One of the main concerns patients face during treatment of HCC is that no two HCC tumours are alike, and tumours can vary greatly in their characteristics and behavior. This difference can make it extremely difficult for both doctors and patients when it comes to deciding on the best possible treatment. A treatment that works well for one patient might not work for another, even in the same stage of the cancer. This is also one of the challenges when developing targeted therapies, as we as scientists do not understand the heterogeneity that exists.and the root

Fortunately, advancements in science are helping us better understand this complexity. One such technology is single-cell genomics, a remarkable scientific advancement that allows researchers to dive deep into the individual cells of the tumour rather than just looking at the average of all cells in a tumour. By investigating each cell on its own, scientists can now uncover the unique characteristics of the tumour. This level of detail gives us a clearer picture of what’s happening inside the tumour and why some cells might behave more aggressively while others remain stable.

This understanding is crucial for the development of precision medicine, which focuses on tailoring treatments to the specific needs of each patient. With insights from single-cell genomics, doctors and scientists can identify particular genetic alterations that drive tumour growth or contribute to treatment resistance. If specific, more aggressive cancer cells are identified, new therapies can be designed to target those cells directly, which may lead to more effective treatment options.
 

Hepatocyte Polyploid

Characterization of the genetic clonal composition of liver tumours, polyploid states and copy number architecture. 

Single cell genomics

 

We are studying patient HCC tumours mutation profile, epigenetic make up and gene expressionat the single-cell level. Our goal is to identify differences in these tumours and discover genes that may drive their growth. This research aims to subgroup patients into categories based on molecular and genetic features and the development of more precise therapies. 

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