Head and neck cancer (HNC), once metastasized, is very difficult to treat as there are limited therapy options. Animal models of such can be very useful for preclinical drug development, including precision medicine and immunotherapy. By whole-exome analyses and functional annotation of five commonly used immune-intact metastatic models for HNC research, we aimed to fully annotate their genomic profiles on key cancer genes as well as signaling-, metastasis-, immune- and drug-related events, with direct comparisons with those of patient tumors. Our analyses revealed marked genomic similarities between these models and HNC patient tumors, and identified new potential drug targets for metastatic HNC. We suggest that more of such immune-relevant metastatic HNC models should be developed with full genomic annotations in order to enable preclinical research, and to accelerate precision medicine and immunotherapy development for this devastating cancer.Trp53, Fanconi anemia, and MAPK and PI3K pathway defects. Collectively, the five models harbor genetic aberrations across 10 cancer hallmarks and 14 signaling pathways and machineries , to extents similar in patients. Immune defects in HLA-A , Pdcd1, Tgfb1, Il2ra, Il12a, Cd40, and Tnfrsf14 are identified. Invasion/metastatic genome analyses first highlight potential druggable ERBB4 and KRAS mutations, for advanced/metastatic oral cavity cancer, as well as known metastasis players  frequently captured by all models. Notable immunotherapy and precision druggable targets  and three druggable hubs  are frequently represented by these models. Immunocompetent metastatic HNC models are worth developing to address therapy- and invasion/metastasis-related questions in host immunity contexts.Immunocompetent metastatic head and neck cancer (HNC) models, although scarce, can help understanding cancer progression and therapy responses in vivo. Their comprehensive genome characterizations are essential for translational research. We first exome-sequenced the two most widely used spontaneous metastatic immunocompetent models, namely AT-84 and SCC VII, followed by comprehensive genomic analyses with three prior-sequenced models , together with patient tumors for utility assessment. AT-84 and SCC VII bear high HNC tumor resemblance regarding mutational signatures— Head and neck cancer (HNC) is the sixth most common cancer worldwide, with nearly 0.83 million new incidences and 0.43 million deaths per year  [+ T cell-inviting tumor microenvironment in HNC shaped by MAPK pathway mutations, which was first informed by bioinformatics [KDELR3, BMI, ANXA2, CCN, TYRP2, VLA-4, HSP70, and HSP90 genes for metastatic melanoma [SERPINE2, S100A9, TGM2, KLF4, and POEM genes for breast cancer metastasis [VEGFA, CCR6, PDGFR-β, CRAMP, RANKL, and IGF-IR for metastatic lung cancer [Among pan-cancers characterized by The Cancer Genome Atlas (TCGA), HNC has been revealed as an immune-altered cancer ,6. Emergormatics . In termmelanoma ,22,23,24tastasis ,26,27,28g cancer ,31,32,33Pik3ca, Rptor, and Ctcf. Importantly, mutational profile analyses of all five models show genetic defects on 10 cancer hallmarks and 14 HNC-relevant signaling pathways and machineries  to extents similar to HNC patients (TCGA). Immune-event analyses reveal patient-relevant aberrations of HLA-A , Pdcd1, Tgfb1, Il2ra, Il12a, Cd40, Tnfrsf14, and several checkpoint regulators. Invasion/metastatic genome analyses first highlight potential druggable ERBB4 and KRAS mutations, present in 5.3% of metastatic HNC patients, that are commonly captured by these models. Strikingly, Muc5ac, Trem3, Trp53, and Ttn, known metastasis players in other cancers, are consistently mutated in all five metastatic models. For drugging purposes, notable immunotherapy and precision druggable targets  and three druggable hubs  are most frequently represented by the models. In conclusion, more metastatic models should be developed to further advance HNC studies in immunocompetent contexts, in terms of metastasis, drugging, and tumor-immune interactions.As of today, for HNC, there are five convenient xenograftable immunocompetent metastatic models available to help in addressing tumorigenesis, invasion/metastasis-related questions, as well as drug-induced or even precision medicine-induced effects in a host immunity context. These are AT-84 , SCC VIIAT-84 and SCC VII represent the two earliest established and most widely used xenograftable immunocompetent metastatic HNC models ,35. As oAPOBEC edit (signature 2), tobacco smoke (signature 4), UV damage (signature 7), and aging-related signature (signature 1)  B. Notablature 1) .Ctcf  [Erbb2 , Rptor  [H2-Q4 . Common gene copy losses represented by both models with HNC patient relevance are Robo2, an important candidate tumor suppressor of the ROBO–SLIT pathway (16qC3), and Fancb gene  involved in the Fanconi anemia (FA) pathway, which is altered in subsets of HNC patients. ROBO2 and FANCB gene copy losses in HNC tumors from TCGA-HNC Firehose (N = 510) are 70% (356/510) and 29% (150/510 cases), respectively  were determined by CNVkit. Both AT-84 and SCC VII have arm-level recurrent gains of mouse chr.2q, 8q, and 11q as well as a loss of 4q D. It hasan CTCF) , Erbb2 ( RAPTOR) , and H2-rtal.org ,49).Pik3ca, Hras, and Fbxw7, all relevant to HNC tumors, are captured by AT-84, whereas copy gain of Egfr is captured by SCC VII. In HNC patient tumors, EGFR, PIK3CA, HRAS, and FBXW7 are gained or amplified in 42% (213/510), 71% (363/510), 13% (64/510), and 7% (36/510), respectively , 27% (139/510), 15% (76/510), 41% (211/510), and 3% (16/510), respectively , 71% 3/510, 13Trp53, Trem3, Muc5ac, and Ttn, corresponding to human TP53, TREM-1/2, MUC5AC, and TTN, are noted . We first assembled a combined human cancer gene list of 830 genes  of the remaining cancer gene events captured by these five models have not been previously studied in HNC  (N = 308 cases). Note that the overall pattern of genetic events between all HNC cases and oral cancer only are largely similar. As shown in TP53 (Trp53), FAT1 (Fat1), KMT2D (Kmt2d) and HLA-A . In particular, TP53 is the most frequently mutated tumor suppressor gene in HNC, affecting 72% of HNC patients (365/510 cases) and 76% of HNC oral cancer ones (239/313). By mutation mapping, we found that both AT-84 and SCC VII carried the Trp53 p.Arg270 hotspot mutation , while 4MOSC2 carried Trp53 p.Glu221 and p.Gly241 mutations, which are equivalent to human TP53 p.Glu224 and p.Gly244 hotspot mutations found in HNC patient tumors  . The muttal.org) C. Since t tumors D. Specif.Arg273C , AT-84 aRobo1, Robo2, Robo3, Robo4, and Slit1 genes. This is followed by aberrations of the Notch, RTK signaling, JAK/STAT, TGF-β/Smad4, PI3K, Wnt, DNA repair, MAPK, FA, and NF-κB pathways, as well as the epigenetic, immune evasion, and metabolic machineries. Although few, these 5 mouse models do appear to capture HNC patient tumors’ diversified pathway aberrations  . Here, wrrations B. Notablrrations C. Lastlyhttps://www.ncbi.nlm.nih.gov/gene/about-generif/; with keyword filtering of “metastasis”, “HNSCC”, “OPSCC”, “OSCC”, etc.). The compiled “HNC invasion/metastatic candidate genome database” comprises a total of 1283 human genes, and their corresponding mouse gene names are also listed for referencing , but were found to be mutated in as high as 15%  of advanced/metastatic solid tumors and 1.07% (2/186 patients) in metastatic cancer annotated as HNC in the MSK-IMPACT cohort from the Memorial Sloan Kettering (MSK) Cancer Center [KRAS mutations in HNC patient tumors implicates their likely causative role in HNC metastasis, which can potentially be druggable. Subsite analysis showed that, in oral cavity cancer, KRAS mutations occur in 0.32% in TCGA-HNC but 1.85% in MSK-IMPACT  of nasopharyngeal cancer, 12.50% (1/8 cases) of salivary gland cancer, 12.50% (1/8 cases) of other squamous cell carcinomas (SCCs) of the head and neck, and 11.11% (1/9 cases) of cancers of unknown primary in the head and neck region, as annotated by MSK-IMPACT  and Mill1 (MICA), which are involved in antigen presentation, as well as an array of inhibitory and stimulatory immune checkpoint molecules, including Slamf7 (SLAMF7), Cd40 (CD40), and Tnfrsf14 (TNFRSF14). For PD-1/PD-L1, MOC2 and MOC2-10 have Pdcd1  mutations, whereas AT-84 carried an Il2ra (IL2RA) mutation. Although gene copy changes were only available for AT-84 and SCC VII per our exome sequencing, we did find that these 2 models could partially capture gene copy changes of some immunomodulatory genes as noted in the TCGA-HNC tumors (Cd274 (CD274), and losses of tumor necrosis factor receptor (TNFR) superfamily genes, including Tnfrsf 18 (TNFRSF18).In order to employ or to allow rational engineering of these models to address specific immune-related questions, their immune profiles must first be defined. First, we examined if these models carry any intrinsic aberrations of a wide spectrum of immunomodulatory molecules, which have the ability to stimulate or suppress cancer growth when targeted by immunomodulatory drugs, theoretically. These immunomodulatory molecules included 75 genes involved in antigen presentation, inhibitory and stimulatory immune checkpoint molecules defined by Thorsson et al. . The humC tumors A. These Il2ra (IL2RA) mutation, copy number gains of Ccl5 (CCL5), Cx3cl1 (CX3CL1), Cxcl9 (CXCL9), Cxcl10 (CXCL10), Il1a (IL1A), Il1b (IL1B), Il4 (IL4), and Il13 (IL13), suggestive of altered chemokine signaling in SCC VII. In contrast AT-84 carried an Il2ra (IL2RA) mutation, as well as copy number gains of Cx3cl1 (CX3CL1), Il4 (IL4), and Il12a (lL12A), and heterozygous loss of Ccl5 (CCL5). Collectively, these 5 models encompass diverse immunomodulatory aberrations partially representing the heterogeneous immunomodulatory signaling of HNC.Within the immunomodulating gene set defined by Thorsson et al. , there ahttps://www.genome.jp/kegg/, hsa04060), we found that 4MOSC2 carried the highest number of mutations (22/159) in these cytokine-related genes, followed by SCC VII (10/159 genes), MOC2 (4/159), MOC2-10 (4/159), and AT-84 (2/159) (Csf1r), which promotes survival of hematopoietic precursor cells, was found to be mutated in 4/5 mouse models (except for AT-84). Regarding AT-84 and SCC VII with CNV data available for analysis, we found that AT-84 harbored gene copy losses of 49 of these genes, including genes of the C-C motif chemokine (CC) subfamily, the C-X-C motif chemokine (CXC) family, the TNF family, and the interleukin (IL) family. Based on the gene-level copy changes, we found that SCC VII harbored copy number gains/amplifications of 85 amplifications of genes across the CC chemokine subfamily, the CXC chemokine family, the TNF family, the interleukin (IL) family, and the TGF-β family . As sho (2/159) B. The coβ family B.Erbb4, Ephx1, Ltk, Fgfr1, Epha6, Ddr1, Csf1r, Tyro3, Ror2, Epha4, Pdgfra, Lmtk3, and Insr (Erbb4 mutation was commonly identified in 3 out of 5 models (p.F1071S and p.E1168*) , DNA damage and cell cycle gene aberrations are found altered in all 5 models, whereas JAK/STAT aberrations are only found in AT-84, SCC VII, and 4MOSC2.Using the most updated druggable gene list including 96 genes currently or potentially druggable by FDA-approved drug indications or potential agents , we examand Insr C. Import.E1168*) C. Among e models . In brieMuc5ac, Trem3, Ttn, and many others. Strikingly, Erbb4 and Kras mutations are present in HNC metastases with relatively higher mutation frequency than in primary oral tumors. Our results first emphasize that as few as five metastatic cell models, potential key human-relevant HNC metastatic aberrations, are being frequently recapitulated. Thus, these models can be readily utilized for metastasis biology studies or drugging of metastatic genetic aberrations, which is an area of emerging importance in HNC in this post-genome era. A summary in As of today, there are five convenient xenograftable immunocompetent metastatic HNC models. Our whole-exome analyses of the two most commonly used models, namely AT-84 and SCC VII, reveal mutational signatures of APOBEC edit, tobacco smoke, UV damage, aging-related signature, and microsatellite instability, similar to that of HNC patient tumors. Importantly, extensive evaluations of the human HNC relevance of all five immunocompetent metastatic HNC models demonstrated mutational hallmarks representative of sustaining proliferation, invasion/metastasis, and resisting cell death, consistent with the reported metastatic nature of these models. Cancer gene analyses indicate the presence of several candidates that have not been previously investigated in HNC. Metastatic gene analyses also uncover new metastasis candidate events that have not been previously examined in HNC, including In terms of immunoregulatory molecules and cytokine/chemokine signaling, the five models partially harbor diverse genetic events as in human HNC tumors. These findings not only imply that more models are to be established to better mimic patient tumors in terms of immunoregulation, but also ultimately define which of these models can be amenable for genetic manipulation if immune regulatory genes and host immune interactions are to be examined one by one in vivo. Lastly, our druggability analyses demonstrate that with these five models alone, they seem to provide a sizeable list of druggable mutations for precision medicine developments, with a decent number of druggable events for metastatic candidates, DNA repair, receptor tyrosine kinase, as well as the JAK/STAT and MAPK/RAS pathways. Our results not only inform the human HNC relevance of these models, but also provide an extensive catalogue of genetic events for both basic and translational HNC research. The community can reference our results to choose the right models for the study of endogenous aberrations, or choose a suitable model based on their genetic background delineated in this study for engineering a specific candidate gene in question. Nevertheless, one has to bear in mind that there are some limitations of these mouse immunocompetent models, which are universal for any tumor types, including HNC. First, despite our detailed genetic characterizations, these tumor models were derived from mouse origin, but not human. Therefore, there could be biological differences between the gene or mutation functions in mouse vs. human. Second, these mouse xenografts are surrounded and supported by mouse stroma; thus, the study of tumor genetic events on stromal interactions will only be relevant in mouse contexts, including immune interactions. Third, therapeutically and for examples, the mouse version of antibodies may be needed for efficacy determination, such as the mouse anti-PD-L1 antibody. Any therapeutic results generated from mouse would still need to be fully investigated in human clinical trials with human versions of the therapeutic antibodies, for example. It should be noted that more sophisticated models, such as human HNC patient-derived xenograft (PDX) models, or even humanized PDX models are possible alternatives for the study of human somatic mutations on tumor growth, drug responses, as well as human immune cell interactions. Yet, these PDX models have to be generated with great coordinated clinical–preclinical research efforts and genomically characterized, and may not be of easy or equal access for experimentation for all investigators at this moment.In conclusion, our findings first highlight the HNC clinical relevance of these immunocompetent metastatic HNC models that may allow future drugging studies or biology studies to be conducted in host immune contexts. Lastly, with only five such models, a number of previously novel metastasis-related and drug targets are revealed for plausible precision medicine investigations. More such models are worth establishing for biology hypothesis-driven studies as well as treatment explorations.2 at 37 °C.The AT-84 cell line was a kind gift from Dr. Michael P. Hier . SCC VII was kindly provided by Professor Sven Brandau  and Dr. Herman D. Suit . Both AT-84 and SCC VII were cultured in RPMI medium 1640  with 10% heat-inactivated fetal bovine serum (FBS) and 1× penicillin (100 units/mL)/streptomycin (100 μg/mL) (Thermo Fisher Scientific). Cells were maintained in a humidified incubator  of 5% CONormal DNA was extracted from the tail of C3H mouse . DNA from AT-84 and SCC VII were extracted using the Qiagen DNAeasy blood & tissue kit  as per the manufacturer’s protocol. DNA samples (a minimum of 200 ng) were whole-exome sequenced by DNA link  using the Illumina Novaseq 6000 platform  with ~50× coverage. Raw FASTQ files were processed for further analysis using GATK tools . The FASTQ files of AT-84 model are archived in doi: 10.6084/m9.figshare.12623786 and the FASTQ files of SCC VII model are archived in doi: 10.6084/m9.figshare.12623882.https://cnvkit.readthedocs.io/en/stable/). Instead of using the matched normal data from each sample, we pooled entire normal samples’ data set together to calculate the log2 copy ratio for individual bins and segments. Scatter plot shows bin-level log2 coverages and segmentation calls together. Chromosome plots display segment gain or loss and corresponding genes in chromosome scale.Somatic mutations were detected by the matched tumor/normal pair through Mutect  and Strelka . Mutation profile and COSMIC mutation signature were called used R package “MutationalPatterns” (Version 2.0.0). Copy number analysis was performed using CNVkit (version 0.8.5; The cancer hallmark gene sets were previously defined by Zhang et al. . The cytComprehensive genomic analyses of these current five xenograftable models have informed us about new potential drug targets for metastatic HNC. Immunocompetent metastatic HNC models are worth developing to address therapy- and invasion/metastasis-related questions in host immunity contexts.


Fossil fuels are energy recourses that fulfill most of the world’s energy requirements. However, their production and use cause severe health and environmental problems including global warming and pollution. Consequently, plant and animal-based fuels , such as biogas, biodiesel, and many others, have been introduced as alternatives to fossil fuels. Despite the advantages of biofuels, such as being renewable, environmentally friendly, easy to source, and reducing the dependency on foreign oil, there are several drawbacks of using biofuels including high cost, and other factors discussed in the fuel vs. food debate. Therefore, it is imperative to produce novel biofuels while also developing suitable manufacturing processes that ease the aforementioned problems. Polyhydroxyalkanoates (PHAs) are structurally diverse microbial polyesters synthesized by numerous bacteria. Moreover, this structural diversity allows PHAs to readily undergo methyl esterification and to be used as biofuels, which further extends the application value of PHAs. PHA-based biofuels are similar to biodiesel except for having a high oxygen content and no nitrogen or sulfur. In this article, we review the microbial production of PHAs, biofuel production from PHAs, parameters affecting the production of fuel from PHAs, and PHAs biorefineries. In addition, future work on the production of biofuels from PHAs is also discussed. Polyhydroxyalkanoates (PHAs) are bacterial polyesters synthesized by several prokaryotic microorganisms under unbalanced nutrition conditions, e.g., carbon and energy storage conditions. Lemoigne first discovered these thermoplastics in 1926, and since then, PHAs have attracted significant commercial and research interest from the eco-friendly polymer market due to their favorable properties such as high biocompatibility, excellent biodegradability, diverse chemical structure, and manufacturing from renewable carbon resources ,4,5.2, H2O, and CH4, which facilitate the natural cycle of circulatory and renewability. In addition, the spent PHAs can undergo hydrolysis and produce optically pure building blocks which can be used as synthons for pharmaceuticals, organic synthesis, and fragrances [Bio-based polyesters are considered alternates for petrochemical plastics. Moreover, among the various biopolymers, PHAs symbolize a sustainable future alternative for fossil fuel-based plastics. PHAs have mostly been synthesized by microbial cultures grown on renewable materials in clean environments ,7,8,9. Fagrances . MoreovePHAs are long polymeric molecules that exhibit ester linkages in their structures. PHAs are synthesized by various types of prokaryotic microorganisms as intracellular storage materials comprising significant amounts of carbon and energy . A PHA mPseudomonas oleovorans and Pseudomonas fragi are bacteria that can produce mcl PHAs through the beta (β) oxidation of alkanoic acids by producing hydroxyalkanoyl-CoA as a substrate [Escherichia coli via genes or exogenous and endogenous processes [The synthesis of PHAs is a simple biosynthetic process consisting of only three genes and three enzymes. ubstrate ,18. Furtrocesses ,20,21. Irocesses ,23,24.R)-3-hydroxybutyrate (P3HB) and several copolymers such as P3HBHHx of (R)-3-hydroxybutyrate (3HB), (R)-3-hydroxyhexanoate (3HHx), P3HBV of (R)-3-hydroxybutyrate (3HB), and (R)-3-hydroxyvalerate (3HV) [In the 1980s, numerous companies tried to produce PHAs on an industrial scale based on the expectations that petroleum prices would increase over time. People would prefer to use eco-friendly biodegradable plastics or green plastics instead. Moreover, industries such as Chemie Linz AG, Austria; ICI, UK; and TianAn, China, successfully produced poly-(te (3HV) ,27,28,29Both wild type and recombinant bacteria are used to produce PHA . The proA. eutrophus, Protomonas extorquens, and P. oleovorans are included in this group. On the other hand, the second group does not require the limitation of essential nutrients bacteria (commonly known as growth-associated PHA biosynthesis). Alcaligenes latus, a mutant strain of Azotobacter vinelandii and recombinant E. coli belongs to the second group of bacteria [A homopolymer can be defined as a polymer that comprises >99% by weight of one type of monomer and <1% by weight of another. PHAs can be produced as homopolymers, copolymers, or blends depending on the bacterial strain or growth substrate used, and more than 300 species, mainly of bacteria, are reported to produce these polymers . The bacbacteria . P3HB, tbacteria ,38, P4HPbacteria , poly, poly, P3HB4HB (over 75%), and P3HBV (over 75%), by C. necator and E. coli. Moreover, these results led to further genetic manipulations of bacteria for the production of PHAs. A. latus is another strain (similar to R. eutropha) that was also used for the production of P3HB and P3HBV [nd P3HBV ,50,51.Pseudomonas putida KT2442, a well-studied producer of PHA, to synthesize PHA homopolymers including PHHx and PHHp. Moreover, they synthesized an almost homopolymer of poly(3-hydroxyoctanoate-co-2mol% 3-hydroxyhexanoate) (PHO*) when hexanoate, heptanoate, and octanoate were used in the growth medium. The phaG gene of P. putida KT2442, encoding for R-3-hydroxyacyl-ACP-CoA transacylase and β-oxidation related genes, had been deleted preventing fatty acid substrates’ shortening. This leads to the accumulation of mutant to produce mcl PHA homopolymers. On the other hand, when PHA synthase genes phaC1 and phaC2 were exchanged with PHA synthase operon phaPCJ from Aeromonas hydrophila 4AK4, or P3HBC from R. eutropha, PHV or P3HB were produced using valerate, butyrate, and γ-butyrolacton as substrates, respectively. In addition, Liu and Chan [fadB and fadA knockout mutant of P. putida KT2442. In another study, Wang et al., [Pseudomonas entomophila LAC23 (designed from P. entomophila L48) and deficient β-oxidation pathways to produce mcl PHA homopolymers. The authors found that P. entomophila LAC23 could be used for the synthesis of different mcl PHAs when using appropriate fatty acids as carbon sources . The S. enterica accumulated significant amounts of P3HBV when grown aerobically using glycerol as a glucose source. Li et al., [E. coli strain for the synthesis of P3HB4HB using glucose as a carbon source. The genes responsible for succinate degradation and accumulation of P3HB in Clostridium kluyveri and R. eutropha, respectively, were co-expressed for the synthesis of P3HB. Additionally, the sad and gabD genes of E. coli were deleted for the synthesis of the 4HB monomer. In another study, Zheng et al., [A. hydrophila 4AK4 and P. putida GPp104 for the production of P3HBHHx copolymers using gluconate and glucose as carbon sources. A truncated gene (tesA) encoding for cytosolic thioesterase I of E. coli, which is used for the conversion of acyl-ACP into free fatty acids, was incorporated into A. hydrophila 4AK4. The recombinant strain was able to synthesize 10% and 19% (w/w) P3HBHHx when grown on gluconate and glucose, respectively. co-3-hydroxybutyrate) (P2HA-co-P3HB) in engineered E. coli using glucose as a carbon source and hydrophobic amino acids as supplementation. Four different amino acids, i.e., leucine, valine , isoleucine (Ile), and phenylalanine, were introduced into the growth medium and P2HB-co-P3HB production was observed when Val was used as supplementation. co-P3HB in E. coli from biomass-derived carbon sources.Koller et al. , reporte et al.,  successf et al.,  construc et al.,  geneticab-P3HBV block copolymers in C. necator with the periodic addition of substrates (fructose and pentanoic acid). The P3HB and P3HBV blocks were synthesized during the fructose utilization and pulse feed of pentanoic acid. Though, the P3HB-b-P3HBV block copolymers still exhibited brittleness due to the brittle nature of scl PHAs. However, the combination of scl and mcl block copolymers could result in better properties compared to pure scl or mcl PHAs copolymers. In this context, Li et al., [b-PHVHHp  (PHVHHp)) block copolymers by recombinant P. putida KTOY06ΔC A.c )(phaPCJ . The authors demonstrated the formation of block copolymers when butyrate (C4) and heptanoate (C7) were introduced into the growth media. Keeping this in view, Tripathi et al., [b-PHHx diblock copolymers in a β-oxidation deficient recombinant P. putida KT2442. The β-oxidation cycle was deleted to its maximum and glycerol was used as a carbon source. Recently, Sudo et al., [b-P3HB polymers in E. coli using glucose as carbon source and hydrophobic amino acids as supplementation. The authors demonstrated that block copolymers successfully accumulated in genetically engineered E. coli by expressing the chimeric PHA synthase (PhaCAR) gene. It was demonstrated that PhaCAR exhibits strict substrate specificity and that it can synthesize P2HB-b-P3HB in engineered E. coli from exogenous 2HB and 3HB. Moreover, 2-hydroxyalkanoate (2HA) units were incorporated using PhaCAR, the lactate dehydrogenase (LdhA), and CoA transferase (HadA). Four hydrophobic amino acids, leucine, Val, Ile, and phenylalanine, were introduced into the culture as supplementation and the required block copolymer was produced. b-P3HB in E. coli from biomass-derived carbon sources.A polymer that contains alternating segments of different polymer compositions, covalently linked via their reactive ends, is called block copolymers. Block copolymers can be in the form of diblock, triblock or repeating multiblocks. Studies have shown that PHA homopolymers and copolymers exhibit many unfavorable properties and a common setback in the commercialization of these polymers is their brittleness, which limits their end-use applications . Therefo et al.,  reported et al.,  adopted  et al.,  were abl2), methane (CH4), methanol (CH3OH), ethanol (C2H5OH), biodiesel, acetone (C3H6O), and several others. Globally, the transportation industry is a major source of carbon dioxide (CO2) emission and energy consumption. Liquid biofuels can replace fossil fuels in the transportation industry [Due to the scarceness of traditional fossil fuels, increased emissions of combustion pollutants, and their costs, biomass-based fuels have become an attractive alternative option. Biofuels refer to the fuels produced from organic materials such as plants and animals. industry . Liquid 2) and high nitrogen (N2) and sulfur (S) contents leading to the generation of environmental pollutants upon combustion. In contrast, HA esters have a high O2 content without any N2 or S. In general, oxygenated additives can reduce the exhaust smoke for diesel as well as decrease combustion times and ignition delay. However, oxygenated additives, like HA esters, have a low cetane number and a high heat of vaporization which makes it difficult to completely fuel diesel engines. Therefore, the introduction of HA esters as sustainable fuels or fuel additives contributed to the divergence of the biofuel market [In 2009, Zhang et al.,  introducl market . In cont2H5OH were compared. The results demonstrated that when HBME was blended with C2H5OH, the combustion heat of C2H5OH improved by up to 30%. However, the combustion heat was reduced when HBME was blended with gasoline and diesel. Furthermore, HBME and HAME were obtained via acid-catalyzed hydrolysis and the most commonly used acid catalyst is sulfuric acid (H2SO4). Moreover, until now, different concentrations of H2SO4 with methanol were used to reach the maximum yield of HBME or HAME.Zhang et al.,  reportedA. eutrophus TISTR 1107 and used it as a substrate to produce HBME using three acids  at three different concentrations  and with different types of solvents including methanol and ethanol. The production of HBME was performed at various reaction times of 10, 20, 30, 40, 50, 60, and 70 h. Moreover, the optimal conditions to produce HBME were methanol with 10% (v/v) H2SO4 at 67 °C for 50 h. The maximum yield of HBME (70.7%) was obtained under these specific conditions. Sangkharak et al., [Bacillus licheniformis M2-12 and used as a biofuel substrate. P3HB underwent esterification under acid- and base-catalyzed reaction conditions. The acid-catalyzed reaction proceeded using methanol with 10% (v/v) H2SO4 at 67 °C for 60 h. In contrast, the base-catalyzed hydrolysis of P3HB was performed using methanol with 2% (w/w) potassium hydroxide at 67 °C for 60 h and exhibited a high recovery of 68%. The fuel-related properties and purity (>95%) of the HBME produced from the acid-catalyzed hydrolysis of P3HB were investigated. The high molar mass, carbon and oxygen content, freezing point, and density of HBME showed that it can be potentially used as novel biofuel or as a fuel additive. The increasing need for biofuels may also increase the demand for biofuel additives or lubricants. Keunun et al., [C. necator, by a two-step fermentation process that utilizes this P3HB as a novel substrate, for the synthesis of biolubricants. The lubricant was produced via a two-step transesterification process.Choonut et al.,  document et al.,  reported et al.,  reportedSeveral factors that affect the yield of HAME biofuels have been identified. These include reaction time, temperature, type and content of alcohol, as well as catalyst type and concentration.The conversion of fatty acids to esters is directly proportional to the reaction time. At the start, the dispersion of alcohols into the PHAs slows down the reaction rate, however, the reaction rate increases after thorough mixing. In general, the product yield reaches a maximum in < 90 min, after which it remains relatively constant upon a further increase in reaction time. Choonut et al.,  studied Studies have shown that a high reaction temperature decreases the viscosity of fatty acids, which leads to an increase in reaction rate and a reduced reaction time. However, increasing the reaction temperature above a certain level results in a decrease in yield due to the saponification of triglycerides. In general, the reaction temperature must be lower than the boiling point of alcohol used. Base-catalyzed alcoholysis is normally performed near the boiling point of the alcohol or even at room temperature . Zhang e3OH, C2H5OH, propanol (C3H7OH), and butanol (C4H9OH), of which CH3OH and C2H5OH are the most used. These two alcohols are the first choice for laboratory-scale research owing to their low cost and physical and chemical properties. In general, a higher amount of alcohol leads to a higher esterification conversion of the polyesters to biofuels. Weerachanchai et al., [3OH or C2H5OH to acid under optimum conditions led to a 73.39% and 54.80% esterification conversion, respectively. However, upon a twofold increase in the mole ratio of alcohol, the conversion only increased by 2.42%. CH3OH gave higher esterification conversion compared to C2H5OH, which could be ascribed to the length of the alkyl group (C1 vs. C2) where the higher solubility and activity of the scl alcohol (CH3OH) promotes a faster reaction rate. Long-chain alcohols result in longer reaction times at the same reaction temperature of the scl alcohols, or shorter reaction time at higher reaction temperatures [3OH and C2H5OH) on the esterification of P3HB to produce HBME and found that CH3OH with 10% acid catalyst gives the highest yield.The alcohols used in the esterification reactions include CH et al.,  perform eratures . Choonuteratures  studied 3PO4, organic sulfonic acids, and HCl are also used. Zhang et al., [3PO4, H2SO4, and HCl, on the conversion of P3HB to HBME. Their findings suggested that an acid-catalyzed system containing H2SO4 as catalyst gives maximum yield.In general, acid- and base-catalyzed systems are used for the esterification of polyesters. Acid-catalyzed systems are mostly used to produce HAME biofuels, for which H2SO4 is the most frequently used catalyst. However, other acids such as H et al., , Wang et et al., , Keunun  et al., , and San et al.,  investigv/v) acid concentration is used, but decrease upon a further increase in catalyst concentration. Zhang et al., [2SO4 and reported a 52% conversion. In contrast, Wang et al., [Catalyst concentration affects the yield of HAME biofuels. In general, the product yield increases when a 10%  . Unlike gasoline . Hence, gasoline ,134,135.Petroleum shortage for plastic materials.Reduced CO2 emissions.Environmental protection.In conclusion, it has become clear that PHA-based biofuels are creating industrial value in energy, and the development of PHAs can address three basic issues:As a source of biofuels, PHAs are very promising biopolyesters since they do not need to be of high purity. Thus, PHAs can be obtained from crops, activated sludge, or nutritious wastewater making it cost-effective while also addressing the food vs. fuel and fuel vs. land controversies. Hence, PHAs are novel substrates for biofuel production where recent developments in PHAs synthesis concerning open and continuous mixed cultures will produce cost-effective PHAs for the biofuel applications. After being used as bioplastics, PHAs can undergo methyl esterification to biofuels, which further extends their application value. However, much work is still needed to make PHAs cost-effective so that PHAs-based biofuels can be used as an alternative to existing biofuels such as biodiesel, ethanol, methane gas, and hydrogen.In the future, the production costs of PHAs should be taken into consideration to enhance their commercialization. The production of PHAs in activated sludge or wastewater should be improved. So far, P3HB is mostly used in the production of HAME biofuels, thus, more monomers should be explored and tested for esterification. It would be worthwhile to develop HAME into biolubricants or fuel additives for the diversification of the biofuel or fuel additive industry. In addition, upcoming research should also focus to improve the quality of HAME biofuels.


TP53 and PIK3CA. Additionally, mutations in the other genes of the PI3K/AKT pathway indicated its importance in the pathogenesis of MBC. Regarding copy number variations (CNVs), MYC was the most frequently amplified gene, and the most frequent gene loss affected the CDKN2A/CDKN2B locus. Furthermore, the pattern of mutations and CNVs of MBC differed from those reported in other TNBC. However, the molecular profile of MBC was not homogeneous among histological subtypes, being the alterations in the PI3K pathway most frequent in spindle cell carcinomas. Transcriptomic studies have demonstrated an epithelial to mesenchymal program activation and the enrichment of stemness genes in most MBC. In addition, current studies are attempting to define the immune microenvironment of these tumors. In conclusion, due to specific molecular features, MBC have a different clinical behavior from other types of TNBC, being more resistant to standard chemotherapy. For this reason, new therapeutic approaches based on tumor molecular characteristics are needed to treat MBC.Metaplastic breast carcinoma (MBC) is a heterogeneous group of infrequent invasive carcinomas that display differentiation of the neoplastic epithelium towards squamous cells and/or mesenchymal-type elements. Most MBC have a triple negative phenotype and poor prognosis. Thus, MBC have worse survival rates than other invasive breast carcinomas, including other triple negative breast carcinomas (TNBC). In this study, we reviewed the molecular features of MBC, pointing out the differences among subtypes. The most frequently mutated genes in MBC were  Among predominantly triple negative breast carcinomas (TNBC), metaplastic breast carcinoma (MBC) is a histologically heterogeneous group of invasive carcinomas that display heterologous differentiation of the neoplastic epithelium towards squamous cells and/or mesenchymal-type elements such as spindle, chondroid, and osseous cells . AlthougAccording to their behavior and histopathological features, MBC can be subclassified as high-grade and low-grade . High-grSpCC is characterized by a predominant proliferation of intermediate to highly atypical spindle cells adopting multiple architectural patterns. Squamous differentiation can be predominant in some MBC or may be present in different proportions with other components, especially spindle cells, in MMBC. Pure SqCC are frequently cystic tumors, in which a central cavity lined by atypical squamous cells is surrounded by neoplastic cells, with different degrees of squamous differentiation and a reactive stroma . MBCHMD MBC is more frequently diagnosed in women between 50 and 60 years old, with a median age around 59 years. In one series, important age differences among histological subtypes were observed, MBC with chondroid differentiation occurring at a mean age of 71 years, whereas spindle and squamous cell carcinomas presented at mean ages of 56 and 48 years old, respectively ,25,26,27HER2 positivity has been reported in 0–13% and 0–10% of the series, respectively [Regarding biomarker expression, around 85% of HG-MBC are triple negative. Hormone receptor positivity and ectively ,25,26,27In this study, we reviewed 14 series ,16,28,29TP53 was the most frequently mutated gene in the 13 series that sequenced it, and it was found altered in all histological subtypes [subtypes ,15,29,31subtypes ,12,13,15subtypes .PIK3CA was the second gene with the highest mutation frequency. This gene was sequenced in 13 of the 14 series reviewed [reviewed ,29,31, areviewed ,12,13,15reviewed ,34. The PIK3CA, mutations in PTEN (12.7%), PIK3R1 (11.2%), NF1 (9.8%), HRAS (8.5%), and AKT1 (3%) also occurred  [Somatic mutations in % of MBC . InteresBC (NF1) ,39,40,41TERT promoter mutations, which are responsible for upregulation of TERT expression and telomerase activation. These TERT promoter mutations occur in 25–33% of MBC [Krings et al.  demonstr% of MBC ,11 (TablCTNNB1 (beta-catenin) mutations in MBC [APC (5%), a key component of the beta-catenin degradation complex, and FAT1 (11%)  . Moreovechanisms .BRCA1, are downregulated in MBC compared to other TNBC [BRCA1 (3–15%), BRCA2 (2–6%), and ATM (2–12%)  . Interescarriers ,45,46,47KMT2D (17%) and ARID1A (6%), as well as in other genes at lower frequencies , CCNE1 (5.9%), and CDK4 (4%). In addition, CCND3 and CCND2 were found amplified in 15% and 5% of MBC in a single study, respectively . Other amplified genes also coding for tyrosine kinase receptors included FGFR1 (5%) and ERBB2 (4.8%). Downstream pathways, such as KRAS and PI3K, were also affected by gene amplification in RAS, NF1, PIK3CA, SOX2, and AKT3 (5% frequency in each gene) (The second gene with the highest frequency of amplification in MBC was ch gene) .CDKN2A/CDKN2B locus (19%), PTEN (14.9%) and RB1 (6.5%) losses were found at lesser frequencies , also involved in the PI3K pathway [TERT mutations in 80% of SpCC and in 20% of SqCC, but in none of the 10 MBCHMD. Amplifications of MYC and EGFR were significantly more frequently observed in tumors with squamous or spindle cell metaplasia [All these data tend to suggest that  pathway ,15. In a pathway  showed ptaplasia . Epithelial to mesenchymal transition (EMT) is a biological process that involves the acquisition of a mesenchymal phenotype by the  epithelial cells, endowing these cells with migratory and invasive properties, promoting cancer progression, preventing cell death and senescence, and inducing resistance to chemotherapy ,49,50. FCDH1), but also occludens zone 1 (ZO1), desmoplakin, keratin 7, keratin 18, and keratin 19, among others [The acquisition of a mesenchymal phenotype in MBC is associated with a switching of cadherins (from E-cadherin to N-cadherin and cadherin 11) and the downregulation of epithelial markers including not only E-cadherin , SNAI2 (Slug), ZEB1, ZEB2, TWIST, etc. Most of these EMT-TF, which function as transcriptional repressors of E-Cadherin, are upregulated in MBC [EMT can be activated by different pathways, such as Transforming Growth Factor Beta 1 (TGFβ), tyrosine kinase receptors, Wnt, and Hippo, among others . These pd in MBC ,54,55,56ZEB1, ZEB2, SNAI1, and SNAI2, ultimately influencing E-cadherin expression levels. The downregulation of the miR-200 family has been reported in MBC and is not only due to the transcriptional repression by EMT-TF, but also to the promoter methylation [The miR-200 family plays a major role in regulating epithelial plasticity, mainly through its involvement in double-negative feedback loops with the EMT-TF hylation . CDH1, EPCAM, CLDN3, and CLDN8. Accordingly, the transcriptomic profile of SpCC is closely related to that reported in claudin-low breast cancer [OSMR, which plays a role in mesenchymal differentiation and bone formation, was found to be mutated in two MBC with extensive osseous differentiation and in no other histopathological subtype [EMT in MBC allows cells to acquire different phenotypes due to secondary trans-differentiation. Accordingly, different expression patterns have been reported in SpCC, SqCC, and MBCHMD with chondroid differentiation ,52. Thus subtype .Finally, MBC have markedly elevated CD44/CD24 and CD29/CD24 ratios and ALDH-1 expression, suggesting that MBC could be enriched in stem-cell-like cells ,54,58.There are few studies analyzing the immune microenvironment in MBC. Results on programmed cell death ligand-1 (PD-L1) expression in MBC tumor cells are conflicting, probably due to the low number of tumors analyzed to date. Joneja et al.  and DillZEB-1 and miR-200 [At present, mechanisms responsible for PD-L1 expression remain unknown, since only one study has reported PD-L1 locus amplification in 0.5% of MBC (1 out of 192)  and that miR-200 . These oThere is scarce information regarding inflammatory cells in MBC. Tray et al. , in a stIn a study by Joneja et al. , 40% of Mismatch repair deficiency, a molecular characteristic associated with inflammatory infiltration in other tumors, is very infrequent or absent in MBC .MBC is a poor prognosis invasive breast cancer. According to our review, its prognosis was worse not only when compared with conventional invasive ductal carcinomas, but also when compared with other TNBC. We reviewed 8 series comparing survival between patients with MBC and TNBC ,62,63,64In addition, we reviewed 12 series in which the survival rates between patients with MBC and other types of breast cancer, not specifically TNBC, were compared ,67,68,69n = 405 and n = 347) that SpCC and mixed histologies had more aggressive biological behaviors than SqCC and MBCHMD. However, other authors analyzing series with a smaller number of cases have not found statistically significant differences among these histological subgroups [There are conflicting reports regarding whether the prognosis of HG-MBC differs among different histological groups. Rakha et al.  and McCaubgroups ,21,22,24There are also conflicting reports regarding whether the prognosis of MBC differs depending on the receptor status. In a study by Mills et al.  analyzinAdditionally, the series by Mills et al.  and SongIt has been suggested that the poor prognosis in MBC might be due to a higher degree of chemoresistance than in other TNBC. In this sense, there are few studies analyzing pathological response to neoadjuvant chemotherapy in MBC. In 11 studies including a total of 150 patients ,74,75,76Although all studies included few cases and the sample is not powered to analyze differences among histological subgroups, these results clearly demonstrate that MBC shows poor chemosensitivity to conventional chemotherapy. Conventional therapeutic approaches, including surgery, chemotherapy, and radiotherapy have been the focus of a recent review .Due to its relative chemoresistance and poor prognosis, new approaches based on tumor molecular characteristics are needed to treat MBC. The high frequency of alterations in the PI3K/AKT/mTOR pathway makes MBC a good candidate to be treated with mTOR inhibitors. Accordingly, it has been reported that patients with advanced MBC treated with an mTOR-based systemic therapy regimen  had better long-term outcomes compared with patients with non-metaplastic triple-negative breast cancer treated with the same regimen, suggesting that metaplastic histology may predict benefits from agents targeting the PI3K/AKT/mTOR pathway. In addition, the authors observed that the presence of a PI3K pathway aberration was associated with a significant improvement in objective response rate ,80.Anecdotic observations have demonstrated that some MBC can respond to check-point inhibitors. Thus, Adams et al.  and Al SBRCA pathogenic variant (gBRCA-positive). As previously reviewed, some MBC can occur in gBRCA-positive women and can respond to PARPi. In this sense, Litton et al. [BRCA2 pathogenic variant. It would be interesting to determine if MBC with somatic mutations in BRCA1 or BRCA2 and with BRCA1 promoter hypermethylation also respond to PARPi.Two randomized phase III trials, the OlympiAD  and the n et al.  reportedOur understanding of the molecular alterations of breast cancer have enormously advanced during the last two decades and have been the basis for the development of new targeted therapies. More recently, studies based on next generation sequencing are also deciphering the molecular profile of infrequent breast cancer histological types, such as MBC. Considering the poor response of MBC to conventional chemotherapy, new targeted therapies are urgently needed. Although some preliminary studies have shown promising results using m-TOR inhibitors and, in anecdotic cases, response to PARPi and check-point inhibitors, at present there are no targeted therapies specifically indicated for MBC. Although it is recommended that MBC should be included in clinical trials designed for TNBC, the differences in the molecular profiles between MBC and other TNBC, as well as the heterogeneity among MBC subtypes, will probably translate into a more complicated interpretation of results. Ideally, specific cohorts of different MBC subtypes should be included and specifically analyzed according to their molecular features in clinical trials. Due to the low prevalence of these tumors, multi-institutional efforts should be made in order to accelerate the identification of effective therapies for this aggressive tumor.


Pathological pain can be initiated after inflammation and/or peripheral nerve injury. It is a consequence of the pathological functioning of the nervous system rather than only a symptom. In fact, pain is a significant social, health, and economic burden worldwide. Flavonoids are plant derivative compounds easily found in several fruits and vegetables and consumed in the daily food intake. Flavonoids vary in terms of classes, and while structurally unique, they share a basic structure formed by three rings, known as the flavan nucleus. Structural differences can be found in the pattern of substitution in one of these rings. The hydroxyl group (–OH) position in one of the rings determines the mechanisms of action of the flavonoids and reveals a complex multifunctional activity. Flavonoids have been widely used for their antioxidant, analgesic, and anti-inflammatory effects along with safe preclinical and clinical profiles. In this review, we discuss the preclinical and clinical evidence on the analgesic and anti-inflammatory proprieties of flavonoids. We also focus on how the development of formulations containing flavonoids, along with the understanding of their structure-activity relationship, can be harnessed to identify novel flavonoid-based therapies to treat pathological pain and inflammation. E. coli as stimulus, it has been demonstrated that the adhesion of neutrophils in sinusoids depends on CD44 rather than Mac-1 (required for sterile inflammation), revealing, therefore, different adhesion molecules for neutrophil recruitment in sterile vs non-sterile inflammation , IC50= 5.5±0.1 and 48.8 ±0.5 µM) than rutin (IC50= 7.4 ±0.2 and 92.4±1.0 µM) [Flavonoids can be found on nature as their glycoside or aglycone forms. Flavonoid glycosides present increased solubility and stability in water, which, however, interferes with their activity. Given glycosylation occurs in hydroxyl groups, it changes structural key elements for their radical scavenging activity. Specifically, glycosylation changes the double bond in conjugation with the 4-OXO group in the C-ring at C2, C3 position, the (A-ring) . For insuercetin . Also, auercetin . Regardi±1.0 µM) . Thus, w− is produced by the reaction between superoxide anion and nitric oxide. Both mediators are produced at high amounts during inflammatory process by NADPH oxidase and inducible nitric oxide synthase [− in vitro, 3-hydroxyl moiety at B ring demonstrated to be important for flavonoids. For instance, quercetin a flavonoid that possess the 3-hydroxyl group has a higher scavenger ability (IC50 = 0.93 ±0.12 µM) when compared to the flavonols galangin (IC50 = 3.37 ±0.99 µM) and kaempferol (IC50 = 4.35 ±0.27 µM) which have the group 4-hydroxyl [O-dihydroxy (catechol group) is determinant to superoxide anion scavenging activity of flavones and flavanones. For instance, the presence of the following elements increases scavenging activity: no hydroxyl groups at the B-ring, a 4′-hydroxyl substitution, and O-dihydroxy (catechol group), where the last feature shows higher antioxidant capacity [− and superoxide anion scavenging activity and its reasonable that this scavenging activity accounts for flavonoids analgesic and anti-inflammatory activity. Flavonoids also present antioxidant effects by indirect mechanisms through activation of Nrf2 signaling pathway, for example [ONOOsynthase . These msynthase , such assynthase  and COX-synthase ,166, or hydroxyl . Similarcapacity . Therefo example . Chalcon example .32 and RelA phosphorylation at Ser536. Thus, 3′,3”,5′,5”-Tetramethoxychalcone seems to interfere with IKK complex responsible for IkB and RelA phosphorylation [536 in LPS-induced NF-κB activation in human primary monocytes [The analgesic and anti-inflammatory activities of flavonoids are related, at least in part, to their NF-κB inhibitory effects ,58,60,62rylation . Moreoveonocytes . Comparionocytes . Regardionocytes . Thus, t2 produced by COX-2 without the usual side effects produced by NSAIDs [H-chromen-4-one; 5,3′,4′-Trihydroxyflavone, 7,3′,4′-Trihydroxyflavone; and luteolin) is the catechol group in the B-ring [385, Trp387, Phe518, Ala201, Tyr248) and luteolin 3,4-dihydroxy groups formed H-bond between Tyr385 and Ser530 [As mentioned, flavonoids are drugs with safe pre-clinical profile without the common side effect of standard NSAIDs. For instance, luteolin inhibits PGIy NSAIDs ,174. Ribe B-ring . Dockingd Ser530 . Regardid Ser530 . It is rd Ser530 ,178.O-dihydroxy group at the B ring, the 2,3-double-bound bond in conjugation with the 4-oxo group at C ring, and the 3-hydroxyl and 5-hydroxyl groups at the C and A rings. Moreover, flavonoids derivation improves their activity, as in the case of the methoxy substitution in 3,3′,5,5′-Tetramethoxychalcone.IL-1β is a pro-inflammatory and hyperalgesic cytokine matured by NOD-like receptor (NLR) family, pyrin domain-containing 3 (NLRP3) inflammasome . Lim et 833 mimics the interaction made by the ketone moiety of LY294002 (PI3K inhibitor) and myricetin is recognized through B ring by Val882 residue of PI3K [473 and pretreatment the cells with quercetin (25 μM) suppressed the EGF-induced Akt phosphorylation at Ser473 [The PI3K/Akt pathway plays an essential role in the regulation of inflammatory responses ,183,184. of PI3K . In thist Ser473 . These fThe use of plants for therapeutic purposes is an ancient practice . As pharFlavonoids represent one of the most studied classes of metabolites with diverse phenolic groups, with an estimated 10,000 different members, having pollinator attractants, antimicrobial, and UV-protective properties in plant kingdom . The ant28H34O15), a flavonoid found in citrus fruits [29H36O15), a chalcone methylated compound, derived from hesperidin, with higher solubility, has been described as effective and safe in the treatment of vascular diseases when combined with other compounds such as vitamin C and Ruscus aculeatus extract . Treatment with HMC reduces symptoms such as pain, heaviness, and paresthesia, as reviewed by Boyle et al. [Hesperidin  is the most abundant dietary flavonol [Quercetin  consumption is considered safe, although muscle relaxation and sedation can occur when 30–100 mg/kg body weight doses are administrated [Apigenin , present in species derived from Silybum marianum, contains seven flavolignans and the flavonoid taxifolin (C15H12O7) [® , extract of Pinus maritima, is a mixture of flavonoids, mainly procyanidins [® daily for 3 weeks presented a decrease in C reactive protein levels and reduced use of painkillers and non-steroidal anti-inflammatory drugs [®, relief from daily pain, stiffness, and physical function were observed [®, a flavonoid-rich extract of Pinus radiate containing approximately 80% total proanthocyanidins and other water-soluble flavonoids, has been linked to neuroprotection properties [®  – 320 mg oligomeric procyanidins – improves leg health and reduces fluid retention in pre-menopausal phase [Plant extracts containing different classes of flavonoids have been studied in clinical trials and presents promising results. Silymarin (Livergol15H12O7) . Paramet15H12O7) . A meta-15H12O7) . Pycnogeyanidins . Sixty-sry drugs ,250. In observed ,205. Alvobserved ,251. Enzoperties ,253 and operties . Furtheral phase .So far, most clinical reports in the literature states flavonoids consumption as safe. Despite the main source of flavonoids is diet, it is important to highlight that supplement intake is growing, which leads to the concern of high-dosage toxicity and/or interactions with other dietary elements or medications, resulting in possible adverse effects . AlthougDifferent types of formulations have been applied to flavonoids, such as topical and oral formulations ,262. TopThe most challenging factor is the flavonoids’ low water solubility, which leads to lower absorption and consequently lower bioavailability after oral administration . In thisMicroencapsulation (pectin/casein by complex coacervation) of quercetin ameliorates acetic acid-induced colitis by providing a controlled release of quercetin at the mouse colon and improves the anti-inflammatory and antioxidant effects of quercetin compared to the non-encapsulated drug . Rutin-LSuperparamagnetic iron oxide nanoparticle (SPION) drug delivery system enhanced the bioavailability of quercetin. The SPION increases blood circulation time of quercetin and increases the concentration of quercetin in the brain that leads to higher antioxidant activity and more efficient interactions of quercetin with RSK2, MSK1, CytC, Cdc42, Apaf1, FADD, CRK proteins . NaringeSelf-Nanoemulsifying Drug Delivery System (SNEDDS) has been proved to improve the bioavailability of naringenin, quercetin, and rutin. The drug concentration time-curve of naringenin from SNEDDS revealed a significant increase in naringenin absorption compared to naringenin suspension . The optThe liposomal encapsulation for four types of flavonoids demonstrated that the quercetin-loaded liposomes showed higher stability and more antioxidant capacity than those loading rutin, luteolin and kaempferol ,275. TheWe have reviewed pre-clinical and clinical data about the anti-inflammatory and analgesic properties of flavonoids. Most studies have been demonstrating the potential therapeutic role and efficacy of flavonoids in cardiovascular diseases, osteoarthritis, Parkinson disease, colitis, cancer pain, arthritis, and neuropathic pain. The mechanisms of action of flavonoids are yet to be fully elucidated, but many studies have shown their relevance as a potent anti-inflammatory, analgesic, and antioxidative group of molecules. Indeed, flavonoids can block the expression and activation of many cellular regulatory proteins such as cytokines and transcription factors, resulting in diminished cellular inflammatory responses and pain. In conclusion, in view of the pharmacological activities of flavonoids, it could also be interesting to further develop protective delivery formulations containing flavonoids to treat inflammatory diseases and pain, since promising effects were already observed ,266.Flavonoids are multi-target molecules, and increasing attention has been given to these molecules due to their anti-inflammatory and analgesic properties. Diminishing the activity of varied pathways seems to present fewer side effects than abolishing the activity of one target, since, in general, the targets also have endogenous physiological roles. Flavonoids block the synthesis of inflammatory mediators such as IL-1β, TNF-α, NO, and COX-2, suppress VEGF and ICAM-1 expression, along with the activation of STAT3, NFkB, NLRP3 inflammasome, and MAP kinases pathways. Regardless of their broad pharmacological properties, flavonoids show a poor water solubility, inadequate permeability, and constrained bioavailability, potentially requiring high doses to show efficacy in . Phase 2Thus, flavonoid pharmacology, therapeutics, and pharmaceutical development remain a hot topic in inflammatory diseases and pain treatment.


BCR-ABL-negative myeloproliferative neoplasms (MPN), primary myelofibrosis (PMF) is the most aggressive subtype from a clinical standpoint, posing a great challenge to clinicians. Whilst the biological consequences of the three MPN driver gene mutations  have been well described, recent data has shed light on the complex and dynamic structure of PMF, that involves competing disease subclones, sequentially acquired genomic events, mostly in genes that are recurrently mutated in several myeloid neoplasms and in clonal hematopoiesis, and biological interactions between clonal hematopoietic stem cells and abnormal bone marrow niches. These observations may contribute to explain the wide heterogeneity in patients’ clinical presentation and prognosis, and support the recent effort to include molecular information in prognostic scoring systems used for therapeutic decision-making, leading to promising clinical translation. In this review, we aim to address the topic of PMF molecular genetics, focusing on four questions: (1) what is the role of mutations on disease pathogenesis? (2) what is their impact on patients’ clinical phenotype? (3) how do we integrate gene mutations in the risk stratification process? (4) how do we take advantage of molecular genetics when it comes to treatment decisions?Among classical  JAK2, CALR, or MPL genes. These mutations were initially described as mutually exclusive, but can indeed coexist in a small proportion of cases [JAK2, CALR, or MPL are sufficient to engender an MPN phenotype has been provided by mouse models, where expression of each mutation alone accurately re-capitulate distinctive features of human disease [The so-called “phenotypic driver mutations”, which are those able to drive the myeloproliferative phenotype in PMF, occur in of cases . Evidenc disease ,4,5.JAK2 V617F is rendered constitutively active. Indeed, the mutation results in loss of the normal inhibitory function provided by the pseudokinase (JH2) domain upon the active (JH1) kinase domain and causes subsequent cytokine independent cell growth.In 2005, a single point mutation V617F) was identified in half of patients with PMF 17F was i,9. JAK2 MPL gene result in amino acid changes of tryptophan 515 to leucine, lysine, or alanine (W515L/K/A), which is located within the cytoplasmic domain, proximal to the transmembrane domain [In 2006, additional genetic aberrations that perturb JAK/STAT signaling were found in 5–10% of patients with PMF. Mutations in exon 10 of the thrombopoietin receptor CALR), an endoplasmic reticulum (ER) chaperone responsible for the appropriate folding of protein before their trafficking either to the cell surface or for extracellular secretion, were identified in around one-third of patients with PMF [CALR mutations occur as heterozygous insertions and/or deletions that are all located in the last exon of the gene (exon 9). Although >50 different CALR mutations have been identified, all result in a +1 bp frameshift to an alternative reading frame that alters the amino acid composition in the C-terminal part of the protein from acidic residues to basic residues and also leads to a loss of its ER retention signal KDEL. Mutant CALR complexes with MPL and results in its constitutive activation [CALR mutations were originally classified as type 1 (52-bp deletion) and type 2 (5-bp insertion) on the basis that these mutations are the most common, accounting for around 50% and 30% CALR mutations, respectively [CALR C terminus [CALR mutations is relevant for MPN phenotype and prognosis, as will be discussed in the next section.In 2013, mutations in calreticulin  have been reported in a fraction of triple-negative MPN patients [Patients who do not carry  and MPL ,19. Therisorders . Recentlpatients . The sampatients , thus suTET2, DNMT3A, IDH1/2), chromatin modifications , RNA splicing , and DNA repair (TP53).Approximately one-third of patients with PMF harbor additional mutations in known drivers of myeloid malignancies. These mutations impact the process of DNA methylation  is now included among the major criteria for both prefibrotic-myelofibrosis (pre-PMF) and overt-myelofibrosis according to the 2016 World Health Organization (WHO) classification [TET2, DNMT3A, ASXL1) have been found in otherwise healthy persons, especially when older than 65 years, advocating caution in interpreting the results of genotyping for diagnosis in the absence of overt clinical and hematological abnormalities [These observations have been acknowledged from a diagnostic standpoint, so that, in the absence of fication , as repomalities . Then, tmalities .The type of mutation, mutation allele burden, order of acquisition, and combinations of genetic events may have an impact on the disease phenotype.JAK2 V617F mutations in PMF are associated with older age, higher HB level, leukocytosis, and lower platelet count [CALR mutations in PMF have been shown to associate with younger age, higher platelet count, less frequent leukocytosis, anemia, and transfusion requirements, fewer spliceosome mutations, and lower dynamic international prognostic scoring system-plus (DIPSS-plus) scores compared with JAK2-mutated disease [CALR type 1 variants with the aforementioned characteristics and phenotypically clustered type 2 variants with JAK2 mutants [CALR mutations on the basis of hematological and clinical variables has yielded inconsistent findings. CALR type 2 mutations have been shown to correlate with higher risk DIPSS-plus scores, marked leukocytosis, and higher circulating blast percentage compared with type 1 variants [JAK2 mutated PMF compared to CALR mutated PMF, despite the fact that calreticulin mutated patients display higher platelet counts, both in essential thrombocythemia and in PMF [JAK2 V617F appears to be thrombophilic also in patients with PMF, as in patients with PV and ET.et count ,27. Conv disease ,28,29. Svariants , Triple-d in PMF . Thus, JJAK2 V617F allele burden as a risk factor for shortened survival in PMF [JAK2 allele burden to be associated with elevated plasma C-reactive protein levels and a pattern of progressive disease, supporting a potential relationship between allelic frequency, inflammation, and disease evolution [JAK2 V617F allele burden higher than 75% are high-risk patients as they are prone to develop thrombo-hemorrhagic complications during the disease course. A link between CALR mutation allelic burden and disease phenotype has been reported in the literature as it was demonstrated for JAK2 mutation. A high CALR allele burden is more frequent in PMF than in ET [CALR-mutant burden have acquired copy neutral loss of heterozygosity (LOH) of chromosome 19p, involving the transition from heterozygosity to homozygosity for the CALR mutation [JAK2-mutant MPN and 1pLOH in MPL-mutant MPN [CALR-mutant MPN is faster than that observed in JAK2-mutant MPN [Driver mutation allele burden may be another factor that influences the clinical course in PMF. Concerning survival, earlier studies identified a low l in PMF ,33, as cvolution . Though volution . Concernan in ET . Patientmutation . Anyway,mutation , in conttant MPN ,38,39. Itant MPN .JAK2 V617F, and other from the same patient bear JAK2 V617F with an additional somatic mutation, then this indicates that JAK2 V617F came first. The order of acquisition influences clinical presentation as it has been demonstrated for ET and PV: mutations in either DNMT3A or TET2 are associated with an ET phenotype when acquired prior to JAK2 V617F; by contrast, acquisition of JAK2 V617F prior to mutation of DNMT3A or TET2 is associated with PV [JAK2 V617F was generally an earlier event in those with PMF [Somatic mutations in MPN do not seem to be acquired in a predetermined order as happens in other malignancies, but occur rather randomly . The ord with PV ,43. Datawith PMF .Finally, also the germline genetic background might influence the molecular and cellular consequences of nascent PMF clones after their acquisition of phenotypic driver mutations .Targeted sequencing of gene sets in myelofibrosis will be increasingly used in the near future because it will allow profiling of the mutational landscape of each patient and to better define the role of single or multiple, interacting mutations on clinical phenotype and prognosis .Over the past 10 years, prognostic scoring systems have been developed for PMF, including the International Prognostic Scoring System (IPSS) in 2009 , the DynIPSS utilizes five independent predictors of inferior survival evaluated at initial diagnosis: age > 65 years, hemoglobin <10 g/dL, WBC count >25 × 109/L, circulating blasts ≥1%, and presence of constitutional symptoms. Scores ranging from 0 to ≥3 define four risk groups  with a corresponding median survival of 11.3, 7.9, 4, and 2.3 years .IPSS was subsequently modified into the DIPSS, which uses the same prognostic variables but assigns 2 points instead of 1 to hemoglobin <10 g/dL and can be applied at any time during the disease course .9/L, and transfusion requirement. The new prognostic model, DIPSS-plus, identifies four risk groups with median survival ranging from 15.4 to 1.3 years [DIPSS was further refined by incorporating three additional DIPSS-independent risk factors: unfavorable karyotype, PLT count lower than 100 × 10.3 years .CALR mutations [CALR type-1 mutations [CALR and ASXL1: the best survival has been, indeed, reported for those patients harboring a CALR mutation with wild type ASXL1, while patients with the opposite genotype (CALR wild type and ASXL1 mutated) displayed a significantly worse prognosis. A third risk category could be identified, including those patients with both mutations or wild type for both genes [With the increasing knowledge of the molecular basis of PMF, it is becoming evident that both driver and non-driver mutations have relevance in terms of prognostic significance. PMF carrying utations , especiautations , have thutations ,48. Howeth genes .NPM1 and FLT3 mutational status do influence prognosis [This is somewhat similar to the AML scenario, where both rognosis .ASXL1, EZH2, SRSF2, or IDH1/2, called high molecular risk (HMR) mutations, have been shown to represent unfavorable prognostic factors, as these genetic lesions identify PMF patients who are at risk for premature death or leukemic transformation independently of the conventional prognostic scoring systems [Mutations in  systems . Moreove systems . The fre systems . The pre systems .Together with the above-mentioned HMR mutations, genetic events occurring in the RAS/MAPK pathway genes have been recently associated with high-risk clinical features and worse prognosis, compared with wild type patients .9/L), platelet count <100 × 109/L, circulating blasts ≥2%, constitutional symptoms, bone marrow fibrosis grade, IPSS/DIPPS-plus category, driver mutations, absence of CALR type 1-like mutation, individual HMR mutations, HMR category, and the presence of ≥2 HMR mutations. Each parameter has a weight of 1 point, except for leukocytosis, thrombocytopenia, and the presence of ≥2 HMR mutations, which are each weighted 2 points. Patients are stratified into three categories: low-risk with a median survival of 27.7 years, intermediate-risk with a median survival of 7.1 years, and high-risk with a median survival of 2.3 years. In the MIPPS-70 plus that includes cytogenetic information, four risk categories are delineated with median survival ranging from 1.7 to 20 years [Then in 2018, a clinical/molecular prognostic model that includes both driver mutations and detrimental co-operating mutations was created. The Mutation-Enhanced International Prognostic Score System (MIPSS-70) includes the following risk factors: hemoglobin <10 g/dL, abnormal leukocyte count  and the GIPSS .U2AF1Q157 as an additional HMR mutation, and new sex- and severity-adjusted hemoglobin thresholds . MIPPS70+ version 2.0 includes five genetic and four clinical variables: very high risk (VHR) karyotype (4 points), unfavorable karyotype (3 points), presence of one (2 points) or ≥2 HMR mutations (3 points), absence of type 1/like CALR mutation (2 points), constitutional symptoms (2 points), severe anemia (2 points), moderate anemia, (1 point) and circulating blasts ≥2% (1 point). MIPSS70+ version 2.0 features five risk categories: very high risk (≥9 points); high risk (5–8 points); intermediate risk (3–4 points); low risk (1–2 points); and very low risk (zero points), with corresponding median survivals of 1.8 years, 4.1 years, 7.7 years, 16.4 years and “not reached” [The MIPSS70+ version 2.0 incorporates the recently revised three-tiered cytogenetic risk levels , U2AF1Q1reached” .CALR mutation (1 point) and presence of ASXL1 (1 point) SRSF2 (1 point) and U2AF1Q157 (1 point) mutations. The GIPSS features four risk categories: high risk (≥3 points), intermediate-2 risk (2 points), intermediate-1 (1 point), and low risk (zero points), with corresponding median survivals of 2 years, 4.2 years, 8.0 years, and 26.4 years [GIPSS, which is based exclusively on mutations and karyotype, represented the first attempt to model PMF survival on genetic features that fully replace traditional clinical variables, ads VHR karyotype (2 points), unfavorable karyotype (1 point), absence of type 1/like .4 years . The curNRAS, KRAS, or CBL [The clinical efficacy of ruxolitinib in myelofibrosis seems not to be affected by the underlying driver mutations ,61, but , or CBL .Furthermore, drug failure has been associated with signs of clonal evolution in a not negligible percentage of cases, ranging from 17% in a cohort of real-life treated patients to 33% in a clinical trial setting, with a consistently negative impact on patients’ survival ,64.ASXL1/SRSF2 or ASXL1 mutations, respectively [In addition, the response to other JAK-inhibitors, such as momelotinib or imetelestat, may be influenced by the presence of ectively ,66. The ectively ,68.JAK2 positive patients [CALR positive patients and a negative impact on patients’ prognosis of triple-negative status [CALR mutation was an independent factor for lower non-relapse mortality, improved progression-free survival (PFS), and overall survival. ASXL1 and IDH2 mutations were independent risk factors for lower PFS, whereas no impact was observed for triple-negative patients. Authors concluded that molecular genetics, especially CALR, IDH2, and ASXL1 mutations, may thus be useful to predict outcomes independently from known clinical risk factors after HSCT. Very recently, driver and subclonal mutations were incorporated in the myelofibrosis transplant score (MTSS), a scoring system that includes clinical-molecular and transplant-specific factors, with the aim of predicting posttransplant outcome. Multivariable analysis on survival identified age ≥57 years, Karnofsky performance status <90%, platelet count <150 × 109/L, and leukocyte count > 25 × 109/L prior to transplantation, HLA-mismatched unrelated donor, ASXL1 mutation and non-CALR/MPL driver mutation genotype being independent predictors of outcome [Different mutations may have an impact on the outcome after hematopoietic bone marrow transplantation (HSCT). Early smaller reports suggested a benefit for patients , wherease status . Howevere status . CALR mu outcome .JAK2/CALR/MPL mutation was recently demonstrated in a cohort of 136 patients who received alloHSCT. Patients with detectable mutations at day +100 or at day +180 had a significantly higher risk of clinical relapse at 5 years than molecular-negative patients  [JAK2 and MPL, a sensitivity of 10−5 has been described by PCR technique [The presence of myelofibrosis-specific molecular markers offers the possibility to monitor the depth of remission after HSCT and to start a preemptive therapy at the first, minimal reappearance of disease ,74,75. T< 0.001) . Minimal< 0.001) . The senechnique ,74.Notably, a JAK2 V617F qPCR assay was generally recommended because of its sensitivity and consistent performance across different qPCR platforms ,79,80.CALR mutation as a marker of MRD is more problematic due to the variety of indels reported in the CALR gene and the scarce quantification accuracy of fragment length analysis and Sanger sequencing. Both a sensitive qPCR approach and a digital PCR assay that allows the accurate determination of CALR allelic burden for the most frequent alterations (type 1 and type 2) have been developed [JAK2 and CALR mutant burdens [The use of eveloped ,82. In a burdens .Subclonal mutations, if present, could be extremely useful to monitor MRD, both in triple-negative patients or as an additional tool for those who have a traditional driver event. In this regard, next-generation sequencing (NGS) approaches for MRD monitoring might be hopefully developed in the future.ASXL1, EZH2, IDH1/2, and SRSF2 is recommended. The same extended panel is also appropriate for prognostic prediction, in particular for patients classified as intermediate risk, for which treatment allocation, counseling and/or frequency of monitoring may be refined according to the individual genetic background. High-sensitivity quantitative monitoring of JAK2 V617F and CALR mutations, or quantitative evaluation of another clonal marker in triple-negative patients, are recommended in all patients after HSCT for MRD assessment.The rapidly expanding field of molecular genetics for myelofibrosis has opened new horizons in the diagnosis, prognosis, treatment decision-making, and monitoring of this disorder. Recommendations for molecular testing in MPN has been recently provided  and inclWhile comprehensive gene sequencing of hematological cancer patients is becoming an increasingly accessible event for routine clinical use, many uncertainties still remain. As an example, how many times should PMF patients be tested? In fact, MPNs are dynamic diseases, so that high-risk genomic features may be gained over time, requiring treatment intervention (or HSCT consideration).Genome profiling will likely become the basis for a personally-tailored prognosis prediction, but we acknowledge that clinical translation of recent scientific advances is still a work in progress.


Background: There is pressing urgency to identify therapeutic targets and drugs that allow treating COVID-19 patients effectively.Methods: We performed in silico analyses of immune system protein interactome network, single-cell RNA sequencing of human tissues, and artificial neural networks to reveal potential therapeutic targets for drug repurposing against COVID-19.Results: We screened 1,584 high-confidence immune system proteins in ACE2 and TMPRSS2 co-expressing cells, finding 25 potential therapeutic targets significantly overexpressed in nasal goblet secretory cells, lung type II pneumocytes, and ileal absorptive enterocytes of patients with several immunopathologies. Then, we performed fully connected deep neural networks to find the best multitask classification model to predict the activity of 10,672 drugs, obtaining several approved drugs, compounds under investigation, and experimental compounds with the highest area under the receiver operating characteristics.Conclusion: After being effectively analyzed in clinical trials, these drugs can be considered for treatment of severe COVID-19 patients. Scripts can be downloaded at https://github.com/muntisa/immuno-drug-repurposing-COVID-19. Coronaviridae family and Betacoronavirus genus, SARS-CoV-2 is the seventh CoV known to infect humans, along with 229E, NL63, OC43, HKU1, SARS-CoV, and Middle East respiratory syndrome (MERS) (The first zoonotic transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was located in China in December 2019 , and it e (MERS) . Coronave (MERS) .pro (nsp5) (The first genome of SARS-CoV-2 named Wuhan-Hu-1 (NCBI reference sequence NC_045512) was isolated and sequenced in China in January 2020 . SARS-Coo (nsp5) , the RNAo (nsp5) , the helo (nsp5) . Lastly,o (nsp5)  (Wu A eto (nsp5) .COVID-19 is caused when SARS-CoV-2 exploits the host cell machinery for its own replication and spread . SARS-CoACE2 is a type I membrane protein widely expressed in nasal goblet secretory cells, lung type II pneumocytes, ileal absorptive enterocytes, kidney proximal tubule cells, gallbladder basal cells, among other human cells , and parin silico analyses of immune system protein-protein interactome (PPi) network, single-cell RNA sequencing (scRNA-seq) of human tissues, and artificial neural networks to reveal potential therapeutic targets for drug repurposing against COVID-19.Additionally, SARS-CoV-2 interacts with the immune system triggering dysfunctional immune responses to COVID-19 progression . Given tet al (http://www.imgt.org) (https://www.innatedb.com/) (https://david.ncifcrf.gov/)  , the Inndb.com/) , and therf.gov/)  using thThe immune system PPi network with a highest confidence cutoff of 0.9 and zero node addition was created between the human proteins physically associated with SARS-CoV-2 and their first neighboring proteins of the immune system. This network was generated using the human proteome of the Cytoscape StringApp , which iet al. published a large-scale multi-omic analysis identifying 146 significantly expressed proteins in patients with severe COVID-19  to obtain significant annotations  related to GO: biological processes, the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways, and Reactome signaling pathways , 15 lung epithelial cells , and 9 ileal epithelial cells  to identify significantly expressed genes in goblet secretory cells, type II pneumocytes, and absorptive enterocytes.https://singlecell.broadinstitute.org/single_cell/covid19), and the Alexandria Project . The three single-cell databases analyzed were: 1) nasal passage cells , 2) lung epithelial cells , and 3) ileal epithelial cells . Lastly, it is important to clarify that the scRNA-seq analyses were done in cells non exposed to the novel coronavirus.The transcriptomics data was taken from the ‘COVID-19 Studies’ section of the Single Cell Portal  cell types’ as load cluster, ‘cell type ontology label’ as selected annotation, and ‘all cells’ as subsampling threshold. Additionally, we adjust the mRNA expression taking into account the Z-scores, that is, overexpressed mRNAs with Z-scores > 2 and underexpressed mRNAs with Z-scores < −2. Regarding visualization of transcriptomics data, we designed heatmaps to compare the expression between cell types, dot plots to visualize the percentage of cells expressing, box plots to compare the expression scores of multiple genes for each cell type taking into account the mean log normalized expression, and 2D t-SNE to visualize the expression score of significantly expressed multiple genes per subpopulation cell.ACE2 and TMPRSS2 co-expressing human cells, we evaluated the druggability of these molecules, and subsequently perform the drug repurposing analysis.After identifying the significantly expressed biological molecules present in the scRNA-seq analyses of https://www.ebi.ac.uk/chembl)  , and frohttps://github.com/deepchem/deepchem). DrugBank (https://www.drugbank.ca/) contains comprehensive information about drugs, their mechanism of action, and their targets  have been used to find the best multitask classification model using 1,024 molecular circular fingerprints (CFPs) as input descriptors for 15,377 ChEMBL compounds and activity (1/0) for the 25 therapeutic targets as outputs/tasks  is presenting all the methodology with python code and results. The repository folder “datasets” contains the dataset with the ChEMBL ID, SMILES formula, and the class of protein target (multiclass_origDS_noDB.csv). The dataset that will be used by the classifier contains the SMILES formulas of 15,377 ChEMBL compounds that interacts with 25 different protein targets with the following UniProt IDs: O00571, P00533, P01024, P01130, P04233, P07339, P08962, P09668, P11021, P15291, P16070, P17301, P21741, P25774, P25963, P26006, P27361, P35222, P40763, P50591, P55085, Q15904, Q16665, Q99519, and Q99814. This means that the dataset was composed by 15,377 examples with 25 classes. The multi-task classification model will be able to predict if a compound with a SMILE formula could have one or more protein targets simultaneously, using separated tasks/outputs for each of the 25 proteins. It is not a simple classification with only an output (class) that can predict only a protein value from the 25 possible targets). The prediction molecules that will be evaluated with the best classifier can be found in DB_toPredict.csv . The input SMILES formulas will be used to calculate molecular descriptors for all molecules (as model inputs).In the first step, CFPs molecular descriptor have been calculated for both ChEMBL dataset and DrugBank prediction set  as a vecIn order to build a classifier (model), the training of the model should be done with a training subset and the final model should be tested for performance with a test subset that was not used during the training process. In addition, if different classifiers with different parameters are used during the training, there is a need of an extra validation subset to decide the best classifier (model) using a specific metrics (in our scripts: AUROC). Thus, the dataset was splitted into 80%-10%-10% training-validation-test subsets using RandomStratifiedSplitter . The training and validation subsets were used to find the best hyperparameters for the FCNN with 1,000 neurons (MultitaskClassifier from DeepChem package). The constant parameters are activation functions as relu, momentum of 0.9, weights initialization using Glorot uniform method , learning rate of 1e-3, decay of 1e-6, 1o epochs, a single hidden layer . During the grid search for the best model, 64 classifiers have been optimized with different combination of the following parameters: batch size = , dropouts = , batch normalization = , and hidden layer sizes (number of neurons) = . Thus, the training subset was used for training of each model/classifier and the validation subset was used to decide the best model.The test set was used to verify the performance of the best model for each task/protein target see . AUROC fhttps://www.whocc.no/atc_ddd_index/), drug category, mechanism of action, approval status by the US Food & Drug Administration (FDA) or the European Medicines Agency (EMA), the pharmacological indications, and the current involvement in COVID-19 clinical trials .The best model has 1,000 neurons in a hidden layer (dropout of 0.5) with all parameters as 'activation': 'relu', 'momentum': 0.9, 'batch_size': 124, 'init': 'glorot_uniform', 'data_shape': (1024), 'learning_rate': 0.001, 'decay': 1e-06, 'nb_epoch': 1, 'nesterov': False, 'dropouts': (0.5), 'nb_layers': 1, 'batchnorm': False, 'layer_sizes': (1000), 'weight_init_stddevs': (0.1), 'bias_init_consts': (1.0), 'penalty': 0.0. This classifier was used to predict the activity of 10,672 drugs from DataBank for the 25 immune system targets: DDX3X, EGFR, C3, LDLR, CD74, CTSD, CD63, CTSH, HSPA5, B4GALT1, CD44, ITGA2, MDK, CTSS, NFKBIA, ITGA3, MAPK3, CTNNB1, STAT3, TNFSF10, F2RL1, ATP6AP1, HIF1A, NEU1, and EPAS1  employ a suite of virulent proteins, which interact with key targets in host interactomes to extensively rewire the flow of information and cause diseases, such as COVID-19 . The humHere, we generated the immune system PPi network encompassing 1,584 nodes and 332,968 edges . Of themThe functional enrichment analysis was performed to validate the correlation between the immune system PPi subnetwork and biological annotations related to severe COVID-19. Therefore, after generating the subnetwork encompassing 319 immune system proteins, we performed a functional enrichment analysis using g:Profiler to obtain significant annotations (Benjamini-Hochberg FDR < 0.001) related to GO: biological processes, KEGG signaling pathways, and Reactome signaling pathways .−60), granulocyte activation (3.9 × 10−60), myeloid leukocyte mediated immunity (3.7 × 10−56), inflammatory response (8.5 × 10−9), blood coagulation (2.0 × 10−7), T-cell activation (3.6 × 10−7), response to interferon-gamma (1.9 × 10−7), platelet degranulation (8.6 × 10−7), and acute inflammatory response (6.6 × 10−5). The most significant KEGG signaling pathways related to severe COVID-19 were chemokine signaling pathway (4.6 × 10−8), coagulation cascade (1.2 × 10−7), and antigen presentation (7.2 × 10−5). Lastly, the most significant Reactome signaling pathways related to severe COVID-19 were neutrophil degranulation (2.3 × 10−60), innate immune system (1.8 × 10−43), hemostasis (1.0 × 10−12), signaling by VEGF (5.9 × 10−7), insulin-like growth factor (6.8 × 10−7), and platelet degranulation (4.9 × 10−6) ( × 10−6) .Omics medicine has evolved the way for identifying therapeutically actionable targets for complex diseases. However, one of the major limitations is the gene expression variability due to the cellular heterogeneity of organs . Single-et al. discovered ACE2 and TMPRSS2 co-expressing cells in nasal goblet secretory cells, lung type II pneumocytes, and ileal absorptive enterocytes through scRNA-seq data analyses  developed by allergic inflammation, and nasal scraping samples  conform the nasal passage cells. Epithelial cells of lung tissue  were the second single-cell database analyzed. Samples from adult human duodenum and ileum  were the third single-cell database analyzed. The current work proposes an innovative virtual high-throughput screening to predict the activity of 10,672 compounds for 25 immune system targets fully detailed in the The classification model was based on the molecular Circular Fingerprints descriptors  of 15,377 ChEMBL compounds and its 25 therapeutic targets as outputs/tasks. The best model was obtained after a hyperparameter grid search (64 topologies) as a fully connected deep neuronal networks with 1,000 neurons in one hidden layer, with the mean AUROC of 0.989 ± 0.019 (AUROC between 0.935 and 1.000 for 25 classes). Our free GitHub repository contains the Jupyter notebook as python script using DeepChem methodology, datasets, calculated descriptors, best model, metrics of the model, and predictions. After applying the best classification model, we evaluated drugs taking into account the first ATC levels associated to COVID-19 symptoms, drug category, mechanism of action, pharmacological indications, and the best ranked AUROC values (threshold > 0.8). Consequently, on one hand, we obtained 44 approved drugs, 16 compounds under investigation, and 35 experimental compounds with the highest affinities for 15 immune system proteins . On the Interestingly, 13 (27%) of the 48 best-predicted approved drugs are currently involved in approximately 54 COVID-19 clinical trials as detailed in Since the finding of patient zero in China, a wide spectrum of clinical manifestations has been discovered, as we have understood the COVID-19 disease. The most common initial symptoms are cough, fever, anorexia, and dyspnea . The mosThe effective immune response of the host, including the innate and adaptive ones, against SARS-CoV-2 seems to be essential to control and solve the infection. However, the clinical seriousness of COVID-19 could be associated to the excessive production of pro-inflammatory cytokines, known as ‘cytokine storm’ , or to tInnate immune response executes the first line of antiviral defense and is essential to obtain immunity against viruses . PatternMucosal immune responses against viruses are orchestrated by myeloid cells such as macrophages, conventional DCs, plasmacytoid DCs, and monocyte-derived DCs . Accumulin vitro study has identified that the CXCL9-11 chemokines are overexpressed in lung cells infected with SARS-CoV-2, suggesting that the CXCR3 signaling pathway drives NK cells from peripheral blood to lungs in COVID-19 patients (Innate lymphoid cells (ILCs) are lymphoid-like immune cells that lack the expression of rearranged antigen receptors. The non-cytotoxic group I, II, and III ILCs and the cytotoxic natural killer (NK) cells form the ILC family . Severalpatients . In addiT cells are involved in fundamental processes in viral infections. CD8 T cells eliminate infected cells and CD4 T cells help B cells for antibody production. Nevertheless, immunopathology is generated when T cells are dysregulated. Several reports have shown that moderate to severe COVID-19 patients with lymphopenia drastically reduce CD8 T cell and CD4 T cells in peripheral blood . T cellset al. and Wu et al., IgM, IgA, and neutralizing IgG antibodies can be detected in 12, 14 and 10–14 days, respectively, after symptom onset on average, suggesting that SARS-CoV-2 causes a robust B cell response in the majority of COVID-19 patients  in nasal goblet secretory cells (n = 5) , lung tyet al , as detailed in our previous study  of the 25 potential therapeutic targets. The best-predicted approved drugs were enrolled in ten different categories: anti-neoplastic and immunomodulating agents, anti-hemorrhagic agents, anti-inflammatory agents, anti-parathyroid agents, anti-viral agents, anti-oxidant agents, cardiovascular agents, central nervous system agents, growth hormone-releasing hormone, and antibiotics see .et al., the renin-angiotensin system is an important pathway linked to hypertension and hypotension in COVID-19 patients because it maintains a balance of blood pressure  protein levels predict acute lung injury and ARDS with poor clinical outcomes, and fostamatinib has been shown to reduce MUC1 abundance in a relevant pre-clinical model and has demonstrated safety profile in patients  of the 48 best-predicted approved drugs found in our study . The carpressure . The ant targets . The anteatments . Finallypatients .Despite enormous scientific effort in drug repurposing studies to inhibit SARS-CoV-2 proteins or control severe COVID-19 symptoms, significant limitations exist. The main concern associated with drug repurposing studies involves the implementation of well-designed validation assays through clinical trials. Other main concerns are related to obtaining the correct therapeutic doses, safety results to avoid detrimental effects of repurposed drugs after treatments, and delivery capabilities worldwide . All of The current COVID-19 pandemic offers a unique opportunity to strengthen mechanisms that promote the use of drug repurposing processes–considering the drug safety profile and the possibility of originate different adverse reactions in patients with distinct concomitant diseases–; inclusively, in the ongoing or future clinical trials, having the potential to reduce the time and costs for finding potential solutions to the current pandemic. Additionally, contributing to future analysis for high threat pathogens and rare diseases. This idea is welcomed by some other authors who conveyed on the potential of drug repurposing for common national and global health benefits . BetweenThe COVID-19 pandemic has evidenced that there is a strong urge to strengthen health systems with a major emphasis on health prevention and the major need, especially of low and middle income countries, to publicly invest on research and development. Consequently, the benefits of innovation and the results of research should be always available and affordable to anyone in need, to comply with the goal of public health . This isFrom a global health perspective, initiatives directed to the improvement of rapid data sharing are critical during health emergency. This rapid sharing includes undoubtedly a transboundary collaboration founded on the principles of reliability and accuracy of the data . Meaning