{"id":22577,"date":"2024-11-07T12:21:40","date_gmt":"2024-11-07T12:21:40","guid":{"rendered":"https:\/\/clinlabint.com\/?p=22577"},"modified":"2024-11-07T12:21:40","modified_gmt":"2024-11-07T12:21:40","slug":"novel-drug-screening-method-enhances-personalised-cancer-treatment-approach","status":"publish","type":"post","link":"https:\/\/clinlabint.com\/novel-drug-screening-method-enhances-personalised-cancer-treatment-approach\/","title":{"rendered":"Novel drug screening method enhances personalised cancer treatment approach"},"content":{"rendered":"
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Novel drug screening method enhances personalised cancer treatment approach<\/h1>\/ in E-News<\/a> <\/span><\/span><\/header>\n<\/div><\/section>
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Finnish researchers have developed a high-throughput screening pipeline that enables simultaneous analysis of multiple drug responses in primary tumour samples at single-cell resolution, offering new possibilities for personalised cancer therapy.<\/strong><\/p>\n

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Background to the breakthrough<\/h4>\n

The challenge of matching the right drug or combination of drugs to individual cancer patients has long been a significant hurdle in oncology. Traditional experimental approaches using cell line models have often fallen short in accurately predicting patient responses to therapy, as they fail to capture the complex biological characteristics of actual tumours.<\/p>\n

Researchers at the University of Oulu have addressed this limitation by developing an innovative pipeline that employs live-cell barcoding technology. The method enables the concurrent screening of 96 different drug treatments at single-cell resolution, providing unprecedented insight into how individual cancer cells respond to various therapeutic agents.<\/p>\n

The study, published in Nature Chemical Biology on 31 October 2024 [1], focused on high-grade serous ovarian cancer (HGSOC), examining the responses to 45 distinct drugs across 13 different mechanism-of-action classes. By incorporating advanced single-cell RNA-sequencing techniques, the researchers were able to map gene regulatory dynamics that drive both drug resistance and sensitivity in real-time, working directly with patient tumour samples.<\/p>\n<\/div><\/section>
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Human ovarian cancer cells stained with fluorescent markers. (Subodh Sharma and Alice Dini.)<\/em><\/p>\n<\/div><\/section>
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Implications for personalised medicine<\/h4>\n

Associate Professor Daniela Ungureanu from the University of Oulu emphasises the significance of this development: \u201cOur ability to directly study drug responses at single-cell levels in primary tumour samples from patients in a multiplexed way represents a huge step toward personalized medicine. This approach enables us to explore how individual cancers behave in response to different therapies, which could help overcome the unpredictability of using cell lines or animal models.\u201d\u00a0 The establishment of a comprehensive drug response database using primary samples represents a significant advancement in the field. This resource has the potential to enhance treatment decision-making by enabling clinicians to identify specific gene regulatory responses that influence treatment outcomes.<\/p>\n

Future applications<\/h4>\n

The research team anticipates that this new methodology will have particular value in drug repurposing efforts and in improving patient selection strategies. Dr Alice Dini, the study\u2019s first author, notes: \u201cOur findings offer a promising framework for enhancing drug repurposing and improving patient selection strategies, especially for those battling cancers with poor prognosis and limited treatment options.\u201d<\/p>\n

The research project forms part of the multidisciplinary<\/h4>\n

Fibrobesity research programme at the University of Oulu and involved collaboration with researchers from the University of Helsinki and the Institute for Molecular Medicine Finland (FIMM). This cross-institutional approach has helped to ensure the robust development and validation of the new methodology.<\/p>\n

Clinical potential<\/h4>\n

The pipeline\u2019s ability to analyse drug responses in primary patient samples offers several advantages over traditional cell line models. By working directly with patient-derived tissue, researchers can better account for the heterogeneity of tumours and their microenvironment, potentially leading to more accurate predictions of treatment outcomes.<\/p>\n

The development of this comprehensive drug response database is expected to significantly enhance the ability to match patients with optimal therapies. By analysing data from diverse patient tumours, clinicians will be better equipped to identify specific gene regulatory responses that influence treatment outcomes, enabling a more precise, evidence-based approach to cancer care.<\/p>\n

The method\u2019s capacity to screen multiple drug treatments simultaneously also presents opportunities for cost-effective drug development and repurposing strategies, particularly beneficial for cancers with limited treatment options or poor prognosis.<\/p>\n

Reference:<\/strong><\/em>
\n1. Dini, A., et al. (2024). A multiplex single-cell RNA-Seq pharmacotranscriptomics pipeline for drug discovery. Nature Chemical Biology. https:\/\/doi.org\/10.1038\/s41589-024-01761-8<\/a><\/em><\/p>\n<\/div><\/section>
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The research is part of the multidisciplinary Fibrobesity research program at the University of Oulu, Finland. In the picture is Daniela Ungureanu\u2019s research team: top row from left to right, Daniela Ungureanu and Emilia Piki; bottom row, Alice Dini, Subodh Sharma, Juuli Raivola, and Harlan Barker. (Photo: University of Oulu \/ Mikko T\u00f6rm\u00e4nen)<\/em><\/p>\n<\/div><\/section>
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