The Impact of Translational Research in Hepatology

Watch a video presentation of this article

Watch the interview with the author

Abbreviations

ALK

anaplastic lymphoma kinase gene

BRAF

b‐rapidly accelerated fibrosarcoma gene

BRCA

breast cancer gene

DAA

direct‐acting antiviral

EGFR

epidermal growth factor receptor

ERBB2

erythroblastic oncogene 2 (synonym: HER2)

FDA

Food and Drug Administration

FISH

fluorescent in situ hybridization

GIST

gastrointestinal stroma tumor

HCC

hepatocellular carcinoma

HCV

hepatitis C virus

HER2

human epidermal growth factor 2

HR

hormone receptor

IFN

interferon

IHC

immunohistochemistry

KRAS

k‐rat sarcoma gene

NSCLC

non‐small‐cell lung cancer

NGS

next generation sequencing

PCR

polymerase chain reaction

PD‐L1

programmed cell death ligand‐1

SNP

single‐nucleotide polymorphism

SVR

sustained virological response

The US National Center for Advancing Translational Sciences defines translational research as the spectrum of each stage along the path from the biological basis of health and disease to interventions that improve the health of individuals and the public. In essence, translational research uses basic/experimental research tools and human specimens to address clinical needs. Translational research has emerged to fill the increasing gap between basic science and clinical research. Broadly speaking, basic science tries to unravel the mechanisms of disease using tools (e.g., culture systems and animal models) that allow for easy manipulation of biological processes. These tools are useful to derive causal associations, but they generally do not include an endpoint directly applicable to clinical practice. This does not mean that basic research has not been instrumental in major medical advancements. On the other extreme, the primary goal of clinical research and public health studies is to solve specific clinical problems. The paradigm of clinical research is clinical trials, designed to evaluate the impact of well‐defined interventions on specific clinical outcomes in humans. A major goal of translational research is to build bridges between these two approaches to conduct biomedical research.

The use of human samples is central to translational research. Analysis of human tissues with genome‐wide molecular profiling technologies (e.g., gene expression arrays and next generation sequencing [NGS]) has been instrumental in the development of this discipline. In cancer, translational research has analyzed tumor samples to develop molecular‐based prognostic and predictive biomarkers, and to identify novel therapeutic targets. Not surprisingly, the number of publications mentioning translational research has increased in parallel to those citing high‐throughput genomic analysis such as NGS (Fig. 1). Like any good language translator, translational scientists need to have a certain level of expertise of both sides of the biomedical research continuum (Fig. 2). This includes knowledge of the main genomic technologies and animal models, as well as the specific clinical challenges that need to be addressed and could benefit from a molecular‐based approach. In this review, we describe some examples of how translational research has helped improve the clinical care of patients with liver diseases.

Figure 1.

Number of entries for terms “translational research” and “next generation sequencing” over the past 15 years in PubMed (data were accessed September 24, 2018). This reflects the increased interest in translational research in the scientific community.

Figure 2.

Translational research in the Biomedical Research Continuum and its relation to basic and clinical research. Visual summary of the interplay between basic and clinical research, and how translational research connects both approaches to understand human physiology and disease.

The development of successful therapies against hepatitis C virus (HCV) infection epitomizes the impact of translational research in clinical practice (Fig. 3). Interferon‐based treatment regimens achieved a modest rate of sustained virological response (SVR) at a cost of significant drug toxicity. A landmark genome‐wide association study using a large cohort of patients demonstrated a close association between a single‐nucleotide polymorphism (SNP) in the IL28B gene (i.e., the C/C genotype) and higher rates of SVR irrespective of gender, ethnicity, degree of liver fibrosis, or viral load.1 This association was independently validated,2 and testing for IL28B genetic variants was incorporated into clinical practice guidelines for the management of HCV.3 This achievement was soon surpassed by the therapeutic success of direct‐acting antivirals (DAAs), which achieved SVR rates greater than 95%. The design of in vitro models to evaluate the efficacy of new HCV antivirals was instrumental for the development of DAAs.4, 5 In the “HCV replicon” model, HCV was able to replicate in vitro for the first time, a crucial step for efficient anti‐HCV drug screening.4, 5 These are two paradigmatic examples of how using modified experimental models and molecular data from human samples can have a direct and significant impact on the clinical management of patients with liver diseases. In addition, the application of NGS has helped identify the primary genetic defect in multiple monogenic liver diseases.6

Figure 3.

Timeline of key events leading to paradigmatic changes in the management of HCV as an example of translational research. This image summarizes how translational research has radically change the treatment of HCV infection, including crucial steps such as the discovery of the IL28B genotype as a prediction of response to IFN‐based therapies or the development of effective in vitro replicon systems for drug screening.

Another area in hepatology that could benefit from translational research is hepatocellular carcinoma (HCC). Until 2016, sorafenib was the only systemic agent able to increase survival in patients at advanced HCC stages. Since then, four drugs have shown clinical efficacy either in first‐ or second‐line therapy after phase 3 clinical trials (i.e., lenvatinib, regorafenib, cabozantinib, and ramucirumab).7, 8 Also, a response rate of 14% and 17%, respectively, and duration of response longer than 1 year in half of responders prompted the US Food and Drug Administration (FDA) approval of nivolumab and pembrolizumab under the accelerated program after single‐arm phase 1/2 trials.9, 10 However, besides serum alpha‐fetoprotein levels for patients receiving ramucirumab in second‐line therapy, there are no biomarkers to identify the best responders to any of these therapies.7, 8 Despite that translational research efforts helped identify an immune subclass in HCC resection specimens,11 its ability to predict response to immune‐based therapies is still under investigation. This is in contrast with other tumor types where comprehensive molecular profiling of large sets of samples enabled the identification of robust predictive biomarkers of treatment response (e.g., BRAF mutations and response to vemurafenib in melanoma, and ALK rearrangements and response to crizotinib in lung cancer). These translational research initiatives helped coin the concept of “oncogene addiction,” a term that describes a selective dependence of cancer cell growth for a certain genetic alteration. Some of these biomarkers are included in clinical practice guidelines and FDA labels (Table 1).

Table 1.

Examples of FDA‐Approved Molecular Biomarkers with Genetic Alteration and Detection Method for Prediction of Response in Solid Tumors

Biomarker	Genetic Alteration	Detection Method	Approved for	Drugs (Examples)
ALK‐positive	Rearrangement/fusion	Tissue (FISH, NGS)	NSCLC	Alectinib, brigatinib, ceritinib, crizotinib
BRAF	Point mutation	Tissue (PCR, NGS)	Melanoma	Binimetinib, vemurafenib, dabrafenib, trametinib
			NSCLC	Dabrafenib, trametinib
			Anaplastic thyroid cancer	Trametinib
BRCA	Point mutation	Tissue (PCR, NGS)	Ovarian cancer	Niraparib, olaparib, rucaparib
			Fallopian tube, primary peritoneal cancer	Rucaparib
EGFR	Deletion, point mutation	Tissue, blood (PCR, NGS)	NSCLC	Afatinib, erlotinib, gefitinib, osimertinib
ERBB2 (HER2)	Overexpression	Tissue (IHC, FISH, NGS)	Breast cancer	Lapatinib, neratinib, pertuzumab, trastuzumab
			Gastric cancer*	Trastuzumab
HR (hormone receptor)	Overexpression	Tissue (IHC)	Breast cancer	Abemaciclib, anastrozole, everolimus, exemestane, fulvestrant, letrozole, palbociclib, ribociclib, tamoxifen
KIT	Point mutation	Tissue (IHC)	GIST	Imatinib
KRAS	Wild type	Tissue (NGS)	Colorectal cancer	Cetuximab, panitumumab
Microsatellite instability, mismatch repair	Microsatellite instability, mismatch repair	Tissue (NGS)	Colorectal cancer	Nivolumab
			All solid cancers	Pembrolizumab
PD‐L1	Overexpression	Tissue (IHC)	NSCLC, gastric cancer, cervical cancer	Pembrolizumab
			Urothelial cancer	Atezolizumab, pembrolizumab
ROS1	Rearrangement/fusion	Tissue (NGS)	NSCLC	Crizotinib

^*Includes gastroesophageal junction adenocarcinoma.

Adapted from the FDA.16 Copyright 2018, FDA.

Proper collection of tissue samples and their adequate clinical annotation was key for the success of these initiatives. Unlike most solid tumors, HCC can be confidently diagnosed without the need for a tumor biopsy,7, 8 which significantly decreases the availability of tumor tissue for biomarker research. As an alternative, many studies have tried to analyze tumor components released to the bloodstream, mainly tumor nucleic acids or circulating tumor cells, in the context of a “liquid biopsy.”12 In 2016, the FDA approved the first liquid biopsy assay for the detection of epidermal growth factor receptor (EGFR) mutations13 based on a phase 3 clinical trial where patients with lung cancer with EGFR mutations detected in plasma had a better progression‐free survival with the EGFR inhibitor erlotinib compared with standard chemotherapy.14 Data on liquid biopsy in HCC are scarce, but ultra‐deep sequencing analysis of circulating tumor DNA identified up to 70% of mutations found in corresponding tissue of the same patients.¹⁵ Potential applications of this technology are numerous, and some are listed as unmet clinical needs in the European HCC guidelines.7 Examples are development of new tools for early detection, including the evaluation of liquid biopsy, identification of tissue biomarkers of treatment response, implementation of precision medicine (link between molecular subclasses and treatment response), and improvement of patient stratification in patients at risk for HCC development to facilitate chemoprevention clinical trials.7 In summary, translational research has emerged as an effective approach to facilitate the development of novel molecular‐based biomarkers and to accelerate the implementation of laboratory discoveries into clinically applicable tools.