BIONDA: a free database for a fast information on published biomarkers

Turewicz, Michael; Frericks-Zipper, Anika; Stepath, Markus; Schork, Karin; Ramesh, Sharan Nurani; Marcus, Katrin; Eisenacher, Martin

doi:10.1093/bioadv/vbab015

Cited by 10 publications

(6 citation statements)

References 13 publications

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“…The proteins were further mapped with the biological pathways and diseases-gene association networking hubs to narrow the list. The knowledge bases used for the curation of markers are eDGAR [ 29 ], PubPular [ 30 ], DisGeNET [ 31 ], BIONDA [ 32 ], and Harmonizome [ 33 ]. In addition, ProteomeXchange [ 34 ], PRIDE [ 34 ], OmicsDi [ 35 ], and Pubmed [ 36 ] were also used to mine the proteomics studies related to Meningioma.…”

Section: Methodsmentioning

confidence: 99%

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors

Halder,

Biswas,

Chauhan

et al. 2023

Clin Proteom

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Background Meningiomas are the most prevalent primary brain tumors. Due to their increasing burden on healthcare, meningiomas have become a pivot of translational research globally. Despite many studies in the field of discovery proteomics, the identification of grade-specific markers for meningioma is still a paradox and requires thorough investigation. The potential of the reported markers in different studies needs further verification in large and independent sample cohorts to identify the best set of markers with a better clinical perspective. Methods A total of 53 fresh frozen tumor tissue and 51 serum samples were acquired from meningioma patients respectively along with healthy controls, to validate the prospect of reported differentially expressed proteins and claimed markers of Meningioma mined from numerous manuscripts and knowledgebases. A small subset of Glioma/Glioblastoma samples were also included to investigate inter-tumor segregation. Furthermore, a simple Machine Learning (ML) based analysis was performed to evaluate the classification accuracy of the list of proteins. Results A list of 15 proteins from tissue and 12 proteins from serum were found to be the best segregator using a feature selection-based machine learning strategy with an accuracy of around 80% in predicting low grade (WHO grade I) and high grade (WHO grade II and WHO grade III) meningiomas. In addition, the discriminant analysis could also unveil the complexity of meningioma grading from a segregation pattern, which leads to the understanding of transition phases between the grades. Conclusions The identified list of validated markers could play an instrumental role in the classification of meningioma as well as provide novel clinical perspectives in regard to prognosis and therapeutic targets.

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Section: Methodsmentioning

confidence: 99%

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors

Halder,

Biswas,

Chauhan

et al. 2023

Clin Proteom

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“…This is reflected in a persistent growth in the number of related scientific publications (journal articles and patents) in the recent decades (Figure A). A number of compendiums such as GOBIOM, GLOBOCAN 2020, OncoMX, , MarkerDB, , LiqBioer, , BIONDA, , BiomarkerBase, The Human Gene Mutation Database, Cancer Biomarkers database, CBD: a biomarker database for colorectal cancer, ONS Biomarker Database, and others have collected hundreds of proposed biomarker candidates. However, even though a large number of biomarker candidates have been proposed, very few have progressed to the stage of clinical validation along their clinical trial pathway. − …”

Section: Biomarker Research Growthmentioning

confidence: 99%

Biomarkers for Early Cancer Detection: A Landscape View of Recent Advancements, Spotlighting Pancreatic and Liver Cancers

Tenchov,

Sapra,

Sasso

et al. 2024

ACS Pharmacol. Transl. Sci.

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Cancer is one of the leading causes of death worldwide. Early cancer detection is critical because it can significantly improve treatment outcomes, thus saving lives, reducing suffering, and lessening psychological and economic burdens. Cancer biomarkers provide varied information about cancer, from early detection of malignancy to decisions on treatment and subsequent monitoring. A large variety of molecular, histologic, radiographic, or physiological entities or features are among the common types of cancer biomarkers. Sizeable recent methodological progress and insights have promoted significant developments in the field of early cancer detection biomarkers. Here we provide an overview of recent advances in the knowledge related to biomolecules and cellular entities used for early cancer detection. We examine data from the CAS Content Collection, the largest human-curated collection of published scientific information, as well as from the biomarker datasets at Excelra, and analyze the publication landscape of recent research. We also discuss the evolution of key concepts and cancer biomarkers development pipelines, with a particular focus on pancreatic and liver cancers, which are known to be remarkably difficult to detect early and to have particularly high morbidity and mortality. The objective of the paper is to provide a broad overview of the evolving landscape of current knowledge on cancer biomarkers and to outline challenges and evaluate growth opportunities, in order to further efforts in solving the problems that remain. The merit of this review stems from the extensive, wide-ranging coverage of the most up-to-date scientific information, allowing unique, unmatched breadth of landscape analysis and in-depth insights.

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“…This is reflected in a persistent growth in the number of related scientific publications (journal articles and patents) in the recent decades (Figure 3A). A number of compendiums such as GOBIOM 84 , GLOBOCAN 2020 85 , OncoMX 86, 87 , MarkerDB 88, 89 , LiqBioer 90,91 , BIONDA 92,93 , BiomarkerBase 94 , The Human Gene Mutation Database 95 , Cancer Biomarkers database 96 , CBD: a biomarker database for colorectal cancer 97 , ONS Biomarker Database 98 , and others 88 have collected hundreds of proposed biomarker candidates. However, even though a large number of biomarker candidates have been proposed 99 , very few have progressed to the stage of clinical validation along their clinical trial pathway.…”

Section: Biomarker Research Growthmentioning

confidence: 99%

Biomarkers for early cancer detection: A landscape view of recent advancements, spotlighting pancreatic and liver cancers

Tenchov,

Sapra,

Sasso

et al. 2024

Preprint

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Cancer is one of the leading causes of death worldwide. Early cancer detection is critical because it can significantly improve treatment outcome thus saving lives, reducing suffering, and lessening psychological and economic burdens. Cancer biomarkers provide varied information about cancer, from early detection of malignancy to decisions on treatment and subsequent monitoring. A large variety of molecular, histologic, radiographic, or physiological entities or features are amongst the common types of cancer biomarkers. Sizeable recent methodological progress and insights have promoted significant development in the field of early cancer detection biomarkers. Here we provide an overview of recent advancement in the knowledge related to biomolecules and cellular entities used for early cancer detection. We examine data from the CAS Content Collection, the largest human-curated collection of published scientiﬁc information, as well as from the biomarker datasets at Excelra, and analyze the publication landscape of recent research. We also discuss the evolution of key concepts, cancer biomarkers development pipelines, with a particular focus on pancreatic and liver cancers, known as remarkably difficult to detect early, with particularly high morbidity and mortality. The objective of the paper is to provide a broad overview of the evolving landscape of current knowledge on cancer biomarkers, to outline challenges and evaluate growth opportunities, in order to further efforts in solving the problems that remain. The merit of the article stems from the extensive, wide-ranging coverage of the most up-to-date scientific information, allowing unique, unmatched breadth of landscape analysis and in-depth insights.

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BIONDA: a free database for a fast information on published biomarkers

Cited by 10 publications

References 13 publications

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors

A large-scale targeted proteomics of serum and tissue shows the utility of classifying high grade and low grade meningioma tumors

Biomarkers for Early Cancer Detection: A Landscape View of Recent Advancements, Spotlighting Pancreatic and Liver Cancers

Biomarkers for early cancer detection: A landscape view of recent advancements, spotlighting pancreatic and liver cancers

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