The first consensus guidelines for scoring the histopathological growth patterns (HGPs) of liver metastases were established in 2017. Since then, numerous studies have applied these guidelines, have further substantiated the potential clinical value of the HGPs in patients with liver metastases from various tumour types and are starting to shed light on the biology of the distinct HGPs. In the present guidelines, we give an overview of these studies, discuss novel strategies for predicting the HGPs of liver metastases, such as deep-learning algorithms for whole-slide histopathology images and medical imaging, and highlight liver metastasis animal models that exhibit features of the different HGPs. Based on a pooled analysis of large cohorts of patients with liver-metastatic colorectal cancer, we propose a new cut-off to categorise patients according to the HGPs. An up-to-date standard method for HGP assessment within liver metastases is also presented with the aim of incorporating HGPs into the decision-making processes surrounding the treatment of patients with liver-metastatic cancer. Finally, we propose hypotheses on the cellular and molecular mechanisms that drive the biology of the different HGPs, opening some exciting preclinical and clinical research perspectives.
Bibliographical noteFunding Information:
The work by CD, PV, GF, VD, LD and DL on breast cancer liver metastasis is supported by the Foundation against Cancer (Stichting tegen Kanker, Grant C/2020/1441). PV and LD are supported by the Koning Boudewijnstichting. GF is a recipient of a post-doctoral mandate sponsored by the KOOR from the University Hospitals Leuven. PS is a William Dawson Scholar of McGill University and acknowledges funding from the Canadian Institutes of Health Research (CIHR: MOP-136907; PJT-175088). HN is supported by the Swedish Research Council, Wallenberg Foundations/Knut and Alice Wallenberg Foundation, Region Västerbotten, the Swedish Cancer Society, the Cancer Research Foundation in Northern Sweden and Umeå University. MG is supported by The Swedish Research Foundation (2018–02023) and The Swedish Association for Medical Research. QZ is supported by Engineering and Physical Sciences Research Council (project EP/N034708/1). DGM is supported by the Fondo de Investigaciones Sanitarias of the Spanish Government, Fondo Europeo de Desarrollo Regional (FEDER) “Una manera de hacer Europa”/“A way of shaping Europe” (grant PI18/1140) and by AGAUR Department of Health of the Generalitat de Catalunya (grant SGR771). WRJ is supported by grant U01 CA238444–02 from the National Cancer Institute.
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