Despite recent scientific headway in deciphering the difficulties of somatic embryogenesis, the overall picture of key genes, pathways, and co-expression networks regulating SE is still fragmented. Therefore, deciphering the molecular basis of somatic embryogenesis of hybrid sweetgum remains pertinent. In the present study, we analyzed the transcriptome profiles and gene expression regulation changes via RNA sequencing from three distinct developmental stages of hybrid sweetgum: non-embryogenic callus (NEC), embryogenic callus (EC), and redifferentiation. Comparative transcriptome analysis showed that 19,957 genes were differentially expressed in ten pairwise comparisons of SE. Among these, plant hormone signaling-related genes, especially the auxin and cytokinin signaling components, were significantly enriched in NEC and EC early. The K-means method was used to identify multiple transcription factors, including HB-WOX, B3-ARF, AP2/ERF, and GRFs (growth regulating factors). These transcription factors showed distinct stage- or tissue-specific expression patterns mirroring each of the 12 superclusters to which they belonged. For example, the WOX transcription factor family was expressed only at NEC and EC stages, ARF transcription factor was expressed in EC early, and GRFs was expressed in late SE. It was noteworthy that the AP2/ERF transcription factor family was expressed during the whole SE process, but almost not in roots, stems and leaves. A weighted gene co-expression network analysis (WGCNA) was used in conjunction with the gene expression profiles to recognize the genes and modules that may associate with specific tissues and stages. We constructed co-expression networks and revealed 22 gene modules. Four of these modules with properties relating to embryonic potential, early somatic embryogenesis, and somatic embryo development, as well as some hub genes, were identified for further functional studied. Through a combination analysis of WGCNA and K-means, SE-related genes including AUX22, ABI3, ARF3, ARF5, AIL1, AIL5, AGL15, WOX11, WOX9, IAA29, BBM1, MYB36, LEA6, SMR4 and others were obtained, indicating that these genes play an important role in the processes underlying the progression from EC to somatic embryos (SEs) morphogenesis. The transcriptome information provided here will form the foundation for future research on genetic transformation and epigenetic control of plant embryogenesis at a molecular level. In follow-up studies, these data could be used to construct a regulatory network for SE; Key genes obtained from coexpression network analysis at each critical stage of somatic embryo can be considered as potential candidate genes to verify these networks.Somatic embryogenesis (SE) is a process of somatic cells that dedifferentiate to totipotent embryonic stem cells and generate embryos  Liquidambar formosana Hance) is distributed in most temperate and subtropical regions of China and is used mainly for medicinal and ornamental purposes (Liquidambar styraciflua L.) is a common southern American hardwood that has become an important feedstock for the timber and paper industries. These two species are interfertile even after 10 million years of separation (L. styraciflua × L. formosana) have biomass productivity that is superior that of either parent species due to faster growth rates and higher wood density, demonstrating obvious heterosis (L. styraciflua (L. styraciflua × L. formosana)  . We succin vitro conditions generates embryogenic or non-embryogenic cells. Some of these non-embryogenic callus (NEC) cells can differentiate further into embryogenic callus (EC) cells , similar in morphology to zygotic embryo without fertilization. Somatic embryos is bipolar structure which has both shoot apex and root apex . Also, SC) cells . The forC) cells . The staC) cells ; hence, C) cells . Somaticma cacao  and Heveiliensis , and hasrovement .Somatic Embryogenesis Receptor-Like Kinase 1 (SERK1) gene, which was overexpression increases the efficiency of somatic cell initiation in Arabidopsis (LEAFY COTYLEDON2 (LEC2) (ABSCISIC ACID INSENSITIVE3 (ABI3), FUSCA3 (FUS3), which encode B3 domain transcription factors that are key regulators of embryogenesis (AGAMOUS-LIKE15 (AGL15). Genes identified as targets of the B3 genes are also targets of AGL15  encodes an APETALA2 (AP2) domain transcription factor that is preferentially expressed in developing embryos and seeds. Overexpression of BBM can trigger spontaneous formation of somatic embryo (WUSCHEL homeobox 2 (WOX2) (AUXIN RESPONSE FACTOR 19 (ARF19)  , ABSCISIogenesis , were idof AGL15 . The hom embryos . BABY BOc embryo . In addi2 (WOX2) , AUXIN R (ARF19) , and LAT (ARF19)  also plaIn the present research, we analyzed the transcriptome profiles and gene regulation changes in the SE process of hybrid sweetgum using a combination of K-means and WGCNA methods. Some genes were identified as being related to the NEC, EC, and redifferentiation of SE. These included genes related to hormones, embryogenesis, and various transcription factors (TFs). This is the first report of SE transcriptomes in hybrid sweetgum, and the results improve our understandings of the molecular mechanisms in the SE of hybrid sweetgum. Some new molecular marker genes were identified, which enriched the molecular regulatory network during SE and provided a new perspective for improving the efficiency of SE through genetic transformation. Furthermore, the results of this research will be provide a valuable resource for future studies and will be helpful to the research in this field, especially hybrid sweetgum breeding programs.L. formosana and L. styraciflua trees. Developing fruits (multiples of capsules) were collected from the L. styraciflua trees. Whole fruits were surface-disinfested using the following sequence: rinse with water for 30 min, soaked in 75% ethanol for 1min and sodium hypochlorite for 4 min on the ultra-clean table, and cleaned with sterile distilled water for 5–6 times. The fruits were then dissected aseptically with a scalpel to remove the immature seeds. Each seed was nicked with a scalpel and cultured, ten seeds per plate, on induction medium: A modified Blaydes medium (–2 s–1) for germination. The cultures at different developmental stages, including NEC, friable EC, PEM after maturation cultured for 20 days (PEM1), PEM after maturation cultured for 45 days (PEM2), GE, HE, TE, CE, roots (R), stems (S), and leaves (L) were sampled, as shown schematically in To obtain hybrid seeds, we performed controlled pollinations between s medium  with 1.0 medium – s–1 for 2 (fold change)| ≥ 1.5 and P-value < 0.01 between seven pairwise comparisons: NEC_vs_EC, EC_vs_PEM1, PEM1_vs_PEM2, PEM2_vs_GE, GE_vs_HE, HE_vs_TE, TE_vs_CE, CE_vs_R, CE_vs_L, and CE_vs_S. Gene expression levels were normalized using the [fragments per kilobase of transcript per million fragments mapped (FPKM)]  following the manufacturer’s recommendations, and index codes were added to attribute sequences to each sample. After sequencing, the raw data were filtered to remove adaptor contamination and low-quality reads. All clean reads were then mapped to the hybrid sweetgum genome using the HISAT2 program. The mapped reads of each gene were extracted using HISAT2 . We filt (FPKM)]  method.  (FPKM)] .2 relative FPKM values. In total, 13,574 genes residing in clusters with even more obvious tissue- or stage-specific expression trends were selected to make the final 35 K-means clusters. Only 18 of the 35 clusters are shown in 2 relative FPKM value of each TF was used to produce heat maps in TBtools  values, a matrix of pairwise (spearman correlation coefficient) SCCs between all pairs of genes was generated and transformed into an adjacency matrix (a matrix of connection strengths) using the following formula: connection strength  = |(1 + correlation)/2|β. Here, β represents the soft threshold for the correlation matrix, which gives greater weight to the strongest correlations while maintaining gene–gene connectivity. Based on the scale-free topology criterion, the β value was selected as 13  enrichment analysis for DEG sets was performed using Cytoscape (BiNGO plug-in) . The P-v® Real-Time PCR Detection System . Each sample included three biological replicates. Nine genes that specifically highly expressed in non-embryogenic callus, embryogenic callus and somatic embryo development stage, respectively, were selected for qRT-PCR to verify the RNA-seq results, and then reverse transcribed of 1 μg total RNA into cDNA using a TransScript One-Step DNA Removal and cDNA Synthesis SuperMix Kit . Each PCR reaction mixture contained 10 μl of Trans Start Top Green qPCR SuperMix , 1 μl of template cDNA, 0.4 μl of forwarding primer, 0.4 μl of reverse primer  was conducted on 33 RNA samples that were used in the preparation of sequencing libraries using a CFX Connecte primer , and 8.21-α gene  served aL. styraciflua × L. formosana) were tissue culture-induced to NEC. The NEC cells could be differentiated from the EC cells by visual discrimination. The NECs were dense and watery, white to brown in color, and had disorganized growth , stems (S), and leaves (L) . In totaThe aim of this study was to reveal the potential key genetic factors related in the SE of hybrid sweetgum. Among these seven comparisons , 3737, 5To evaluate the potential functions of the DEGs, we used GO term assignment to classify the functions of the DEGs in pairwise comparisons under three main GO categories: biological process, cellular component, and molecular function . In all Based on the KEGG and GO annotations, plant hormone signal transduction, zeatin biosynthesis, and IAA biosynthesis were the representative pathways in our study. A large number of genes involved in auxin (95 DEGs) and cytokinin (40 DEGs) biosynthesis and signal transduction pathways were differentially expressed when comparing EC with NEC and different SE stages.PIN1-like, PIN2, AUX1, ARFs , GH3 , and five SAUR genes—all involved in auxin signal transduction—were significantly upregulated from NEC to EC. Nevertheless, AUX1, GNOM, GNOM-like, DRM1, PIN, PIN2, AUX4-like, TIR1, IAA9, ARFs , GH3 , and SAUR  were mainly expressed in the NEC stage and downregulated in EC. From the EC to PEM and GE stages, GNOM, AFB2, GH3.6, IAA33, ARFs , and two SAUR32-like genes showed noteworthy upregulated expression  with the most obvious tissue- and stage-specific expression trends were selected. Among these, 18 clusters representing 6815 genes are shown in Clusters with similar expression trends were combined into 12 superclusters , and speRLK/Pelle family kinases, one C2C2 gene, and one ethylene response factor gene with potential roles in embryogenic competence. Interestingly, the embryo development-specific (superclusters 5–8) cluster has one GRF gene, indicating that this gene plays a key role in the morphogenesis of SEs.Among the 6815 genes that make up the aforementioned 12 superclusters , 142 arep = 8 × 10–22, r = 0.99), whereas genes in the green module had a higher correlation with EC  than NEC, except for PEM2. Genes in the blue module were comparatively highly correlated with early SE . Interestingly, three co-expression modules, the pink, salmon, and purple modules, showed relatively high correlation (r ≥ 0.15) with somatic embryo development stages   with leaf tissue, whereas the midnight-blue and red modules were specifically correlated with root  and stem  tissues, respectively , was adopted. WGCNA is a systems biology approach that aims to understand entire gene networks rather than single genes. In this study, we constructed a co-expression network based on the pairable correlation of gene co-expression trends in all sample tissues. Modules were defined as clusters of genes that were highly interrelated; The correlation coefficient between genes in the same cluster was high. This analysis resulted in 22 different modules, color-coded in the dendrogram , where e TE, CE) . Many ofectively .WRKY, RLK-Pelle, MYB, and STE_STE11 TFs. Another nine hub genes were also identified as key proteins or enzymes that play a key role in early SE (blue module) , seed biotin-containing protein (SBP65), and late embryogenesis abundant protein 6 (LEA6), are involved in regulation of the cell cycle, seed germination capacity, and embryo development ending in seed dormancy , C2C2-Dof, GNAT, bHLH, AP2/ERF-ERF, and NAC TFs (protein NRT1/PTR FAMILY 4.3 (NPF4.3), cytokinin dehydrogenase 1 (CKX1), and brassinosteroid-related acyltransferase 1 (BAT1), are involved in regulation of transmembrane transporter activity, cytokinin metabolic processes, and response to brassinosteroids. Interestingly, after we performed the co-expression analysis of the data again, we observed that one module displayed opposite expression patterns between the two types of calluses (NEC and EC) having different embryogenic potentials. For example, the thistle module showed low transcript abundance in NEC but high abundance in EC. In this module, 38 of the 212 genes encode TFs. Selecting only the top 15 genes showing high connectivity weight revealed 10 TFs representing distinct families, including the HB-WOX, AP2/ERF-AP2, MYB, B3-ARF, AP2/ERF-ERF, FAR1, and C2H2 TFs. Another five hub genes, namely, peptidyl-prolyl cis-trans isomerase (FKBP43), CASP-like protein 1E1, beta-fructofuranosidase, insoluble isoenzyme 1 (INV1), GDSL esterase/lipase (At5g45910), and WAT1-related protein (At1g25270) were involved in regulation of peptidyl-prolyl cis-trans isomerase activity, protein histidine kinase binding, carbohydrate storage, lipid catabolic processes, and transmembrane transporter activity  . In the dormancy . In the dormancy , 37 of t NAC TFs . Anotheractivity . InteresGene Ontology (GO) enrichment analysis was performed for each module using Cytoscape (BiNGO plug-in)  highlighTo verify the reliability of transcriptome data, twenty genes related to SE were selected.GLP1-13 (EVM0020840), ARF5 (EVM0026553), ABI3-1 (EVM0020968), LTP3 (EVM0021586), WOX9 (EVM0013624), LEA6 (EVM0000925), SMR4 (EVM0007351), ECP40 (EVM0003818), and MYB36 (EVM0015487) genes with high specific expression in various stages of hybrid sweetgum transcriptome were selected as marker genes to measure expression by qRT-PCR , indicated that those molecular markers played a key role in SE. In addition, the transcription level of GLP1-13 was highly and specific expressed in NEC, and this gene may inhibit the transition from non-embryonic to embryonic cells. qRT-PCR verification of SE-related genes also demonstrated a high correlation between RNA-seq and qRT-PCR data.The  qRT-PCR . The qRT qRT-PCR . WOX9 anL. styraciflua × L. formosana) is a tree species that grows faster and has higher wood density than its parents, its SE is becoming increasingly important. We successfully developed an SE system for hybrid sweetgum from hybrid seed explants. However, the mechanism of its SE remained unknown. In this study, we performed transcriptomic analyses of 11 types of tissues and stages of SE. The RNA sequencing (RNA-seq) data were analyzed using two different bioinformatics methods, K-means and WGCNA. This analysis yielded several new insights, including the identification of some time-specific modules, hub genes, and transcription factors.Because hybrid sweetgum  family genes had the largest number. However, the levels of endogenous auxin and cytokinin are influenced by their exogenous application  had lower expression in NEC. Most of them were dramatically upregulated in EC and downregulated during SE, indicating that the auxin-responsive genes played an important role in hybrid sweetgum SE. Tryptophan (Trp)-dependent IAA biosynthesis is an important pathway in higher plants, and exogenous application of doses of Trp and IAA produced similar enhancements during rice SE , seven B-ARR (two upregulated and five downregulated), and 11 A-ARR (two upregulated and four downregulated) genes. In the zeatin synthesis pathway, TRIT1 was upregulated from NEC to EC, and most of the CisZOG, IPT, and CKS were downregulated in EC and remained low during SE. However, IAA and zeatin biosynthesis- and signal transduction-related genes regulate SE in a complex and comprehensive way. Additional study of these genes in hybrid sweetgum SE is required.Aside from auxin being a main inducer of SE, the use of exogenously supplied cytokinin to induce SE has been well established in many species . Large nLEC1, LEC2, FUS3, ABI3, WOX9, WOX2, and BBM, were identified as molecular marker genes for early microspore embryogenesis of Brassica napus , and some of these gene functions on embryogenesis have been well characterized in various plants  genes encoding plant-specific homeobox TFs play key roles in plant development and growth . Of those with annotations, we found that the expression of many TFs, such as the ongation . Severaln longan . WUSCHELd growth , can regd growth . AP2/ERFbidopsis , are alsAP2/ERF-ERF, C2C2, C3H, bHLH, GRF, and bZIP TFs , 23 hub genes that showed high connectivity weight included 11 TFs representing distinct families, such as the bZIP TFs . Anothers volume . Gaudinobidopsis . LEA probidopsis  and werebidopsis . LEA genyo stage . We specWOX9, an important regulator of plant stem cell fate in the shoot meristem, which also may regulate the stem cell fate in the callus; the BBM1 transcription factor involved in the growth regulation of organ primordia; the R2R3-MYB transcription factors are involved in cell proliferation and elongation, which may promote callus proliferation. ARF proteins are believed to activate or repress the target genes and in the transient and heterologous assays, individual ARFs are classified as activators/repressors of the gene transcription. ARF5 is a activator, which encodes the MONOPTEROS (MP) protein, to be the most highly expressed member of the ARF gene family in the embryogenic culture of Arabidopsis. About the early embryo development stage, there are interesting interactions between MYB15, AGL15, LTP3, WOX11, and ABI3. MYB15 was involved in drought and salt tolerance and may enhance expression levels of genes involved in abscisic acid (ABA) biosynthesis and signaling, as well as those encoding stress-protective proteins. Therefore, MYB15 may promote somatic embryogenesis by regulating the dryness stress in early SE. AGL15 is known to enhance the embryogenic response in somatic cells if ectopically overexpressed. AGL15 can stimulates ABI3 expression and also represses the auxin response and interacts with GA metabolism to promotes the generation of somatic embryos. The LTP homologous gene has been implicated as a well-known early marker of somatic embryogenesis induction in different systems, being that it is linked to the protoderm layer formation, which exerts a regulatory role in controlling cell expansion during embryo development in developing somatic. The WOX11 genes participate in the early stages of the formation of callus and adventitious roots, initiating the division of the procambium cells. With the further development of somatic embryos, the need for energy stimulates the high expression of SMR4, ECP40 and LEA6, which are involved in the stress signaling pathway, RNA process and protein synthesis, resulting in the accumulation of proteins and ribosomes in proper embryo cells and promoting the maturation of somatic embryos. Our study is the first to use an integrated approach to study SE in hybrid sweetgum. The results of our study are an important starting point for future analyses and provide new insights useful for exploring alternative strategies and possibilities.According to our main findings of the hybrid sweetgum SE DEGs and their related networks , in combination with the relevant literature, we herein propose a possible molecular model for hybrid sweetgum SE, as shown in PRJNA762421.The data presented in the study are deposited in the NCBI repository, accession number JFZ, LK, and JZ designed the study. SQ and RZ conducted the experiments, analyzed the data, and drafted the manuscript. CH, HL, JY, TZ, YF, and SC critically reviewed and improved the manuscript. All authors have read and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The search was current as of March 2021. Studies which evaluated COVID-19 vaccine hesitancy and its determinants in high-income countries  were included. Studies conducted in low, lower-middle, and upper-middle income countries or regions were excluded. Factors associated with vaccine hesitancy were grouped into four themes . Of 2237 articles retrieved, 97 articles were included in this review. Most studies were conducted in U.S. (n = 39) and Italy (n = 9). The rates of vaccine hesitancy across high-income countries or regions ranged from 7–77.9%. 46 studies (47.4%) had rates of 30% and more. Younger age, females, not being of white ethnicity and lower education were common contextual factors associated with increased vaccine hesitancy. Lack of recent history of influenza vaccination, lower self-perceived risk of contracting COVID-19, lesser fear of COVID-19, believing that COVID-19 is not severe and not having chronic medical conditions were most frequently studied individual/group factors associated with increased vaccine hesitancy. Common vaccine-specific factors associated with increased vaccine hesitancy included beliefs that vaccine are not safe/effective and increased concerns about rapid development of COVID-19 vaccines. Given the heterogeneity in vaccine hesitancy definitions used across studies, there is a need for standardization in its assessment. This review has summarized COVID-19 vaccine hesitancy determinants that national policymakers can use when formulating health policies related to COVID-19 vaccination.Vaccine hesitancy forms a critical barrier to the uptake of COVID-19 vaccine in high-income countries or regions. This review aims to summarize rates of COVID-19 hesitancy and its determinants in high-income countries or regions. A scoping review was conducted in Medline Since its first reported case in December 2019, the coronavirus-2019 (COVID-19) pandemic has culminated in nearly 179 million infections and 3.88 million deaths globally as of 24 June 2021 . In cohort studies which reported longitudinal rates of vaccine hesitancy, the mean vaccine hesitancy rates were extracted. Other variables collected included the study design and methodology, characteristics of participants and determinants of COVID-19 vaccine hesitancy. Graphical charts and tables were used to present the results.0 of 2–3.5, a 60–70% vaccination uptake is estimated for herd immunity  while North America ranked second [n = 25 (59.5%)]. Studies conducted in Europe and Oceania had a lower proportion of studies with vaccine hesitancy 30% or more. Individually, vaccine hesitancy rates were highest in UAE (77.9%), U.S. (66.8%), Hong Kong (60%), and Italy (59.9%). In contrast, the vaccine hesitancy rates were lowest in Canada (7%) and Saudi Arabia (7%).n = 75, 77.3%) were the most frequent study designs while online surveys  were the most frequently used methods a.Reasons for vaccine hesitancy/acceptance were explored in 21 studies through open ended questions but only 7 (7.2%) attempted to describe methods on thematic analysis. Of these, only four are qualitative studies with well described methodologies ,25,26,27a. a Detailed data available in Pertaining to the definition of vaccine hesitancy used to derive its proportion, just slightly over half of the studies (51.5%) conformed to SAGE working group definition of vaccine hesitancy A total of 25 themes were identified and grouped under the eight sub-categories in “Contextual determinants of vaccine hesitancy” . “Sociodn = 37), [n = 31) [n = 24), [n = 19) [n = 13) [Among the sociodemographic variables, being females n = , [37,40,n = 37), ,73,74,75[n = 31) ,87,88,89n = 24), ,87,89,93[n = 19) ,96,97 an[n = 13) ,82,89,97n = 8) [n = 8) [With regards to policies and politics related factors, political inclination towards non-democrats in the U.S. (n = 8) ,45,46,47 [n = 8) ,51,52,53n = 6) [n = 5) [For communications and media environment factors, the use of social media or internet as a main source of information (n = 6) ,31,32,33 [n = 5) ,36,37,38n = 7), [n = 5), [n = 5), [n = 7) [n = 5) [Other notable factors associated with vaccine hesitancy included healthcare workers in non-clinical roles  (n = 7), ,70,73,87[n = 5), ,40,56,57[n = 5), ,86,100 r [n = 7) ,92,102 a [n = 5) ,71,75,94Two studies found an increased vaccine hesitancy mainly in nursing staff among healthcare workers with clinical fronting roles ,72.A total of seven sub-categories of factors with 22 themes were identified for the “Individual/group determinants of vaccine hesitancy” . “Beliefn = 16), [n = 15), [n = 12), [n = 11) [n = 12) [A lesser fear for health or worry about COVID-19 (n = 16), ,79,81,90n = 15), ,104,105 n = 12), ,98,105 h[n = 11) ,107,108 [n = 12) ,102,105 n = 28) [Previous influenza vaccination was the most common determinant associated with lower vaccine hesitancy (n = 28) ,95,104.A total of 10 themes were identified and grouped under the original eight sub-categories for “Vaccine related determinants” of vaccine hesitancy . Among tn = 24) [n = 9) [The most studied determinants associated with increased vaccine hesitancy included beliefs that COVID-19 vaccines are unsafe or ineffective n = 24) ,110,111  ,110,111 [n = 9) ,108,110.n = 4), [n = 3) [n = 2) [n = 4) were mixed [Other notable factors associated with increased vaccine hesitancy included presence of perceived barriers to accessibility of vaccine (n = 4), ,97,111 l [n = 3) ,52,88 an [n = 2) . Evidencre mixed ,97,104.This review has highlighted a few salient points and some research gaps.Firstly, it showed that despite the variable rates of vaccine hesitancy across high-income countries or regions, nearly half of studies reported vaccine hesitancy of 30% or more. Our review discovered that only slightly more than half of the studies conducted on COVID-19 vaccine hesitancy conformed to the SAGE proposed definition. In those studies which did not conform, participants who expressed being “unsure” instead of rejecting the vaccine were excluded in the hesitancy rate, leading to a potential falsely reassuring low hesitancy rate.Studies conducted among high income regions across four continents revealed a high proportion of studies with high vaccine hesitancy mostly in Asia and North America. Countries with the highest vaccine hesitancy rates included UAE, U.S., Hong Kong, and Italy. Compared to low-income countries or regions, the current vaccine hesitancy rates in high income countries or regions are worrisome.The varying vaccine hesitancy rates across countries or regions are complex and may partly be attributed to differences in ideological beliefs, demographics, and context specific factors, as seen for other vaccinations. For example, vaccine hesitancy appears to have a lesser impact on general vaccine uptake rates in lower-middle income countries or regions and affects lower socioeconomic status individuals to a greater extent . The reaThe global vaccination census showed that the share of population fully vaccinated against COVID-19 stood at 18.3% in high income countries or regions as of May 2021 . Of noteThe second point our study highlighted was to summarize determinants of COVID-19 vaccine hesitancy that were the frequently studied . FemalesLiterature discussing higher vaccine hesitancy in females suggested the underlying reasons attributable to lower perceived risk of COVID-19, higher beliefs in conspiracy related theories about the pandemic compared to their male counterparts  and concThe association between younger individuals and COVID-19 vaccine hesitancy may be a result of increased public health focus on vaccinating the elderly (due to their risk for severe COVID-19 outcomes) and the lack of outreach on COVID-19 vaccination in social media platforms which they commonly frequent .With respect to ethnicity, Blacks have been shown to have increased mistrust in COVID-19 vaccination with possible reasons due to racism, discrimination and mistreatment within the healthcare systems . We shouOur review also discovered that users of social media/internet as a primary source of COVID-19 related information were more prone to increased vaccine hesitancy. With the advent of infodemic on these non-traditional media platforms, innovations on ways to deliver accurate and timely health information by traditional and non-traditional platforms have become incredibly important. Employing active strategies such as pre-emptive cognitive inoculation techniques and pre-bunking techniques have also been suggested to tackle misinformation . Clear aIn addition, the other determinants previously mentioned should also be systematically addressed. While it is not within the scope of this review, the way different themes are being measured such as knowledge about COVID-19 disease and vaccination, is an important area of research impacting on the study of vaccine hesitancy across different populations. Our review noted that most studies used self-designed instruments in the evaluation of COVID-19 vaccination knowledge which limits cross-comparison of knowledge levels across populations. Future research should consider developing a standardized instrument for the assessment of knowledge of COVID-19 vaccine and disease which can potentially be adapted for future pandemics.Hopefully, the summary of these determinants will allow policymakers at the national level to deep dive into local context and conduct multi-pronged, multi-tiered studies coupled with interventions to overcome vaccine hesitancy in high income countries.With the ongoing vaccination drive globally and evolving landscape for COVID-19, it remains premature to conclude the real-world impact of vaccine hesitancy on the true uptake of COVID-19 vaccination. Uptake can be confounded by logistic and administrative challenges in vaccine deployment, vaccine production capacity issues from manufacturers, affordability of vaccines and global allocation of vaccines in the context of limited supplies . This waNonetheless, vaccine hesitancy studies will continue to provide insights into possible future directions to drive vaccination efforts. In planning vaccination programs, two considerations related to COVID-19 vaccination are important moving forward. Firstly, if COVID-19 vaccinations can stop transmissibility of COVID-19, at least 60–70% of population needs to be vaccinated . SecondlSeveral research gaps related to COVID-19 related vaccine hesitancy were identified in this review. Currently, there are limited studies which have evaluated longitudinal changes in COVID-19 related vaccine hesitancy. COVID-19 vaccine hesitancy may fluctuate or even increase due to fatigue with lockdown and preventive measures, or secondary to increased complacency coupled with reduced risk perceptions with a long duration of pandemic . Future This review is not without its limitations. Firstly, the determinants of vaccine hesitancy listed in this review were factors identified from most studies which employed online surveys predominantly. While this was inevitable given the lockdowns and travel restrictions imposed during the COVID-19 pandemic, population groups with limited access to the internet such as older adults, may not be comprehensively captured.n = 38; 39.2%, data available in The findings from online studies may be influenced by self-selection bias, survey fraud, and inability of respondents to seek clarity on questions . Among tSecondly, the grey literature as well as literature from pre-print servers were not searched in this review. Future systematic reviews which seek to evaluate vaccine hesitancy among specific populations or perform an updated review should consider searching these resources to improve the comprehensiveness of the search.n = 9 (36%), 40.9% n = 9 (40.9%), and n = 8 (80%) respectively. A possible insufficient exploration of a theme in the included studies has to be taken into consideration while interpreting and contextualizing the results to individual country.Thirdly, among the 57 themes of vaccine hesitancy found in the systematic review, 26 (45.6%) themes had fewer than five studies. The percentages in We would also like to point out a preponderance of studies done in the U.S. exploring the two sub-categories on “policies/politics” and “influential leaders, gate-keepers and anti or pro-vaccination lobbies”. Due to geopolitical differences, generalizability of these themes may be limited.Lastly, assessments of methodological quality of the included studies, presentations of strength of statistical associations with vaccine hesitancy and meta-analyses of the vaccine hesitancy rates were not performed as these were not the primary aims of this scoping review. Moreover, the heterogeneity in the definition and assessment of vaccine hesitancy in different studies would not have allowed a meaningful meta-analysis. Researchers who are planning to investigate COVID-19 vaccine hesitancy may want to consider adopting the standardized definition of vaccine hesitancy from SAGE workgroup in future studies. This will facilitate and enable future systematic reviews and meta-analyses to evaluate the variation in vaccine hesitancy rates across countries or regions, as well as the temporal variation in vaccine related hesitancy.Overall, COVID-19 vaccine hesitancy remains a highly prevalent problem in high income countries or regions. Individuals who were younger, females, non-Whites, and have a lower education or income levels, were more prone to vaccine hesitancy. Trust at different systems levels seem to play an important role in modifying vaccine hesitancy as well. Other commonly studied factors associated with vaccine hesitancy included a history of not receiving influenza vaccination, a lower self-perceived risk of contracting COVID-19, a lesser fear for health outcomes or COVID-19, not believing in the severity of COVID-19, having concerns about the rapid development of COVID-19 vaccines as well as disbeliefs in the safety and effectiveness of the vaccines. Healthcare administrators need to be cognizant of these determinants of vaccine hesitancy when formulating policies related to COVID-19 vaccination and public health messages.


It is, however, doubtful, whether ROS can contribute to the stabilization of the endothelial barrier.Endothelial cells (ECs) are exposed to molecular dioxygen and its derivative reactive oxygen species (ROS). ROS are now well established as important signaling messengers. Excessive production of ROS, however, results in oxidative stress, a significant contributor to the development of numerous diseases. Here, we analyze the experimental data and theoretical concepts concerning positive pro-survival effects of ROS on signaling pathways in endothelial cells (ECs). Our analysis of the available experimental data suggests possible positive roles of ROS in induction of pro-survival pathways, downstream of the G ROS include superoxide anion (O2●−), hydrogen peroxide (H2O2), and hydroxyl radical (●OH). The reaction of superoxide anion with nitric oxide (NO) produces peroxynitrite (ONOO−). There are multiple sources of ROS in ECs, including nicotinamide adenine dinucleotide phosphate (NADPH) oxidases, xanthine oxidases, nitric oxide synthase (NOS), cyclooxygenase (COX), cytochrome P450 monooxygenases, and mitochondria , S1P2 (Edg5), S1P3 (Edg3), S1P4 (Edg6), and S1P5 (Edg8) receptors , Rac1, PI3K, Akt, and endothelial nitric oxide synthase (eNOS) i activates CaMKII, but ROS can also activate CaMKII via oxidation of methionines 281/282 in a Ca2+-independent manner  and its upstream kinase MEK5 (MAPK/ERK kinase 5) as a signaling module that integrates both SS-induced athero-protective signaling ,133 and t manner . Mechanoted ERK5 . Since Cin BAECs , ROS canchannels  and via channels .TFs of the Krüppel-like factor (KLF) family include 17 members, among which KLF2, KLF4, and KLF6 are expressed in ECs ,139. KLF2O2 activated the c-Src–MEK5–ERK5–MEF2C pathway [2O2 is also likely to activate MEF2C and contribute to the inhibition of inflammation.The MEF2 family of transcription factors includes four members—MEF2A, MEF2B, MEF2C, and MEF2D . Among t pathway , suggestNrf2 is a key transcription factor, which is activated by oxidants and turns on the cellular defense against oxidative stress ,144,145.At physiological ROS levels, Nrf2 is kept inactive and directed to proteasomal degradation via association with the redox sensor KEAP1 (Kelch-like Ech-associated protein 1) . ROS indNormal level of ROS is well-known to provide antioxidant defense in ECs via stimulation of Nrf2, which activates antioxidant response element (ARE)-dependent expression of antioxidant genes. Nrf2-dependent vascular protection also includes the suppression of the NF-κB-dependent pro-inflammatory pathway and improvement of the mitochondrial function . Recentl2O2 ― via activation of the c-Src–MEK5–Erk5 pathway [The family of nuclear receptors PPARs are presented by three subtypes—PPARα, PPARβ/δ, and PPARγ . PPARγ p pathway ,135―can  pathway .There is increasing evidence that ROS derived from NADPH oxidases significantly contribute to signaling mechanisms regulating angiogenesis, a process of formation of new blood vessel from the pre-existing vessel. ECs’ proliferation, migration, differentiation, and capillary tube formation constitute the main features of angiogenesis. Angiogenesis is important for embryonic development, wound healing, and post-ischemic neovascularization. Endothelial NADPH oxidases, particularly NOX2 and NOX4, produce ROS that play important role in the regulation of angiogenesis ,161,162.ROS derived from NOX1 and NOX4 are important regulators of proliferation, hypertrophy and apoptosis in human pulmonary artery endothelial and smooth muscle cells, which can lead to airway and vascular remodeling. Lung airway and vascular remodeling lead to disorders such as pulmonary artery hypertension, chronic obstructive pulmonary disease, asthma, and neonatal bronchopulmonary dysplasia. Factors inducing NADPH oxidases and increased ROS generation in lung include hyperoxia, hypoxia, LPS, allergens, angiopoietin-2, EGF, TGF-β, bone morphogenetic proteins, interleukins, and S1P. Downstream, ROS activate transcription factors such as NF-κB and AP-1, which results in the development of inflammation and vascular cell proliferation . In caseSurprisingly, both ROS generation by NOX4 and ROS scavenging by thioredoxin 2 (TRX2) can promote angiogenesis. TRX2, a key mitochondrial ROS scavenger, promote EC survival and proliferation via elimination of ROS and thus enhancement of NO availability, and also via inhibition of apoptosis signaling kinase-1 (ASK1). The mechanism of cross-talk between NOX4 and TRX2 may depend on regulation by common angiogenic factors, such as hypoxia, ischemia, and VEGF , or spatEffects of NADPH-derived ROS on angiogenesis depend on isoform of NADPH oxidase. NOX4-generated ROS can promote vascular restoration after hypoxic and ischemic injuries and can inhibit vascular inflammation. However, in case of oxygen-induced retinopathy, NOX4 promotes pathological angiogenesis. NOX2 appears to be involved not only in normal physiological angiogenesis but also in pathological angiogenesis, in cases of choroidal neovascularization, retinopathy, and tumor growth. Moreover, NOX2-generated ROS were shown to inhibit physiological angiogenesis via activation of apoptotic signaling in the retina and the brain, but promotes vascular restoration in ischemic hindlimb. Additionally, activation of NOX2 by proinflammatory TNFα can contribute to vascular inflammation . NOX2-ge2H), and sulfonic acid (-SO3H). Protein tyrosine phosphatases contain a conserved cysteine residue in their catalytic domain and oxidation of this cysteine to sulfenic acid and sulfonic acid reversibly and irreversibly, respectively, inhibit tyrosine phosphatases [NADPH-produced ROS exert their actions on angiogenesis via regulation of intracellular signaling and gene expression. ROS regulate signaling proteins via reversible oxidation of cysteine residues to sulfenic acid (-SOH), sulfinic acid , and membrane type 1-MMP (MT1-MMP) .Since mitochondria also generate ROS, the cross-talk between NADPH oxidases, and mitochondria, the process referred to as ROS-induced ROS release (RIRR), contribute to VEGF- and angiopoietin-1-induced angiogenesis ,174,175.i-protein coupled receptors, as well as insulin receptor and other growth factor receptors. Although, the prevalent view is that ROS are responsible for an increase in paracellular endothelial permeability, accumulating data suggest that physiological ROS may be actively contributing to endothelial barrier stabilization or maintenance. Development of endothelial dysfunction involves numerous signaling proteins, and a few of them can be either activated or inhibited by ROS. In particular, vascular inflammation is one of primary conditions leading to vascular diseases. Of great interest would be to explore the causal relationships between ROS and the activities of transcription factors that regulate inflammatory response. Further investigations are needed to better delineate the boundary between normal physiological and pathological ROS levels. As ROS are tiny and short-lived, their live-cell, real-time observation is difficult. Nevertheless, the progress in the field depends on studies of complexes between sources of ROS and targets of ROS.The aim of this review was to analyze the literature evidence to test our hypothesis that ROS can evoke beneficial effects on ECs. Analysis of the available experimental data has shown that ROS can mimic, to some extent, signaling through the G


Collagen, an extracellular protein, covers the entire human body and has several important biological functions in normal physiology. Recently, collagen from non-human sources has attracted attention for therapeutic management and biomedical applications. In this regard, both land-based animals such as cow, pig, chicken, camel, and sheep, and marine-based resources such as fish, octopus, starfish, sea-cucumber, and jellyfish are widely used for collagen extraction. The extracted collagen is transformed into collagen peptides, hydrolysates, films, hydrogels, scaffolds, sponges and 3D matrix for food and biomedical applications. In addition, many strategic ideas are continuously emerging to develop innovative advanced collagen biomaterials. For this purpose, it is important to understand the fundamental perception of how collagen communicates with receptors of biological cells to trigger cell signaling pathways. Therefore, this review discloses the molecular interaction of collagen with cell receptor molecules to carry out cellular signaling in biological pathways. By understanding the actual mechanism, this review opens up several new concepts to carry out next level research in collagen biomaterials. Collagen regulates several intrinsic and extrinsic signaling pathways generally involving regeneration mechanisms. By triggering microenvironment cues, collagen greatly improves the healing process. Several studies have been initiated to explore the potential of collagen in tissue engineering ,2. NotabRegardless of raw materials, it is important to understand how collagen’s interaction modulates biological cellular activities during development, regeneration and repair to ensure tissue homeostasis. The interaction of collagen with biological cells is mainly facilitated by specific receptors that bi-directionally transmit mechanical signals from inside to outside and vice versa. To support this statement, Barczyk et al.  proved tAdditionally, the interaction of collagen with cells is closely related to growth factors and other modulations of the cytoskeleton complex. In general, extracellular signals of collagen often trigger specific cellular cascades pathways such as MAPK, RUNX2, JNK, ERK, STAT, NF-KB, ITAM, FcRγ, etc., to carry out biological reactions. Based on these facts, this review covers the pathways of the signaling interaction of collagen with biological cells in terms of regeneration and other biological applications. Therefore, this review helps biomaterial scientists understand the basic fundamental background of collagen in tissue engineering, which will create a new platform for innovative theories in collagen biomaterial research.As an abundant ECM protein, collagen possibly binds with at least five different groups of receptors in biological cells based on the available data. These are integrins, DDR, Glycoprotein VI, Osteoclast-associated receptor (OSCAR), LAIR-1, and uPARAP/Endo180. It is reported that collagen plays a biological role by binding with one or more of these receptors and activating cellular function.Integrins are well-known cell surface heterodimeric receptors distributed to almost all biological cells, which regulate the development and pathological processes of organs. Integrins constitute a major group of receptors for extracellular matrix components, including collagens. Integrins are widely distributed in organs such as skin, kidney, lungs, muscles, inner ears, eyes, heart, blood vessels, vascular endothelium, heart, gut (Peyer’s patches), lymphatic endothelium, mesenchymal tissue, cartilage and periodontal ligaments; and cells such as macrophage, platelets, fibroblasts, immune cells, bone cells, cancer cells, leucocytes , eosinophils, chondrocytes, embryonic stem cells and so on . IntegriBased on the available evidence from the literature, integrin α1β1 was first discovered by Hemler et al.  and is mThe α2β1 integrin, also known as VLA-2, GPIa-IIa, and CD49b, was first identified as an extracellular matrix receptor for collagens and/or laminins ,34. InteIntegrin α10β1 is a primary receptor of collagen type II that was first identified on chondrocytes in 1998 . Since cIntegrin α11β1 was identified on human fetal myotubes in 1995 by Gullberg et al. . Like inReceptor tyrosine kinase is also known as the discoidin domain receptor (DDR1 and DDR2), which plays an important role in the development and growth of organs and is generally activated by binding with different types of collagens such as collagen I–V ,50. SincDDR1, a transmembrane tyrosine kinase receptor, is an important collagen receptor for intracellular signals for cell proliferation, survival, homing, and colonization and is expressed in many cells and organs . TriggerGlycoprotein VI (GPVI) is an immunoglobulin-based transmembrane stimulatory receptor that is expressed in megakaryocytes and platelets and specifically binds with Gly-Pro-Hyp amino acid residues of collagen. The non-covalent interaction of GPVI with Fc receptor is attained by the presence of positively charged arginine in the transmembrane region. Additionally, the proline-rich motif of GPVI cytosolic tail selectively binds with the Src homology 3 (SH3) domain of the Src family tyrosine kinases Lyn and Fyn ,66. InsiThe G6B receptor belongs to the immunoglobulin (Ig) superfamily and is located in the MHC class III region. There are two types of receptor isoforms—G6B-A and G6B-B—with similar N-terminal and varying C-terminal cytoplasmic tails. This receptor binds with SHP-1 and SHP-2 through phosphorylation of immunoreceptor tyrosine-based inhibitory motifs (ITIMs) in its cytoplasmic tail. This receptor accelerates SHP-1 and SHP-2 through ITIMs in its cytoplasmic domain in order to inhibit signaling pathways. G6B is articulated on platelets and megakaryocytes, and functions as a negative regulator of platelet function .Human osteoclast-associated receptor (OSCAR) is another collagen receptor that belongs to the immunoglobulin (Ig) superfamily. This receptor is expressed in a wide range of myeloid cells and is specifically involved in osteoclast growth induction for bone resorption. The level of OSCAR expression is higher during osteoclastogenesis towards bone resorption, which could be achieved through triggering leukocyte receptor complex and FcRγ. Therefore, OSCAR is mainly essential for the differentiation of osteoclast, since it acts as a vital co-stimulatory receptor for osteoclast function and formation ,71,72,73LRC is a typical group of receptors primarily expressed in immune cells and plays a diverse role in immune functions such as autoimmunity, antiviral immunity, and graft tolerance ,75. The Fibronectin (FBN) is an abundant high MW glycoprotein in the extracellular matrix. FBN has multiple binding domains for several biomolecules such as collagens, proteoglycans and TGF-β; the first isolated domain of FBN, consisting of the 6FNI1–2FNII7–9FNI repeats near the N-terminus, is specific for collagen ,81. The Another glycoprotein of the extracellular matrix that binds with collagen is Vitronectin (VTN), which belongs to the hemopexin family and was first identified in serum, named as serum spreading factor . It is mThe urokinase plasminogen activator receptor-associated protein  is a multi-domain type I transmembrane glycoprotein that belongs to the mannose receptor family. It has several characteristic protein domains such as a series of 8–10 C-type lectin-like domains, cysteine-rich/ricin B-like domain, N-terminal and a fibronectin type-II domain. uPARAP/Endo180 located on the mesenchymal cell surface plays a major role in collagen internalization and turnover ,91,92,93Integrin, a major regulatory receptor, contributes to several biological functions of collagen. The molecular interaction of α1β1 integrin with collagen triggers several biological signals such as adapter protein activation, Grb2 recruitment, MAPK activation for cellular proliferation and phosphorylation of focal adhesion kinase (FAK) at Tyr-397 for fibroblast to myofibroblast differentiation in order to activate the Shc-mediated pathway in skin regeneration. In keratinocyte, collagen XVII binding with integrin α6β4 and α1β1 stimulates FAK, PI3K and Rac1 activity as a downstream consequence.Integrins have a strong affinity to collagen and transfer several biological signals from the extracellular region to the intracellular region and vice versa . In geneActivation of integrin by collagen phosphorylates FAK/Src pathways, which leads to upregulated cell proliferation and survival via downstream signaling pathways contributing to JNK/MAPK, ERK1/2, PI3K, Akt molecules and transcriptional gene regulation. The activated FAK/Src can also regulate cytoskeletal organization and cell motility in normal and diseased tissue states by mediating Rho/Rho-associated kinase (ROCK) signaling .The two subunits  of integrin can activate unique cellular activities such as growth, adhesion, differentiation and movement. The intracellular signaling pathway of the alpha subunit of integrin starts by recruiting and activating Src family kinases (SFKs), which additionally recruit FAK through the beta subunit, and the FAK activates signals from phosphatidylinositol 3-kinase (PI3K) to AKT/protein kinase B (PKB) with the help of phosphatidylinositol-3,4,5-trisphosphateP3), as well as employing Src for focal adhesions. The activated Src is further activated Rac by recruiting the Crk–DOCK180 complex and CAS-paxillin phosphorylation . Then, t2+ sensitization of vascular smooth muscle cell contraction [Interaction of collagen with α1β1 activates integrin-linked kinase (ILK) through upstream regulators such as phosphatidylinositol 3 kinase (PI3K), PIP3 lipid phosphatase (PTEN) and integrin-linked kinase-associated phosphatase 2C (ILKAP) , which rtraction ,111.In cardiac hypertrophy, the activation of ERK1/2 by collagen-bound integrin directly or indirectly depends on FAK autophosphorylation at Tyr925 through interacting with the Src homology 2 (SH2) domain of Src or Fyn, making a binding region for the signaling complex such as the adapter Grb2 and Ras GTP-exchange factor mSOS. A complex formation of Grb2 with Shc indirectly activates ERK through phosphorylation of FAK at Tyr925 that reframes the cytoskeleton and ERK cascade organization. Shc might also be involved in the initial high-level activation of ERK through a complex formation with Shc/Fyn/Cav-1, though it plays a different role (slow and sustained) in FAK-mediated ERK activation. Hence, based on the above mechanism, FAK can act as an upstream regulator of MAP kinase activity. However, integrins can also stimulate ERK independent of FAK activation through the involvement of PI3K and PKC activation .Empirical evidence confirmed that the intracellular signaling pathways are modulated by increasing integrin  expression on hepatocytes in a fibrotic liver, leading to the development of hepatocellular carcinoma ,114. HenSeveral noncollagenous domains of type IV collagen (α1(IV)NC1) are reported as novel inhibitors of tumor growth and angiogenesis . For insAnother study reported that inhibition of the FAK/PI3K/Akt/mTOR pathway in melanoma cells via subsiding the phosphorylation and activity of major proteins was achieved by the interaction of α1β1/αvβ3 integrin with noncollagenous (NC1) domain of collagen XIX (NC1(XIX)), providing new insight, i.e., anticancer treatments targeting this central signaling pathway in the development of melanoma are promising for the design of new anticancer drugs .Downregulation of TSC1 and TSC2 via activation of AKT and PI3K by collagen-bound integrin indirectly activates mTOR kinase activity through the GTP binding protein Ras homolog enriched in the brain (Rheb), creating a promising cancer therapeutic target ,120,121.The proliferation of tumor cells depends on matrix stiffness, less in soft matrix, and is regulated by multiple signaling pathways ,124,125.The binding affinity of collagen with different integrin proteins enables cells to express an enormous array of extracellular elements and facilitate unique signaling cascades in response to a changing matrix environment. For instance, the composition of collagen is attributed to a different binding pattern of integrins at the cell surface, contributing the development of epithelial–mesenchymal transition (EMT) under the control of the pericellular environment . RegardiOverall, the interaction of collagen with integrin is a key regulator in normal and diseased biological processes. The specific binding pattern of collagen with each integrin triggers unique signals for the regulation of various biological mechanisms, for instance, collagen binding with α1β1 activates FAK, ERK, MLCK, p-MLC and E-cadherin in endocytosis; activates ERK/MAPK and PI3K/Akt pathway in osteoblast growth; activates p-α-actinin, vinculin, paxillin, FAK, Shc and Grb2/Erk expression in chondrocytes; activates FAK and ILK signaling pathway to reduce cancer cell–cell adhesion; and inhibits FAK/c-Raf/MEK/ERK1/2/p38 MAPK activation in epithelial cells during antiangiogenic activity and tumor angiogenesis. In the case of α5β3, phosphorylation of p53 at Ser-376 and Ser-378 in PKCα, p53 relocalization (nucleus-cytoplasm), PUMA, Apaf 1, Bax, Bcl-2, Raf, MEK-1, ERK 1/2 and DAPK signals are regulated.Collagen binds to two types of DDRs including DDR1  and DDR2  spontaneously at the extra/intracellular juxtamembrane domain, N-terminus, tyrosine kinase domain at the C-terminus and transmembrane domain. Collagen binding with the discoidin domain causes conformation changes in DDRs and tyrosine kinase domain phosphorylation, leading to the engagement of ShcA and Nck2 adapter proteins to the cytoplasmic domain of DDRs. Unlike integrin , the ECM cell signal transduction mediated by DDRs is unidirectional.The action of DDR2 upon collagen II interaction indirectly depends on integrin or cytokines (Interleukin (IL)-1, Toll-like receptor (TLR) ligand) and advanced glycation end products-mediated signaling, resulting in activation of RAS/RAF/MEK/extracellular-regulated kinase (ERK), JNK, MTK, MKKs, p38-MAPK, activator protein 1 (AP-1) (cFos/cJun), E Twenty Six (ETS) factors, Runx2, HIF2α, C/EBPβ and NFκB translocation to nucleus, HIF2α, Elf3, and MMP13 signaling ,134,135.Extracellular fibrillary collagen-bound DDR2 mediates JNK/MAPK and PI3K/Akt signaling pathways to influence gene expression for proliferation and survival . Figure Collagen stimulation of DDRs intermediates several signaling molecules and adapters such as p85α PI3K, ShcA, STAT1/3/5β, the protein tyrosine kinases (PYK2 and CSK) and the phosphatases (SHP-2 and SHIP-1/2). Not only types of collagen and cells, cell–matrix communication or collagen-independent cell–cell communications also play a major role in triggering different signaling pathways by DDRs. Collagen-bound DDR1 activates JNK, NF-kB, p38, ERK1/2 MAPKs and PI3K/Akt, whereas inactivated DDR1 interacts with E-cadherin supporting cell–cell interactions. DDR1 also works together with other cell receptors such as Frizzled5 and Notch1 to support or alienate collagen-binding integrin signaling pathways linked to cell growth and movement, whereas DDR2 promotes cell migration by interacting with the insulin receptor and, hence, activates MAPKs including p38 and ERK/JAK2 signaling pathway .It was reported that collagen-bound DDR2 triggers PI3K/Akt and JNK/MAPK signaling pathways  to upregDDR1 is mainly involved in cell differentiation and remodeling through various signaling pathways, for instance, alternative splicing of tyrosine-513 of DDR1b is related with the PTB domain of ShcA upon receptor activation . DDR1-meDDR1 has been overexpressed in multiple cancers such as non-small-cell lung carcinomas, pancreatic ductal adenocarcinoma, ovarian tumor, breast cancer, gastric cancer, endometrial tumors, glioblastoma, head and neck squamous cell carcinomas, esophageal carcinoma, cholangiocarcinoma, non-small-cell lung cancer, hepatocellular carcinoma, and prostate cancer. Likewise, DDR2 is also overexpressed in acute myelocytic leukemia, thyroid cancer, cholangiocarcinoma, Hodgkin’s lymphoma, breast cancer, and nasopharyngeal carcinoma .Collagen-bound DDR1 activates the interaction of PTP and SH2-SH2 domains of SHP-2 and the docking sequence in the cytoplasmic domain of DDR1. This interaction between DDR1 and SHP-2 is interrupted by the mutation of tyrosine residues 703 and 796 in DDR1, which subsequently restore collagen-induced cell migration, Stat1/Stat3 activation, and HGF-induced branching tubulogenesis . Ample eIt has been reported that collagen from ECM controls cancer cell behavior by regulating invasiveness and mortality of cells ,142,143 In vitro studies disclosed that the action of fibrillary collagen can be regulated by DDR2 in order to accelerate vascular endothelial growth factor (VEGF) expression and lung fibroblasts to undergo myofibroblastic changes through phosphorylation of Akt, p38, ERK1/2 and Smad2. The studies conclude that the activation of myofibroblast and neovessel formation during pulmonary fibrosis can be prevented by targeting the DDR2 signaling pathway . In tumoIn vitro 3D cell culture demonstrated that the DDR1 enhances chemo-resistance by the STAT3 and NF-kB signaling pathway in Jurkat cells and T47D breast cancer cells ,151. TheWhen collagen interacts with cancer cell DDR1/2, a non-canonical NFκB2 (p52/RelB) resistance pathway is activated. The matrix-mediated drug resistance is achieved by activating NIK, IKKa, and p52, and the MEK1/2 and ERK1/2 regulate the proliferation and survival of melanoma cells Inhibition of DDR1 resulted in upregulation of E-cadherin and downregulation of N-cadherin and vimentin protein expression, confirming that DDR1 inhibition decreased cell survival and proliferation of prostate cancer cells by downregulating P-DDR1, P-Pyk2, and P-MKK7 levels, which leads to G1 cell cycle arrest and induced cell death by an increase in the Bax/Bcl-2 ratio, depletion of the mitochondrial membrane potential, and reactive oxygen species creation. Further, DDR1 inhibition prevents EMT through the MKK7 and Pyk2 signaling pathways, which cause apoptosis in the prostate tumor cell. Accordingly, DDR1 activates EMT via stimulating the protein expression of N-cadherin and vimentin and phosphorylation of Pyk2 and MKK7 in prostate cancer .The interaction of collagen and DDR1 promotes EMT via the JNK1–c-Jun pathway with the help of integrins. Along with DDR1, DDR2 also induces EMT by activating NF-κB, LEF-1 transcription factors and other transcription factors (TFs) to upregulate the expression of SNAI1/2 and LEF1 . The actDDR1 activates ERK 1/2 in mammary epithelial, smooth muscle, transfected embryonic kidney cells, and megakaryocytes ,155 and The interaction between collagen and GPVI plays an important role in platelet signaling. In platelets, binding of collagen with GPVI recruits PPARγ to interact with the adapter molecule, Syk , leadingCollagen triggers platelet activation by phosphorylation of downstream signal molecules of the collagen-specific receptor GPVI signal pathway, including ITAM-Syk, PLCy2, and PI3K-Akt-GSK3β, which is inhibited by αIIbβ3-mediated β3-Src signals .2+ mobilization, degranulation, aggregation, and platelet integrin activation. GPVI/FcR γ-chain-mediated signaling in platelets is negatively regulated by immunoreceptor tyrosine-based inhibition motif (ITIM)-containing receptors including CEACAM1, PECAM-1, or G6b [More specifically, the interaction of repetitive glycine–proline–hydroxyproline (GPO) motifs of collagen with GPVI dimers triggers subsequent signaling pathways including Src kinases Fyn/Lyn-mediated tyrosine phosphorylation of the FcR γ-chain–ITAMs , tyrosin, or G6b .Collagen interaction with GPVI triggers a series of signaling cascades by the release of synthesis of thrombin, and granule-stored mediators  such as Collagen stimulation is activated by several cellular receptors of the platelets including integrin α2β1 for platelet adhesion to collagen and GPVI for platelet activation. The cytoplasmic domain of GPVI is noncovalently attached to the Fc receptor γ chain (FcRγ) and activates tyrosine phosphorylation of ITAM by SFKs (mainly Lyn and Fyn) with the help of CD148, a receptor-like protein tyrosine phosphatase ,173. The2+ mobilization and NOX-mediated ROS production. The higher intracellular Ca2+ level activates PLA2 for the production of ROS by COX1 during AA conversion in TXA2. In the Syk-independent pathway, TRAF4 and Lyn activate NOX by interacting with PKC and thrombin-PAR1/PAR4 and release ROS in the extracellular environment. NOX-mediated ROS production is also triggered by the interactions of sCD40L/CD40, ox-LDL/CD36 and TXA2/TP [ROS production mediated by collagen and GPVI interaction depends on two different pathways such as Syk-dependent and Syk-independent pathways. In the Syk-dependent pathway, the cytoplasmic tail of GPVI-containing TRAF4 and Src family kinase Lyn triggers phosphorylation of ITAM sequences, activating PI3K and Syk, which activates the (PLCγ2)–IP3/PKCs axis, Ca TXA2/TP .Oscar, a specific collagen receptor to collagen I–III motifs, is involved in the normal development, maintenance and repair of bone. Oscar is widely expressed on human myeloid and osteoclast precursor cells and acts as a positive regulator for collagen-induced osteoclast formation to support bone resorption  through Oscar-FcRγ mediated activation of CAMK IV and calcineurin releases co-stimulatory signals to amplify the induction of NFATc1 during RANK–RANKL interaction in order to support osteoclast activation and maturation . The rec2+ and calcineurin [The process of bone development, maintenance and repair starts by the accumulation of osteoclast precursor cells to the collagen-rich bone surfaces from the circulation (blood capillaries) by transendothelial migration that expresses RANKL and collagen I/III ,183, whicineurin .Collagen-bound Oscar upregulates the osteoclastogenic effect of RANKL by co-stimulatory signaling pathways through the stimulation of DAP12/FcRγ-Syk-PLCγ signaling cascade that triggers calcium signaling and NFATc1 induction. More specifically, Oscar transduces signals to the immunoreceptor tyrosine-based activation motif in DNAX-activation protein 12 and the Fc receptor common γ subunit and then activates the downstream signals of Syk and phospholipase C γ2 (PLCγ2) ,186.LAIR1 acts as an inhibitory receptor to negatively regulate the osteoclastogenic stimulatory effect of Oscar, even though both receptors belong to the LRC family. Collagen interaction with LAIR-1 (primarily expressed in NK cells) triggers biological signals to maintain the immune tolerance at the maternal–fetal interface by downregulating the activity of NK cells. Collagen-bound LAIR-1 initiates the interaction of SHP-1 to JAK1/2 in NK cells and thereby reduces phosphorylation of STAT1/4 and IFN-γ and TNF-α production. Collagens alone do diminish the expression of natural cytotoxicity receptor NKp30 and perforin production , and uprThe attachment of collagen to LAIR extracellular surface phosphorylates LAIR1 ITIM tyrosin residues by Src family kinases and further recruits SHP-1 and SHP-2 phosphatases through ITIMs regulatory SH2 domains to carry out phosphatase activity . The actThe uPARAP or Endo180 (CD280 or MRC2)-associated type 1 membrane protein, an endocytic receptor for collagen, belongs to a mannose receptor family consisting of three main domains (a cysteine-rich (CR), fibronectin-type II (FNII) and tandemly arranged C-type lectin-like domains ). The collagen-bound uPARAP regulates the collagen turnover in biological cells. However, the actual signaling mechanism of uPARAP with collagen interaction in collagenolysis is not well known. It is established that native intact and partially degraded collagen can be processed by the interaction of uPARAP/Endo180 with components of the plasminogen activator system. The uPARAP interacts with collagen through their common domains such as FNII domain for collagen binding, CR domain for sulfated carbohydrates recognition and CTLD domain for binding to mannose .Therefore, among the three domains, the FnII domain of uPARAP plays a key role in interacting collagen with uPARAP; however, the lack of three domains leads to it being incapable of internalizing collagen . It is oBased on the theoretical evidence, most of the diseases are partially (indirectly) or completely (directly) regulated by at least one of the collagen binding cellular receptors such as integrins, DDRs, GPVI, OSCAR, LAIR, Endo180, etc. Additionally, it is opined that the regulation of collagen receptor controls cancer growth, delivery systems and the regeneration of tissues such as skin, bone, tendon, cartilage, neural, etc.Overall, this review summarizes the possible signaling mechanism of collagen interacting with the cell receptors for biological functions. The activation of different types of cell receptors highly depends on the molecular pattern and types of collagen. By analyzing the hypothesis, the collagen receptors act as stimulatory and inhibitory receptors for various biological signaling pathways, and the signaling mechanism of collagen-bound receptors is regulated by the microenvironment of cells (intra and extracellular cues). It is evident that regulating specific cell signaling pathways by manipulating the interaction of collagen with its receptor is a breakthrough in future therapeutic treatment. Therefore, this review provides the fundamental basis of the signaling mechanism of collagen-induced cell receptors in normal and diseased physiological functions.


The F-box protein 22 (FBXO22), an F-box E3 ligase, has been identified to be critically involved in carcinogenesis. However, a systematic assessment of the role of FBXO22 across human cancers is lacking. Here, we performed a pan-cancer analysis to explore the role of FBXO22 in 33 cancer types using multiomic data from The Cancer Genome Atlas (TCGA). First, we found that high FBXO22 expression in multiple cancers was closely associated with poor overall survival and relapse-free survival. Next, we identified ten proteins that interact with FBXO22 and 13 of its target substrates using the STRING database and a literature search to explore the regulatory role of FBXO22 in tumorigenesis. Genes encoding these proteins were found to be significantly enriched in cell cycle negative regulation and ubiquitination pathways. This was confirmed in nonsmall cell lung cancer A549 cells, where FBXO22 overexpression enhanced cyclin-dependent kinase 4 (CDK4) protein levels and promoted cell proliferation. Similarly, overexpression or interference of FBXO22 changed the protein level of one of its substrates, PTEN. Additionally, we found that FBXO22 mutations were accompanied by altered substrate expression, especially in uterine corpus endometrial carcinoma and lung adenocarcinoma; endometrial carcinoma patients with FBXO22 genetic alterations also had better overall and relapse-free survival. Notably, FBXO22 methylation levels were also decreased in most tumors, and hypomethylation of FBXO22 was associated with poor overall survival, relapse-free interval, and progression-free interval in pancreatic adenocarcinoma. Finally, we analyzed the correlation between the abundance of tumor infiltrating lymphocytes (TILs) and FBXO22 expression, copy number variation, and methylation. Multiple algorithms revealed that high FBXO22 expression was associated with lower TIL levels, especially in lung adenocarcinoma, lung squamous cell carcinoma, and sarcoma. Taken together, our findings demonstrate that FBXO22 degrades tumor suppressor genes by ubiquitination and inhibits the cell cycle to promote nonsmall cell lung cancer progression. Our study also provides a relatively comprehensive understanding of the oncogenic role of FBXO22 in different tumors. The correlations between protein posttranslational modifications (PTMs) and cancer progression have been extensively studied. Targeting regulators of PTM represents a promising strategy for anticancer treatment. Thus, mining cancer genomic data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to explore the clinical prognosis and potential molecular mechanisms of PTM-related genes is important.F-Box only protein 22 (FBXO22), a PTM regulator, is a member of the F-box protein family with E3 ligase activity . Recentlvia proteasome-mediated degradation in colorectal cancer, leading to tumorigenesis  ubiquitination and degradation, which is involved in tumorigenesis . A recenvia upregulating HIF1α and VEGFA , vascular endothelial growth factor A (VEGFA), matrix metalloproteinase-1 (TIMP-1), and matrix metalloproteinase-9 (MMP-9) , 16. FBXnd VEGFA . FBXO22 These studies suggest that FBXO22 plays an important role in tumorigenesis, especially in mediating ubiquitinated degradation of proteins. However, the role of FBXO22-mediated ubiquitination of substrates in human cancer is poorly understood. Here, we performed a pan-cancer analysis of FBXO22 using TCGA database to explore the role of FBXO22-mediated ubiquitination in cancer. We also analyzed a group of factors, such as gene expression, survival status, DNA methylation, genetic alteration, immune infiltration, and relevant cellular pathway, to investigate the potential molecular mechanism of FBXO22 in the pathogenesis or clinical prognosis of different cancers.www.proteinatlas.org) in order to obtain FBXO22 expression levels in different healthy cell and tissue types. Next, we downloaded HTSeq-FPKM data for 33 cancer types from TCGA using the software package TCGAbiolinks (v2.20.0)   in R (v4v2.20.0)  to obtaiv2.20.0) , 20..0  in R FBXO22 gene in each cancer type, and overall and relapse-free survival (RFS) analyses were performed. We performed a “tumor vs. normal” meta-analysis, a “survival” meta-analysis, and an “overall survival” (OS) analysis of FBXO22 gene expression using the LUNG CANCER EXPLORER service , human bronchial epithelial cells 16HBE, and HEK293T cells were purified from the Chinese Academy of Sciences Shanghai cell bank . A549 and 16HBE cells were cultured in Dulbecco’s modified Eagle’s medium  supplemented with 10% fetal bovine serum . Human NSCLC H1975 cells were cultured in RPMI-1640 medium  with 10% FBS. For DNA methyltransferase inhibition assays, SGI-1027  was added to the culture medium for a final concentration of 2, 4, or 8 μM. All cells were cultured in a humidified cell incubator at 37°C with 5% CO3 per well and cultured for 1, 2, and 3 days. CCK-8 solution (10 µl) was added into each well at the indicated time points, then the plates were stored for 2 h at 37°C. Next, the number of viable cells was estimated by measuring the absorbance at 450 nm.Cell proliferation was evaluated using a Cell Counting Kit-8 (CCK8) assay . In brief, cells were seeded in 96-well plates at a concentration of 3 × 10g for 10 min, the protein content in the supernatant was determined using the BCA protein assay kit . Equal amounts of protein were boiled by adding 4× sample loading buffers for 10 min at 100°C and resolved using sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE). Antibodies against α-tubulin (11224-1-AP), CDK4 (11026-1-AP), and FBXO22 (13606-1-AP) were purchased from Proteintech , DNTM1 (ab188453) were purchased from Abcam , and PTEN (9188S) and ubiquitin (3936S) were purchased from Cell Signaling Technology .Cells were collected and lysed using Qproteome™ Mammalian Protein Prep Kit . After centrifugation at 13,800×g for 10 min at 4°C, the supernatant (whole-cell lysate) was collected from each sample. PTEN antibodies were incubated with protein A magnetic beads at room temperature for 4 h, and unbound antibodies were washed off with elution buffer. Subsequently, the beads were incubated with cell lysate supernatants at 4°C overnight. The precipitates were washed three times with immunoprecipitation buffer, boiled in sample buffer, and Western blot analysis was then performed.Cells were harvested, lysed, and briefly sonicated. After centrifugation at 12,000×Plasmids pLV[Exp]-EGFP:T2A:Puro-CMV>FLAG/hFBXO22[NM_147188.3] (VB210508-1064ndh), pRP[shRNA]-EGFP:P2A:Puro-U6>Scramble[shRNA#1] (VB200706-2709njm) and pRP[shRNA]-EGFP:P2A:Puro-U6>hFBXO22[shRNA#1] (VB210408-1046ugc) were purchased from VectorBuilder . For the lentiviral packaging, we used pCMV delta R8.2 (Addgene 12263) and pCMV-VSV-G (Addgene 8454) systems. For plasmid transfection, we used Lipofectamine 2000 .The Catalogue of Somatic Mutations in Cancer (COSMIC) is the largest source of expert manually curated somatic mutation information relating to human cancers in the world . First, To assess the methylation level of FBXO22 in cancer and healthy tissues, we used “TCGA” module in the UALCAN database to obtain boxplots for FBXO22 methylation level in COAD, PRAD, CESC, TGCT, READ, KIRP, LUAD, LUSC, BRCA, UCEC, and SARC . DNMIVD TISIDB, a web portal for tumor and immune system interaction , was usep < 0.05, and all statistical tests were two-sided. All statistical data were analyzed using R or online analysis tools described in the relevant Materials and Methods subsections.Correlations between variables were explored using Spearman’s coefficients. Wilcoxon’s rank-sum tests were used to compare continuous variables between binary groups. Survival curves for categorical variable prognostic analyses were generated using the Kaplan-Meier method, while the log-rank test was used to estimate statistical significance. The significance level was set at First, we aimed to characterize the expression level of FBXO22 in different healthy tissues and cells, based on consensus data from the human protein atlas (HPA) database. The expression of FBXO22 gene was highest in the liver, followed by the placenta and adrenal gland, and lowest in the ductus deferens  compared with adjacent healthy tissues, but no significant difference in expression was observed in PRAD or KIRC (p = 0.016), ACC (log-rank p = 0.097), UVM (log-rank p = 0.031), PAAD (log-rank p = 0.014), and SARC (log-rank p = 0.21). Conversely, low FBXO22 expression was associated with poor prognosis and OS in patients with ESCA (log-rank p = 0.32) or KIRC (log-rank p = 0.002). We also observed that high expression of the FBXO22 gene was associated with poor RFS in KICH (log-rank p = 0.039), ACC (log-rank p = 0.011), UVM (log-rank p = 0.16), and HNSC (log-rank p = 0.39), but with better RFS in COAD (log-rank p =0.022), ESCA (log-rank p = 0.22), and TGCT (log-rank p = 0.14). Additionally, we used the LUNG CANCER EXPLORER service to perform tumor vs. normal and survival meta-analyses in different lung cancer datasets. We found that FBXO22 expression was positively associated with hazard rate (HR) in most datasets , progression-free (p = 0.0395), and disease-specific (p = 0.091) survival, but not disease-free (p = 0.357) survival, compared with cases without FBXO22 alteration among UCEC cases  and are involved in the occurrence, development, and metastasis of tumors . HoweverTo avoid computational errors arising from the use of a single algorithm and different marker gene sets of TIICs, we utilized the CIBERSORT, CIBERSORT-ABS, EPIC, MCP-counter, quanTIseq, TIMER, TIP, and xCell algorithms to evaluate the correlation between FBXO22 expression and the level of immune infiltration of TILs. Although there were differences in the levels of immune cell infiltration calculated using different algorithms, we noted that the calculations produced by at least five of the algorithms showed that B-cell and macrophage infiltration levels were negatively correlated with FBXO22 expression in multiple cancers, including LUAD, LUSC, and SARC Figure 6Antitumor immune responses can be conceptualized as a series of stepwise events including the release of cancer cell antigens (step 1), cancer antigen presentation (step 2), priming and activation (step 3), trafficking of immune cells to tumors (step 4), infiltration of immune cells into tumors (step 5), recognition of cancer cells by T cells (step 6), and killing of cancer cells (Step 7) . Xu and via the proteasome, and this alters their localization, affects their activity, and promotes or interferes with protein interactions, thereby affecting the regulation of cellular events such as proliferation, apoptotic death, and cell cycle progression  can lead to inappropriate regulation of protein levels and promote tumorigenesis. Degradation of proteins by ubiquitylation is an important mechanism of PTM and is involved in multiple diseases, including multiple types of cancer. Ubiquitinated proteins are degraded gression . DysreguThe results of our analysis showed that FBXO22 was highly expressed in multiple cancer types. Nevertheless, the impact of FBXO22 expression on survival outcomes varied depending on the cancer type, and variation in data sources may also lead to variable results for the same cancer type. For example, we used the LUNG CANCER EXPLORER tool to perform survival analysis in the lung cancer datasets GSE37745  and GSE1Although many studies have shown that FBXO22 is involved in oncogenesis owing to its ubiquitination activity and the subsequent degradation of multiple proteins , 7, 11, The genetic alteration of FBXO22 may affect the expression level of substrates. The highest alteration frequency of FBXO22, in which “mutation” was the primary type, appears in patients with UCEC, as established using the cBioPortal tool; we discovered that those with this alteration in FBXO22 had a better prognosis in terms of overall, progression-free, and disease-specific survival compared with those without the FBXO22 alteration. Notably, the expression of FBXO22 in UCEC patients was not significantly associated with OS or RFS. This may be because, in a subset of cancer types, changes in FBXO22 expression levels alone are not sufficient to affect tumor progression, and genetic alterations in FBXO22 have a more pronounced effect on tumors. Indeed, mutations in FBXO22 in UCEC were accompanied by increased expression of multiple substrate genes in our analysis, including CDKN1A, KDM4B, STK11, and PTEN. Therefore, genetic alterations in FBXO22 have a greater impact on UCEC specifically.DNA methylation is one of the most abundant and well-studied epigenetic modifications, playing an essential role in tumorigenesis . Using tThe number, localization, and phenotypes of TILs have an important effect on cancer progression . We founTaken together, our pan-cancer analyses revealed correlations between FBXO22 expression, methylation, mutation and clinical prognosis, and immune cell infiltration, which contribute to a better understanding of the role of FBXO22 in tumorigenesis. In future studies, the potential relationship between FBXO22 methylation and expression and antitumor immunity warrants in-depth exploration. Our analysis provided a relatively comprehensive understanding of the oncogenic role of FBXO22 in different tumor types. In addition, FBXO22 has been discussed as a new potential therapeutic target for hepatocellular carcinoma ; based oThe original contributions presented in the study are included in the article/YW and XC designed this work. SC and SM analyzed the data. HW, JY, BD, ZG, and YM helped or performed experiments and analyses. XC helped in the revision of the manuscript. SC and SM wrote the manuscript.This work was supported by grants from the National Science and Technology Major Project of China (Grant No. 2019ZX09201004-001).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


EMC2 in breast cancer have not been entirely determined. The potential roles of EMC2 in different tumors were explored based on The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Gene Expression Profiling Interactive Analysis 2 (GEPIA2), Tumor Immune Estimation Resource (TIMER), Shiny Methylation Analysis Resource Tool (SMART), starBase, and cBioPortal for cancer genomics  datasets. The expression difference, mutation, survival, pathological stage, DNA methylation, non-coding RNAs (ncRNAs), and immune cell infiltration related to EMC2 were analyzed. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to identify the differences in biological processes and functions among different related genes. The expression levels of core prognostic genes were then verified in breast invasive carcinoma samples using immunohistochemistry and breast invasive carcinoma cell lines using real-time polymerase chain reaction. High expression levels of EMC2 were observed in most cancer types. EMC2 expression in breast cancer tissue samples correlated with poor overall survival. EMC2 was mutated and methylated in a variety of tumors and affected survival. The LINC00665-miR-410-3p axis was identified as the most potential upstream ncRNA-related pathway of EMC2 in breast cancer. EMC2 levels were significantly positively correlated with tumor immune cell infiltration, immune cell biomarkers, and immune checkpoint expression. Our study offers a comprehensive understanding of the oncogenic roles of EMC2 across different tumors. The upregulation of EMC2 expression mediated by ncRNAs is related to poor prognosis and tumor immune infiltration in breast cancer.Ferroptosis is an iron-dependent programmed cell death process. Although ferroptosis inducers hold promising potential in the treatment of breast cancer, the specific role and mechanism of the ferroptosis-related gene  Cancer is the leading cause of death and an essential obstacle to increasing life expectancy, globally. With the aging of populations and increasing socio-economic development, the burden of cancer is rapidly increasing. According to the 2020 Global Cancer Statistics Report , female EMC1 mutations are associated with severe human neurodegenerative diseases, which manifest as growth retardation, cerebellar atrophy, scoliosis, hypotonia, psychomotor retardation, epilepsy, and craniofacial abnormalities  related to EMC2, including microRNA (miRNA) and long non-coding RNA (lncRNA), in breast cancer. Finally, we determined the relationship between EMC2 expression and immune cell infiltration, immune cell biomarkers, or immune checkpoints in breast invasive carcinoma (BRCA). Taken together, our findings indicate that the ncRNA-mediated upregulation of EMC2 expression is associated with prognosis and poor tumor immune infiltration in of BRCA.In this study, we performed expression, survival, and mutation analyses for https://genome-cancer.ucsc.edu/. For differential expression analysis, the R (version “4.1”) package ‘limma’ was used (https://www.oncomine.org/resource/login.html). Search for “TTC35”, threshold : 0.05, threshold (fold change): 1.5, threshold (gene rank): Top 10%, data type: all  is a tumor/normal differential expression analysis based on TCGA and gene tissue expression (GTEx) data, for analysis according to cancer type or pathological stage, patient survival analysis, network tools for similar gene detection, correlation analysis, and dimensionality reduction analysis , as well as to evaluate the prognostic value of candidate lncRNAs in BRCA. A log-rank p-value < 0.05 was considered statistically significant. In addition, the GEPIA2 database was used to evaluate the correlation between EMC2 expression in BRCA and immune checkpoints. Absolute values of R > 0.1 and p < 0.05 were judged as statistically significant. Univariate and multivariate Cox proportional hazards models were used for survival analysis, and the R package ‘Survival’ (2.41-3) was used for the Kaplan–Meier estimation of OS.Gene expression profiling interactive analysis 2 , “TCGA Pan-Cancer Atlas Research” was selected in the “Quick Selection” column, and “EMC2” was entered to query gene mutation characteristics  is a user-friendly and easy-to-use web application for comprehensively analyzing the DNA methylation data of TCGA  is the most comprehensive database of mRNA and protein-RNA interaction networks  was used to perform a hsa-miR-410-3p survival analysis on BRCA, and a log-rank p-value < 0.05 was considered statistically significant (The online Kaplan–Meier plotter (nificant .https://cistrome.shinyapps.io/timer/) is a web server for the comprehensive analysis of tumor-infiltrating immune cells . The MCF7 and MDA-MB-231 cells were maintained in high-glucose Dulbecco’s modified Eagle medium  supplemented with 10% fetal bovine serum , and 1% penicillin–streptomycin (Gibco). The MFC10A cells were cultured in DMEM/Ham’s F-12 medium (Invitrogen) supplemented with 10% FBS (Gibco), 0.5 µg/ml hydrocortisone , 20 ng/ml epidermal growth factor (Sigma-Aldrich), 10 μg/ml insulin (Sigma-Aldrich), and 1% penicillin–streptomycin (Gibco). Cells were cultured in a humidified atmosphere containing 5% CO–ΔΔCt method was used to calculate the relative gene expression levels and then normalized against GAPDH. Primers were designed and synthesized by Sangon Biotech . The primer sequences are listed in Total RNA was extracted from the normal human breast epithelial cell line MCF 10A and breast cancer cell lines MCF7 and MDA-MB-231 using TRIzol reagent (Sigma-Aldrich). The extracted RNA was reverse-transcribed to cDNA using HiScript II Q RT SuperMix . Real-time PCR was performed on a QuantStudio™ 6 Flex  using ChamQ SYBR qPCR Master Mix . The 2p-value < 0.05 or log-rank p-value < 0.05 was considered to be statistically significant.The statistical analysis in this study was automatically calculated by the online databases mentioned in the above sections. A EMC2 in carcinogenesis, we first analyzed its expression in 33 human cancers. As shown in EMC2 was expressed differently in 22 cancer types, of which 18 were highly expressed in the tumor group, that included breast invasive carcinoma (BRCA), cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), lymphoid neoplasm diffuse large B-cell lymphoma (DLBC), glioblastoma multiforme (GBM), head and neck squamous cell carcinoma (HNSC), kidney chromophobe (KICH), kidney renal clear cell carcinoma (KIRC), brain lower grade glioma (LGG), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), pancreatic adenocarcinoma (PAAD), prostate adenocarcinoma (PRAD), rectum adenocarcinoma (READ), stomach adenocarcinoma (STAD), skin cutaneous melanoma (SKCM), and thymoma (THYM). There were four cancer types with low expression in the tumor group, comprising acute myeloid leukemia (LAML), ovarian serous cystadenocarcinoma (OV), testicular germ cell tumors (TGCT), and thyroid carcinoma (THCA). However, BRCA, CHOL, DLBC, GBM, HNSC, KIRC, LAML, LIHC, LUAD, LUSC, OV, PAAD, PRAD, SKCM, STAD, TGCT, and THYM showed significant differences in 17 tumors. We further verified the expression of EMC2 in tumors containing paired samples. As shown in EMC2 in BRCA, CHOL, esophageal carcinoma (ESCA), HNSC, KIRC, papillary renal cell carcinoma (KIRP), LIHC, LUSC, STAD, and THCA compared with the corresponding adjacent normal tissue controls. Second, we used GEPIA2 to analyze the influence of EMC2 expression on tumor grading and found significant differences in COAD, ESCA, KIRC, and TCGT , BRCA, and uveal melanoma (UVM); however, KIRC patients with higher EMC2 expression showed a better prognosis  patients with high EMC2 expression levels had better prognostic survival . Therefore, the expression of EMC2 in breast cancer can have significant effects on factors such as tumor progression and even patient survival. GO and KEGG enrichment analysis found that genes positively related to EMC2 are mainly involved in RNA transport and cell cycle regulation , followed by breast cancer (10.33%). Uterine corpus endometrial carcinoma (UCEC) was mainly of the “mutation” type, and its mutation frequency was about 4.54%. Some patients (about 1.15%) with mesothelioma lacked EMC2. EMC2 mutations. In addition, we explored the potential relationship between EMC2 mutations and the clinical survival and prognosis among patients with different cancer types. EMC2 mutations, those with EMC2 mutations had decreased OS (p = 3.384e-4), disease-free survival (p = 1.137e-3), and progression-free survival (p = 8.209e-4), whereas the disease-specific survival rate (p = 2.81e-7) was particularly poor. In breast cancer patients, survival was not affected by the above mentioned mutations. Considering the number of clinical samples, the effect of EMC2 structural mutations on breast cancer prognosis requires further analysis.We observed EMC2 promoter were significantly methylated in the tumor samples compared to in the normal samples of most cancer types  cells, T helper cells , and neutrophils.Immunotherapy is a treatment method that enhances or inhibits immune system function to cure diseases. Immunotherapy has achieved satisfactory results in malignant melanoma, lung cancer, and other tumors. Compared with lung cancer and melanoma, breast cancer is considered a “weakly immunogenic” tumor, and its immunotherapy effect is not sufficient. Therefore, it is necessary to find new genes to improve the immunotherapy of breast cancer. As correlation analysis can provide critical clues for studying EMC2 in tumor immunity, we used the GEPIA database to determine the correlation of EMC2 expression with immune cell biomarkers in BRCA. As shown in EMC2 showed correlation with B-cell biomarkers (CD19 and CD79A), CD8+ T cell biomarkers (CD8B), M1 macrophage biomarkers (IRF5), M2 macrophage biomarkers (CD163 and MS4A4A), dendritic cell biomarkers , NK cell biomarkers , mast cell biomarkers (TPSB2 and TPSAB1), Th1 cell markers (TNF-α), Th2 cell markers (GATA3), Th17 cell markers (STAT3), and Tfh cell markers (BCL6). These findings partially indicate a significant correlation between EMC2 expression and immune cell infiltration.To further explore the role of EMC2 in BRCA, the relationships between BRCA and PD1, PD-L1, CTLA-4, and TIM-3 were evaluated. EMC2 expression is significantly positively correlated with PD-L1, CTLA-4, and TIM-3 in BRCA, regulated by purity. From the expression correlation analysis, we also found that EMC2 was significantly positively correlated with PD-L1, CTLA-4, and TIM-3 in BRCA .After analyzing EMC2 is still unclear, and further research is needed.The incidence and mortality of breast cancer in women rank first and second globally, respectively . This diEMC2 in cancer, in this study, we aimed to perform a pan-cancer analysis of EMC2 expression using TCGA. We found that EMC2 is highly expressed in many tumors, but lowly in LAML, OV, TGCT, and THCA. The survival analysis of EMC2 in tumors shows that BRCA patients with high EMC2 expression could have a poor survival prognosis. In general, hypermethylation of genes lead to downregulated gene expression  as an oncogene in various tumor, including breast cancer. For example, knockdown of LINC00665 significantly inhibits the growth of breast cancer cells in vitro, significantly weakens the migration and invasion abilities, reduces the expression of EMT-related genes, and promotes apoptosis. By contrast, the overexpression of LINC00665 can promotes breast cancer progression  can be found in the article/XL designed the research framework and revised the manuscript. XL, PY, QZ, and LH contributed to the data analysis. XL wrote the manuscript. XS and QQ provided comments during the writing. All authors contributed to the article and approved the submitted version.This study was supported by the National Natural Science Foundation of China .The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.