Mettl3-mettl14-complex inhibitors for the treatment of neuromuscular degenerative pathologies caused by or linked to mutations in the FUS gene

Abstract

The present invention relates to an inhibitor of the METTL3-METTL14 complex, or a pharmaceutically acceptable salt or solvate thereof, for use in the treatment of neuromuscular degenerative pathologies. These pathologies are preferably caused by or linked to mutations in the FUS gene and / or by the accumulation of pathological protein aggregates or aberrant stress granules. The inhibitor can be used alone or in combination with other pharmaceutically active ingredients. Additionally, the invention includes pharmaceutical compositions comprising the inhibitor and a pharmaceutically acceptable carrier or excipient, potentially combined with other agents known to treat or mitigate neuromuscular disorders.

Description

[0001]Treatment of neuromuscular degenerative disorders **** Field of invention The present invention relates to the treatment of neuromuscular degenerative disorders, in particular to the treatment of disorders characterized by the formation and the persistence in the cells of proteinaggregates, for example aberrant stress granules (SG).Prior Art Neurological disorders and neuromuscular disorders are two distinct categories of medical conditions that affect different aspects of the nervous system, resulting in varying symptoms and implications for patients. Neurological disorders primarily involve the central nervous system (CNS) and peripheral nervous system (PNS), which includes the brain, spinal cord, and nerves. These disorders often stem from abnormalities in brain function, nerve signaling, or neurotransmitter imbalances. Neurological disorders can lead to cognitive, sensory, and motor impairments, affecting a wide range of bodily functions. On the other hand, neuromuscular disorders and in particular neuromuscular degenerative disorders, specifically target the muscles and the nerves that control them. These conditions disrupt the normal functioning of the neuromuscular junctions, leading to muscle weakness, wasting, and loss of voluntary muscle control. Disorders like muscular dystrophy, and amyotrophic lateral sclerosis (ALS) are examples of neuromuscular disorders. Unlike neurological disorders, which can have diverse effects, neuromuscular disorders primarily impact movement and muscle-related functions. While both types of disorders involve the nervous system, the key distinction lies in the affected areas and the resulting symptoms. Neurological disorders focus on the overall functioning of the nervous system, impacting cognitive and sensory abilities, while neuromuscular disorders are more localized to muscles and their control, leading to motor-related issues. Accurate diagnosis and differentiation of these disorders are crucial for appropriate treatment and management strategies to improve the quality of life for affected individuals. Among the neuromuscular disorders ALS is a progressive neuromuscular disease due to gradual motor neuron degeneration that leads to the atrophy of the innervating muscles and consequently to paralysis and death (Brown and Al-Chalabi 2017). Many cellular processes have been associated to ALS pathogenesis, one of them is the formation of Stress Granules (SG) due to mutant proteins which lead to liquid-solid phase-transition and protein aggregation. Physiological SG are ribonucleoprotein membrane-less organelles that form to protect cells from stress conditions. They are composed of mRNAs, RNA-binding proteins, and translation initiation factors that are sequestered in a reversible manner to regulate mRNA stability and translation under stress conditions. SGs can be induced by a variety of stressors, such as oxidative stress, hypoxia, and heat shock, and are thought to represent a key adaptive response to cellular stress. Usually, SG are transient structures that disassemble when the stress is over, but they can become pathological when specific mutant proteins are expressed and cause cell death when stress is prolonged. Defects in both SG assembly and disassembly have been linked to neurodegenerative disorders (Fan and Leung n.d.; Wolozin and Ivanov 2019). Among the processes associated to ALS pathogenesis, there is the formation of cytoplasmic inclusions producedby mutant protein aggregation, among which the RNA binding protein FUS (Dudman and Qi 2020).FUS encodes 526 amino acid protein that is part of the FET family of RNA binding proteins. FUS is a ubiquitously expressed protein that is predominantly localized in the nucleus under normal physiological conditions but crosses over to the cytoplasm, functioning in nucleocytoplasmic transport (Zinszner et al. 1997). Over 50 autosomal dominant FUS variants have now been identified in ALS patients. Many of the pathogenic variants are clustered within the nuclear localization signal and lead to the redistribution of FUS to the cytoplasm (Vance et al. 2013). No cure for ALS exists today and the drugs commonly used to treat ALS patients are not curative, and while they can improve patient survival rates and ease symptoms, they have modest effects on quality of life and have significant side effects. N6-methyladenosine (m6A) modification is a post-transcriptional chemical modifications of RNA that plays an important part in the regulation of gene expression and in multifaceted biological activities; m6A writers are a large family composed of various members in particular the m6A– METTL complex (MAC) and m6A–METTL-associated complex (MACOM). The core of this methyltransferase complex (MTC) is the METTL3 -METTL14 complex, that is reported to be the initial factors that catalyze the methylation of adenosines. METTL16 is a RNA N6-methyltransferase that methylates adenosine residues at the N6 position of a subset of RNAs and is involved in S-adenosyl-L-methionine homeostasis by regulating expression of MAT2A transcripts. METTL14 is required for RNA binding while METTL3 is the catalytic subunit of the m6A- METTL- complex and it makes it capable of the deposition of a modification, N-6-methyladenosine (m6A), on RNAs; m6A is a RNA modification known for its role in many biological processes (Zaccara, Ries, and Jaffrey 2019). However, very little is known about its role in the dynamics of physiological or pathological condensates and it has been shown to be unable to play a significant role in mRNA recruitment in SGs in vivo (Khong et al. 2022). In preclinical studies, METTL3 inhibitors have shown promising in the treatment of many types of proliferative diseases as cancer, including lung, breast and ovarian cancer. No data are available regarding the effects of the inhibition of METTL3 in other medical conditions, and in particular in neurodegenerative diseases and neuromuscular disorders. Summary of the invention Is an object of the present invention an inhibitor of the METTL3-METTL14 complex or a pharmaceutically acceptable salt or solvate thereof for use in the treatment of neuromuscular degenerative pathologies preferably for pathologies that are characterized by the accumulation of pathological protein aggregates or aberrant stress granules. The inhibitor according to the present invention can be used alone or in combination with at least one other pharmaceutically active ingredient. By “inhibitor” is meant any molecule or compound, gene therapy or biotechnological approach that is able to downregulate the target or to function as an inhibitor of the target activity. According to a preferred embodiment the pathologies to be treated are caused by or linked to mutations in the FUS gene. In a preferred embodiment the inhibitor is an inhibitor of METTL3. It is also object of the present invention a composition comprising an inhibitor of the METTL3- METTL14 complex or a pharmaceutically acceptable salt or solvate thereof and at least one pharmaceutically acceptable carrier or excipient for use in the treatment of said neuromuscular degenerative pathologies. In a preferred embodiment the composition according to the invention can further comprise other pharmaceutically active ingredients known to be effective in the treatment of neuromuscular disorders or in the mitigation of its symptoms. Brief description of the drawings Figure 1: a. Densitometry analyses showing the relative protein level of FUS in SK-N-BE cells upon doxycyclin induction (D+) with respect to the control condition (D-). n=3 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. b. Representative western blots (upper) and the corresponding densitometry analyses (lower) evaluating the decrease of METTL3 protein upon shRNAs (sh) transfection in SK-N-BE FUSwtor SK-N-BE FUSP525Lcell lines; ACT-β was used as loading control. Relative protein levels were as relative quantities with respect to wild-type cells set to 1. n=3 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. c. Relative quantification of m6A on mRNA upon METTL3 knock-down (sh) with respect to a control condition (scr) in either FUSwtor FUSP525LSK-N-BE cells. n=3 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. d. Bar plot depicting SG enrichment (log2FC SG / INP) of selected RNAs to confirm proper SG purification in D- (black bar), FUSWT(grey bar) and FUSP525L(white bar) conditions: HUWE1, TRIO and AHNAK were used as positive controls while ATP5PO as negative one. The log2FC thresholds to define SG enriched RNAs (log2FC > 1) and depleted ones (log2FC < -1) are indicated as dotted grey lines. e. Scatter plot depicting RNA differential enrichment in SG in FUSWTvs FUSWTMETTL3- KD conditions. Axes describes log2FC of SG RNA enrichment in the indicated conditions. Darker dots and numbers indicate ∆METTL3-enriched RNAs (lower, right), ∆METTL3- depleted RNAs (upper, left), commonly enriched RNAs that are enriched in SG in both conditions (upper, right). Lighter dots indicate invariant RNAs. n=2. f. Venn diagram depicting the overlap between ∆METTL3 Relocated RNAs and SG enriched RNAs in FUSWTand FUSP525Lconditions. g. Scatter plot depicting RNA differential enrichment in SG in FUSP525Lvs FUSP525LMETTL3- KD conditions. Axes describes log2FC of SG RNA enrichment in the indicated conditions. Darker dots and numbers indicate ∆METTL3-enriched RNAs (lower, right), ∆METTL3- depleted RNAs (upper, left), commonly enriched RNAs that are enriched in SG in both conditions (upper, right). Lighter dots indicate invariant RNAs. n=2. h. Scatter plot depicting RNA differential enrichment in SG in FUSwtvs FUSP525LMETTL3- KD conditions. Axes describes log2FC of SG RNA enrichment in the indicated conditions. Darker dots and numbers indicate ∆METTL3-enriched RNAs (lower, right), ∆METTL3- depleted RNAs (upper, left), commonly enriched RNAs that are enriched in SG in both conditions (upper, right). Lighter dots indicate invariant RNAs. n=2. i. Venn diagram depicting the overlap among the SG enriched RNAs in the three analyzed condition D-, FUSWTand FUSP525Lin control cells (left panel) and upon METTL3 downregulation (∆METTL3, right panel). j. Venn diagrams depict the overlap among the top 5000 (left panel) and top 500 RNAs (right panel) ranked by SG enrichment in each analyzed condition (D-, FUSWTand FUSP525Lupon METTL3 depletion). k. Barplot depicting the library sizes of RNA-Seq samples before (left, upper panel) and after the resampling procedure (left, lower panel). Library sizes of FUSP525Lsamples were used as reference in order to resample fragments of other samples. Venn diagram (right panel) displaying the high overlap between SG enriched RNAs in the three analyzed condition D-, FUSWTand FUSP525Lupon METTL3 depletion that after the resampling procedure. l. Heatmap (lower panel) showing k-mers (4-mers) enrichment in SG among different condition. Rows represent each possible k-mer with k=4, while columns represent conditions. K-mers enrichment is described as ratio between mean k-mer percentage in SG enriched RNAs vs invariant RNAs. The three clusters identified using K-means clustering (n clusters=3) indicate k-mers depleted (#1), neither (#2) or enriched (#3) in FUSP525Lcondition. Color scale describes the magnitude of k-mer enrichment, enrichment values > 1 are represented in red while enrichment values < 1 are represented in blue. Pie charts (upper panel) represents the fraction of GC and AU nucleotides in k-mers clusters. Sequence logo representing the consensus DRACH motif significantly over-represented in the m6A-IP peak regions. m. Metagene plot resulted from m6A-IP data displaying m6A increased signal intensity near the STOP codon. n. Enrichment of selected RNAs resulted to be methylated according to m6A-IP data. WTAP and ATP5O were used as positive and negative controls, respectively; immunoprecipitation with IgG was used as control. n = 2. o. Pie charts displaying the percentage of meRIP-Seq enriched RNAs among invariant, commonly enriched and relocated defined in the comparison between FUSP525Lvs FUSP525LMETTL3-KD. n=2. p. Box plots displaying RNA length (Kb) of the indicated RNA groups identified by SG differential enrichment analysis among FUSP525Lvs FUSP525LMETTL3 KD. Statistical significance was evaluated with Mann-Whitney U test. P-value are indicated in the figure. Figure 2: a. Genomic analyses of selected SK-N-BE clones after CRISPR / Cas9 mediated genome editing to insert a degron tag (mAID) at the N-terminus of METTL3. Heterozygotes are squared. Arrows indicate the size of the amplicons deriving from a either wild type (METTL3 WT) or an edited genome (mAID METTL3). The donor DNA and gDNA from unedited cells were used as positive or negative controls, respectively. b. Representative western blot analysis showing METTL3 and METTL14 decrease in the indicated SK-N-BE cells after degron tag insertion (mAID). ACT-β was used as loading control. c. Relative protein levels of METTL3 (n=4 biologically independent replicates) and METTL14 (n=3 biologically independent replicates) in the indicated SK-N-BE degron tag (mAID) insertion. Levels were normalized over ACT-β protein level and expressed as relative quantities with respect to wild-type cells set to 1. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. d. Bar plot showing the m6A level decrease in the indicated SK-N-BE cells. Levels are represented as percentage with respect to control cells set as 100%. n=3 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. e. Box plots representing the number of stress granules per cell in the indicated SK-N-BE cell lines. The x indicates the average number of granules in each sample after 1hr stress. Each black dot represents the number of granules in a single field. Seven fields were acquired for each biological replicate. n=3. f. Box plots showing granule volumes in the indicated SK-N-BE cells. Black dots represent the average volumes. Gray dots represent the volume of each measured granule. n=3 biologically independent replicates. Seven fields were acquired for each biological replicate. n=3. g. Genomic analyses of selected iPS clones after CRISPR / Cas9 mediated genome editing to insert a degron tag (mAID) at the N-terminus of METTL3. Homozygotes are squared. Arrows indicate the size of the amplicons deriving from a either wild type (METTL3 WT) or an edited genome (mAID METTL3). The donor DNA and gDNA from unedited cells were used as positive or negative controls, respectively. h. Representative western blot analysis (left) showing METTL3 and METTL14 decrease in the indicated SK-N-BE cells after degron tag insertion (mAID). ACT-β was used as loading control. i. Relative protein levels (right) of METTL3 (n=4 biologically independent replicates) and METTL14 (n=3 biologically independent replicates) in the indicated SK-N-BE degron tag (mAID) insertion. Levels were normalized over ACT-β protein level and expressed as relative quantities with respect to wild-type cells set to 1. n=3. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. j. Box plots representing METTL3 signal intensity analyses. Seven fields were acquired. Black dots represent signal average. Each gray dots represents a single cell signal. P-value are indicated. The scale bar is 20 µm. k. Bar plot showing the m6A level decrease in the indicated iPSC derived MN. Levels are represented as percentage with respect to control cells set as 100%. n=3 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. l. Box plots representing the number of stress granules per cell in the indicated iPS-derived MN. The x indicates the average number of granules in each sample after 1hr stress. Each black dot represents the number of granules in a single field. Seven fields were acquired for each biological replicate. n=4. m. Box plots showing granule volumes in the indicated Mn. Black dots represent the average volumes. Gray dots represent the volume of each measured granule. n=3 biologically independent replicates. Seven fields were acquired for each biological replicate. n=3. n. Box plots representing the number of stress granules per cell in the indicated iPSC. The x indicates the average number of granules in each sample after 1hr stress. Each black dot represents the number of granules in a single field. Seven fields were acquired for each biological replicate. n=2. Figure 3: a. Box plots showing the percentage of unrecovered indicated SK-N-BE cells after 1hr stress followed by 4hr recovery. The x indicates the average percentage in each sample. Each back dot represents the percentage in a single field. Seven fields were acquired for each biological replicate. n=4 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. b. Box plot showing the colocalization analysis of G3BP1 and FUS signals in SK-N-BE FUSP525Lcells both in stress and in recovery conditions. Seven fields were acquired for each biological replicate. Each x represents the average percentage. n=3 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. c. Box plots showing the number of FUS-only granules in the indicated FUSP525LSK-N-BE cells. The red dot indicates the average granules number in each sample. Seven fields were acquired for each biological replicate. n=4 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. d. Box plot showing the comparison of granule volumes in stress or in recovery conditions. Black dots represent the average volumes. Gray dots represent the volume of each measured granule. Seven fields were acquired for each biological replicate. n=3 (stress) n=4 (recovery) biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. Figure 4: a. Bar plot showing the m6A level decrease of SK-N-BE FUSP525Lcells treated either with DMSO or STM-2457. Levels are represented as percentage with respect to control cells set as 100%. n=3 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. b. Box plots representing the number of stress granules per cell in stressed SK-N-BE FUSP525Ltreated either with DMSO or STM-2457. The x indicates the average number of granules in each sample. Each black dot represents the number of granules in a single field. Seven fields were acquired for each biological replicate. n=3 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. c. Box plots showing the percentage of unrecovered SK-N-BE FUSP525Ltreated either with DMSO or STM-2457. The x indicates the average percentage in each sample. Each black dot represents the percentage in a single field. Seven fields were acquired for each biological replicate. n=3 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. d. Box plots representing the number of stress granules per cell in stressed iPS-derived MN expressing FUSP525Ltreated either with DMSO or STM-2457. The x indicates the average number of granules in each sample. Each black dot represents the number of granules in a single field. Seven fields were acquired for each biological replicate. n=4 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. e. Box plots representing the number of stress granules per cell in stressed patients-derived fibroblasts treated either with DMSO or STM-2457. The x indicates the average number of granules in each sample. Each black dot represents the number of granules in a single field. Seven fields were acquired for each biological replicate. n=4 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. f. Bar plot showing the m6A level decrease of iPSC-derived MN FUSP525Ltreated either with DMSO or STM-2457. Levels are represented as percentage with respect to control cells set as 100%. n=3 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. g. Bar plot showing the m6A level decrease of patient derived fibroblasts treated either with DMSO or STM-2457. Levels are represented as percentage with respect to control cells set as 100%. n=3 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. h. Box plots showing the percentage of unrecovered patients-derived fibroblasts treated either with DMSO or STM-2457. The x indicates the average percentage in each sample. Each black dot represents the percentage in a single field. Seven fields were acquired for each biological replicate. n=3 biologically independent replicates. The ratio of each sample versus its experimental control was tested by two-tailed Student’s t test. P-value are indicated. Detailed Description Any reference in the description to a method of treatment is to be interpreted as referring to a compound, composition or medicament for use in a method of treatment. Unless otherwise stated, the terms used in the description and claims have the meaning commonly intended in the relevant technical field. All the biological material (i.e. cell lines) origin is correctly identified in the example section, when said biological material is obtained from patients it is always obtained upon informed consent signature. The present invention thus relates to the treatment of neuromuscular degenerative pathologies. In a preferred embodiment the present invention also relates to the treatment of neuromuscular degenerative pathologies characterized by the accumulation of pathological protein aggregates or aberrant SG; e.g. aggregation diseases such as ALS, Alzheimer and Parkinson diseases. In a preferred embodiments the present invention relates to the treatment of neuromuscular degenerative pathologies linked to or caused by mutations in the FUS gene (HGNC: 4010 NCBI Gene: 2521 Ensembl: ENSG00000089280) as in ALS, Tremor, Hereditary Essential, Frontotemporal Dementia, and polyglutamine diseases (Deng, Gao, and Jankovic 2014). The present invention relates to systems that enable the reduction of m6A levels in cellular RNAs, and in particular to systems that are able to interfere with the function of or to downregulate, or to function as an inhibitor of the METTL3-METTL14 complex and METTL16. In a preferred embodiment, the present invention relates to system that can interfere with the function of or to downregulate, or to function as an inhibitor of METTL3 or of its interactors, including METTL14. The present invention relates specifically to an inhibitor of METTL3 or a pharmaceutically acceptable salt or solvate thereof, for use in the treatment of one of the pathologies above described. The present invention relates also to an inhibitor of METTL14 or a pharmaceutically acceptable salt or solvate thereof, for use in the treatment of one of the pathologies above described. The present invention relates also to an inhibitor of METTL16 or a pharmaceutically acceptable salt or solvate thereof, for use in the treatment of one of the pathologies above described. The present invention also relates to an inhibitor of METTL3, METTL14 and / or METTL16 or a pharmaceutically acceptable salt or solvate thereof in combination with at least one other pharmaceutically active ingredient or gene therapy agent, for use in the treatment of one of the pathologies above described. According to the invention by “inhibitor” is meant any molecule or compound, gene therapy or biotechnological approach that is able to downregulate the target or to function as an inhibitor of the target activity or in the specific case to reduce cellular m6A levels. Particularly preferred is an inhibitor of METTL3 or an inhibitor of METTL14. According to the invention by “inhibitor of METTL3” is meant any molecule or compound, gene therapy or biotechnological approach that is able to downregulate METTL3 or to function as an inhibitor of the METTL3-METTL14 complex activity or to reduce cellular m6A levels. As a non-limiting example such inhibitor could be an agent involved in RNA-Based Regulation, in RNA-RNA Interaction Regulation, in Protein-Based Regulation, in Protein-Protein Interaction Regulation, in Protein-RNA Interaction Regulation, Epigenetic Regulation, in Small Molecule Mediated Regulation, in Antibody and Peptide Mediated Regulation, in Competitive Binding and Post-Translational Regulation, in Gene Mutations and editing, in Indirect Regulation and Inducible Systems, Substrate or Cofactor Availability Manipulation, Targeted Protein Degradation. Particularly preferred are CRISPR / Cas derived technologies, virus-mediated siRNA expression in particular lentiviral-mediated, siRNA, shRNA, gapmer, antisense oligonucleotides (ASO), ceRNA, LNA, morpholino, Monoclonal Antibodies, Allosteric Modulators, Ribozymes, Transcription Factors and Enhancer Activation, aptamers. In a preferred embodiment an siRNA or an ASO against METTL3 or METTL14 is used. Is within the reach of the field expert that RNA based approaches as for example siRNA, ShRNA, gapmer, ASOs and LNA are to be subject to chemical modifications to be stable in in-vivo conditions. It is also within the reach of the field expert that many of these approaches are based on an administration based on inducible Expression Systems, and on a delivery mediated by appropriate vectors, particularly viral vectors preferably Retroviral or Lentiviral vectors. As a non-limiting example an inhibitor of METTL3 could be chosen among STM-2457 (CAS#: 2499663-01-1; PDB access code 7O2I), adenosine, N-substituted amides of the ribofuranuronic acid derivatives of adenosine, UZH1a, UZH1b, UZH2, STM1760, 2-deoxy-2-fluororibose and 2- deoxyribose derivatives, pyrido[1,2-a]pyrimidinone derivatives, cyclopentane-1,2-diol, 4-[2-[5- chloro-1-(diphenylmethyl)-2-methyl-1H-indol-3-yl]-ethoxy] benzoic acid(CDIBA), eltrombopag, flavonoids quercetin, luteolin, and scutellarin, elvitegravir and their derivatives and their analogues. In a preferred embodiment the inhibitor of METTL3 is STM-2457. According to the invention said other pharmaceutically active ingredient is preferably an active ingredient that is known to be effective in the treatment of neuromuscular disorders or in the mitigation of its symptoms. Said other pharmaceutically active ingredient can be, as a non-limiting example, be selected from the group comprising of Aeolus 10150, ALS-357, albumin, Antithymocyte globulin, Arimoclomol, Atorvastatin,AVP-923, Avanier 07-ACR-123 (Zenvia®), anti-CTGF agents, benzodiazepines (e.g., diazepam, clonazepam), Botulinum toxin type B, brain-derived neurotrophic factor (BDNF), cannabinoids, celecoxib, ceftriaxone, CK-2017357,coenzyme Q10, copper, corticosteroids, corticotropin, creatine, creatine monohydrate, cistanche total glycosides, cyclosporin, Dronabinol, escitalopram (Lexapro®), edaravone, ezogabine, fasudil, fingolimod, Gabapentin GSK1223249, glatiramer acetate, glycopyrrolate, GM604, granulocyte stimulating factor, growth hormone (somatropin), growth factors (e.g. HGF, IGF, bFGF, NGF), imipramine, incobotulinum toxin A, inosine, interleukin 1 receptor antagonist, interleukin-2 (IL-2), itriptyline, KNS-760704, levetiracetam, lithium carbonate, MCI 186, mecobalamin, methylcobalamin, methylprednisolone, mexiletine, memantine, minocycline, MN-166, modafinil, mycophenolate mofetil, neurotrophin 3 (NT3),nonsteroidal anti-inflammatory drugs (NSAIDs),nortriptyline, NP001, Nuedexta, ODM-109, olanzapine, ONO-2506PO, olexisome, opiates, pioglitazone, prednisone, propantheline, pyrimethamine, rasagiline, R(+) pramipexole, R(+) pramipexole dihydrochloride monohydrate, riluzole (6-(trifluoromethoxy)benzothiazol-2-amine), RNS60, SB-509, scopolamine, sNN0029, sodium phenylbutyrate, sodium valproate, Talampanel, tamoxifen, TCH346, tauroursodeoxycholic acid, Thalidomide, tirasemtiv, tocilizumab, tretinoin, TRO19622, tizanidine, tolterodine tartate, tofersen, voluntary muscle relaxants, YAM80, zinc. Particularly preferred are memantine, creatine monohydrate, botulinum toxin type B, tauroursodeoxycholic acid, coenzyme Q10, lithium carbonate, riluzole, edavarone, tofersen. By gene therapy agent is meant the medical approach aiming to treat or prevent diseases by using gene replacement, gene removal, gene addition, gene editing, gene silencing, and targeting and modulation of gene expression (i.e. by CRISPR / Cas9, shRNA, ASO). The pharmaceutically active ingredients and the gene therapy agents can be administered sequentially or simultaneously to the inhibitor of the METTL3-METTL14 complex according to the invention. The present invention further relates to a pharmaceutical composition comprising at least one inhibitor of the METTL3-METTL14 complex or a pharmaceutically acceptable salt or solvate thereof, for use in the treatment of neuromuscular degenerative pathologies, preferably characterized by the accumulation of pathological protein aggregates or aberrant SG; e.g. aggregation diseases such as ALS, Alzheimer and Parkinson diseases. In a preferred embodiment the present invention relates to said pharmaceutical composition for use in the treatment of neuromuscular degenerative pathologies linked to or caused by mutations in the FUS gene (HGNC: 4010 NCBI Gene: 2521 Ensembl: ENSG00000089280) as ALS. The composition can further comprise at least one pharmaceutically active ingredient. According to the invention the other pharmaceutically active ingredient can be preferably an active ingredient that is known to be effective in the treatment of neuromuscular degenerative disorders or in the mitigation of its symptoms. The other pharmaceutically active ingredient can be for example selected from the group of Aeolus 10150, ALS-357, albumin, Antithymocyte globulin, Arimoclomol, Atorvastatin,AVP-923, Avanier 07-ACR-123 (Zenvia®), anti-CTGF agents, benzodiazepines (e.g., diazepam, clonazepam), Botulinum toxin type B, brain-derived neurotrophic factor (BDNF), cannabinoids, celecoxib, ceftriaxone, CK-2017357,coenzyme Q10, copper, corticosteroids, corticotropin, creatine, creatine monohydrate, cistanche total glycosides, cyclosporin, Dronabinol, escitalopram (Lexapro®), edaravone, ezogabine, fasudil, fingolimod, Gabapentin GSK1223249, glatiramer acetate, glycopyrrolate, GM604, granulocyte stimulating factor, growth hormone (somatropin), growth factors (e.g. HGF, IGF, bFGF, NGF), imipramine, incobotulinum toxin A, inosine, interleukin 1 receptor antagonist, interleukin-2 (IL-2), itriptyline, KNS-760704, levetiracetam, lithium carbonate, MCI 186, mecobalamin, methylcobalamin, methylprednisolone, mexiletine, memantine, minocycline, MN-166, modafinil, mycophenolate mofetil, neurotrophin 3 (NT3),nonsteroidal anti-inflammatory drugs (NSAIDs),nortriptyline, NP001, Nuedexta, ODM-109, olanzapine, ONO-2506PO, olexisome, opiates, pioglitazone, prednisone, propantheline, pyrimethamine, rasagiline, R(+) pramipexole, R(+) pramipexole dihydrochloride monohydrate, riluzole (6-(trifluoromethoxy)benzothiazol-2-amine), RNS60, SB-509, scopolamine, sNN0029, sodium phenylbutyrate, sodium valproate, Talampanel, tamoxifen, TCH346, tauroursodeoxycholic acid, Thalidomide, tirasemtiv, tocilizumab, tretinoin, TRO19622, tizanidine, tolterodine tartate, tofersen, voluntary muscle relaxants, YAM80, zinc. Particularly preferred are memantine, creatine monohydrate, Botulinum toxin type B, tauroursodeoxycholic acid, coenzyme Q10, lithium carbonate, riluzole, edavarone, tofersen. The composition can further comprise at least one gene therapy agent, preferably a gene therapy agent known to be effective in the treatment of the aforementioned pathologies for example can be one of tools for gene replacement, gene removal, gene addition, gene editing, gene silencing, and targeting and modulation of gene expression by technologies including delivery of siRNA, shRNA, gapmer, antisense oligonucleotides (ASO), LNA, morpholino. Particularly preferred are CRISPR / Cas derived technologies, virus-mediated siRNA expression in particular lentiviral-mediated, siRNA, shRNA, gapmer, antisense oligonucleotides (ASO), ceRNA, LNA, morpholino, Monoclonal Antibodies, Allosteric Modulators, Ribozymes, Transcription Factors and Enhancer Activation. The composition can further comprise at least one of pharmaceutically acceptable carrier, medium and / or excipient, buffer, pH adjusters. According to the present invention, the inhibitor or the pharmaceutical composition may be formulated in different forms and states; the formulation may be suitable for oral administration or may be injectable or may be suitable for intrathecal, parenteral, topical, mucosal or transdermal administration. Particularly preferred is the oral administration. The form of the pharmaceutical composition may vary and can be selected with regards to the pathology to be treated by the expert in the field. In a preferred embodiment the pathology to be treated is ALS preferably the pathology to be treated is a FUS-associated form of ALS. The inhibitor of the METTL3-METTL14 complex for use according to the present invention reduces the formation of pathological SG and promotes the dissolution of the existing ones. Disease progression is also delayed and symptoms relieved. It is therefore an object of the present invention an inhibitor of METTL3 or of METTL14 or of the METTL3-METTL14 complex or a pharmaceutically acceptable salt or solvate thereof, or composition comprising said inhibitor as above described for use in the reduction of the formation and in the stimulation of dissolution of mutant FUS-containing SG, by reducing the levels of m6A deposition on RNA. RNA-binding proteins (RBPs) assemblies vary in a dynamic manner (Wolozin and Ivanov 2019) and changes in the relative abundance of proteins and RNAs can lead to liquid-solid phase transition and eventually to the formation of aggregates (Murakami et al. 2015; Markmiller et al. 2018). Such aggregates acquire significant relevance in neuromuscular degenerative and protein aggregation diseases where protein mutations and physicochemical insults can induce liquid-solid phase- transition (Murakami et al. 2015). ALS is associated with appearance of protein aggregates and aberrant SG in motor neurons (MNs) (Blokhuis et al.2013) and several findings causatively link this phenomenon with pathological states: in fact, overexpression of either wild-type or mutant RBPs such as FUS in different model organisms resulted in reduction of motility and processivity of mitochondrial axonal transport and altered displacements of RBPs assemblies(Ishiguro et al. 2016; Kreiter et al. 2018; Yu et al. 2022). Spatial localization of RNA is a very crucial process in neurons, as it controls local protein synthesis that mediates directional and morphological responses and transport defects have been ascribed to RBPs and their ability to control correct subcellular compartmentalization of several macromolecular structures, from large organelles to mRNAs, and their localized translation. Therefore, the inventors believed that the ability to prevent or revert aggregates formation represent an important therapeutic approach for several neuromuscular degenerative pathologies and have hence decided to investigate the interplay between SG and m6A and analyzed it in the context of ALS. They surprisingly were able to demonstrate that while m6A plays a limited role in SG physiology in control conditions, it has a strong impact in ALS genetic contexts, such as those where the FUS protein is mutated especially in domains that confer its cytoplasmic relocation. Using cellular models of ALS, the inventors first found out that SG formed in the presence of mutant FUS differ from those of control cells not only in the number of condensates and in the rate of recovery from stress but also in RNA composition. For the experiments was mainly used two mutant variants of FUS (FUSP525L, FUSR518I), that are hot spot variants having a mutation in its nuclear localization signal. FUSR518Iis a FUS mutant form where the arginine in the nuclear localization signal at the aminoacidic position 518 is replaced with an isoleucine, FUSP525Lis a FUS mutant form where the proline in the nuclear localization signal at the aminoacidic position 525 is replaced with a leucine. Different approaches of inhibition and down-regulation of METTL3 and METTL14 were tested in order to obtain the reduction of FUS-containing SG (aggregates). Surprisingly the reduction of FUS-containing SG was obtained not only in METTL3 knock-down, realized both via transient shRNA technology and stable genome editing of cell lines, but also by inhibition of the methyltransferase activity of METTL3 in cell lines and in patient-derived fibroblasts treated with the small molecule STM-2457, a known inhibitor of the methyltransferase activity of METTL3. In addition, we obtained a similar reduction of FUS-containing SG number in stable METTL14 knock-down conditions, in iPSC expressing FUSP525L, homozygous for the insertion of a degron tag (mAID) at the N-terminus of METTL14. All these different approaches lead to the reduction of FUS-containing SG, identifying for the first time the link between m6A modification and altered SG dynamics in ALS. Notably, the phenotypes observed in the presence or depletion of m6A were paralleled by an interesting reshaping of the transcriptomes: while the RNA content of SG obtained in FUSP525Lwas considerably different from that of FUSWT(Mariani et al. 2023), when m6A was reduced, the transcriptome reverted towards the control one. These data indicated the important role of m6A in contributing to the phase transition occurring in SG of FUSP525Lcells, and confirmed that modulation of m6A plays a relevant role in aberrant SG formation demonstrating that targeting this modification can indeed revert not only the morphology but also the RNA composition of these condensates, resulting in a promising approach for use in the treatment of ALS, and other pathologies linked to or caused by mutations in the FUS gene. STM-2457 is a molecule already used in medicine and specifically in the treatment of cancer; the molecule was previously adopted in clinical trials as an inhibitor of cell proliferation in the therapeutic treatment of Acute myeloid leukemia. The inventors, demonstrating that STM-2457 phenocopies the decrease of FUS aggregates obtained in METTL3 knock-down cell lines, were now able to find a new medical use for the molecule; it is therefore an object of the present invention STM-2457 for use in the treatment of neuromuscular degenerative, protein aggregation diseases and diseases linked to or caused by FUS mutation. In a preferred embodiment the neuromuscular degenerative disease is ALS, preferably a FUS-associated ALS. EXAMPLES METTL3 downregulation restores the physiological RNA composition of stress granules in ALS cellular models. In order to unveil the impact of m6A on SG RNA composition in physiological and ALS-linked conditions, SK-N-BE cells, a human neuroblastoma cell line widely used to model neurodegenerative diseases, were used (CRL-2271). SK-N-BE cell lines expressing either wild type FUS (FUSWT -, SEQ ID NO: 1) or its mutant form with the proline in its nuclear localization signal at the aminoacidic position 525 replaced with a leucine (FUSP525L -SEQ ID NO: 2) under a doxycycline-inducible promoter were produced by Dr. Morlando, as described in Morlando et al. 2012, and constitutively expressing the SG marker G3BP1 tagged with GFP. Upon doxycycline induction (“D+”), a three folds overexpression of FUS was obtained (Fig. 1a). As expected, FUSP525L, due to the mutation in its nuclear localization signal, is not efficiently imported in the nucleus and associates into SG upon stress induction it was verified that, in this condition, its signal almost completely colocalized with that of G3BP1. FUSWTor FUSP525Lcells were treated with a control shRNA or with the combination of two shRNAs against METTL3 (>TRCN0000289812, TRCN0000289814, > SHC202 TRC2 - SEQ ID NO: 4,5 and 6) the main m6A writer acting on mRNAs, obtaining about 50% reduction of the protein (Fig. 1B). Furthermore, was colorimetrically evaluated the m6A reduction on mRNAs upon METTL3 decrease through the epiquik assay and found a m6A reduction (20%, Fig. 1C). Upon doxycycline treatment and oxidative stress induction with sodium arsenite (“Ars+”), SG were isolated thanks to immunoprecipitation with anti-GFP antibodies. SG enrichment in the immunoprecipitated fraction was confirmed by the enrichment of positive controls such as HUWE1, TRIO and ANHAK and the lack of ATP5O mRNA used as a negative control (Fig. 1D). In order to identify transcripts possibly altered in their association with SG upon m6A reduction, RNA-seq data were analyzed through “Differential Enrichment Analysis” (DEA) comparing enrichment in SG in the presence of METTL3 and upon its downregulation. The inventors distinguished four groups of transcripts: 1) RNAs significantly enriched in SG both in control and METTL3 KD conditions, defined as “commonly enriched”; 2) transcripts enriched only upon METTL3 depletion, named “∆METTL3-enriched”; 3) transcripts not enriched upon METTL3 depletion, defined as “∆METTL3-depleted”; 4) RNAs not enriched or showing no significant difference in SG enrichment, defined as “invariant”. Comparing the SG-associated transcriptome of FUSWTcells in the presence or absence of METTL3, it is not observed any differentially enriched RNA, suggesting that m6A does not alter SG RNA composition in wild type conditions (Fig.1E). Differences were found in the composition of SG when comparing cells expressing FUSWTor FUSP525L, with 599 and 1267 transcripts specifically gained or lost, in the mutant FUS genetic background, respectively (Fig. 1F). Surprisingly, when analyzing SG composition in FUSP525L cells, differences were observed with a numerous group of transcripts (differentially enriched RNAs: 461), specifically recruited in FUSP525L-containing SG upon METTL3 downregulation (Fig. 1G). Surprisingly, most of these transcripts (~85%) are enriched in SG in FUSWTcondition, suggesting that, in condition of depletion of the m6A writer, the transcriptome returned similar to that of FUSWTrelocating in SG a conspicuous fraction of RNAs not enriched in FUSP525Lcontrol condition (Fig. 1F). For this reason, in the present description those RNAs will be named “relocated RNAs”. This evidence is confirmed by the differential enrichment analysis comparing FUSWTversus FUSP525Lexpression upon METTL3 downregulation in which it was observed a strong similarity between the SG transcriptome in these conditions (only 57 differentially enriched transcripts, Fig. 1H). Indeed, while SG transcriptome in presence of FUSP525Ldisplayed strong differences with FUSWTor D- control conditions, upon sh-METTL3 the three SG transcriptomes displayed similar RNA composition (Fig. 1I). Through enrichment convergence and resampling analyses, it was verified that this similarity was not dependent by the threshold adopted to define enriched RNAs in SGs or by the RNA-Seq library size variability (Fig. 1J, Fig. 1K). In agreement with these results, while the nucleotide composition of FUSWTand FUSP525LSG in control conditions was significantly different, it returned similar following METTL3 downregulation (Fig. 1L). Overall, these data indicate that while the SG transcriptomes of FUSWTand FUSP525Lare markedly different, they revert similar under conditions of m6A downregulation. In order to correlate the methylation status of the transcripts with their localization, was performed MeRIP-Seq in FUSP525Lcells. The correct purification of methylated RNA was testified by the significant over-representation of the consensus DRACH motif in peaks regions (Fig. 1M). Furthermore, as expected, the metagene plot resulting from these data displayed peak density near the stop codon (Fig. 1N). Finally, the m6A content of several RNA species identified in the MeRIP- seq was validated by RT-PCR (Fig. 1O). When analyzing the commonly enriched RNAs in FUSP525LSG, the inventors found that m6A- containing RNAs accounted for 22% while those of invariant species corresponded to 11% (Fig.1P). Such difference is mainly due to an increase in the length of the RNA (Fig. 1O), further confirming previous observations that long transcripts are enriched in SG and are more likely to contain m6A. Instead, the percentage of m6A-containing RNAs increased up to 37% when looking at the relocated RNA (Fig. 1P). Importantly, at difference with the previous group this enrichment could not be accounted for differential length of the transcripts since it resulted comparable to that of other transcripts included in granules (Fig. 1Q). The inventors therefore found that the downregulation of METTL3 restored SG transcripts loss in ALS-like condition, and that there is a higher percentage of m6A-containining mRNAs among the transcripts included in FUSP525LSG, identifying for the first time the link between m6A modification and altered SG dynamics in ALS. METTL3 and METTL14 downregulation reduces the number of SG in ALS cellular models. In order to investigate if the downregulation of METTL3 could impact not only on the RNA content of FUSP525LSG, but also on their number and size, and therefore to understand if it could represent a therapeutic target the inventors combined immunostaining for FUS and G3BP1. Aiming to obtain stable and homogenous METTL3 knock-down conditions, CRISPR-Cas9 technology was used to insert a degron tag (mAID) at the N-terminus of METTL3(SEQ ID NO: 7). Only heterozygous clones in both FUSWTand FUSP525Lcell lines were obtained (Fig. 2A). These clones showed about 50% decrease of METTL3 protein (~50%, Fig. 2B), even without auxin induction. Notably, the downregulation of METTL3 in these conditions produced a similar decrease of its interacting partner METTL14 (Fig. 2B, Fig. 2C). Furthermore, in order to check whether the level of METTL3 downregulation was sufficient to obtain variation in the amount of m6A mRNA, the epiquik m6A RNA methylation quantification kit was applied and a reduction was again found (~20-30%, Fig. 2D). In consideration of these data, the mAID-METTL3 cell lines as stable METTL3 knock-down systems were chosen for imaging studies. The number of SG per cell were counted upon arsenite treatment to induce oxidative stress induction in control and in mAID-METTL3 cells expressing either FUSWTor FUSP525L. In the presence of physiological levels of m6A, a conspicuous increase of SG in FUSP525Lcells was observed compared to FUSWT(Fig. 2E). When mAID-METTL3 cells were analyzed, it was not observed any significant variation in FUSWTcells; instead, a great reduction was noted in the number of SG in FUSP525L cells, where the number returned to levels comparable to those of FUSWT(Fig.2E). Evaluation of SG volumes revealed no relevant average variation across the different conditions (Fig. 2F). Since ALS affects motor neurons (MN), the same analysis was performed in human iPSC-derived MN expressing endogenous levels of FUSWTor FUSP525L. In these cells homozygous clones were obtained for the insertion of the degron-tag mAID at the N- terminus of METTL3 (mAID-METTL3-HYGRO N-terminal tagging donor - SEQ ID NO: 7), leading to an almost complete depletion of the protein, even in the absence of auxin, that was also paralleled by a strong downregulation of METTL14 (Fig.2G, 2H, 2I). iPSCs were converted into motor neurons according to the protocol disclosed in Garone, M. G. et al. (Garone et al. 2019), and analyzed after eleven days of differentiation. Immunofluorescence experiments for METTL3 confirmed its decrease in these iPSC-derived MNs (Fig. 2J). Moreover, it was also verified that m6A RNA methylation decreased in mAID-METTL3 MNs thanks to the epiquik quantification kit, which indicated an approximate ~30-40% reduction of mRNA m6A levels (Fig. 2K). The number and volumes of SG in FUSWTor FUSP525LMN, with or without METTL3 depletion were then compared (Fig.2L, Fig.2M). The results confirmed what was previously observed in SK-N-BE cells, namely that FUSP525Lcells produce a larger number of SG which are recovered to normal levels upon METTL3 downregulation with no relevant average variation in their volumes. Coherently, we obtained a similar reduction of stress granules number in stable METTL14 knock- down conditions, in iPSC expressing FUSP525L, homozygous for the insertion of a degron tag (mAID) at the N-terminus of METTL14 (SEQ ID NO: 48; Fig. 2N). In conclusion, although METTL3 decrease did not affect SG number and size in a physiological context where wild type FUS is expressed, in the FUS-associated ALS model tested, it reduced the number of SG to levels similar to the control conditions. Furthermore, these data indicate that the effect of m6A in SG dynamics is the same in cells expressing either the endogenous or the overexpressed mutant FUS. METTL3 decrease restores SG recovery rate in ALS cellular models In order to further investigate the use of METTL3 as a therapeutic target in neuromuscular degenerative pathologies as ALS, it was then analyzed the dissolution of SG; SG usually dissolve when stress is removed and defects in such process are linked to several human neurodegenerative diseases. In order to investigate the effects of m6A on SG disassembly, the recovery rate in METTL3 knock- down conditions was evaluated through immunofluorescence analysis. Fig. 3A shows the percentage of FUSWTand FUSP525LSK-N-BE cells still containing granules after 4hr recovery from stress removal, in control conditions or upon METTL3 downregulation. The results indicate that FUSP525Lcells show a higher percentage of unrecovered cells with respect to FUSWT(Fig. 3A). Moreover, while the depletion of the m6A writer did not change the recovery rate of FUSWT, in mutant cells it rescued the recovery rate to wild type levels (Fig. 3A). Interestingly, in FUSP525Lcells, while it was observed an almost total overlap of G3BP1 and FUS signals upon stress, granules displaying FUS-only signals were noticed after recovery (Fig. 3B). Coherently, colocalization analysis showed that the observed total overlap of the two signals in stress conditions was significantly reduced to about 40% in recovery condition (Fig. 3B). Notably, the number of FUS-only aggregates decreased upon m6A downregulation (Fig.3C) and these condensates resulted smaller than the granules observed in stress conditions (Fig. 3D). These observations suggest the hypothesis that, upon stress, SG containing both G3BP1 and FUSP525Lare formed but that, after stress removal, G3BP1 is released free into the cytoplasm while FUS persists in an aggregate form. More importantly, FUS aggregation is relieved if the levels of m6A are reduced. METTL3 chemical inhibition relieves FUS-containing SG In order to further proceed to prove that the inhibition of METTL3 could be used in the treatment of ALS the inventors decided to test chemical compounds that are inhibitor of METTL3. STM-2457, which has been previously shown to be an effective inhibitor of METTL3 (Yankova et al.2021), was used to verify whether it could reproduce some of the phenotypes observed in cell models of ALS. Initially its activity was tested in SK-N-BE cells expressing FUSP525L. Figure 4A shows the effective m6A decrease upon STM-2457 treatment with respect to the DMSO control (~75% m6A reduction). The decrease of m6A due to STM-2457 administration recapitulated the effects of the lack of METTL3: indeed, cells formed less granules and displayed a higher recovery rate (Fig.4B, Fig.4C). Secondly iPSC-derived MNs carrying FUSP525Land patient-derived fibroblasts carrying the mutant FUSR518I(Deng, Gao, and Jankovic 2014) (the FUS mutant form where the arginine in the nuclear localization signal at the aminoacidic position 518 is replaced with an isoleucine) allele were treated with STM-2457 (Fig. 4D, Fig. 4E). This mutation, although different from the highly pathogenic FUSP525L, also causes relocalization of FUS in the cytoplasm, albeit to a lower extent, and causes the formation of FUS-containing SG upon stress induction. For these cellular models we assessed the m6A decrease on mRNAs with the epiquik assay showing the efficient downregulation (~70-80%) of m6A deposition (Fig. 4F, Fig. 4G). Figures 4D and 4E show how the inhibition of METTL3 activity significantly reduces the number of stress granules in iPSC-derived MNs as well as in patient-derived fibroblasts. Furthermore, in line with our previous results, a higher recovery rate in patient-derived fibroblasts upon STM-2457 treatment was also observed (Fig. 4H). Cell lines and biological material SK-N-BE cell lines (ATTC: CRL-2271) expressing either FUSWTor FUSP525Lunder a doxycycline- inducible promoter were produced by Morlando et al. (2012) (Morlando et al. 2012). Patient-derived fibroblasts were recovered from the ALS biopsy from an informed donor and were kindly provided by Prof. M. Sabatelli, Catholic University, Rome, Italy. Human iPSC lines used in this study were previously generated and characterized by Lenzi et al.(Lenzi et al. 2015), the cells are originally derived from informed donors, in particular ALS patients, harboring mutations in the FUS gene, recruited in order to obtain skin biopsies. The human iPSC lines were kindly provided for this study. Cell culture and preparation Human NIL (SEQ ID NO: 8) iPSCs were cultured in Nutristem (Sartorius, #05-100-1A) supplemented with Pen / Strep 0.1% on geltrex-coated plates (Thermo Fisher Scientific, #A1413202) and differentiated towards spinal motoneurons as described in De Santis et al. 2018 (DOI: 10.1016 / j.scr.2018.04.012). After 5 days of differentiation, cells were dissociated with Accutase (Thermo Fisher Scientific, #00-4555-56) and 200,000 cells / well were plated on geltrex-coated glass coverslips in 24-well plates. After additional 6 days of differentiation, the iPSC-derived motoneurons were treated with sodium arsenite. As regards for METTL3-inhibition experiments, MNs were treated with 15uM STM-2457, while control MNs were treated with same volumes of DMSO, for 48h before the arsenite treatment. For acute oxidative stress treatment, all cell lines used were exposed to 0.5 mM sodium arsenite for 1 hr. Recovery experiments were performed by restoring normal growth medium for 2h after acute arsenite treatment in fibroblasts. All cell lines used in were grown at 37°C, 5% CO2. All cell lines were tested for mycoplasma contamination. SK-N-BE cells were cultured in RPMI (Sigma-Aldrich, Saint Louis, MO, USA) supplemented with 10% FBS (Sigma-Aldrich, #F2442), GlutaMAX supplement 1X (ThermoFisher Scientific, # 35050061), sodium-pyruvate 1mM (Thermo Fisher Scientific, #11360070) and Pen / Strep 1X (Sigma- Aldrich, #P4458). For the inducible expression of FUS-FLAG WT or P525L, SK-N-BE cells were exposed to 50 ng / mL Doxycycline (Sigma-Aldrich, #D9891) for 24h before the sodium arsenite treatment (Sigma-Aldrich, #106277). Recovery experiments were performed by restoring normal growth medium for 4h after acute arsenite treatment in SK-N-BE cells. For the immunofluorescence experiments, SK-N-BE cells were dissociated with Trypsin 1X (Sigma- Aldrich, #T4549) and 20,000-30,000 cells / well were plated on glass coverslips in 24-well plates. Human primary fibroblasts were cultured in DMEM high-glucose with 1mM sodium-pyruvate (Sigma-Aldrich, # P5280) supplemented with 20% FBS, L-glutamine 2mM and Pen / Strep 1X. Cells were dissociated with trypsin-EDTA 1X (Corning, #25-053-CI) and 50,000 cells / well were plated on collagen-coated glass coverslips in 24-well plates. The following day, fibroblasts were treated with 15uM STM-2457, while control fibroblast were treated with same volumes of DMSO (Sigma Aldrich, #D2650), for 48h before the sodium arsenite treatment. All cell lines used in were grown at 37°C, 5% CO2. All cell lines were tested for mycoplasma contamination. For acute oxidative stress treatment, SK-N-BE cells, iPSC-MNs and primary fibroblasts were exposed to 0.5 mM sodium arsenite for 1 hr. Rescue experiments were performed in SK-N-BE cells by restoring normal growth medium for 4h or 2h after acute arsenite treatment in SK-N-BE cells or fibroblasts, respectively. Dregon Tag Insertion The degron tag (mAID) was inserted at the N-terminus of METTL3 or METTL14 together with the coding sequence for the hygromicyn resistance and a p2A signal for a proteolytic cut in SK-N-BE and iPS cells by Crispr / Cas9-induced DNA break (>mAID-METTL3-HYGRO (N-terminal tagging donor SEQ ID NO: 7; >mAID-METTL14-HYGRO (N-terminal tagging donor SEQ ID NO: 48 ). Two guide RNAs targeting the 5’UTR region of METTL3 were designed with CHOPCHOP (https: / / chopchop.cbu.uib.no / ) and cloned in a px330 vector through BbsI digestion (see >GUIDE_1_METTL3_TOP SEQ ID NO: 9; >GUIDE_2_METTL3_TOP SEQ ID NO: 10; >GUIDE_1_METTL14_TOP SEQ ID NO: 45; >GUIDE_2_METTL14_TOP SEQ ID NO: 46; >GUIDE_3_METTL14_TOP SEQ ID NO: 47). The plasmid donor carrying the sequence to be inserted plus 500 nt of homology upstream and downstream was synthetized by GENEWIZ (>mAID- METTL3-HYGRO (N-terminal tagging donor). 106 SK-N-BE cells were transfected with 3 ul of Lipofectamine 2000 (Life technologies) in 300 μL of Optimem with donor 2 ug of DNA donor and 2 ug of each guide plasmid. Same amount of DNA was transfected in 106 iPS cells with Neon™ Transfection System 100 µL Kit (Invitrogen, #MPK10096) according to manufacturer’s instruction (1 pulse, 20 V, 30ms). Cells transfected with donor only were used as selection control. Medium was replaced with fresh one added with 450 ug / ml or 300ug / ml hygromycin 24hr after transfection for SK-N-BE and iPS cells, respectively. Selection was carried out until control cells were died. Single colonies were transferred to 24-well plates. Colonies were then split, and a half was used for gDNA extraction and genotyping through Rapid Extraction PCR kit (PCR biosystems, #PB10.24). Oligos 9F and 4R were used for amplifying the WT and recombinant alleles (>9F- Mettl3 Promoter_fw SEQ ID NO: 13; >5R- CDS METTL3_rev SEQ ID NO:14. Immunocytochemistry Cells were fixed for 20 min at RT with cold 4% paraformaldehyde (Electron Microscopy Sciences , #15710) diluted to in complete PBS (Sigma Aldrich, # D1283), rinsed 3 times with complete PBS and stored in PBS at 4°C. Cells were permeabilized with 0.3% Triton X-100 (Sigma-Aldrich, #648466) diluted in complete PBS for 10 min and blocked with 5% goat and / or donkey serum, depending on the host species of the secondary antibody used. Samples were then incubated overnight at 4°C with the primary antibody diluted in blocking solution (5% goat and / or donkey serum in PBS, #G9023 and #D9663 Sigma-Aldrich). Cells were washed with complete PBS 3 times for 5 min at RT and then incubated with the following secondary antibodies for 1h at RT. diluted in blocking solution and were incubated for 1h at RT. Nuclei were stained with 1 ug / ml DAPI (#D9542, Sigma-Aldrich) diluted in complete PBS for 5 min and coverslips were mounted applying ProLong™ Glass Antifade Mountant (P36980, Thermo Fischer Scientific) leaving the slides on the bench. Confocal images were acquired with an inverted Olympus iX73 equipped with an X-Light V3 spinning disc head (Crest Optics), a Prime BSI Scientific CMOS (sCMOS) camera (Photometrics) and MetaMorph software (Molecular Devices), as Z-stacks (0.3 um step size) with a 60× oil-immersion objective. The following antibodies were used for immunohistochemistry in this study: a rabbit monoclonal anti-G3BP1 antibody (1:300, ab181150 Abcam) mouse anti-FLAG antibody (1:400, F1804 Sigma-Aldrich) mouse anti-FUS antibody (1:300, sc-47711 Santa Cruz Biotechnology) rabbit monoclonal anti-METTL3 antibody (1:500, ab195352 Abcam) chicken Anti-Beta III Tubulin (TUJ1) Antibody (1:400, AB9354 Sigma-Aldrich) goat anti-rabbit Alexa Fluor 488 (1:300, A11008 Thermo Fisher Scientific), goat anti-mouse Alexa Fluor 488 (1:300, A11001 Thermo Fisher Scientific) goat anti-rabbit Alexa Fluor 555 (1:300, 111-165-003 Jackson Immunoresearch) goat anti-mouse Alexa Fluor 555 (1:300, 115-165-003 Jackson Immunoresearch) goat anti-chicken Alexa Fluor 594 (1:300, ab150176 Abcam) donkey anti-mouse Alexa Fluor Plus 647 (1:300, A32787 Thermo Fisher Scientific), donkey anti-rabbit Alexa Fluor Plus 647 (1:300, A32795 Thermo Fisher Scientific) Image Analysis The analysis of immunofluorescence images was performed through the ImageJ software (Schneider et al, 2012). G3BP1 was used as SG marker. The ImageJ tool “3D Object Counter” was used for the quantification of SGs number and volumes. For the estimation of cells forming SGs in the recovery experiments cells were scored as SG-positive when they presented at least one G3BP1 granule-like cytoplasmic signal. For the intensity fluorescence analysis shown, a nuclear mask was generated using the DAPI signal to specifically select nuclear regions; this mask was then used to measure the METTL3 fluorescence intensity mean of each nucleus with the ImageJ tool “Measure”. For the signal colocalization analysis shown, the ImageJ plugin “Jacop” was used to calculate the Manders coefficient of FUS signal colocalizing with G3BP1 signal. In order to consider only the cytoplasmatic signal of FUS, a nuclear mask was created for each image and removed from both the FUS and G3BP1 images prior to proceed with the analysis. For the signal profile analysis shown in Fig X random granules were selected and sectioned with a 20-pixel length straight line and the ImageJ tool “Signal Profile” was used to quantify the signal intensity. For the quantification of “FUS-only” granules in recovery experiments, the G3BP1 signal was used to create a mask and then removed from the FUS signal before the quantification of the number and volumes of “FUS-only” granules using the ImageJ tool “3D Object Counter”. Stress granules isolation 2x106SK-N-BE cells FUSWTor FUSP525Lwere plated on a 6cm plate and transfected with 4 µg of vectors expressing sh1 and 4 µg of sh2 (>TRCN0000289812 SEQ ID NO: 4, >TRCN0000289814 SEQ ID NO: 5) or 8µg of sh ctrl (>SHC202 TRC2 SEQ ID NO: 6). The day after cells were transferred to a 15cm plates. When required, 96 hr after transfection FUS expression was induced with doxycycline for 24hr, stressed 1hr before harvesting, and harvested according to the protocol described by Khong et al. (Khong et al. 2017): cells were washed once with media, transferred to falcon tubes, and pelleted at 1,500 x g for 3 min. Upon aspirating the media, the pellets were immediately flash-frozen in dry ice and stored at −80°C until isolation of mammalian SG cores was performed. For the isolation of SG cores the pellet was thawed on ice for 5 min, re-suspended in 1 mL SG lysis buffer (50 mM TrisHCl pH 7.4, 100 mM KOAc, 2 mM MgOAc, 0.5 mM DTT, 50 μg / mL Heparin, 0.5% NP40, PIC 1×(Complete, EDTA free, Roche) and RNase Inhibitor (Thermo Fisher Scientific) and passed through a 25 gauge 5 / 8 needle attached to a 1 mL syringe 7 times. After lysis, the lysates were spun at 1000 x g for 5 min at 4°C to pellet cell debris. 50 μL and 950 μL of the supernatants were transferred to new microcentrifuge tubes for isolating total and SG RNAs respectively. For isolating total RNA, Qiazol reagent (QIAGEN) (Thermo Fisher Scientific, 10296-028) was added and RNA was extracted following the manufacturers protocol. Following Direct-zol RNA Miniprep (Zymo Research) kit, the total RNA was eluted in 50 μL RNase-free H2O. The following steps were performed to isolate mammalian SG cores and extract its RNA: 1) The 950 μL supernatant was spun at 18,000 x g for 20 min at 4°C to pellet SG cores. 2) The resulting supernatant was discarded, and the pellet was re-suspended in 1 mL SG lysis buffer. 3) Steps 1 and 2 were repeated to enrich for SG cores. 4) The resulting pellet was then re-suspended in 300 μL of SG lysis buffer and spun at 850 x g for 2 min at 4°C.5) The supernatant which represents the mammalian SG core enriched fraction was transferred to a new tube. 6) The enriched fraction was pre-cleared twice by adding 60 μL equilibrated DEPC-treated Protein A Dynabeads (Thermo Fisher Scientific) and nutating at 4°C for 30 min. Dynabeads were removed using a magnet. 7) 20 μL of anti-GFP antibody (Thermo Fisher Scientific) was added to the enriched fraction and nutated at 4°C for 1 hr to affinity purify SG cores.8) The solution was spun at 18,000 x g for 20 min at 4°C and the supernatant was discarded to remove any unbound antibody. 9) The pellet was then re-suspended in 500 μL SG lysis buffer and 60 μL equilibrated DEPC-treated Protein A Dynabeads.10) The sample was nutated for 3 hr at 4°C. 11) The Dynabeads were washed three times with wash buffer 1 (20 mM Tris HCl pH 8.0, 200 mM NaCl, RNase Inhibitor) for 5 min, once with wash buffer 2 (20 mM Tris HCl pH 8.0, 500 mM NaCl, RNase Inhibitor) for 5 min, and once with wash buffer 3 (SG lysis buffer + 2M Urea, RNase Inhibitor) for 2 min at 4°C. 12) The beads were resuspended in 200 μL of 100 μg / mL Protease K solution (1X TE buffer, 2M Urea, RNase Inhibitor) and incubated for 15 min at 37°C.13) Qiazol reagent was added to the samples and RNA was extracted following the manufacturers protocol. Following Direct-zol RNA Miniprep (Zymo Research) kit, the immunoprecipitated RNA was eluted in 25 μL RNase-free H2O. m6A-seq and m6A-CLIP m6A-seq was performed on FUSP525LSK-N-BE cells as indicated in the protocol by Dominissini et al. 2013(Dominissini et al. 2013) with some adjustments: poly-A selection was performed thanks to the Poly(A)Purist-MAG kit (Invitrogen, #AM1922). Poly-A+ RNA was incubated 4min at 94 °C for fragmentation and 5ug of fragmented poly-A+ RNA was used for the immunoprecipitation with the anti-m6A polyclonal antibody (Abcam, #ab151230). The elution of the immunoprecipitated fraction was carried out thanks to the protocol described in Molinie et al, 2017. M6A CLIP was performed according to the protocol described by Linder et al., 2015 with some modifications. Briefly, total RNA was purified from SK-N-BE cells, 5-20 μg of RNA were diluted in IP buffer supplemented with RNase Inhibitor (Thermo Fisher Scientific) and incubated with 1-5 μg of anti-m6A antibody for 2hrs at 4°C rotating head over tail and crosslinked, 10% of the solution was saved to be used as input, the leftover incubated with protein A / protein G dynabeads (Thermo Fisher Scientific) for 2hrs at 4°C. Bead-bound antibody-RNA complexes were washed and recovered. After phenol-chloroform extraction and precipitation, RNA was resuspended in 30 μL and 7 μL were reverse-transcribed with VILO Superscript (Thermo Fisher Scientific) in a 10 μL reaction. q-PCR was performed to evaluate targets enrichment. Protein analyses Cells were harvested in a suitable volume of Protein Extraction Buffer (Tris pH 7.5100 mM, EDTA 1 mM, SDS 2%, PIC1X (Complete, EDTA free, Roche) and incubated 10 min on ice, then incubated on a rotator for 30 min at 4 °C and centrifuged at 16000 × g for 10 min at 4 °C. The supernatant was transferred to a clean tube, used for subsequent analyses, or stored at −80 °C. Total protein concentration was measured through the Bradford reagent (Bio-Rad Protein Assay) following manufacturer’s instructions. 20–50 μg of proteins were loaded on 4–12% bis-tris polyacrylamide gel (Thermo Fisher Scientific) and transferred to a nitrocellulose membrane. The membrane was blocked in 5% milk and then hybridized with specific antibodies for 1 hr at room temperature or overnight at 4 °C. After three washes in TBST, the filter was hybridized with the corresponding secondary antibody, if required, for one hour at room temperature. All antibodies used in this study are reported below.Protein detection was carried out with WesternBright® ECL Chemiluminescent HRP Substrate (Advansta) or with Clarity Max Western ECL Substrate (Bio-Rad). Images were acquired using a ChemiDocTM MP Imager (Bio-Rad) and images were analyzed using Image LabTM 5.2.1 Software (Bio-Rad). The following antibodies were used in western blots for protein analyses: mouse anti-FUS antibody (1:300, sc-47711 Santa Cruz Biotechnology) rabbit monoclonal anti-METTL3 antibody (1:500, ab195352 Abcam) Anti-METTL3 [EPR18810] monoclonal antibody Abcam ab1953521:1000 Anti-METTL14 polyclonal antibody Atlas HPA0380021:1000 Anti-Flag M2-Peroxidase (HRP) Sigma-Aldrich A85921:2500 Anti-ACTB-Peroxidase (AC-15) monoclonal antibody Sigma-Aldrich A38541:2500 Anti-GAPDH (6C5) monoclonal antibody Santa Cruz Biotechnology sc-322331:1000 Anti-Rabbit IgG (H+L) Secondary Antibody, HRP Thermo Fisher Scientific 314601:10000 Anti-Mouse IgG (H+L) Secondary Antibody, HRP Thermo Fisher Scientific 324301:10000 RNA analyses Total RNA was extracted with Qiazol reagent (QIAGEN) and Direct-zol RNA Miniprep (Zymo Research) kit according to the manufacturer’s specifications or through standard phenol-chloroform extraction and precipitation. When needed, DNAseI treatment was performed (Thermo Fisher Scientific). Reverse transcription reactions were performed using PrimeScript RT Master Mix (Takara Bio). DNA amplification was monitored on an Applied BiosystemsTM 7500 Fast or StepOnePlus System qPCR instrument with the 7500 Software (Applied Biosystems) version 2.3 or with the StepOneTM Software (Applied Biosystems) version 2.3, respectively. Relative RNA quantity was calculated as the fold change (2−ΔΔCt) with respect to the experimental control sample set as 1 and normalized over ACTN1 or GAPDH mRNA. A complete list of the oligonucleotides used for qRT-PCR experiments is provided. m6A RNA Methylation Quantification After polyA+ RNA selection through Poly(A)Purist-MAG kit (Invitrogen, #AM1922), m6A level quantification was performed thanks to the EpiQuik m6A RNA Methylation Quantification Kit (EPIGENTEK, # P-9005) according to manufacturer’s instructions using 50-200 ng of RNA per well. SG RNA-Seq analysis Purified SGcore RNAs and relative inputs were retrieved in absence of doxy-induction (4 replicates); in condition of doxy-induced overexpression of FUS P525L (2 replicates) and FUS WT (2 replicates). For the latter two, also samples in condition of METTL3 depletion were generated. RNA library for all samples was produced using Stranded Total RNA Prep with Ribo-Zero Plus (Illumina). All samples were sequenced on an Illumina Novaseq 6000 Sequencing system. Trimmomatic (v0.39) (Bolger, Lohse, and Usadel 2014) and Cutadapt (v3.2) (Martin 2011) were used to remove adapter sequences and poor quality bases; minimum read length after trimming was set to 35. STAR software (v2.7.7a) (Dobin et al. 2013) was used to align reads to GRCh38 genome using ENCODE standard parameters referred in the manual. Reads aligning to rRNAs were filtered out; this first alignment was performed using Bowtie2 software (v2.4.2) (https: / / bowtie- bio.sourceforge.net / bowtie2 / index.shtml). PCR duplicates were removed from all samples using MarkDuplicates command from Picard suite (v2.24.1) (https: / / broadinstitute.github.io / picard / ). Uniquely mapping fragments were counted for each annotated gene (ensemble release 99) using HTseq software (v0.13.5) (Anders, Pyl, and Huber 2015). edgeR R package (v3.34.1) (Chen, Lun, and Smyth 2016) was used to compare SG enriched RNAs to relative input samples. RNAs with log2FC > 1 and FDR < 0.05 were defined “enriched” in SGcore while those with log2FC < -1 and FDR < 0.05 were defined “depleted” all the other were labelled as “invariant”. Differential enrichment analysis was performed using edgeR software defining the contrasts: (IP1- INP1)-(IP2-INP2) for the compared conditions (1 vs 2). Significance threshold was set to FDR < 0.05. Moreover, only RNAs expressed more than 1 FPKM in at least one sample type (IP1 or INP1 or IP2 or INP2) and that resulted as SG “enriched” in one of the analyzed conditions were defined as differentially enriched. In all the analyses that adoperate transcript sequences, fasta files were retriveved from Ensembl using biomart (Durinck et al.2009). In case of genes with multiple isoforms a representative isoform was selected. For protein coding genes the longest isoform with the same biotype of the gene was selected as representative, while for non-coding, the longest isoform was choosen. In order to define the SG enriched RNAs in different conditions we used the same logFC threshold (1 for enriched RNAs). However, the high variability of the immunoprecipitation-based experiments could result in high variability in the enrichment efficiency. Experiments with low enrichment efficiency could be penalized by a fixed threshold compared to others with an high efficiency, affecting the comparison of the defined enriched RNA sets. In order to overcome this technical limit linked to the logFC threshold selected we performed an Enrichment convergence analysis. For each analyzed condition, we first ranked the expressed RNAs by their SG enrichment (logFC) and then we selected a fixed number of enriched RNAs equal for each datasets. We then compared these three equally sized RNA sets using Venn Diagrams. We repeated this analysis selecting different fixed numbers of enriched RNAs gradually reducing the inclusion of the noise from the background transcriptome (fixed numbers of top enriched RNAs: 5000, 4500, 4000, 3500, 3000, 2500, 2000, 1500, 1000, 500). This analysis revealed that the similarity observed among the datasets in shMETTL3 condition is not dependent by the logFC threshold used to define the enriched sets. Indeed, while differences of SG enriched RNAs between FUSP525L condition and the others were exacerbated when we gradually exclude noise, we don’t observe the same divergence of the FUSP525L dataset in condition of METTL3 depletion. In the RNA-Seq analysis, the high variability of the library size of IP samples could affect the number of SG enriched RNAs identified. This could introduce technical bias especially when we need to compare the enriched RNAs of Ips performed in different conditions. In order to overcome this bias, we performed a Resampling analysis. We decided to use the observed number of fragments in FUS P525L condition experiment and then we randomly sampled fragments from the alignment files of the other conditions in order to mirrored the library size composition of the reference condition. In this way we obtained samples with similar technical variability and with a simulated similar library size. Then we compared the enriched RNAs resulted by this analysis without the bias introduced by the variability of the resulted library size. This analysis revealed that the similarity observed among the datasets in shMETTL3 condition is not dependent by the variability of library size of RNA-Seq samples. Random sampling of fragments was performed with Picard suite using FilterSamReads function and using random subsets of fragments ids list as input (https: / / broadinstitute.github.io / picard). k-mers analysis The average transcript frequency of each k-mer was calculated for SG enriched RNAs and background distribution (invariant group), and their ratio (fold-change, FC) was computed. Then, the log2FC of k-mers with k = 4 of all the analyzed conditions were used for Heatmap representation. Heatmaps graphical representations were depicted using ComplexHeatmap R package (v2.8.0) (https: / / bioconductor.org / packages / release / bioc / html / ComplexHeatmap.html). MeRIP-Seq analysis RNA library for all samples was produced using Stranded Total RNA Prep with Ribo-Zero Plus (Illumina). All samples were sequenced on an Illumina Novaseq 6000 Sequencing system with an average of about 74 million 100 nucleotides long paired-end read pairs. Trimmomatic (v0.39) (Bolger, Lohse, and Usadel 2014) and Cutadapt (v3.2) (Martin 2011) were used to remove adapter sequences and poor quality bases; minimum read length after trimming was set to 35. Using Bowtie2 software (v2.4.2) (Langmead and Salzberg 2012) were discarded reads aligned to contaminant sequences of human rRNAs retrieved from NCBI. STAR software (v2.7.7a) (Dobin et al.2013) was used to align reads to GRCh38 genome using ENCODE standard parameters referred in the manual. PCR duplicates were removed from all samples using MarkDuplicates command from Picard suite (v2.24.1) (https: / / broadinstitute.github.io / picard / ) and multi-mapped and un-properly paired reads were filtered out using bamtools (v2.5.1) (Barnett et al.2011) and samtools (v1.7) (H. Li et al. 2009) respectively. Peak calling was performed using exomePeak2 (v1.9.1) (https: / / github.com / ZW-xjtlu / exomePeak2) software filtering out peaks with log2FC (IP / INP) < 1; adjusted p-value > 0.01 and with less than a total of 10 fragments in input or m6A-IP samples. Peaks were annotated with Ensembl reference gtf (release 99) using bedtools (v2.29.1) with –s –split –wao parameters. After peak annotation, isoform and gene expression was assessed using RSEM (v1.3.1) (B. Li and Dewey 2011) on input samples. Genes expressed < 1FPKM in the INP condition were filtered out. 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Claims

CLAIMS 1. An inhibitor of the METTL3-METTL14 complex or a pharmaceutically acceptable salt or solvate thereof for use in the treatment of neuromuscular degenerative pathologies, wherein the pathologies are caused by or linked to mutations in the FUS gene.

2. The inhibitor of the METTL3-METTL14 complex or a pharmaceutically acceptable salt or solvate thereof for use according to claim 1 wherein the pathologies are characterized by the accumulation of pathological protein aggregates or aberrant stress granules.

3. The inhibitor of the METTL3-METTL14 complex or a pharmaceutically acceptable salt or solvate thereof for use according to any one of the preceding claims wherein the pathology is chosen among, ALS, Tremor Hereditary Essential, Frontotemporal Dementia, or polyglutamine diseases.

4. The inhibitor of the METTL3-METTL14 complex or a pharmaceutically acceptable salt or solvate thereof for use according to any one of the preceding claims wherein the inhibitor is used in combination with at least one other pharmaceutically active ingredient.

5. The inhibitor of the METTL3-METTL14 complex or a pharmaceutically acceptable salt or solvate thereof for use according to claim 4 wherein the pharmaceutically active ingredient is chosen in the group comprising Aeolus 10150, ALS-357, albumin, Antithymocyte globulin, Arimoclomol, Atorvastatin,AVP-923, Avanier 07-ACR-123, anti-CTGF agents, benzodiazepines, Botulinum toxin type B, brain-derived neurotrophic factor, cannabinoids, celecoxib, ceftriaxone, CK-2017357, coenzyme Q10, copper, corticosteroids, corticotropin, creatine, creatine monohydrate, cistanche total glycosides, cyclosporin, Dronabinol, escitalopra, edaravone, ezogabine, fasudil, fingolimod, Gabapentin GSK1223249, glatiramer acetate, glycopyrrolate, GM604, granulocyte stimulating factor, growth hormone (somatropin), growth factors, imipramine, incobotulinum toxin A, inosine, interleukin 1 receptor antagonist, interleukin-2 (IL-2), itriptyline, KNS-760704, levetiracetam, lithium carbonate, MCI 186, mecobalamin, methylcobalamin, methylprednisolone, mexiletine, memantine, minocycline, MN-166, modafinil, mycophenolate mofetil, neurotrophin 3 (NT3), nonsteroidal anti-inflammatory drugs, nortriptyline, NP001, Nuedexta, ODM-109,olanzapine, ONO-2506PO, olexisome, opiates, pioglitazone, prednisone, propantheline, pyrimethamine, rasagiline, R(+) pramipexole, R(+) pramipexole dihydrochloride monohydrate, 6-(trifluoromethoxy)benzothiazol-2-amine, RNS60, SB-509, scopolamine, sNN0029, sodium phenylbutyrate, sodium valproate, Talampanel, tamoxifen, TCH346, tauroursodeoxycholic acid, Thalidomide, tirasemtiv, tocilizumab, tretinoin, TRO19622, tizanidine, tolterodine tartate, tofersen, voluntary muscle relaxants, YAM80, zinc.

6. The inhibitor of the METTL3-METTL14 complex for use according to any one of the preceding claims wherein the inhibitor is chosen among the group of siRNAs, an antisense oligonucleotides, shRNA, gapmer, ceRNA, LNA, morpholino directed against METTL3 or METTL14.

7. The inhibitor of the METTL3-METTL14 complex or a pharmaceutically acceptable salt or solvate thereof for use according to any one of the preceding claims wherein the inhibitor is an inhibitor of METTL3.

8. The inhibitor of the METTL3-METTL14 complex or a pharmaceutically acceptable salt or solvate thereof for use according to claims 1-5 wherein the inhibitor is an inhibitor of METTL3 chosen among the group of STM-2457, adenosine, N-substituted amides of the ribofuranuronic acid derivatives of adenosine, UZH1a, UZH1b, UZH2, STM1760, 2-deoxy- 2-fluororibose and 2-deoxyribose derivatives, pyrido[1,2-a]pyrimidinone derivatives, cyclopentane-1,2-diol, 4-[2-[5-chloro-1-(diphenylmethyl)-2-methyl-1H-indol-3-yl]- ethoxy]benzoic acid(CDIBA), eltrombopag, flavonoids quercetin, luteolin, and scutellarin, elvitegravir.

9. The inhibitor of the METTL3-METTL14 complex or a pharmaceutically acceptable salt or solvate thereof for use according to claim 8 wherein the inhibitor of METTL3 is STM-2457.

10. A composition comprising at least one inhibitor of METTL3-METTL14 complex or a pharmaceutically acceptable salt or solvate thereof and at least one pharmaceutically acceptable carrier or excipient for use in the treatment of neuromuscular degenerative pathologies, wherein the pathologies are caused by or linked to mutations in the FUS gene.

11. The composition for use according to claim 10, wherein the pathologies are characterized by the accumulation of pathological protein aggregates or aberrant stress granules.

12. The composition for use according to any one of claims 10-11 wherein the composition additionally comprises at least one pharmaceutically active ingredient preferably chosen in the group of Aeolus 10150, ALS-357, albumin, Antithymocyte globulin, Arimoclomol, Atorvastatin,AVP-923, Avanier 07-ACR-123, anti-CTGF agents, benzodiazepines, Botulinum toxin type B, brain-derived neurotrophic factor, cannabinoids, celecoxib, ceftriaxone, CK-2017357, coenzyme Q10, copper, corticosteroids, corticotropin, creatine, creatine monohydrate, cistanche total glycosides, cyclosporin, Dronabinol, escitalopra, edaravone, ezogabine, fasudil, fingolimod, Gabapentin GSK1223249, glatiramer acetate, glycopyrrolate, GM604, granulocyte stimulating factor, growth hormone (somatropin), growth factors, imipramine, incobotulinum toxin A, inosine, interleukin 1 receptor antagonist, interleukin-2 (IL-2), itriptyline, KNS-760704, levetiracetam, lithium carbonate, MCI 186, mecobalamin, methylcobalamin, methylprednisolone, mexiletine, memantine, minocycline, MN-166, modafinil, mycophenolate mofetil, neurotrophin 3 (NT3), nonsteroidal anti-inflammatory drugs, nortriptyline, NP001, Nuedexta, ODM-109, olanzapine, ONO-2506PO, olexisome, opiates, pioglitazone, prednisone, propantheline, pyrimethamine, rasagiline, R(+) pramipexole, R(+) pramipexole dihydrochloride monohydrate, 6-(trifluoromethoxy)benzothiazol-2-amine, RNS60, SB-509, scopolamine, sNN0029, sodium phenylbutyrate, sodium valproate, Talampanel, tamoxifen, TCH346, tauroursodeoxycholic acid, Thalidomide, tirasemtiv, tocilizumab, tretinoin, TRO19622, tizanidine, tolterodine tartate, tofersen, voluntary muscle relaxants, YAM80, zinc.

13. The composition for use according to any one of claims 10-12 wherein the inhibitor of the METTL3-METTL14 complex is STM-2457.

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