Key Biomarkers for Prediction Response to Melanoma Therapy identified

Using advanced computing technology scientists at the Wistar Institute (Philadelphia) have been able to provide evidence of novel, reliable biomarkers that better predict therapy response of patients undergoing immune checkpoint inhibitor (ICI) treatment. ICI therapy, a type of treatment for melanoma (skin cancer) blocks proteins on tumour or immune cells that prevent the immune system from killing cancer cells. While this treatment has shown some clinical success in patients with advanced stages of melanoma, its efficacy depends on reliable predictors of a patient’s response to the therapy. Currently, the only FDA approved biomarker for ICI melanoma treatment is the tumour mutation burden assay, but the mechanisms linking it to ICI remain unclear.

Noam Auslander, assistant professor in the Molecular & Cellular Oncogenesis Program of Wistar’s Ellen and Ronald Caplan Cancer Centre and Andrew Patterson, graduate student in the Auslander lab, have now identified novel predictors of ICI therapy for melanoma. In particular, mutations in the processes of leukocyte and T-cell proliferation regulation show potential as biomarkers with reliable and stable prediction of ICI therapy response across multiple different datasets of melanoma patients.

“This work aims to identify better and more biologically interpretable genomic predictors for immunotherapy responses,” notes Auslander. “We need better biomarkers to help select patients that are more likely to respond to ICI therapy and understand what factors can help to enhance responses and increase those numbers.” 

Using publicly available de-identified clinical data, researchers investigated why some melanoma patients responded to ICI therapy and others did not. Patterson, first author on the paper, detailed that their research process involved training machine learning models on a dataset to predict whether a patient responds to ICI therapy, then confirming that the model was able to continually predict response or resistance to this treatment over multiple other datasets.  

The team found that leukocyte and T-cell proliferation regulation processes have some mutated genes that contribute to ICI treatment response and resistance. This knowledge could be used to identify targets to enhance responses or mitigate resistance in patients with melanoma.

“We were able to better predict if a patient would respond to ICI therapy than the current clinical standard method as well as extract biological information that could help in further understanding the mechanisms behind ICI therapy response and resistance,” Patterson explained.

The paper was published in Nature communications

More information online