Role of Machine Learning in Liquid Biopsy of Brain Tumours

Zanib Javed, Saqib Kamran Bakhshi, Saad Akhtar Khan, Muhammad Shahzad Shamim

Research output: Contribution to journalArticlepeer-review


Liquid biopsy has multiple benefits and is used extensively in other fields of oncology, but its role in neuro-oncology has been limited so far. Multiple tumour-derived materials like circulating tumour cells (CTCs), tumour-educated platelets (TEPs), cell-free DNA (cfDNA), circulating tumour DNA (ctDNA), and miRNA are studied in CSF, blood (plasma, serum) or urine. Large and complex amounts of data from liquid biopsy can be simplified by machine learning using various algorithms. By using this technique, we can diagnose brain tumours and differentiate low versus high-grade glioma and true progression from pseudo-progression. The potential of liquid biopsy in brain tumours has not been extensively studied, but it has a bright future in the coming years. Here, we present a literature review on the role of machine learning in liquid biopsy of brain tumours.

Original languageEnglish
Pages (from-to)1194-1196
Number of pages3
JournalJournal of the Pakistan Medical Association
Issue number6
Publication statusPublished - Jun 2024


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