OncoDB: an interactive online database for analysis of gene expression and viral infection in cancer

Tang, Gongyu; Cho, Minsu; Wang, Xiaowei

doi:10.1093/nar/gkab970

Cited by 137 publications

(122 citation statements)

References 20 publications

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“…A myriad of analytical options maximise the data's value in, for example, biomarker discovery and understanding drug resistance mechanisms. Other new cancer-related databases include CancerMIRNome ( 93 ) that covers miRNAs in cancer cells and offers particularly rich analytical options; CancerSCEM ( 94 ) that offers similarly diverse options for studying single cancer cell gene expression data; GPEdit ( 95 ) which links A-to-I RNA editing in cancer cells to pharmacogenomic responses and patient survival; and OncoDB ( 96 ), which focuses on the contributions of gene expression dysregulation and viral infection to cancer development and progression. This year also sees Update papers from two major general resources in drug design.…”

Section: New and Updated Databasesmentioning

confidence: 99%

The 2022Nucleic Acids Researchdatabase issue and the online molecular biology database collection

Rigden

Fernández

2021

Nucleic Acids Research

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The 2022 Nucleic Acids Research Database Issue contains 185 papers, including 87 papers reporting on new databases and 85 updates from resources previously published in the Issue. Thirteen additional manuscripts provide updates on databases most recently published elsewhere. Seven new databases focus specifically on COVID-19 and SARS-CoV-2, including SCoV2-MD, the first of the Issue's Breakthrough Articles. Major nucleic acid databases reporting updates include MODOMICS, JASPAR and miRTarBase. The AlphaFold Protein Structure Database, described in the second Breakthrough Article, is the stand-out in the protein section, where the Human Proteoform Atlas and GproteinDb are other notable new arrivals. Updates from DisProt, FuzDB and ELM comprehensively cover disordered proteins. Under the metabolism and signalling section Reactome, ConsensusPathDB, HMDB and CAZy are major returning resources. In microbial and viral genomes taxonomy and systematics are well covered by LPSN, TYGS and GTDB. Genomics resources include Ensembl, Ensembl Genomes and UCSC Genome Browser. Major returning pharmacology resource names include the IUPHAR/BPS guide and the Therapeutic Target Database. New plant databases include PlantGSAD for gene lists and qPTMplants for post-translational modifications. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). Our latest update to the NAR online Molecular Biology Database Collection brings the total number of entries to 1645. Following last year's major cleanup, we have updated 317 entries, listing 89 new resources and trimming 80 discontinued URLs. The current release is available at http://www.oxfordjournals.org/nar/database/c/.

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Section: New and Updated Databasesmentioning

confidence: 99%

The 2022Nucleic Acids Researchdatabase issue and the online molecular biology database collection

Rigden

Fernández

2021

Nucleic Acids Research

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“…Given that non-malignant cells that share the cancer's tissue of origin can be found in cancer biospecimens (for example, normal alveolar cells in a lung biopsy) we embedded a cancer signature scoring and cell differentiating module in scATOMIC. Using an established transcriptional program scoring method 11 , cancer-type-specific up and down-regulated programs 24 are evaluated in cells receiving an original annotation of a cancer type by scATOMIC (Methods, Fig. 1f).…”

Section: Results: An Overview Of Scatomicmentioning

confidence: 99%

“…Lists of genes differentially expressed between different cancer types and their matched normal tissues were obtained from OncoDB 24 . We selected DEGs with a log2 fold change greater than 1 or less than -1 and an adjusted P-value less than 0.01.…”

Section: Methodsmentioning

confidence: 99%

“…Since OncoDB is based on bulk RNA-seq, we further filtered the DEG list to only include those with reported expression values in the query scRNA-seq dataset. Upregulated gene programs and downregulated gene programs 24 were scored using the AddModuleScore function from Seurat 11,14 in each cell predicted as cancer by random forests. Ward.D2 hierarchical clustering was then performed on a Euclidean distance matrix of each cell’s upregulated and downregulated cancer programs.…”

Section: Methodsmentioning

confidence: 99%

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Pan-cancer classification of single cells in the tumour microenvironment

Nofech-Mozes

Soave

Awadalla

et al. 2022

Preprint

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Single-cell RNA sequencing reveals valuable insights into cellular heterogeneity within tumour microenvironments (TMEs), paving the way for a deep understanding of cellular mechanisms contributing to cancer. However, high heterogeneity among the same cancer types and low transcriptomic variation in immune cell subsets present challenges for accurate, high-resolution confirmation of cells' identities. Here we present scATOMIC; a modular annotation tool for malignant and non-malignant cells. We trained scATOMIC on >250,000 cancer, immune, and stromal cells defining a pan-cancer reference across 19 common cancer types and employed a novel hierarchical approach, outperforming current classification methods. We extensively confirmed scATOMIC's accuracy on 198 tumour biopsies and 54 blood samples encompassing >420,000 cancer and a variety of TME cells. Lastly, we demonstrate scATOMIC's practical significance to accurately subset breast cancers into clinically relevant subtypes and predict tumours' primary origin across metastatic cancers. Our approach represents a broadly applicable strategy to analyze multicellular cancer TMEs.

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“…At first, we utilized the OncoDB (http://oncodb.org/) server to retrieve the mRNA level expression pattern DCTN in LIHC and adjacent normal liver tissues [33]. The differential expression module of the server was utilized, and the evaluation parameters were kept at default values during the analysis.…”

Section: Methodsmentioning

confidence: 99%

A Multi-omics Study on the Oncogenic Roles and Clinical Significance of Dynactin Family Gene (DCTN1-6) Expression in Liver Hepatocellular Carcinoma

Ullah

Rashid

Islam

et al. 2022

Preprint

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In this study, we employed a comprehensive database mining approach to examine the possible oncogenic roles and clinical relevance of Dynactin family genes (DCTN1-6) in Liver Hepatocellular Carcinoma (LIHC). All the DCTNs were observed to be differentially expressed in LIHC tissues compared to the adjacent normal liver tissues. Most of the DCTNs were discovered to be aberrantly methylated (less methylated) and contain multiple somatic mutations (alteration frequency: 0.2-2.5%) in LIHC tissues. Overexpression of DCTNs was mostly associated with poor overall and relapse-free survival of LIHC patients. Alongside, all the DCTN genes were reported to be overexpressed across different demographic and clinical conditions, i.e., age, cancer stage, tumor grades, and metastatic stages of LIHC patients. DCTN expression was also associated with the infiltration levels of different immune cells, i.e., B cell, T cell, and macrophages in LIHC microenvironment. The co-expressed genes of DCTNs in the LIHC tissues were previously found to be involved in oncogenic processes in different cancer types and control crucial biological processes, i.e., nucleotide metabolism, RNA degradation, and chromosome organization. Later, the expression pattern of DCTNs was validated in two independent microarray datasets (i.e., GSE17856, GSE98383), which also supported our initial findings. All these findings suggest that DCTNs and their transcriptional and translational products are potential prognostic and therapeutic targets for LIHC diagnosis and treatment. This study will help further the development of DCTN-based diagnostic and therapeutic measures for LIHC and translate them into clinical implications.

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OncoDB: an interactive online database for analysis of gene expression and viral infection in cancer

Cited by 137 publications

References 20 publications

The 2022Nucleic Acids Researchdatabase issue and the online molecular biology database collection

The 2022Nucleic Acids Researchdatabase issue and the online molecular biology database collection

Pan-cancer classification of single cells in the tumour microenvironment

A Multi-omics Study on the Oncogenic Roles and Clinical Significance of Dynactin Family Gene (DCTN1-6) Expression in Liver Hepatocellular Carcinoma

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