Integrated and personalized approach in the treatment of hepatocarcinoma

During EASL 2024, the rise of AI in radiology and liver pathology; and of multisystem / multiscale integration in HCC patient care was discussed.

Multidisciplinary Tumor Boards in HCC today and tomorrow

Multidisciplinary Tumor Boards (MTBs) are a key component in the management of hepatocellular carcinoma (HCC), bringing together specialists from different disciplines to discuss and plan the best course of treatment for each patient. Currently, MTBs include oncologists, surgeons, radiologists, hepatologists, pathologists and other specialists, who collaborate to analyze clinical data and diagnostic images, formulate precise diagnoses and recommend customized treatments.

In the current context, MTBs facilitate a comprehensive and integrated patient assessment, considering not only tumor characteristics, but also the patient's general health status, comorbidities and personal preferences. This multidisciplinary approach is crucial for managing complex cases of HCC, where the choice of treatment may vary considerably depending on the specific clinical condition.

In the future, MTBs will further evolve through the integration of advanced technologies. The use of AI, genomics, liquid biopsies and advanced imaging will provide MTBs with powerful tools for even more precise and personalized assessment. MTBs' meetings will be supported by multimodal dashboards that aggregate clinical, genetic and imaging data, offering a holistic and detailed view of the patient. In addition, AI will be able to assist in data analysis and outcome prediction, enhancing the MTBs' ability to make robust evidence-based recommendations.

Predicting response to treatments

One of the main topics has been the use of artificial intelligence (AI) to predict response to cancer treatments. Predicting the future is one of the most difficult challenges and we will probably never be able to do it with absolute certainty. However, looking at the current state of AI, there is a lot of research trying to combine existing biomarkers, blood analysis and other information to create new predictive models. We can hope that AI can extract information that we cannot see today.

For example, radiomics promises to reveal details that are most often missed today. Many studies are trying to stratify patients by analyzing the texture and heterogeneity of images at the granular level using radiomics and deep radiomics. These studies show the feasibility of building consistent models to predict post-surgical recurrence. Although the current performance is not excellent, the concept is valid. The future will depend on our ability to validate these results.

Recent studies have shown how AI can classify patients according to their risk of responding to treatments, thus enabling a more targeted and personalized approach.

The impact of liquid biopsies

Liquid biopsies represent a promising alternative to traditional biopsies. These analyses, performed on blood samples, make it possible to monitor genetic mutations and tumor evolution in real time. This non-invasive method allows early detection of disease progression and early adaptation of therapeutic strategies. Preliminary results indicate that the presence or absence of mutations in circulating DNA may correlate with treatment response, offering an additional monitoring tool.

The French genomics project for resistant tumors

In France, the national genomics programme for systemic treatment-resistant cancers is a pioneering example of how genomics can be integrated into clinical practice. Through whole genome sequencing and RNA analysis, specific therapeutic targets are identified for each patient, allowing personalized treatments. The first results of this approach show promising responses in highly pre-treated patients, demonstrating the potential of precision medicine.

The role of surgery remains an important pillar in cancer treatment

Despite advances in medical therapies, surgery will remain a key pillar in cancer treatment. However, an evolution towards increasingly robot-assisted, and in the future, fully robot-assisted surgeries is expected. This transition will improve the precision of surgery, reducing risks and recovery time for patients. Robotic surgery will be integrated with other emerging technologies, such as organ regeneration on normothermic perfusion machines.

New tools for patient monitoring

Monitoring of cancer patients will benefit greatly from wearable technologies and connected devices. These tools will make it possible to constantly monitor the health status of patients, detecting early signs of drug toxicity and other side effects. Analysis of the collected data will allow further personalisation of treatments and improve patients' quality of life.

Take-away messages: The HCC therapy of the future

  1. Artificial Intelligence: crucial for predicting response to cancer treatments and classifying patients according to risk.
  2. Liquid biopsies: offer a non-invasive method to monitor tumor progression and adapt therapies in real time.
  3. Clinical genomics: enables personalized treatments through genome sequencing and RNA analysis.
  4. Robotic surgery: will improve the precision of operations and reduce patients' recovery times.
  5. Wearable devices: facilitate continuous monitoring of patients' health by detecting early signs of drug toxicity.
  6. Multidisciplinary Tumor Boards: they will be increasingly integrated with advanced technologies, improving the precision and personalisation of treatments.

The management of hepatocarcinoma will therefore be increasingly patient-centred, thanks to technologies that will allow more precise diagnoses and personalised treatments, thus improving clinical outcomes and patients' quality of life.

  1. Beaufrère A, Nault JC, Vogel A. The future of multidisciplinary tumour board in HCC. EASL 2024. Thursday, 6 Jun, 15:00 - 16:00 CEST