggesting impairment of tumor stem cells. Moreover, ablation of Uhrf2 suppressed tumor cell proliferation through downregulation of the Wnt/ß-catenin pathway. Mechanistically, Uhrf2 directly interacts with and sumoylates Tcf4, a critical intranuclear effector of the Wnt pathway. Uhrf2 mediated SUMOylation stabilized Tcf4 and further sustained hyperactive Wnt signaling. Together, we demonstrate that Wnt-induced Uhrf2 expression promotes tumorigenesis through modulation of the stability of Tcf4 for maintaining oncogenic Wnt/ß-catenin signaling. This is a new reciprocal feedforward regulation between Uhrf2 and Wnt signaling in tumor initiation and progression.

Co-occurrence and Mutual Exclusivity Analysis of DNA Methylation Reveals Distinct Subtypes in Multiple Cancers.

Co-occurrence and mutual exclusivity (COME) of DNA methylation refer to two or more genes that tend to be positively or negatively correlated in DNA methylation among different samples. Although COME of gene mutations in pan-cancer have been well explored, little is known about the COME of DNA methylation in pan-cancer. Here, we systematically explored the COME of DNA methylation profile in diverse human cancer. A total of 5,128,332 COME events were identified in 14 main cancers types in The Cancer Genome Atlas (TCGA). We also identified functional epigenetic modules of the zinc finger gene family in six cancer types by integrating the gene expression and DNA methylation data and the frequently occurred COME network. Interestingly, most of the genes in those functional epigenetic modules are epigenetically repressed. Strikingly, those frequently occurred COME events could be used to classify the patients into several subtypes with significant different clinical outcomes in six cancers as well as pan-cancer (p-value ≤ = 0.05). Moreover, we observed significant associations between different COME subtypes and clinical features (e.g., age, gender, histological type, neoplasm histologic grade, and pathologic stage) in distinct cancers. Taken together, we identified millions of COME events of DNA methylation in pan-cancer and detected functional epigenetic COME events that could separate tumor patients into different subtypes, which may benefit the diagnosis and prognosis of pan-cancer.

DNMIVD: DNA methylation interactive visualization database.

Aberrant DNA methylation plays an important role in cancer progression. However, no resource has been available that comprehensively provides DNA methylation-based diagnostic and prognostic models, expression-methylation quantitative trait loci (emQTL), pathway activity-methylation quantitative trait loci (pathway-meQTL), differentially variable and differentially methylated CpGs, and survival analysis, as well as functional epigenetic modules for different cancers. These provide valuable information for researchers to explore DNA methylation profiles from different aspects in cancer. To this end, we constructed a user-friendly database named DNA Methylation Interactive Visualization Database (DNMIVD), which comprehensively provides the following important resources: (i) diagnostic and prognostic models based on DNA methylation for multiple cancer types of The Cancer Genome Atlas (TCGA); (ii) meQTL, emQTL and pathway-meQTL for diverse cancers; (iii) Functional Epigenetic Modules (FEM) constructed from Protein-Protein Interactions (PPI) and Co-Occurrence and Mutual Exclusive (COME) network by integrating DNA methylation and gene expression data of TCGA cancers; (iv) differentially variable and differentially methylated CpGs and differentially methylated genes as well as related enhancer information; (v) correlations between methylation of gene promoter and corresponding gene expression and (vi) patient survival-associated CpGs and genes with different endpoints. DNMIVD is freely available at http://www.unimd.org/dnmivd/. We believe that DNMIVD can facilitate research of diverse cancers.

Comprehensive Identification and Characterization of Human Secretome Based on Integrative Proteomic and Transcriptomic Data.

Secreted proteins (SPs) play important roles in diverse important biological processes; however, a comprehensive and high-quality list of human SPs is still lacking. Here we identified 6,943 high-confidence human SPs (3,522 of them are novel) based on 330,427 human proteins derived from databases of UniProt, Ensembl, AceView, and RefSeq. Notably, 6,267 of 6,943 (90.3%) SPs have the supporting evidences from a large amount of mass spectrometry (MS) and RNA-seq data. We found that the SPs were broadly expressed in diverse tissues as well as human body fluid, and a significant portion of them exhibited tissue-specific expression. Moreover, 14 cancer-specific SPs that their expression levels were significantly associated with the patients' survival of eight different tumors were identified, which could be potential prognostic biomarkers. Strikingly, 89.21% of 6,943 SPs (2,927 novel SPs) contain known protein domains. Those novel SPs we mainly enriched with the known domains regarding immunity, such as Immunoglobulin V-set and C1-set domain. Specifically, we constructed a user-friendly and freely accessible database, SPRomeDB (www.unimd.org/SPRomeDB), to catalog those SPs. Our comprehensive SP identification and characterization gain insights into human secretome and provide valuable resource for future researches.