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System-Wide Pollution of Biomedical Data: Consequence of the Search for Hub Genes of Hepatocellular Carcinoma Without Spatiotemporal Consideration

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A Correction to this article was published on 05 May 2021

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Abstract

Biomedical institutions rely on data evaluation and are turning into data factories. Big-data storage centers, supercomputing systems, and increased algorithmic efficiency allow us to analyze the ever-increasing amount of data generated every day in biomedical research centers. In network science, the principal intrinsic problem is how to integrate the data and information from different experiments on genes or proteins. Data curation is an essential process in annotating new functional data to known genes or proteins, undertaken by a biobank curator, which is then reflected in the calculated networks. We provide an example of how protein–protein networks today have space-time limits. The next step is the integration of data and information from different biobanks. Omics data and networks are essential parts of this step but also have flawed protocols and errors. Consider data from patients with cancer: from biopsy procedures to experimental tests, to archiving methods and computational algorithms, these are continuously handled so require critical and continuous “updates” to obtain reproducible, reliable, and correct results. We show, as a second example, how all this distorts studies in cellular hepatocellular carcinoma. It is not unlikely that these flawed data have been polluting biobanks for some time before stringent conditions for the veracity of data were implemented in Big data. Therefore, all this could contribute to errors in future medical decisions.

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Acknowledgements

The authors are very thankful to Les Foster for proofreading the manuscript. We would also like to thank the referees and the editor for constructive comments.

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  1. Ankush Sharma

    Present address: Institute of Cancer Research, Institute of Clinical medicine, University of Oslo, Oslo, Norway

Authors and Affiliations

  1. Department of Biosciences, University of Oslo, Oslo, Norway

    Ankush Sharma

  2. Department of Informatics, University of Oslo, Oslo, Norway

    Ankush Sharma

  3. Medical Informatics, AOU-Vanvitelli, Università della Campania, Naples, Italy

    Giovanni Colonna

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  1. Ankush Sharma
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  2. Giovanni Colonna
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Correspondence to Ankush Sharma.

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Ankush Sharma and Giovanni Colonna have no conflicts of interest that are directly relevant to the content of this article.

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The original online version of this article was revised due to a retrospective Open Access cancellation.

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Sharma, A., Colonna, G. System-Wide Pollution of Biomedical Data: Consequence of the Search for Hub Genes of Hepatocellular Carcinoma Without Spatiotemporal Consideration. Mol Diagn Ther 25, 9–27 (2021). https://doi.org/10.1007/s40291-020-00505-3

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