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How can bioinformatics identify new cancer drug targets?

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Cancer is a complex and heterogeneous disease that involves the abnormal growth and spread of cells. Finding effective treatments for cancer requires understanding the molecular mechanisms that drive its development and progression. Bioinformatics is a field that applies computational tools and methods to analyze large-scale biological data, such as DNA, RNA, proteins, and metabolites. Bioinformatics can help identify new cancer drug targets by revealing the genetic and molecular alterations that underlie different types of cancers, as well as the interactions and pathways that modulate their effects. In this article, you will learn how bioinformatics can use various approaches and techniques to discover and validate new cancer drug targets.

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Antoine B.

Driving Business Success: Integrating Strategy and Efficiency for Sustainable Growth

1 Genomic analysis

One of the main applications of bioinformatics in cancer research is genomic analysis, which involves the sequencing and comparison of the DNA of normal and cancer cells. Genomic analysis can reveal the mutations, copy number variations, and structural rearrangements that affect the genes and chromosomes of cancer cells. These genomic alterations can lead to the activation of oncogenes, which promote cell growth and survival, or the inactivation of tumor suppressor genes, which prevent cell proliferation and induce apoptosis. By identifying the genes that are frequently mutated or altered in different cancers, bioinformatics can help prioritize potential drug targets that can block or restore their functions.

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2 Transcriptomic analysis

Another application of bioinformatics in cancer research is transcriptomic analysis, which involves the measurement and comparison of the RNA expression levels of normal and cancer cells. Transcriptomic analysis can reveal the changes in gene expression that reflect the cellular state and response of cancer cells. These changes can be influenced by various factors, such as the tumor microenvironment, the immune system, the signaling pathways, and the epigenetic modifications. By identifying the genes that are differentially expressed or spliced in different cancers, bioinformatics can help identify potential drug targets that can modulate their transcription or translation.

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Julien Willard, MD MPH

Life Sciences Strategist | Advisor on RWD, Clinical R&D | Former diplomat, economist at World Bank | Board Member
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The current model of clinical drug development in oncology faces a major challenge: a very high exclusion rate for patients in early phases and a high attrition rate of drugs in phase 3. Selection of compounds for phase 3 trials is traditionally based on preclinical evidence of bioactivity, unmet medical needs, clinical trial results in one or a limited number of diseases, and limited (often DNA-based) assessment of drug-gene variant matching. Must know — the WINTHER prospective clinical trial demonstrated that integrating transcriptomics as a predictive biomarker for personalized therapies can yield a 35% increase in the proportion of patients eligible for targeted therapeutic options.

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3 Proteomic analysis

A third application of bioinformatics in cancer research is proteomic analysis, which involves the detection and quantification of the proteins and their modifications in normal and cancer cells. Proteomic analysis can reveal the changes in protein abundance, activity, interaction, and localization that affect the cellular functions and processes of cancer cells. These changes can be mediated by various mechanisms, such as the post-translational modifications, the protein degradation, the protein-protein interactions, and the protein-ligand interactions. By identifying the proteins that are aberrantly expressed or modified in different cancers, bioinformatics can help identify potential drug targets that can alter their activity or interaction.

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Antoine B.

Driving Business Success: Integrating Strategy and Efficiency for Sustainable Growth
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Bioinformatics helps in understanding protein functions and their interactions in cancer pathways. This is crucial for developing drugs that can specifically modulate these proteins.

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4 Metabolomic analysis

A fourth application of bioinformatics in cancer research is metabolomic analysis, which involves the characterization and comparison of the metabolites and their pathways in normal and cancer cells. Metabolomic analysis can reveal the changes in metabolic fluxes and networks that affect the energy production and consumption of cancer cells. These changes can be driven by various factors, such as the oxygen availability, the nutrient supply, the hormonal signals, and the enzyme expression. By identifying the metabolites and pathways that are dysregulated or altered in different cancers, bioinformatics can help identify potential drug targets that can influence their synthesis or degradation.

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Antoine B.

Driving Business Success: Integrating Strategy and Efficiency for Sustainable Growth
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Changes in metabolic pathways are often associated with cancer and the TME. Bioinformatics tools are analyzing these pathways, identifying key enzymes and metabolites that could serve as drug targets. Where cancer trials have failed, metabolomics can also help to identify better subjects sub-groups.

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5 Network analysis

A fifth application of bioinformatics in cancer research is network analysis, which involves the integration and visualization of the biological data from different levels and sources. Network analysis can reveal the complex and dynamic interactions and relationships among the genes, proteins, metabolites, and other molecules that regulate the cellular functions and processes of cancer cells. These interactions and relationships can form networks that represent the biological systems and modules that govern the cancer phenotypes and behaviors. By identifying the key nodes and edges that are essential or influential in different networks, bioinformatics can help identify potential drug targets that can perturb or disrupt their connectivity or functionality.

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Antoine B.

Driving Business Success: Integrating Strategy and Efficiency for Sustainable Growth
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Bioinformatics is effectively bridging the gap between the massive biological data obtained through multi omics and the practical development of effective, targeted cancer therapies. It accelerates the discovery, screening, and optimization of new drug compounds, ultimately leading to more personalized and effective cancer treatments.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Julien Willard, MD MPH

Life Sciences Strategist | Advisor on RWD, Clinical R&D | Former diplomat, economist at World Bank | Board Member
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There are a few techniques in computational drug discovery (in silico) that any biotechnologist should be aware of: — Network-based analysis — Data mining, machine learning — Ligand-based target prediction — Reverse / inverse docking — Biospectra analysis — Target-based in silico prediction and genomic-based analysis (covered in this article above) As biological systems are complex, combining these techniques is often used. For instance: Integration of ML and DM approaches with network-based analysis helps understand biological networks and identify potential gene or pathway targets for combinatorial therapy. Genomics combined with molecular docking simulations is an approach used in infectious disease research and is another example.

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How can bioinformatics identify new cancer drug targets?

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1 Genomic analysis

2 Transcriptomic analysis

3 Proteomic analysis

4 Metabolomic analysis

5 Network analysis

6 Here’s what else to consider

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