ArticleBritish journal of cancer2016
Gene expression profiling identifies distinct molecular subgroups of leiomyosarcoma with clinical relevance.
Article in British journal of cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Predicting immunotherapy benefit in leiomyosarcoma through active chromatin cfDNA profiling.NPJ precision oncology · 2026Article
- MiR-221, miR-320a, miR133a, and miR-133b as potential biomarkers in leiomyosarcoma.Frontiers in oncology · 2025Article
- Molecular Heterogeneity in Leiomyosarcoma and Implications for Personalised Medicine.Current treatment options in oncology · 2024Review
- Metabolic targeting of cancer associated fibroblasts overcomes T-cell exclusion and chemoresistance in soft-tissue sarcomas.Nature communications · 2024Article
- Article
- MiR-130b modulates the invasive, migratory, and metastatic behavior of leiomyosarcoma.PloS one · 2023Article
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Authors and funding
6 authors.
Funding
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Abstract
backgroundSoft tissue sarcomas are heterogeneous and a major complication in their management is that the existing classification scheme is not definitive and is still evolving. Leiomyosarcomas, a major histologic category of soft tissue sarcomas, are malignant tumours displaying smooth muscle differentiation. Although defined as a single group, they exhibit a wide range of clinical behaviour. We aimed to carry out molecular classification to identify new molecular subgroups with clinical relevance.
methodsWe used gene expression profiling on 20 extra-uterine leiomyosarcomas and cross-study analyses for molecular classification of leiomyosarcomas. Clinical significance of the subgroupings was investigated.
resultsWe have identified two distinct molecular subgroups of leiomyosarcomas. One group was characterised by high expression of 26 genes that included many genes from the sub-classification gene cluster proposed by Nielsen et al. These sub-classification genes include genes that have importance structurally, as well as in cell signalling. Notably, we found a statistically significant association of the subgroupings with tumour grade. Further refinement led to a group of 15 genes that could recapitulate the tumour subgroupings in our data set and in a second independent sarcoma set. Remarkably, cross-study analyses suggested that these molecular subgroups could be found in four independent data sets, providing strong support for their existence.
conclusionsOur study strongly supported the existence of distinct leiomyosarcoma molecular subgroups, which have clinical association with tumour grade. Our findings will aid in advancing the classification of leiomyosarcomas and lead to more individualised and better management of the disease.
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