Can computers help estimate the quality of cancer cell lines?
In a study funded by Open Targets, Lucia Trastulla and Francesco Iorio discuss the limitations of immortal cancer cell lines (CCLs) to investigate cancer biology in vitro and review the latest computational methods to evaluate the suitability of each CCL as experimental model on a case-by-case basis.
Immortal CCLs are widely adopted models to study cancer biology in vitro and are often used in high-throughput screening for drug discovery. However, misidentification, misclassification, and heterogeneity, as well as usage out of the original in vivo tumour context, not always make CCLs appropriate to translate findings from the bench to the bedside.
Lucia Trastulla and Francesco Iorio at the HT Computational Biology Research Centre, in collaboration with colleagues from the Cancer Dependency Map Project at the Broad Institute, USA, provide an overview of the main limitations of using CCLs as in vitro surrogates for in vivo cancer features and describe how computational methods can be leveraged to identify the best and most representative CCLs depending on the type of primary tumor under investigation. Furthermore, the researchers discuss how machine-learning-based approaches may help reduce discrepancies arising from multi-omics analyses, transfer CCL-based findings to more complex model systems and develop approaches for the realization of personalised medicine.
The review is now published in Molecular Systems Biology.
DOI 10.15252/msb.202211017
Share:
You could also like:
-
Expanding the reach of the pangenome era with COSIGT
Researchers at Human Technopole have developed a novel pangenome-based pipeline that captures structural genomic diversity from low-coverage sequencing data at the population level. Their innovative work, including a step-by-step protocol, is published in Genome Biology.
-
UniMi and Human Technopole strengthen collaboration on research and education
Scientific research in the life sciences, materials science, biomedical and environmental fields, alongside joint education programmes and reciprocal access to laboratories and infrastructure, are at the heart of the six-year agreement through which the two institutions are strengthening their cooperation as key players in MIND – Milano Innovation District.
-
HT Management Committee – Call for Candidates
Human Technopole, a leading biomedical and life sciences research institute based in Milan, is seeking three highly qualified candidates to join its Management Committee, the governing body responsible for the operational leadership of the Foundation.
-
Beyond cancer dependency maps: the PRECISE vision
PRECISE (Predictive Relationships Explaining Cancer Genetic Interactions and Synthetic Essentiality) is a pan-European initiative that aims to move cancer research beyond cataloguing cancer vulnerabilities towards predicting them before they are experimentally tested. Human Technopole (HT) is among the founding partners of the consortium, with Francesco Iorio leading its scientific activities across the institute alongside other HT research groups. The consortium and its scientific vision are presented in a Nature Genetics commentary.
-
When less is more: optimising fluorescence microscopy with Micro𝕊plit
Researchers at Human Technopole have developed a novel machine learning-based method that transforms composite fluorescence microscopy images with overlapping signals into separate images revealing individual cellular structures. The tool is published in Nature Methods, with experimental models and training data openly available on GitHub.