Arabidopsis thaliana and Populus trichocarpa using high-throughput gene expression data. We analyzed four pathways: (1) lignin biosynthesis pathway in A. thaliana and P. trichocarpa; (2) flavanones, flavonol and anthocyannin biosynthesis in A. thaliana; (3) light reaction pathway and Calvin cycle in A. thaliana. (4) light reaction pathway alone in A. thaliana. The efficiencies of two methods were evaluated by examining the positive known regulators captured, the receiver operating characteristic (ROC) curves and the area under ROC curves (AUROC). Our results showed that TGMI is in general more efficient than SPLS in identifying true pathway regulators and ranks them to the top of candidate regulatory gene lists, but the two methods are to some degree complementary because they could identify some different pathway regulators. This study identified many regulators that potentially regulate the above pathways in plants and are valuable for genetic engineering of these pathways.Identification of biological process- and pathway-specific regulators is essential for advancing our understanding of regulation and formation of various phenotypic and complex traits. In this study, we applied two methods, triple-gene mutual interaction (TGMI) and Sparse Partial Least Squares (SPLS), to identify the regulators of multiple metabolic pathways in  Arabidopsis thaliana has 549 annotated metabolic pathways and a few thousand biological processes, but the regulators for almost all of these pathways except a few of them have not yet been identified2. With the advent of the high-throughput sequencing technology and the mounting gene expression data being deposited into public databases, there is a great need for well-evaluated computational tools that can be utilized to predict pathway regulators using high-throughput gene expression datasets.A multitude of biological processes and metabolic pathways are present in a plant species, and our understanding of their underlying regulatory mechanisms remains limited. For example, 4, where the connectivity of each transcription factor (TFs) and pathway genes, and network complexity and structures can convey the information based on which potential candidate regulators can be identified for experimental validation5. However, there are some inherent challenges for gene association or network construction due to the linear multicollinearity and high dimensionality in high-throughput gene expression data sets. A multitude of gene variables with respect to a small number of samples can easily result in linear multicollinearity. Both high dimensionality and multicollinearity impede us from accurately associating regulatory genes-target genes or constructing gene regulatory network via mathematical modeling.Identification of biological process and pathway regulators is very important to understand the regulation of various physiological and biochemical characteristics, and phenotypical and complex traits as well. This can be accomplished through constructing gene regulatory networks operating above biological processes and pathways6. The main principle of SPLS is to impose sparsity within the context of partial least squares and thereby accomplish dimension reduction and variable selection simultaneously. SPLS regression performs well even when the sample size is much smaller than the number of variables. TGMI is specially developed for identifying the pathway regulators by evaluating all combined triple gene blocks using a novel mutual interaction measure (MIM) calculated with mutual information and conditional mutual information7. MIM represents the regulatory strength exerted by a transcription factor (TF) on two combined pathway genes in a triple gene block, and it can facilitate the recognition process of true causal relationships between TFs and pathway genes. Comparison TGMI with SPLS allows us to learn their performance, efficacy, commonality and specification, and utilize them for different purposes and applications.To circumvent such obstacles, we need to develop novel algorithms and assess their performance and efficacy. SPLS regression methodology was designed to deal with the high dimension and multicollinearity property of gene expression dataArabidopsis thaliana, a unified flavanone, flavonol and anthocyannin biosynthesis pathway in A. thaliana, lignin biosynthesis pathway in Populus trichocarpa, a unified pathway of light reaction and Calvin cycle in A. thaliana, and finally the light reaction pathway in A. thaliana. These unified pathways contain two to three closely linked pathways. We selected these pathways because their regulators have been mostly or partially identified. We set out to test the viability of combining multiple pathways in identifying their regulators. At the same time, it also provides clues for researchers to explore new regulatory mechanisms of these complex pathways. The results show that TGMI and SPLS are instrumental for identifying true biological pathway regulators. However, TGMI algorithm has an overall higher efficacy than SPLS algorithm and may identify more positive known regulators than SPLS.In this study, we compared the efficiency of TGMI and SPLS in identifying regulatory factors of several metabolic pathways in two species, which include lignin biosynthesis pathway in https://plantcyc.org/). A complete gene list of flavanone, flavonol and anthocyannin biosynthesis pathway is provided in Table A. thaliana’s. The poplar lignin pathway genes were extracted from Phytozome’s annotation file based on their counterparts’ annotation in A. thaliana   protein complexes10. MYC1 is a known component of MYB-bHLH-WD Repeat (MBW) transcriptional complex that controls flavonoid11. By DNA affinity purification sequencing (DAP-seq), ATAF1 is a predicted regulator that controls flavonoid synthesis pathway genes, including C4H and CHS12. SVP affects the accumulation of flavonol and anthocyanin in drought-stressed Arabidopsis plants13. HY5 induces biosynthesis of flavonoids by regulating the expression of DFR at low temperature14. STH2 has been reported to enhance anthocyanin accumulation by interacting with HY515. MYB32 regulates the accumulation of flavonoids by interfering with the transcriptional activity of the MBW complex16. NAC019 negatively regulates the biosynthesis of anthocyanins17. MYB65 participates in regulating the accumulation of isoflavone18. Of the TFs identified by SPLS, MYB112 promotes the formation of anthocyanins19. PFG1 (PRODUCTION OF FLAVONOL GLYCOSIDES1)/MYB12 and PAP1 (PRODUCTION OF ANTHOCYANIN PIGMENT1)/MYB75 promote the accumulation of flavonoids under oxidative and drought stress20.The efficacy of TGMI algorithm and SPLS algorithm in identifying pathway regulators was scrutinized using Data Set 1 from ay Table  and all ay Table , and genA. thaliana microarray compendium data set (Data Set I) produced from stem tissues where wood formation was intensified by short-day treatment. The expression data of the genes involved in lignin pathway  group, and serve as transcription switches to activate secondary cell wall biosynthesis22. Five additional VND genes, VND1-5, have recently been proven to have similar functions to SWN genes24. Among the above genes, SND1 is a master transcriptional activator of secondary wall synthesis. The transcription factors regulated by it include SND2, SND3, MYB20, MYB42, MYB43, MYB46, MYB52, MYB54, MYB58, MYB61, MYB63, MYB69, MYB83, MYB85, MYB86, MYB103, KNAT7, C3H14 and C3H1526. TGMI algorithm identified 15 SWN genes and their downstream regulatory factors . SPLS algorithm also identified 15 TFs . In addition to these TFs, TGMI also identified 8 other known lignin pathway regulators  while SPLS identified 5 other known regulators . GATA12 and LBD15 are upstream transcription factors that regulate the transcription of VND728. WRKY12 binds to the promoter of NST2, thereby negatively regulating the biosynthesis of lignin29. AtSIZ1, a small ubiquitin-related modifier (SUMO) E3 ligase, regulates the formation of secondary cell walls in A. thaliana by mediating the SUMOylation of transcription factor LBD3030. XYLEM NAC DOMAIN 1 (XND1) inhibits xylem differentiation and secondary wall synthesis31. BLH6 and KNAT7 together form the KNAT7-BLH6 complex, which inhibits the formation of secondary cell walls, and REV is the direct target of this complex32. MYB31 has been shown to be involved in regulation of lignin synthesis genes multiple species33. bZIP6 and bZIP17 also regulate secondary cell wall synthesis35.In https://phytozome.jgi.doe.gov/)37 , Potri.001G045000, Potri.001G045100, Potri.001G045500, Potri.001G046100, Potri.001G046400, were highly expressed only in drought-treated xylem, and may be specifically involved in poplar drought stress response in tree xylem.According to the verified lignin biosynthesis genes and the annotation information of the genes collected from Phytozome  , AtLBD18 , AtBLH4 , one homologous gene of AtKNAT1(Potri.002G113300). The overexpression of NAC075, an upstream regulator of VND7, induces secondary cell wall deposition24. LBD18 participates in the positive feedback loop of VND7 and regulates tracheary elements differentiation-related genes38. KNAT1 regulates vascular cambium development and xylem differentiation39. The gene regulatory networks of the lignin pathway constructed by two methods are shown in Fig. We used genes from lignin biosynthesis pathway to study which regulatory genes can potentially control wood formation in LS Table , and gen 1) Fig. A,B, indiA. thaliana leaves under Mock, JA or SA treatments. Expression data for all TFs and 130 pathway genes were extracted from the above compendium data set and used for analyses. The resulting regulator lists identified and ranked by TGMI and SPLS , LATE ELONGATED HYPOCOTYL (LHY), and TIMING OF CAB EXPRESSION 1 (TOC1)46. They form the central oscillator of the circadian clock and a double negative feedback loop. In the morning, CCA1 and LHY bind to the promoter region of TOC1, reducing its mRNA abundance; at night, TOC1 inhibits the transcription of CCA1 and LHY48. TOC1 is a member of the PRR (PSEUDO-RESPONSE REGULATOR) family that includes PRR9, PRR7, PRR5, PRR3, and PRR1/TOC1. In addition to TOC1, PRR9, PRR7, PRR5, PRR3, and CCA1 HIGH EXPEDITION (CHE)/TCP11 also inhibit CCA1 at different times of the day50.The circadian clock regulates a large number of biological processes in plants, including light harvesting, electron transport in photosynthesis and ATP concentration in chloroplasts52. There are 6 sigma factors, SIG1-6 in A. thaliana. SIG1 and SIG5 function in adjusting the photosynthetic apparatus during photosynthesis, and SIG2 and SIG6 are necessary for chloroplast development. It has been proved that that SIG1, SIG2 and SIG3 regulate psaA, PIF4, and psbN, respectively54, and SIG5 regulates psaA, psaB, psbB, psbH, petB, petD, psbD, and psbC55. Phytochrome interacting factors (PIFs) are a class of bHLH transcription factors that regulate the response of plants to light. PIF1, PIF3, PIF4 and PIF5 have been shown to affect the expression of photosynthesis-related genes, including genes encoding LHCA, LHCB, and PsaD proteins. PIF7 is also involved in the regulation of circadian rhythms57.The circadian clock controls the transcriptional expression of chloroplast genes by regulating a class of nuclear-encoded sigma factors, thereby affecting the production of photosynthetic apparatus and photosynthetic efficiencyCCA1, PRR3, PRR5, CHE/TCP11, SIG1, PIF4, PIF5 and PIF7. SPLS algorithm identified 3 regulators, PIF4, PIF5 and PIF7. In addition to these regulators, TGMI also identified 8 other known photosynthesis pathway positive regulators, namely, STO/BBX24, STH/BBX25, COL7, COL5, NAC016, BNQ2, REV2 and GLK2) while SPLS identified 5 other known positive TFs, namely, BEH1, BEH3, COL5, EIN3 and HSFA1A. BBX24 and BBX25 physically interact with photosynthesis regulator HY5 to inhibit its transcriptional activation activity59. CIR1/RVE2 have been shown to affect the transcription of Lhcb family genes by regulating CCA1, LHY and TOC160. The two genes of the GOLDEN TWO-LIKE (GLK) family, GLK1 and GLK2, directly regulate the expression of a series of photosynthetic genes, including the genes encoding the PSI-LHCI complex and PSII-LHCII complex62. EIN3 directly interacts with PIF3, inhibiting the expression of most light-harvesting complex  genes63. Photoreceptors, phyA and phyB are required for stabilization of the COL7 protein, and COL7 is a critical factor linking light perception to changes in auxin level in A. thaliana64. BNQ2 and COL5 are regulated by PIF4 and their proteins participate in the integration of optical signals and GA signals65. NAC016 can promote the degradation of chlorophyll by directly increasing the transcription of STAYGREEN1 (SGR1), and may affect the detoxification of chlorophyll by SGR-CCE-LHCII complex66. HSFA1, a master regulator of transcriptional regulation under heat stress, regulates photosynthesis by inducing the expression of downstream transcription factors67. BEH1 and BEH3 are homologous genes of BZR1, genetic analysis indicates that the BZR1-PIF4 interaction controls a core transcription network by integrating brassinosteroids and light response68. It is worth mentioning that there are 4 B-box family genes  in the top 50 TFs in TGMI recognition results. The genes of this family are involved in many plant processes regulated by light, so the role of BBX8 and BBX18 in photosynthesis is worth noting. It is noticeable that the positive known regulators identified by TGMI congregated at the top of the list  curves of all pathways we analyzed are shown in Fig. Our studies on TGMI and SPLS support that TGMI has higher efficacy in recognition of the potential pathway regulators than SPLS. As summarized in Table A. thaliana. For A. thaliana, we identified a lignin biosynthesis regulatory network with several SWN genes  known as the main switches. In Populus. we only identified 4 SWN orthologs, which include Potri.007G135300 (SND2), Potri.017G016700 (SND2); Potri.007G014400 (VND2); Potri.012G126500 (VND5). We also identified two homologous genes of NAC075 , two homologous genes of LBD18 . NAC075 and LBD18 are the upstream regulators of VND7, which is known to regulate a handful of downstream lignocellulosic biosynthesis pathway regulators. These findings indicate that pathway regulators in perennial woody plants and annual herbs may be different. It is worth to mention that NAC075 and LBD18 were identified by TGMI rather than SPLS, suggesting TGMI is probably more sensitive to recognize pathway regulators.To examine what kinds of pathway regulators the two method can identify in different species, we compared the inferred lignin biosynthesis pathway regulators between poplar and A. thaliana resulted in 14 and 7 positive regulators, respectively. The application of TGMI and SPLS algorithms for identifying the combined pathway regulators in Arabidopsis resulted in 16 and 8 positive regulators, respectively. Although we do not know if a combination will certainly lead to identification of more true positive regulators in all cases, it is worth undertaking. As evidenced, we identified CCA1 and SIG1 master regulators when the two photosynthesis and light reaction pathways were combined.We investigated if a combination of multiple pathways for analysis may be beneficial more than analyzing each pathway separately. We combined light reaction pathway and photosynthesis pathway as unified pathway for analysis. We found that combining two linked and coordinated pathways can improve the efficiency in identifying their regulators to a certain extent. The application of TGMI and SPLS algorithms for identifying light reaction pathway regulators in A. thaliana and P. trichocarpa demonstrated that TGMI in general performs more efficiently than SPLS. TGMI tends to rank more true positive TFs at the top of candidate regulatory gene lists. This is an advantage given the fact that biological experimental validation can only be applied to the top candidate genes. In addition, TGMI appears to has more stable recognition efficiency in identifying true positive pathway regulators of multiple pathways in both species. In the two candidate regulatory gene lists of the same pathway yielded by TGMI and SPLS, there were always some different regulatory genes, indicating that the two methods are also complementary to each other to some degree. Moreover, both methods can be used to identify regulators for a unified pathway of several closely linked pathways, which may possibly increase the potential for identifying regulators that control both one or multiple pathways. Finally, we showed that TGMI is capable of identifying more tissue-specific pathway regulators than SPLS. In conclusion, both methods are instrumental for identifying pathway regulators from high-throughput data though TGMI is more efficient than SPLS for identifying positive known and/or tissue-specific regulators.The application of two methods to five metabolic pathways in Arabidopsis stem compendium dataset contains 128 Affymetrix microarrays pooled from six experiments  (http://www.ncbi.nlm.nih.gov/geo). These datasets were originally obtained from hypocotyledonous stems under short-day conditions known to induce secondary wood formation. The original CEL files were downloaded from GEO and preprocessed using the affy package in Bioconductor (https://www.bioconductor.org.) and then normalized with the robust multi-array analysis (RMA) algorithm in affy package. This compendium data set was also used in our previous studies7. The annotation information of all genes was acquired from the Arabidopsis Information Resource website (TAIR) (https://www.arabidopsis.org/), and the list of all transcription factors was acquired from the PlantTFDB website (http://planttfdb.cbi.pku.edu.cn/).The Arabidopsis leaf compendium dataset contains 686 RNA-seq data sets downloaded from NCBI BioProject database (https://www.ncbi.nlm.nih.gov/bioproject), with an accession number of PRJNA224133. These datasets were originally obtained from the 6th leaves from the apical buds in time series with three treatments: mock, salicylic acid (SA) or jasmonic acid (JA). This project contains 172 experiments; each has 4 samples except for the one that only has two samples. In total, there are 686 samples. Raw reads were trimmed to remove adaptors and low‐quality base pairs via Trimmomatic (v3.3). Clean reads were aligned to the Arabidopsis thaliana TAIR10 genome with STAR, followed by the generation of normalized FPKM (fragments per kb of transcript per million reads) using Cufflinks software (v2.1.1)72. The annotation of all genes and transcription factors was obtained from TAIR and PlantTFDB as described in Data Set 1.The Populus trichocarpa compendium data set comprising of 134 developing xylem samples was downloaded from NCBI database: BioProject (https://www.ncbi.nlm.nih.gov/bioproject) with an accession number of PRJNA300564. Raw reads were aligned to the P. trichocarpa v4.0 genome with TopHat (v2.1.1), followed by generation of raw counts using Bedtools73. Finally, the raw counts were normalized with TMM  using edgeR package74. The annotation information of all genes including transcription factors was acquired from the Phytozome website (https://phytozome.jgi.doe.gov/) and the list of all transcription factors was acquired from the PlantTFDB website (http://planttfdb.cbi.pku.edu.cn/).The Populus trichocarpa  were acquired by sequencing the 81 RNA-seq libraries made from the total RNA isolated from three tissues, mature vascular leaves, stem xylem and roots, which were sampled from plants subjected to cold, heat, drought and high salinity treatments. The sequencing reads were downloaded from NCBI database: BioProject (https://www.ncbi.nlm.nih.gov/bioproject) with an accession number of PRJEB19784. Raw reads were aligned to the P. trichocarpa v4.0 genome with TopHat (v2.1.1), followed by the generation of raw counts using Bedtools73. Finally, the raw counts were normalized with TMM  contained in edgeR package74. The annotation information of the transcription factors was acquired from Phytozome website (https://phytozome.jgi.doe.gov/).RNA-seq data sets of different tissues of 7 calculates the mutual information and conditional mutual information among a triple-gene block (Two pathway genes and one TF) using high-throughput gene expression data, and then evaluates if there are causal relationships among the triple genes. The significance of causal relationships was determined by bootstrapping. This algorithm was developed based on two biological phenomena: one is that genes within the same biological pathway/process or closely related biological pathways/processes are often more tightly co-expressed75; the other one is that genes with same or similar expression patterns are often under the regulation of the same molecular mechanism77. In addition, previous studies have showed that triple gene block is better than pairwise gene block for capturing causal relationships79. TGMI does not have tuning parameters and was implemented in R7. It can be can be download from: http://sys.bio.mtu.edu/sample_output/TGMI/.Triple-gene mutual interaction (TGMI)6 is a very effective method for achieving independent variable reduction given a set of dependent variables in high-dimensional data sets. It has a very wide range of applications for variable selection in high-dimensional genomic data with multicollinearity. PLS regression for either a univariate or multivariate response provides consistent estimators only under restricted conditions, and the consistency property does not extend to the very large variables and small number of samples. Chun and Keles (2010) formulated sparse partial least squares (SPLS) regression by relating it to sparse principal components analysis (SPCA) and developed an efficient algorithm for solving SPLS regression formulation. SPLS aims to achieve good predictive performance and variable selection by producing sparse linear combinations of the original predictors. We have used it to identify pathway regulators and found it is powerful in recognizing true regulators80. SPLS has two parameters: one is eta, representing the sparsity, eta should have a value between 0 and 1. The other parameters is K, which is the number of hidden (latent) components, K should take a value between 1 and min {p,(v − 1)n/v}, where p is the number of predictors and n is the sample size. We used an optimalization function to identify the optimal eta and K based on mean squared prediction errors (MSPEs) calculated for each data set and pathway. SPLS was implemented in R (https://cran.r-project.org/web/packages/spls/spls.pdf) and the R-package can be downloaded from the Comprehensive R Archive Network (CRAN)( https://cran.r-project.org/).Sparse partial least squares (SPLS)https://cran.r-project.org/web/packages/ggpubr/index.html) to investigate true positive (TP) versus false positive (FP) rate for different cut-off points in the candidate regulatory gene lists yielded from the two methods. The negative set contains all TFs except known true positive (TP) regulatory factors. For a specific list, true negative (TN) set contained all those in negative minus the false negative (FN) in the top list above the cut-off point. Each point on the ROC curve represented a true positive/false positive pair corresponding to a particular decision threshold. The sensitivity and specificity are calculated based on sensitivity = TP/(TP + FN) * 100, and specificity = TN/(TN + FP)*100.ROC curves were plotted using R package called ggpubr (Supplementary Information.


Ciona robusta, due to its philogenetic position close to vertebrates, is an excellent model to investigate mechanisms of post-transcriptional regulation evolutionarily highly conserved in immune homeostasis. The combined use of NGS and bioinformatic analyses suggests that in the pharynx, the hematopoietic organ of Ciona robusta, the Tgf-β, Wnt, Hedgehog and FoxO pathways are involved in tissue homeostasis, as they are in human. Furthermore, ceRNA network interactions and 3′UTR elements analyses of Tgf-β, Wnt, Hedgehog and FoxO pathways genes suggest that different miRNAs conserved , species-specific , pseudogenes  and mRNA 3′UTR elements are involved in post-transcriptional regulation in an integrated way in C. robusta.The transforming growth factor-β (TGF-β) family of cytokines performs a multifunctional signaling, which is integrated and coordinated in a signaling network that involves other pathways, such as Wintless, Forkhead box-O (FOXO) and Hedgehog and regulates pivotal functions related to cell fate in all tissues. In the hematopoietic system, TGF-β signaling controls a wide spectrum of biological processes, from immune system homeostasis to the quiescence and self-renewal of hematopoietic stem cells (HSCs). Recently an important role in post-transcription regulation has been attributed to two type of ncRNAs: microRNAs and pseudogenes.  The transforming growth factor-β (TGF-β) is a cytokine involved in regulation of cell fate and behavior in all tissues of the body . In humaRecent evidence indicates an association between different noncoding RNAs (ncRNAs) and TGF-β signaling . An impoCiona robusta, that shows a close phylogenetic relationship with vertebrates [C. robusta is the main haemopoietic organ, and can be challenged by inoculating LPS and can express immune related genes such as mannose binding lectin-like (Mbl-like) [Gal-like) [Il-17) [Tgf-β) [Mif1 and Mif2) [C. robusta Mif2 show cis-acting gamma interferon inhibitor of translation element (GAIT) and a cytoplasmic polyadenylation element (CPE) in 3′-UTR, which is not present in the 3′-UTR of Mif1, suggesting the presence of both transcriptional and post-transcriptional control mechanisms involved in the gene expression of the Mif genes  in innate immune response [Tlr2, MyD88, IκB, Ikkα, and Nf-κB mRNA confirmed that mechanisms involved in post-transcriptional regulation control of immune genes in human resulted highly conserved [C. robusta the signaling pathways and their post-transcriptional regulation in hematopoiesis are poorly studied and only some authors have described haematopoietic nodules in the pharynx in proliferation zones. In haemolymph, Lymphocyte-like cells (LLCs), can be marked by anti-CD34 monoclonal antibodies in agreement with the potential role of a pluripotent cell able to differentiate in different cell types [The urochordate tebrates ,23,24,25tebrates . Recentlbl-like) , galectial-like) , interle [Il-17)  tumor gr [Tgf-β)  and macrnd Mif2) . In humand Mif2) . In C. rresponse . Furtheronserved . In C. rC. robusta as in humans, the Tgf-β, Wnt, FoxO, and Hedgehog pathways could be involved in tissue homeostasis and that miRNAs, pseudogenes and elements of 3′-UTR are involved in post-transcriptional regulation of genes mechanisms that have been highly conserved during the evolution of animal species.RNA-Seq is becoming increasingly utilized to profile the annotated transcriptome, to detect and quantify known and novel transcripts, and identify novel classes of RNA. In the present study, using NGS and bioinformatics analysis we provide the first view of the pathways involved in homeostasis in the pharynx. Gene Ontology (GO) and Pathway analysis and ceRNA interaction analysis (miRNA-mRNA target-pseudogene) suggest that in C. robusta immunocompetent organ (pharynx) under physiological conditions we used next-generation sequencing (NGS) analysesTo profile ensembl.org, release August 2021; NGS data shown in NGS identified 15,074 transcripts and 6729 of these were annotated by the Ensembl database  shows that 6% of transcripts in C. robusta genome are ncRNAs, including also RNA transfer (tRNAs) and long noncoding RNAs (lncRNAs). The different percentage of ncRNAs in our study (1% compared to 6%) is probably justified by the fact that we investigated only one organ (pharynx) and not the whole C. robusta transcriptome. Coding RNAs from NGS sequencing were analyzed through the functional classification system of a Gene Ontology (GO) tool (panther.org) , National Center of Biotechnology Information (ncbi) data , binding (GO:0005488), and molecular function regulator (GO:0098772). The most represented categories for the biological process subclass were: cellular process (GO:0048511), metabolic process (GO:0008152), and biological regulation (GO:0065007). For the cellular component subclass the most representative categories were: cellular anatomical entity (GO:0110165) and intracellular (GO:0005622). As shown in mirbase.org, release October 2018) to find a match with annotated mature miRNA sequences within the precursors , and MirGeneDB 2.0  database of homologous miRNA genes to search animal genomes that have been validated and annotated. Although cin-mir-375 is not present in the ZooMir list and cin-mir-141 is not present in MirGeneDB, both are present in miRBase database . The cin-mir-92c-5p, cin-mir-92a-3p, cin-mir-375-3p, cin-mir-153-5p and cin-let-7d-5p were highly conserved in chordate species  have multiple let-7 isoforms. Indeed D. rerio and H. sapiens have diverse let-7 family members  although some differences may be observed . According to miRBase, in human the let-7 family is composed of nine mature let-7 miRNAs encoded by 12 different genomic loci, some of which are clustered together (data not shown), in D. rerio the let-7 family is composed of eighteen mature let-7 miRNAs.The let-7 miRNA was one of the first miRNAs discovered in of let-7 . let-7 mof let-7 , that spC. robusta that resulted annotated in Ensembl database and that were analyzed through Basic Local Alignment Search Tool (Blastn tool) , to find their parental gene and percentage of identity with parental genes     and the Protein Analysis Through Evolutionary Relationships (PANTHER) tool .To investigate Gene Ontology (GO) annotations of targets which were predicted to interact with specific miRNAs and pseudogenes obtained by NGS sequences, gene enrichment and pathway analyses were performed using two different web servers: the Database for Annotation, Visualization and Integrated Discovery (DAVID) tool  and the Benjamini correction test (Benjamini < 0.05). Most representative terms were linked to WNT signaling , MAP kinase activity, transcription regulation and protein binding. p-value statistical test  and Benjamini correction test (Benjamini < 0.05). Pathway analysis evidenced four pathways linked to homeostasis: the Tgf-β, Wnt, FoxO, and Hh pathways  and the Benjamini correction test (Benjamini < 0.05). Pathway selection was done filtering for the highest correction values of pathway analysis.Gene enrichment analysis was performed according to the three GO annotation classes: biological processes (BP), molecular functions (MF), and cellular component (CC)  to investigate the cis-elements of the 3′-UTR involved in post-transcriptional regulation of Tgf-β, Wnt, Hedgehog and FoxO pathways genes , p38 kinase, transforming growth factor β receptor IIa (tgfbr-iia), transcription factor protein(Gli) a cytoplasmic polyadenylylation element (CPE), involved in Poly(A) tail elongation after the export of the mRNA to the cytoplasm, though a mechanism called cytoplasmic polyadenylation; in Nemo-like kinase, Glycogen synthase kinase α/β(Gsk) a polyadenylation response element (MOS-PRE); an AU found in Smad4, Wnt ligand, p38 kinase; in Smad 4, Tgfbr-iib, Smoothened protein, a GU-rich destabilization element, identified in human as a conserved sequence, involved in rapid mRNA turnover; in Wnt signaling ligand, sfrp2, Gli, there was a UNR binding site. The RNA binding protein UNR can act as an activator or inhibitor of translation initiation, promote mRNA turnover, or stabilizes mRNA.Almost all mRNAs showed musashi-binding elements (MBE), and a γ-interferon activated inhibitor of translation (GAIT) element. In addition, RegRNA 2.0 identified in 3′-UTR of C. robusta zinc finger protein (zf(c2h2)-31), Not4 protein (not4), and Rrp12-like protein (LOC100184722)  .In humans, numerous studies show the crucial role of transforming growth factor β (TGF-β) to regulate the self-renewal capacity of hematopoietic stem cells (HSCs) in vivo, precisely, in the bone marrow (BM) it maintains the homeostasis of normal hematopoiesis through the precise generation of mature blood cells ,36,37,38Ciona robusta the pharynx, its hematopoietic organ, consists of two epithelial monolayers aligned in transversal and longitudinal bars, where flows the haemolymph containing hemocytes, mainly lymphocyte-like cells, hyaline amoebocytes, morula cells, unilocular refractile granulocytes, signet ring cells [C. robusta following LPS challenge, Tgf-β cytokine was transcriptionally upregulated and expressed by the hemocytes that are found to flow inside the pharynx vessels. In upregulation of Tgf-β mRNA time profile (1–72 h) two phases can be recognized, the first (1–4 h) when the inflammatory response starts end the second (48–72 h) in which homeostasis is reached and maintained [In ng cells . In C. rintained .In this study, NGS and bioinformatics suggest that combinatorial and crosstalk at multiple levels, between TGF-β, WNT, FOXO, and Hedgehog (HH) signaling pathways are involved in pharynx tissue homeostasis.The HH signaling pathway is evolutionarily conserved and is required for embryonic patterning, tissue repair, and regeneration. In vertebrates, HH signaling is controlled by polypeptide ligand, an intracellular signaling molecule called Hedgehog (HH). If the ligand is not present, two cell-surface transmembrane proteins called the patched receptor (PTCH1 or PTCH2) repress the 7-membrane-spanning receptor-like protein smoothened (SMO) leading to the phosphorylation of GLI (glioma-associated oncogene homolog) transcription factors by several protein kinases such as kinase A (PKA), GSK-3b, and CK1, and subsequent cleavage of GLI into truncated forms that act as repressors of HH target genes . The binIn vertebrates, the WNT signaling pathways is involved in regulating many aspects of development and play important roles in cell-fate determination, self-renewal, and maintenance of stem cells . CompletC. robusta gene enrichment and pathway analyses from NGS data, together with RNA–RNA interaction predictions evidenced a ceRNA  interaction network involved in post-transcriptional regulation of four pathways  linked to pharynx tissue homeostasis.In C. robusta NGS identified 15,074 transcripts and of these 1% (201 elements) was classified as noncoding RNA (ncRNA). Of these 201, 90 were miRNAs and 27 pseudogenes. Gene enrichment and pathway analyses from NGS data, together with RNA–RNA interaction predictions by miRNATIP predictor, evidenced a ceRNA interaction network involving the four pathways linked to pharynx tissue homeostasis. Both conserved  and species-specific miRNAs were found in ceRNA interaction network. Moreover, only three pseudogenes were found to interact with miRNAs involved in gene expression regulation of Wnt and Hh pathways.MicroRNAs (miRNAs), found in diverse eukaryotes from plants to animals, inhibit gene expression largely in a posttranscriptional manner, by interacting with miRNA response elements (MREs) in the mRNA 3′-UTRs of the target genes. Pseudogenes which have the similar MREs target genes of miRNAs , leadingC. robusta Tgf-β, Wnt, FoxO, and Hh signaling pathways showed a variety of cis-regulatory elements, including the CPE, ARE, MBE, GU-rich destabilization element, UNR binding site (an important cis-element for RNA regulation) and GAIT elements that, in humans, are implicated in post transcriptional regulation of several immune-related mRNAs, and have an important role in gene specific translation control in innate immunity [After transcription, mRNAs are exported to the cytoplasm  to be trimmunity .C. robusta, as in humans, Tgf-β, FoxO, Wnt, and Hh signaling extensively cross-talk at many levels, and that multiple signaling inputs are integrated into the core transcription factor network to regulate target gene expression cooperatively in tissue homeostasis and the genes of these signaling pathways are subjected to a complex system of post-transcriptional regulations that involve in an integrated way miRNAs, pseudogenes and 3′UTR elements.All these data suggest that in Ciona robusta, was formerly classified as Ciona intestinalis. Molecular studies have confirmed that C. intestinalis constitutes a compilation of species rather than a single species [In this study, the model organism  species ,56,57,58C. robusta specimens were collected from Sciacca harbor  and were acclimatized and maintained as reported in Arizza et al. [a et al. Fragments of pharynx tissue (200 mg) were immediately soaked in RNAlater tissue collection solution  and Total RNA extraction was performed as reported in in Arizza et al. .C. robusta (N = 3) were examined by NanoDrop and Agilent RNA 6000 Nano kits on an Agilent 2100 Bioanalyzer , respectively. High-quality RNA samples  were used for cDNA library construction. RNA sequencing (RNA-Seq) was performed by BMR Genomics  on an Illumina platform in a single-end format 75 bp (1 × 75 bp) containing ~40 million ± 10% of reads/sample [The RNA purity and quality of total RNA extracted from the pharynx of s/sample .https://www.ensembl.org/index.html, release August 2020). The annotation evidenced different classes of RNA molecules: protein-coding and noncoding RNA. Between the ncRNAs the annotation evidenced the following RNA classes: miRNAs, pseudogenes, small nuclear RNA (snRNAs), small nucleolar RNAs (snoRNAs), ribosomal RNAs (rRNAs), miscellaneous RNAs (miscRNAs), and mitochondrial RNAs (mtRNAs).All transcripts produced by NGS were annotated by Ensembl database  database . All the three different Gene Ontology subcategories were investigated: (i) molecular functions (MF); (ii) cellular components (CC); (iii) and biological pathways (BP). The results for the three GO categories were filtered for p-value and for adjusted p-value (<0.05), and for Benjamini correction test (Benjamini < 0.05).Gene Ontology enrichment analysis: The Protein Analysis Through Evolutionary Relationships  system connected to the COG database was used to expand the annotation data of the gene and protein families obtained from GO. The “GO-slim” analysis mode was set, as it is more reliable and accurate than the GO annotation mode “GO-complete”.mirbase.org, release October 2018). This tool allows us to find similar protein or nucleotide sequences to the target sequence under investigation. Each sequence was taken from the Ensembl genome browser . Only “query” sequences with E-value < 0.05 and S score > 100 were considered as significant results.The sequences of the 36 miRNA precursors were aligned using miRBase Blastn alignment tool  or lower, just a few sequences were considered as potential good results.C. robusta were selected to blast the “query” sequence.Sequence alignment was performed both with miRNA precursor sequences than with mature sequences. This choice allowed us to compare E-values results for each alignment to increase the power of analysis  and MirGeneDB  database of homologous microRNA genes search in animal genomes that have been validated and annotated. Results were also compared with miRNAs annotated in miRBase database (http://www.mirbase.org/ release October 2018).To study evolution pattern of conserved blast.ncbi.nlm.nih.gov/Blast.cgi, release October 2020), to find regions of similarity between biological sequences and to see if pseudogenes produced by NGS derived by known genes and if they were conserved through evolution. The pseudogenes were analyzed according to Ensembl “genebuild” algorithm. Two parameters were used to evaluate the significance of the match: the expected value (E), a parameter that describes the number of hits one can “expect” to see by chance when searching a database of a particular size; and the score S (S), that is inversely correlated with the E value.The pseudogenes annotated by Ensembl database were analyzed through Basic Local Alignment Search Tool (Blastn tool)  were performed through the miRNA target interaction predictor (miRNATIP) algorithm . For eacThe first step of the algorithm is the training of a self-organizing map (SOM) neural network . This neThe third step, take care of clustered elements. For each pair of miRNA seed and mRNA/pseudogene fragment, miRNATIP compute the dissimilarity between the miRNA tail and an extended version of mRNA/pseudogene fragment . The algorithm also considers potential bulges between miRNA seed and tail. If the computed dissimilarity is under a specific threshold, the putative interaction is considered for the next step. The last step filters out wrongly predicted interactions, by means of the computation of the binding free energy.http://regrna.mbc.nctu.edu.tw/html/prediction.html, release February 2021).To characterize the 3′UTR elements of mRNAs, a computational analysis was performed using the regulatory RNA motifs and elements finder tool  pathway chart. DAVID pathway viewer displays user genes on static pathway maps generated by BioCarta and KEGG.Pathway analysis was performed using the DAVID tool. First, functional annotation analysis was selected. The p-value used for functional annotation analysis, was set as 0.1. Results were considered statistically significant if p-value and adjusted p-value were < 0.05. The updated version of DAVID tool was 20 August 2020, DAVID release 6.7.EASE (Exact Annotation Significance Enrichment) score threshold, a modified Fisher exact p-value and Benjamini thresholds were set as <0.05.All statistical assessments of GO term enrichment and pathway analyses were performed by Fisher’s exact test in combination with a robust Benjamini correction test, for multiple testing. The row C. robusta pathways  were downloaded from KEGG database  in the Cytoscape tool . Cytoscape is an open-source software platform for visualizing molecular interaction networks and biological pathways and integrating these networks with annotations. The Cytokegg app was used to load KGML files, previously downloaded from KEGG, in Cytoscape db, and the STRING app was then used to convert the networks into STRING networks (STRINfy networks).To build ceRNA network evidenced by RNA-RNA interaction prediction, https://www.r-project.org/, release October 2020); .R package and R studio were then used to merge all pathways and to evidence common proteins (In particular, “igraph” package of R was used to analyses networks produced by STRING and to generate the image of integrated networks


Recent reports suggest a link between positive regulation of the Hippo pathway with bipolar disorder (BD), and the Hippo pathway is known to interact with multiple other signaling pathways previously associated with BD and other psychiatric disorders. In this study, neuronal-like NT2 cells were treated with amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), valproate (0.5 mM), or vehicle control for 24 h. Genome-wide mRNA expression was quantified and analyzed using gene set enrichment analysis (GSEA), with genes belonging to Hippo, Wnt, Notch, TGF- β, and Hedgehog retrieved from the KEGG database. Five of the eight drugs downregulated the genes of the Hippo pathway and modulated several genes involved in the interacting pathways. We speculate that the regulation of these genes, especially by aripiprazole, clozapine, and quetiapine, results in a reduction of MAPK and NFκB pro-inflammatory signaling through modulation of Hippo, Wnt, and TGF-β pathways. We also employed connectivity map analysis to identify compounds that act on these pathways in a similar manner to the known psychiatric drugs. Thirty-six compounds were identified. The presence of antidepressants and antipsychotics validates our approach and reveals possible new targets for drug repurposing. Hpo) was associated with tissue overgrowth of the eyes, wings, and limbs, a phenotype that gave name to the pathway [The Hippo pathway is a signaling cascade that integrates a broad range of different biological, chemical, and mechanical cues to control several cellular processes through its downstream effectors YAP (yes-associated protein) and transcriptional co-activator with PDZ-binding motif (TAZ) ,2. It wa pathway . The Hip pathway ,2.The canonical Hippo signaling pathway is a key regulator of organ size and tissue remodeling . The nonYAP, the authors suggested that this pathway might have important implications in understanding the pathophysiology of BD, and could be a source of new targets for treatment. Further, the Hippo pathway genes were also reported as hypermethylated in a twin affected with BD compared with the non-affected twin [Due to its role in both healthy and pathologic processes in the central nervous system and its crosstalk with other signaling pathways, it is unsurprising that the genes involved in the Hippo pathway have recently been associated with various psychiatric conditions ,17,18,19ted twin . Althougted twin . Valproited twin .Therefore, this study aimed to evaluate the effects of commonly prescribed psychoactive drugs used in treating affective disorders (BD and SZ) on the expression of genes in the Hippo pathway. We expect these medications to downregulate the genes involved in the Hippo pathway, as upregulation of the Hippo pathway was previously observed in people with BD compared to healthy controls .The list of genes involved in the Hippo pathway was extracted from the KEGG database, and the acute effects of the eight drugs on these genes was analyzed by GSEA. Five of the eight drugs, amisulpride, aripiprazole, clozapine, quetiapine, and risperidone, significantly downregulated genes in the Hippo pathway, as shown in Having ascertained that five of the psychoactive drugs significantly altered the expression of genes in the Hippo pathway, we further investigated the effects of these drugs on a smaller set of genes. This smaller set of genes included the core genes of the Hippo pathway and its transcription factors, which are the critical effectors of the pathway  A–E.p = 0.007, p = 0.025, p = 0.001, and p = 0.008, respectively). Risperidone and quetiapine downregulated the core genes of the Hippo pathway , and amisulpride (p = 0.05) showed a tendency to downregulate the core genes of the Hippo pathway.Amisulpride, aripiprazole, clozapine, and quetiapine significantly reduced the expression of the transcription factors involved in the Hippo pathway , aripiprazole (p = 4.80 × 10−6), clozapine (p = 0.0013), and risperidone , aripiprazole (p = 0.043), and clozapine (p = 0.0033) reduced the expression of genes in the notch signaling pathway. Again, quetiapine increased or decreased the expression of several genes in the pathway, but did not have a significant overall effect , and tended to be reduced by aripiprazole  and risperidone (p = 0.06)  .p < 0.1; p < 0.05  significantly downregulated the expression of Hippo signaling pathway genes, together with differential effects of each drug on various interacting pathways. These results complement reports of upregulation of these sets of genes in samples derived from patients with BD ,19, possNF2 and WWC1 genes, accompanied by the downregulation of the Wnt and Notch pathways.The atypical antipsychotics aripiprazole and clozapine modulate dopaminergic receptors, as well as a range of other targets . Our resNF2 plays an indispensable role in the recruitment of MST1/2 and LATS1/2 to the plasma membrane, which enables LATS1/2 phosphorylation and repression of YAP/TAZ and MOB1 ,24,25. CNF2 and WWC1 observed following treatment with aripiprazole and clozapine could lead to YAP/TAZ nuclear translocation and its non-canonical activities: inhibition of TGF-β signaling [The downregulation of ignaling ,31 and mignaling ,33. YAP/ignaling ,35 .GLI2, a downstream effector of SHH. The Hh signaling pathway has been associated with maintaining the stem propriety in cells in the hippocampus and cerebellum [GLI2 following treatment with clozapine, haloperidol, and chlorpromazine in ShhL2, C3H10T1/2, and T98G cells [In addition, clozapine also downregulated the Hh pathway, accompanied by significant downregulation of rebellum ,38. Simi8G cells . The fin8G cells .LATS1 following treatment with amisulpride could lead to YAP/TAZ sequestration to the cytoplasm, which binds to β-catenin differently to nuclear YAP/TAZ, preventing translocation to the nucleus and therefore inhibiting Wnt signaling [Similar to aripiprazole and clozapine, amisulpride also significantly downregulated the Wnt and Notch signaling pathways. The overall downregulation exerted by amisulpride in the Hippo signaling pathway seems to be primarily driven by effects on the expression of the transcription factors, particularly TCFs and TEADS A. T-cellignaling . TEA domignaling ,44. TGFβignaling ,46. Finaignaling ,48 .Quetiapine and risperidone have different mechanisms of action compared to the medications above , which mThe opposite was found for risperidone, with the GSEA analysis indicating a trend for downregulation of genes in the Hippo signaling pathway, despite none of the genes reaching statistical significance.NF2 and WWC1 was observed following administration of aripiprazole, clozapine, and quetiapine. Likely consequences include reduced inflammatory signaling mediated by MST1/2 and NF2, and reduced MAPK and NFκB activity levels following upregulation of YAP/TAZ. Aripiprazole also downregulates T-cell factors, potentially compromising Wnt signaling [Downregulation of ignaling .YAP deletion in astrocytes induced JAK-STAT pathways, inducing reactive astrogliosis, microglial activation, and BBB dysfunction in mice [Several authors have demonstrated that MST1/2 directly regulates many aspects of immune activation and the activity of inflammatory pathways ,53. Exam in mice .When considered as a whole, the net effects of these changes would reduce pro-inflammatory signaling mediated by MAPK and NFκB. This is of interest as aripiprazole , quetiapp-value < 0.05 acting on the signaling pathway genes similarly to amisulpride, aripiprazole, clozapine, quetiapine, and risperidone  is a natural pentacyclic triterpenoid carboxylic acid present in various plants and is a recurrent component of our diet . As partThe identification of the antipsychotics, including clozapine, piperacetazine, and triflupromazine by this CMap analysis adds weight to our contention that this is a valuable methodology to identify drugs which act in a similar manner to the drugs we tested, and gives confidence that they represent potential targets for repurposing to treat psychotic and affective disorders.−5 M for 28 days. Following retinoic acid treatment, cells were plated for experiments in 24-well plates at 2 × 105 cells/well and treated with mitotic inhibitors  for 7 days.NT2 human teratocarcinoma cells  were cultured, maintained and differentiated as previously described . BrieflyOnce enriched cultures of differentiated neuronal cells (NT2-N) were obtained, the cells were treated with drugs commonly prescribed in psychiatry (amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), or valproate (0.5 mM); Sigma-Aldrich) or the appropriate vehicle control (DMSO 0.2% or Milli-Q water 0.5%) for 24 h (n = 4–5 per group). The dosages chosen for the in vitro treatment were determined based on previous dose–response studies so that, when used in combination, no single drug dominated the overall effect on gene expression nor affected cell viability. Such doses were carried out throughout the following projects . The exp® mini kits  and quantified by spectrophotometry . The quality of the extracted RNA was evaluated using an Agilent 2100 Bioanalyzer . RNAseq libraries were prepared from 1 ug of total RNA using a TruSeq RNA samples Preparation kit . The libraries were sequenced using a HiSeq 2500 flow cell  according to the manufacturer’s instructions.Following the 24-h drug treatment, cells were harvested using Trizol, and total RNA was extracted using RNeasyhttps://github.com/m-richardson/RNASeq_pipe, accessed on 1 July 2017). In summary, this involves: Raw read quality filtering and adapter trimming  with Trimmomatic v35 [p-values of <0.05 were considered to be differentially expressed.The raw data were obtained in fastq format, and processed using the Deakin Genomics Centre RNAseq alignment and expression quantification pipeline  database was used as a reference database, and only gene sets with sizes ranging from 3 to 800 genes inclusive were considered. The resulting tables had enrichment scores and p-values calculated from 10,000 permutations, with accompanying false discovery rate q-values adjusted for multiple testing.GSEA was deployed using the R package cluster Profiler  from BioThe list of genes belonging to the Wnt signaling pathway, Notch signaling pathway, Hedgehog signaling pathway, Transforming Growth Factor Beta (TGF-β) signaling pathway were obtained from KEGG, and then tested for overall transcriptional regulation by the drugs. The distribution of logFC data was checked for normality using Kolmogorov–Smirnov tests. Drug treatment groups were compared against their respective controls using independent samples t-tests for normally distributed data and Mann–Whitney U tests for data not normally distributed.https://www.affymetrix.com/site/mainPage.affx; Thermo Fisher Scientific, accessed on 1 November 2020). The IDs were collated in sets of “up” or “down” regulated genes and submitted to CMap. The similarities between the gene expression patterns induced by the compounds in the CMap database and those caused by the psychoactive drugs used in this project were reported as connectivity scores ranging from +1 (increased similarity) to −1 (inverse similarity).Genes in the Hippo pathway that were significantly increased or decreased by 4 or more of the drugs were assigned a tag ID recognizable by CMap using Human Genome U133 Plus 2.0 Array on Affymetrix (To our knowledge, this is the first study to evaluate the effects of mood stabilizers and antipsychotics on the expression of genes involved in the Hippo pathway and its interacting pathways. Remarkably, the effects and routes described here were previously observed in oncology, due to the role of the Hippo signaling pathway in tumorigenesis. In this context, further research investigating the effects of these genes and pathways in psychiatry is necessary. We acknowledge some limitations of our study. All experiments were conducted in neuronal-like cells without the induction of any disease state model; therefore, underlying disease-specific pathophysiological processes might alter the drug effects. In addition, we tested a single dose of each drug and measured its acute effects, hence these findings do not capture chronic administration effects or drug-drug interaction during polypharmacy.The identification of new pathways associated with psychiatric conditions that can be targeted by known pharmacological treatments can highlight an opportunity for the development of new treatment options for these debilitating conditions. This represents an opportunity to offset the lack of mechanistic understanding in BD and SZ, as well as other psychiatric conditions, and the curtailment in research and development by major pharmaceutical companies . The use


Here, we studied deeply the solid-state characteristics of KLS to possibly identify new polymorphic drugs. Conducting a polymorph screening study and combining conventional techniques with solid-state nuclear magnetic resonance, we identified, for the first time, a salt/cocrystal polymorphism of the ketoprofen (KET)–lysine (LYS) system, with the cocrystal, KET–LYS polymorph 1 (P1), being representative of commercial KLS, and the salt, KET–LYS polymorph 2 (P2), being a new polymorphic form of KLS. Interestingly, in vivo pharmacokinetics showed that the salt polymorph has significantly higher absorption and, thus, different pharmacokinetics compared to commercial KLS , laying the basis for the development of faster-release/acting KLS formulations. Moreover, intrinsic dissolution rate (IDR) and electronic tongue analyses showed that the salt has a higher IDR, a more bitter taste, and a different sensorial kinetics compared to the cocrystal, suggesting that different coating/flavoring processes should be envisioned for the new compound. Thus, the new KLS polymorphic form with its different physicochemical and pharmacokinetic characteristics can open the way to the development of a new KET–LYS polymorph drug that can emphasize the properties of commercial KLS for the treatment of acute inflammatory and painful conditions.Ketoprofen– During the last decade, cocrystallization has emerged and established itself in the field of pharmaceutical solid-state chemistry as an advanced and valuable method to modify the physicochemical characteristics of drugs . Like phaK rule” has been proposed to provide, at least to some extent, reliable indications about the possibility of obtaining a salt and vice versa. Accordingly, a larger ΔpaK  − paK (acid)) leads to a greater chance of obtaining a salt and vice versa [Most commonly, when a specific pair of molecules is combined with the same stoichiometry and at the same temperature, the outcome is either a salt (ionic) or a cocrystal  . Howeverce versa ,10,11, waK = 1, wherein the chances to get a salt or a cocrystal are very similar. In this region usually fall the rare cases in which the same chemical species can give rise to both a cocrystal and a salt , which have the same composition and stoichiometry at the same temperature, depending on the crystallization protocol. Stainton et al. were the first to report a cocrystal and a salt of the same chemical composition (isonicotinamide and citric acid [dl-tartaric acid [These formulas identify a region of uncertainty around Δpric acid ) and, suric acid ,14, sulfric acid , dinitroric acid , and ethric acid . Some ofric acid , or dissric acid , and cocric acid , but mosric acid , which cric acid . Lastly,l-lysine salt (KLS) to identify its already known and new crystalline forms and, thus, possibly discover new polymorphic drugs, we thoroughly investigated, for the first time, the existence of polymorphs of the ketoprofen (KET)–lysine (LYS) system (With the aim of studying deeply the solid-state characteristics of ketoprofen–) system . KET belHere, we report the method of crystallization and characterization of two distinct KET–LYS polymorphic forms, with salt and cocrystal structural characteristics, and we compare their physicochemical properties, their organoleptic characteristics by electronic tongue analysis, and their pharmacokinetics in vivo.As part of a project aimed at the identification of new polymorphs of the KET–LYS system, we obtained two polymorphic forms of KET–LYS, KET–LYS P1 and KET–LYS P2, through different crystallization techniques . We perfaK rule, the reaction between KET and LYS should result in a salt, as the ΔpaK of these molecules is 5.84 (paK (protonated LYS γ-NH2) − paK (KET COOH) = 10.29 − 4.45). However, since the model suggested by Cruz-Cabeza et al. [aK < 4 and the ΔpaK in this case is higher than 4, the probabilities of obtaining a salt or a cocrystal cannot be quantitatively estimated.According to the pSince crystals of suitable size for single-crystal X-ray diffraction could not be produced, we performed an XRPD analysis to investigate the microstructure and properties of the powders. The non-superimposition of the XRPD diffraction patterns  showed tTo define the nature of these two polymorphs, we firstly performed differential scanning calorimetry (DSC). Interestingly, the DSC profile of KET–LYS P1 showed an endothermic event at 170.7 °C (onset 164.1 °C) that was associated with sample melting and degradation , whereas−1 and could represent the OH stretching in carboxylic acid dimer bands; on the contrary, this band was not detectable in KET–LYS P2, which showed instead a very broad band at 3400–3660 cm−1. Lastly, in KET–LYS P2, the strong band at 1.550 cm−1 could be due to the KET carboxylate anion group [We then performed an FT-IR analysis and observed that the vibration peaks of characteristic functional groups  of the KET−LYS system significantly differed between the two polymorphs, and this could be attributable to hydrogen bonding and salt formation . Indeed,on group .13C and 15N chemical shifts are in fact very sensitive to the protonation state of carboxylic and N-containing functional groups [13C chemical shift undergoes a high-frequency shift in the following order: neutral carboxylic groups (COOH) < COOH involved in HB interactions (COOH⋯X) < formation of a dimer through a homosynthon (COOH⋯HOOC) ≈ carboxylate groups (COO−) [15N chemical shift is even more sensitive, as protonation induces shifts that can be as large as 25 ppm toward higher frequencies for aliphatic amines in agreement with the minor contribution of the lone pair to σploc [13C and 15N CPMAS) and 2D (1H–13C HETCOR) experiments were acquired for KET–LYS P1, and the 13C CPMAS spectrum was acquired for KET–LYS P2. For comparison, we also analyzed pure KET, its sodium salt (Na+KET−), dl-LYS·2HCl, and pure l-LYS, the latter being selected as a reference due to its crystal structure displaying a free ε-NH2 group , relying on the accuracy of this technique  to undoul groups . In genes (COO−) ; the 15Nto σploc . Here, 1H2 group . Table 113C CPMAS spectra of KET–LYS P1 and KET–LYS P2 exhibited consistent shifts in the resonances associated both with KET and with l-LYS carbon atoms . In the case of KET–LYS P1, we observed two peaks in the carboxylic region, at 174.5 and 177.6 ppm.In 1H–13C FSLG HETCOR) in two different versions, with on- and off-resonance CP conditions; the first  and KET (50.2 ppm) to the corresponding protonic peaks, leading to their assignment at 3.4 and 3.6 ppm, respectively. Being the CH groups closest to the carboxylic moieties in both KET and LYS, we were then able, through the long-range version of the experiment (− in pure LYS (176.7 ppm), which, together with the 15N data (see below), confirms the zwitterionic nature of LYS in KET–LYS P1. The KET signal resonates at a frequency which is much lower than that of both the COO− groups of Na+KET− (181.4/180.5 ppm) and the homodimeric COOH group of pure KET (184.0 ppm). In particular, the KET signal is very similar to that unambiguously assigned to a neutral carboxylic group involved in an HB, observed at ca. 177 ppm in the (ibuprofen)2 cocrystal [To understand which signal refers to the carboxylic group of KET and which refers to that of LYS, we performed a 2D experiment , and it showed that the ε-N signal falls at 32.8 ppm, which is intermediate between the chemical shifts of α-NH3+ and ε-NH2 of pure l-LYS. Although ambiguous, its chemical shift suggests the presence of a neutral NH2 group involved in HB interactions, i.e., H2N⋯H–X. Indeed, a proper ε-NH3+ signal falls at 41.3 ppm as observed in the spectrum of dl-LYS·2HCl. Thus, it can be said that this system falls in the salt/cocrystal continuum but points more toward a neutral nature, again supporting the concept that the KET–LYS P1 structure is more referable to a cocrystal rather than to a salt.To confirm this assumption, we further investigated the system by 13C CPMAS spectra, it can be observed how, in KET–LYS P2, the signal at 181.5 ppm (referred to KET) is quite close to the signal of pure KET (184.0 ppm) and especially of Na+KET− (181.4/180.5 ppm). This suggests that, in KET–LYS P2, the COOH of KET is in a carboxylate form, since dimeric COOH groups and COO− moieties resonate at similar frequencies.From the comparison among the aK rule and the fact that the ΔpaK of our system is higher than 4, for which a salt is to be definitely expected. Thus, while the paK rule has a statistical and predictive value that is fundamental in the design phase, once the adduct is obtained, the characterization of the protonation state must be always supported by diffraction and/or spectroscopic data. This is because, as also for this system, the influence of the crystalline environment in defining the hydrogen position along an HB is more important than the strength of the acidic and basic sites [Altogether, these data clearly demonstrate that the crystallization outcome of the reaction between KET and LYS is a case of salt/cocrystal polymorphism. This result is unexpected if we consider the pic sites .aK rule”, which has been validated only for a limited ΔpaK range [aK outside the −1 < ΔpaK < 4 range.Surprisingly, the subsequent analysis of commercial samples of KLS from different manufacturers showed that it is representative of KET–LYS P1 , thus reKa range . Thus, tHaving identified two distinct polymorphs of the KET–LYS system, we then analyzed them with regard to some of the intrinsic chemical and physical properties that have to be considered before the development of a pharmaceutical formulation. Among these properties, the dissolution rate of a drug is usually modified by cocrystallization processes . Thus, wThese results further confirm that the outcomes of KET and LYS crystallization are two different structural entities and demonstrate that the two forms are characterized by different IDRs. In vitro dissolution is an important factor in defining drug absorption, distribution, metabolism, and excretion (ADME), and different IDRs among drugs can allow for the development of formulations with different release kinetic profiles . CommercOne of the central challenges of drug manufacturing is to sweeten the unpleasant taste of APIs, which can be bitter, salty, sour, and even metallic or astringent, as it negatively affects the compliance of patients, especially in pediatric and geriatric populations . TechnolAs some studies have reported, the taste of a drug is among the chemical properties that cocrystallization can modify . For exaWe, thus, investigated and compared the taste and the sensorial kinetics of KET–LYS P1 and KET–LYS P2, to assess whether the substitution of an ionic bond  with a neutral HB , rather than the substitution or the addition of coformers as described in the above examples, can alter these characteristics. To analyze the variation of bitterness and palatability characteristics of KET and LYS pharmaceutical preparations, we used a potentiometric E-tongue system application, a method that was successfully employed in previous researches dedicated to the evaluation of soft cheese salinity , water tmax, T1/2, and mean residence time (MRT); however, notably, the dose-normalized area under the curve to infinity (AUC-inf) and Tmax values of KET–LYS P1 were significantly higher than those of KET–LYS P2  (max) depends on the rate of drug absorption. Thus, the lower AUC-inf of KET–LYS P2 compared to that of commercial KET–LYS P1 could probably mean a lower bioavailability of KET–LYS P2, in addition to a lower Tmax that indicates a faster absorption of this latter compared to commercial KLS. These data agree with IDR data and show the potential advantages of KET–LYS P2 for a further improvement of fast-acting formulations for the treatment of acute inflammation conditions.Having assessed the differences in IDRs between the polymorphic salt and cocrystal forms of KET and LYS, we studied and compared the in vivo pharmacokinetics. We analyzed the major pharmacokinetic parameters after oral administration of the two compounds at the dose of 3.5 mg/kg to not fasted Sprague Dawley male rats. Results showed that the two polymorphs were comparable in terms of Cn ± SEM) . After smax, for its rapid absorption and subsequent therapeutic action [While it can be expected that cocrystals and salts with different coformers have different physicochemical and pharmacokinetic characteristics, finding significant differences in the IDR, taste, and pharmacokinetics of a salt and its cocrystal polymorph surely opens new perspectives. Altogether, these differences clearly highlight the actual impact that (in this case) the substitution of one ionic bond  with a neutral HB  can have on drug clinical performance, to the extent that different formulations and different coating processes or flavor addition can be suggested for the two polymorphs. KLS is a widely used NSAID that is already known, as also confirmed by our data on KET–LYS P1 Tc action , which mTo deeply investigate the solid-state characteristics of KLS, we conducted a polymorph screening study to identify all the crystalline forms that this API can adopt. To this end, several crystallization conditions were tested on the basis of the solubility properties of the compounds . ExperimFor all the compounds, various stoichiometric ratios were investigated in the range of 0.5 to 2 equivalents with respect to the amount of KET or LYS. The slurry experiment with saturated solutions in various solvents was performed when possible.RS)-KET was added to 350 mL of ethanol, and the mixture was stirred at RT until complete solubilization. Then, 29 g of dl-LYS, 50% w/w in water (1:1 ratio), was added, and the solution was stirred at RT until the first precipitation occurred. The mixture was left under these conditions for 3 h and then cooled to 5 °C. After 5 h, the product was recovered by filtration, washed with 60 mL of ethanol, and dried under reduced pressure at 40 °C. The final KET–LYS P1 was obtained as a white powder .First, 50 g of (RS)-KET and 0.69 g of dl-LYS (1:1 ratio) were suspended in 20 mL of methanol and left under stirring at 40 °C for 1 h. The suspension was then filtered (0.45 μm filter) directly in a Mettler Toledo Easymax 102 reactor. The solution was left under stirring for 5 min in the reactor; then, 100 mL of ethyl acetate was added, and the solution was cooled to −5 °C without solid formation. Ethyl acetate (20 mL) was added through a pipette in two aliquots (10 mL and 10 mL) to trigger nucleation. The system was left under stirring until the suspension became “milky”. An additional 30 min of stirring was applied. The precipitate was then filtered, and the collected sample was stored in a sealed vial at room temperature. The final KET–LYS P2 was obtained as a white powder .First, 1.2 g of (θ) and speed of 10.0°/min (2θ) from 3° to 40° 2θ. The tube voltage and amperage were 40 kV and 15 mA, respectively.XRPD experiments were performed on a powder X-ray diffractometer  using Cu Kα radiation (1.540598 Å). Samples were scanned with a step size of 0.01°  spectra of KET, LYS, Na13C CPMAS spectra were acquired at a spinning speed of 12 kHz, using a ramp cross-polarization pulse sequence with a 90° 1H pulse of 3.60 μs, a contact time of 3 ms, optimized recycle delays between 1.5 and 3.5 s, and a number of scans in the range 430–640, depending on the sample. 15N CPMAS spectra were acquired at a spinning speed of 9 kHz using a ramp cross-polarization pulse sequence with a 90° 1H pulse of 3.60 μs, a contact time between 1 and 4 ms, optimized recycle delays between 1.1 and 3.4 s, and a number of scans in the range 14,330–22,770, depending on the sample. For every spectrum, a two-pulse phase modulation (TPPM) decoupling scheme was used, with a radiofrequency field of 69.4 kHz. The 13C chemical shift scale was calibrated through the methylenic signal of external standard glycine (at 43.7 ppm). The 15N chemical shift scale was calibrated through the signal of external standard glycine (at 33.4 ppm with reference to NH3).Powder samples were packed into cylindrical zirconia rotors with a 4 mm o.d. and an 80 μL volume. A certain amount of sample was collected from each batch and used without further preparation to fill the rotor. 1H−13C on- and off-resonance  HETCOR spectra were measured with contact times of 0.1 and 7 ms, respectively, and FSLG t1 decoupling and TPPM t2 decoupling (rf fields of 82 kHz). Accordingly, 288 and 384 scans were averaged for 88 and 128 increments, respectively, with 3.4 s of relaxation delay. The indirect 1H chemical shift scale in the HETCOR spectra was experimentally corrected by a scaling factor of 1/√3 because the 1H chemical-shift dispersion is scaled by a factor of 1/√3 during FSLG decoupling.The 2D 13 CPMAS spectrum of KET–LYS P2 was acquired with a Jeol ECZR 600 instrument, operating at 600.17 and 150.91 MHz, respectively, for 1H and 13C nuclei. The powder sample was packed into a cylindrical zirconia rotor with a 3.2 mm o.d. and a 60 μL volume. A certain amount of sample was collected from the batch and used without further preparations to fill the rotor. The 13C CPMAS spectrum was acquired at 273 K, at a spinning speed of 20 kHz, using a ramp cross-polarization pulse sequence with a 90° 1H pulse of 2.19 μs, and a contact time of 3.5 ms. An optimized recycle delay of 6 s was used, for a number of scans of 240. A two-pulse phase modulation (TPPM) decoupling scheme was used, with a radiofrequency field of 108.5 kHz. The 13C chemical shift scale was calibrated through the methylenic signal of external standard glycine (at 43.7 ppm).The 15N-NMR low sensitivity together with the poorly crystalline nature of KET–LYS P2 prevented a proper parameter optimization of the CPMAS experiment. Several attempts were made for acquiring the 15N CPMAS spectrum of KET–LYS P2 by changing several parameters , without succeeding.The well-known KET–LYS P1 and KET–LYS P2 were tested for intrinsic dissolution rate (IDR). The IDR experimental method was performed using a 150 mg powder sample; this was compacted by means of a hydraulic press in a round Ø = 11 mm matrix, under approximately 2 tons of force for 3 min. The obtained compacts were maintained inside the matrix and tested in a USP42 Apparatus 2  under the following conditions: 500 mL of gastric simulated fluid (GSF) without pepsin, 37 °C, and 30 rpm paddle rotation speed. The amount of solid dissolved at each time point was determined spectrophotometrically at 260 nm. The test was performed in three replicates. Statistical analysis of the data was performed by Microsoft Excel.2, and 0.06 mol/L of fructose were used, respectively. Millipore-grade water was used for aqueous solution preparation. All the other chemicals were of analytical grade and used without further purification.The composition and properties of tested samples (KET–LYS P1 and KET–LYS P2) are listed in Membrane components, high-molecular-weight poly(vinyl chloride) (PVC), bis(2-ethylhexyl) sebacate (DEHS) plasticizer, tridodecylmethyl ammonium chloride (TDMACl), potassium tetrakis-(4-chlorophenyl)borate (TpClPBK) lipophilic additives, and nonactine ionophore were purchased from Sigma-Aldrich . Tetrahydrofuran (THF) used for PVC membrane preparation was obtained from Carlo Erba Reagents  and distilled prior to use. 5,10,15,20-Tetraphenylporphyrin manganese(III) chloride ionophore (Mn(TPP)Cl) was synthesized in our laboratories and fully characterized according to the literature procedure . Millipo3 membrane. The PVC-based solvent polymeric membranes were prepared according to the previously reported procedures [4C1 for sensor A1 and sensor C1, respectively. The sensor A1 and C1 membrane potential was registered against the internal, homemade Ag/AgCl reference electrode.The potentiometric E-tongue system was composed of eight sensors with three different types of sensing membranes: PVC-based solvent polymeric membranes doped with Mn(TPP)Cl (sensor A1) and nonactin (sensor C1) ionophores, chalcogenide glass membranes doped with different metal salts , and sensor A7 with polycrystalline LaFocedures ,43. For 3 membrane had solid Cu-wire/Ag-paste solid contacts and were purchased from Sensor Systems . The potentials of E-tongue system sensors were measured versus a saturated calomel reference electrode , in a standard two-electrode configuration cell. Potentiometric measurements were performed with a LiquiLab  high-impedance analog-to-digital potentiometer. Prior to measurements, the sensors were soaked in 0.01 mol/L NaCl aqueous solution for at least 24 h.Chalcogenide glass sensors and sensor A7 with a polycrystalline LaFThe quantity of samples KET–LYS P1 and KET–LYS P2 corresponded to the standard dosage of administration of commercial KLS (40 mg). This amount of sample was dissolved in 20 mL of distilled water.All analyses were performed in analytical triplicate for all the above time conditions. The pH value and electrical conductivity of the t24 h and t48 h solutions were also measured. The samples were stored in closed containers at room temperature (+22 °C) during the study period.For the pharmacokinetics studies, Sprague Dawley male rats (body weights 250–275 g at the time of the treatment) were used. The animals were originally supplied by Harlan, Italy. The animals were acclimatized to local housing conditions for approximately 5 days.The animals were housed in a single, exclusive room, air-conditioned to provide a minimum of 15 air changes/h. The environmental controls were set to maintain temperature within 22 °C and relative humidity within the range 50–60% with an approximate 12 h light and 12 h dark cycle that was controlled automatically. Food (Mucedola Standard GLP diet) and water were available ad libitum throughout the study. All animals were weighed on the day of each treatment. Clinical signs were monitored at regular intervals throughout the study in order to assess any reaction to treatment. Each animal was uniquely identified with a colored spray on the back before the experiment.®). To perform this, capsules were individually filled and weighed up with the substances and then filled with rice starch up to about 20 mg, weighed again, and closed. After administration, blood (approximately 60–80 µL) was sampled from tail vein at the following timepoints: 15 min, 30 min, 1 h, 2 h, 4 h, 6 h, 8 h, 24 h, and 48 h. Blood samples were collected in heparinized Eppendorf tubes (Heparin Vister 5000 UI/mL), gently mixed, and placed immediately on ice; then, Eppendorf tubes were centrifuged , and the resulted plasma was collected and transferred to uniquely labeled Eppendorf tubes, before being frozen at −20°C till the HPLC–MS analysis.The compounds were administered at a dose of 3.5 mg/kg as KET free acid in gelatin capsules ). For pharmacokinetics experiments, data were expressed as the mean ± standard error of the mean (SEM). Multiple statistical comparisons between groups were performed by two-tailed unpaired Student’s max in vivo of KET–LYS P2 suggest potential advantages of this new form for fast-acting formulations of the drug. Nevertheless, it should be considered that this new polymorph may exhibit a more bitter taste and a lower AUC compared to the commercially available KLS form, and this should prompt the design of specific formulation studies to hypothesize different potential formulations (faster release) and coating or flavoring processes, according to the specific characteristics of the starting API material.In this study, we synthesized and characterized, for the first time, two different polymorphic forms of KLS, a cocrystal, KET–LYS P1, and a salt, KET–LYS P2. Through advanced and sophisticated analyses, we were able to undoubtedly define the structural characteristics of the two polymorphs and compare their physicochemical characteristics, in terms of dissolution rate and taste, and pharmacokinetic profiles in vivo. What emerged is that, from a structural point of view, the commercial KLS, which was introduced in the market as a KET salt, should instead be more appropriately defined as a cocrystal (KET–LYS P1), and that the newly identified salt KET–LYS P2 has significantly different chemical and pharmacokinetic characteristics compared to KET–LYS P1. The faster dissolution rate and reduced TThe present study advances our knowledge regarding the solid-state characteristics of KLS and gives a comprehensive view of its polymorphic diversity; while doing this, it led to the discovery of a new polymorph of KLS, KET–LYS P2, thus opening the way for the development of a new potential KET–LYS polymorph drug, the pharmacological and pharmacokinetic characteristics of which will be further investigated to define the appropriate formulation and the conditions that would most benefit from the treatment with this drug.


Malignant tumors remain the health problem of highest concern among people worldwide due to its high mortality and recurrence. Lung, gastric, liver, colon, and breast cancers are among the top five malignant tumors in terms of morbidity and mortality. In cancer biology, aberrant signaling pathway regulation is a prevalent theme that drives the generation, metastasis, invasion, and other processes of all malignant tumors. The Wnt/β-catenin, PI3K/AKT/mTOR, Notch and NF-kB pathways are widely concerned and signal crosstalks exist in the five solid tumors. This review provides an innovative summary of the recent progress in research on these signaling pathways, the underlying mechanism of the molecules involved in these pathways, and the important role of some miRNAs in tumor-related signaling pathways. It also presents a brief review of the antitumor molecular drugs that target these signaling pathways. This review may provide a theoretical basis for the study of the molecular biological mechanism of malignant tumors and vital information for the development of new treatment strategies with a focus on efficacy and the reduction of side effects. Malignant tumors are a public health problem of worldwide concern and a leading cause of death for people in the world. According to a 2017 report by the American Cancer Society, lung cancer (LC), gastric cancer (GC), liver cancer, colorectal cancer, and breast cancer (BC) remain the top five causes of cancer deaths . The higThe numerous studies that have been performed in recent decades suggest that signaling pathways are implicated in the development of cancer. Abnormal pathways drive the generation, metastasis, invasion, and other processes of all malignant tumors. Among the five tumors that received the most attention and emerged as crosstalk pathways were Wnt/β-catenin pathway, PI3K/AKT/mTOR, Notch and NF-kB pathway . Four siMicroRNAs are a group of very conservative small single-stranded noncoding RNA molecules that, by pairing with complementary RNA molecules, negatively regulate the expression patterns of different genes at the post-transcriptional or translational level, thereby inhibiting translation through RNA degradation. MiRNAs participate in many cellular processes, such as transcription, cell growth, proliferation, inflammation, cell movement, differentiation, and apoptosis, as well as in the cell cycle . Mirna cThis review provides an innovative summary of several signaling pathways that have been associated with the occurrence and progression of malignant tumors with high morbidity and mortality worldwide in recent years . NotablyDrosophila gene Wingless and the mouse proto-oncogene Int1  pathway. The β-catenin-dependent signaling pathway is initiated by the binding of the Wnt ligand to lipoprotein receptor-related protein (LRP)-5/6 receptors, which activate disheveled (DVL) and in turn induce the recruitment of the receptor axis inhibition protein Axin, glycogen synthase kinase-3β (GSK-3β), casein kinase 1 (CK1), and adenomatous polyposis Escherichia coli (APC) in the form of a complex   . PLC incinase-II . These pinase-II   gene codes for the SOX2 transcription factor which is expressed in the main histological types of LC  10 and sonic hedgehog and epithelial–mesenchymal transition (EMT). Matrix metalloproteinases are the targets of canonical and noncanonical Wnt signaling pathways and are critical for tissue remodeling; they are increased in spread tumors  intervention therapy . In a Hewith HCC . Liu thoenhanced . These din vitro . Thus, min vitro .APC and β-catenin protein. Gene mutations in β-catenin, GSK-3β, Axin, or APC leads to abnormal activation of the Wnt/β-catenin pathway, and simultaneous Wnt overexpression causes abnormal activation of this pathway  1, zinc finger E-box binding homeobox 1 and SNAI2. This action therefore leads to metastasis and invasiveness.Wnt/β-catenin pathway dysregulation also occurs frequently in CRC. The abnormal activation of this pathway is related to cell proliferation, invasion behavior, and drug resistance, suggesting the potential value of targeting Wnt/β-catenin pathway as an intervention method for CRC. Most CRC patients have at least one mutation in a Wnt signaling cascade gene such as  pathway . The WntAbnormal expression of miRNA is related to the disorder of cancer-related signaling pathways, Wnt/β-catenin pathway is included. Further research showed that Smad7 is a protein necessary for nuclear accumulation of β-catenin. MiR-93 inhibits the Wnt/β-catenin pathway by targeting Smad7 . SimilarThe PI3K enzyme mainly participates in the phosphorylation of the inositol lipid membrane and mediates signal transduction . Two recThe therapeutic targeting of the PI3K/AKT/mTOR pathway has led to the advancement of some different kinds of drugs, PI3K and AKT inhibitors, as well as catalytic and allosteric mTOR kinase inhibitors are included. For example, the mTOR inhibitors Temsiro-Limus and Everolimus and the PI3K inhibitors Idelalisib and Copanlisib have been accepted by the FDA for Clinical treatment of patients with cancer . HoweverDysregulated PI3K/AKT/mTOR pathway also contributes to LC initiation and progression, and eukaryotic translation initiation factor 4E (eIF4E), one of its downstream effectors , has beein vitro and in vivo have demonstrated the antiproliferative and antitumor effects of rapamycin . Aberrant PI3K pathway activation is mediated by mechanisms including altered genes for AKT and PIK3CA, decreased upstream RTK,  10q23.3 . The Akttastatic .Consequently, four major kinds of drugs that target the PI3K/AKT/mTOR pathway have been identified : PI3K, ARecent life science studies have proposed that aberrant PI3K/AKT/mTOR signaling pathway activation is the key to the shortened life cycle of cancer patients and that aberrant activation of this pathway is a vital mechanism of resistance to targeted therapies . It is eApamycin was the first available mTOR inhibitor for BC therapy and was originally developed as an immunosuppressant for transplant recipients. Researchers classified the new generation of mTOR inhibitors into PI3K/mTOR inhibitors and mTORC1/2 inhibitors. Besides, more and more compounds that block the upstream of the mTOR pathway have been developed. These compounds include AKT and PI3K inhibitors . LY29400In cell lines, miR-758-3P repair inhibits cell proliferation, migration, and invasion. Jiang and his colleagues showed that miR-758-3P significantly down-regulates the expression of murine double minute 2 (MDM2) and mTOR while up-regulating the expression of p53, AKT, and PRAS40 . In addiJagged-1, Jagged-2, DLL-1, DLL-3, and DLL-4) and four receptors   and transfer to the nucleus  . The NotNotch-4) . Total tNotch-4) . First,  nucleus . CSL is  nucleus  , RelB, Rel (c-Rel), NF-κB1 (p50/p105), and NF-κB2 (p52/p100) . There aNF-κB is an activator of antiapoptotic genes. It could also monitor tumor angiogenesis and metastatic invasiveness, the signaling pathways that mediate its activation have shed new light on chemotherapy and prevention of cancer .NF-κB is related to angiogenesis and EMT formation in CRC and controls the CRC cells to migrate and invade. Angiogenesis represents the occurrence of cancer. Vascular endothelial growth factor (VEGF) drives the formation of some angiogenesis regulators, which include the angiogenesis regulator cyclooxygenase-2, CXCL1, CXCL8, and IL-8 in the NF-κB pathway. Monoclonal antibodies against VEGF are widely exploited for CRC therapy. VEGF is also inducible under HIF . The HIFAccording to the report, Approximately 760 natural and synthetic molecular inhibitors of the NF-κB pathway have been developed . A wide In addition to the above four signaling pathways, there are other important signaling pathways in the process of tumor development, such as p53 signaling pathway, Hippo signaling pathway, Hedgehog pathway, TGF-β pathway and JAK-STAT pathway. P53 signaling pathway is a typical pathway of abnormal disorder in tumors. Due to the complexity of p53 pathway, imperfect drug design methods and other restrictive conditions. Although some drugs targeting p53 have entered the clinical stage, including APG-115 and UBX-0101, no drugs are on the market. Hippo signaling pathway is closely related to tumor immunity. YAP in the Hippo pathway is highly expressed and functions in the generation of regulatory T cells and plays a certain role in anti-tumor immunosuppression. On the other hand, the Hippo pathway can regulate the immune checkpoint molecule PD-L1, thereby enhancing the body’s immunity . InhibitIn addition to miRNAs, noncoding RNAs, such as long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), have also attracted extensive attention due to their important regulatory roles in tumor development involving in Wnt/β-catenin, PI3K/AKT/mTOR, Notch and NF-KB pathways . LncRNAsin vivo and in vitro. CircRNA APLP2 can activate Notch signaling pathway in CRC by targeting miR 101-3p to promote proliferation and metastasis (CircRNAs also plays an important role in the occurrence, migration and invasion of malignant tumors by affecting Wnt/β-catenin, PI3K/AKT/mTOR and Notch pathways. In HCC, circRNA DEND4C enhances the expression of TCF4 through activating Wnt/β-catenin pathway and regulates the malignant behavior of HCC cells. Overexpression of circ0067934 increases FZD5 expression by activating miR-1324, which leads to Wnt/β-catenin pathway is activated. There is evidence that circ_001946 up-regulates SIRT1 expression, SIRT1 exerts promotive effects on Wnt/β-catenin cascade by targeting miR-135a-5p promotes the proliferation of LC cells. Circ_0006427 up regulates the expression of DKK1 and Wnt/β-catenin signaling pathway is inactivated . Overexptastasis . In viewCurrently, scientists have designed an increasing number of drugs targeting signaling molecules. In clinical practice, molecular targeted therapy does reduce the toxic side effects of drugs to greatly improve the quality of patient survival, and can substantially prolong the survival time of patients, which brings new hope to many patients with cancer . But tarIn fact humans have an extremely limited knowledge of signaling pathways. At present, in the internet age, big data is considered to be a powerful tool to broaden and deepen people’s understanding of targeted drugs. We guess, if gene sequences of every cancer patient in the world and the therapeutic effects by drugs targeting one or more genes mutations are documented and shared, for patients with the same genetic mutation, the key genetic mutations will be more quickly identified and the best treatment to the patient will be formulated. In addition, by big data, scientists could further understand the molecular mechanisms in the genesis and development of tumors, which is very helpful for developing a new generation of targeted drugs. Thus, it seems a powerful measure for pushing molecular targeting research, which has shown great promise but has always been hard to see in practice. At that, as the cost of gene sequencing drops, more cancer patients are willing to have their genes sequenced, the explosion of genomic data makes this idea a reality.