Gene-Based Prognostic Signatures and Biomarkers
Chairs: Jorge Marrero, MD (USA) and Peter Schirmacher, MD (Germany)
Gene-Signatures Predicting Survival
Augusto Villanueva, MD, PhD (Spain)
Recent genomics technology has enabled simultaneous, comprehensive analysis of wide variety of biomolecules, including coding- and non-coding-RNA, genomic DNA, and protein for their abundance, structural alterations, and biochemical properties such as methylation, phosphorylation, and acetylation. This has been expected to facilitate and greatly increase the likelihood of successful identification of traditional, single molecular biomarkers for each specific clinical problem. Application of these technologies in hepatocellular carcinoma (HCC) has enabled tumour classification based on molecular features. HCC subclasses correlate with signalling pathway de-regulation, specific gene mutations and some suggest progenitor cell origin. A number of prognostic gene signatures have been generated from tumour and adjacent non-tumoral tissue. Presumably, incorporation of additional layers of molecular information such as DNA methylation or non-coding RNA will improve prediction power of current mRNAbased clusters. However, there is a remarkable imbalance in the amount of signatures reported and the ones that reach full clinical implementation. Small studies are prone to overestimate or underestimate the actual association, and the lack of appropriate validation has also jeopardized study interpretation when considering cancer outcome with microarrays. Additional issues related to tumour heterogeneity could become critical, particularly in advanced tumour stages.
HCC Classification Based on Pathological Markers
Irene Ng, MD, PhD (Hong Kong)
Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. The diagnosis of HCC can be challenging. In this presentation, HCC subtypes with emphasis on their distinguishing histological features will be discussed. Furthermore, incorporation of recently described immunohistochemical markers would be able to devise an algorism for the initial approach of challenging HCC cases. Discussion will also be made into the recent interest and discussion in stratifying primary liver cancers according to the hepatobiliary differentiation or the component of hepatobiliary stem/progenitor cell origin. This classification has been shown to bear significance on the prognostication of patients. Recent studies have demonstrated that using a panel of selective immunomarkers as molecular classifiers on HCC tissues may provide a useful approach to identify patients at greater risk for postsurgical recurrence. Knowledge about molecular pathogenesis of HCC has dramatically improved in recent years, and some progress has been made in translation into clinical application. This development will enhance our ability to better classify HCC, stratify HCC patients, and provide more effective targeted treatment options. In the foreseeable future, the relevant clinical material will remain to be small biopsy material or formalin-fixed, paraffin-embedded specimens. Therefore, routine clinical practice has to be taken into consideration in devising diagnostic algorithms and for changes in treatment strategies.
Tissue Biomarkers Predicting Survival or Response in HCC
Andrew X. Zhu, PhD (USA)
In the era of personalised cancer medicine, there is an increased need for developing biomarkers for predicting survival and treatment response for patients with hepatocellular carcinoma (HCC). While there are many efforts examining circulating biomarkers including circulating tumour cells in HCC, it is generally accepted that tissue based biomarkers would provide more comprehensive information on the molecular signature of both the tumour and surrounding nontumoral liver tissue that have prognostic and predictive values. While many investigators have examined the association of various molecules in different pathways of hepatocarcinogenesis (proliferation, survival, differentiation, angiogenesis etc) with clinical outcomes, the new efforts have turned to the latest technology and focused on examining the genomic signatures (gene expression, miRNA and epigenetic biomarkers etc) in HCC. Despite the latest progress on the identification of many tissue based biomarkers in predicting the recurrence and overall survival, there is a paucity of data with tissue based biomarkers in predicting the response to treatment, particularly to molecularly targeted agents in HCC. The author will attempt to summarise the current status and discuss the challenges and future perspectives of tissue biomarker development in HCC.
Translating Tissue Biomarkers into Diagnostic Application – Challenges, Bias, Pitfalls
Peter Schirmacher, MD (Germany)
Translation of promising experimentally derived biomarkers into tumour tissue diagnostics is multistep process that is challenged by many obstacles. It is decisive for the successful implementation of the respective targeted therapy but at the same time represents the most neglected part of translational research as well as industrial strategies. Implementation of predictive diagnostics involves preclinical assessment of suited collectives, trial associated diagnostics, roll-out strategies, quality assessment and bedside-bench research concepts. Among the many pitfalls are consideration of rapid, robust, financed and broadly implemented assays, need for intensive industry-academic interaction, international differences in approval conditions, and changes in therapeutic concepts, just to name a few. The situation for HCC is specifically worrisome as it is the only relevant tumour disease, which does not require tumour tissue acquisition before initiation of specific antineoplastic therapy and as no targeted therapy is approved for HCC so far, leaving an unpaved road ahead. HCC threatens to lose further ground in competition with other major tumour diseases, already offering multiple targeted concepts (e.g. breast, colon, lung cancer). Aim of the presentation is to delineate the challenges ahead and strategies to implement predictive diagnostics for targeted HCC therapy in the most reliable and rapid manner.