CROSS-REFERENCE TO RELATED APPLICATIONS

This application is the U.S. national stage of International Patent Application No. PCT/EP2019/075319, filed on Sep. 20, 2019, which claims the benefit of priority under 35 U.S.C. § 119(e) from Austrian Patent Application No. A 50804/2018, filed Sep. 20, 2018. The disclosures of the foregoing applications are incorporated herein by reference in their entirety.

SEQUENCE LISTING

The entire content of a Sequence Listing titled “Sequence_Listing.txt,” created on Mar. 22, 2021 and having a size of 2 kilobytes, which has been submitted in electronic form in connection with the present application, is hereby incorporated by reference herein in its entirety.

FIELD OF THE INVENTION

The present invention provides a method, specifically an in vitro method, to determine a subject's risk of liver dysfunction, in particular following liver resection, wherein the level of one or more selected miRNAs is quantified in a sample from said subject.

BACKGROUND OF THE INVENTION

Liver resection represents the only curative treatment in many liver malignancies. Post-resectional hepatic regeneration is the main determinant for clinical outcome of patients undergoing liver resection (1), as insufficient hepatic regeneration after liver resection was shown to result in postoperative liver dysfunction (LD), which occurs in up to 30% of patients after major hepatic resections (2). Importantly, currently available treatment options for patients with postoperative LD are very limited, mostly symptomatic and goal-directed (2, 3). Hence, risk stratification for optimized patient selection prior to liver surgery is key for minimizing the incidence of postoperative LD and concomitant complications. Furthermore, identifying patients at risk of developing liver dysfunction, not only following liver resection, as well as monitoring patient response to treatments aiming to stimulate liver regeneration is essential to provide optimal patient care. However, currently available markers are often expensive, time consuming and sometimes invasive, highlighting the need for an easily assessable test to determine liver dysfunction and to predict postoperative liver function recovery.

Emerging evidence suggests that microRNA (miRNA) signatures represent potent diagnostic, prognostic and treatment response biomarkers for several diseases (4). As master regulators of expression of multiple genes in different tissues, miRNAs can control virtually every cellular process on a transcriptional level, including cellular development, proliferation, migration, survival, metabolism, homeostasis and regeneration (5). Estimates based on computational analyses suggest that over 50% of the human transcriptome is regulated by at least one miRNA (6). Hence, it is not surprising that aberrant miRNA expression can have detrimental effects on signaling pathways and indeed has been implicated with a wide range of diseases (7-9). To date, almost 2000 miRNAs have been identified and some have already been validated for in vitro diagnosis and/or prognosis of various malignant diseases, demonstrating their potential as biomarkers in the clinic (10-12).

For example, WO2011/076141A1 and EP2196543A1 provide microRNA biomarkers for the diagnosis of hepatocellular cancer. WO2012/151736A1 discloses microRNA biomarkers which can be used to diagnose hepatocellular carcinoma or to distinguish between hepatocellular carcinoma and chronic hepatitis B or cirrhosis. WO2016/036994A1, for example, uses microRNA profiling in combination with further biomarkers, such as oncogenes, for the diagnosis of liver cancer.

US20170166975A1 discloses a kit or device for the detection of liver cancer, comprising a nucleic acid capable of specifically binding to microRNA in a patient sample.

CN101418343A discloses a kit for predicting postoperative liver cancer relapse of early primary liver cancer patients.

Micro RNAs have also been discovered as biomarkers for diseases other than malignancies. WO2018/231851A1, for example, discloses a method of diagnosing nonalcoholic steatohepatitis (NASH) or liver fibrosis, wherein the levels of one or more microRNAs are detected in a patient sample.

Besides highly tissue-specific expression profiles of some miRNAs, they also offer several other beneficial features sought after in biomarkers—e.g. miRNAs are easily accessible from biofluids such as blood, urine and saliva via non-invasive methods. Furthermore, they exhibit high stability and relatively low complexity (e.g. no post-processing modifications) and can be readily assessed by various methods with high specificity that also allow for signal amplification, making them superior compared to other classes of biomarkers including DNA, RNA and proteins.

Micro RNAs have also been used to modulate the translation of target mRNA. US2016089453A1, for example, discloses RNA modulating agents using miR-122 as guide to modify mRNA in hepatocytes.

Despite such advancements, treatment options as well as reliable predictive markers to determine patients at risk to develop LD, in particular after surgery, are limited. Accordingly, there is an urgent need for an easily assessable test to predict the risk of developing liver dysfunction and to monitor treatment response to liver regeneration stimulation, specifically as current markers are often expensive, time consuming and sometimes invasive.

SUMMARY

It is the objective of the present invention, to provide reliable biomarkers, with high specificity and validity, for the prediction of liver dysfunction, in particular after partial liver resection and for the monitoring of liver function, in particular following partial liver resection or liver regeneration stimulation.

The problem is solved by the present invention.

The inventors have shown that expression levels of specific miRNAs are significantly altered in patients who developed liver dysfunction after partial liver resection compared to patients who did not develop liver dysfunction. Surprisingly, these changes in expression levels were shown in blood samples derived from patients before surgery and thus enable reliable prediction of development of liver dysfunction. Further, the risk of developing liver dysfunction after partial liver resection can be predicted with precision even before surgery.

The present invention provides a selected set of miRNAs that are specifically up- or down-regulated and are thus useful as valuable biomarkers and represent a diagnostic and predictive signature applicable over a broad range of liver diseases.

According to the invention there is provided an in vitro method of determining a subject's risk of liver dysfunction, specifically after partial liver resection, said method comprising the steps of:

a) providing a sample from said subject,

b) determining in said sample the expression level of at least one miRNA, selected from the group consisting of miR-151a, miR-192 and miR-122, and

i. comparing the expression level(s) of b) with at least one reference expression level, or

ii. identifying the ratios of miR-151a to miR-192 and/or of miR-122 to miR-151a based on the expression levels determined in b), and comparing said expression level ratios with reference expression level ratios, and

classifying the sample from the outcome of the comparison of step i) or step ii) into one of at least two classes, wherein each class is one of the at least two categories “high-risk” and “low-risk”.

Specifically, the in vitro method provided herein allows determining a subject's risk of developing liver dysfunction. Preferably, the in vitro method provided herein allows determining a subject's risk of developing liver dysfunction after partial liver resection.

Specifically, in a patient's sample the expression level of at least one miRNA selected from the group consisting of miR-151a, miR-192 and miR-122 is determined. Specifically, the expression level of at least two of miR-151a, miR-192 and miR-122 is determined. Specifically, the expression level of miR-151a and miR-192 is determined. Specifically, the expression level of miR-151a and miR-122 is determined. Specifically, the expression level of miR-192 and miR-122 is determined.

According to a specific embodiment, the expression levels of miR-151a, miR-192 and miR-122 are determined.

Specifically, the miRNAs used herein are selected from the group consisting of hsa-miR-151a-5p, hsa-miR-192-5p and hsa-miR-122-5p.

Specifically, a decreased expression level of miR-151a is indicative of increased risk of liver dysfunction. Specifically, an increased expression level of miR-122 and/or miR-192 is indicative of increased risk of liver dysfunction.

Specifically, in pre-surgical samples of patients with increased risk of liver dysfunction the expression level of miR-151a is down-regulated. Specifically, in pre-surgical samples of patients with increased risk of liver dysfunction the expression level of miR-122 and/or the expression level of miR-192 is up-regulated. Specifically, pre-surgical samples are samples provided from a patient before partial liver resection.

According to a specific embodiment, the outcome of the comparison of step i) or step ii) can be classified into further classes of the categories “no-risk” and “medium-risk”. Specifically, comparing the miRNA expression levels or expression level ratios in a subject's sample to the miRNA expression levels or expression level ratios in samples of subjects which did not develop liver dysfunction after partial liver resection or to samples of healthy subjects allows classification of a subject's sample into one of the categories “no-risk”, “low-risk”, “medium-risk” or “high-risk”.

Specifically, a subject, whose sample is classified as belonging to the category “no risk”, thus, has no risk or very low risk of developing liver dysfunction, in particular after partial liver resection. Preferably, no risk or very low risk refers to a risk of 25% or less than 25% to develop liver dysfunction. A subject, whose sample is classified as belonging to the category “low risk”, thus, has a low risk of developing liver dysfunction after partial liver resection. Preferably, low risk refers to a risk of more than 25% and up to 50% to develop liver dysfunction. A subject, whose sample is classified as belonging to the category “medium risk”, thus, has a medium risk of developing liver dysfunction after partial liver resection. Preferably, medium risk refers to a risk of more than 50% and up to 75% to develop liver dysfunction. A subject, whose sample is classified as belonging to the category “high risk”, thus, has a high risk of developing liver dysfunction after partial liver resection. Preferably, high risk refers to a risk of more than 75% to develop liver dysfunction.

Specifically, the reference expression level is the expression level of at least one miRNA, selected from the group consisting of miR-151a, miR-192, and miR-122 of a healthy subject or a subject without post-operative liver dysfunction or a group or pool thereof.

Specifically, reference expression level ratios are expression level ratios of miR-151a to miR-192 and of miR-122 to miR-151a of a healthy subject or a subject without post-operative liver dysfunction or a group thereof.

Specifically, said reference expression level can be the average level of corresponding miRNAs in subjects which did not develop liver dysfunction after partial liver resection, specifically in a pool of samples derived from such subjects, wherein a difference by more than one standard deviation, specifically by about 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, specifically about 2 standard deviations or more is indicative of increased risk of developing liver dysfunction after partial liver resection. Specifically, a difference in the miRNA expression level or in the miRNA expression level ratios compared to the expression levels or expression level ratios of corresponding miRNAs in subjects who did not develop liver dysfunction after partial liver resection by at least 1.3 fold is indicative of increased risk of developing liver dysfunction.

Specifically, a difference by more than 1.5 standard deviations, preferably more than 2 standard deviations, specifically about 2.1, 2.2, 2.3, 2.4, 2.5 or 3 is indicative of high risk of developing liver dysfunction, specifically after partial liver resection.

Specifically, a difference by at least one standard deviation is indicative of medium risk of developing liver dysfunction, specifically after partial liver resection.

Specifically, a difference by less than one standard deviation is indicative of low risk of developing liver dysfunction, specifically after partial liver resection.

Specifically, miRNA expression levels or expression level ratios which are comparable to the corresponding reference expression levels or reference expression level ratios, specifically which levels or ratios differ by no more than 0.5 standard deviations from reference levels or reference ratios are indicative of very low risk of developing liver dysfunction, specifically after partial liver resection. Such samples can thus be classified as belonging to the category “no-risk”. A subject whose sample is classified as belonging to the category of “no-risk” is less likely to develop liver dysfunction after partial liver resection than a subject whose sample is classified as belonging to the category “low-risk”.

It is within the embodiment of the invention to use either a single reference sample from a healthy subject or a subject which did not develop liver dysfunction after partial liver resection or a pool of samples derived from healthy subjects or subjects which did not develop liver dysfunction after partial liver resection for comparison with the respective sample from the subject whose LD risk to be determined. Said pool can consist of 2, 3, 4, 5, 6, 7, or more samples, specifically up to 10, 100 or more than 100 samples from different individuals.

According to a specific embodiment of the invention, subjects classified as “low-risk” are subjected to partial liver resection, subjects classified as “medium-risk” are subjected to stimulation of liver regeneration before partial liver resection and subjects classified as “high-risk” are not subjected to partial liver resection. Specifically, subjects classified as “no-risk” are also subjected to partial liver resection without prior stimulation of liver regeneration. Specifically, subjects classified as “medium-risk” are subject to partial liver resection, but first they are subjected to treatment aiming to stimulate liver regeneration. Preferably, following stimulation of liver regeneration regeneration-success is assessed and the subject's risk of developing liver dysfunction after partial liver resection is determined before the subject is subjected to partial liver resection.

Specifically, subjects classified as “medium-risk” are subjected to treatment before partial liver resection, which treatment is selected from the group consisting of neoadjuvant chemotherapy, portal vein embolization, associating liver partition and portal vein ligation for staged hepatectomy (ALPPS), exercise intervention (“prehabilitation”) or pharmacological therapy reducing portal vein hypertension. Specifically, exercise intervention and/or diet changes can aid in liver regeneration by improvement of overall fitness and health. Specifically, a further option for subjects classified as medium-risk is a modified surgical strategy. Preferably, in said modified surgical strategy, the necessary size of the resected liver portion is reduced by combination with thermic ablation of tumor centers.

Specifically, miRNA signatures described herein are used to determine a time-point for partial liver resection at which the patient's risk of developing post-operative liver dysfunction is low. Specifically, samples of subjects that are classified as “medium-risk”, and thus subjected to treatment such as ALPPS before liver resection, are provided at more than one time-point so that an optimal time-point for partial liver resection can be determined. Specifically, samples are provided and the risk of developing liver dysfunction is determined once every two weeks, once a week, daily or at least twice a day. Specifically, once the sample is classified as “low-risk”, the time-point for partial liver resection is optimal.

Specifically, subjects classified as “high-risk” are not subjected to partial liver resection. Specifically, said subjects are instead subjected to liver transplantation, palliative chemotherapy, radiofrequency ablation, or transarterial chemoembolisation (TACE). Specifically, said treatment is selected in dependence of the tumor load.

Herein further provided is an in vitro method of monitoring regeneration-success of liver regeneration stimulation of a subject, comprising the steps of

a) providing a sample from said subject,

b) determining the expression level ratios of miR-151a to miR-192 and of miR-122 to miR-151a in said sample,

c) determining the expression level ratios of miR-151a to miR-192 and of miR-122 to miR-151a in a reference sample, wherein the reference sample is an earlier sample of the subject,

d) comparing the expression level ratios of b) with the expression level ratios of c), and

e) classifying the sample of said subject from the outcome of the comparison of step d) into one of two categories, “regeneration-success” or “no regeneration-success”.

Specifically, the liver regeneration stimulation whose regeneration-success is to be determined according to the in vitro method provided herein is selected from the group consisting of induction of liver hypertrophy by portal vein embolization, induction of liver hypertrophy by associating liver partition and portal vein ligation for staged hepatectomy (ALPPS), exercise intervention (“prehabilitation”) to improve overall fitness, and pharmacological therapy reducing portal vein hypertension.

Specifically, the subject is suffering from malignant lesions in the liver, preferably metastatic colorectal cancer, hepatocellular carcinoma or cholangiocellular carcinoma, or from benign liver tumors, hepatic cysts and/or parasites. Specifically, the subject is suffering from one or more tumors, benign or malignant, in the liver. The tumors can originate from any tissue or organ.

According to a specific embodiment, the sample is selected from the group consisting of blood, serum, plasma, specifically platelet-poor plasma, lymph, urine and saliva and biopsy probes. Specifically, the sample is cell-free blood.

According to a further specific embodiment, the expression levels or expression level ratios of the sample are compared with the reference expression levels or expression level ratios using a classification model.

Specifically, a classification model classifies the sample of a subject from the outcome of the comparison with the reference into one of the at least two classes.

Specifically, the classification model is selected from the group consisting of logistic regression models, support vector machine models and decision tree models.

Further described herein are clinically useful cut-offs predicting risk of liver dysfunction, in particular following partial liver resection. Specifically, a low stringency cut-off with a Probability Score of less than 0.59, specifically less than 0.58, 0.57, 0.56, 0.55, 0.54, 0.53, 0.52, 051 or 0.50 identifies subjects at low risk of developing liver dysfunction and patients that can undergo partial liver resection with low risk. Preferably, a Probability Score of less than 0.58 (P<0.58) classifies a patient as low-risk. Specifically, a stringent cut-off with a probability score of more than 0.58, specifically more than 0.59, 0.60, 0.61, 0.62, 0.63, 0.64 or 0.65 identifies patients with medium risk of developing liver dysfunction, such patients should be optimized prior to surgery. Preferably, a Probability Score of more than 0.58 (P>0.58) classifies a patient as medium-risk. Probability Scores of higher than 0.66, 0.67, 0.68, 0.69, 0.70, 0.71, 0.72, 0.73, 0.74 or 0.75 identify subjects as high-risk patients, who preferably should not undergo surgical partial liver resection. Preferably, a Probability Score of higher than 0.68 (P>0.68) identifies subjects at high-risk of developing liver dysfunction.

According to a specific embodiment, the expression levels are determined using a method selected from the group consisting of a sequencing-based method, specifically next-generation sequencing, an array-based method and a PCR-based method, specifically a quantitative PCR-based method.

Specifically, the difference in miRNA levels is determined by quantitative or digital PCR, DNA/RNA sequencing, specifically Next-Generation Sequencing, microarray, Luminex™ luminescence based nucleic acid assays, or other hybridization-based techniques.

Herein further provided is a kit-of-parts comprising

a) detection reagents capable of detecting the expression level of at least one microRNA, selected from the group consisting of miR-151a, miR-192 and miR-122, in a subject's sample,

b) reference expression levels,

software comprising the classification models for comparison of expression levels of a) with expression levels of b) and for classification of the subject's sample into one of at least two classes, wherein each class is one of the at least two categories “high-risk” and “low-risk” of liver dysfunction after partial liver resection.

