Method for predicting the occurrence of resistance to BRAF inhibitors, alone or in combination with MEK inhibitors, in anti-tumor therapy

Abstract

The present invention relates to a method for predicting the development of resistance to a BRAF inhibitor, alone or in combination with a MEK inhibitor (i.e., a MAPK pathway inhibitor or simply MAPKi), during anti-tumor therapy, said method comprising measuring the expression of both microRNAs miR-579-3p and miR-4488 in a biological sample collected from a tumor patient prior to the initiation of anti-tumor therapy with said MAPK pathway inhibitor, and determining the expression ratio of miR-4488 to miR-579-3p.

Description

Technical Field

[0001] The present invention relates to a method for predicting the occurrence of resistance to BRAF inhibitors, alone or in combination with MEK inhibitors (i.e., MAPK pathway inhibitors or simply MAPKi), during anti-tumor therapy. Specifically, the present invention relates to a method for predicting the occurrence of resistance to BRAF and / or MEK inhibitors in anti-tumor therapy, the method comprising measuring the expression levels of two microRNAs, miR-579-3p and miR-4488, in a biological sample collected from a cancer patient before initiating anti-tumor therapy with a BRAF inhibitor and / or a MEK inhibitor.

Background Art

[0002] Certain tumors are known to be treatable with MAPK pathway inhibitors.

[0003] Specifically, the treatment of metastatic melanoma has seen significant developments in recent years, which is due to the emergence of targeted therapy with MAPKi and immunotherapy with immune checkpoint inhibitors [1,2]. The gold standard of targeted therapy consists of the combinatorial use of BRAF inhibitors and MEK inhibitors aimed at blocking the BRAF / MEK / MAPK signaling pathway in BRAFV600 mutant melanoma (MAPKi). This method provides significant benefits in terms of objective response, time to progression, and overall survival, but its effect is often nullified by innate or acquired drug resistance, resulting in a median time to recurrence of about 15 months and tumor recurrence [2,3]. Recurrent tumors are highly invasive and almost untreatable [4,5]. It should be noted that although immunotherapy is often used as a salvage option after disease progression to MAPKi in BRAF mutant melanoma patients, important studies have shown that acquired resistance to MAPKi is a negative factor in the response after immunotherapy [9].

[0004] Based on these important evidences, it is necessary to develop a novel diagnostic tool that can predict a treatment method that may bring the optimal benefit to patients with progressive melanoma.

[0005] In recent years, tissue biopsy has been the "gold standard" test for cancer diagnosis. However, the removal of metastatic tumor tissue by surgery is an invasive process and is associated with many limitations [10 - 12]. Furthermore, such a method is not suitable for the clinical longitudinal monitoring of melanoma patients. In contrast, liquid biopsy aimed at analyzing biomarkers released by tumors into the blood provides a great opportunity to overcome these limitations. This technique can longitudinally monitor the efficacy of patients for specific treatments and enable the decision of whether to continue or quickly change the treatment [12, 13]. Some evidences in the past few years have highlighted the availability of circulating molecular biomarkers for melanoma diagnosis and prognosis determination. In fact, this technique utilizes several biomarkers present in the blood, including circulating tumor cells (CTCs), cell-free circulating tumor DNA (ctDNA), lactate dehydrogenase (LDH), S100 calcium-binding protein B (S100B), and cell-free circulating RNA (cfRNA), which are suitable prognostic factors for monitoring the disease progression of patients with progressive melanoma [10, 14 - 19].

[0006] Among the latter, a class of small non-coding RNAs called microRNAs (miRNAs) has been increasingly recognized as important. In cells, these small molecules are essential regulators of post-transcriptional gene expression, and changes in their balance are associated with several pathological conditions, including cancer [14, 20 - 24]. Furthermore, changes in miRNAs have also been correlated with the establishment of treatment resistance [25, 26, 27]. In addition to their standard intracellular functions, several findings have shown that miRNAs can be released and move through biological fluids while protected by proteins such as AGO2 or encapsulated in highly stable extracellular vesicles (EVs) such as exosomes [28, 29, 30]. Notably, miRNA expression can be easily detected by standard real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR).

[0007] For these reasons, circulating miRNAs are increasingly emerging as potential non-invasive biomarkers for diagnosing the occurrence of many cancers, such as breast cancer, leukemia, lung cancer, pancreatic cancer, and even melanoma [31 - 36]. For example, in one study, the potential of serum-exosomal miR-105 to predict or diagnose early-stage patients who may develop or have already developed breast cancer metastasis was shown

[37] . Again, another study of plasma-derived pancreatic ductal adenocarcinoma (PDAC) shed light on the potential role of miRNA-483-3p as a biomarker for PDAC. In particular, the deregulation of this miRNA was observed as an early event in PDAC. Indeed, miR-483-3p is overexpressed in the serum and serum exosomes of PDAC patients, suggesting that it could be a potential liquid biopsy biomarker for early detection of PDAC

[38] . Finally, regarding lung cancer, several studies have highlighted the potential diagnostic and / or prognostic role of miRNAs carried by exosomes. In recent years, it has been reported that exosomal miRNA profiles, including let-7 and other miRNAs, can dramatically differentiate lung cancer patients from healthy controls

[39] .

[0008] Regarding melanoma, several studies have documented that a specific set of miRNAs can be used as prognostic biomarkers for cancer development or to predict the outcome of treatment [34, 35, 36]. For example, Margue et al. [23, 40] showed that miR-301a-3p was downregulated in stage III / IV melanoma patients compared to healthy controls. Additionally, Greenberg et al. [23, 41] also reported that miR-29c-5p and miR-324-3p were lower in the serum of metastatic melanoma patients (stage IV) compared to healthy control individuals.

[0009] It is important to note the existence of two important aspects regarding circulating miRNAs, namely their normalization and quantification in plasma / serum. The first problem arises from the observation that there is no miRNA that functions as a circulating reference. Unfortunately, standard reference miRNAs used in tissue samples such as RNU48 and RNU6 are not suitable for normalizing extracellular miRNAs due to degradation mediated by RNase in the bloodstream

[23] . Total RNA extracted from serum / plasma samples is also usually below the threshold of standard quantification methods such as UV spectrophotometry and fluorescence spectrophotometry.

[0010] To overcome both of the above problems, a fixed amount of plasma or serum is often selected for use as input for the reverse transcription reaction (RT). Another approach for normalizing miRNA expression is the global mean normalization (GMN) and the REfFinder (RF) method. Global mean normalization consists of determining Ct values for multiple miRNAs tested per sample. High Ct values (above a certain threshold) that are (noise) must be removed, and the remaining Ct values should be used to calculate the average Ct across all miRNAs individually for each sample. Subsequently, the arithmetic mean Ct value is calculated for each individual sample and then subtracted from each individual Ct value of that sample. RefFinder is a web-based comprehensive tool developed for the evaluation of large experimental datasets and the screening of reference genes. Specifically, RefFinder performs a rapid analysis based on the major currently available computer programs (geNorm, Normfinder, BestKeeper, and the comparative delta-Ct method) to compare and rank the candidate reference genes tested. By doing so, it is possible to establish miRNAs that can function as reference miRNAs with less variation between the various methods analyzed by the program.

[0011] Over the past few years, the role of miRNAs in melanoma progression and treatment resistance has been investigated [26, 45, 46, 47]. In the first study, a novel tumor-suppressive miRNA, namely miR-579-3p, was identified, which was downregulated in BRAF-mutant melanoma cells and further downregulated upon acquisition of resistance to MAPKi. Furthermore, this miRNA was strongly downregulated in both matched patient-derived tumor samples before and after the development of resistance to targeted therapy

[45] . Following this first study, a comprehensive analysis of the changes in the entire miRnome deregulated upon the development of in vitro resistance to MAPKi ensued. This led to the identification of over 20 deregulated miRNAs and the detailed characterization of 5 of them

[46] . During the development of drug resistance, in particular, three miRNAs (miR-9-5p, miR-4443, and miR-4488) were strongly upregulated, while the remaining two miRNAs were downregulated (miR-199b-5p and miR-204-5p) [47, 48]. These miRNAs were also strongly regulated in solid and liquid biopsies of melanoma patients after disease recurrence

[46] . In a specific case of liquid biopsy, miR-199b-5p expression levels were found to be downregulated in the plasma of 25 melanoma patients after MAPKi treatment compared to that of untreated patients. Conversely, miR4488 levels were significantly increased in patients after MAPKi treatment

[46] .

[0012] The patent application WO2019 / 198115 is also known, which relates to a method for in vitro diagnosis of resistance to MAPK pathway inhibitors in tumors, detecting two or more of miR-199b-5p, miR-204-5p, miR-4443, and miR-4488 from a biological sample by measuring the expression of miRNAs during treatment. According to this patent application, the above miRNAs are predictive of drug resistance during treatment with MAPK pathway inhibitors.

[0013] Previously, there has been no known method capable of predicting resistance to MAPK pathway inhibitors before the initiation of treatment with MAPKi. An important disadvantage is associated with the delay in detecting the above resistance, which not only means there is no therapeutic benefit for the patient but also that the patient will suffer from side effects. In addition, the delay in detecting the above resistance hinders the early initiation of alternative therapies such as immunotherapy with checkpoint inhibitors (ICI) for patients who are resistant to MAPK pathway inhibitors, thus reducing the chance of recovery. All of these disadvantages are also linked to high medical costs.

[0014] Based on the above, there is a clear need to provide a novel diagnostic method and biomarker for predicting drug resistance in cancer patients, particularly melanoma patients, that can overcome the disadvantages of known methods.

Summary of the Invention

[0015] According to the present invention, it has now been found that both miR-579-3p and miR-4488 are predictive biomarkers capable of identifying progressive melanoma patients who benefit from MAPKi treatment. Specifically, as shown by the experimental data described below, first, a retrospective analysis of 70 serum samples from BRAF-mutated melanoma patients treated with MAPKi therapy was performed, and six circulating miRNAs, specifically three oncomiRs (miR-9-5p, miR-4443, and miR-4488) and three tumor suppressors (miR-579-3p, miR-204-5p, and miR-199b-5p), were evaluated in detail as predictors of response to therapy before treatment initiation. The results showed that only miR-579-3p and miR-4488 among the candidates are promising predictive biomarkers capable of identifying progressive melanoma patients for whom MAPKi treatment is effective.

[0016] The above two miRNAs can predict the response to MAPKi therapy before the initiation of therapeutic treatment.

[0017] In addition, according to the present invention, it has been found that the expression ratio of miR-4488:miR-579-3p exhibits good sensitivity and specificity for predicting disease progression in patients treated with MAPKi.

[0018] Therefore, the present invention provides for the first time a miRNA-based assay as a method for predicting the therapeutic efficacy of MAPKi therapy before the start of the therapy.

[0019] Thus, a specific problem of the present invention is an in vitro method for identifying tumor patients who are non-responsive to antitumor therapy (MAPK pathway inhibitor) by BRAF inhibitor alone or in combination with a MEK inhibitor, measuring or obtaining the measurements of the expression of both miR-579-3p (MIMAT0003244) and miR-4488 (MIMAT0019022), which are microRNAs, in a biological sample of a tumor patient before the start of the antitumor therapy, calculating or obtaining the ratio (miR-4488:miR-579-3p) of the expression of miR-4488 to the expression of miR-579-3p, providing a method wherein when the ratio is higher than the ratio of the expression of miR-4488 to the expression of miR-579-3p measured from a biological sample of a responsive tumor patient who has received the same antitumor therapy before the start of the antitumor therapy, the above tumor patient is a non-responsive tumor patient.

Mode for Carrying Out the Invention

[0020] For non-responsive tumors, the patient is intended to be a tumor patient suffering from progressive disease (PD) within 6 months from the start of treatment with BRAF inhibitor alone or in combination with a MEK inhibitor.

[0021] For responsive tumors, the patient is intended to be a tumor patient who has experienced partial or complete response (PR or CR) or stable disease (SD), for example, based on the RECIST criteria, for at least 6 months from the start of treatment with BRAF inhibitor alone or in combination with a MEK inhibitor.

[0022] According to the present invention, the identification of non-responding tumor patients is intended to identify tumor patients with a high probability of developing progressive disease during therapy with a BRAF inhibitor alone or in combination with a MEK inhibitor.

[0023] The above ratio between the expression of miR-4488 and the expression of miR-579-3p measured from a biological sample of a responsive tumor patient before the start of the above anti-tumor therapy may be the average value or median value of the ratio calculated from the group of responsive tumor patients.

[0024] The expression of miR-579-3p and miR-4488, which are microRNAs, is intended to be the quantitative value of the expressed miRNA.

[0025] According to the method of the present invention, when the above tumor patient is a non-responding tumor patient, the above ratio may be higher than the cut-off ratio value obtained in the following steps. Before the start of anti-tumor therapy with a BRAF inhibitor alone or in combination with a MEK inhibitor, measure or obtain the measured values of the expression of both miR-579-3p and miR-4488, which are microRNAs, in the biological samples of a tumor patient population, and the above tumor patient population includes a group of non-responding tumor patients and a group of responsive tumor patients. For each tumor patient, calculate the ratio (miR-4488:miR-579-3p) of the expression of miR-4488 to the expression of miR-579-3p. Obtain a cut-off ratio value by means of an ROC curve to distinguish responsive tumor patients from non-responding tumor patients.

[0026] According to the present invention, when the above tumor patient is a non-responding tumor patient, Before the start of the above anti-tumor therapy, the expression of miR-579-3p measured from the biological sample of the above tumor patient may be lower than the expression of miR-579-3p measured from the biological sample of a tumor patient responsive to anti-tumor therapy with a BRAF inhibitor alone or in combination with a MEK inhibitor, and Before the start of the above anti-tumor therapy, the expression of miR-4488 measured from a biological sample of the above tumor patient can be higher than the expression of miR-4488 measured from a biological sample of a tumor patient who responds to anti-tumor therapy with a BRAF inhibitor alone or in combination with a MEK inhibitor.

[0027] According to one embodiment of the present invention, the measured expression of miR-579-3p and the measured expression of miR-4488 can be determined as absolute levels (or absolute values) without normalizing against the expression of other miRNAs.

[0028] According to a further embodiment of the present invention, the measured expression of miR-579-3p and the measured expression of miR-4488 can be normalized against the expression of miR-579-3p, miR-4488, miR-204-5p (MIMAT0000265), miR-199b-5p (MIMAT0000263), miR-9-5p (MIMAT0000441) and miR-4443 (MIMAT0018961). Specifically, according to the present invention, when the expression of miRNA is measured by PCR and a Ct value is obtained as a measurement value of the expression, the normalized expression can be calculated as follows: Calculate the average value of the Ct values from the expression of each of the above six miRNAs measured, then subtract the average value from the single Ct value measured for each miRNA to obtain the ΔCt value for each miRNA, and the normalized expression value for each miRNA can be obtained by applying the formula 2-ΔCt.

[0029] According to a further embodiment of the present invention, the measured expression of miR-579-3p and the measured expression of miR-4488 can be normalized against the expression of miR-199b-5p.

[0030] According to the method of the present invention, therefore, the expression of the above microRNA can be measured using a pair of primers and / or probes suitable for this purpose. Primers and probes are known to be oligonucleotide sequences complementary to the microRNA sequence to be detected. According to the present invention, the above method can be carried out using one or more synthetic sequences complementary to at least a part of miR-579-3p, or one or more synthetic sequences complementary to at least a part of miR-4488. In particular, the above one or more synthetic sequences can be primers and / or probes.

[0031] According to the present invention, the expression of miRNA can be measured by RNA hybridization methods such as real-time PCR, droplet digital PCR, microarray, Northern blot or dot blot, RNA next-generation sequencing, preferably by real-time PCR.

[0032] According to the present invention, the BRAF inhibitor can be selected from vemurafenib, dabrafenib, encorafenib (BRAF inhibitors), and the MEK inhibitor can be selected from cobimetinib, trametinib, binimetinib (MEK inhibitors).

[0033] According to the present invention, the tumor patient can be a patient suffering from a BRAF mutant tumor.

[0034] According to the present invention, the tumor patient can be a patient suffering from a tumor selected from the group consisting of melanoma, colorectal cancer, papillary thyroid cancer, non-small cell lung cancer, brain tumor, non-Hodgkin lymphoma.

[0035] According to the experimental results described in the examples, it is reasonable for those skilled in the art that the method of the present invention is effective against any tumor treated with a BRAF / MEK pathway inhibitor that can become resistant to the BRAF / MEK pathway inhibitor. In fact, resistance depends on genetic changes that result in the reactivation of MAPK signaling, independent of the type of tumor. Thus, tumor patients who are non-responsive to anti-tumor therapy with a BRAF inhibitor and / or a MEK inhibitor exhibit lower miR-579-3p expression than that in responsive patients and higher miR-4488 expression than that in responsive patients, which directly depends on the above genetic changes and not on the type of tumor.

[0036] According to the method of the present invention, the biological sample can be a liquid biological sample such as blood, serum, plasma, urine, etc.

[0037] The present invention also relates to a method for diagnosing non-responsive tumor patients and treating them with anti-tumor therapy (MAPK pathway inhibitors) with a BRAF inhibitor alone or in combination with a MEK inhibitor. The method comprises a) obtaining measurement values of the expression of both microRNAs miR-579-3p (MIMAT0003244) and miR-4488 (MIMAT0019022) from a biological sample of a tumor patient before the start of the above anti-tumor therapy; b) calculating the ratio of the expression of miR-4488 to the expression of miR-579-3p (miR-4488:miR-579-3p); c) identifying tumor patients who are non-responsive to anti-tumor therapy with a BRAF inhibitor alone or in combination with a MEK inhibitor, and in the above non-responsive tumor patients, the above ratio is higher than the ratio of the expression of miR-4488 to the expression of miR-579-3p measured from the biological sample before the start of the same anti-tumor therapy in tumor patients who are responsive to the same anti-tumor therapy with a BRAF inhibitor alone or in combination with a MEK inhibitor, and d) Treat the patient with immunotherapy as an alternative to BRAF inhibitors and / or MEK inhibitors, or treat the patient with an antagonist against at least one of miR-4443 and miR-4488, and / or a miRNA mimic against at least one of miR-199b-5p, miR-204-5p and miR-579-3p in combination with a BRAF inhibitor alone or a MEK inhibitor, The antagonist can be selected from the group consisting of a locked nucleic acid targeting miR-4443, a locked nucleic acid targeting miR-4488, anti-miR-4443: aaaacccacgcctccaa (SEQ ID NO: 1) and anti-miR-4488: cgccggagcccgccccct (SEQ ID NO: 2), The miRNA mimic can be selected from the group consisting of miR-199b-5p mimic: cccaguguuuagacuaucuguuc (SEQ ID NO: 3), miR-204-5p mimic: uucccuuugucauccuaugccu (SEQ ID NO: 4) and miR-579-3p mimic: uucauuugguauaaaccgcgauu (SEQ ID NO: 5).

[0038] The present invention also relates to a method for obtaining a cut-off ratio value for identifying non-responding tumor patients from responding tumor patients to anti-tumor therapy by a BRAF inhibitor alone or in combination with a MEK inhibitor, the method comprising: Before the start of anti-tumor therapy by a BRAF inhibitor alone or in combination with a MEK inhibitor, measure or obtain the measurements of the expression of both microRNAs miR-579-3p and miR-4488 from a biological sample of a tumor patient population, the tumor patient population including a non-responding tumor patient group and a responding tumor patient group, For each tumor patient, calculate the ratio of the expression of miR-4488 to the expression of miR-579-3p (miR-4488: miR-579-3p), Obtaining a cut-off ratio value from an ROC curve.

[0039] Here, the present invention will be described specifically but without limitation with reference to its preferred embodiments, examples and the accompanying drawings.

Brief Description of the Drawings

[0040]

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Example 1

[0041] Identification of miRNA-Based Non-Invasive Predictive Biomarkers for Response to Targeted Therapy in BRAF-Mutant Melanoma

[0042] Materials and Methods Experimental Design Patients with metastatic BRAF - mutated melanoma (n = 36 men and n = 34 women) participated in this retrospective study. All of them received treatment with inhibitors of the MAPK pathway, namely vemurafenib or dabrafenib (as BRAF inhibitors) alone or in combination with cobimetinib or trametinib (as MEK inhibitors) respectively. Serum samples (1 ml) were collected from each patient before and after the initiation of MAPK therapy and stored in the tumor biobank of the Istituto Nazionale per la Cura dei Tumori “Fondazione G. Pascale” in Naples, Italy or the Istituto Nazionale Tumori “Regina Elena” (IFO) in Rome, Italy.

[0043] Human Samples The use of human samples was approved by the Ethics Committee of the Istituto Pascale on June 11, 2014 for protocol DSC / 1504, on April 11, 2015 for protocol DSC / 2893, and by the Ethics Committee of the Istituto Nazionale Tumori “Regina Elena” (IFO) on July 23, 2017 for protocol 8393. All patients signed a general informed consent form, which enabled the use of the material for research purposes, and the analysis was performed anonymously at the Istituto Nazionale per la Cura dei Tumori “Fondazione G. Pascale” and the Istituto Nazionale Tumori “Regina Elena” (IFO).

[0044] Patients eligible for this study were candidates for therapy with BRAF inhibitors alone or in combination with MEK inhibitors. All melanoma patients were 18 years of age or older, understood the informed consent form seeking their response before any procedure, and proceeded to sign it.

[0045] Diagnosis was confirmed as locally advanced stage melanoma histology or metastatic lesion according to the American Joint Committee on Cancer (AJCC). Clinical characteristics of the patients participating in this study, such as gender, mutation, therapy, LDH level, were referenced to those of patients participating in the Istituto Nazionale per la Cura dei Tumori “Fondazione G. Pascale” or Istituto Nazionale Tumori “Regina Elena” (IFO).

[0046] Isolation and Evaluation of cfMRNA Before the start of therapy, the miRNeasy Mini Kit (Qiagen) was used according to the manufacturer's instructions to extract circulating miRNAs from the sera of 70 melanoma patients. Since total RNA concentration could not be detected using both the Nanodrop system and the Qubit assay, it was arbitrarily determined to reverse-transcribe 4 microliters per sample, similar to a previously reported study

[46] . After extraction, the expression levels of miRNAs were analyzed using TaqMan MicroRNA assay probes. Real-time PCR of miR-204-5p, miR-199b-5p, miR-579-3p, miR-9-5p, miR-4443, and miR-4488 was analyzed using TaqMan Gene Expression. Circulating miRNA data were normalized using global mean (GMN) normalization and the web tool RefFinder (RF) (HYPERLINK “http: / / www.ciidirsinaloa.com.mx / RefFinder-master / ”http: / / www.ciidirsinaloa.com.mx / RefFinder-master / )

[49] .

[0047] To perform GMN, the arithmetic mean of the Ct values resulting from qRT-PCR analysis was calculated for each individual sample. This parameter was then used as a reference value to be subtracted from all individual miRNA values to obtain the normalized levels of expression of each miRNA candidate (see below for results).

[0048] To perform RF method, a comprehensive web-based tool developed to evaluate and screen reference genes from an extensive experimental dataset was collated. Specifically, this tool collates the results of four different algorithms (i.e., geNorm, Normfinder, BestKeeper, and comparative Delta-Ct method) and enables the identification of the most stable biomarkers from a given pool of expression data.

[0049] For the purpose of analysis, progressive disease (PD)-specific conditions were regarded as stable variables, and ΔCt miRNA values were divided into two groups based on the cut-off established using the receiver operating characteristic (ROC) curve. Overall survival (OS) analysis and progression-free survival (PFS) analysis were performed by the Kaplan–Meier product-limit method. Specifically, it was used to obtain the graph of the Kaplan–Meier

[50] plotter site (HYPERLINK “https: / / kmplot.com / analysis / ”https: / / kmplot.com / analysis / ). The log-rank test was used to demonstrate the existence of any statistical significance between subgroups (p-value < 0.05). In addition, the raw Ct values of two miRNAs and their miRRatio (ratio miR-4488:miR-579-3p) were incorporated into the test and the same analysis was performed. The full values of AUC, p-value, and cut-off obtained by GM, RF, and Ct are reported in Tables 1, 3, and 4, respectively. Finally, a forest plot graph

[51] was created to compare the results of various univariate and bivariate analyses related to OS and PFS. The variables used in this analysis were the expression values of two miRNAs (obtained from GM, RF method, or their raw Ct) and the LDH value.

[0050] Results Circulating levels of miR-579-3p and miR-4488 identify BRAF melanoma patients who benefit from targeted therapy. In this retrospective study (Figure 1), serum samples from 70 BRAF-mutated melanoma patients were analyzed, who were referred from two cancer centers, namely, the National Cancer Institute IRCCS “G. Pascale Foundation” in Naples and The Regina Elena National Cancer Institute (IRE) in Rome. All progressive melanoma patients were treated with MAPKi (BRAF inhibitor alone or in combination with a MEK inhibitor) as first-line therapy. Circulating microRNAs were extracted from baseline serum samples (i.e., samples collected before the start of therapy) according to the procedure described in the Materials and Methods section. MiRNA levels were analyzed by qRT-PCR. Six miRNAs that have already been identified in the literature: three oncomiRs (i.e., miR-9-5p, miR-4443, and miR-4488) and three miRNA tumor suppressors (i.e., miR-199b-5p, miR-204-5p, and miR-579-3p) were analyzed [45,46]. Given the absence of reference miRNAs in serum, circulating miRNA data were normalized using two different methods: global mean normalization (GMN)

[46] and RefFinder, a web-based comprehensive tool developed to evaluate and screen reference genes from a wide range of experimental datasets. In addition, as shown below, it was decided to add the cycle threshold (Ct value) to the assay for analysis. The data obtained were used to generate ROC curves and Kaplan–Meier survival curves. The results showed that the ratio of miR-4488 levels to miR-579-3p levels (miRatio) was the optimal predictor for response to MAPKi therapy. The overall picture of the study is schematically shown in Figure 1.

[0051] First, patients were determined to be divided into two groups based on the RECIST criteria: a) those who benefited from treatment with BRAF and MEK inhibitors, and b) those in whom the disease progressed (PD). Specifically, the first group was represented by patients who had experienced complete response, partial response, or stable disease (collectively disease control or DC) [52, 53]. The second group was represented by patients in whom response to therapy was not achieved, resistance to MAPKi developed, and progressive disease ensued (PD). The expression level of each miRNA was represented by the 2^-dCt value obtained in GMN (Figs. 2 - 7)

[46] .

[0052] Of the six miRNAs analyzed, the results revealed that only miR-4488 (Fig. 2) and miR-579-3p (Fig. 3) showed significantly different expression (p < 0.05) between the two groups. In particular, melanoma patients experiencing faster PD were characterized by higher circulating levels of miR-4488 compared to patients experiencing DC. miR-579-3p levels showed the opposite trend. For the other miRNAs evaluated, no significant results were obtained in discriminating PD patients from DC patients (Figs. 4 - 7). Based on these results, further studies focused on these two miRNAs.

[0053] Based on the RECIST criteria, 70 melanoma patients were further divided into four groups: CR = complete response; PR = partial response; SD = stable; PD = progressive, and the distribution of miR-4488 and miR-579-3p was evaluated (Figs. 8 and 9). Interestingly, for miR-4488, the highest expression levels were found in basal serum samples from patients who developed resistance to MAPKi treatment (Fig. 8). The opposite trend was observed for miR-579-3p, whose expression levels decreased stepwise from CR patients to PD patients (Fig. 9). Furthermore, a significant negative Spearman correlation was observed between the circulating levels of miR-4488 vs miR-579-3p in basal samples (Fig. 10).

[0054] Therefore, from these data, it can be concluded that the circulating levels of miR-579-3p, a tumor suppressor, and miR-4488, a cancer miR, can identify BRAF mutant melanoma patients who will or will not benefit from targeted therapy with BRAF and MEK inhibitors before the start of treatment with MAPKi.

[0055] The relative ratio of circulating mir-4488 to miR-579-3p predicts response to targeted therapy in BRAF-mutant melanoma patients. A useful approach for assessing the expression levels of miRNAs in biological fluids is to determine their expression ratios, especially when including anti-correlated candidates in the study [42, 43]. For this purpose, the relative ratio of the circulating levels of miR-4488 to miR-579-3p was calculated based on the GMN value. The results clearly showed that the miRRatio significantly discriminates BRAF mutant melanoma patients characterized by DC responders vs PD responders (P < 0.05). Specifically, higher levels of this parameter were observed in the basal samples from patients who developed PD earlier. These data suggest that patients characterized by circulating miR-4488 levels that are dominant over miR-579-5p levels show the worst response to MAPKi (Figure 11). These findings were confirmed when patients were divided into four groups, namely CR, PR, SD, and PD, based on the RECIST criteria (Figure 12).

[0056] The challenge in cancer therapy is the development of tools for predicting the efficacy of a certain therapy in patients. Therefore, the potential predictive ability of the combination of upregulation of miR-4488 and downregulation of miR-579-3p was evaluated. These expression levels before the start of therapy were used to construct a receiver operating characteristic (ROC) curve. The area under the curve (AUC) was determined, and parameters related to sensitivity, specificity, and accuracy were collectively evaluated to assess the performance of each classifier in a single measurement. Specifically, an AUC value of 0.699 was obtained for miR-579-3p, and miR-4488 was 0.649 (Figure 13). Preferably, the highest AUC value, i.e., the optimal predictive value represented by 0.729, was observed for miRatio compared to individual miRNAs (Figure 13) (p-value < 0.5).

[0057] The cut-off value calculated from the ROC curve was used to generate a Kaplan-Meier curve to estimate whether the basal miRNA expression level was predictive of progression-free survival (PFS in months). The results of the Kaplan-Meier curve clearly showed that high expression levels of miR-579-3p before the start of therapy were predictive factors for improved PFS in metastatic melanoma patients compared to patients with lower levels of this miRNA (Figure 14). As shown in the Kaplan-Meier curve (Figure 15), the opposite result was obtained for miR-4488. Most importantly, the optimal value of predicted PFS based on statistical significance (p = 0.0024 in the log-rank test) was observed in the Kaplan-Meier curve plotted using the miRatio value (Figure 16). These results are consistent with those of the ROC curve. The summary of values used for graphing is reported in Table 1. Specifically, Table 1 reports the AUC, p-value, and cut-off value obtained by global mean (GM) normalization.

[0058]

Table 1

[0059] Next, we investigated whether the circulating levels of these miRNAs could also predict the overall survival (OS) of melanoma patients. Again, the ROC and Kaplan–Meier curves were plotted using OS as the hypothesis parameter (Figs. 17–20). The results revealed that miR-579-3p, miR-4488, and miRRatio could not predict survival, thus suggesting their specificity as parameters for monitoring only these PFSs.

[0060] Finally, to strengthen the results, we tested another normalization method, normalization by ReFinder, which functions by comparing various normalization methods, to determine the most stable gene to use as a reference for normalization, as described above (Table 2). Using this approach, among the miRNA candidates, the miR-199b-5p level was found to vary less between various samples and was used as the reference miRNA. From this, the levels of all other miRNA candidates (miR-204-5p, miR-579-3p, miR-9-5p, miR-4443, and miR-4488) were normalized against the miR-199b-5p expression level.

[0061] Table 2 reports the results of different normalizations by the RefFinder method and identifies miR-199b-5p as the most stable candidate to be used later as a reference miRNA.

[0062]

Table 2

[0063] Considering the expression levels of the six miRNAs, among the 70 serum samples tested, the circulating level of miR-199b-5p was observed to be the most stable, and thus it was used as the reference miRNA for the analysis (Figure 21). Interestingly, also in this case, and in agreement with the GMN results, it was confirmed by the ROC curve that the miRRatio yielded the best AUC value (0.728) (Figure 22). These results were used for the plot of the Kaplan–Meier curve, which demonstrated that a higher miRRatio value predicted a worse PFS compared to when this parameter was low (Figure 23). Table 3 reports the summary of the values used to generate the graph by the RF method. Here, the AUC, p-value, and cut-off values obtained by the normalization of RefFinder (RF) are reported.

[0064]

Table 3

[0065] In conclusion, the ratio of miR-4488 / miR-579-3p can predict the efficacy of targeted chemotherapy in melanoma patients.

[0066] Absolute miRNA expression values can predict the development of drug resistance. In this part of the study, it was decided to incorporate directly into the test not only the cycle threshold (Ct value), i.e., the absolute expression levels of miR-579-3p and miR-4488, but also their ratio. The goal was to determine whether these parameters were effective in predicting the success of targeted therapy even before the start of treatment. Measuring miRNA as an absolute expression level is interesting because it is advantageous compared to a plurality of miRNAs in a normalization control group and the interpretation of the results becomes easier. The data was plotted on an ROC curve. As shown in Figure 24, the measured values of a single miRNA yielded excellent AUC values. In addition, in this case, the miRRatio (based on the absolute Ct value) also generated an ROC curve with an improved AUC value (0.724) and a higher significance (p-value < 0.05). Again, it was confirmed by the Kaplan-Meier curve plotted using the ROC cut-off that higher circulating levels of miR-579-3p predicted better PFS (Figure 25). As expected, higher levels of miR-4488 were associated with the worst PFS in melanoma patients (Figure 26). Finally, the previous findings could also be confirmed from the miRNA ratios obtained using the CT values (Figure 27).

[0067] Finally, these results were also plotted as a bar graph, with the ROC curve-derived CT cut-off values used to divide melanoma patients into groups with high or low expression of each of miR-579-3p and miR-4488. The resulting graph shows that the group of patients with CT cut-off values below the median, i.e., the group composed of those with high miR-579-3p expression, is enriched for long PFS compared to the group of patients with CT cut-off values above the median (Figure 28). The reverse is also true for miR-4488 (Figure 29). The data obtained by CT values are summarized in Table 4, which reports the AUC, p-value, and cut-off values obtained by absolute Ct evaluation.

[0068]

Table 4

[0069] miR-579-3p and miR-4488 are better predictors of PFS compared to LDH. To obtain predictive values by combining miRNA levels alone or with measured values of lactate dehydrogenase (LDH) levels in the blood, univariate and multivariate analyses were performed. The baseline LDH value is widely known to represent a major prognostic factor associated with the overall survival of patients with progressive melanoma [54, 55]. First of all, according to previous findings, univariate analysis showed a significant effect size for miR-579-3p, miR-4488, and miRRatio to predict PFS with all normalization methods used. The hazard ratio (HR) value of oncogenic miR-4488 was >1, indicating that its expression is a risk factor for PFS (Figure 30). The opposite was true for the tumor suppressor miR-579-3p, and the HS result was <1, which was classified as a protective factor (Figure 30). In contrast, LDH showed no association with PFS in univariate analysis, as shown by the confidence interval. Further considering the multivariate subgroup of the analysis, it was observed that the combination of LDH with circulating miRNA alone or in combination did not produce any improvement in HR in predicting PFS (Figure 30). Furthermore, the forest plot graph showed that the modulation of miR-579-3p and miR-4488 was not associated with OS in both univariate studies and in combination with LDH (bivariate study) (Figure 31). The lack of association between the LDH parameter and PFS was also confirmed from the ROC curve (Figure 32). It is important to note that, consistent with other reported data [10, 55, 56], modulation of LDH alone produced a significant association with OS. Similarly, the ROC curve showed a significant AUC value of 0.647 (Figure 33). As predicted, the Kaplan–Meier graph did not show a significant association with the PFS parameter (Figure 34), but high levels of LDH in the baseline serum samples were significantly associated with the worst OS (p = 0.0379 in the log-rank test) (Figure 35). These data enabled the conclusion that miR579-3p and miR-4488 are better predictors of PFS than LDH.

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Claims

1. A method for identifying non-responding tumor patients for anti-tumor therapy by BRAF inhibitor alone or in combination with a MEK inhibitor, comprising: measuring the expression of both miR-579-3p and miR-4488, which are microRNAs, in a biological sample of a tumor patient before the start of the anti-tumor therapy; calculating the ratio of the expression of miR-4488 to the expression of miR-579-3p; and when the ratio is higher than the ratio of the expression of miR-4488 to the expression of miR-579-3p measured from a biological sample of a responding tumor patient who received the same anti-tumor therapy before the start of the anti-tumor therapy, the tumor patient is a non-responding tumor patient.

2. The method according to claim 1, wherein when the tumor patient is a non-responding tumor patient, the ratio is higher than a cut-off ratio value obtained in the following steps: Before the start of anti-tumor therapy by BRAF inhibitor alone or in combination with a MEK inhibitor, measure the expression of both miR-579-3p and miR-4488, which are microRNAs, in biological samples of a tumor patient population, wherein the tumor patient population includes a group of non-responding tumor patients and a group of responding tumor patients; for each tumor patient, calculate the ratio of the expression of miR-4488 to the expression of miR-579-3p; obtain a cut-off ratio value by an ROC curve to distinguish non-responding tumor patients from responding tumor patients.

3. the tumor patient is a non-responding tumor patient; the measured expression of miR-579-3p from the biological sample of the tumor patient is lower than the expression of miR-579-3p measured from a biological sample of a responding tumor patient who received the anti-tumor therapy before the start of the anti-tumor therapy; and the measured expression of miR-4488 from the biological sample of the tumor patient is higher than the expression of miR-4488 measured from a biological sample of a responding tumor patient who received the anti-tumor therapy before the start of the anti-tumor therapy. The method according to claim 1 or 2.

4. The method according to any one of claims 1 to 3, wherein the measured expression of miR-579-3p and the measured expression of miR-4488 are determined as absolute values.

5. The method according to any one of claims 1 to 3, wherein the measured expression of miR-579-3p and the measured expression of miR-4488 are normalized with respect to the expression of miR-579-3p, miR-4488, miR-204-5p, miR-199b-5p, miR-9-5p and miR-4443.

6. The method according to any one of claims 1 to 3, wherein the measured expression of miR-579-3p and the measured expression of miR-4488 are normalized against the expression of miR-199b-5p.

7. The method according to any one of claims 1 to 6, which is measured by real-time PCR, droplet digital PCR, microarray, RNA hybridization methods such as Northern blot or dot blot, RNA next-generation sequencing, preferably real-time PCR.

8. The method according to any one of claims 1 to 7, wherein the BRAF inhibitor is selected from vemurafenib, dabrafenib, encorafenib, and the MEK inhibitor is selected from cobimetinib, trametinib, binimetinib.

9. The method according to any one of claims 1 to 8, wherein the tumor patient is a patient suffering from a BRAF mutant tumor.

10. The method according to any one of claims 1 to 9, wherein the tumor patient is a patient suffering from a tumor selected from the group consisting of melanoma, colorectal cancer, papillary thyroid cancer, non-small cell lung cancer, brain tumor, non-Hodgkin lymphoma.

11. The method according to any one of claims 1 to 10, wherein the biological sample is a liquid biological sample such as blood, serum, plasma, urine.

12. A method for obtaining a cut-off ratio value for identifying non-responding tumor patients from responding tumor patients to an anti-tumor therapy with a BRAF inhibitor alone or in combination with a MEK inhibitor, before the initiation of anti-tumor therapy with a BRAF inhibitor alone or in combination with a MEK inhibitor, measuring the expression of both miR-579-3p and miR-4488, which are microRNAs, from a biological sample of a tumor patient population, the tumor patient population including a non-responding tumor patient group and responding tumor patients, calculating, for each tumor patient, the ratio of the expression of miR-4488 to the expression of miR-579-3p, the method comprising obtaining a cut-off ratio value from an ROC curve.

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