WO2022096486A1

WO2022096486A1 - Methods of diagnosing and/or prognosing a disease in tears

Info

Publication number: WO2022096486A1
Application number: PCT/EP2021/080467
Authority: WO
Inventors: Ozan Fidan
Original assignee: Ideogen Ag
Priority date: 2020-11-03
Filing date: 2021-11-03
Publication date: 2022-05-12

Abstract

The invention relates to methods of diagnosing and/or prognosing stratifying, determining the progression or regression of a disease based on the detection of one or more metabolite profiles in tears.

Description

Methods of diagnosing and/or prognosing a disease in tears

FIELD OF THE INVENTION

The invention relates to methods of diagnosing and/or prognosing stratifying, determining the progression or regression of a disease based on the detection of one or more metabolite profiles in emotional tears.

BACKGROUND OF THE INVENTION

Finding reliable markers to detect diseases (such as cancers, infectious diseases, immune diseases, neurological and a neurodegenerative diseases), is often a great challenge. Furthermore, the method for detecting the presence of these markers in a sample must be sensitive while not being (too) invasive and the results obtained must be reliable, easily interpretable and reproducible.

Glioblastoma multiforme (GBM) is a highly malignant primary tumor of the central nervous system and most common and lethal of all primary malignant brain tumors (13-16 % of all brain tumors). The current standard therapy is based on oral Temozolomide (TMZ) combination with radiotherapy. Isocitrate dehydrogenase 1 (IDH1) and IDH2 mutations are well known clinical markers of GBM disease. Because of IDH1 and IDH2 mutations, mutated enzymes triggers to produce 2-hydroxyglutarate (2HG) instead of 2-oxoglutarate. There are several LC/MS based 2- HG quantification methods which were validated for gliomas based on human plasma sampling. Relevance of increased levels of 2-hydroxyglutarate (2-HG) and glioblastoma have been shown by investigators. 2-HG is clinically relevant biomarker not only for glioblastoma but also for other neurological diseases such as, e.g. acute myeloid leukemia. 2-HG quantification in human plasma is well known tool for detection of IDH mutations.2- hydroxy glutarate has 2 enantiomers L( L2HG) and D (D2HG).

However, regarding complexity of human plasma as well as false-positive and false-negative interpretation of results, 2-HG quantification of GMB patients needs to combine integrative test methods such as next generation sequencing (NGS) technologies and MR. Thus, there is an unmet need for a reliable and very sensitive method of diagnostic and/or prognostic of diseases such as cancer, infectious disease, neurological disease and/or neurodegenerative disease in tears.

BRIEF DESCRIPTION OF THE FIGURES

Figure 1: TOF MS ES: Electrospray time-of-flight mass spectrometry - A) LC-IMS-MS chromatogram of CSF samples of GBM patients, Tears samples of Controls and Tears samples of GBM patients which indicates 2-HG existence only in tears of GBM patients. 2-HG could not be detected neither in samples of Cerebrosipinal Fluid of GBM patients nor in samples of Control (Healty Volunteers). B) display of 2-HG peaks at LC-IMS-MS chromatogram. Both chromatograms are demonstrating the presence of 2-HG in tears of GBM patient 1 (20191025_P3272_6172_l_mSOPl_neg_GBT_l ) and GBM patient 2 (20191025_P3272_6172_2_mSOP l_neg_GBT_2).

Figure 2: Comparison of control samples (3 points left), relapse samples of GBM patients (3 points at right).

Figure 3: Experimental data for GBM patients stratification and disease phenotyping as clinical assessment tool. The stratification of GBM patients is based on 2-HG existence (presence).

Figure 4: PCA analysis of GBM patients A) 2D diagram This figure illustrates the success of LC-IMS-MS analysis for stratification of metabolite content of different patient groups. B) 3D diagram depicting spatial biology of metabolite profile of GBM. Discrimination of different groups can clearly be seen (GBM pretherapy, GBM posttherapy, GBM relapse and Control).

Blank: Blank samples for analysis, Control: Metabolites of healty volunteers, GBTpost: Metabolite samples of post therapy GBM patients, GBTpre: Metabolite samples of pre therapy GBM patients, GBTrelap: metabolite samples of relapse GBM patients. Figure 5: 2-HG existence (presence) in different groups of patients (GBM Phenotyping) as prognostic tool for GBM. 2-HG presence in pre-therapy, post-therapy and control (healthy volunteers) groups. This figure also shows the possibility to discriminate the risk of relapse and therapeutic success rate. Blank: Mixture for analysis, Pool: Mixture of all oncometabolites, Rel: Samples of Relapse Patients, Ctrl: Samples of Controls, Pre: Samples of Pre-Therapy, Post: Samples of Post-Therapy.

Figure 6: Concentration (ng/ml) comparison of 2-HG, Glutamic acid (Glu), Glutamine (Gin) 2-HG analysis by LC-IMS-MS. 2-HG is separated on the drift time axis from other compounds (Isototopologues of Glutamate and Glutamine).

Figure 7: 2-HG tear concentrations (multiplied concentrations to evaluate difference between different patients -relative concentration in ng/ml ) in 3 patients at different stages of GBM

Figure 8: Quantitative Enrichment Analysis (metaboanalyst.ca) showed Biotinidase deficiency in group of GBM patients. Biotinidase deficiency causing Biotin metabolism aberration. These data show that biotinidase deficiency may enroll pathology of GBM. Also metabolites from tears of GBM patients show similarity in terms of metabolic pattern with Alzheimer’s disease because of inflammation driven pathology.

DESCRIPTION OF THE INVENTION

Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. The publications and applications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. In addition, the materials, methods, and examples are illustrative only and are not intended to be limiting. In the case of conflict, the present specification, including definitions, will control. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as is commonly understood by one of skill in art to which the subject matter herein belongs. As used herein, the following definitions are supplied in order to facilitate the understanding of the present invention.

Reference throughout this specification to "one aspect", "an aspect", "another aspect", "a particular aspect", "combinations thereof' means that a particular feature, structure or characteristic described in connection with the invention aspect is included in at least one aspect of the present invention. Thus, the appearances of the foregoing phrases in various places throughout this specification are not necessarily all referring to the same aspect. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more aspects.

The term "comprise(s)", or "comprising" is generally used in the sense of include(s)/including, that is to say, permitting the presence of one or more features or components. The terms "comprise(s)" and "comprising" also encompass the more restricted ones "consist(s)" and "consisting", respectively.

As used in the specification and claims, the singular form "a", "an" and "the" include plural references unless the context clearly dictates otherwise.

As used herein, "one or more" metabolite(s) means "at least one" metabolite, e.g. a combination of two, three, four, five, six, etc. . . metabolites.

The term “about”, particularly in reference to a given quantity or percentage, is meant to encompass deviations of plus or minus ten (10) percent (+/- 10%). For example, about 5 % encompasses numeral between, and including, 4.5% and 5.5%.

The term “level,” when used in reference to a particular metabolite in a sample in the present application, means an absolute level (e.g. count per second (cps)) or a relative level such as a percentage or fraction compared to one or more other molecules in said sample.

The term “amount,” when used in reference to a particular metabolite in a sample in the present application, means concentration of said particular metabolite in said sample. In view of the above, it is understood that an amount can be a molar concentration (mol/L) or weight concentration (e.g. pg /mol, ng/mol, pg/mol, efc...)

Determining both the amount and the level of a metabolite of the invention is also within the scope of the present invention.

In one aspect, the disease is selected from the group comprising, or consisting of, a cancer, an infectious disease, an immune disease, a neurological disease and a neurodegenerative disease or a combination of one or more thereof.

In one aspect, the cancer is solid or a liquid cancer.

Non-limiting liquid cancers are selected from the group comprising acute myeloid leukemia, lymphatic leukemia, lymphocytic leukemia, and lymphoblastic leukemia.

In one aspect, the disease is tumor affecting the brain, whether noncancerous or cancerous. Nonlimiting brain cancers are selected from the group comprising acoustic neuroma, astrocytoma, brain metastases, choroid plexus carcinoma, craniopharyngioma, embryonal tumors, ependymoma, glioblastoma, glioma, medulloblastoma, meningioma, oligodendroglioma, pediatric brain tumors, pineoblastoma, pituitary tumors, and a combination of one or more thereof. In one preferred aspect, the brain cancer is glioblastoma, more preferably glioblastoma multiform.

Noncancerous (benign) tumors affecting the brain are also considered in the present invention.

In one aspect, the disease is an infectious disease. Non-limiting examples of infectious diseases include those selected from the group comprising Covid- 19, septicemia, meningitis, myelitis, encephalitis, influenza, and pneumonia.

In one aspect, the disease is a neurological disease or a neurodegenerative disease. Non-limiting examples of neurological disease or a neurodegenerative disease include those selected from the group comprising Parkinson’s disease, Alzheimer’s disease as well as any other tauopathy such as progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), argyrophilic grain disease (AGD) and Pick’s disease, amyotrophic lateral sclerosis (ALS), meningitis, ataxia, epilepsy and seizures, Guillain-Barre syndrome, multiple sclerosis (MS), strokes, Huntington's disease, prion diseases and a combination of one or more thereof. As used herein the terms "subject"/" subject in need thereof, or "patient" /"patient in need thereof " are well -recognized in the art, and, are used interchangeably herein to refer to a mammal, including dog, cat, rat, mouse, monkey, cow, horse, goat, sheep, pig, camel, and, most preferably, a human. In some cases, the subject is a subject in need of treatment or a subject with a disease or disorder. However, in other aspects, the subject can be a normal subject, i.e. a healthy subject. The term does not denote a particular age or sex. Thus, adult and newborn subjects, whether male or female, are intended to be covered. Preferably, the subject is a human, most preferably a human suffering from a disclosed described herein or a human that might be at risk of suffering from a disease disclosed herein.

The term "tears" refers to basal tears, reflex tears or emotional tears.

Basal tears are basic functional tears that are released continuously in tiny quantities to lubricate the cornea and keep it clear of dust. Basal tears also fight against bacterial infection as a part of the immune system.

Reflex tears or irritant tears result from irritation of the eye by foreign particles, or from the presence of irritant substances such as vapors from chopping onions, or having any kind of perfume or fragrance, tear gas, or pepper spray in the eye’s environment. These tears can also occur with bright light and hot or peppery stimuli to the tongue and mouth. They are released in much larger amounts than basal tears.

Emotional or psychic tears are referred to as crying or weeping. These tears are associated with all emotions and are often brought on by strong emotional stress, anger, suffering, mourning, or physical pain.

Preferably, the tears of the invention are emotional tears.

Any technique and method known in the art for obtaining and collecting emotional tears from a subject are contemplated in the methods described herein as long as they are fast, non- invasive, inexpensive, easy to use, and with minimal risk of injury to the subject. Non-limiting examples comprise direct and non-direct methods selected from microcapillary tubes (MCT) or micropipettes such glass or polyester fiber rod which will be placed in contact intermittently with the tear fluid, absorbing supports such as Schirmer test strips (STS), filter paper disks, cellulose sponges and polyester rods. Once collected, solvent can optionally be added to the tear samples and they will be either frozen or analyzed before degradation of the metabolites. The solvent will be either polar or non-polar solvent. A preferred polar solvent will be alcohol, most preferably methanol, even more preferably 98-99% of methanol.

Tears can be collected either without previous stimulation (non-stimulated tears) or after previous stimulation or instillation of different volumes of sterile saline (stimulated tears).

Tears can be collected from any part of the eye, in particular they can be collected from one or more of the following part(s): lower fornix, cul-de-sac, upper punctum, plica semilunaris, lower punctum, lateral canthus, and caruncle.

In an aspect of the invention, the tears, once collected, can be stored frozen (at -20 to -80°C or in liquid nitrogen) theoretically, for years protected from degradation.

Tears can be obtained and collected from a subject in need of treatment or a subject with a disease or disorder or from a healthy donor.

The detection of the one or more metabolite profile(s) (i.e. qualitative and/or quantitative tear metabolites) comprises determining the presence, the amount and/or the level of said metabolite(s). Non-limiting detection and examination methods include one- and two- dimensional gel electrophoresis, ELISA, high performance liquid chromatography (HPLC), mass spectrometry (MS) related techniques such as MS-MS, matrix-assisted laser desorption/ionization time-of-flight MS, surface enhanced laser desorption/ionization time-of- flight MS, Liquid chromatography coupled to mass spectrometry (LC/MS), Liquid chromatography coupled to mass spectrometry and ion mobility spectrometry (LC-IMS-MS), various antibody arrays, multiplex bead analysis, NMR, Western blot analysis, etc. . . Preferably, LC-IMS-MS is used to detect the one or more metabolite profile of the invention.

The present invention is based, in part, on surprising results showing that the presence of one or more metabolites in emotional tears can correlate with the presence, the stratification as well as the progression or regression of a disease. An aspect of the invention concerns a method of diagnosing a disease in a subject comprising:

(a) detecting the profile of one or more metabolite(s) in emotional tears obtained from said subject;

(b) comparing the subject's metabolite profile to a healthy control metabolite profile for the same metabolite(s); and

(c) identifying differences between the subject's metabolite profile and the healthy control metabolite profile; wherein a variation in the profile of said one or more metabolite(s), or an enantiomer thereof, in the subject's metabolite profile as compared to the healthy control metabolite profile indicates the presence of a disease in the subject.

An aspect of the invention concerns a method of diagnosing a disease in a subject comprising:

(c) identifying differences between the subject's metabolite profile and the healthy control metabolite profile; wherein at least one metabolite is 2 -hydroxyglutarate (2-HG), or an enantiomer thereof, and wherein a variation in the profile of said one or more metabolite(s), or an enantiomer thereof, in the subject's metabolite profile as compared to the healthy control metabolite profile indicates the presence of a disease in the subject.

The one or more metabolite(s), as disclosed herein, refer to both untargeted and targeted metabolites, and will be selected from the non-limiting group comprising, or consisting of, amino acids (L or D-forms), lipids, carbohydrates, nucleotides, nucleosides, hormones, organic acids, and any small molecule, any derivative thereof or any combination thereof. In some aspects of the invention, the one or more metabolite is selected from the group comprising 2-hydroxyglutarate (2-HG) or an enantiomer thereof. Examples of 2-HG enantiomers include D-2-HG and L-2-HG.

2-HG, and in particular its D-enantiomer (D-2-HG) is regarded as an oncometabolite. It is found at elevated levels in plasma in certain malignancies such as acute myeloid leukemia and glioma (e.g. glioblastoma multiforme). It is produced by a mutated isocitrate dehydrogenase IDH1/2, a low-affinity /high-capacity enzyme D-2-HG (Berger, R.S. et al. Degradation of D-2- hydroxyglutarate in the presence of isocitrate dehydrogenase mutations. Sci Rep 9, 7436 (2019).

In some aspects of the invention, the one or more metabolites is selected, apart from 2-HG, from the group of amino-acids comprising Alanine, Arginine, Asparagine, Aspartic Acid, Cysteine, Glutamic acid, Glutamine, Glycine, Histidine, Isoleucine, Leucine, Lysine, Methionine, Phenylalanine, Proline, Serine, Threonine, Tryptophan, Tyrosine, Valine, Pyrrolysine and Selenocysteine, or an enantiomer or a salt thereof. In a preferred aspect, the amino acid is Glutamic acid or its anionic form Glutamate, or an enantiomer or a salt thereof.

A combination of one or more metabolites can include, e.g. an amino acid and as small molecule, e.g. an oncometabolite such as 2-hydroxyglutarate (2-HG) or an enantiomer thereof. Preferably, the combination of one or more metabolites comprises i) Glutamic acid or its anionic form Glutamate, or an enantiomer or a salt thereof and 2-hydroxyglutarate (2-HG) or an enantiomer thereof, ii) 2-hydroxyglutarate (2-HG) or an enantiomer thereof and cysthiatonine or an enantiomer thereof, iii) 2-hydroxyglutarate (2-HG) or an enantiomer thereof and tryptophan or an enantiomer thereof, iv) 2-hydroxyglutarate (2-HG) or an enantiomer thereof and diethylthiophosphate, v) 2-hydroxyglutarate (2-HG) or an enantiomer thereof and lysin or an enantiomer thereof, and vi) 2-hydroxyglutarate (2-HG) or an enantiomer thereof and ascorbic acid or any derivative thereof.

The methods of the invention comprise the steps of comparing the subject's metabolite profile(s) to a healthy control metabolite profile (e.g. subject not affected by a disease or by a disease of the invention) for the same metabolite biomarker and identifying differences between the subject's metabolite profile and the healthy control metabolite profile. A variation in the profile of the one or more metabolite(s), in particular of 2-hydroxyglutarate (2- HG), or one of its enantiomers, in the subject's metabolite profile as compared to the healthy control metabolite profile indicates the presence of a disease in the subject. This variation identification can comprise i) the presence of a metabolite that was not detected in the healthy control metabolite profile, ii) the absence of a metabolite that was detected in the healthy control metabolite profile, iii) an increase or decrease in the amount and/or level of said metabolite when compared to the healthy control metabolite profile, as well as iv) a variation of the ratio between two or more metabolites (e.g. 2-HG/Glutamate) or between one metabolite and one or more lipid metabolite profile.

As shown in the examples and figures, analysis of the subject's PCA (Principal Component Analysis) and comparing it with the PCA of a healthy control is also considered in the present application.

The increase in the amount and/or level of said one or more metabolite when compared to the healthy control metabolite profile in tears sample according to the methods of the present invention refers, usually, to an increase of equal or superior to about 5 %, preferably equal or superior to about 20 %, more preferably equal or superior to about 40 %, most preferably equal or superior to about 60 %, more preferably equal or superior to about 500%, even more preferably equal or superior to about 1000 %, in particular equal or superior to about 5000 %. The decrease in the amount and/or level of said one or more metabolite when compared to the healthy control metabolite profile in tears sample according to the methods of the present invention refers, usually, to a decrease of equal or superior to about 5 %, preferably equal or superior to about 20 %, more preferably equal or superior to about 40 %, most preferably equal or superior to about 60 %, more preferably equal or superior to about 500%, even more preferably equal or superior to about 1000 %, in particular equal or superior to about 5000 %.

Referring in more details to the examples, we have shown that: the level of 2-HG is higher in GBM tumor samples than in healthy control, the level of lysine (1.63 145.1015) is lower in GBM tumor samples than in healthy control, the level of ascorbic acid derivatives (1.09 126.9912) is lower in GBM tumor samples than in healthy control, the level of L-cystathionine (1.95^221.0642) is lower in GBM tumor samples than in healthy control, the level of L-tryptophan (2.12J203.0871) is higher in GBM tumor samples than in healthy control, the level of diethylthiophosphate (1.52 169.0028) is higher in GBM tumor samples than in healthy control.

The present invention also encompasses a method of stratifying a disease in a subject comprising:

(b) comparing the subject's one or more metabolite profile to a healthy control metabolite profile for the same metabolite biomarker; and

(c) identifying differences between the subject's one or more metabolite profile and the healthy control metabolite profile; wherein at least one metabolite is 2 -hydroxyglutarate (2-HG), or an enantiomer thereof, and wherein a variation in the profile of the level of said one or more metabolite(s), or an enantiomer thereof, in the subject's metabolite profile as compared to the control metabolite profile is indicative of the disease stage or grade.

According to comparison of targeted metabolomics profile of pretherapy and post therapy patients, existence of 2-HG has been investigated at relapsed GBM patients correlatively pretherapy GBM patients. In terms of disease stratification of post therapy GBM patients, as divided into post therapy GBM patients and relapsed GBM patients, significant discrimination at principal component analysis (PCA) has been observed. Patient stratification analysis was performed as tears phenotyping at several stages GBM patients between February - March 2020 (Fig. 3). In one aspect, the level of 2-HG is higher in pre therapy GBM patients than in a healthy subject (healthy control). Correct

In one aspect, the level of 2-HG is lower in post therapy GBM patients than in healthy subject (healthy control) or pre therapy GBM patients (control metabolite profile). Correct

In one aspect, the level of 2-HG is higher in relapsed GBM patients than in healthy subject (healthy control), pre therapy GBM patients or post therapy GBM patients (e.g. control metabolite profiles).

In one aspect, level of 2-HG in relapse patient can increase and reach to same level of pre therapy period of patient, depending on metastasis pathways and clonogenicity of cancer cells, 2- HG level in relapse samples can exceed level of 2-HG in pre-therapy period of GBM patients.

Also encompassed is a method of determining the progression or regression of a disease in a subject suffering from said disease, said method comprising

(a) detecting the profile of a one or more metabolite(s) in emotional tears obtained from said subject;

(b) periodically determining the profile of said one or more metabolites, wherein at least one metabolite is 2 -hydroxyglutarate (2-HG), or an enantiomer thereof, and wherein an alteration in the profile of said 2-hydroxyglutarate (2-HG), or an enantiomer thereof, in said emotional tears, relative to the profile of said one or more metabolite(s), or an enantiomer thereof, determined previously, is indicative of the progression or regression of said disease.

Periodically means every week, month, every two months, every three months, etc. In one aspect, the periodical determination occurs every 3 months for early-stage diseases (e.g. brain tumors) and every month for late-stage tumors (e.g. brain tumors).

An alteration refers to a change in the presence, the amount and/or the level of one or more metabolite(s) of the invention.

The regression of a disease according to the methods of the present invention refers, usually, to a diminution of the presence (e.g. tumor size, . . .) or symptoms of said disease equal or superior to 5 %, preferably equal or superior to 20 %, more preferably equal or superior to 40 %, most preferably equal or superior to 60 %, more preferably equal or superior to 500%, even more preferably equal or superior to 1000 %, in particular equal or superior to 5000 % when compared to the presence or symptoms of said disease in a control biological sample of a disease-free subject, as described above.

In contrast, the progression of a disease according to the methods of the present invention refers, usually, to an augmentation of the presence (e.g. tumor size, . . .) or symptoms of said disease equal or superior to 5 %, preferably equal or superior to 20 %, more preferably equal or superior to 40 %, most preferably equal or superior to 60 %, more preferably equal or superior to 500%, even more preferably equal or superior to 1000 %, in particular equal or superior to 5000 % when compared to the presence or symptoms of said disease in a control biological sample of a disease-free subject, as described above.

According to targeted metabolomics data from several stages of GBM patients (progression investigation via targeted metabolomics research / 2-HG);

2-HG presence was found within chromatogram of emotional tears of pre-therapy GBM samples.

2-HG presence was found within chromatogram of emotional tears of post-therapy GBM samples. As can be seen from Fig. 5, 2-HG concentration is consistent with clinical condition of patient. Post-therapy patient is recently tumor resected and cured with chemotherapy however still there are plenty of cancer cells in brain. So, 2-HG existence in post therapy as lower than pre-therapy and relapse is highly significant to predict prognosis of disease.

2-HG existence was found within chromatogram of emotional tears of relapsed GBM samples. (Recurrent tumor existence at relapsed GBM patients in comply with LC-MS profiling of tears).

Surprisingly, the Inventors have also shown that lipid metabolite profiles (i.e. patterns) of, e.g. subjects suffering from GBM, are altered depending on relapse after post therapy. Therefore, in some aspects of the invention, the methods described herein further comprise a step a') comprising detecting the profile of one or more lipid metabolite in emotional tears obtained from said subject.

Further encompassed is a method of diagnosing and/or prognosing a disease in a subject comprising:

(a) detecting the profile of one or more metabolite(s) and/or metabolomic pattern in tears obtained from said subject;

(b) comparing the one or more subject's metabolite profile(s) and/or metabolomic pattern to healthy control metabolite profile(s) and/or metabolomic pattern for the same metabolite biomarker(s); and

(d) identifying differences between the subject's metabolite profile(s) and/or metabolomic pattern and the healthy control metabolite profile(s); wherein an increase or decrease in the profile of said one or more metabolite(s) and/or metabolomic pattern in the subject's metabolite profile(s) as compared to the healthy control metabolite profile(s) indicates the presence of a disease in the subject.

Further encompassed is a method for determining if a patient having a predetermined disease is responsive to a treatment, the method comprising

(b) periodically determining the profile of said one or more metabolites, wherein at least one metabolite is 2 -hydroxyglutarate (2-HG), or an enantiomer thereof, and wherein an alteration in the profile of said 2-hydroxyglutarate (2-HG), or an enantiomer thereof, in said emotional tears, relative to the profile of said one or more metabolite(s), or an enantiomer thereof, determined previously, is indicative of the response of the patient to said treatment.

Usually, an increase or decrease in the profile of said one or more metabolite(s) and/or metabolomic pattern in the subject's metabolite profile(s) as compared to the metabolite profile(s) previously (i.e. before or after the start of the treatment) determined for the same one or more metabolite(s) indicates the response of the patient to said treatment. In one aspect, this method of treatment comprises determining the progression or regression of a disease in tears of a subject suffering from said disease using a method described herein, and if the disease is not regressing, the method further comprises a step of adapting the treatment (i.e. changing the treatment or changing the dosage of the treatment).

In an aspect of the invention, any method described herein can be a computer- implemented method. The computer may include a user interface wherein said user interface relates the presence, the amount and/or the level of said one or more metabolite(s), to detecting a disease in said subject.

Also encompassed in the present invention is an assay for use in a method of anyone of the preceding claims, comprising means and/or reagents for collecting, preparing and / or determining the profile of one or more metabolite, including 2-HG, or an enantiomer thereof, in tears of a subject.

In some aspects, the assay described herein further comprises a step comprising means and/or reagents for determining the profile of one or more lipid metabolite in tears obtained from said subject.

Also provided is a kit for performing a method according to the invention, said kit comprising a) means for collecting emotional tears of a subject, b) means and/or reagents for preparing and / or determining the profile of 2-HG, or an enantiomer thereof, in said tears, and c) instructions for use.

In some aspects, the kit described herein further comprises a step b') comprising means and/or reagents for preparing and / or determining the profile of one or more lipid metabolite in tears obtained from said subject. The present invention further encompasses a device for performing a method of the invention, said device comprising a) a sample chamber for holding tears collected from a subject, b) an assay module in fluid communication with said sample chamber, said assay module comprising means and/or reagents for preparing and / or determining the profile one or more metabolite(s), in said tears, wherein said assay module comprises: a user interface wherein said user interface relates the presence, the amount and/or the level of said one or more metabolite(s), in said assay module to detecting a disease in said subject.

The present invention further encompasses methods of treatment.

In one aspect, the method of treatment comprises i) diagnosing a disease in tears, preferably in emotional tears, using a method described herein, ii) administering a treatment useful in treating said disease.

Preferably, the disease is selected from the group comprising a cancer, an infectious disease, an immune disease, a neurological disease and a neurodegenerative disease or a combination of one or more thereof.

In case the disease is cancer, then the treatment will consist in surgery, radiotherapy, chemotherapy, immunotherapy or hormone therapy, or a combination of one or more thereof.

A chemotherapy of the present invention can concern as well agents that damage DNA and / or prevent cells from multiplying, such as genotoxins. Genotoxins can be selected from the group comprising alkylating agents, antimetabolites, DNA cutters, DNA binders, topoisomerase poisons and spindle poisons. Non-limiting examples of immunotherapy include immune check point inhibitors (such as e.g.

PD1 and/or PD-L1 inhibitors, CTL4 inhibitors), adoptive T cell transfer therapy, or a combination of one or more thereof.

Radiotherapy refers to the use of high-energy radiation to shrink tumors and kill cancer cells. Examples of radiation therapy include, without limitation, external radiation therapy and internal radiation therapy (also called brachytherapy).

In case the disease is a neurological disease or a neurodegenerative disease, then the treatment will consist in cell (e.g. stem cells) and/or organelle transplantations (e.g. mitochondria transplantation, see Lightowlers RN et al. EMBO Rep. 2020 Sep 3), administration of drugs aimed to restore, minimize or compensate functional deficits, or mitigate some symptoms with surgery, or a combination of one or more thereof.

In one aspect, the method of treatment comprises determining the progression or regression of a disease in tears of a subject suffering from said disease using a method described herein, and if the disease is not regressing, the method further comprises a step of adapting the treatment (i.e. changing the treatment or changing the dosage of the treatment).

In one aspect, the method of treatment comprises stratifying a disease in tears of a subject suffering from said disease using a method described herein, and depending on the disease grade, the method further comprises a step of administering the most adapted treatment.

Those skilled in the art will appreciate that the invention described herein is susceptible to variations and modifications other than those specifically described. It is to be understood that the invention includes all such variations and modifications without departing from the spirit or essential characteristics thereof. The invention also includes all of the steps, features, compositions and compounds referred to or indicated in this specification, individually or collectively, and any and all combinations or any two or more of said steps or features. The present disclosure is therefore to be considered as in all aspects illustrated and not restrictive, the scope of the invention being indicated by the appended Claims, and all changes which come within the meaning and range of equivalency are intended to be embraced therein. Various references are cited throughout this Specification, each of which is incorporated herein by reference in its entirety. The foregoing description will be more fully understood with reference to the following Examples.

EXAMPLES

Example 1

Material & Methods

Analysis of metabolites in serum and tissue

Metabolite extraction from tears

50 pL of tears were mixed with 200 pl of methanol (HPLC grade) in a 1.5ml Eppendorf tube. The mixture was vortexed for 10 s, and then incubated for 20 min on ice. After centrifugation (16,000 x g, 4 °C, 15 min), 200 pl of the supernatant containing the extracted metabolites was transferred to a 1 ml glass vial and stored at -20 °C until analysis.

Sample preparation for LC-MS analysis

50 pL methanol extract was dried under a nitrogen stream and reconstituted in 20uL water (MS grade) and diluted with 80uL injection buffer. The dilution was vortexed and centrifuged (16,000 x g, 4 °C, 15 min). 50 pL of the supernatant was transferred to a glass vial with narrowed bottom (Total Recovery Vials, Waters) for LC-MS injection. In addition, method blanks, QC standards, and pooled samples were prepared in the same way to serve as quality control for the measurements. Injection buffer was composed of 90 parts of acetonitrile (HPLC grade), 9 parts of methanol (HPLC grade) and 1 part of 5M ammonium acetate (p.a.).

LC-MS analysis

Metabolites were separated on a nanoAcquity UPLC (Waters) equipped with a BEH Amide capillary column (150 pm x50mm, 1.7 pm particle size, Waters), applying a gradient of 5mM ammonium acetate in water (A) and 5mM ammonium acetate in acetonitrile (B) from 5% A to 50% A over 12min. The injection volume was 1 pL. The flow rate was adjusted over the gradient from 3 to 2 pl/min. The UPLC was coupled to Synapt G2Si mass spectrometer (Waters) by a nanoESI source. MSI (molecular ion) and MS2 (fragment) data was acquired using negative polarization and MS^E over a mass range of 50 to 1200 m/z at MSI and MS2 resolution of 25’000 FWHM.

Targeted Data analysis

Target metabolites (2-HG) were quantified by the area under the peak (AUP) of the MSI extracted ion chromatogram (EIC) of the respective [M-H]' ion by using MassLynx v4.2 software (Waters). Reference samples were used to locate and verify the correct peaks on the EIC of 2-HG by retention time and MS2 fragment information. AUP values reported are unit less and are proportional to the concentration of the targets in the samples (relative quantification). AUP values can be used to calculate fold changes.

Untargeted Metabolomics Data analysis

Metabolomics data sets were evaluated in an untargeted fashion with Progenesis QI software (Nonlinear Dynamics), which aligns the ion intensity maps based on a reference data set, followed by a peak picking on an aggregated ion intensity map. Detected ions were identified based on accurate mass, detected adduct patterns and isotope patterns by comparing with entries in the Human Metabolom Data Base (HMDB). A mass accuracy tolerance of 5mDa was set for the searches. Observed fragmentation patterns were considered for the identifications of metabolites by comparison to theoretical fragmentation spectra. All biological samples were analysed in triplicate and quality controls were run on pooled samples and reference compound mixtures to determine technical accuracy and stability.

Results

Targeted metabolomics analysis of tears of GBM patients (GBM patients phenotyping) 2-HG was found LC-MS chromatogram of tear samples of pre-therapy GBM patients. 2 independent programs were used to identify existence of 2-HG; MassLynx and Progenesis QI (multivariate data analysis). However, 2-HG was not found neither in samples of control groups nor in samples of post-therapy samples of GBM patients.

Furthermore, 2-HG was found within samples of relapsed GBM patients even recurrence of tumor couldn’t have been detected by imaging systems such as MR. Example 2

Data processing and Normalization

MetaboAnalyst accepts a variety of data types generated in metabolomic studies, including compound concentration data, binned NMR/MS spectra data, NMR/MS peak list data, as well as MS spectra (NetCDF, mzXML, mzDATA). We had to specify the data types when uploading their data in order for MetaboAnalyst to select the correct algorithm to process them. Table 1 summarizes the result of the data processing steps.

Reading Peak Intensity Table

The peak intensity table should be uploaded in comma separated values (.csv) format. Samples can be in rows or columns, with class labels immediately following the sample IDs. Samples are in columns and features in rows. The uploaded _le is in comma separated values (.csv) format. The uploaded data _le contains 45 (samples) by 4006 (peaks(mz/rt)) data matrix.

Data Integrity Check

Before data analysis, a data integrity check is performed to make sure that all the necessary information has been collected. The class labels must be present and contain only two classes. If samples are paired, the class label must be from -n/2 to -1 for one group, and 1 to n/2 for the other group (n is the sample number and must be an even number). Class labels with same absolute value are assumed to be pairs. Compound concentration or peak intensity values should all be non-negative numbers. By default, all missing values, zeros and negative values will be replaced by the half of the minimum positive value found within the data.

Missing value imputations

Too many zeroes or missing values will cause di culties for downstream analysis. MetaboAnalyst o ers several different methods for this purpose. The default method replaces all the missing and zero values with a small values (the half of the minimum positive values in the original data) assuming to be the detection limit. The assumption of this approach is that most missing values are caused by low abundance metabolites (i.e.below the detection limit). Data Filtering: No data filtering was performed

Data Normalization

The data is stored as a table with one sample per row and one variable (bin/peak/metabolite) per column. The normalization procedures implemented below are grouped into four categories. Sample specific normalization allows users to manually adjust concentrations based on biological inputs (i.e. volume, mass); row-wise normalization allows general-purpose adjustment for differences among samples;data transformation and scaling are two different approaches to make features more comparable. We could use one or combine both to achieve better results.

The normalization consists of the following options:

1. Row-wise procedures:

. Sample specific normalization (i.e. normalize by dry weight, volume)

. Normalization by the sum

. Normalization by the sample median

. Normalization by a reference sample (probabilistic quotient normalization^

. Normalization by a pooled or average sample from a particular group

. Normalization by a reference feature (i.e. creatinine, internal control)

. Quantile normalization

2. Data transformation :

. Generalized log transformation (glog 2)

. Cube root transformation

3. Data scaling:

. Mean centering (mean-centered only)

. Auto scaling (mean-centered and divided by standard deviation of each variable)

. Pareto scaling (mean-centered and divided by the square root of standard deviation of each variable)

. Range scaling (mean-centered and divided by the value range of each variable)

Preferably, the methods are selected from the group comprising: Row-wise normalization, Quantile Normalization, Data transformation, Log 10 Normalization,; Data scaling, Range and Scaling. Example 3

Comparison of Metabolomic Pattern of Emotional Tears and Basal Tears

Material

Emotional tears collected directly from patients and were preserved in Eppendorf 1,5 ml tubes before liquid / liquid extraction with methanol (97-99%). To collect basal tears (as liquid exist on surface of eyes- known as lacrimal fluid), eyes of patient were washed by injectable grade distilled water and basal tears collected in an Eppendorf tube. Adequate amount of attention was paid to collect same quantity of emotional tears and basal tears. (100 microliters emotional tears, 100 microliter basal tears)

Sample Preparation

100 microliters of emotional tears and basal tears were extracted with 400 microliters of methanol (97-99%) and 500 microliters of both samples preserved to perform LC-IMS-MS analysis.

Method

LC-IMS-MS (Mass-Ion Mobility Spectrometry)

Results and Conclusion

Oncometabolites from emotional tears: L- Glutamate, L Asparagine, L-Phenylalanine, Valine, Isocitrate, Cirate, Malate, 2-Oxoglutarate, 2-Hydroxyglutarate, Acetyl-CoA, S-Lactate, Tryptophan, Leucine, Isoleucine, Diethylthiophosphate, L-Cystathionine, Lysine, Succinate Oncometabolites from basal tears: Citrate, Succinate (both very low concentration)

Emotional tears involving more than 1400 metabolites and we have investigated existence of oncometabolites within emotional tears. Basal tears which were collected from eye surface involve very limited number of metabolites. We only identified a few oncometabolites which were present in lower quantity than identification limits of LC-MS.

Claims

1. A method of diagnosing a disease in a subject comprising:

(b) comparing the subject's one or more metabolite(s) profile to a healthy control metabolite profile for the same one or more metabolite biomarker(s); and

(c) identifying differences between the subject's one or more metabolite(s) profile and the healthy control metabolite profile; wherein at least one metabolite is 2 -hydroxyglutarate (2-HG), or an enantiomer thereof, and wherein a variation in the profile of said 2-hydroxyglutarate (2-HG), or an enantiomer thereof, in the subject's metabolite profile as compared to the healthy control metabolite profile indicates the presence of a disease in the subject.

2. A method of stratifying a disease in a subject comprising:

(b) comparing the subject's one or more metabolite(s) profile to a healthy control metabolite profile for the same metabolite biomarker; and

(c) identifying differences between the subject's metabolite profile and the healthy control metabolite profile; wherein at least one metabolite is 2-hydroxyglutarate (2-HG), or an enantiomer thereof, and wherein a variation in the profile of the level of said 2-hydroxyglutarate (2-HG), or an enantiomer thereof, in the subject's metabolite profile as compared to the healthy control metabolite profile is indicative of the disease stage.

3. A method of determining the progression or regression of a disease in a subject suffering from said disease, said method comprising

(b) periodically determining the profile of said one or more metabolite(s), wherein at least one metabolite is 2 -hydroxyglutarate (2-HG), or an enantiomer thereof, and wherein an alteration in the profile of said 2 -hydroxyglutarate (2-HG), or an enantiomer thereof, in said tears, relative to the profile of said 2-hydroxyglutarate (2-HG), or an enantiomer thereof, determined previously, is indicative of the progression or regression of said disease.

4. The method of anyone of the preceding claims, wherein detecting the profile of one or more metabolite in tears comprises determining the presence, the amount and/or the level of said one or more metabolite(s).

5. The method of anyone of the preceding claims, wherein the disease is selected from the group comprising a cancer, an infectious disease, a neurological disease and/or a neurodegenerative disease.

6. The method of claim 5, wherein the disease is selected from the group comprising glioblastoma multiforme (GBM), acute myeloid leukemia, parkinson’s disease, alzheimer’s disease, amyotrophic lateral sclerosis (ALS), or a combination of one or more thereof.

7. The method of anyone of the preceding claims, wherein the 2-HG enantiomer is selected from the group comprising L-2HG and D-2-HG, or a combination thereof.

8. An assay for use in a method of anyone of the preceding claims, comprising means and/or reagents for determining the profile of 2-HG, or an enantiomer thereof, in tears of a subject.

9. A kit for performing a method according to any one of claims 1 to 7, said kit comprising a) means for collecting tears of a subject, b) means and/or reagents for determining the profile of 2-HG, or an enantiomer thereof, in tears of a subject, and c) instructions for use.

10. A method of diagnosing and/or prognosing a disease in a subject comprising: (a) detecting the profile of one or more metabolite(s) and/or metabolomic pattern in tears obtained from said subject;

11. The method of claim 10, wherein the disease is selected from the group comprising a cancer, an infectious disease, an immune disease, a neurological disease and a neurodegenerative disease.

12. The method of claim 10, wherein the disease is selected from the group comprising glioblastoma multiforme, acute myeloid leukemia, parkinson’s disease, alzheimer’s disease, Covid- 19, and amyotrophic lateral sclerosis (ALS).

13. The method of claim 10 or 11, wherein the metabolite is an oncometabolite.

14. The method of any one of claims 1 to 7 or claims 10 to 13, wherein said method is a computer-implemented method.

15. A method of diagnosing a disease in a subject comprising:

16. A device for performing a method according to any one of claims 1 to 7 or claims 10 to

14, said device comprising a) a sample chamber for holding tears collected from a subject, b) an assay module in fluid communication with said sample chamber, said assay module comprising means and/or reagents for determining the profile one or more metabolite(s), in said tears, wherein said assay module comprises: a user interface wherein said user interface relates the presence, the amount and/or the level of said one or more metabolite(s), in said assay module to detecting a disease in said subject.