Bos grunniens) is a unique breed living on the Qinghai–Tibet Plateau and its surrounding areas, providing locals with a variety of vital means of living and production. However, the yak has poor sexual maturity and low fertility. High-quality mature oocytes are the basis of animal breeding technology. Recently, in vitro culturing of oocytes and embryo engineering technology have been applied to yak breeding. However, compared to those observed in vivo, the maturation rate and developmental capacity of in vitro oocytes are still low, which severely limits the application of in vitro fertilization and embryo production in yaks. This review summarizes the endogenous and exogenous factors affecting the in vitro maturation (IVM) and developmental ability of yak oocytes reported in recent years and provides a theoretical basis for obtaining high-quality oocytes for in vitro fertilization and embryo production in yaks.The yak ( The yak is a unique breed that lives in the Qinghai–Tibet Plateau and offers various necessities for local people’s survival and production. However, the reproductive performance of the yak is low. Yaks are generally calved every other year, with one in two years or two in three years, and the average annual reproductive rate for female yaks is less than 60% ,2. The yIn order to improve the reproductive performance of yaks, assisted reproductive procedures such as in vitro fertilization (IVF), somatic cell nuclear transfer (SCNT), and embryo transfer (ET) have been widely used in yak breeding ,7,8,9. TA series of drastic morphological and molecular changes occur during oocyte maturation, such as the change in transcription, the repositioning of organelles, and the storage and utilization of maternal materials. Therefore, oocyte maturation is a complex process influenced by several internal and external influences ,15,16. DOocyte quality and maturation rate vary depending on follicle type and morphology. Liu Ben et al. found no noticeable difference in the cleavage rates of embryos after fertilization between oocytes from pre-estrus calves and adult yaks. However, the blastocyst rate of fertilized embryos from pre-estrus calves was lower than that those from adult yaks . Yan PinAccording to the criteria established by Wang Yuheng et al. for the yak oocyte classification, yak COCs were divided into four grades . The resCENPF, TOP2A, MIS18BP1, FST, and INHA were highly expressed in yak oocytes. The FST and TOP2A genes could be considered as the molecular features of yak oocytes within primordial follicles. They also discovered that the yak oocytes regulated the other types of ovarian cells primarily via the interaction between the ligands FAM3, INHA, and JAG1 with their corresponding receptors. However, the endothelial, epithelial, and granulosa cells regulated the oocytes principally via the BMP family [The maturation and development of oocytes are complicated processes involving the regulation of various genes and proteins ,24. DynaP family . Lan Daoliang et al. sequenced the transcriptome of MII stage yak oocytes and analyzed the primary biological functions and signaling pathways involved in the differentially expressed genes. KEGG analysis revealed that actin cytoskeleton regulation was the most significantly enriched pathway. the cell cycle, tight junction, adhesion patch, MAPK signaling, Wnt signaling, and endocytosis pathways were effectively enriched. The results suggested that yak oocyte maturation involved a series of dynamic processes that was highly spatially and temporally regulated . MoreoveZhao Yanling et al. applied the liquid chromatography tandem mass spectrometry (LC-MS-MS) technique to construct the protein expression profiles of yak oocytes at the GV stage. They identified 550 proteins, of which MVP, PDIA3, HSP90B1, HSPA5, and BSA were the proteins with the highest abundance expression in yak oocytes. GO analysis revealed that the proteins related to cell components were mainly concentrated in the cytoplasm (125 proteins). In the enrichment analysis related to molecular function, the number of proteins that perform the function of poly A binding RNA was the highest (54 proteins), In enrichment analyses related to biological processes, the number of proteins involved in the negative regulatory process of endopeptidase activity was the highest (26 proteins). According to KEGG analysis, the representative pathways include the complement system, ribosome metabolism, phosphatidylinositol 3 kinase-serine/threonine kinase (PI3K-Akt) signaling, and carbon metabolism pathways. Additionally, protein network analysis revealed that ALB, GAPDH, HSP90AB1, ACLY, ACTA1, HSPA8, ACTG1, UBA52, PLG, and EEF2 were the key nodes of protein–protein interactions (PPI) in oocytes . Huang YEpigenetic regulation is a kind of regulation of gene expression by changing non-gene sequence, mainly including DNA methylation, histone modification , and regulation of non-coding RNA, etc., which is a hot research topic in different fields of biology ,33. The DNMT3a and DNMT3b. It is well known that the major function of the methyltransferases DNMT3a and DNMT3b is to establish DNA methylation, and the methyltransferases DNMT1 play a major role in the subsequent maintenance of genome-wide methylation patterns [DNMT1 and DNMT3a, and attenuated the DNA methylation [During mammalian development, DNA methylation plays a crucial role in genomic imprinting, transposon silencing, X-chromosome inactivation, and tissue-specific gene expression regulation . Li Qin patterns ,36,37. Thylation .DNMT3a and ten-eleven translocation enzyme (TET3) at the 2-cell, 4-cell, 8-cell, and morula stages of yak embryos. At the blastocyst stage, the promoter region of pluripotency gene NANOG exhibited moderate methylation. Addition of 50 µg/mL AA decreased the methylation level of the NANOG promoter, and significantly increased the mRNA transcript abundance of NANOG. These results suggested that 50 µg/mL AA might regulate the formation of yak blastocysts via regulating the methylation and expression of NANOG [In addition, adding 50 µg/mL AA increased the mRNA transcript abundance of of NANOG ,39.Histone modification refers to altering the interaction of histones with DNA by adding or removing specific chemical markers on histones, thereby affecting the gene transcription regulation and the occurrence of other cellular processes ,41. SeveKDM1A mRNA expression decreased and then increased during IVM of yak oocytes, with the MI stage exhibiting the lowest KDM1A expression. After repressing the expression of KDM1A in yak oocytes by adding GSK-KDM1A, the specific inhibitor of KDM1A, the cumulus cell expansion, the first polar body excretion rate, and the cleavage rate of yak oocytes were significantly decreased. The expressions of OCT4 and SOX2 were significantly up-regulated after the treatment. The results suggested that KDM1A was involved in regulating the meiosis of yak oocytes, possibly influencing oocyte maturation and embryo development [KDM1A is a histone demethylase with specificity for H3K4me2/me1 demethylation . Han Jieelopment ,48.KDM2 was dynamically expressed during oocyte meiosis. Its mRNA/protein expression level was significantly higher in the MI stage than in the GV and MII stages. Moreover, adding butyrazide, a specific inhibitor of KDM2, to the in vitro maturation medium reduced oocyte maturation but increased the cleavage and blastocyst rates, suggesting that KDM2 may play opposing roles in regulating oocyte maturation and embryo development in yaks [KDM2 is a demethylase with a JmjC domain . Cai Wen in yaks .SIRT1, FOXO3a, and SOD2 mRNA expressions and down-regulating BAX mRNA expression [SIRT1 is a class-III nicotine adenine dinucleotide (NAD)-dependent histone deacetylases (HDACs) that have been proven to be essential for delaying oocyte aging and promoting oocyte maturation in mice ,52. Xionpression .miRNAs are a class of small non-coding RNAs that play a regulatory role at the post-transcriptional level by recognizing binding sites in the untranslated regions of target genes, leading to mRNA degradation or protein translation inhibition ,55. ReceBCL2, CCND1, DNMT1, and BMP7 were analyzed in GV oocytes, MII oocytes, and preimplantation embryos. The results showed that BCL2, CCND1, and BMP7 were expressed in the opposite direction to miR-16 and miR-342, while DNMT1 had no defined expression pattern throughout the developmental stages [Xiong Xianrong et al. sequenced miRNAs in yak GV and MII stage oocytes and obtained 801 and 1018 known miRNAs, respectively. Seventy-five of these miRNAs were significantly differentially expressed, with 47 miRNAs exhibiting up-regulated expression and 28 miRNAs exhibiting down-regulated expression in MII stage oocytes compared to the GV stage. Moreover, they analyzed the expression patterns of miR-16 and miR-342 in GV and MII oocytes and preimplantation embryos . The results revealed that miR-16 was highly expressed in GV oocytes but significantly decreased from the MII stage to the blastocyst stage. However, miR-342 expression was significantly higher in MII oocytes than in GV oocytes and significantly decreased from the two-cell embryo to the blastocyst stage. Subsequently, the miR-16 and miR-342 potential target gene expressions, such as l stages .DNMT1 expression and significantly inhibited oocyte meiotic maturation by targeting the 3′-untranslated regions (UTR) of DNMT1 [Xiong Xianrong et al. studied the role of miR-342-3p in the meiotic maturation of yak oocytes. They discovered that miR-342-3p inhibitor effectively up-regulated of DNMT1 GPR50 knockdown and overexpression on yak oocytes. The results indicated that the GPR50 knockdown significantly reduced the oocyte maturation rate and the polarbody excretion rate, while GPR50 overexpression exerted no significant influence on the excretion rate and maturity level of the yak oocytes, suggesting that GPR50 might play a crucial role in yak oocyte maturation in vitro [GPR50 is an orphan G protein-coupled receptor on the X chromosome . Previouin vitro .The effects of some endogenous factors on yak oocytes and the possible mechanisms are shown in Growth factors are a class of peptides that regulate multiple effects, such as cell growth and other cellular functions, by binding to specific, high-affinity cell membrane receptors. They play critical roles in resuming oocyte meiosis, oocyte maturation, and follicular development ,65. MoreBAX and the promotion of EGF on the expression of anti-apoptosis genes BI-1 [Several important growth factors, such as epidermal growth factor (EGF), insulin-like growth factor I (IGF-1), fibroblast growth factor 10 (FGF10), and leukemia inhibitory factor (LIF) are essential for oocyte maturation and embryo development. EGF can promote cell proliferation, differentiation, and mammalian oocyte maturation ,69,70,71nes BI-1 .IGF-1 belongs to the insulin-like growth factor family , which iCD9, CD81, DNMT1 and DNMT3B expressions in COCs to optimize sperm–egg interaction and DNA methylation during fertilization [FGF10 is a paracrine fibroblast growth factor involved in numerous biological processes, including embryonic development, cell growth, morphogenesis, tissue repair, tumor growth, and invasion ,78,79,80lization .BCL2, CAPASE3, SURVIVIN, SOD2 and GPX4 in yak oocytes. Furthermore, blastocysts formed from 50 ng/mL LIF-treated oocytes had higher total cell numbers and lower apoptosis rates than the control group [LIF is a potent cytokine in the IL-6 family of cytokines . Zhao Tiol group .ROS are small molecules produced by biological aerobic metabolism, an include superoxide, peroxide, and oxygen radicals . ReactivSTRA8, RARA, and RXRA were highest in the MII stage compared with those in the GV and MI stages under the treatment of 2 μM Vitamin A. Additionally, the mRNA expressions of several genes in the typical signaling pathway, including RXRA, RARA, and STRA8, were significantly higher than those of MEK and MEK1, which were node genes of the atypical signaling pathway. These results suggested that RA was mainly dependent on the typical signaling pathway for the yak oocyte development in vitro [Vitamin A is an indispensable nutrient that regulates physiological processes such as reproduction, embryonic development, vision, growth, cell differentiation, and proliferation . Vitaminin vitro ,94.Vitamin C (ascorbic acid) is a strong water-soluble antioxidant that can catalyze the reduction of oxidized glutathione to reduced glutathione . Exposur−9 M melatonin could significantly increase the oocyte maturation rate, IVF embryo cleavage and blastocysts rates, and GSH content of oocytes and blastocysts. Reductions of ROS levels, mitochondrial protein extent, DNA damage, and cell apoptosis were observed after melatonin treatment. Additionally, 10−9 M melatonin repaired the spindle mismatch and chromosomal abnormalities caused by oxidative stress. The results suggested that 10−9 M melatonin addition could alleviate oxidative stress during the IVM of oocytes and improve the oocyte maturation rate and the developmental ability of subsequent embryos [The addition of antioxidants to oocytes and embryos during in vitro culture is necessary to maintain normal levels of intracellular ROS. Melatonin is a natural endogenous indole hormone produced by the mammalian pineal gland . Since m embryos ,99.Li Ruizhe compared the effects of antioxidants, including melatonin, Vitamin C, resveratrol, and cysteamine, on the maturation and developmental capacity of yak oocytes in vitro. The results showed that adding melatonin to the oocyte maturation solution significantly increased the maturation rate and the proportion of mitochondrial homogenous distribution of yak oocytes. The oocyte cleavage rate of in-vitro-fertilized embryos also increased. Among these three antioxidants, cysteamine had the strongest effect on the increase of GSH content in oocytes .2+ inducing the up-regulation of Zn transporters 3 (ZnT3), Zrt, and Irt-like protein 14 (ZiP14) expressions in yak oocytes [Solute-linked carrier (SLC30A) and SLC39A family members, including SCL30A3, SLC30A6, SCL30A9, SLC39A6 and SLC39A14 in yak mature oocytes, facilitating the cleavage of the fertilized ovum and blastocyst formation [SOD1, CAT, TXN1, and PRD1) expression levels, and also up-regulating the cumulus cell expansion related genes (PTX3 and TSG6) in the oocyte [Zinc (Zn) is an essential trace element in mammals that plays an important role in cell growth, proliferation, division, and immunity ,102. Xio oocytes . Hu Jiajormation . Feng Yue oocyte . 2+ concentration are closely related to regulating physiological functions by affecting signal transduction [2+ at 0.24 mM in yak oocyte culture medium significantly increased the oocyte maturation rate in vitro. The mechanism was that Ca2+ activated the activity of calmodulin-dependent protein kinaseII (CaMKII), increased GSH content, and decreased the ROS level in the oocyte. Ca2+ up-regulated the expressions of BCL-2, EGF, EGFR, and C-FOS, whereas it down-regulated BAX expression [Calcium (Ca) is an important second messenger in cells, and the changes in Casduction . Chen depression .GPX4, SEPP1, RPL22, and CCND1 in oocytes and cumulus cells [Selenium (Se) is an essential trace element for reproduction, immunity, antioxidant systems, embryonic growth, and other physiological functions ,109,110.us cells .PKA1 and CY3 mRNA expression levels. It also significantly decreased the PDE3A mRNA expression level in yak COCs and blastocysts [Cyclic adenosine monophosphate (cAMP) is the first discovered second messenger. cAMP can regulate the various target genes’ transcription, primarily via protein kinase A (PKA) and its downstream effectors . cAMP plstocysts . SOD2, anti-apoptotic gene BCL-2, and development-related genes GDF9, EGFR, and ZAR1, and significantly down-regulated the mRNA expression of the pro-apoptotic gene BAX [Roscovitine and C-type natriuretic peptide (CNP) are two meiotic arrest factors promoting yak oocyte maturation in vitro. Roscovitine is a member of the 2,6,9-trisubstituted purine family and has a structure similar to ATP. Therefore, roscovitine interacts with amino acids in the ATP-binding pocket of the catalytic domain of some Cyclin-dependent kinases (CDK), preventing ATP from binding to CDK, inhibiting CDK activity, and ultimately blocking the cell cycle . Pretreagene BAX . NPR2, anti-apoptotic gene BCL-2, and growth differentiation factor GDF9 in oocytes and blastocysts. CNP suppressed the EGF and its receptor EGFR gene expressions in oocytes while promoting EGF, EGFR, and DNMT1 expressions in blastocysts and repressing the expression of pro-apoptotic gene BAX in blastocysts [CNP is a natural determinant of meiotic arrest that can maintain gap junction activity and support the key gene expressions essential for oocyte development . Jing Tistocysts .Current studies on mouse, pig, and buffalo oocytes indicate that glucose is an important energy source for oocyte maturation ,126,127.EGF and EGFR mRNA expression levels, and it might inhibit oocyte apoptosis by increasing antiapoptotic gene BCL-2 expression while reducing pro-apoptotic gene BAX expression [Xiao Xiao et al. demonstrated that supplementing IVM medium with 5 μg/mL FSH and 50 IU/mL LH improved the developmental ability of yak oocytes after in vitro fertilization (IVF) . He Hongpression . −4 mM endogenous 17β-estradiol to the IVM medium of COCs could increase the cumulus expansion and subsequent oocyte development. These might result from increasing the expressions of cumulus-expansion-related factors  and the oocyte-secreted factors  [Estradiol (E2) is the most active and predominant maternal estrogen during pregnancy . A suppld BMP15) . −6 mol/L) RFRP-3 inhibited yak oocyte proliferation, induced oocyte apoptosis, and decreased 17β-estradiol and progesterone (P4) concentrations. RFRP-3 dose-dependently elevated the expression of apoptosis markers (Caspase and Bax), whereas the expression levels of steroidogenesis-related factors  were down-regulated in a dose-dependent manner [Rfamide-related peptides 3 (RFRP-3), a structural and functional homolog of gonadotropin-inhibiting hormone (GnIH), has been proposed as a new breeding inhibitory neurohormonal peptide that plays a crucial role in the reproductive axis across various species ,142. Xiot manner .Cytochrome P450arom (CYP19A1) is the key enzyme for gonadal hormone synthesis in most animals . CYP19A1−7 mol/L PFA significantly increased the maturation, cleavage, and blastocyst rates of yak oocytes by regulating BAX, BCL-2, EGF, EGFR, C-FOS, OCT-4, and NANOG gene expressions [PAF is an acetylated glycerol signaling phospholipid important physiological regulator in reproduction . PAF exeressions ,149.The effects of some exogenous factors on yak oocytes and the possible mechanisms are shown in Pang Bo et al. investigated the effects of ovarian preservation temperature and the culture methods on the maturation rate of yak oocytes in vitro, and the results showed that preserving the ovaries from 20 °C to 25 °C could improve the oocyte maturation rate in vitro . Ma Li e2) is vital to maintain and complete oocyte maturation and embryonic development. Changes in oxygen concentration during oocyte maturation in vitro affect nuclear DNA methylation, intracellular reactive oxygen species (ROS) levels, and cellular aging [Oxygen (Oar aging ,152. Lowar aging ,154. Sevar aging ,156,157.HIF-1α expression. HIF-1α subsequently increased the BCL-2 mRNA expression and decreased the BAX mRNA expression in yak COCs and blastocysts, whereas CDX2, POU5F1, SOX2, and NANOG mRNA expressions in blastocysts were significantly increased [He Honghong et al. investigated the development of yak oocytes and preimplantation embryos under low oxygen concentrations. The results showed that 5% oxygen facilitated yak oocyte maturation in vitro and significantly increased the cleavage and blastocyst rates of the subsequent PA embryos. The blastocyst rate of IVM embryos was significantly increased at the same oxygen concentration. The proper mechanism might be that 5% oxygen up-regulated ncreased ,159,160.WDR26, MKP2K1, MAPK1, TICRR, WAC, EIF4ENIF1, ODC1, CHAMP1, MKI67, MCM10, SFMBT1, PBRM1, KAT8, IQGAP2, EPS8, and RANBP9 genes. The genes up-regulated in the 20% oxygen concentration group, including ACAT1, ATP5MF, AURKAIP1, COX6A1, NDUFA10, NDUFA11, NDUFS7, LYRM7, UQCR10, EIF1AX, RPL13, RPL13A, RPL34, RPLP2, GSTA2, QARS, NOSTRIN, SH3BGRL3, TIMP1, S100A11, and PTX3, were primarily involved in energy metabolism, protein synthesis, redox homeostasis, and oocyte regulation [2 increased the oocyte maturation rate and GSH content, decreased the oocyte ROS level, and improved the quality of PA and IVF blastocysts. The effects were achieved by decreasing the expressions of the antioxidant genes CAT and GPX1, increasing the expression of the metabolism-related gene LDHA, and embryo development-related genes CDX2 and OCT4 in yak IVF blastocysts [Li Ruizhe compared the expression differences in the transcriptome of yak oocytes at 5% and 20% oxygen concentrations and revealed that the genes up-regulated in the 5% group were mainly involved in hypoxia response, the cell cycle, chromatin conformation and remodeling, and the cytoskeleton, including the stocysts .Various endogenous, exogenous and environmental factors that regulate yak oocyte and embryo development in vitro have also been reported to play important roles in regulating bovine oocyte and embryo development ,180,181.However, the concentration or molecular mechanism of these factors to exert their optimal effects on oocyte and embryo development in bovines are somewhat different from those in yaks. For example, the optimal concentrations of FGF10 and LIF in promoting oocyte and embryo development in yaks were 5 ng/mL and 50 ng/mL ,84, respThe number of factors that regulate oocyte and embryo development in yaks is still far less than that in traditional domestic animals, such as bovines and pigs. Furthermore, current studies mainly focus on the effects of different factors in the maturation and developmental competence of yak oocytes in vitro; little is known about the related molecular mechanisms. As the yak is an atypical animal living on the plateau, the difficulty of sample collection brought great obstacles to the preparation of experimental materials. In addition, the individual differences between different yaks greatly interfere with the accuracy of experimental results. These problems need to be solved urgently in the field of yak breeding in the future.High-quality oocytes are the basis of the application of assisted reproductive technology in livestock breeding. The various factors that influence the maturation and developmental competence of yak oocytes in vitro summarized here will help researchers to further optimize the conditions of IVM of yak oocytes in vitro, thus promoting the improvement of yak breeding and the development of animal husbandry in the plateau area.


Chronic tissue inflammation often results in fibrosis characterized by the accumulation of extracellular matrix components remodeling normal tissue architecture and function. Recent studies have suggested common immune mechanisms despite the complexity of the interactions between tissue-specific fibroblasts, macrophages, and distinct immune cell populations that mediate fibrosis in various tissues. Natural killer T (NKT) cells recognizing lipid antigens bound to CD1d molecules have been shown to play an important role in chronic inflammation and fibrosis. Here we review recent data in both experimental models and in humans that suggest a key role of type 1 invariant NKT (iNKT) cell activation in the progression of inflammatory cascades leading to recruitment of neutrophils and activation of the inflammasome, macrophages, fibroblasts, and, ultimately, fibrosis. Emerging evidence suggests that iNKT-associated mechanisms contribute to type 1, type 2 and type 3 immune pathways mediating tissue fibrosis, including idiopathic pulmonary fibrosis (IPF). Thus, targeting a pathway upstream of these immune mechanisms, such as the inhibition of iNKT activation, may be important in modulating various fibrotic conditions. Fibrosis is characterized by the deposition of extracellular matrix components, such as collagen and fibronectin. The fibrotic process can affect different tissues and represents an ultimate outcome of chronic inflammatory diseases . Althoug+ (mouse) or CD161+/CD56+ (human) and share common features in mice and in humans (NKT cells are a group of innate-like T cells expressing NK cell receptors and antigen T cell receptors (TCR) that recognize lipid antigens presented in the context of a class I MHC-like, non-polymorphic molecule CD1d –10. NKT n humans –15, theyn humans . iNKT ann humans , 19. Morn humans , 21. A pn humans –24 and w+ helper T subsets, and accordingly affect distinct type 1, type 2 and type 3 immune pathways, respectively , and αGalCer/CD1d-tetramers can be used for the monitoring iNKT cells in both mice and humans , 32. Mur•αGalCer is a high affinity binder for CD1d and TCR and acts like a super antigen for iNKT cells that can activate most iNKT cells in a non-physiological manner. In contrast, self-lipids recognized by iNKT cells, are generally low affinity binders for CD1d or TCR, do not behave like αGalCer . αGalCer+CD56+ cells as a marker for NKT cells. It is clear from several studies that CD3+CD56+ cells are comprised of population of unconventional T cells, including iNKT cells, MAIT cells, γδ T cells, type 2 NKT cells and a subset of CD8+ T cells  and fibrosis staging in patients (+CD3+) that are not specific for NKT cells and may include other T cell populations as described in + T cells in both mice -induced fibrosis, ischemia reperfusion injury, Con A-induced hepatitis, primary biliary cirrhosis, Lieber-DeCarli liquid alcohol diet, and choline-deficient amino acid enriched (CDAA) diet, iNKT cells become activated and are pathogenic , 47, 48.liorated , 47, 51.liorated –54. It iliorated . It is llunteers , 40, 56.oth mice  and in hoth mice –60. Accor tissue , 57. It r tissue , 47. Amor tissue . Consistr tissue , 57. Oner tissue .+NKT cells in bronchial alveolar lavage (BAL) fluid relative to healthy volunteers also correlates with increased alveolar macrophages, a predictive marker of disease progression in IPF patients. Collectively, data in experimental models as well as in NASH, alcoholic liver disease, and IPF patients implicate iNKT cells in the pathogenesis of fibrosis in humans.Similarly, in the bleomycin-induced lung injury model of pulmonary fibrosis, inhibition or skewed activation of iNKT cells by sulfatide or αGalCer, respectively, leads to inhibition of vimentin concentration in lung tissues as well as reduction of fibrosis-promoting cytokines, including TGF-β, IL-5, and IL-13 , 49, 62.-/- mice with decreases in IL-4, IL-5, and IL-13 cytokines in BAL fluid  are co-clustered with these SAMs in the fibrotic tissue. Accordingly, in murine models, blockade of GM-CSF, IL-17A and TGF-β significantly inhibited the expansion of these FABP5+ SAMs and hepatic and pulmonary fibrosis. These studies indicate that IL-17A, GM-CSF and TGF-β can collaboratively induce monocytes-to-FABP5+ SAM differentiation and promote pathogenic collagen deposition by mesenchymal cells in IPF and NASH patients  iNKT subsets, NKT1, NKT2 and NKT17 have major influences on type 1, type 2 and type 3 immunity and are implicated in the progression fibrosis (2) infiltration and the accumulation of neutrophils following tissue injury is inhibited in the absence iNKT cells (3) adaptive Th1/Th2 skewing of adaptive immunity has been shown to be driven by an early activation of iNKT cells; 4) NKT2 interactions with type 2 driven lymphocytes, including eosinophils and ILC2, should play an important role in type 2 cytokine immune responses (5) additionally, iNKT activation also has been shown to promote Hh-Wnt signaling that plays a key role in the transition of epithelial cells into myofibroblasts that deposit matrix proteins  are the earliest cytokines secreted following tissue damage and they contribute to fibrosis indirectly with actions from type 2 cytokine-secreting immune cells, such as NKT2, ILC2, CD4patients . Aside f5, TSLP apatients , 66, 68.fibrosis , 56, 105KT cells , 40, 41;esponses , 107; 5)proteins , 51. Basproteins Figure 1Alarmins, like IL-33, are constitutively expressed at high levels in epithelial barrier tissues and endothelial barriers and are immediately released following tissue injury. iNKT cells constitutively express the ST2 chain specific of the IL-33 receptor on their surface , 109, an1) mixed type 1, 2, and 3 driven responses in which a single cytokine response does not dominate; 2) unintended consequences of cross-regulation of cytokine signaling in the fibrotic tissue; and/or 3) disruption of the beneficial or protective aspects of some cytokines. Thus, rather than blocking a particular key cytokine that has many pleiotropic effects, targeting an immune pathway that can facilitate a re-balancing of downstream pathways, and restoring immune homeostasis, may be crucial for an effective treatment strategy for fibrosis. As covered in this brief review, the blocking of an earlier upstream pathway, such as iNKT cell activation, may dampen all three key cytokine-associated pathways and ultimately may lead to the development of novel therapeutic strategies in IPF. As mentioned earlier, it is likely that in patients different NKT cell subsets may promote fibrosis at different timepoints or stages of disease. In this scenario, an agent that blocks all iNKT cell subsets is highly desirable. We have found that an agonist of RARβγ inhibits cytokine secretion from all three iNKT cell subsets and leads to significant inhibition of fibrosis in murine models (As investigations continue to unravel the details of the cellular and molecular pathways in fibrosis that are common across tissues, such as the activation of iNKT cell subsets and their role in promoting fibrosis, it may be possible to develop novel biomarkers and therapeutic targets that differentiate stages of fibrosis progression. We have shown that activated iNKT cells in PBMCs from patients strongly correlate with fibrosis and disease progression . Develope models  Future sVK: Conceptualization, Writing – original draft. MH: Writing – review & editing. AA: Writing – review & editing. AB: Writing – review & editing.


Hepatocellular carcinoma remains crucial due to its high prevalence and the need for improved understanding and treatment options. This study utilizes extensive microarray and RNA-seq data to identify key differentially expressed genes in hepatocellular carcinoma (HCC) and FDA-approved novel druggable genes. We uncovered potential associations between metal ion exposure and tumorigenesis, as well as the relevance of kinases in HCC. Topological analysis reveals 25 hub genes and their regulatory transcription factors, while computational drug repurposing suggests several novel therapeutic candidates targeting key genes, highlighting potential avenues for future experimental assays and clinical cohorts with HCC patients.Background: Drug repurposing is a strategy that complements the conventional approach of developing new drugs. Hepatocellular carcinoma (HCC) is a highly prevalent type of liver cancer, necessitating an in-depth understanding of the underlying molecular alterations for improved treatment. Methods: We searched for a vast array of microarray experiments in addition to RNA-seq data. Through rigorous filtering processes, we have identified highly representative differentially expressed genes (DEGs) between tumor and non-tumor liver tissues and identified a distinct class of possible new candidate drugs. Results: Functional enrichment analysis revealed distinct biological processes associated with metal ions, including zinc, cadmium, and copper, potentially implicating chronic metal ion exposure in tumorigenesis. Conversely, up-regulated genes are associated with mitotic events and kinase activities, aligning with the relevance of kinases in HCC. To unravel the regulatory networks governing these DEGs, we employed topological analysis methods, identifying 25 hub genes and their regulatory transcription factors. In the pursuit of potential therapeutic options, we explored drug repurposing strategies based on computational approaches, analyzing their potential to reverse the expression patterns of key genes, including AURKA, CCNB1, CDK1, RRM2, and TOP2A. Potential therapeutic chemicals are alvocidib, AT-7519, kenpaullone, PHA-793887, JNJ-7706621, danusertibe, doxorubicin and analogues, mitoxantrone, podofilox, teniposide, and amonafide. Conclusion: This multi-omic study offers a comprehensive view of DEGs in HCC, shedding light on potential therapeutic targets and drug repurposing opportunities. Precision medicine is a patient-centric approach that leverages individualized genomic information to inform drug treatment decisions, aiming to enhance clinical outcomes. In recent years, various methods have emerged to decipher and interpret multi-omics data, leading to the development of strategies for precise drug selection. These methods enable the identification of specific genetic characteristics associated with drug sensitivity or resistance while also integrating genetic markers with gene ontologies and biological networks to predict drug response on an individual level. Furthermore, by integrating multiple data sources, these approaches hold promise for optimizing drug therapies for personalized medicine .Drug repositioning, or drug repurposing, involves the identification of novel uses for approved or investigational drugs beyond their original intended targets. This drug reprofiling approach offers a cost-effective and time-efficient process for drug development compared to traditional de novo drug discovery, which often involves long and expensive processes . Among tIn this scenario, bioinformatics has emerged as a powerful discipline, allowing for the analysis and interpretation of large-scale biological data. With the advancement of high-throughput methodologies, such as next-generation sequencing and omics technologies, computational tools and algorithms have become crucial in the exploration of complex biological processes, disease mechanisms, and the discovery of potential therapeutic targets ,3. In adAmong distinct types of cancers, hepatocellular carcinoma (HCC) is the most common primary liver cancer and a leading cause of cancer-related mortality worldwide. It predominantly arises in the setting of chronic liver diseases, including hepatitis B and C virus infections, alcoholic liver disease, non-alcoholic fatty liver disease, and cirrhosis. HCC is characterized by aggressive tumor growth, high recurrence rates, and limited treatment options, necessitating a comprehensive understanding of its molecular pathogenesis and the development of effective therapeutic strategies. In this context, it is undeniable that significant progress has been made in the treatment of HCC with multiple drugs and combinations. Available drugs such as sorafenib, levantinib, regorafenib, cabozantinib, ramucirumab, nivolumab, and pembrolizumab, either alone or in combination, have proven to be effective in phase I/II studies and prolong survival in phase III randomized controlled trials. However, the limitations of these chemotherapeutics involve common side effects, including hypertension, weight loss, hand-foot skin reactions, fatigue, liver injury, and bleeding . These sCCNA2, CCNB1, CDC20, CDK1, PTTG1, and TTK, elucidating their relevance to HCC-related events. Conversely, Wang et al. [MARCO, CLEC4M, FCGR2B, LYVE1, TIMD4, STAB2, CFP, CLEC4G, CLEC1B, FCN2, FCN3, and FOXO1 reflects altered genes that may contribute to the pathogenesis of HCC, deserving a deep exploration. The disparities observed in these gene signatures are associated with different and diverse carcinogenic events. These events encompass various biological processes, such as mitotic events and stress responses to specific metal ions. Additionally, they pertain to molecular functions involving immune system responses, carbohydrate and peptide binding capacities, heme interactions, and microtubule-related activities. Moreover, these signatures implicate crucial pathways, including MAPK, FoxO, VEGF signaling, and detoxification of inorganic compounds. Consequently, it becomes evident that the ongoing debate regarding the selection of pertinent genes remains an open and intricate subject of discussion.The integration of genomic, transcriptomic, and epigenomic data has led to the identification of molecular signatures and biomarkers associated with HCC diagnosis, progression, and prognosis ,6. Molecg et al.  pointed In part, the discrepancies found in different studies can be explained by the fact that cells from healthy (non-tumor) tissues and cells collected from tissues adjacent to the tumor  differ in their genetic and expression profiles . FurtherThe efficacy of a drug to reverse cancer-associated gene expression has already been proven efficient and able to be tested in subsequent experimental procedures . The suchttps://www.ncbi.nlm.nih.gov/geo/ (accessed on 10 May 2023)) to locate microarray gene expression datasets containing samples of HCC that could be compared with non-tumor tissue samples. For data processing, we utilized the R language through the R Studio platform [https://sbc.shef.ac.uk/geo_tutorial/tutorial.nb.html# (accessed on 20 May 2023) with few adaptations to scrutinize the GEO Series (GSE) datasets; in cases where genes required normalization and resulted in a significant number of missing values (NAs or NANs), they were excluded from the study.In the initial phase, we conducted an active and manual search in the public repository GEO  access to raw data were permitted. Each dataset was individually analyzed using a univariate statistical approach with the lmFit and eBayes functions of the R package limma [2 fold change (log2FC) and adjusted p-values. The threshold values log2FC > 2.0 and p-value < 0.05 indicated up-regulated DEGs, while log2(FC) < −2.0 and p-value < 0.05 indicated down-regulated DEGs. We filtered out genes without concurrent Ensembl, Entrez, and HCNG identifiers, which were gathered using hgnc [2FC value. The gene distribution was visualized using Volcano plots created with the EnhancedVolcano package [Our workflow was conducted based on the following inclusion criteria: (I) GSE datasets with a minimum of 10 tumor and non-tumor samples that include gene symbols or minimum information to find gene symbols; (II) the species ge limma , resultiing hgnc , biomarting hgnc , and orging hgnc  packages package . https://www.cancer.gov/ccg/research/genome-sequencing/tcga (accessed on 1 June 2023)) and the GTEx project ); those genes comprise the “TCGA group”. To obtain TCGA/GTEx DEGs, we used the R script described in [p-value of 0.05 and a fold change of 2.0.Our primary objective was to illustrate the differences between DEGs in tumor versus adjacent-tumor tissue samples and those in normal  patients versus HCC samples. For the sake of simplicity, from now on, we will refer to the “adjacent group”, the DEGs comparing adjacent tumor and tumor tissue, and to those genes that differ between healthy and tumor tissue as the “normal group”. We aimed to identify DEGs shared between these two conditions using Venn diagrams . We alsoribed in , which iribed in  and edgeribed in  packagesTo propose a robust profile of HCC-associated DEGs, we applied a final filtering step. We selected only DEGs that appeared in at least 5 GSEs in the adjacent group and in at least 2 GSEs in the normal group. The final profile comprised the genes that were also present in the TCGA group. For gene enrichment analysis, we used Gene Ontology (GO) to define DEGs and their RNA or protein products and to determine the unique biological properties of transcriptomic and genomic data. The Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome pathway and Wiki pathways, which represent a collection of databases that deal with genomes, drugs, diseases, chemical materials, and biological pathways, were also consulted . Enrichmhttps://sankeymatic.com/ (accessed on 1 July 2023)). To propose a HCC signature, we elaborated a PPI Network and identified hub genes by analyzing the centrality of nodes (genes) using the CytoNCA plugin version 2.1.6 . Four cehttp://string-db.org, accessed on 10 July 2023). We employed the following arguments: full STRING network; active interaction sources: text mining, experiments, databases, co-expression, neighborhood, gene fusion, co-occurrence; minimum required interaction score: 0.9 (highest confidence). The resulting PPI network was visualized using Cytoscape software version 3.9.1 [To assess functional protein association networks and evaluate protein–protein interaction (PPI) networks, we utilized the STRING online tool (on 3.9.1 .http://octad.org (accessed on 10 August 2023)) [https://www.dgidb.org/ (accessed on 15 August 2023)), using the R package rDGIdb [https://labsyspharm.shinyapps.io/depmap (accessed on 24 August 2023)) to check out the essentiality of genes for cancer cell survival, i.e., the growth reduction caused by knockdown/knockout (efficacy) and the selectivity of our set of genes across 423 distinct cancer cell lines [Individual hub gene and TF expression were corroborated through the GSCA  database . The GSCt 2023))  to searct 2023)) . To furte rDGIdb . Finallyll lines .2FC was similar between the three conditions , 4 datasets for paired cancerous and non-cancerous healthy tissue , and the TCGA-LIHC/GTEx database (TCGA group), ultimately totaling 2292 HCC samples and 1361 non-tumor samples; in nditions . APOF, GPC3, C9, CLEC1B, CYP1A2, FCN3, HAMP, and the gene MT1M were the most frequent genes found in the datasets we examined. The genes −21), and other diseases related to the liver were also found , 18 molecule functions (MF), and 6 cellular components (CC). The top five BP included “steroid metabolic process” (GO:0008202), “cellular response to zinc ion” (GO:0071294), “cellular response to copper ion” (GO:0071280), “exogenous drug catabolic process” (GO:0042738), and “cellular response to cadmium ion” (GO:0071276). The top five MF included “steroid hydroxylase activity” (GO:0008395), “oxidoreductase activity” (GO:0016712), “arachidonic acid epoxygenase activity” (GO:0008392), “estrogen 2-hydroxylase activity” (GO:0101021), and “arachidonic acid monooxygenase activity” (GO:0008391). The top five CC included “Endoplasmic Reticulum Membrane” (GO:0005789), “Membrane Attack Complex” (GO:0005579), “Collagen-Containing Extracellular Matrix” (GO:0062023), “Serine-Type Endopeptidase Complex” (GO:1905370), and “Endopeptidase Complex” (GO:1905369) A. Up-regWe performed functional annotation for DEGs using three distinct pathway analyses: the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and WikiPathways. Down-regulated DEGs were significantly enriched in 15 KEGG, 38 Reactome, and 29 Wiki pathways. KEGG analysis showed that down-regulated DEGs were mainly enriched in Caffeine, Retinol, Drug metabolism, “Mineral absorption”, and “Metabolism of xenobiotics by cytochrome P450”. The top five Reactome pathways were “Metallothioneins Bind Metals”, “Cytochrome P450—Arranged by Substrate Type”, “Response to Metal Ions”, “Phase I—Functionalization Of Compounds”, and “Xenobiotics”. In the Wikipathways the main terms were “Oxidation by Cytochrome P450”, “Metapathway biotransformation Phase I and II”, “Nuclear Receptors in Lipid Metabolism and Toxicity”, “Zinc homeostasis” and “Fatty Acid Omega Oxidation”. The number of significantly enriched pathways for the up-regulated DEGs was 7 (KEGG), 81 (Reactome), and 11 (WikiPathways). The top five KEGG pathways were “Cell cycle”, “Oocyte meiosis”, “p53 signaling pathway”, “Human T-cell leukemia virus 1 infection” and “Cellular senescence”. Reactome pathways were “Cell Cycle, Mitotic”, “Mitotic Prometaphase”, “M Phase”, “APC/C-mediated Degradation Of Cell Cycle Proteins” and “Resolution Of Sister Chromatid Cohesion”. The top five Wiki pathways were “Retinoblastoma gene in cancer”, “Cell cycle”, “Regulation of sister chromatid separation at the metaphase-anaphase transition”, “Gastric Cancer Network 1” and “DNA damage response”. Pathways enrichment are depicted in We used CytoNCA V2.1.6, a CytoScape plugin, for centrality analysis of the PPI network to identify crucial nodes (hub genes). The hub genes were selected based on degree centrality (DC), eigenvector centrality (EGC), betweenness centrality (BC), and maximal clique centrality (MCC) . Accordip-value lower than 0.05 (X2KWeb database). The TFs that regulate a higher number of hub genes are E2F4 and NFYB (both regulating 15 genes), followed by NFYA (14), SIN3A (13), and FOXM1 (10). The hub genes that are targets of distinct TFs were CCNB1 (12), CDK1 (11), AURKA (9), and TOP2A (7). Interestingly, PTTG1 acts as both a FOXM1-regulated gene and a modulator of CCNB1 and CDK1 expression (Transcription factors (TFs) are pivotal gene expression regulators, orchestrating the intricate process by which genetic information is converted into functional molecules in living organisms. In the context of cancer, TFs play a dual role, acting as both drivers and suppressors of tumorigenesis. We searched for TFs that regulate the expression of the 25 hub genes and found 28 TFs that have been described to repress or activate a specific target gene (TRRUST database) or have a hypergeometric pression A. We alspression B.p-value < 10−16 ) for the purpose of identifying compounds with potential utility in the treatment of HCC. Leveraging advanced deep-learning methodologies, OCTAD generates a succinct metric known as the summarized reversal gene expression score (sRGES). This metric serves as an indicator of a candidate drug’s ability to modulate gene expression profiles, specifically by either inhibiting the overexpression of particular genes or promoting the activation of genes exhibiting lower expression levels. In accordance with the recommendations provided by the platform, we considered candidate drugs with sRGES values less than −0.25 for further investigation. To search for candidate-druggable genes, we submitted the 53 genes to the publicly accessible OCTAD platform ; kenpaullone (CCNB1); alvocidib, aminopurvalanol-a, AT-7519, CDK1-5-inhibitor, indirubin, JNJ-7706621; kenpaullone, PHA-793887 (CDK1); thiostrepton (FOXM1); piceatannol (IRF3); bortezomib, caffeic-acid-phenethyl-ester, pyrrolidine-dithiocarbamate, triptolide (RELA); cladribine, gemcitabine (RRM2); amonafide, amsacrine, daunurobicin, doxorubicin, idarubicin, mitoxantrone, pirarubicin, podofilox, teniposide (TOP2A); pifithrin-mu (TP53). Details about each drug are described in By selecting the drugs that have been tested in HCC cells only, such as Huh7.5 and HepG2, we retrieved 190 candidate compounds, which are categorized into the following experimental stages: 70 “launched”, 9 “phase 1”, 1 “phase 1/2”, 13 “phase 2”, 1 “phase 2/3”, 11 “phase 3”, 81 “preclinical stage”, and 4 drugs were withdrawn. The top 50 drugs ranked by sRGES are depicted in nt drugs . Nine ofand TP53 . These gTo double-check our findings, we consulted the repository DGIdb . The ninhttps://labsyspharm.shinyapps.io/depmap (accessed on 24 August 2023)), which presents the efficacy and selectivity of specific genes regarding cell growth. Though the five genes had lower selectivity, all of them presented relative high efficacy, especially TOP2A, RRM2, and CDK1 genes  and the pathway activity module, we verified some cancer-related pathways and their relationship with our genes. Apoptosis, cell cycle, and epithelial mesenchymal transition (EMT) showed a positive and significant correlation; on the other hand, the hormone AR, hormone ER, RASMAPK, and RTK pathways correlate inversely with our genes A. The esK1 genes B.Besides being the most common primary liver malignancy, HCC also accounts for an elevated rate of morbidity and mortality. HCC is strongly associated with previous conditions and environmental risk factors, such as liver cirrhosis, HBV and HCV infections, alcohol abuse, and non-alcoholic steatohepatitis. This last one deserves special attention as it is intrinsically correlated with obesity, the 21st century epidemic . GeneticOne difference between this study and other studies that have proposed gene signatures for HCC ,14,41,42APOF codes for Apolipoprotein F, which inhibits cholesteryl ester transfer among plasma circulating lipoproteins. In vitro and in vivo experiments showed that the reversion of APOF expression was effective against tumor growth, proliferation, and migration [GPC3 (Glypican 3) is not normally expressed in healthy liver tissues, but the gene is up-regulated in HCC. GPC3 is involved with Wnt signaling and Hippo pathways, both associated with liver tumor cell differentiation, survival, proliferation, migration, and invasion [CLEC1B, encoding the CLEC-2 protein, a C-type lectin-like receptor 2, is down-regulated in HCC samples. CLEC1B regulates distinct signaling pathways related to immune and inflammatory responses and is inversely correlated with the proliferation and migration of HCC cells [CYP1A2) is down-regulated in HCC. CYP1A2 was identified as an antagonist of the hepatocyte growth factor/c-mesenchymal–epithelial transition factor (HGF/MET) signaling pathway, which is associated with tumor progression, survival, and metastasis [FCN3) is a protein member of the ficolin family that is down-regulated in HCC. Through pathways associated with mannose-binding lectin-associated serine proteases, ficolin-3 activates the complement system. In distinct HCC cell lines, the overexpression of FCN3 inhibited cell proliferation and led cells to apoptosis [HAMP gene) is a protein hormone mainly produced and secreted from the liver that, associated with ferroportin, contributes to iron homeostasis. The downregulation of HAMP, as we demonstrated in HCC, was also related to liver fibrosis and cirrhosis, both important risk factors for liver cancer [MT1M gene) participates in metal detoxification, and its overexpression was found to avoid HCC progression in vitro and in a xenograft nude mice model [Some of the most frequently deregulated genes we found have been previously confirmed to be altered in HCC ,43. The igration . The proinvasion . CLEC1B,CC cells . The pretastasis . Ficolinpoptosis . Hepcidir cancer . The cysce model . Of the 110 DEGs, most are down-regulated in HCC, while 37 are up-regulated genes. The 110 genes are closely related to liver cancer as well as other events associated with liver disease. Through GO enrichment analysis, we demonstrated that down-regulated genes are involved in distinct biological processes associated with zinc, cadmium, and cooper ions. This may not be unexpected, as chronic exposure to some metal ions has a strong association with the tumorigenesis process. Low concentrations of cadmium trigger fibrogenic and oncogenic signaling pathways in distinct HCC cell lines . In vivoASPM, AURKA, BUB1B, CCNB1, CCNB2, CDC20, CDK1, CENPF, CYP1A2, CYP26A1, CYP2E1, DLGAP5, HMMR, KIF20A, KIF4A, MELK, NCAPG, NDC80, NEK2, PBK, PRC1, PTTG1, RRM2, TOP2A, TTK). Transcription factors (TFs) play a pivotal role in gene regulation, orchestrating the intricate process by which genetic information is converted into functional molecules in living organisms. We found 28 TFs that regulate our hub genes and showed E2F4, NFYB, NFYA, SIN3A, and FOXM1 to control at least 10 different genes. The overexpression of those five TFs has already been described to participate in different stages and events related to liver cancer and to have prognostic values for patients with HCC [As can be seen in this and other studies, the number of genes with altered expression in HCC is enormous, running into hundreds. We suggest that the higher number of deregulated genes is more likely to be the consequence rather than the cause of the carcinogenic process; thus, trying to generalize about all dysregulated genes seems uninformative. One strategy is to use tools that predict degrees of centrality based on gene co-expression networks. As a mathematical model, node centrality analyses have limitations, but in biological terms, it is assumed that co-expressed genes must be co-regulated, and the degree of connectivity between genes may reflect their physiological and pathological roles . We adopwith HCC ,59,60. TChemotherapy remains the cornerstone of treatment for solid tumors like HCC, with various drugs and regimens under constant investigation. Notably, the drug 5-fluorouracil (5-FU), a breakthrough that emerged from research on rat hepatoma, has played a pivotal role in this field. First synthesized in 1950 by Charles Heidelberger and collaborators and approved for human trials in 1962, 5-FU undergoes metabolic transformations involving enzymes like dihydropyrimidine dehydrogenase, orotate phosphoribosyltransferase, uridine phosphorylase, and uridine kinase. Through a series of phosphorylation steps, 5-FU is converted into active metabolites, including FdUTP and FdUMP, which disrupt DNA synthesis by irreversibly inhibiting thymidylate synthase. Thymidylate synthase is essential for DNA synthesis as it converts deoxyuridine monophosphate (dUMP) into deoxythymidine monophosphate (dTMP), a basic component of pyrimidines ,62. ThusAURKA, CCNB1, CDK1, RRM2, and TOP2A. We also showed that the loss-of-function of CDK1, RRM2, and TOP2A has the highest efficacy in reducing cellular proliferation. A promising strategy in therapeutic treatment involves the systematic re-utilization of drugs with well-established safety and pharmacokinetic profiles, considering that numerous drugs possess multiple targets and targets can be influenced by multiple drugs. The exploration of drug repositioning extends beyond approved drugs and encompasses a growing pool of late-stage failures that have been halted due to insufficient efficacy or safety concerns . One strCDK1 (Cyclin-Dependent Kinase 1) is a critical regulator of the cell cycle, and its dysregulation has been implicated in various cancers. We found CDK1 to be upregulated, which has been associated with tumor development and HCC progression. Five drugs may interact with CDK1: (i) Alvocidib, the cyclin-dependent kinase inhibitor, is being considered to treat acute myeloid leukemia [(ii) AT-7519, the second-generation small molecule multi-CDK inhibitor, was experimented against glioblastoma, lung cancer, myeloma, and leukemic cells [(iii) Kenpaullone, a multiple kinase inhibitor known for its inhibitory potential of GSK3 activity, has been experimented to be effective in some neurological disorders, cystic fibrosis, ototoxicity, and preventing oxidative stress damage in cardiomyocytes [CCNB1, the gene that encodes Cyclin B1. The CCNB1 gene is significantly up-regulated in HCC, and there is a positive correlation with CCNB1 overexpression and vascular invasion in HCC samples [(iv) PHA-793887: Few experimental studies have been conducted to certify its activity, but it was demonstrated in vitro that PHA-793887 was able to interfere with the viability of osteosarcoma cells [(v) JNJ-7706621: a potent inhibitor of CDKs and Aurora kinase (AURKA) demonstrated effectiveness in dealing with the herpes simplex virus 1 [leukemia ; (ii) ATic cells ,67,68,69ic cells ; (iii) Kmyocytes ,72,73,74ma cells . (v) JNJAURKA, coding for Aurora A kinase, is up-regulated in HCC. AURKA is a mitotic regulator that is subject to several regulatory interactions and post-translational modifications, including covalent CoA modification induced by oxidative stress [danusertibe is able to reverse the AURKA expression. Danusertibe exhibits inhibitory activity against all known Aurora kinases and was identified to inhibit DNA helicases [e stress . Besideselicases . Danuserelicases . RRM2) overexpression found in HCC samples increased the proliferative and migratory capabilities of Hep3B and Huh7 cells [RRM2 is the target of cladribine and gemcitabine. Some of the applications for cladribine are for treating acute myeloid leukemia, the rare Rosai–Dorfman disease, and multiple sclerosis [Ribonucleotide reductase regulatory subunit M2  doxorubicin, (ii) daunorubicin, and (iii) idarubicin are predicted to be able to reverse TOP2A upregulation. Their chemical properties and differences can be consulted elsewhere [TOP2A by doxorubicin contributes to suppressing the growth of sorafenib-resistant HCC tumors in vitro and in vivo [lsewhere . Inhibit in vivo . At this in vivo ,89. As a in vivo ,91.(iv) Mitoxantrone also has the ability to reduce the growth of chronic myeloid leukemia K562 cells by a mechanism involving proteasomal activity [(v) Podophyllotoxin (Podofilox), an aryltetralin cyclolignan extracted from the roots and rhizomes of Podophyllum species, and its derivative (vi) teniposide have already shown anti-tumoral properties for distinct types of neoplasia, including HCC [(vii) Amonafide, a naphthalimide, was initially tested to treat acute myeloid leukemia and breast cancer. By intercalating DNA and blocking the binding of topoisomerases, amonafide promotes apoptotic cell death [(viii) amsacrine has a mechanism of action similar to amonafide and showed potential effects in treating malignant lymphoma and acute myeloid leukemia [Similar to doxorubicin and idarubicin, activity . (v) Podding HCC ,94,95. (ll death  and was ll death . The synleukemia . We founThe concomitant administration of drugs with distinct mechanisms of action holds promise as a viable strategy for addressing neoplastic conditions. The synergy resulting from the combination of two or more drugs can yield superior therapeutic outcomes in the context of HCC, as demonstrated by prior research . To citeThis study encountered two relevant constraints. Firstly, bioinformatics analyses were executed without undergoing experimental validation. Secondly, empirical verification is essential for confirming the identified hub genes and drug-gene interactions. With these limitations in mind, investigations akin to ours not only broaden the spectrum of potential therapeutic approaches but also pave the way for forthcoming experimental studies.CDK1, TOP2A, and RRM2 emerge as promising candidates for potential drug testing, either in isolation or in combination. Upon successful experimental validation of these novel therapeutic approaches, they hold the potential for clinical testing within a specific cohort of HCC patients.Through a comprehensive evaluation and comparison of multiple datasets highlighting DEGs in HCC, we have meticulously curated a robust list of genes. This compilation comprises 25 DEGs along with their associated transcription factors. Notably,


The aggressive features of glioblastoma (GBM) are associated with dormancy. Our previous transcriptome analysis revealed that several genes were regulated during temozolomide (TMZ)-promoted dormancy in GBM. Focusing on genes involved in cancer progression, Chemokine (C-C motif) Receptor-Like (CCRL)1, Schlafen (SLFN)13, Sloan-Kettering Institute (SKI), Cdk5 and Abl Enzyme Substrate (Cables)1, and Dachsous Cadherin-Related (DCHS)1 were selected for further validation. All showed clear expression and individual regulatory patterns under TMZ-promoted dormancy in human GBM cell lines, patient-derived primary cultures, glioma stem-like cells (GSCs), and human GBM ex vivo samples. All genes exhibited complex co-staining patterns with different stemness markers and with each other, as examined by immunofluorescence staining and underscored by correlation analyses. Neurosphere formation assays revealed higher numbers of spheres during TMZ treatment, and gene set enrichment analysis of transcriptome data revealed significant regulation of several GO terms, including stemness-associated ones, indicating an association between stemness and dormancy with the involvement of SKI. Consistently, inhibition of SKI during TMZ treatment resulted in higher cytotoxicity, proliferation inhibition, and lower neurosphere formation capacity compared to TMZ alone. Overall, our study suggests the involvement of CCRL1, SLFN13, SKI, Cables1, and DCHS1 in TMZ-promoted dormancy and demonstrates their link to stemness, with SKI being particularly important.  Glioblastoma (GBM) represents the most common and most malignant primary brain tumor in adults . BesidesCCRL1 is an atypical chemokine receptor that was shown to predominantly exhibit tumor-restricting effects in different malignancies ,8,9. HowTo date, only limited-to-no data concerning the role of CCRL1, SLFN13, SKI, Cables1, and DCHS1 in GBM are available, and their relation to phenomena known to be associated with the high therapy resistance of the disease, such as dormancy and stemness, are still mainly uncharted. Hence, this study aimed to further validate the role of the markers in TMZ-promoted cellular dormancy, to examine whether CCRL1, SLFN13, SKI, Cables1, and DCHS1 inherit a potential connection to the phenomenon of stemness in GBM, and investigate whether targeting (any of) these markers can improve the antitumor potential of TMZ. n = 20) were obtained by surgical dissection at the Department of Neurosurgery  with the approval of the ethics committee of the University of Kiel, Germany, after the written informed consent of donors (file reference: D471/15 and D524/17) and in accordance with the Helsinki Declaration of 1975, revised in 2013. Tumors were diagnosed and classified, according to World Health Organization (WHO) criteria, as GBMs CNS WHO Grade 4 by a pathologist .Human tumor samples (n = 2) were produced by dissociation and cultured according to established techniques as described before [n = 8) as well as GBM cell line-derived stem-like cells were established and intensively characterized by the formation of neurospheres, the ability to survive and proliferate under stem cell conditions, and the ability to differentiate into more mature cells as described before [The human glioblastoma cell lines LN229 ATCC-CRL-2611), U251 , U87MG (ECACC 89081402), and T98G (ECACC No. 92090213) were obtained from the European Collection of Authenticated Cell Cultures  or the American Type Culture Collection  and cultured as described previously . Human pd before . Human p11, U251 d before . The pur5 LN229, U251, primary culture (PC)a, or PCb cells, respectively, were stimulated for 10 days with TMZ  dissolved in dimethyl sulfoxide  in Dulbecco’s modified Eagle’s medium  supplemented with 10% fetal bovine serum . DMSO 0.5% (v/v) was used as a control. Hereafter, the medium was changed, and the cells were cultured for another 15 days without TMZ stimulation. Stem-like U251 and LN229 cells were stimulated under the same conditions and for the same periods, but in neurosphere medium [50% DMEM, 50% F12 medium (Thermo Fisher Scientific) containing the following supplements: 2 mM L-glutamine, 0.6% glucose , 9.5 ng/mL putrescine dihydrochloride (Sigma-Aldrich), 6.3 ng/mL progesterone (Sigma-Aldrich), 5.2 ng/mL sodium selenite (Sigma-Aldrich), 0.025 ng/mL insulin (Sigma-Aldrich), 2 µg/mL heparin (Sigma-Aldrich), and 4 mg/mL bovine serum albumin (Thermo Fisher Scientific). The growth factors EGF  and bFGF  were added at a concentration of 20 ng/mL as described before [v/v) and PBS were used as controls. Then, the medium was changed and the cells were used for different experiments or cultured for another 11 days without TMZ stimulation but with the continuous addition of Disitertide (100 µg/mL) [As previously described in detail, 1.5  ×  10d before . In addi® reagent  or with the ARCTURUS® PicoPure® RNA isolation kit  according to the manufacturer’s instructions. DNase digestion, cDNA synthesis, and qRT–PCR were performed as previously described [T) were determined, and the ∆CT values of each sample were calculated as CT gene of interest − CT GAPDH. Either ∆CT values or linearized ∆CT values (2−∆CT) are shown in the figures. The regulation of gene expression upon stimulation with Disitertide is displayed as n-fold expression changes = 2∆CTcontrol − ∆CTstimulus.RNA of cells and tissue were isolated with the TRIzolescribed  using TaCryostat sections of GBM ex vivo tissues were prepared as previously described . Cells wp-values were adjusted using a Benjamini–Hochberg FDR correction.Gene set enrichment analyses (GSEA) were performed with the tool gProfiler based on the gene ontology (GO) source ‘biological process’ . p-valuen-fold number of viable cells as described in Equations (1) and (2) after 10 and 21 days of stimulation, respectively. Growth rates were calculated as an n-fold number of alive cells compared to day zero of the treatment.The cytotoxic effects were determined using the CytoTox-FluorTM Cytotoxicity Assay (Promega) according to the manufacturer’s instructions and as described before . Supernahttp://bioinf.wehi.edu.au/software/elda, accessed on 13 April 2023) [The self-renewal capacity of 10- versus 3-day-TMZ-pretreated cells and 10 day-TMZ- or TMZ + Disitertide-pretreated cells were measured using an extreme limiting dilution analysis (ELDA) as described before [il 2023) .t-test or a one- or two-way analysis of variance (ANOVA) was performed using the GraphPad Prism 8 software . The sample sizes and a description of the sample collection, including the number of biological/technical replicates, are described in the figure legends. In general, the data are presented as mean  ±  standard deviation. Correlations were calculated with the Pearson correlation index. Statistical significance is marked with asterisks depending on the p-value: * p  <  0.05, ** p  <  0.01, and *** p  <  0.001. Depending on the experimental setup, either a two-tailed Student’s To evaluate the relevance of CCRL1, SLFN13, SKI, Cables1, and DCHS1 in GBM progression, we first examined their gene expression under TMZ-promoted dormancy entry and exit in different GBM cell lines (LN229 and U251) and primary cultures (PCa and PCb), respectively, using our previously established in vitro model with sole-TMZ stimulation. Except for SLFN13, which was not found in PCb, all genes were expressed in the regarded cell lines and primary cultures at different levels. The highest gene expression level amongst all examined cell cultures was found for SKI, whereas CCRL1 and especially SLFN13 exhibited overall a rather low gene expression. The gene expression of DCHS1 and also, though to a lesser extent, Cables1, appeared heterogeneous among the different cell cultures. p = 0.017), whereas Cables1 (p = 0.028) and DCHS1 (p = 0.026) revealed a downregulation in TMZ-promoted dormancy exit. Furthermore, Cables1 (p = 0.008) and DCHS1 (p = 0.026) showed a significantly higher gene expression after 15 days of stimulation with DMSO in comparison to 10 days of stimulation. Albeit not statistically significant, SKI was found to be slightly upregulated during the entry and downregulated during the exit of TMZ-promoted dormancy; however, high standard deviations were observed. U251 cells revealed the downregulation of CCRL1 (p = 0.016) after 15 days of stimulation with TMZ in comparison to 10 days. Contrary to this, SLFN13 (p = 0.019) was found to be upregulated after 15 days of stimulation with TMZ. In accordance with LN229, the expression of SKI tended to be downregulated during TMZ-promoted dormancy exit in U251 cells, and a significant downregulation was observed when comparing 10 and 15 days of TMZ stimulation (p = 0.049). Whereas Cables1 revealed a downregulation during TMZ-promoted dormancy entry (p = 0.004) and a trend of upregulation during exit, DCHS1 was downregulated in both scenarios . In addition, DCHS1 revealed an upregulation after 15 days of stimulation with DMSO versus 10 days (p = 0.016), and a downregulation after 15 days of stimulation with TMZ in comparison to after 10 days of treatment (p = 0.005). Concerning the primary cultures, tendencies or even statistically significant upregulations for CCRL1 (PCa: p entry = 0.021) and Cables1  during TMZ-promoted dormancy entry and exit were observed. Whereas SLFN13 was found to be upregulated during the entry and exit of TMZ-promoted dormancy in PCa , no expression of the gene was observed in PCb. However, DCHS1 (p < 0.001), which was only detected in a low amount and not significantly regulated in PCa under TMZ-promoted dormancy, revealed an upregulation during dormancy exit in PCb. In PCa, SLFN13 (p = 0.007) and Cables1 (p < 0.001), and in PCb, Cables1 (p = 0.004) and DCHS1 (p < 0.001), exhibited upregulation after 15 days of TMZ stimulation in comparison to 10 days of stimulation. Data are presented in Concerning gene regulation under TMZ-promoted cellular dormancy entry and exit, differences were observed amongst the regarded cells. Overall, a more homogeneous pattern of gene regulation was found, particularly within the primary culture group. Whereas most of the examined genes exhibited an upregulation in dormancy entry and exit in the primary cultures, the cell lines revealed a more complex profile of gene regulation . In detaT = 3.44), followed by DCHS1 (average ΔCT = 4.23). SLFN13 (average ΔCT = 6.87), CCRL1 (average ΔCT = 7.19), and Cables1 (average ΔCT = 7.22) altogether exhibited similar comparatively lower gene expression levels , SLFN13 and Cables1 (corr. = 0.97), and CCRL1 and Cables1 (corr. = 0.85). Medium correlations were detected for SKI and DCHS1 (corr. = 0.73), SKI and Cables1 (corr. = 0.69), SKI and CCRL1 (corr. = 0.68), Cables1 and DCHS1 (corr. = 0.62), and DCHS1 and CCRL1 (corr. = 0.56) see B.Given the positive correlations found between the selected genes, immunofluorescence double staining of the respective molecules with each other was performed. Since this is a non-quantitative methodology and, in most cases, only individual or small groups of cells exhibit clear co-staining, a purely qualitative assessment of staining was performed here. Overall, staining for all five proteins was detected in the GBM samples. A co-staining of the molecules and solely positive cells was observed in all different staining combinations in varying amounts. Whereas most of the markers revealed either direct co-staining or solely positive cells, SLFN13 and Cables1 also often seemed to be stained in different structures of the same cell. Representative staining examples are shown in To identify the cellular sources of the investigated genes, immunofluorescence double staining of the selected molecules with cell type-specific markers was carried out. Von Willebrand factor (vWF) served as a marker for endothelial cells, a cluster of differentiation molecule (CD)11b tagged microglia, and glial fibrillary acidic protein (GFAP) detected cells of astroglial origin. Furthermore, the stemness markers octamer binding transcription factor (OCT)4, sex-determining region Y-box (Sox)2, and krüppel-like factor (KLF)4 were used to detect a possible link of the markers to tumor stem-like cells. CCRL1, SLFN13, SKI, Cables1, and DCHS1 were stained with or nearby vWF to different extents. Whereas SLFN13, SKI, and Cables1 mainly exhibited direct co-staining with vWF, respectively, DCHS1 and especially CCRL1 also seemed to be expressed in different structures of the same vWF-positive cell. Concerning the microglial marker, CD11b, CCRL1, SLFN13, SKI, and DCHS1 seemed to be expressed in different structures of the same CD11b-positive cell. In contrast, Cables1 revealed either a co-staining or was found to be stained separate from CD11b. All of the examined dormancy-associated markers were also found to be stained in GFAP-positive areas. In particular, SKI, Cables1, and DCHS1 revealed a co-staining with GFAP. Interestingly, all of the mentioned markers exhibited individual co-staining patterns with stemness markers. Since tumor stem-like cells are known to represent only a small subpopulation within the total tumor mass (ranging from ~2–20% depending on GBM and stem-like cell subtypes ), only sT = 4.37), followed by KLF4 (average ΔCT = 7.0), and OCT4 (average ΔCT = 7.14). To validate the detected link between the genes regulated under TMZ-promoted dormancy and the stemness markers, we performed a correlation analysis. Positive correlations were found, especially for the stemness markers OCT4 and KLF4 with CCRL1, SLFN13, and SKI. In detail, medium correlations were found for OCT4 and SKI (corr. = 0.79), CCRL1 (corr. = 0.74), and SLFN13 (corr. = 0.68); and for KLF4 and CCRL1 (corr. = 0.75), SKI (corr. = 0.74), SLFN13 (corr. = 0.68), and Cables1 (corr. = 0.58). Sox2 exhibited medium correlations with DCHS1 (corr. = 0.65), and CCRL1 (corr. = 0.54). Sox2 and Cables1 (corr. = 0.47), as well as Sox2 and SLFN13 (corr. = 0.45) only revealed weak correlations. Based on the previously described finding of a co-staining for CCRL1, SLFN13, SKI, Cables1, and DCHS1 with stemness markers, respectively, we examined the gene expressions of OCT4, Sox2, and KLF4 in human GBM ex vivo samples. All stemness markers were clearly detected in the samples to different extents . The higTo further validate the link between CCRL1, SLFN13, SKI, Cables1, and DCHS1 with stemness properties, we examined their expression in stem-like cells of different GBM cell lines and patient-derived primary cultures. T = 7.65) was followed by CCRL1 (average ΔCT = 9.31), DCHS1 (average ΔCT = 10.96), Cables1 (average ΔCT = 12.02), and SLFN13 (average ΔCT = 13.89). In U251, the gene expression of SKI (average ΔCT = 6.05) was followed by DCHS1 (average ΔCT = 8.92), Cables1 (average ΔCT = 10.66), CCRL1 (average ΔCT = 11.02), and SLFN13 (average ΔCT = 11.91). In U87MG, the gene expression of SKI (average ΔCT = 7.38) was followed by CCRL1 (average ΔCT = 10.47), DCHS1 (average ΔCT = 11.18), SLFN13 (average ΔCT = 14.06), and Cables1 (average ΔCT = 16.57). Finally, in T98G, the gene expression of SKI (average ΔCT = 7.45) was followed by CCRL1 (average ΔCT = 10.16), Cables1 (average ΔCT = 10.50), DCHS1 (average ΔCT = 13.14), and SLFN13 (average ΔCT = 15.77). The data are displayed in In most cases, the markers were detectable in the stem-like cells generated from commercial cell lines to different extents. Overall, the highest gene expression in all stem-like cell lines was observed for SKI. The other markers revealed a rather heterogenous pattern between the different stem-like cell lines, which was especially observed for SLFN13 and Cables1. In LN229, the gene expression of SKI (average ΔCT = 11.08), the patient-derived GBM stem-like cells (n = 8) also mostly revealed an expression of the examined markers. DCHS1 (average ΔCT = 7.26) exhibited the highest gene expression among all markers, closely followed by SKI (average ΔCT = 7.44). The lowest gene expressions were observed for Cables1 (average ΔCT = 11.15), and CCRL1 (average ΔCT = 12.00). Data are shown in Except for SLFN13 , which was more pronounced in LN229 stem-like cells. When considering dormancy exit, SKI was slightly downregulated in LN229 stem-like cells, but further induced in U251 stem-like cells, and this was also in contrast to native U251 cells (p < 0.0001). CCRL1 and SLFN13 were rather lowly expressed in both stem-like cell types but showed partly significant induction of gene expression compared to the controls, respectively, after 10 days of TMZ stimulation and a further 15 days of recovery . The Cables1 expression level was at a rather low level in LN229 and U251 stem-like cells and was partially significantly induced in both cell types in dormancy entry and exit (U251 entry and exit: p = 0.0005). Interestingly, this aspect was not observed in native LN229 and U215 cells. Finally, a strong statistically significant reduction in DCHS1 expression in dormancy exit was observed, particularly in LN229 stem-like cells (p < 0.0001), which was consistent with the results observed in native LN229 cells. DCHS1 expression in U251 stem-like cells was more intermediate and was significantly induced in dormancy exit (p < 0.0096), whereas a reduction in gene expression was observed in native U251 cells in dormancy exit compared to the control.Interestingly, the results in LN229 and U251 stem-like cells showed similar trends to those obtained for native LN229 and U251, although there were clear differences in some aspects  to investigate sphere formation capacity after pretreatment with TMZ for 3 or 10 days. Here, previous work by our group using native LN229 as an example has shown that LN229 cells pretreated with TMZ for 10 days exhibited a higher self-renewal capacity compared to cells pretreated for a shorter time, yielding sphere formation even at high dilutions [As the relationship between the expression of CCRL1, SLFN13, SKI, Cables1, and DCHS1 and the stemness characteristics of GBM cells became increasingly clear based on our results, we next performed gene set enrichment analyses. We used the microarray-based transcriptome datasets previously published by our group, which analyzed the regulation of gene expression during TMZ-promoted entry and exit from cellular dormancy in GBM cells . In detap = 0.019) for the comparison between TMZ versus DMSO in dormancy entry. Genes assigned to this GO term also included SKI. All data from the gene set enrichment analysis are given in Indeed, the stemness GO term GO:0019827 (stem cell population maintenance) yielded significant results . In line with this, treatment with TMZ + Disitertide significantly decreased the proliferation of LN229 to a higher extent in comparison to after the administration of TMZ alone .Since SKI appeared to be particularly important in TMZ-promoted dormancy and its link to stemness, finally, we examined to what extent TMZ application with the simultaneous inhibition of SKI led to increased cytotoxicity and a decreased proliferation of GBM cells compared to TMZ treatment alone. Using our previously established in vitro model, native LN229 cells were stimulated with TMZ alone or in combination with Disitertide for 10 days, after which TMZ was omitted but Disitertide was added for an additional 11 days. Disitertide  itself is a TGF-β inhibitor, which also mediates its efficacy via the downregulation of SKI at both transcriptional and translational levels . The nump = 0.006).To further examine whether TMZ application with the simultaneous inhibition of SKI affected stemness properties, we performed neurosphere formation assays with ELDA to investigate the sphere formation capacity of native LN229 cells stimulated for 10 days with TMZ alone or with TMZ in combination with Disitertide. The results are shown in Overall, our study suggests the involvement of CCRL1, SLFN13, SKI, Cables1, and DCHS1 in TMZ-promoted dormancy and demonstrated their link to stemness with SKI being particularly important. GBM is the most aggressive primary brain tumor known and still an incurable disease with a medium life expectancy of 15 months despite surgery, and radio- and chemotherapy . The curWe observed differences in the gene regulation patterns of chosen molecules under TMZ-promoted dormancy entry and exit between different GBM cell cultures. Whereas patient-derived GBM primary cultures revealed an upregulation of most of the markers during the entry and exit of dormancy, cell lines exhibited a more heterogeneous gene-regulation pattern.6-methylguanine-DNA methyltransferase (MGMT) expression status does significantly affect TMZ response. Silencing of the DNA-repair enzyme MGMT by its promoter methylation abolishes its inhibitory effects against alkylating agents such as TMZ [GBM is known to exhibit a vast molecular intra- and inter-tumoral heterogeneity, which might account for the differences in the gene regulation observed. Intense research and technical advancements have yielded a subclassification of the tumor into either a classical, mesenchymal, and proneural subtype depending on the molecular signature . Furtherh as TMZ . Additioh as TMZ ,35,36, ah as TMZ . Consistent with the upregulation of most of the markers during the entry into and exit from dormancy observed in the primary cultures, our study revealed a relationship between CCRL1, SLFN13, SKI, Cables1, and DCHS1 as indicated by co-staining and correlation analysis of their gene expressions. To date, no further studies focusing on a connection between these markers exist. Concerning the function of the respective markers, SLFN13, CCRL1, and SKI, especially, were shown to exert tumor-promoting effects in different malignancies. In accordance with the mainly observed upregulation of SLFN13 during TMZ-promoted dormancy exit in our study, previous investigations revealed an increase in the gene expression with progressive glioma grade and hence with incremental aggressive properties . ConcernHowever, besides tumor cells, endothelial cells and tumor-associated microglia/macrophages were shown to account for the gene expression of the regarded markers. This finding might also contribute to the connection between the markers observed. Supporting our observations, atypical chemokine receptors, such as CCRL1, are known to be involved in adherence to endothelium and the extravasation from blood vessels . FurtherAfter performing co-staining and correlation analyses of the studied molecules with stemness-associated markers, and realizing expression studies in both stem-like cells generated from commercial GBM cell lines and patient-derived primary cultures, our results showed, in a first using this approach, an association between CCRL1, SLFN13, Cables1, DCHS1, and SKI, and stemness. Indeed, all the molecules studied were clearly expressed in GSCs and exhibited co-staining with OCT4, Sox2, and KLF4 to varying extents, underscoring the results of correlation analyses. Among them, CCRL1, SLFN13, and SKI particularly showed a correlation with the expression of OCT4 and KLF4. When we examined regulation during TMZ-promoted entry and exit from dormancy in GSCs, CCRL1, SLFN13, Cables1, DCHS1, and SKI were regulated in complex patterns, confirming our results from native GBM cell lines and patient-derived primary cultures. When neurosphere formation assays were performed from TMZ-treated native GBM cells, the ability to form neurospheres and the expression of stemness markers indeed increased during treatment. Finally, gene set enrichment analyses indicated the importance of SKI in the phenomenon of stemness in particular. Consistent with our findings, Arslan et al. previously reported SLFN family members of SLFN13 to be expressed in GSCs . AdditioDespite not being explored in GSCs yet, CCRL1 and Cables1 were shown to be connected to stemness. Whereas CCRL1 was found to label mesenchymal subpopulations in an alveolosphere model of mice , Cables1Although one limitation of our study is the limited amount of cell lines and primary cultures and the small sample sizes included, which prohibits the generalization of the results, our study points to an involvement of CCRL1, SLFN13, Cables1, DCHS1, and particularly SKI in TMZ-promoted dormancy and reveals their connection to the phenomenon of stemness. It seems that the roles of the markers in this disease are complex and also include the tumor microenvironment. However, our study provides basic descriptive research with initial insights into the functions of the selected genes during GBM progression. Further studies are needed to elucidate the detailed impact and function of the selected genes in GBM. GBM still depicts an incurable disease due to phenomena such as dormancy—a reversible growth arrest even promoted by the standard-of-care TMZ itself—and stemness. These complex mechanisms, which contribute to the high therapy resistance of the disease, consist of a large number of downstream factors, whose activities partly overlap and are still not fully understood. In our study, CCRL1, SLFN13, SKI, Cables1, and DCHS1 were all shown to be regulated under TMZ-promoted dormancy and, besides tumor cells, to be expressed by endothelial cells and tumor-associated microglia/macrophages. Moreover, all of the markers, and of particular importance, SKI, were shown to be related to stemness, which highlights the connection between TMZ-promoted dormancy and this phenomenon. Future research is required to investigate the distinct function of CCRL1, SLFN13, SKI, Cables1, and DCHS1 in GBM. Only by understanding the mechanism involved will it be feasible to overcome the enormous therapy resistance and improve the disastrous outcome of GBM patients in the future.