Arabidopsis (GASA) gene family is a class of functional cysteine-rich proteins characterized by an N-terminal signal peptide and a C-terminal-conserved GASA domain with 12 invariant cysteine (Cys) residues. GASA proteins are widely distributed among plant species, and the majority of them are involved in the signal transmission of plant hormones, the regulation of plant development and growth, and the responses to different environmental constraints. To date, their action mechanisms are not completely elucidated. This review reports an overview of the diversity, structure, and subcellular localization of GASA proteins, their involvement in hormone crosstalk and redox regulation during development, and plant responses to abiotic and biotic stresses. Knowledge of this complex regulation can be a contribution to promoting multiple abiotic stress tolerance with potential agricultural applications through the engineering of genes encoding GASA proteins and the production of transgenic plants.Gibberellic acid-stimulated  Arabidopsis thaliana L., where GASA (Gibberellic acid-stimulated Arabidopsis) is one of those proteins  with an array of cysteine-rich (Cys) peptides regulated by gibberellins (GAs)  (where X can be any of the 20 proteinogenic amino acid residues except for cysteine) [OsGSR1, which is involved in the regulation of GA and BR crosstalk through an interaction with brassinosteroid (BR) synthase DIM/DWF1 protein [GASA proteins are typically small (~7 kDa) and positively charged, while Cys-rich proteins  are invotability . The pretability ,22,34,43tability . The conysteine) . While tysteine) , while iysteine) . Previouysteine) . GASA prysteine) . GASA pr protein ; potato  protein . Crystal protein . A helix protein ,72. AccoArabidopsis, AtGASA4 and AtGASA6 are located at the cell periphery if they contain a signal peptide. However, they are found in the nucleus if the signal peptide is missing [Petunia hybrida’s GASA) is localized in the ER membrane. Just like GIP1, GIP4 is potentially localized in the ER membrane. However, based on their cleavable hydrophobic N-terminal segment, GIP2 and GIP5 are estimated to be localized in the cell wall [Nicotiana benthamiana agro-infiltrated leaves contain potato StSN1—GFP fusion proteins, which are located throughout the plasma membrane [A series of experiments have attempted to determine where the GASA proteins are located in planta, as the protein’s function is largely related to its subcellular location. Although the function of a GASA protein is related to its GASA domain, its subcellular location is linked to its signal peptide. This implies that such a protein may belong to a class of secreted proteins. Bouterra et al.  showed b missing . The locell wall . In addiell wall . The citell wall . Nicotiamembrane . Importamembrane . CollectGASA genes was determined in different tissues and organs in many studies. Overall, these studies demonstrated that GASA genes are differentially expressed in different organs regarding spatial and temporal regulation. For example, in potato, Snakin-1 transcripts are found to be widely present in axillary, stem, floral buds, and fully developed petals. However, transcripts were not found in roots, stolon, or leaves [Snakin-1 promoter’s activity declines over time as the plant ages [Snakin-2 is developmentally expressed in tubers, stems, flowers, shoot apex, and leaves, but not in roots [Snakin-1 and Snakin-2, the third potato Snakin (Snakin-3) is expressed in roots, stems, and axillary buds [OsGASR1 was only found in florets with high levels, whereas OsGASR2 was found in both florets and branches, but it was not present in mature and flag leaves. This indicates that OsGASR1 and OsGASR2 are important in meristems and the development of panicles [OsGASR9 transcripts were detected in high levels in panicles, while in leaves, they were low [GASA genes were observed. However, three of these genes  are more active in fruits [FaGAST1 is mainly expressed in ripe fruits and roots [TdGASA2, TdGASA5, TdGASA9, TdGASA14, TdGASA18, and TdGASA19 were revealed in leaves, whereas TdGASA17 was accumulated in stems. The TdGASA6, TdGASA11, and TdGASA15 genes showed significantly greater expression in roots than in other tissues. Although the expression levels differ across tissues, TdGASA3 showed a high expression in all tissues [TdGASA3, MsSN1 expression was found in all tissues studied in alfalfa, including roots, stems, leaves, and immature floral buds [Peltophorum dubium’s developing seedlings, PdSN1 transcript levels are 40 times higher than in adult leaves [VvGASA1 and VvGASA2 genes showed high levels in grapevine leaves, while VvGASA9 and VvGASA10 genes were high in fruits and seeds [Hevea brasiliensis tree, snakin-1 was accumulated in the early stages of leaf development [Arabidopsis, the AtGASA14 gene expression was detected in young leaves and the elongation zone of roots [AtGASA4 promoter-directed GUS has strongly stained in the vegetative shoot apical meristems and imitating leaves [AtGASA5 gene is active in the root hairs, the basal portion of the roots, the shoot apex, and the inflorescent meristems [ZmGSL2, 4, 6, and 9 are expressed in newly formed lateral root primordia, indicating that GASA genes play a role in lateral root development [GASA genes are most active at specific developmental stages. In petunia, GIP2 was expressed in the elongating stem and corollas, whereas GIP4 and GIP5 are expressed at earlier development stages [SN1 promoter has been shown to be active in the early stages of the plant and gradually decreases as the plant ages [CrGASAs genes family of C. rosea and reported that CrGASAs are expressed at higher levels in the flowers or fruit than in the leaves, vines, and roots.The expression of r leaves , while ir leaves . Moreoveant ages . Snakin-in roots . Unlike ary buds . In ricepanicles . OsGASR9were low . In an an fruits . In strand roots . In durural buds . In Peltt leaves . The trand seeds . In Heveelopment . In Arabg leaves . Howevereristems . The in-elopment . Additiot stages ,80. Furtant ages . Moreoveant ages  studied GASA genes are tissue/developmental stage-specific expressed. The majority of them are highly expressed in young plant tissues and organs, in the vigorous growth site, or in reproductive and storage organs, indicating their role in plant growth and development as well as in the first line of defense.Overall, these findings support that the GASA family are involved in numerous physiological processes in plants where members of the same GASA family may have similar, different, or opposite functions. Interestingly, they all seem to be associated with young tissues and organs that are actively growing, which suggests that GASA genes are engaged in biological activities like cell division or expansion. Indeed, the simultaneous suppression of AtGASA4 and AtGASA6 leads to late blooming in Arabidopsis. However, early flowering is achieved by an overexpression of AtGASA6 [AtGASA4 in transgenic plants results in a reduction of seed weight and yield, as well as an abnormal shoot and flower phenotype, while overexpressing it leads to an increase in seed weight and yield. [AtGASA5 in Arabidopsis reduces stem growth rate and delays flowering AtGASA5 delays the onset of flowering by increasing the expression of flowering repressor FLC (Lowering Locus C) and decreasing the transcript levels of the flowering factors FT (Flowering Locus T) and LFY (Leaf Y) [St-GSL1 (StSN1) altered the cell-wall composition of leaves, influenced cell division and metabolism, and led to a smaller size of leaves [GEG and PRGL have opposite functions, while PRGL increases the size of petals by promoting cell elongation [GEG limits the size of petals by inhibiting cell elongation [GIP4 and GIP5 play a role in cell division, whereas GIP1, GIP2, and tomato GAST1 seem to display a similar ability to enhance stem elongation by promoting cell elongation [ZmGSL2, 4, 6, and 9 genes are detected in emerging lateral root primordia in maize, revealing their function in lateral root development [FaGAST1 resulted in a delay of the plant and a reduction in the size of fruits caused by an inhibition of the cell elongation during fruit development [OsGASR9 positively regulates maize grain size and yields [TuGASR7 in wheat (Triticum urartu) exhibited pleiotropic effects on grain weight and yield [VvGASA5 was highly expressed in seedless fruits but undetectable in seeded fruits, which suggests its involvement in ovule abortion [GASA genes were highly induced in young tissues during proliferation and contributed to the panicle differentiation process with a gain in grain size/weight [GASA genes are highly induced during the seedling and flower stage [Members of the  AtGASA6 . Silencid yield. . The ove(Leaf Y) . Additiof leaves . In gerbongation ,82, but ongation . Petuniaongation ,46. The elopment . In straelopment . In contd yields . Similarnd yield . In grapabortion . Furthere/weight ,64,84,85er stage .CcGASA4, of Citrus, was shown to inhibit the synthesis of lignin and flavonoids and may play a role in plant–pathogen interactions, inhibiting growth, and affecting flowering development [elopment .GASA genes may be involved in cellular processes like cell division or expansion, as they all correlate with young tissues and actively growing organs.Interestingly, 3) participates in various plant developmental processes, including flowering [GASA family genes have been reported to be modulated by GA3, abscisic acid (ABA), and other phytohormones [GASA genes are responsive to exogenous GA3 treatment, and the transcript level of six out of 15 AtGASA genes (AtGASA4/6/7/8/13) are shown to have increased transcript levels after GA3 treatment [GIP (GIP1/2/4/5) genes [GASA genes, maize ZmGSL1/2/4/6/9 [OsGASR1/2 and OsGSR1 [Salvia miltiorrhiza SmGASA4 [Fagus sylvatica FsGASA4 [HbGASA4-2/7-1/13/14-1/16 [MdGASA1/6/7/19 [GASA genes [3. However, GA does not similarly affect all GASA gene expressions. Arabidopsis AtGASA1/5/9/11 [snakin-2 [MdGASA13/26 [3. GASA genes’ response to exogenous GA3 also seem to be different depending on the tissue or the development stage, such as in the case of soybean GsGASA1, which is upregulated in leaves but downregulated in roots [Arabidopsis AtGASA4 is repressed in roots and leaves but promoted in meristem tissues [MdGASA5, which is promoted initially but becomes inhibited during the flower-induction period [GASA is derived from their responsiveness to GA3, some genes are unaffected by it like AtGASA2/3/10/12/14/15 and SN1 gene [Phytohormones are frequently recognized as growth regulators, but they also play a significant role in response to various stresses both biotic and abiotic. Gibberellic acid  genes . Just li/2/4/6/9 , rice Osd OsGSR1 , Salvia  SmGASA4 , Fagus s FsGASA4 , HbGASA4/14-1/16 , apple M1/6/7/19 , and allSA genes  are upresnakin-2 , and appASA13/26  are downin roots . Arabidon period . AlthougSN1 gene .3, GASA proteins are also responsive to exogenous ABA. Indeed, ABA enhances AtGASA2/3/5/14 expression but reduces the expression of AtGASA7/9 in Arabidopsis [TdGASA genes except for TdGASA10 in durum wheat [snakin-2 in potato but reduces that of snakin-3, while snakin-1 is not affected by ABA [MdGASA expressions are promoted by ABA [Hevea brasiliensis, HbGASA4-2/14-1/15 are highly responsive to exogenous ABA [GASA genes can also be affected antagonistically by ABA and GA, such as in the case of snakin-2 in potato [FsGASA4 in Fagus sylvatica [GIP1 in petunia [GsGASA1 in Glycine soja [GAST1 in tomatos [GASA genes can also be induced by other phytohormones. In Hevea brasiliensis, HbGASA7-1/14-1/14-3/15/16 is upregulated by jasmonic acid (JA), while HbGASA4-2/14-1/15/7-1 is slightly responsive to salicylic Acid (SA) where HbGASA15/7-1 shows continuous expression after 24 h of treatment [GASA gene expression is either promoted or inhibited by phytohormones, it can in turn influence the level of some phytohormones. While OsGARS1 expression is promoted by GA, it activates a BR biosynthetic enzyme to regulate BR levels, which in turn inhibits its expression [snakin-1 gene in potato plants induced reactive oxygen species (ROS), SA, and GA accumulation, and ABA and sterol biosynthesis decrease [FsGASA4 promotes the expression of SA biosynthesis-related genes, which positively impacts the levels of endogenous SA [AtGASA6 was integrated with the GA, ABA, and glucose-signaling pathways to achieve the regulation of seed germination by promoting cell elongation [Alongside GAum wheat ; it alsod by ABA ,57. In ad by ABA , and in nous ABA . GASA geylvatica , GIP1 in petunia , GsGASA1ine soja , and GAS tomatos . GASA gereatment . While Gdecrease . Moreoveenous SA . Furtherongation .Collectively, these results proved that GASA proteins maintain redox balance and play essential roles in complex crosstalk among several hormonal signaling pathways. Therefore, they are involved in the development and plant responses to environmental stressors.GASA genes are highly implicated in abiotic stress responses [OsGASR1 in rice is induced by UV irradiation [TdGASA1 in durum wheat was increased following the exposure of durum wheat seedlings to salt and osmotic treatment [TdGASA1 gene exhibited enhanced growth compared to the control cells under NaCl, mannitol, LiCl, H2O2, and heat treatments [CrGASAs showed habitat- and environmental-stress-regulated patterns in C. rosea and the heterologous induced expression of some CrGASAs in yeast-enhanced tolerance to H2O2. In addition, some CrGASAs showed elevated heat tolerance and heavy metal (HM) cadmium/copper (Cd/Cu) tolerance. Other reports support that AtGASA14 is positively regulated by abiotic stresses [AtGASA5 gene expression is negatively affected by abiotic stress, especially heat stress [TaGASA1 (homolog of rice OsGASA1 gene) was involved in heat-stress responses. In rice, the highest OsGASA1 transcript level was induced by salt treatments [OsGASA3, also showed the highest transcript level under salt stress [Arabidopsis AtGASA4 overexpression enhances heat-stress tolerance. Sun et al. [AtGASA14 is involved in abiotic-stress responses via modulation of reactive oxygen species (ROS) accumulation. Other reports suggest that the heat-induced expression of AtGASA5 gene promotes SA signaling regulation and heat-shock-protein accumulation [Fagus sylvatica FsGASA4 gene expression in Arabidopsis lines confers tolerance to salt, oxidative, and heat stresses [TaGASA1 from wheat, which is the homolog of OsGASA1, was regulated by heat stress. Indeed, in rice, the highest transcript level of rice OsGASA1 was regulated by salt and ABA stresses [OsGASA3 from rice showed a high accumulation of transcript by salt stress [OsGASA family genes in responses to biotic stress have not been well studied so far. Recently, in the cacao plant, TcGASA1/14 transcript levels were shown to be induced under osmotic and salt stress, while the TcGASA16/17 transcript showed the opposite result [GsGASA1 isolating from Glycine soja was reported to be involved in inhibiting root growth via the accumulation of DELLA proteins under chronic cold stress [GASA5-overexpressing plants, and GASA5 is downregulated by exogenous GA3. Thus, GA signaling may mediate the degradation of the GAI protein through GASA5 [Phaseolus vulgaris, Pvul-GASA-18 expression is enhanced under salt stress in all tissues. However, Pvul-GASA-1 was induced in leaves and inhibited in roots, while Pvul-GASA-16/23 levels were not affected in roots but decreased in leaves under the same conditions of salt stress [Canavalia rosea, all CrGASA genes were promoted in leaves after 2 h of Mn treatment and after 48 h in roots. CrGASA also showed an increase in transcript levels after long-term treatment of Zn and Cu. However, CrGASA3/5/10/1 was initially promoted but then inhibited after 48 h of Cd treatment in both leaves and roots. Under salt stress, CrGASA2/14/16 showed a temporary peak. However, only CrGASA7/16 was responsive to heat stress [TdGASA genes seem to be responsive to salt and osmotic stress, and the overexpression of TdGASA genes in yeast showed better growth compared to non-transgenic control yeast under salt, osmotic, LiCl, H2O2, and heat stress [CrGASA genes in which overexpression enhanced H2O2 resistance in transgenic yeast and complemented Cd sensitivity, while there were no obvious effects on yeast cells treated with Zn, Co, Ni, or Mn [GASA gene from tobacco is expressed in yeast alleviated Cd toxicity [SmGASA4 gene isolated from S. miltiorrhiza was involved in secondary metabolites biosynthesis and its ectopic expression in Arabidopsis lines promotes their development and abiotic stress tolerance [Numerous studies support that esponses ,68,91. Fadiation . The expreatment . Indeed,eatments . The expt stress . In the t stress  proved tt stress . Ko et at stress  reportedmulation . Similarstresses . Zhang estresses  demonstrt stress . Howevere result . GsGASA1d stress . The DELgh GASA5 . On the t stress . In Canatoxicity . In the olerance . OverallGASA family members can influence ROS accumulation [Arabidopsis overexpressing AtGASA4 by repressing the accumulation of H2O2 and nitric oxide in wounded leaves [FsGASA4, it also enhances oxidative stress tolerance [2O2 promotes GIP2/4/5 expression, the overexpression of GIP2 in petunia prevents the accumulation of H2O2 caused by osmotic stress or ABA in stomatal guard cells and wounded leaves [Although ROS serves as a secondary messenger in many important physiological processes, such as cellular signaling transmission, it can also cause oxidative damage when exposed to a variety of environmental stressors, such as salinity and heavy metals . The GASmulation ,6,23,89.olerance . While HSN1 silencing lines, indicating an altered redox balance [SN1-silencing lines compared to wild-type plants. This supports the hypothesized role for this molecule in regulating cell division, further suggesting that SN1 may perform its action by regulating ascorbate accumulation [AtGASA4 inhibits ROS accumulation and provides partial resistance to NO donor sodium nitroprusside (SNP) in seeds. Indeed, E. coli expressing either the whole AtGASA4 or a shortened AtGASA4 with only its GASA domain intact, was resistant to SNP, but mutant GASA4 lost its redox activity and capacity to trigger GA responses when conserved cysteines were replaced by Alanine [Additionally, higher levels of ROS were detected in  balance . Furthermulation . The GAS Alanine . In summGASA genes are also induced by biotic stress like viruses, fungi, and bacteria, which suggests their involvement in the plant’s innate immune system [StSN2) [GASA genes was based on their expression profile [snakin-1 or 2 in transgenic potato and tomato plants enhanced tolerance to Rhizoctonia solani and Erwinia carotovora [Gaeumannomyces graminis var. tritici [snakin-2 gene in Nicotiana benthamiana, induced susceptibility to Clavibactermi chiganensis [snakin-1 gene affects cell wall composition, cell division, and leaf primary metabolism, suggesting that StSN1 may also be involved in numerous cellular processes [StSN1 and StSN2 play a large spectrum of anti-bacterial and anti-fungal bioactivity [StSN1, MsSN1, and Snakin-1 from alfalfa and Solanum chacoense, respectively, it has proven in-vitro and in-vivo antimicrobial activity against several bacterial and fungal pathogens [Snakin-3 expression was linked to the plant defense process, as its gene expression levels were significantly induced upon pathogen infection. Intriguingly, HbGASA genes from the rubber tree were regulated by C. gloeosporioides  where HbGASA7-1/15/16 transcript levels increased while HbGASA6 transcript levels decreased after one day of inoculation [TcGASA was highly expressed in tolerant Cacao after 24 h of P. megakarya inoculation [CcGASA4 transcript levels increased significantly in leaves after an infection with Citrus tristeza virus [Solanum chacoense snakin-1, which had a reduced and delayed infection with Blumeria graminisf. sp. Tritici [StSN1 and StSN2 expression under the control of the potato light-inducible Lhca3 promoter led to enhanced resistance against blackleg disease with no morphological penalties in potato plants [OsGASR3 from rice-mediated defense against pathogens and plant development in growing seedlings and during panicle formation.Like hormones and environmental stress, e system . GASA ise system  and Snak [StSN2)  are the  [StSN2) ,57,61. T profile ,98 and t profile ,99,100. rotovora ,99,100,  tritici . Howeverganensis . In addirocesses . In vitractivity . Consistathogens ,50. Nahiathogens  showed tculation . Similarculation . Additioza virus . Moreoveo plants  suggest turnip mosaic virus and Soybean mosaic virus resistance was enhanced in GmSN1 transgenic Arabidopsis and soybean [Citrus tristezavirus, the citrus homolog gene CcGASA4 is highly induced in citrus leaves [CaSn was confirmed to be activated by nematode infections and plays a major role in its host defense [Interestingly, the GASA family genes protect plants from viruses and nematodes besides their antifungal and antibacterial activity. Additionally,  soybean . After as leaves . Pepper  defense .E. coli, Pichia pastoris, and, more recently, in baculovirus/insect cells [StSN1 has been shown to have a significant inhibitory effect against some food spoilage yeasts, but it does not pose a risk to human consumption [Intriguingly, GASA proteins are attractive biotechnological targets due to their biological properties, particularly for the creation of novel agents for disease control . Heterolct cells , which ect cells ,58,59,71sumption . This suggests that the GASA peptides could be used to protect food, pharmaceuticals, or cosmetics from microorganisms’ decomposition.GASA family play in plants, there are still a few unanswered questions. To investigate some of the GASA peptides’ more significant and specific characteristics, further in-depth structural and functional confirmations are required. On the other hand, these proteins have been shown to function as antioxidants, but the nature of this antioxidant activity and whether it has a direct or indirect effect on physiological responses and development are still unknown. Certainly, protein–protein interaction analysis would better clarify the function of this family. Finally, it requires further in-depth studies to uncover the underlying mechanism(s) and the contributions of these valuable proteins before their future agricultural applications.Crop-yield losses are primarily caused by environmental constraints. This situation is compounded further by climate change, the limited availability of land, and the rapid spread of devastating diseases. It is urgent to cultivate plants that can better withstand both biotic and abiotic stresses to achieve food security. This will necessitate a thorough understanding of the various mechanisms that control stress tolerance. Several studies demonstrated the central role played by different families of GASA proteins during biotic and abiotic stresses. In the meantime, they play active roles in numerous aspects of plants’ growth and development process. They have great biotechnological potential in the fields of pathology and agronomy due to their outstanding properties. Despite the progress in our understanding of the significant function that the genes of


CDKN3) in ccRCC. The ccRCC cohort from the Cancer Genome Atlas Program was accessed through the UCSC Xena browser to obtain CDKN3 mRNA expression data and their corresponding clinicopathological variables. The independent prognostic signature of CDKN3 was evaluated using univariate and multivariate Cox logistic regression analysis. Gene set enrichment analysis and co-expression gene functional annotations were used to discern CDKN3-related altered molecular pathways. The tumor immune microenvironment was evaluated using TIMER 2.0 and gene expression profiling interactive analysis. CDKN3 upregulation is associated with shortened overall survival  in the Cancer Genome Atlas Program ccRCC cohort. Univariate  and multivariate  Cox logistic regression analyses indicate that CDKN3 is an independent prognostic variable of the overall survival. High CDKN3 expression is associated with enrichment within the following pathways including allograph rejection, epithelial–mesenchymal transition, mitotic spindle, inflammatory response, IL-6/JAK/STAT3 signaling, spermatogenesis, TNF-α signaling via NF-kB pathway, complement activation, KRAS signaling, and INF-γ signaling. CDKN3 is also associated with significant infiltration of a wide spectrum of immune cells and correlates remarkably with immune-related genes. CDKN3 is a poor prognostic biomarker in ccRCC that alters many molecular pathways and impacts the tumor immune microenvironment.Cell cycle regulatory proteins plays a pivotal role in the development and progression of many human malignancies. Identification of their biological functions as well as their prognostic utility presents an active field of research. As a continuation of the ongoing efforts to elucidate the molecular characteristics of clear cell renal cell carcinoma (ccRCC); we present a comprehensive bioinformatics study targeting the prognostic and mechanistic role of cyclin-dependent kinase inhibitor 3 ( Globally, there is a 3:2 male predominance, with a peak incidence in the sixties and seventies. The prognosis of RCC patients varies considerably based on age, clinical stage, and pathological classification. During the past decade, a pressing need to explore new biomarkers and potential therapeutic targets has emerged. RCC risk factors include obesity, hypertension, and smoking. These factors are widely recognized as major contributors to RCC. Although some studies have suggested other associations with RCC, including a possible protective effect of alcohol consumption, a negative effect of red meat consumption, and occupational exposure to carcinogens, the data on these factors and their relationship to RCC are not fully elucidated.–8Primary malignant renal tumors represent an aggressive and heterogenous group of malignancies. The most prevalent type is renal cell carcinoma (RCC), which constitutes around 1% to 3% of all cancers and 90% of kidney neoplasms. Generally, structural alterations of the short arm of chromosome 3 are observed in RCC patients. To date, certain genome-wide association studies of RCC have identified 6 susceptibility loci on chromosome regions 2p21, 2q22.3, 8q24.21, 11q13.3, 12p11.23, and 12q24.31.–14 Moreover, genetic studies on familial RCC have revealed some critical genetic mutations in a number of genes involved in different cellular processes , which have also been linked to the development of some sporadic RCC cases.,16 Some of these genetic variations have been associated with distinct autosomal dominant syndromes each with its own genetic basis and phenotypic manifestations. Among them, von Hippel-Lindau syndrome, hereditary papillary renal cell carcinoma, Birt-Hogg-Dubé syndrome, hereditary leiomyomatosis cell carcinoma, and tuberous sclerosis.Approximately 97% of RCC cases occur sporadically, devoid of any family history or genetic predisposition, while the remaining 2% to 3% have been identified due to causative genetic events.CDKN3 gene is mapped to14q22 encoding the CDKN3 protein. It belongs to the dual-specificity protein phosphatase family, which possesses dephosphorylation activity by interacting with CDK2 kinase at Thr160, thus preventing its activation. Due to the role of Thr160 phosphorylation in activating CDK2 and promoting cell cycle progression, CDKN3 upregulation leads to the suppression of G1-S phase transition. Further, it is recognized as an MDM2 binding protein that can form a complex with p53 and MDM2, leading to the repression of p21 induction and the promotion of the cell cycle. Conversely, Srinivas et al revealed that cell cycle inhibition is controlled by binding to the MSP1 region of the centrosome and blocking the formation of abnormal spindles. Previous studies have reported different expression patterns of CDKN3 in several types of cancers. However, the effect of CDKN3 on tumorigenesis and the molecular mechanisms involved remains unclear. In the majority of cancer types, CDKN3 functions as an oncogene and its gene expression is upregulated, including, nasopharyngeal, cervical, lung, prostate, breast, esophageal, liver, and renal cancer cells. Thus, it promotes tumorigenesis and is negatively correlated with survival. However, studies on gastric cancer, leukemic, and glioblastoma cell lines found that CDKN3 overexpression has been associated with the inhibition of cell proliferation and metastasis promotion.–28 In contrast, CDKN3 is a tumor suppressor gene and found to be downregulated in brain tumors.Aberrant expression of cell cycle regulatory genes plays a vital role in cancer progression. These regulatory elements are considered potential survival markers and therapeutic targets. There is increasing evidence that cyclin-dependent kinase inhibitor 3 (CDKN3) has significant regulatory roles in cancer development. CDKN3 expression in RCC has been conducted.The use of bioinformatics in oncology has become a prevalent multidisciplinary tool to uncover potential genetic targets implicated in the development of neoplasm and to assess drug responsiveness. Such an approach can provide valuable insights into the molecular mechanisms of tumor pathogenesis, central signaling pathways, and cellular activity networks involved in RCC. In the current study, a comprehensive bioinformatics analysis evaluating the prognostic potential of CDKN3 mRNA expression in ccRCC patients. Cancer Genome Atlas Program (TCGA) level 3 expression data along with the corresponding clinicopathological variables were retrieved using the California Santa Cruz Cancer Genomics Browser .CDKN3 expression from tumor samples and normal tissues adjacent to the tumor (NAT) were obtained in a normalized RNA-Seq by expectation maximization count transformed as log2(x + 1). Clinicopathological parameters include age, gender, International Society of Urologic Pathologists grade, TNM scoring system, and the American Joint Committee on Cancer stage. The primary endpoints were the overall survival (OS) and progression-free interval (PFI). The ccRCC cohort was manually curated by omitting patients with OS time of 0 and patients without CDKN3 expression data. ccRCC cohort was also divided into 2 subsets based on CDKN3 expression (high vs how expression) with a cut-point determined by X-tile software as previously described.The main objective of this work is to investigate the prognostic potential of  In brief, IBM SPSS statistical package for Windows v.26  and GraphPad Prism v.9.3.1  were utilized for conducting statistical analyses and generating graphs. The presentation of nominal data included frequency (percentage). Normally distributed continuous variables were represented using mean ± standard deviation of the mean or standard error of the mean, while non-normally distributed data were described using median (interquartile range). The assessment of normality involved the Kolmogorov-Smirnov test, Shapiro–Wilk test, and analysis of quantile-quantile plots. To analyze the relationship between CDKN3 expression status and clinicopathological variables, several statistical tests were utilized. Categorical variables were evaluated using the Chi-square test or Fisher exact test. Paired t-test was applied for normally distributed paired samples, and unpaired t-test and Welch corrected unpaired t-test were used for normally distributed non-paired samples, taking into account variance equality. Non-normally distributed data were analyzed using Wilcoxon matched pairs test and Mann–Whitney U-test.Statistical analysis was performed as previously described.CDKN3 expression status on OS and PFI. The log-rank test was used to identify statistical differences across survival curves, and the outcomes were reported with 95% confidence intervals (95% CI) and hazard ratios (HR). CDKN3 expression data were evaluated for predicting the aforementioned endpoints. The predictability power was evaluated with receiver operating curve analysis. Univariate and multivariate Cox logistic regression models were applied to assess the independent prognostic significance of clinicopathological variables and CDKN3 expression. Prior to Cox logistic regression analysis, the variables were dichotomized as follows: age (reference: ≤53 years), gender , pT stage (reference: T1 + T2), pN stage (reference: N0), American Joint Committee on Cancer stage (reference: stage 1 + 2), ISUP grade (reference: grade 1 + 2), and CDKN3 expression (reference: low). All statistical tests conducted were two-sided, and a significance level of P ≤ .05 was considered to indicate statistical significance.Kaplan–Meier survival methods were employed to examine the impact of CDKN3 signature, a specialized GSEA was conducted.,34 GSEA involved a comprehensive exploration of gene expression patterns, comparing 2 distinct groups based on their CDKN3 expression levels (high vs low) using the C1 gene sets . The GSEA analysis incorporated 1000 permutations using the “gene set” permutation type, utilizing the Human_UniProt_IDs chip platform. Significance of gene set enrichment was determined by an adjusted P value of ≤ .001 and a false discovery rate (FDR) below 0.25.To investigate the underlying molecular mechanisms related to the prognostic CDKN3-related interacting genes were browsed using STRING v.11 (https://string-db.org). Significant interactions were labeled if a combined score ≥ 0.4 was observed based on phylogenetic co-occurrence, homology, co-expression, experimentally determined interaction, and automated text mining scoring. The maximum number of interactions was limited to 50.Retrieval and construction of http://www.linkedomics.org/login.php) was accessed to analyze CDKN3-related co-expressed genes within the TCGA ccRCC cohort. A gene was considered statistically significant with a Spearman correlation’s P-value ≤ .05 and FDR ≤ .05. Co-expressed genes were functionally annotated using GSEA within the gene ontology (GO) terms including biological process, molecular function, cellular component. In addition, the Kyoto encyclopedia of genes and genomes (KEGG) pathway classification and micro-RNA (micro-ribonucleic acid) target prediction ports were applied as well. The rank criteria were set to the P-value with a minimal number of 3 genes per set and 500 simulations.The LinkedOmics database (https://cistrome.shinyapps.io/timer/); a comprehensive resource that provides a systematic and extensive analysis of immune infiltrates across a wide spectrum of human malignancies. TIMER functions through a well-established statistical methodology known as deconvolution to infer the abundance of tumor-infiltrating immune cells from gene expression profiles. Immune components infiltration was reported using Spearman correlation coefficient and its associated P-value.Tumor immune infiltration was evaluated using TIMER 2.0 . The correlation was reported with Spearman correlation coefficient and its associated P-value within the TCGA ccRCC, TCGA NAT, and GTEx normal kidney cortex cohorts.Selected genes known to influence significantly correlated immune cells were subjected to correlation analysis with CDKN3 in comparison to the corresponding normal tissues in the TCGA database , papillary, and clear cell renal cell carcinomas (KIRC). The latter is the focus of the current study.A pan-cancer analysis has been conducted to evaluate the expression of ase Fig. A. CDKN3 CDKN3 expression is significantly upregulated in ccRCC tissues compared to NAT  in comparison to the low expression group  as shown in the receiver operating curve analysis  , grade , stage , pT , pM , and CDKN3 expression . Both gender  and pN  did not exhibit significant predictability. PFI univariate Cox logistic regression illustrated the same statistical trend in the following variables; age , gender , grade , stage , pT , pM , and CDKN3 expression , except for the pN .Univariate Cox logistic regression was utilized to evaluate the prognostic impact of CDKN3 expression in the OS and PFI with the elimination of confounding variables, multivariate Cox logistic regression was used , grade , stage , pM , and CDKN3 expression . In contrast, gender , pT , and pN  predictability did not reach statistical significance. Figure P = .022), grade , stage , and pM  were significantly different compared to age , pT , pN , and CDKN3 expression  which did not exhibit any significance.To test the absolute predictability of sed Fig. E and F. CDKN3 expression group in comparison to the low expression cohort using several gene sets  with an FDR ≤ 0.05. In contrast, only 5 molecular functions achieved the significant threshold including structural constituent of ribosome, cyclin-dependent protein kinase activity, catalytic activity acting on DNA, nucleosome binding, and threonine-type peptidase activity. Co-expressed genes were also mapped to the following KEGG pathways involved in tumorigenesis of ccRCC including cell cycle, ribosome, p53 signaling pathway, proteasome, pyrimidine metabolism, cellular senescence, homologous recombination, DNA replication, drug metabolism, base excision repair, mismatch repair, and cytosolic DNA-sensing pathway. Through miRNA target prediction, across the significantly enrich targets non scored an FDR ≤ 0.05 except for a negatively enriched ACACTGG, MIR-199A, and MIR-199B.LinkedOmics was utilized to identify positively and negatively significant ort Fig. B–D folloort Fig. E and KEGCDKN3 expression and CD8+ cells , FH Tcells , γδ T cells , Tregs , TNK cells , macrophages , M0 macrophages , M1 macrophages , M2 macrophages , CAF , neutrophils , mDCs , CD34+ cells , and MDSC . In contrast nonsignificant correlations were observed in CD4+ T cells , NK cells , monocytes , eosinophils , mast cells , CLP cells , CMP , and GMP .To investigate the tumor immune infiltration of ccRCC; TIMER server was utilized Fig.  and a siCDKN3 expression and immune genes of various immune cell types, including but not limited to CD8+ T cells, T cells , B cells, monocytes, TAMs, M1 and M2 macrophages, neutrophils, NK cells and mDCs, in KIRC normal and KIRC NATs. For comparative analysis, we utilized kidney cortex tissue as the control , CD2 , CD3D , CD3E , CD8A , CD8B , CD19 , CD68 , CD79A , CD86 , CD163 , CSF1R , IL10 , IRF5 , ITGAM , KIR2DL4 , MS4A4A , PTGS2 . VSIG4 , STAT4 , STAT1 , IFNG , FOXp3 , CCR8 , TGFB1  and GZMB  and CTLA4  Additionally, TBX21 , TNF , STAT6 , STAT5A , and STAT5B  show a relatively weak correlation with disease susceptibility. Moreover, the gene markers indicative of Th2 cells, M2 macrophages, Treg cells, and T cell exhaustion had the highest correlation with CDKN3 were GATA3 , CD163 , TGFB1 , and LAG3 , respectively.Furthermore, a comprehensive analysis of the interrelationships between CCL2 , CD1C , CEACAM8 , HLA-DPA1 , HLA-DPB1 , HLA-DRA , HLA-DQB1 , ITGAX  NOS2 , IL13 , BCL6 , STAT3  and IL17a , HAVCR2 , NRP1 , KIR2DL1 , KIR2DL3 , KIR2DS4 , KIR3DL1 , KIR3DL2 , and KIR3DL3 .The following correlations didn’t reach statistical significance including CDKN3 has been portrayed as a prognostic biomarker in ccRCC through a comprehensive bioinformatics analysis using the TCGA database. CDKN3 is associated with shortened OS and poor prognosis in ccRCC. Enrichment analysis has highlighted the following pathways to be affected by CDKN3 upregulation, including allograph rejection, epithelial–mesenchymal transition, mitotic spindle, inflammatory response, IL-6/JAK/STAT3 signaling, spermatogenesis, TNF-α signaling via NF-kB pathway, complement activation, KRAS signaling, and INF-γ signaling. In addition, CDKN3 expression correlated significantly with many immune cellular components and immune-related genes. Although the main role of CDKN3 is to inhibit the progression of the cell cycle, it is overexpressed in many types of malignancies such as gastric cancer, prostate cancer, hepatocellular, cervical, breast, and epithelial ovarian cancers which was in concomitant with expression pan-cancer analysis conducted.,39–42 Overexpression of CDKN3 in these malignancies is associated with inadequate prognosis, while CDKN3 in glioblastomas is considered a tumor suppressor gene. A study showed that CDKN3 prevents aneuploidy and it performs the complex task of managing cell division through a combination of direct pathways that involve regulating the SAC and the mitotic clock, as well as indirect mechanisms that involve preserving the integrity of centrosomes.,43In the current work,  Moreover, silencing or inhibiting of CDKN3 reduces the migration of breast cancer cells. Furthermore, silencing also increases apoptosis in gastric cancer cell lines and reduces survival by lowering the expression of different cell-regulating proteins such as CDK2, CDC25, and CCNB1/2 thus inhibiting proliferation and invasion of gastric cancer cells. Moreover, CDKN3 knockdown elicits an effect on human ovarian cancer cells, manifesting as a substantial reduction in their proliferative and invasive capabilities, concurrently with a remarkable elevation in apoptosis. In addition, CDNK3 silencing in nasopharyngeal carcinoma subdues its ability to proliferate. Hence, affecting carcinogenesis through the modulation of p27. It also decreased the phosphorylation of AKT while increasing the activated form of caspase 3 hence, increasing apoptosis in nasopharyngeal carcinoma. A recent work done on esophageal squamous cell carcinoma confirmed that the mechanism involved in the increase of tumor characteristics by CDKN3 such as migration, invasion, and cell proliferation was modulated through the activation of the AKT pathway. When CDKN3 was silenced, inhibited or knocked, it suppressed the migration and cellular proliferation in addition to invasion in esophageal squamous cell carcinoma. Downregulation in the expression levels of CDKN3 was found in high-stage HCC that have immature tumor cells. Paradoxically, knocking down CDKN3 increased the elements of AKT pathway with its downstream targets such as p21/p53 leading to cell survival. Furthermore, culture cells mimicking HCC with CDKN3 knocked down tolerated cisplatin more than cells expressing it. Thus, confirming the variation in CDKN3 expression in different types of malignancies. On the other hand, a more recent paper showed that there was a notable association between the expression of CDKN3 in HCC and a substantial increase in the OS time. Moreover, CDKN3 levels were increased compared to adjacent para-carcinoma tissues. Furthermore, upregulation of CDKN3 expression is positively associated with an increased incidence of HCC-related mortality. Macro- and micro-invasion were analyzed to explore the relationship with the levels of CDKN3. HCC with vascular invasion showed higher levels of CDKN3. A positive relationship with CTNNB1 was also observed. The same article showed that suppressing CDKN3 promotes the proliferation of HCC cells and confers a diminished sensitivity to Adriamycin chemotherapy. Overexpression of CDKN3 is associated with poor progression in prostate cancer and its inhibition significantly reduces cancer cell growth. It induced cells into G0/G1 arrest and apoptosis. Moreover, it inhibited the invasion of prostate cancer cells and lowered the expression of MCM2/MCM3, PCNA, and CDK2. Also, a mice model xenograft transfected with siRNA hindered the tumor progression of androgen-independent prostate cancer cells in an in vivo setting. All the aforementioned findings were observed through gene enrichment and co-expression analysis.A variety of studies found that CDKN3 played a crucial role in tumor progression. A study performed on esophageal carcinoma revealed that CDKN3 enhances tumor progression and chemoresistance against cisplatin through modulation and interaction of RAD51.CDKN3 overexpression xenograft model experiments found that tumors extracted from overexpressing CDKN3 cells were greater in size than the mock experiment. ZNF677 is a zinc finger protein-coding gene. It has recently been shown that its upregulation downregulates and inhibits CDKN3 through interaction with its promoter. As reported in the same study, CDKN3 correlated with poor prognosis and survival in RCC, and when inhibited, reduced prefiltration rates and increased apoptosis were observed in RCC cell lines. Furthermore, RCC cell lines CDKN3 knocked down had a reduced tumor size compared to the mock injection. Yin-Yang 1 (YY1) is a protein that is involved in transcriptional regulation and many biological processes such as proliferation, differentiation, and apoptosis. A study found a direct association between YY1 and CDKN3 in pancreatic cancer. Additionally, YY1 inhibited proliferation and migration by downregulating CDKN3 and higher CDKN3 levels correlated negatively with survival and prognosis. Additionally, overexpression of YY1 inhibited the p21/p53 pathway via CDKN3. CDKN3 is increased in BLC and correlated with poor prognosis and survival compared to BLC patients with low expression of CDKN3. Moreover, inhibition of CDKN3 showed lower cell proliferation, migration, and arrested cells in M0/M1 phases. CRC tissues had higher levels of CDKN3 expression than tissues surrounding CRC. It contributed to cellular proliferation and migration, as proven when CDKN3 was knocked down it had a lower colony-forming capacity and proliferation rate. Furthermore, CDKN3 expression had a negative correlation with tumor necrosis factor-α-induced protein 8-like 1. CDKN3 was found to modulate the resistance of CRC cells to cisplatin, thereby driving their proliferation. This was accomplished through the regulation of tumor necrosis factor-α-induced protein 8-like 1 by CDKN3. Another finding about CDKN3 involvement in cisplatin resistance in BLC showed that CDKN3 altered/inhibited GC chemoresistance in BLC cell lines.Although, the role of CDKN3 in RCC has been previously discussed through wide genetic associations and experimental results; its prognostic and mechanist role are not well understood. CDKN3 upregulation. The relationship between CDKN3 and miRNA is very well understood. miR-181a-5p is of a particular importance because in recent years it was found that it suppresses non-small cell lung carcinoma. There is a theoretical possibility that hsa-miR-181d-5p may regulate CDKN3 expression through the AKT signaling pathway, thereby potentially influencing the progression of non-small cell lung carcinoma. Additionally, CDKN3 was found to be expressed at high levels, in contrast to has-miR-181d-5p, which showed low levels of expression. Sequence prediction software showed has-miR-181d-5p has a binding site and interacts with the CDKN3 3′UTR. Furthermore, upregulation of has-miR-181d-5p or silencing/inhibiting CDKN3 demonstrated inhibition of cellular proliferation, increased apoptosis, inhibition of cellular migration/invasion, repression of the Akt signaling pathway, and inhibiting tumor growth in mice.GSEA identified a negatively enriched ACACTGG, MIR-199A, and MIR-199B to be affected by CDKN3 poor prognostic signature requires rigorous experimental evidence. Based on the available data, the impact of CDKN3 upregulation in modulating tumor immune microenvironment is still vague and requires further exploration.The study has multiple limitations mainly presented by its retrospective nature and moderate sample size. In addition, the TCGA database present a bulk RNA sequence data lacking the single cell RNA sequencing input for more precise analysis. The detailed molecular mechanisms behind the CDKN3 has been identified as a poor prognostic biomarker in ccRCC through bioinformatics analysis utilizing the TCGA cohort. GSEA highlighted several impacted molecular pathways. Immune correlations suggest that CDKN3 influences tumor immune microenvironment and modulates immune-genes expression.As an important element of cell cycle regulatory proteins; The leading author would thank the 6th year medical school surgery final exam for giving the time and inspiration to learn the basis of bioinformatics which was the core nucleus to this work.Conceptualization: Ahmed Hesham Al Sharie, Tamam El-Elimat, Yazan O. Al Zu'bi, Feras Q. Alali.Data curation: Abdulmalek M. Abu Zahra, Balqis M. Abu Mousa, Mohammad S. Bani Amer, Kinda Al-Kammash, Alma Abu Lil, Abubaker A. Al Malkawi, Zainab Alazzeh.Formal analysis: Ahmed Hesham Al Sharie, Reem F. Darweesh, Ayah K. Al-Khaldi, Balqis M. Abu Mousa, Mohammad S. Bani Amer, Kinda Al-Kammash, Yazan O. Al Zu'bi, Alma Abu Lil, Abubaker A. Al Malkawi.Funding acquisition: Feras Q. Alali.Investigation: Tamam El-Elimat, Mohammad S. Bani Amer, Alma Abu Lil.Methodology: Ahmed Hesham Al Sharie, Abdulmalek M. Abu Zahra, Reem F. Darweesh, Ayah K. Al-Khaldi, Balqis M. Abu Mousa.Project administration: Tamam El-Elimat, Feras Q. Alali.Resources: Tamam El-Elimat.Software: Balqis M. Abu Mousa, Mohammad S. Bani Amer, Kinda Al-Kammash.Supervision: Ahmed Hesham Al Sharie, Tamam El-Elimat, Balqis M. Abu Mousa, Feras Q. Alali.Validation: Abdulmalek M. Abu Zahra, Reem F. Darweesh, Ayah K. Al-Khaldi, Yazan O. Al Zu'bi, Abubaker A. Al Malkawi.Visualization: Abdulmalek M. Abu Zahra, Kinda Al-Kammash, Alma Abu Lil.Writing – original draft: Ahmed Hesham Al Sharie, Abdulmalek M. Abu Zahra, Tamam El-Elimat, Reem F. Darweesh, Ayah K. Al-Khaldi, Zainab Alazzeh.Writing – review & editing: Tamam El-Elimat, Feras Q. Alali.


The results showed that the pre-spraying of GB under LL stress significantly alleviated the growth inhibition of pepper seedlings; increased plant height by 4.64%; increased root activity by 63.53%; and decreased photoinhibition by increasing the chlorophyll content; upregulating the expression levels of encoded proteins Capsb A, Capsb B, Capsb C, Capsb D, Capsb S, Capsb P1, and Capsb P2 by 30.29%, 36.69%, 18.81%, 30.05%, 9.01%, 6.21%, and 16.45%, respectively; enhancing the fluorescence intensity (OJIP curves), the photochemical efficiency , qP, and NPQ; improving the light energy distribution of PSΠ (Y(II), Y(NPQ), and Y(NO)); and increasing the photochemical reaction fraction and reduced heat dissipation, thereby increasing plant height by 4.64% and shoot bioaccumulation by 13.55%. The pre-spraying of GB under LL stress also upregulated the gene expression of CaSOD, CaPOD, and CaCAT; increased the activity of the ROS-scavenging ability in the pepper leaves; and coordinately increased the SOD activity in the mitochondria, the POD activity in the mitochondria, chloroplasts, and cytosol, and the CAT activity in the cytosol, which improved the LL resistance of the pepper plants by reducing excess H2O2, O2−, MDA, and soluble protein levels in the leaf cells, leading to reduced biological membrane damage. Overall, pre-spraying with GB effectively alleviated the negative effects of LL stress in pepper seedlings.Low temperature combined with low light (LL stress) is a typical environmental stress that limits peppers’ productivity, yield, and quality in northwestern China. Glycine betaine (GB), an osmoregulatory substance, has increasingly valuable effects on plant stress resistance. In this study, pepper seedlings were treated with different concentrations of GB under LL stress, and 20 mM of GB was the best treatment. To further explore the mechanism of GB in response to LL stress, four treatments, including CK (normal temperature and light, 28/18 °C, 300 μmol m Plants live in an ever-changing environment that is often unfavorable for growth and development or stressful, which can include biotic stress (pathogen infection) and abiotic stresses such as drought, high and low temperature combined with low light, nutrient deficiency, and excessive salt or toxic metals in the soil . Among tCapsicum annuum L.), the second largest edible crop of Solanaceae after tomatoes, has an annual yield of more than 37 million tons and great economic benefits , maximum photochemical efficiency of photosystem II (Fv/Fm), quantum yield of regulatory energy dissipation of photosystem II [Y (NPQ)], quantum yield of nonregulatory energy dissipation of photosystem II [Y(NO)], and portion of energy reaction in PSII were P = (Fv′/Fm′) × qP, Ex = (1 − qP)/(Fv′/Fm′), D = 1 − (Fv′/Fm′) , Y(NPQ), Y(NO), NPQ, and qP, regulating the lipid peroxidation of membranes, thereby improving the ability to scavenge excess H


It is well understood that epigenetic alterations drive PCa initiation and progression, coupled with somatic alterations in genes encoding epigenetic enzymes. However, differences in the somatic alterations in these genes in African- versus European-derived prostate tumors and how they may contribute to PCa health disparities has yet to be investigated, which forms the objective of this study. With current PCa care almost exclusively based on and tailored for men of European ancestry, the identification of African-specific novel PCa epigenetic cancer drivers . Through clustering of all variant types and copy number alterations, we describe two epigenetic PCa taxonomies capable of differentiating patients by ancestry and predicted clinical outcomes. We identified the top genes in African- and European-derived tumors representing a multifunctional “generic machinery”, the alteration of which may be instrumental in epigenetic dysregulation and prostate tumorigenesis. In conclusion, numerous somatic alterations in the epigenetic machinery drive prostate carcinogenesis, but African-derived tumors appear to achieve this state with greater diversity among such alterations. The greater novelty observed in African-derived tumors illustrates the significant clinical benefit to be derived from a much needed African-tailored approach to prostate cancer healthcare aimed at reducing prostate cancer health disparities.Prostate cancer is driven by acquired genetic alterations, including those impacting the epigenetic machinery. With African ancestry as a significant risk factor for aggressive disease, we hypothesize that dysregulation among the roughly 656 epigenetic genes may contribute to prostate cancer health disparities. Investigating prostate tumor genomic data from 109 men of southern African and 56 men of European Australian ancestry, we found that African-derived tumors present with a longer tail of epigenetic driver gene candidates (72 versus 10). Biased towards African-specific drivers (63 versus 9 shared), many are novel to prostate cancer (18/63), including several putative therapeutic targets ( GSTP1 promoter region is typically hypermethylated in prostate cancer (PCa), resulting in the loss of its expression [The epigenetic machinery comprises genes that encode proteins involved in regulating chromatin organization, histone modifications, DNA methylation, non-coding RNA, and RNA methylation ,2. Many pression ,4. Andropression ,6. UltimTET2, MBD1), histone acetylation , histone methylation , as well as in chromatin remodelers  [A number of studies have shown that driver gene mutations in several cancer types are enriched for epigenetic machinery genes, including PCa. While most individual genes are mutated infrequently, epigenetic machinery genes, as a class, are some of the most frequently mutated in PCa ,8. HowevSMARCA1) ,10,11. TSMARCA1) . Of releSMARCA1) ,14,15. ZSMARCA1) , showed SMARCA1) .CD44 in prostate tumors derived from African-American compared to European ancestral Americans, which was positively correlated with tumor grade [RARB, which was significantly associated with a higher risk of PCa in African-American over European ancestral American men [What remains to be considered is the potential contribution of somatic alterations within the epigenetic machinery and its relevance to PCa health disparities. Notably, genetic ancestry is a significant risk factor for aggressive PCa, specifically African ancestry. Within the United States, African American men are 1.7 times more likely to be diagnosed with, and over twice as likely to die from, PCa than European ancestral American men, reaching 3.1-fold greater incidence for men younger than 65 years at diagnosis . Globallor grade , and theican men . While gican men ,11, the ican men  and a reican men ,32,33,34ican men , we set n = 6), were Brazilian (n = 7), were of admixed ancestry , or if their tumors were hypermutated . Of a total of 165 treatment-naïve PCa patients included in our study, 4/109 (3.7%) of the African and 3/56 (5.4%) of the European ancestral patients lacked any genomic aberrations within the epigenetic machinery, leaving 105 and 53 for further interrogation, respectively. Both cohorts were biased towards aggressive disease, representing the International Society of Urological Pathology (ISUP) Group Grading 4 and 5 in 73% of African and 85% of European-derived tumors, respectively (see Patients were recruited as part of the Southern African Prostate Cancer Study (SAPCS), with approval granted by the University of Pretoria Faculty of Health Sciences Research Ethics Committee  in South Africa (43/2010). In Australia, participant recruitment was approved by the St. Vincent’s Human Research Ethics Committee (HREC) (SVH/12/231), with genomic data generation approved by the St. Vincent’s HREC (SVH/15/227). Additional study-specific approval was granted by the University of Pretoria Faculty of Health Sciences Research Ethics Committee (504/2022). Fresh blood-tumor paired deep sequenced whole genome data were generated, as previously published . From thn = 530 genes, n = 240, n = 101, n = 136, n = 253, Using the PathCards database to identify genes that map the epigenetic process pathways , we idenWhole genome tumor mutational burden (TMB) was calculated for each patient by taking the total number of small somatic variants (SNVs and indels), divided by the total genome size (3088 Mbp). For each EPG classification, we defined mutational burden as the total number of small somatic coding variants present in a respective collection of epigenetic machinery genes, divided by the total coding size (Mbp) of that gene collection. The damaging variant mutational burden was defined as the total number of potentially damaging variants present in a respective collection of epigenetic machinery genes, as per functional impact prediction, divided by the total coding size (Mbp) of that gene collection. Coding the genome size for each EPG was mined using the Ensembl v.108 BioMart online data retrieval tool ,38.For each EPG, two approaches were used to identify potentially damaging variants and genes, including functional impact prediction and mutational recurrence. Specifically, the SIFT  and PolyFor recurrently mutated genes, we applied the computational tool DrGaP (driver genes and pathways)  to synonOf the potentially damaging variants and genes found, we further identified genes that overlap with the Pan Cancer Analysis of Whole Genomes (PCAWG) compendium of mutational drivers . To visuWe performed integrative clustering of three genomic data types  overlapping epigenetic process-related genes for 158 patients using the MOVICS  R package . We ran p-value < 0.05 was regarded as statistically significant. Biochemical relapse (BCR) survival probability and cancer survival probability for European patients were analyzed with the Kaplan–Meier method, followed by group comparison for significance using a log-rank test.For continuous variables, group means were compared using the Mann–Whitney U test, while for categorical variables, the groups were compared using Fisher’s exact test. A We have previously shown that African-derived prostate tumors present with an elevated TMB and potentially damaging somatic variants ,50. WhenKMT2C, identified here as a potentially damaging gene and by the PCAWG as a candidate cancer driver, although not predicted to contain functionally impactful variants, showed the highest recurrence rate, irrespective of ancestry . The following most recurrent genes in African-derived tumors were CHD3 and ARID1B , and in Europeans, were BRD7, KDM6A, KDM6B, KMT2A, KMT2B, and RANBP2 (each 3.6%). Seven genes presented in tumors from three or more patients of African ancestry, while being notably absent from European-derived tumors and included CHD3 (5 patients), ARID1B (4), HDAC4 (3), ARID1A (3), CHD1 (3), PRDM16 (3), and STAG2 (3). Conversely, genes exclusively altered in two or more European-derived tumors included KMT2B (2 patients) and RANBP2 (2). In each EPG, African-derived tumors displayed a greater mutation frequency for most genes (likely reflective of a greater sample number), along with richer diversity in variant types than European-derived tumors  or South Africa (n = 1).Hierarchical consensus clustering through joint analysis of somatic variant data  for epigenetic machinery genes identified three PCa subtypes . These three subtypes are presented for 158 patients, as shown in SETD1B, CHD4, and BRD4, while we observed a longer tail of unique drivers within Africans, including SRCAP, ARID1A, HCFC1, BRD1, POLR1B, STAG2, VPS72, UBTF, MXD1, KDM6B, HDAC4, ELL, RANGAP1, SMARCA4, KDM2B, and NCOR1. This suggests that different epigenetic mechanisms, particularly chromatin organization and regulation, play a role in PCa among Africans.Feature selection identifies genomic features that make important contributions the oncogenic processes and drive the integrative clustering. Using iClusterBayes, we calculated the posterior probability for each genomic feature as a driver. We found the top five identified features were dominated by genes belonging to EPG 1, followed by EPG 2 and EPG 5. Posterior probability was only high for small somatic mutation-identified features, with 30 potential drivers identified in total  and ECSs (p < 0.001).As CNAs appear to be the strongest determinant for ECS clustering, we performed hierarchical clustering on the CN data alone B. Recognp = 0.15), and ECS2 tumors predicted poorer survival probability than ECS1 tumors (p < 0.001). Notably, of the seven deaths recorded, three Australian European men presenting with ECS2 died within 172.5 months of their surgeries. Although not significant, when considering the CN subtypes, BCR-free probability showed a better clinical outcome for patients presenting with EcnCS1 over EcnCS3 (p = 0.11), even when considering only the GMS-C tumors (p = 0.32), which are characterized by poor clinical outcome.Through the availability of extensive follow-up data for our European Australian patients , we previously predicted significantly better clinical outcomes, defined as no biochemical relapse (BCR) and/or survival, for patients presenting with GMS-A over GMS-C tumors . Here, wKMT2C to be the most frequently mutated PCa epigenetic regulator gene, concurring with the results of previous studies reporting frequencies of ~5–8% [KMT2C is one component of chromatin remodeling machinery responsible for DNA promoter and enhancer regulation, ultimately promoting active chromatin conformations. With strong links to numerous cancer types, mutations in these components confirm their roles as tumor suppressors [KMT2C, the only recurrent driver genes to be shared between the ancestries are the well-known tumor suppressor genes KDM6A and TP53. In contrast to a lack of European-specific recurrent drivers, 35 African-specific recurrent driver genes were observed. The latter included putative loss-of-function PCa mutations previously reported for ARID1A, ATRX, CHD1, CHD3, HDAC4, KMT2A, KMT2D, SETD2, and SMARCA1 [BRMS1, CARM1, EHMT2, GLI3, HDAC1, KDM6B, PRDM16, RBBP5, and REST possessing known roles in PCa [ARID1B, ARID5B, BRWD1, EP300, HDAC3, NCOR2, PSIP1, SMARCA4, STAG2, and XPO1, although reported by PCAWG [CHD7, DPF3, ELP2, GATAD2B, NUP35, SETD1B, and TADA2B as novel candidate drivers.Overall, compared with European-derived tumors, African-derived prostate tumors presented with a higher burden of variants, as well as potentially damaging variants across epigenetic machinery genes. Although our findings were in line with our previous work, demonstrating a whole-genome African-elevated TMB , the epiof ~5–8% ,8. The tpressors . Irrespe SMARCA1 , with BRs in PCa ,58,59,60by PCAWG , are newDNMT3B and TDG (DNMT3B is a DNA methyltransferase (DNMT) enzyme responsible for establishing and maintaining methylation in satellite sequences and gene bodies [DNMT3B expression in aggressive versus non-aggressive PCa cell lines [DNMT1 was observed in an African sample. TDG, or Thymine DNA Glycosylase, plays a key role in active DNA demethylation and in tumor suppression. Several polymorphisms in TDG are associated with increased risk for cancer, although this gene has also been found to act as an oncogene, promoting tumorigenesis [TDG damaging variants identified in our study possess gain-of-function or loss-of-function properties. Ultimately, aberrant DNA methylation is a hallmark of cancer progression, and dysregulation of the DNA methylation machinery may lead to a reprogramming of the epigenomic landscape in cancer.Taking a closer look at the epigenetic processes, in contrast to our whole genome data and EPGs 1, 2, 4, and 5 exhibiting an African ancestry-elevated burden, we consistently showed EPG3 alterations to be similar between the ancestries. Overall, this group of DNA methylation gene regulators appears to be highly conserved, as previously reported , with no and TDG . DNMT3B e bodies ,63. DNMTe bodies  and elevll lines . Similarigenesis ,67,68. IUsing hierarchical consensus clustering for all somatic mutational types , we describe two epigenetic PCa taxonomies (ECS and EcnCS), which independently showed significant agreement with our previously-reported GMSs . ShowingMore aligned with the whole genome-derived GMSs , the EcnRAI1, SETD1B, SRCAP, ARID1A, and MED26; for SV data, they were SMYD4, GATAD2B, PPARG, MEF2D, and SMARCAD1; and for CNAs, they were HMGA2, SMYD5, SUMO3, SP110, and RAG2. Of the top five selected features for SV and CNA data, and for the 30 small somatic mutation-identified drivers  gene family, while implicated in several cancer types, does not include PCa [CHD7, a somatic driver candidate in colorectal cancer (CRC), promotes CRC cell growth by binding target gene promoters, encouraging an open chromatin conformation and subsequent transcription, whereas CHD7 knockdown inhibits CRC cell growth [POLR1B knockdown induces lung cancer cell apoptosis [VPS72 knockdown inhibits the proliferation, invasion, and migration of hepatocellular carcinoma (HCC) cells [UBTF silencing suppresses melanoma cell proliferation [DPF3, a chromatin remodeling cofactor significantly downregulated in breast cancer tissue, promoting the proliferation of breast cancer cells, has been suggested as a novel therapeutic target for breast cancer therapy [SETD1B expression in HCC positively correlated with tumor size, clinical stage, and liver cirrhosis. Decreased SETD1B expression was associated with increased patient survival times, identifying this histone methyltransferase as a potential therapeutic target in HCC [As a function of hierarchical clustering, feature selection identified the top five genes for each variant type for potential driver gene classification. In rank order, based on posterior probability, the top five features for small somatic variant data were  drivers , the gen unknown . SETD1B,in cells , althougin cells . MED26, lude PCa . Additiol growth . Similarpoptosis , VPS72 kC) cells , and UBTferation . DPF3, a therapy . Increast in HCC . While st in HCC ,81,82,83ARID1A, CHD4, HCFC1, STAG2, SMARCA4, and NCOR1 are known cancer driver genes [CHD4, or Chromodomain Helicase DNA Binding Protein 4, is the main component of the nucleosome remodeling and deacetylase (NuRD) complex that plays an important role in epigenetic transcriptional repression. CHD4/NuRD also regulates RNA synthesis [CHD4 warrants its inclusion in EPGs 1, 2, 4, and 5. Rather than the top genes being epigenetic machinery components exclusive to a single EPG, this broad overlap is reminiscent of the previously discussed CN-DNA methylation aberration events, arising from some “generic machinery”, common in many cancer types. Indeed, epigenetic regulators are well-conserved and mutate infrequently. However, should epigenetic regulation be disrupted, as a class, perhaps the genomic alteration of a common core group of multifunctional epigenetic regulators will achieve this mutation, promoting tumorigenesis. Many of our top-identified genes have well-established roles across cancer types, further supporting the representation of these altered genes as a “generic machinery” promoting cancer. Yegnasubramanian describes alterations in epigenetic reprogramming to be almost universal in human cancers [Ultimately, alterations to genes encoding epigenetic machinery components are increasingly recognized in many cancer types, including PCa. From this study, based on genes containing potentially damaging variants as per functional impact prediction and/or recurrence, as well as putative driver gene status, as defined by feature selection during hierarchical clustering, we have summarized the top genes in African and European-derived tumors (per EPG) that may be instrumental in epigenetic dysregulation and the subsequent development and/or progression of PCa . Identifer genes . Notablyynthesis . As such cancers . HoweverBRD1, DR1, ELL, ELP2, ELP5, GATAD2B, MED26, MXD1, NUP35, RAI1, SP110, TADA2B) and some which are putative therapeutic targets . Here, we also described two epigenetic PCa taxonomies (ECS and EcnCS) that differentiate patients by ancestry, predict clinical outcomes, resemble whole-genome derived global subtypes, and identify more African-specific putative drivers, ultimately indicating a significant role for epigenetic mechanisms in PCa development. Identifying many more African-specific (versus European-specific) potentially novel PCa drivers highlights the urgency for African inclusion in precision medicine-informed healthcare approaches to ultimately reduce PCa health disparities and improve health outcomes for African men.Alterations to epigenetic machinery components dysregulate epigenetic programming, chromatin structure, and consequent transcription, a feature of PCa development and progression that is increasingly becoming better understood. Here, we describe somatic alterations within the epigenetic machinery and their relevance to PCa health disparities, with African-derived tumors demonstrating a longer tail of African-specific epigenetic driver gene candidates, a number of which are novel to PCa (


To explore the difference and diagnostic value evaluation of serum tumor markers in different clinical stages of elderly non-small cell lung cancer (NSCLC) patients.Select 100 elderly NSCLC patients admitted to our hospital from June 2018 to June 2021, collect the general data, pathology data and imaging data of the patients, and the patients were divided into I-IV clinical stages according to the International Union Against Cancer (UICC) 8th edition lung cancer TNM staging standard. Detect the subjects' peripheral serum tumor markers, serum carcinoembryonic antigen (CEA), cytokeratin fragment 21-1 (CYFRA21-1), squamous cell carcinoma-associated antigen (SCCA), carbohydrate antigen 125 (CA125) and sugar Class antigen 199 (CA199). Compare the differences of serum CEA, CYFRA21-1, SCCA, CA125, CA199 levels in different clinical stages of elderly NSCLC patients, and the diagnostic value of the above indicators for elderly NSCLC patients was analyzed by receiver operating characteristic curve (ROC curve) and area under the curve (AUC). Non-small cell lung cancer (NSCLC) is one of the most common types of lung cancer, accounting for about 80% of lung cancer patients, and its incidence is closely related to factors such as air pollution, smoking, and ionizing radiation With the in-depth research of molecular genetics and molecular biology, domestic and foreign scholars have gradually gained a deeper understanding of the etiology and pathogenesis of NSCLC A total of 100 elderly patients with NSCLC who were admitted to our hospital from June 2018 to June 2021 were selected. Inclusion criteria: (1) confirmed by imaging and pathological examinations; (2) age greater than 60 years old; (3) no anti-tumor therapy such as radiotherapy or chemotherapy; (4) clinical data and follow-up data are complete. Exclusion criteria: (1) combined with other malignant tumors, (2) combined with severe damage to important organs such as heart, liver and kidney; (3) combined with physical diseases; (4) combined with autoimmune diseases; (5) combined with mental diseases. This study was approved by the The Fourth Hospitalof Hebei Medical University ethics committee, and all subjects gave informed consent and signed aninformed consent form(2022KS018).According to the International Union Against Cancer (UICC) 8th edition lung cancer TNM staging standard Collect 5 mL of fasting venous blood from all subjects in the morning, and centrifuge at 3000 r/min for 10 min to obtain serum. Chemiluminescence immunoassay analyzer  was used to detect serum levels of CEA, CYFRA21-1, SCCA, CA125, and CA199. All operations are carried out in strict accordance with the instructions.p <0.05 is considered statistically different.All data are statistically analyzed using SPSS 22.0 software . The count data is expressed as N and the chi-square test is performed, and the measurement data is expressed as mean ± standard deviation and a one-way analysis of variance is performed. GraphPad 8.0 software  was used for drawing. Among all 100 elderly NSCLC patients, 13 were in stage I, 25 were in stage II, 27 were in stage III, and 35 were in stage IV. Among them, stage I patients are 60–83 years old, with an average age of (71.20±5.92) years; 6 males, 7 females, 3 people have a history of smoking; pathological type: 7 cases of adenocarcinoma, 6 cases of squamous cell carcinoma; differentiation degree: 5 cases were highly differentiated, 8 cases were poorly differentiated; 4 cases of lymph node metastasis; tumor diameter: 5 cases of 5 cm, 8 cases of less than 5 cm; stage II patients are 60–82 years old, with an average (71.10±5.93) years; 12 males, 13 females, 11 people have a history of smoking; pathological types: 14 cases of adenocarcinoma, 11 cases of squamous cell carcinoma; differentiation degree: 8 cases of highly differentiated, 17 cases were poorly differentiated; 7 cases of lymph node metastasis; tumor diameter: 7 cases of 5 cm, 18 cases of less than 5 cm; stage III patients are 62-79 years old, with an average age of (71.01±5.98) years; 18 males, 9 females, 17 have a history of smoking; pathological types: 12 cases of adenocarcinoma, 15 cases of squamous cell carcinoma; differentiation degree: 16 cases were highly differentiated, 11 cases were poorly differentiated; 18 cases of lymph node metastasis; tumor diameter: 17 cases of 5 cm, 10 cases of less than 5 cm; stage IV patients are 64–80 years old, with an average (71.15±5.95) years old; 22 males, 13 females, 22 have a history of smoking; pathological types: 19 cases of adenocarcinoma, 16 cases of squamous cell carcinoma; differentiation degree: 23 cases of highly differentiated, 12 cases of poorly differentiated; 17 cases of lymph node metastasis; tumor diameter: 23 cases of 5 cm, 12 cases of less than 5 cm. There was no statistical difference in age, gender, and pathological type of patients in each stage, but there were significant differences in smoking history, degree of differentiation, lymph node metastasis, and tumor diameter .In order to study the expression patterns of serum tumor markers in elderly NSCLC patients at various clinical stages, we tested the serum levels of CEA, CYFRA21-1, SCCA, CA125 and CA199 in all patients. The results showed that the serum levels of CEA, CYFRA21-1, SCCA, CA125 and CA199 gradually increased with the patient's disease progression, suggesting that as the NSCLC disease progression increases, the serum tumor marker levels are also increasing A-E.Unsupervised PCA analysis was performed with serum tumor markers, and the results showed that the samples of each clinical stage were significantly separated between the PC1 dimension groups A; at theThe clinical stages of elderly NSCLC patients were divided into I-II and III-IV stages. The diagnostic value of serum CEA, CYFRA21-1, SCCA, CA125 and CA199 in elderly NSCLC patients was analyzed by ROC curve and AUC. The results showed that the AUC of serum CEA, CYFRA21-1, SCCA, CA125 and CA199 were 0.9217, 0.8680, 0.8888, 0.9994, 0.9975, respectively, and the 95% confidence intervals were 0.8716–0.9718, 0.8007–0.9353, 0.8222–0.9552, 0.9975-1, and 0.9926-1, suggestingthat serum tumor markers have diagnostic value for elderly NSCLC patients A-B.The onset of elderly NSCLC is insidious and lacks typical clinical phenotypes in the early stage Serum tumor marker is a peptide substance that is produced or secreted and released into the periphery during the host body's tumorigenesis and development The degree of tumor malignancy is the proliferation and invasion activity of tumor cells, which is mainly determined by the expression of related proliferation/invasion genes In summary, the elevation of serum CEA, CYFRA21-1, SCCA, CA125 and CA199 in elderly patients with NSCLC is positively correlated with the degree of tumor malignancy. The detection of the above indicators is of great value for the early diagnosis and condition monitoring of elderly NSCLC.Not applicable.Not applicable.This study was approved by the The Fourth Hospital of Hebei Medical University ethics committee, and all subjects gave informed consent and signed aninformed consent form (2022KS018).All the authors declare that they have no conflict of interest in this work.


Zirconia disks  were fabricated using a computer-aided design/computer-aided manufacturing system. Following the ALD of TiO2, Al2O3, SiO2, or ZnO thin film, the thin-film thickness, elemental distribution, contact angle, adhesion strength, and elemental elution were determined. The L929 and MC3T3-E1 cell proliferation and morphologies on each sample were observed on days 1, 3, and 5 (L929) and days 1, 4, and 7 (MC3T3-E1). The ZR-Ti, ZR-Al, ZR-Si, and ZR-Zn thin-film thicknesses were 41.97, 42.36, 62.50, and 61.11 nm, respectively, and their average adhesion strengths were 163.5, 140.9, 157.3, and 161.6 mN, respectively. The contact angle on ZR-Si was significantly lower than that on all the other specimens. The eluted Zr, Ti, and Al amounts were below the detection limits, whereas the total Si and Zn elution amounts over two weeks were 0.019 and 0.695 ppm, respectively. For both L929 and MC3T3-E1, the cell numbers increased over time on ZR, ZR-Ti, ZR-Al, and ZR-Si. Particularly, cell proliferation in ZR-Ti exceeded that in the other samples. These results suggest that ALD application to zirconia, particularly for TiO2 deposition, could be a new surface modification procedure for zirconia dental implants.Zirconia is a promising material for dental implants; however, an appropriate surface modification procedure has not yet been identified. Atomic layer deposition (ALD) is a nanotechnology that deposits thin films of metal oxides or metals on materials. The aim of this study was to deposit thin films of titanium dioxide (TiO Pure titanium (Ti) and certain Ti alloys are the most commonly used materials for dental implants because the properties of Ti include osseointegration potential, excellent biocompatibility, non-toxicity, and non-inflammation . To enhaHowever, a polished zirconia surface exhibits hydrophobicity and is bio-inert. As hydrophilicity is generally required for the integration of zirconia dental implants into the alveolar bone, surface modification of zirconia dental implants is performed to obtain high osseointegration potential, as for Ti dental implants ,12. For Atomic layer deposition (ALD) is a vapor-phase nanotechnology-based technique in which ultra-thin or thin films of metals, metal oxides, sulfides, and nitrides are deposited on various materials. Using ALD, high-quality thin films can be deposited via a routine atomic layer-by-layer procedure, and the film thickness can be controlled on complex three-dimensional materials, as well as on materials with high aspect ratios or porous surfaces. Moreover, thin films deposited using ALD appear uniform across the material, conformal, and pinhole-free . Accordi2; ZR-Ti), aluminum oxide , silicon dioxide , and zinc oxide  thin films were deposited on zirconia discs (ZR) using ALD for zirconia surface modification, and the proliferation abilities of mouse fibroblasts (L929) and mouse osteoblastic cells (MC3T3-E1) on each sample were evaluated.In this present study, titanium dioxide  is deposited on the surface. These four steps are repeated cyclically to deposit a thin film with the desired thickness. Therefore, thin-film thickness control with atomic-level precision is expected when ALD is employed [The ALD thin-film deposition process is based on the repetition of four cycles. First, a precursor, which is usually a metallic element surrounded by organic functional groups, is introduced to a reactor and chemically absorbed into the target material. The unreacted precursor is then purged from the reaction chamber using an inert gas, such as Nemployed .2, Al2O3, SiO2, and ZnO deposition onto ZR was confirmed using STEM and energy-dispersive X-ray spectroscopy (EDS) analyses. During the wettability test, the contact angle of ultra-pure water on ZR-Si was significantly lower than that on the other specimens. The ZR and ZR-Ti surfaces were found to be slightly hydrophilic, whereas the ZR-Al and ZR-Zn surfaces were found to be slightly hydrophobic. Moreover, L929 cell proliferation increased over time on ZR, used as a control, and on ZR-Ti, ZR-Al, and ZR-Si, indicating good cell compatibility and well-developed cytoskeletons. In the MC3T3-E1 cell culture, cell proliferation on ZR-Si was slower than that on ZR, ZR-Ti, and ZR-Al. Although there were almost no statistically significant differences, cell proliferation on ZR-Ti was notably higher than that on ZR and ZR-Al. In addition, the MC3T3-E1 cell compatibility appears to have surpassed that of the L929 cells, as the former reached confluence on day 4 of culturing, compared to day 5 for the latter. Although the exact mechanism is unknown and may depend on the material and cell type, the hydrophilicity of a material surface has been reported to increase cell adhesion and proliferation [In this study, TiOferation ,17,20. H2 film deposited on Ti6Al4V [2 film deposited on polyetheretherketone [2O3 thin film deposited on glass cover slips [2O3 nanostructures deposited on round-shaped glass cover slips [2-SiO2 (30:70) coating produced on Ti disks [2 and Al2O3 depositions were chemically stable on ZR. The gradual proliferation of MC3T3-E1 cells on ZR-Si was probably attributed to the slight elution of Si, i.e., the SiO2 thin-film-depositing state was chemically somewhat unstable. By contrast, for both cell cultures, the number of cells on ZR-Zn did not increase from the first day, and irregular cell morphologies were observed.As reported previously, nanostructured TiO Ti6Al4V , bioactierketone , Al2O3 ter slips , one-dimer slips , and TiOTi disks  have allTi disks ,30,31,32The target thin-film thickness was set to 50 nm but an error of approximately ±10 nm was observed. This is because each molecule differed in size and, thus, the number of deposition cycles varied with the deposition molecule. Therefore, it is difficult to specify the number of cycles necessary to obtain a target thin-film thickness. Furthermore, it is currently unknown whether the differences in the thin-film thickness affected the element elution, adhesion strength, or cell proliferation results. Hence, more precise deposition conditions must be determined to obtain the target thin-film thickness for each deposition molecule and examine if the differences in thin-film thickness affect the abovementioned outcomes.The dental implant insertion torque is an indicator of the stability of a primary implant and reflects the cutting resistance of the bone at the osteotomy site during dental implant placement, which is expressed in Newton centimeters (Ncm). An insertion torque value of ≥32 Ncm is recommended to secure primary stability, particularly when immediate implant loading is assumed ,34. Ther2, SiO2, and ZnO thin films were deposited on Ti using ALD [2+ has been reported to increase the viability of epithelial cells on ZnO-deposited zirconia [2/ZnO coatings on Ti have been found to promote SaOS-2 osteoblastic cell adhesion and differentiation [In a previous study, ZrOsing ALD . The elusing ALD . One possing ALD  and the sing ALD . By contzirconia , increaszirconia  and enhazirconia . In addintiation . Thus, t2 layer can be formed immediately upon exposure to the atmosphere [2 layer between Ti and the deposited thin film [2. In other words, the TiO2 that naturally forms on the Ti surface is osseointegrated. Therefore, if a TiO2 thin film is deposited on the surface of a zirconia dental implant using ALD, higher osseointegration ability than that of a conventional zirconia dental implant can be achieved. Furthermore, because zirconia is a ceramic, the problems of corrosion and allergy concerning Ti can be eliminated, and dental implants with high strength and excellent biocompatibility can be developed.Ti is a highly oxidizable metal, and a TiOmosphere . In facthin film . This imThis study had some limitations. As we decided to only focus on ALD on zirconia, we only studied a singular technique. Further destructive surface treatments have been introduced including ultra-short laser pulses to the zirconia surface, where the surface roughness increases with a minor tetragonic to monoclinic transformation ,45. Futu2); Amman Girrbach AG, Vorarlberg, Austria) was used in this study. First, a computer-aided design/computer-aided manufacturing (CAD/CAM) system  was used to machine the zirconia block into a cylindrical shape . Disk-shaped samples (thickness: 630 μm) were then cut using a low-speed diamond saw , and the cut samples were sintered in an electric furnace . The temperature of the electric furnace was increased by 300 °C/h until it approached 1450 °C, after which it was maintained at 1450 °C for 2 h and then cooled down for 6 h. The final sample dimensions were approximately 500-micrometer thickness and 10-mm diameter. The sintered zirconia samples were polished using a barrel polishing machine  and further sequentially polished with abrasives down to a 0.3-micrometer alumina suspension using a rotary polishing machine . This polishing step was followed by washing with a synthetic detergent, ultrasonic cleaning for 20 min, and air drying.A commercially available zirconia block (Ceramill ZOLID 71L (20 mm) zirconium dioxide . The TiO2, Al2O3, SiO2, and ZnO thin films were deposited using tetrakis(dimethylamido)titanium , trimethylaluminum , tris(dimethylamino)silane , and diethylzinc , respectively, as precursors. With regard to oxidizing agents, ultra-pure water (Grade II) was used for TiO2, Al2O3, and ZnO thin films, and O3 was used for the SiO2 thin film. The target deposition thickness was set to 50 nm. Details of the deposition conditions are listed in Prior to the ALD treatment, the ZR were irradiated with plasma for 10 min to maximally remove elemental contaminants. TiO₂, AlThe thickness and elemental distribution of each thin film were determined using a STEM equipped with an EDS . STEM parameters used were as follows: electron-beam spot size, 1 nm; sample acceleration, 200 kV.The hydrophilic or hydrophobic property of each specimen surface was evaluated using an automatic contact angle meter  to measure the contact angle between a 0.5 μL drop of ultra-pure water and each specimen surface. Based on the obtained image of a sessile drop, the contact angle meter measured the angle between the point of intersection of the drop profile and the projection of the specimen surface.A scratch test was performed using an oscillating microscratch tester  to measure the ZR-Ti, ZR-Al, ZR-Si, and ZR-Zn adhesion strengths to ZR. Each sample was analyzed three times, and the average was calculated. The change point on the scratch mark of each sample was observed with a laser microscope .Each sample was immersed in 50 mL conical tubes containing 45 mL of ultra-pure water. The tubes were placed in a constant-temperature oven  set at 37 °C and stored statically for two weeks. After storage, the concentrations of the eluted elements in the immersed solution were measured using an inductively coupled plasma (ICP) atomic emission spectrometer .The procedures used to obtain cell concentrations and cell cultures were based on protocols established in previous studies ,46,47. 2. The MC3T3-E1 cells were cultured under the same conditions in alpha-Eagle’s MEM  supplemented with 10% FBS, penicillin (100 IU/mL), and streptomycin (100 µg/mL).In this study, mouse fibroblasts  and osteoblastic cells  were used for the cell culture experiments. The L929 cells were cultured at 37 °C in Eagle’s minimal essential medium  supplemented with 5% fetal bovine serum , penicillin , and streptomycin  in a humidified atmosphere with 5% CO5 cells/mL in their respective medium and seeded at 200 µL/well. The cells were also seeded directly on ZR (without ALD treatment) as a control. The culture media were changed every other day. The L929 cells were cultured for 5 days, and cell proliferation was measured from three samples on days 1, 3, and 5. MC3T3-E1 cells were cultured for 7 days, and cell proliferation measurements were performed on three samples on days 1, 4, and 7. The cell proliferation at each time point was measured via a water-soluble tetrazolium salt (WST) assay using Cell Counting Kit-8  at 450 nm).Each sample was then placed in a 48-well microplate. The cells were suspended at a density of 1 × 10During the culture period, the pH values of both L929 and MC3T3-E1 culture media were measured using a pH meter .To observe the post-culture morphologies, the L929 and MC3T3-E1 cell samples were fixed with 2% glutaraldehyde  for 24 h, followed by incubation in 1% osmium tetroxide  for 2 h, sequential dehydration in increasing alcohol concentrations, and freeze-drying. Finally, the samples were sputter coated with platinum and imaged using a SEM  at 10 kV acceleration. The L929 cell morphology was observed on days 1, 3, and 5, and that of the MC3T3-E1 cells was observed on days 1, 4, and 7.n = 3) values. Statistical analyses for the wettability test, scratch test, and cell proliferation assay were performed using one-factor analyses of variance, followed by Tukey’s post-hoc tests. p values of less than 0.05 were considered statistically significant.In this study, all quantitative data were collected as the mean ± standard deviation (SD) (2, Al2O3, SiO2, and ZnO thin films onto ZR using ALD provided promising results for dental implant creation. The number of L929 and MC3T3-E1 cells on the ZR-Ti, ZR-Al, and ZR-Si increased over time, and, in particular, cell proliferation was most prominent on ZR-Ti, demonstrating excellent biocompatibility. We found that the contact angle on the ZR-Si surface was significantly lower than the other specimens; however, there were no statistically significant differences in the thin-film adhesion strength among the samples and wettability did not seem to have a significant effect on the results of this cell proliferation test. Additionally, as the TiO2 and Al2O3 deposited on the ZR were chemically stable, the amounts of Ti and Al elution were below detection limits in the immersion test. These results indicate that the use of ALD for coating zirconia dental implants, particularly for TiO2 deposition, could be employed as a novel surface modification technique. Future studies should assess the effect of zirconium and oxygen within the zirconia sample and the crystal structure of zirconia on thin film deposition.In conclusion, the deposition of TiO