Better outcomes in managing hepatocellular carcinoma

Sub-optimal selection of liver cancer patients for liver transplantation

Liver transplantation offers a curative-intent treatment for patients with HCC in early stages of the disease. This is a complex and costly procedure that is limited by the low availability of organs for transplantation, being offered only to patients likely to benefit from the procedure in the long term. Many criteria have been proposed over the years to identify these patients, but these are still sub-optimal: drop-out rates from transplant waiting list due to HCC progression are still significant (10-30%)1,2 and approximately 8-20% of patients that fall within the most widely used criteria (Milan) develop HCC recurrence following the procedure 3,4. On the other hand, some patient selection criteria are quite restrictive, excluding patients that could benefit from liver transplantation. While inclusive criteria are associated with increased costs and risks related to a second surgical intervention due to cancer recurrence, exclusive criteria imply the denial of a curative treatment to a patient that would benefit from it5,6. HepatoPredict is a new in vitro diagnostics test that provides solid prognostic information for HCC patients.

HepatoPredict uses tumour biomarkers

Most criteria for the selection of HCC patients for liver transplantation use information from image diagnosis (e.g.: number of nodules, nodule diameter, and/or volume) and blood tests (e.g.: AFP levels). HepatoPredict captures the biology of the tumor through biomarkers that are, then, reflected in a four gene expression signature that can predict tumor recurrence after liver transplantation. Additionally, HepatoPredict combines biomarkers with image diagnosis information using machine learning, outperforming existing criteria, providing higher sensitive, precise, and specific prognostic information. 

How does HepatoPredict work?

HepatoPredict is a gene expression signature that is measured directly in the tumour tissue (needle biopsy, surgical explant); a machine learning algorithm integrates the molecular information with routinely collected tumour properties (number, size). HepatoPredict is offered as a laboratory kit that can be tested in the local pathology laboratory based on standard FFPE prepared samples. 

HepatoPredict works at two different levels, identifying patients with good prognosis that will benefit from liver transplantation with very high or high confidence. At very high confidence HepatoPredict includes less HCC patients for liver transplantation but with high certainty (very low recurrence rates). At high confidence HepatoPredict identifies more patients for liver transplantation with similar recurrence rates as currently used clinical criteria 7

Scientific Evidence

Scientific Publication

Pinto-Marques H, Cardoso J, Silva S, Neto JL, Gonçalves-Reis M, Proença D, Mesquita M, Manso A, Carapeta S, Sobral M, Figueiredo A, Rodrigues C, Milheiro A, Carvalho A, Perdigoto R, Barroso E, Pereira Leal JB (2022) A gene expression signature to select hepatocellular carcinoma patients for liver transplantation. Annals of Surgery.

Gonçalves-Reis M, Proença D, Frazão L, Neto JL, Silva S, Pinto-Marques H, Pereira Leal JB, Cardoso J. (2024) Analytical validation of HepatoPredict kit to assess hepatocellular carcinoma prognosis prior to a liver transplant. Practical Laboratory Medicine. In Press.

Conference Presentations

ILTS 2023

Cardoso, J., Proença, D., Caetano Oliveira, R., Frazão, L.P., Andrade, R., Gonçalves-Reis, M., Neto, J.L., Pereira-Leal, J.B., Tralhão, J.G. (2023) Testing HepatoPredict kit performance in liver transplantation prognosis for hepatocellular carcinoma when facing intra- and inter-tumoral heterogeneity [ePoster]. ILTS Annual Congress, Rotterdam, Netherlands (May 3-6, 2023).

ILTS 2022

Cardoso, J., Pinto Marques, H., Mesquita, M., Manso, A., Carapeta, S., Sobral, M., Silva, S., Rodrigues, c., Carvalho, A., Milheiro, A., Perdigoto, R., Barroso, B., Pereira-Leal, J. (2022) New criteria in liver transplantation for hepatocellular carcinoma: a combined molecular and clinical predictor of survival. [Oral presentation]. Transplantation. https://ilts.org/education/abstracts

EASL 2021

Cardoso, J., Pinto Marques, H., Mesquita, M., Manso, A., Carapeta, S., Sobral, M., Silva, S., Rodrigues, c., Carvalho, A., Milheiro, A., Perdigoto, R., Barroso, B., Pereira-Leal, J. (2021) A new tool for predicting survival in liver transplantation for hepatocellular carcinoma combining molecular and clinical variables [Poster Presentation]. Journal of Hepatology, 75(2), S475.  https://doi.org/10.1016/S0168-8278(21)01843-2 

Clinical Trials

HepatoPredict is being validated in an interventional clinical study at Centro Hospital de Lisboa Central (NCT04499833). In this trial, patients with HCC in cirrhotic liver and outside “Milan criteria” are suggested to be submitted to HepatoPredict test. If the test predicts a good prognosis after liver transplantation, the patient will be proposed for the procedure using marginal livers or livers from patients with Familial Amyloid Polyneuropathy, and followed up for 5 years after transplantation.

Clinical Validation

We are expanding HepatoPredict clinical validation in a series of collaborative studies.

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Order HepatoPredict

If you wish to order HepatoPedict or request more information, please contact one of our distributors worldwide.

References

1 Mehta et al (2022) A novel waitlist dropout score for hepatocelular carcinoma – identifying a threshold that predicts worse post-transplant survival. Journal of Hepatology. doi: 10.1016/j.jhep.2020.10.033

2 Sokolich et al (2020) HCC Liver Transplantation Wait List Dropout Rates Before and After the Mandated 6-Month Wait Time. The American Surgeon. doi: 10.1177/0003134820942165

3 Hoof et al (2022) External Validation of the RETREAT Score for Prediction of Hepatocellular Carcinoma Recurrence after Liver Transplantation. Cancers. doi: 10.3390/cancers14030630

4 Stras et al (2022) Recurrence of Hepatocellular Carcinoma After Liver Transplantation: Risk Factors and Predictive Models. Annals of Transplantation. doi: 10.12659/AOT.934924

5 Pelizzaro et al (2021) Management of Hepatocellular Carcinoma Recurrence after Liver Transplantation. Cancers. doi: https://doi.org/10.3390/cancers13194882 

6 Herreras et al (2019) Milan-out Criteria and Worse Intention-to-Treat Outcome Post-liver Transplantation. Transplantation. doi: 10.1097/TXD.0000000000000934 

7 Pinto-Marques and Cardoso et al (2022) A gene expression signature to select hepatocellular carcinoma patients for liver transplantation. Annals of Surgery. doi: 10.1097/SLA.0000000000005637