It’s not just a lack of funding that makes LMS a tough cancer to treat effectively.

LMS is in effect a headline descriptor covering a whole range of LMS cancer sub-types, which we need to define more precisely in order to be able to treat the disease.  Leiomyosarcomas are heterogeneous cancers between patients and even intratumorally within an individual patient.

Currently all LMS is treated the same way, despite its biological heterogeneity, and the fact that no two patients are the same.

This means also for example that a novel treatment could be deemed ineffective as it may appear to have only minor benefit in LMS overall, but in fact could be extremely effective in treating an individual patient with a specific sub-type which may not have yet been clearly defined.

Precision-based medicine is therefore the goal in treating LMS effectively. To do that, we need:

  • Identification of relevant biomarkers which indicate sub-type and responsiveness to targeted treatment (ICR has already shown that the benefit of pazopanib, a targeted form of cancer treatment known as a TKI, is 3x more effective in treating sarcoma in a subgroup of patients defined through its KARSARC prediction method – a result which should soon make pazopanib used as standard of care for that subgroup).

  • Improved understanding of molecular classification of LMS (ICR’s 2023 paper in Nature Communications has already begun this process with the definition of 3 distinct LMS proteomic subtypes).

  • Better laboratory models which faithfully replicate LMS in human disease which can be used in drug screening for patients and for evaluating ex vivo tumour responses. ICR already has one of the largest collections of LMS avatars globally.

  • Use of AI and data science to analyse The Royal Marsden’s catalogue of records and pathology samples. This will include use of radiomics (i.e. the extraction of information from medical images using advanced feature analysis).