SFXN3) is an important mitochondrial serine transporter during one-carbon metabolism, which is involved in the proliferation of cancer cells. However, the specific role of SFXN3 in HNSC remains unknown. In this study, we performed expression and survival analysis for SFXN3 in pan-cancer using data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) and found that SFXN3 served as a potential oncogene in HNSC. Notably, SFXN3 expression was found to be positively associated with enriched tumor-infiltrating macrophages, other immune suppressive cells, and immune checkpoint expression and resistance to paclitaxel. Gene, clinical, and immune variables included in the univariate and multivariate analyses showed that SFXN3 expression was an independent risk factor. Moreover, the LINC01270/hsa-miR-29c-3p/SFXN3 axis was identified as the most likely upstream non-coding RNA-related pathway of SFXN3 in HNSC using bioinformatic analysis, expression analysis, correlation analysis, and survival analysis. Taken together, our findings demonstrated that a non-coding RNA-mediated high expression of SFXN3 is a prognostic biomarker and is associated with the immunosuppressive microenvironment in HNSC.Chemoresistance is the leading cause of poor prognosis in head and neck squamous cell carcinoma (HNSC); however, promising biomarkers to identify patients for stratified chemotherapy are lacking. Sideroflexin 3 ( Head and neck cancer is the seventh most common cancer globally, and squamous cell carcinoma is the most common histological type , 2. The SFXN3) is a member of the sideroflexin family, of which there are five homologs of these mitochondrial proteins in humans. The expression of SFXN homologs varies across tissues  related to the regulation of SFXN3, such as long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), were also investigated in HNSC. Taken together, our findings suggested that the ncRNA-mediated upregulation of SFXN3 was associated with poor prognosis, paclitaxel resistance, and the immunosuppressive microenvironment in HNSC.In this study, we analyzed the expression and prognostic value of https://xenabrowser.net/) database. The samples of common cancer types were used for further analysis, including glioblastoma multiforme (GBM), cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), lung adenocarcinoma (LUAD), colon adenocarcinoma (COAD), breast invasive carcinoma (BRCA), esophageal carcinoma (ESCA), stomach and esophageal carcinoma (STES), kidney renal papillary cell carcinoma (KIRP), stomach adenocarcinoma (STAD), prostate adenocarcinoma (PRAD), uterine corpus endometrial carcinoma (UCEC), head and neck squamous cell carcinoma (HNSC), kidney renal clear cell carcinoma (KIRC), lung squamous cell carcinoma (LUSC), liver hepatocellular carcinoma (LIHC), thyroid carcinoma (THCA), rectum adenocarcinoma (READ), pancreatic adenocarcinoma (PAAD), pheochromocytoma and paraganglioma (PCPG), bladder urothelial carcinoma (BLCA), kidney chromophobe (KICH), and cholangiocarcinoma (CHOL). Then, we extracted the expression data of the ENSG00000107819 (SFXN3) gene in each sample with log2(x+0.001) transformation for each expression value.The normalized pan-cancer dataset, TCGA Pan-Cancer , was downloaded from the UCSC (https://xenabrowser.net/) database. Normalization was conducted by the “limma” package. The univariate and multivariate Cox regression analyses for survival in HNSC and CIBERSORTx and xCell analysis were conducted.In addition, transcriptional profiles of count values and clinicopathological characteristics for HNSC (n = 546) were also obtained from the UCSC  is a web resource providing a comprehensive analysis of cancer transcriptome data, such as that from TCGA (t test. GEPIA (http://gepia.cancer-pku.cn/) is a web tool for analyzing RNA sequencing expression and correlation data of cancer and normal samples from TCGA and the Genotype-Tissue Expression (GTEx) data  data . SFXN3 ahttps://cistrome.shinyapps.io/timer/) (SFXN3 and the correlation of SFXN3 expression with tumor immune infiltration using TIMER in the HNSC dataset.Tumor Immune Estimation Resource (TIMER) is a comprehensive resource for the analysis of tumor-infiltrating immune cells across more than 30 types of cancer (/timer/) . In the https://xcell.ucsf.edu/) is another signature-based method for quantifying the infiltration of immune cells in tissues. We used the “xCell” R package to generate immune estimates to validate the CIBERSORT results by R software (version 3.6.4)  .SFXN3 expression, the levels of immune cell infiltration by CIBERSORT, clinical data , and tumor purity. The high and low groups of immune cell infiltration levels were determined based on the median values. Tumor purity estimates on HNSC were obtained from a previous study .All covariates with a SFXN3 expression and drug sensitivity and tolerance, we downloaded transcriptome data and drug sensitivity half-maximal inhibitory concentration (IC50) values of the NCI-60 panel of human cancer cell lines from the CellMiner database (https://discover.nci.nih.gov/cellminer/)  . The the“impute”  and “lim“impute” . MissingSFXN3 expression and the sensitivity of commonly used chemotherapy drugs for HNSC, we downloaded the HNSC cell line half-maximal inhibitory concentration (IC50) values of commonly used chemotherapy drugs from the Genomics of Drug Sensitivity in Cancer (GDSC) database (SFXN3 expressions of the corresponding cell lines reported in the Cancer Cell Line Encyclopedia (https://sites.broadinstitute.org/ccle/). In the analysis of each drug, the expression of SFNX3 was grouped high and low according to the median value. The Wilcoxon rank-sum test was used to compare IC50 values between the high and low SFXN3 expression groups using the Sangerbox online tool.To assess the relationship between database . These vSFXN3 were predicted using eight target gene prediction programs, including DIANA TOOLS  is a comprehensive database for the interactive analysis of miRNA expression profiles from TCGA projects  (SFXN3 and the expression level of lncRNAs in HNSC were performed at ENCORI using Pearson’s correlation coefficient.The upstream candidate lncRNAs of hsa-miR-29c-3p were predicted using the ENCORI database (dex.php) . CorrelaSFXN3 in pan-cancer, we first analyzed its expression in 22 common cancer types. Compared with that in the normal samples, the expression of SFXN3 was significantly upregulated in 12 cancer types, namely, COAD, ESCA, STES, KIRP, STAD, HNSC, KIRC, LIHC, THCA, READ, PCPG, and CHOL . SFXN3 expression levels in CHOL, HNSC, KIRC, acute myeloid leukemia (LAML), PAAD, PCPG, and sarcoma (SARC) were upregulated compared with those in the corresponding normal controls in the GEPIA database  and disease-specific survival (DSS) analyses were conducted. For OS, a higher expression of SFXN3 in patients was associated with significantly worse prognosis in COAD, HNSC, LIHC, PAAD, and KICH . COAD, HNSC, and KICH were consistent with a high expression in the tumor .Furthermore, Cox survival analysis was performed on SFXN3 demonstrated poorer prognosis in COAD and HNSC  , macrophages , neutrophils , and dendritic cells , but not B cells  and CD8+ T cells . The CIBERSORT algorithm was used to further confirm these results. The levels of tumor‐infiltrating B cells, CD8+ T cells, dendritic cells, gamma delta T cells, macrophages, NK cells, and plasma cells correlated significantly with SFXN3 expression : r = 0.318, p < 0.001; and membrane-spanning 4-domains subfamily A 4A (MS4A4A): r = 0.35, p < 0.001) and correlated negatively with one of the M1 macrophages’ biomarkers (NO synthase 2 (NOS2): r = −0.192, p < 0.001) : r = 0.181, p < 0.001, fucosyltransferase 4 (FUT4): r = 0.332, p < 0.001), TAMs (C–C motif chemokine ligand 2 (CCL2): r = 0.226, p < 0.001, CD68: r = 0.339, p < 0.001, interleukin (IL)-10: r = 0.354, p < 0.001), and Tregs (forkhead box P3 (FOXP3): r = 0. 258, p < 0.001, C–C motif chemokine receptor 8 (CCR8): r = 0.304, p < 0.001, signal transducer and activator of transcription 5 (STAT5B): r = 0.243, p < 0.001) were significantly and positively associated with the SFXN3 expression level  , CTLA4  , PDCD1LG2 (encoding programmed cell death 1 ligand 2 (PD-L2)) , VSIR ; r = 0.128, p = 0.004), and TIGIT (encoding T-cell immunoglobulin and ITIM domain)  (In addition to tumor-associated macrophages (TAMs), especially M2 macrophages, myeloid-derived suppressor cells (MDSCs) and Tregs also contribute to forming an immunosuppressive microenvironment in tumor tissues . Next, wn level , 45. Inhn level . We furttivation . The anaSFXN3 expression was associated with an immunosuppressive microenvironment, possibly via inhibition of T-cell activity.These data indicated that a high p = 0.002], tumor-infiltrating macrophages , gender , and N stage  were significant predictors of OS in patients with HNSC, which are shown in Univariate Cox regression analysis revealed that SFNX3 expression , gender , and N stage , which are demonstrated in All covariates with a SFXN3 expression to predict drug resistance in cancer, we acquired NCI-60 compound activity and corresponding NCI-60 cell line RNA-seq/composite expression from the CellMiner database. Compound activity scores and sensitivity to the corresponding compound correlated positively. We further selected 792 drugs or compounds in the database that are closely related to clinical treatment, including 574 drugs in clinical trials and 218 US FDA-approved drugs, for further analysis. Overall, SFXN3 expression was found to be associated with the increased activity of 42 drugs or compounds and the decreased activity of 20 drugs or compounds . We also divided patients into high or low SFXN3 expression groups according to the median value of SFXN3 expression and then investigated whether SFXN3 expression has an impact on the activity of the drugs. Patients with a high expression of SFXN3 were found to possess a lower drug activity for paclitaxel and docetaxel  guidelines, cisplatin, gemcitabine, paclitaxel, docetaxel, carboplatin, 5-FU, and methotrexate are commonly used chemotherapy drugs for head and neck cancer. Correlation analysis for these drugs showed that the activity of paclitaxel and docetaxel was negatively and significantly related to the expression of SFXN3 expression has an impact on the activity of the drugs in HNSC, we divided the expression values of SFNX3 in different HNSC cell lines into two high and low groups, which are shown in supplementary material SFXN3 were confirmed to have higher IC50 values for paclitaxel . Moreover, there was no significant difference between SFXN3 expression and the IC50 values of methotrexate, 5-FU, cisplatin, and gemcitabine .In order to evaluate whether SFXN3 expression might function as a paclitaxel resistance predictor, which might be closely related to poor prognosis in head and neck cancer.These findings suggested that Non-coding RNAs can act as regulators of gene expression, which has been widely investigated. MicroRNAs (miRNAs) are short RNAs that perform their function by binding to the target mRNAs .SFXN3, we first predicted miRNAs that could bind to SFXN3. Using eight prediction programs, 568 predicted miRNAs were identified, which are shown in supplementary material SFXN3 expression. In the CancerMIRNome analysis of TCGA database, 29 positive prognostic miRNAs and 131 significantly downregulated miRNAs were found in HNSC (p < 0.05). Pearson’s correlation analysis showed that SFXN3 expression was also significantly and negatively correlated with hsa-miR-29c-3p expression  (SFXN3 in HNSC.To clarify the possible mechanism by which ncRNAs might mediate the regulation of AC098828.2 (ENSG00000223734), LINC01270 (ENSG00000203999), MIR193BHG (ENSG00000262454), PVT1 (ENSG00000249859), NOP14-AS1 (ENSG00000249673), and LINC01907 (ENSG00000226125). However, only four lncRNAs were positively associated with the expression of SFXN3 .The upstream lncRNAs of hsa-miR-29c-3p were further predicted using the ENCORI database. A total of 114 possible lncRNAs were predicted. Among them, six predicted lncRNAs were negatively associated with the expression of hsa-miR-29c-3p in HNSC, including LINC01270 was considered to be the most likely upstream lncRNA of the hsa-miR-29c-3p/SFXN3 axis in HNSC.Based on the results of the correlation, expression, and survival analyses, SFXN3 indicated that HNSC patients with a high expression of SFXN3 had poor prognosis. Correlation analysis and comparative analysis between groups based on SFXN3 expression indicated that SFXN3 might function as a paclitaxel and docetaxel resistance predictor and is related to enriched tumor‐infiltrating macrophages, immune-suppressive cells, and immune checkpoint expression.In this study, the expression analysis and survival analysis for SFXN1 and SFXN3 are the main mitochondrial serine transporters in human cells. Both of them are likely to be regulated by the Myc transcription factor, which is a well-known oncogene. Serine transported to mitochondria is converted into glycine and formate, while generating reactive one-carbon units. Glycine can also provide one-carbon units to the folate cycle , can act as regulators of gene expression. Many ncRNAs function as competitive endogenous RNAs (ceRNAs) to regulate the biological behaviors of cancer , 55. To t cancer –59. Corrt cancer –63.SFXN3 and the estimation of infiltrated immune cell types were computationally predicted. Experimental exploration and multicenter and prospective studies are needed to further verify the clinical value of SFXN3 and its underlying mechanisms.Our study had several limitations. First, the heterogeneity of head and neck cancer varies. The subsites of head and neck tumors and treatment modalities might have affected the identification of significant prognostic variables. Second, the potential upstream axis of SFXN3 was highly expressed and correlated with unfavorable prognosis in HNSC. We identified the LINC01270/hsa-miR-29c-3p/SFXN3 axis as a potential regulatory pathway in HNSC .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.


Despite recent therapeutic advances in the treatment of prostate cancer, metastatic castration-resistant prostate cancer continues to cause significant morbidity and mortality. New research into highly expressed proteins in metastatic castration-resistant prostate cancer shows that Six-Transmembrane Epithelial Antigen of the Prostate 1–4 (STEAP1–4) are significant drivers of prostate cancer aggressiveness and metastasis. STEAP1, in particular, is highly expressed on the plasma membrane of prostate cancer cells and has received significant attention as a potential therapeutic target. This review highlights what is known about STEAP1–4 and identifies knowledge gaps that require further research.Six-Transmembrane Epithelial Antigen of the Prostate 1–4 (STEAP1–4) compose a family of metalloproteinases involved in iron and copper homeostasis and other cellular processes. Thus far, five homologs are known: STEAP1, STEAP1B, STEAP2, STEAP3, and STEAP4. In prostate cancer, STEAP1, STEAP2, and STEAP4 are overexpressed, while STEAP3 expression is downregulated. Although the metalloreductase activities of STEAP1–4 are well documented, their other biological functions are not. Furthermore, the properties and expression levels of STEAP heterotrimers, homotrimers, heterodimers, and homodimers are not well understood. Nevertheless, studies over the last few decades have provided sufficient impetus to investigate STEAP1–4 as potential biomarkers and therapeutic targets for prostate cancer. In particular, STEAP1 is the target of many emerging immunotherapies. Herein, we give an overview of the structure, physiology, and pathophysiology of STEAP1–4 to provide context for past and current efforts to translate STEAP1–4 into the clinic. Among males worldwide, prostate cancer (PCa) is the most commonly diagnosed malignancy and second leading cause of cancer-related death . While tGiven the lethality of mCRPC, much effort has been dedicated to understanding its biology. The medical oncology community has made great strides in developing new treatments for mCRPC, which include novel androgen-directed therapies, chemotherapies, and radiolabeled therapies targeted to cell-surface antigens . However, males with mCRPC continue to progress, and there is a critical need to find new biomarkers and targets for PCa.A unique and promising therapeutic target is Six-Transmembrane Epithelial Antigen of the Prostate (STEAP), a family of metalloproteinases that are variably expressed in normal prostate tissue and, except STEAP3, overexpressed in PCa . Since SIn mammals, iron and copper exhibit several biochemical similarities: Both alternate between two oxidation states, are absorbed in the small intestine via divalent metal transporter 1 (DMT1), and are cofactors for several enzymes  ,11,12. ISaccharomyces cerevisiae ferric reductase (FRE), while the N-terminal and C-terminal domains of STEAP2-4 are homologous with prokaryotic F420:NADP+ oxidoreductase (FNO) and Saccharomyces cerevisiae FRE, respectively [STEAP1–4 are metalloproteinases that play important roles in iron and copper homeostasis [ectively . In mammectively ,15.The literature is inconsistent concerning the interactions that STEAP1–4 have with each other. STEAP1 can form heterotrimers with STEAP2 and STEAP4; STEAP1, STEAP2, and STEAP4 can form homotrimers; STEAP3 and STEAP4 can form homodimers; STEAP proteins may form heterodimers ,17,18. HIn this section, we briefly summarize the structural and physiologic properties of STEAP1–4 . For mor3+ or Cu2+ reductase activity [C-terminal domain contains a b-type heme cofactor [STEAP1, which is also called STEAP, is a 339-amino-acid (39.9 kDa) protein with six transmembrane α-helices and intracellular, hydrophilic N- and C-terminal domains [activity ,17,18. Icofactor . DespiteSTEAP1 is expressed at surface cell–cell junctions ,9,15. It3+ or Cu2+ reductase activity due to its lack of an NADPH-binding FNO domain [STEAP1B is a truncated homolog of STEAP1. Like STEAP1, STEAP1B does not exhibit FeO domain . It has 3+ and Cu2+ reductase activity, allowing them to reduce extracellular iron and copper [C-terminal contains a b-type heme-containing FRE domain. The Fe3+ or Cu2+ reductase activity of STEAP2-4 is mediated by electron transfer from NADPH to membrane-embedded b-type heme and FAD+, as well as to extracellular metal–ion complexes.STEAP2-4 exhibit Fed copper . Like STd copper . The N-tSTEAP2, which is also called Six-Transmembrane Protein of Prostate 1 (STAMP1), is a 490-amino-acid 56.1 kDa) protein that is highly expressed in the Golgi complex, trans-Golgi network, and plasma membrane 6.1 kDa p. This suSTEAP3, which is also called STAMP3, pHyde, and Tumor-Suppressor-Activated Pathway 6 (TSAP6), is a 488-amino-acid (54.6 kDa) protein that is an essential component of the transferrin–transferrin receptor cycle ,22. MoreSTEAP4, which is also called STAMP2 and TNF-α-Induced Adipose-Related Protein (TIARP), is a 459-amino-acid (52.0 kDa) protein that regulates inflammatory responses, fatty-acid metabolism, and glucose metabolism ,23,24. IAlthough STEAP1–4 are homologs, they exhibit different expression and localization patterns in different tissues. Thus, a complex set of phenotypes is associated with these metalloreductases and, subsequently, a complex set of associated oncogenic properties . The mosb-type heme cofactor is unknown, but one can speculate that it reduces molecules that travel through STEAP1.Relative to normal prostate tissue, STEAP1 is overexpressed in malignant prostate tissue . STEAP1 Since mesenchymal stem cells (MSCs) often express STEAP1, STEAP1 overexpression in PCa may be the sum result of STEAP1 upregulation in malignant prostate cells and MSC-derived PCa stromal cells ,27,28. FThe implications of these considerations are two-fold. First, STEAP1 overexpression in PCa may be the result of its local tumor microenvironment (rather than solely due to STEAP1 overexpression in primary tumor cells). This may increase the attractiveness of STEAP1 as a biomarker and therapeutic target. Numerous studies, as described later, show that STEAP1 overexpression is immunogenic; enhancing the immune response against STEAP1-overexpressing PCa cells may further induce anti-cancer activity. Second, STEAP1 therapeutics may not be as specific to malignant prostate tissue as previously assumed. There may be off-tumor effects on other tissues that express STEAP1, namely, MSC-derived stromal tissues.Classically, the Gleason grading system is used to evaluate prognoses in patients with PCa . The GleThe literature on the association between PCa and STEAP2-4 is scarcer than that for STEAP1. Nonetheless, STEAP2 and STEAP4 are overexpressed in PCa and, thus, deserve attention ,35,36,37Overexpression of STEAP2 increases the proliferation of PCa cells, while low expression levels of STEAP2 are associated with decreased PCa cell proliferation ,34. STEAThe literature on the association between STEAP3 and PCa is sparse. As of now, the expression and function of STEAP3 are best understood in the context of erythrocytes and erythropoietic tissues ,38. Howe3+ reduction and consumes NADPH. The subsequent increase in ROS induces ATF4 expression, which may promote PCa growth and progression, as well as eventual development of castration resistance [Overexpression of STEAP4 seems to play a role in PCa progression, as malignant prostate cells abundantly express STEAP4 in the Golgi complex and plasma membrane ,37. The sistance . Third, sistance . Althougsistance .STEAP1–4 have many functions outside of or secondary to their intrinsic metalloreductase activity . HoweverMuch remains to investigate regarding the tumorigenic mechanisms of STEAP1–4. Nevertheless, that STEAP1, STEAP2, and STEAP4 are upregulated in PCa provides enough impetus to investigate them as possible biomarkers and therapeutic targets for PCa. In this section, we describe efforts to translate STEAP1–4 into the clinic.Serum PSA is currently the gold-standard biomarker for PCa screening, detection, and prognostication. However, recent PCa screening trials highlighted the limitations of using PSA—namely, that PSA screening does not significantly reduce mortality in PCa patients and is associated with a high risk of overdiagnosis ,47. ThisSTEAP1, STEAP2, and STEAP4 have been evaluated as possible diagnostic and prognostic biomarkers in glioblastoma, breast cancer, Ewing sarcoma, lung cancer, and PCa ,52,53,54STEAP1 is a promising diagnostic and prognostic biomarker. One method of using STEAP1 as a biomarker is detecting the number of circulating STEAP1-positive extracellular vesicles (EVs). In two studies, PCa patients were found to have significantly elevated STEAP1 EV levels when compared to healthy males ,56. Khan89Zr-DFO-MSTP2109A, which uses an STEAP1-specific humanized immunoglobulin G1 (MSTP2109A) to target 89Zr-desferrioxamine (DFO), a positron emission tomography radionuclide, to mCRPC [89Zr-DFO-MSTP2109A is well tolerated and demonstrates excellent uptake in bone and soft-tissue mCRPC sites .STEAP1-specific antibodies are being tested as diagnostic imaging agents. A notable example is to mCRPC ,60. OngoSTEAP2 and STEAP4 are interesting biomarker candidates because, in the prostate, they are overexpressed in malignant tissue. Burnell et al. showed that STEAP2 overexpression was significantly correlated with the Gleason score, a measure of prognosis . STEAP2 Ultimately, further investigation is needed to determine whether STEAP1, STEAP2, and STEAP4 are useful diagnostic and prognostic biomarkers for PCa.PCa-specific antigens that are therapeutic targets include prostate stem cell antigen (PSCA), prostate-specific membrane antigen (PSMA), and STEAP1. This section will only discuss STEAP1. Given its localization to surface cell–cell junctions, particularly that of the prostatic secretory epithelium, STEAP1 is a promising target for T-cell and antibody-based immunotherapy ,62. Beca86–94, STEAP262–270, and STEAP292–300, making them attractive targets for cancer vaccines. In cell-line and mouse models, vaccination with these epitopes conferred protection against new tumor growth; vaccination against some of these epitopes also attenuated the growth of well-established tumors. Since STEAP1 is a self-antigen, one concern about these vaccines is that they may trigger autoimmunity. Recognizing this possibility, Luz Garcia-Hernandez et al. tested whether STEAP1 vaccines induce autoimmunity in mice [STEAP1 is immunogenic; STEAP1-derived peptides expressed on MHC class I molecules induce cytotoxic CD8+ T lymphocyte (CTL) activity in PCa ex vivo ,75,76. TCommercially developed PCa vaccines include CureVac’s CV9104, a self-adjuvanted full-length mRNA vaccine that targets the PCa antigens PSA, PSCA, PMSA, STEAP1, prostatic acid phosphatase (PAP), and mucin 1 . Althoug89Zr-DFO-MSTP2109A, contains MSTP2109A [DSTP3086S (vandortuzumab vedotin) is an antibody–drug conjugate (ADC) that, like STP2109A . In DSTP®2+1 T-cell engager that contains two identical anti-STEAP1 Fab domains, an anti-CD3 scFv domain, and an Fc domain that prolongs serum half-life [50 of 37 pM across 19 STEAP1-expressing cancer cell lines. Notably, the presence of two identical anti-STEAP1 Fab domains (versus one) increased CTL activity against cancer cells and decreased off-target activity against normal cells. The bispecificity of AMG 509 ensures that AMG 509 largely binds cells that overexpress STEAP1, resulting in more robust anti-cancer activity and fewer AEs. A phase I, multicenter, open-label study for assessing the safety, tolerability, pharmacokinetics, and efficacy of AMG 509 is currently recruiting mCRPC patients  [AMG 509 is an Xmabalf-life . Announc4221542) . As of tOther anti-STEAP1 therapeutics are under investigation for renal cell carcinoma, urothelial carcinoma, and Ewing sarcoma ,79. Lin Although STEAP1 is the primary target of current clinical investigation, other STEAP proteins are also the subjects of translational studies. For example, Machlenkin et al. identify STEAP3-derived epitopes as good vaccine candidates for immunotherapy of PCa. In vitro cytotoxicity assays demonstrated that these epitopes induced strong CTL-mediated antitumor activity . Other aGiven the dynamic physiologic and pathologic mechanisms associated with STEAP1–4, they may have potential as therapeutic targets. However, further investigation is needed on many fronts. The remaining questions to answer include: STEAP1–4 expression patterns in different grades of PCa, the role of AR in regulating STEAP1–4 expression, other mechanisms by which STEAP1–4 promote PCa pathogenesis, and the roles of STEAP1–4 in the PCa tumor microenvironment. Answering these questions will allow us to better understand the implications and utility of STEAP1–4 in the clinic.


MYC, NR5A2, CXCR2, HMGA2, LIN28A, OCT4A, OCT4B, OCT4B1, TWIST1, STK11, SNAI1, and miR-205-5p expression. The expression levels of MYC, NR5A2, SNAI1, TWIST1, and STK11 were significantly higher in tumor-adjacent tissues than in the matched EC samples, and this difference was not influenced by the content of cancer cells in cancer-adjacent tissues. The expression of MYC, NR5A2, and SNAI1 was also higher in EC-adjacent tissues than in samples from cancer-free patients. In addition, the expression of MYC and CXCR2 in the tumor related to non-endometrioid adenocarcinoma and reduced the risk of recurrence, respectively, and higher NR5A2 expression in tumor-adjacent tissue increased the risk of death. In conclusion, tissues proximal to EC present higher levels of some cancer-promoting genes than the matched tumors. Malignant tumor-adjacent tissues carry a diagnostic potential and emerge as new promising target of anticancer therapy.Molecular alterations in tumor-adjacent tissues have recently been recognized in some types of cancer. This phenomenon has not been studied in endometrial cancer. We aimed to analyze the expression of genes associated with cancer progression and metabolism in primary endometrial cancer samples and the matched tumor-adjacent tissues and in the samples of endometria from cancer-free patients with uterine leiomyomas. Paired samples of tumor-adjacent tissues and primary tumors from 49 patients with endometrial cancer (EC), samples of endometrium from 25 patients with leiomyomas of the uterus, and 4 endometrial cancer cell lines were examined by the RT-qPCR, for  Tissues adjacent to a primary malignant tumor (TA) have been shown to present substantial molecular alterations, such as loss of heterozygosity, aneuploidy, mutations, transcriptomic and epigenetic alterations, protein expression changes, and metabolic disturbances ,2,3. MorAs shown in breast and lung cancers, molecular changes in TA may relate to cancer subtype ,8. MolecTWIST1, SNAI1, NR5A2, MYC, CXCR2, STK11, POU5F1 , HMGA2, as well as miR-205-5p, in the matched samples of tumor-adjacent tissues and tumors from patients with endometrial cancer, and in the samples of endometrium from patients with uterine leiomyoma.We aimed to molecularly characterize tumor-adjacent tissues in patients with EC. Therefore, we analyzed the expression of genes associated with cancer progression and metabolism, MYC in carcinogenesis, including the pathogenesis of endometrial cancer , p = 0.020).Higher miR-205-5p expression in tumor-adjacent tissue related to tumor cell presence in the tumor-adjacent tissue .Higher TWIST1, SNAI1, NR5A2, MYC, CXCR2, STK11, POU5F1 , and HMGA2 was studied in endometrial cancer cell lines, AN3 CA, HEC-1-A, MFE 280, and MFE 296. HMGA2, MYC, STK11, and TWIST expression was comparable to that in tumors from EC patients, while CXCR2, NR5A2, and SNAI expression was different from that in EC clinical samples. Inconsistent results on the expression of the other genes were observed  in EC-adjacent tissues than in paired tumors and in endometrial samples from cancer-free leiomyoma patients. We are the first to show NR5A2 expression in clinical samples of EC. NR5A2 expression in TA and TAc exceeded that in tumors, and in TAc, higher NR5A2 expression increased the risk of death. In breast cancer, an increased NR5A2 expression has been reported in tumor-adjacent adipose tissue as compared to normal breast tissue both from cancer-free patients and from breast cancer patients [NR5A2 is an estrogen receptor target gene [CYP19A1 gene, is a key enzyme responsible for estrogen biosynthesis [NR5A2 expression in EC-adjacent samples contributed to the aberrant aromatase expression/activity in peritumoral tissues, resulting in local estrogen production and EC progression. It has also been demonstrated that NR5A2 may positively regulate MYC expression [NR5A2 expression may also contribute to the above-described MYC upregulation in EC-adjacent tissues. Noteworthy, in leiomyomas, a decreased expression of MYC and NR5A2 in tumors compared to the corresponding myometrium has also been observed [We showed significantly higher levels of patients . NR5A2 iget gene , and NR5get gene . Aromataynthesis . Noteworynthesis . Thus, ipression , therefoobserved .SNAI1 and TWIST1 in EC-adjacent tissues than in the matched tumor samples. Similarly, in breast cancer, high expression of SNAI1 and/or TWIST1 in tumor-adjacent tissues has been demonstrated [Noteworthy, Aran et al. have recently characterized a set of genes overexpressed in tumor-adjacent tissues as compared to tumors in several cancer types, and those genes strongly associated with various signaling pathways, including EMT . Our datnstrated ,69. Montnstrated .STK11 expression level was lower than in the matched TA and in Ctrl samples. Our data implicating a tumor suppressor role of STK11 in EC are in agreement with previous studies involving cell lines and animal models, where STK11 deficiency was strongly associated with highly invasive phenotype of endometrial carcinoma cells [We demonstrated that in EC, tumor ma cells ,71,72.HMGA2 in EC tumors are in line with previous results [Our data demonstrating elevated expression of miR-205-5p and  results ,51,73,74POU5F1 isoform A (OCT4A) expression in EC in tumors than in the matched tumor-adjacent samples is consistent with previous literature data demonstrating OCT4A enrichment in EC tumor-initiating/cancer stem cells [OCT4A expression in TA samples were significantly lower compared to Ctrl samples derived from leiomyoma patients. The underlying mechanism of the difference is not clear. It is worth noting that recent data on patients with the most common MED12mt fibroid subtype showed a set of tumor-promoting genes to be upregulated in myometrium adjacent to tumors compared to normal myometrium [The higher em cells . Surprisometrium .HMGA2 and SNAI1 and higher levels of STK11 and TWIST1, while all the other transcripts were similarly expressed. Hence, the possible contribution of cancer or myometrial cells in TA in the expression of all or most of the analyzed transcripts, respectively, seems limited. Interestingly, regarding CXCR2 that was expressed at similar levels in T, TA, and TAc, patients with higher CXCR2 expression in tumor samples presented reduced risk of recurrence independent of cancer cell presence in tumor surrounding. Explaining this issue requires further research.Similar expression levels of all of the assessed transcripts, except miR-205-5p, were shown in cancer cell-free and cancer cell-containing tumor-adjacent tissues from EC patients. In full-thickness biopsy samples of relatively thin endometrium of postmenopausal women, the underlying myometrial cells are often present . ConsideMYC, NR5A2, SNAI1, and TWIST1 in tumor-adjacent tissues is not clear. The expression of MYC, NR5A2, and SNAI1 was found to be higher in EC-adjacent tissues than in samples from cancer-free patients, which shows that tumor-surrounding tissues presented truly elevated expression, not just higher expression than in a tumor because of a decreased tumor expression. The increased expression of cancer-promoting genes found in tumor-surrounding tissues may represent pre/pro-cancerous alterations associated with field cancerization [The molecular etiology of EC and the pathogenic role of the demonstrated here overexpression of rization . The tumrization . Trujillrization . Troesterization . A possirization . An accurization . Recentlrization . The imprization .MYC, NR5A2, SNAI1, and TWIST1, in tumor-adjacent tissues than in tumors, which suggests field cancerization effect. Whether a field cancerization initially defined as cancer-preceding may also be tumor-induced and how far the tumor microenvironment reaches out remain open questions. Cancer-adjacent tissue, instead of being regarded as representative of the molecularly normal tissue  should rather be considered a potential target of anticancer therapy.In summary, our data provide important insights into the biology of tumors and the surrounding tissues in EC and highlight the need to characterize tumor-adjacent tissues. We showed significant abnormalities in the expression of cancer-promoting genes in tissues proximal to endometrial cancer, with higher expression of We are currently further exploring the molecular changes in EC tumor-adjacent tissues.


During carcinogenesis, Ca2+ signaling is significantly remodeled due to mutations and/or ectopic expression. Here, we summarize current knowledge on how alterations in Ca2+ signaling contribute to the development of different cancer hallmarks. Emphasis is placed on the structure/function relationship of the well-studied store-operated Ca2+ channel, i.e., Orai1, and the Ca2+-activated K+ channel, i.e., SK3, alongside their individual and joint roles in cancer. This review lays out the current state of knowledge of Ca2+-signaling effectors and proteins as potential targets for the treatment of certain cancer types, with Orai1 and SK3 presented as emerging therapeutic targets.Cell fate is ultimately determined by the precisely coordinated action of the Ca2+-permeating and Ca2+-regulated ion channels in cancer cell development, proliferation, and migration make them promising molecular targets in cancer therapy. In particular, the co-regulation of the Orai1 and SK3 channels has been well-studied in breast and colon cancer cells, where it finally leads to an invasion-metastasis cascade. Nevertheless, many questions remain unanswered, such as which key molecular components determine and regulate their interplay. To provide a solid foundation for a better understanding of this ion channel co-regulation in cancer, we first shed light on the physiological role of Ca2+ and how this ion is linked to carcinogenesis. Then, we highlight the structure/function relationship of Orai1 and SK3, both individually and in concert, their role in the development of different types of cancer, and aspects that are not yet known in this context.Cancer represents a major health burden worldwide. Several molecular targets have been discovered alongside treatments with positive clinical outcomes. However, the reoccurrence of cancer due to therapy resistance remains the primary cause of mortality. Endeavors in pinpointing new markers as molecular targets in cancer therapy are highly desired. The significance of the co-regulation of Ca In this review, we first describe the general role of Ca2+ in tumor development. Since the co-regulation of the Ca2+ channel: Ca2+ release-activated Ca2+ (CRAC) channel, and the Ca2+-regulated channel: Ca2+-activated K+ channel, or SK3, have been extensively reported to play a role in certain cancer types in the last century, we delineate here the current knowledge of the molecular mechanisms of both channels individually and in co-regulation. We highlight critical factors that determine their structure/function relationship, their roles in carcinogenesis identified to date, and outstanding questions in this context.Every year, 18.1 million cases of cancer are diagnosed worldwide, of which 9.5 million lead to death. These numbers are expected to rise 1.6-fold by 2040 ,4,5,6,7.2+ ions are versatile intracellular signals that regulate a plethora of cellular processes including gene transcription, proliferation, and cell migration [2+ concentration on the extracellular side and in intracellular organelles is in the range of mM, and it is 10,000-fold lower in the cytosol [2+ gradient defines the versatility of this signal ion in the life cycle of a cell, to initiate and drive processes such as immune cell activity, neurotransmitter release, or muscle contraction [2+ levels that occur either through Ca2+ release from intracellular stores  or Ca2+ influx across the plasma membrane (PM) from the extracellular space [Caigration ,9. They  cytosol ,12,13. Ttraction ,9,14. Acar space . 2+ signaling is orchestrated by Ca2+-transporting and Ca2+-sensing proteins. Ca2+ level enhancements can be initiated by the stimulation of a membrane receptor ), membrane depolarization , diacylglycerol (DAG)) that activate Ca2+ ion channels in intracellular compartments  and/or the plasma membrane  to allow Ca2+ flux into the cytosol. Cytosolic Ca2+ elevations are sensed by a number of proteins such as Calmodulin (CaM) and downstream targets including CaM kinase (CaMK), calcineurin (CN), or protein kinase C (PKC)  or to the extracellular side (PMCA) [Cellular Cachannels ), or mecchannels ). Ca2+ s C (PKC) A, which e (PMCA) . 2+-signaling components, disrupting the healthy Ca2+ balance [2+ acts at different stages of cancer signaling cascades either directly via Ca2+ signaling proteins  or indirectly via transcription factors  or oncogenic routes. The two major oncogenic pathways [2+ and these oncogenic pathways can affect each other in a bidirectional manner to promote cancer progression. On the one hand, distinct Ca2+ signals can tune oncogene-dependent signaling [2+ ions with Ras regulatory factors, such as CaM [2+ signals, as evidenced by the fact that the oncogene Ras interacts with and activates PLCε to produce IP3, which triggers ER-Ca2+ store-depletion [In cancer cells, genetic and epigenetic alterations can lead to the remodeling of Ca balance ,6,19,20. balance . Ca2+ acpathways  that havpathways . Within pathways . In the pathways . , cAMP-responsive element binding protein (CREB), and AP1  families [2+ also drives their complex formation  at the end of G1 to finally ensure the transition to the S phase. The progression of the G1 phase is further fine-tuned by CDK inhibitor proteins , whose action is controlled directly by Ca2+ via Ca2+-sensing proteins, CaM, CaMKII, and calcineurin (CN) and the tumor suppressor p53 [2+ is also essential for subsequent cell cycle phase transitions  and associated rearrangements of centrosomes are triggered by Ca2+ oscillations acting in concert with CaM and CaMKII [The multitude of Cafamilies . These cssor p53 . Ca2+ isd CaMKII ,27  target Myc to modulate cell cycle progression [2+ route can control Ca2+ signaling. The Wnt-Ca2+ pathway is initialized by Frizzled receptors, which initiate a classical G-protein-coupled signaling cascade that results in the production of IP3 and DAG and is thus directly linked to Ca2+ signaling pathways [A variety of other cancer signaling pathways  and anti-apoptotic  factors at the mitochondria ,32. Dysrproteins ,41,42,43m the ER ,25 , cell migration, invasion, angiogenesis, and intravasation, all of which are controlled by Ca2+ ,25. EMT 2+ . In seve2+ ,51,52,53er types ,32. For er types . Furtherinvasion ,51,54,55-catenin  , followed by actomyosin contraction and disassembly of focal adhesions. The latter is governed by the Ca2+-sensitive protease calpain, which cleaves focal adhesion kinase (FAK), vinculin, talin, and integrins to disconnect the membrane from the cytoskeleton. Conversely, directed actin polymerization and growing focal adhesions located at the leading edge of migrating cells to form membrane extension are stimulated by spatially confined Ca2+ signals. This is modulated by small GTPase, such as Ras and Rac1, Ca2+-dependent factors, including CaMK and proline-rich tyrosine kinase 2 (PYK2), and FAK [2+ levels in tumor cells can further promote FAK disassembly and contribute to the reduction of cell adhesions that promote cell migration. Moreover, the formation of membrane extensions (invadopodia) is driven by the expression of Ca2+-dependent pro-invasive enzymes ) that contribute to the degradation of the extracellular matrix (ECM) [Directional movement of migratory cells is usually driven by highly localized Ca and FAK   ,32,40  and non-voltage Cachannels ,40. Despchannels ,72. Non-channels , receptochannels ,75, SOC channels ,76, acidchannels , and mecchannels . A numbechannels ,87,88,89channels ,91,92. T2+ ion channel, the CRAC channel, in the co-regulation with Ca2+-dependent K+ ion channels in cancer, we focus initially on its currently known structure/function relationship as well as its individual role in cancer. It is composed of the stromal interaction molecule, STIM, containing its Ca2+ sensor embedded in the ER lumen [2+-selective ion channel Orai in the PM [2+ entry mechanisms in most cancer cells [Due to the essential role of the most studied store-operated CaER lumen ,94,95,96n the PM ,101,102.er cells ,109,110 er cells ,109,111.2+ from the ER. Precisely, ligand binding to PM receptors leads to the activation of G-proteins, which initiate the production of phospholipase C to generate IP3 from phosphatidylinositol-biphosphate (PIP2). Subsequently, IP3 couples to the IP3 receptor in the ER membrane, which triggers ER-Ca2+ store depletion [2+ ion channels [CRAC channels, composed of STIM and Orai proteins, are distinguished by their activation mechanism via the release of Caepletion ,116,117.epletion ,118 and channels  in the Pchannels ,121  ,124,128 2+ levels, and the C-terminus relays the activation signal to Orai1 in the PM [In general, the STIM structure consists of a single-pass TM domain with the N-terminus embedded in the ER lumen and its long C-terminal tail exposed to the cytosol. The N-terminus senses fluctuations in Can the PM . The STIn the PM ,137,138 2+-sensing EF-hand domain in a complex with the sterile alpha motif (SAM) region. In the resting state, the EF-SAM domain is folded into a compact structure that is stabilized by hydrophobic interactions [2+ store depletion, Ca2+ ions dissociate, leading to destabilization of the EF-SAM complex, which initiates signal transmission to the C-terminus [Specifically, the luminal side of STIM1 comprises the Caractions . Upon Caterminus ,143,144.2+ store depletion is conveyed from the N- to the C-terminus via the STIM1 TM domain. Two TM domains within a STIM1 dimer are considered to form a crossing angle that alters upon activation [Next, the activation signal of Cativation . In supptivation .2+ store depletion, the STIM1 C-terminal domain undergoes an extensive conformational rearrangement to change from a folded quiescent to an extended state, which leads to the exposure of STIM1 oligomerization and Orai1 coupling sites. The STIM1 C-terminus is composed of three typical protein–protein interaction domains known as coiled-coil regions , the inhibitory [Upon Cahibitory  or CRAC hibitory , the michibitory , and thehibitory ,148  and CC3 of monomers within a dimer is further modulated by intrahelical interactions within two other parts of CC1 (CC1α2 with CC1α3) ,150,151.2+ influx.A minimal portion of the STIM1 C-terminus called CAD (CRAC-activating domain) or SOAR (STIM1-Orai1-activating region) is sufficient for coupling to and activation of Orai channels. They include mainly CC2 and CC3 ,154,155.2+-selective ion pores in the PM. The Orai protein family comprises three human Orai paralogs, namely, Orai1–3  connected by two extracellular and one intracellular loop and flanked by a cytosolic N- and C-terminus ,166,167.Drosophila melanogaster Orai (dOrai) and corresponding gain-of-function (GoF) dOrai  mutants consistently exhibit a hexameric assembly of Orai subunits. Based on the high homology of dOrai to human Orai1 (hOrai1) within the TMs, it is assumed that hOrai1 also forms a hexamer. Of the four TM domains, the first TMs (TM1s) form an inner ring lining the pore in the center of the channel [2+ accumulation region at the extracellular side followed by the selectivity filter (E106), the hydrophobic cavity , and at the cytosolic side, the basic region. Interestingly, TM1 expands helically approximately 20 Å into the cytosol, forming an extension of the Ca2+ ion pore [2+ ion pore, another essential feature of the Orai1 complex represents its periphery, composed of TM4 and the C-terminus [Structural resolutions of the  channel ,178,179. filter E6, the hyion pore ,136,180.ion pore . In additerminus ,170. Theterminus ,170. Theterminus ,170,174,terminus ,182. Theterminus ,182.The general structure of the three Orai isoforms is comparable, yet they have an overall sequence identity of 50–60%, with TM1 being identical among the three Orai proteins, whereas the other TM domains are approximately 81–87% similar C. The cyIn summary, CRAC channel activation represents a multistep activation cascade involving STIM1 unfolding, STIM1 oligomerization, STIM1-Orai1 coupling, and Orai1 activation. Resolving these different intermediate activation states could help researchers to find new targets for selective therapeutic strategies also in cancer. In particular, the isoform-specific differences of Orai channels might be promising in cancer-type-specific drug discovery and therapy development . Neverth2+ ion channels may involve their altered arrangement and interplay in the membrane due to structural rearrangements of the channel, assembly of the channel complex, or channel interaction with regulatory proteins that affect their function [2 and PI4P, cholesterol, and sphingomyelin [Increasing evidence reveals that membrane proteins are localized in microdomains containing especially cholesterol, sphingolipids such as sphingomyelin, and glycosphingolipids . These cfunction . In the function ,189, altfunction . This defunction . The fungomyelin ,196,197.2 modulates STIM1 function via direct binding to its C-terminal end, a lysine-rich region [2 and PIP3 located in cholesterol-rich regions in the PM [2 and PIP3 in cholesterol-rich regions before interacting directly with Orai1 [2 and is therefore essential for modulating Orai1 in membrane domains with different PIP2 content [2 on Orai1 due to its dependence on STIM1. Moreover, the precursor of PIP2, PI4P, regulates CRAC channel function [Specifically, PIPh region ,200,201.n the PM ,204,205.th Orai1 . The N-t content . Howeverfunction ,208,209,Cholesterol affects CRAC channel function via direct interaction with STIM1 and Orai1. Both CRAC channel proteins contain a cholesterol-binding motif, namely, the cholesterol recognition amino acid consensus motif (-L/V-(X)(1-5)-Y-(X)(1-5)-R/K-; X represents from one to five any amino acids before the next conserved residue) ,212,213.2+ store depletion. However, whether this modulatory role occurs due to direct binding or allosterically is still unknown [Sphingomyelin, which is also abundant in cholesterol-rich regions, controls CRAC channel function. Indeed, the application of sphingomyelinase (SMase) D diminished CRAC channel currents without impacting Ca unknown ,216.Additionally, STIM1 and Orai1 undergo S-acylation, the posttranslational tethering of a medium-length fatty acid, to a cysteine—in these cases, C437 in STIM1 and C143 in Orai1. S-acylation of STIM1 controls its puncta formation and maximal activation of CRAC channels . In Orai2, of the membranes, thereby having various effects on the modulation of STIM1/Orai1 coupling and function. Additionally, ER- or PM-associated proteins located in the ER-PM junctions, in particular, septins [Additionally, perturbations to plasma membrane lipids affect other proteins that impact STIM1 and Orai1 expression and function. These include a variety of lipid- or ER-PM transition-dependent accessory proteins at the ER–PM contact sites , as we r septins ,226,227, septins ,229, RAS septins , SARAF [ septins ,231,232, septins ,235,236  septins ,239,240, septins ,242,243.The fact that the CRAC channel complex is not a closed entity but can be modulated by a variety of proteins and lipids in the vicinity of the ER–PM contact sites highlights the multiple regulatory possibilities that may also play a role in the pathogenesis of cancer and could be exploited for therapeutic applications.2+ influx to maintain healthy body functions [2+ influx into cancer cells, where they are linked to tumorigenesis. This is due to either altered expression of CRAC channel proteins [Although CRAC channels are one of the most important pathways for the cellular Caunctions , there iproteins ,245,246,proteins ,250,251 Distinct expression levels of STIM and Orai compared to corresponding healthy tissues have been detected in cells of the breast ,252,253,2+ ion channels, for instance, the canonical transient receptor potential channels, which have been found in breast cancer (TRPC1 and TRPC6) [2+ signaling in dependence with not only STIM1 and Orai1, but also TRPC1 [2+ entry occurs via a molecular complex of TRPC6, STIM1, and Orai1 controlling cell proliferation [2+ entry through Orai1 activation via the accessory protein Secretory Pathway Ca2+-ATPase 2 (SPCA2) has been identified [2+ pump, where it is involved in protein glycosylation, sorting, and processing. However, in this cancer cell line, there is a direct interaction of the N- and C-termini of SPCA2 with Orai1 at the cell surface, which controls EMT [Notably, other molecular components also contribute to STIM- or Orai-dependent cancer progression. Altered expression and function of the molecular components of SOCE include not only CRAC channel components, such as Orai1 and Orai3, but also other Cad TRPC6)  and ovard TRPC6) . Chronicso TRPC1 . Moreoveferation . In the entified . Physiolrols EMT ,278. The2+ entry via the STIM1/Orai1 machinery affects the various cell cycle effectors, either directly via Ca2+-binding proteins or indirectly via transcription factors, Ras/ERK, or PI3K/Akt pathways.In several tumor types, enhanced proliferation correlates with ectopic STIM1/Orai1 expression ,276,277.+ breast cancer cells, SOCE is mediated exclusively by Orai3 and STIM1/STIM2, whereas in ER- breast cancer cells, the canonical CRAC channel consists of STIM1/Orai1, which is sufficient to trigger SOCE [+) breast cancer cells (MCF-7), Ca2+ entry via Orai3 targets the proto-oncogenic transcription factor c-myc via the MAPK  pathway to trigger cell proliferation arrest [+ breast tumorigenesis [In some cancer types, Orai3 and/or STIM2 expression exerts pro-proliferative effects by influencing the cell cycle via various signaling cascades A. In ER+ger SOCE . Specifin arrest , contribigenesis . Indeed,igenesis . In pancigenesis ; however2+ concentration, which controls cell proliferation via Ca2+/CN-dependent activation of the transcription factor NFAT. Interestingly, in mouse models, Orai3 silencing controls the G1/S phase cell cycle by decreasing cyclin D1 expression. Conversely, Orai3 overexpression promoted proliferation [In other cancer types, enhanced Orai3 expression increased Orai1/Orai3 heteromeric formation and thus reduced the number of functional Orai1 channels  Figure A. In proferation . Anotherferation  suggesteferation ,259. In feration . This paferation  providesApoptosis resistance is another cancer hallmark connected to up- or downregulated expression and function of CRAC channel components.2+ crosstalk between ER and mitochondria and/or balance between pro- and anti-apoptotic factors is altered and thus determines apoptosis resistance. Nevertheless, prostate cancer cells benefit from the abrogated SOCE, whereas upregulated SOCE has a pro-survival and pro-migration effect in several other cancer cell types [The androgen-independent stage of prostate cancer, which represents an aggressive phenotype, is manifested by downregulated Orai1 expression, which leads to apoptosis resistance. In accordance, SOCE is abrogated in these androgen-independent prostate cancer cells . Supportll types ,275,276.ll types . Moreovell types . These fCRAC channel components are further of great importance in EMT, migration, and invasion of tumor cells ,278,280.The expression of important markers of EMT and requisite regulators of mesenchymal cell migration, such as vimentin or fibronectin, is downregulated in esophageal  and gastAmong factors that promote cell migration, the expression level of small GTPases Ras or Rac is critical in STIM1- and/or Orai1-dependent cancer types, as reported in breast  and esop2+ influx via Orai1 [2+-dependent Wnt signaling. Specifically, increased Ca2+ levels phosphorylate CaMKII and ß-catenin, thereby switching off Wnt and subsequently inhibiting EMT [The reversal of EMT in a highly aggressive type of breast cancer depends on the enhanced expression of SPCA2, which triggers constitutive Caia Orai1   playing a role in the prostaglandin  synthesis. It is activated by the Ras/ERK pathway ,284,285 and CREB   by which STIM1 and COX-2/PGE2 affect EMT  as well as migration have not been explored in detail.2+ levels can underlie the upregulation of Orai channels; however, the mechanism underlying their upregulation remains unknown. Regarding Orai1, it has been shown to upregulate in breast, colon, and glioma cancer cells due to hypoxia together with TRPC6 [2+ levels due to hypoxia were diminished by the application of SKF-96365, a CRAC channel blocker [Hypoxia-dependent enhancements in Cath TRPC6 . This en blocker ,286,287. blocker   , stomach2+ levels, which might be responsible for the cancer development. Mechanistically, most of these mutations  are located at key checkpoints in the Orai TM domains controlling pore opening. Their manipulation likely initiates a global conformational change that finally induces pore opening [All these cancer-related Orai1 mutants have been reported to lead to constitutive activity independent of STIM1 . This li opening . Positio opening  and cont opening ,294. How2+ influx through Orai1 channels. The mechanistic role of S116N, located in the non-canonical EF hand, is still unknown. Several other cancer-related mutants are located in the STIM1 C-terminus, which is essential in both maintaining the quiescent state and establishing CRAC channel activation. For instance, W350L is located in the CC2 of STIM1, part of the minimal region sufficient to activate Orai1, and G446C/V, T517I, and S521L are located in the flexible portion of the STIM1 C-terminus. Further studies are still required to understand their mechanistic impact.Among the STIM1 mutants identified to occur in cancer, several  are loc2+ ion channels and their interconnectedness with cancer-promoting signaling pathways has opened new possibilities for future therapeutic strategies.The altered expression of CaA variety of CRAC channel drugs are available, which has provided valuable insights into CRAC channel mechanisms, but only a few have reached clinical trials due to low selectivity or undesirable side effects. In the treatment of cancer, SKF-96365, a SOCE/Orai1 blocker, has been shown to impair cell proliferation of GBM cells in vitro  and meta2+ overload and inhibition of Ca2+-dependent survival pathways [Carboxyamidotriazole (CAI) interferes indirectly with SOCE via the PI3K/Akt pathway. Tested as a potential therapeutic, it affects the expression of BCL2 members ,300 in opathways .Drebrin, an actin-reorganizing protein boosting SOCE, is linked to prostate cancer cell invasion, especially at earlier stages of cancer development. There is evidence that BTP2, an Orai1 inhibitor, targets drebrin . Notably2+ levels through Orai3 and caused cell death of AMLC lines [Additionally, store-operated channels in acute myeloid leukemia cells containing Orai3 have been reported to be targeted by tipifarnib, a farnesyltransferase inhibitor, that prevents farnesylation of Ras . This enLC lines .RP4010, a synergistic drug, prevents SOCE activation by inhibiting Orai1. The drug is undergoing clinical trials and might serve as a treatment for pancreatic ductal adenocarcinoma  and esopIn addition to their function as drug targets, CRAC channel proteins can facilitate the circumvention of a therapeutic effect, known as therapy resistance. This is particularly challenging in the case of the chemotherapeutic agents 5-fluorouracil (5-FU) and cisplatin, that induce autophagy and cell death in cancer cells. In hepatocarcinoma tissues, overexpression of Orai1 impairs the effect of 5-FU , making In summary, although several studies have reported the effect of CRAC channel drugs on various cancers, several questions remain to be addressed, such as why cancer cells continue to proliferate and migrate even though the applied CRAC channel drug blocks store-operated currents. Moreover, of the selective CRAC channel drugs currently available, only a few have made it to clinical trials . Thus, t2+, but other channels also sense Ca2+, either by direct binding of Ca2+ or indirectly by Ca2+-binding proteins, such as CaM [2+ channels, Ca2+ often has an inactivating effect, providing a negative feedback mechanism that protects against too much Ca2+ entering the cell [2+, such as Ca2+-activated K+ channels and Ca2+-activated Cl- channels [2+-activated K+ channels and their role in cancer.An important property of many ion channels is not only the transport of Cah as CaM ,311,312.the cell . Other ichannels ,322,323.channels ,330,331.2+-activated K+ channels include the large (BK), intermediate (IK or SK4), and small conductance Ca2+-activated K+ channels  [+ channels, containing six TM regions (S1–S6) with the pore region located between TM5 and TM6 and both the N- and C-termini located at the cytosolic side [Caand SK3) ,333, whelic side   in the C-terminus of each α-subunit. Functional studies of SK channels have demonstrated that the CaM C-lobe is constitutively bound to the SK channel, and the N-lobe is bound upon cytosolic Ca2+ elevations [2+-dependent interaction of the CaM N-lobe is formed with the S4–S5 linker of the SK channel and triggers a conformational change within the channel complex to induce pore opening [45A, which then moves to the cytosolic side. Additionally, S45B moves away from the pore region, leading to further changes in S6, finally causing channel activation [SK ion channels are activated by changes in intracellular Ca+ levels ,315,332. outside . Howeverevations ,312,337. opening . Specifitivation   , glioma SK4 is expressed in different cancer types, including glioma , glioblaThe catalogue of somatic mutations in cancer (COSMIC)  reports 2+-dependent manner. Specifically, an increase in intracellular Ca2+ levels in SK channel-expressing cells leads to their activation and thus to potassium (K+) efflux, which in turn promotes Ca2+ entry via Ca2+ channels in a positive feedback loop. The increase in intracellular Ca2+ levels achieved in this manner controls Ca2+-dependent cancer hallmarks [The development of cancer features triggered by SK channels generally occurs in a Caallmarks ,292,325,2+ entry, as inhibition of SK4 led cells to accumulate in the G1 phase, whereas the number of cells in the cell cycle S phase decreased [2+ entry, cell cycle progression, and the proliferation rate of primary breast tumor cells [Insights into the influence of the SK channel on cell cycle progression have only been gained for SK4. It is able to indirectly control cell cycle progression by driving cellular Caecreased ,368. In or cells   that trigger EMT. Indeed, silencing of SK4 expression abolished the expression of certain EMT markers   Figure .Overall, there is evidence that SK channels are present in cancer cells and can control the development of cancer features. However, knowledge about the influence of SK channels on individual steps in signaling cascades regulating the cell cycle or migration is limited. In this context, identification of the effects on key players modulating, for instance, the focal adhesion dynamics  is required. A detailed understanding in this regard could improve therapeutic options for cancer cells.Drugs targeting SK channels include peptides extracted from scorpions, sea anemone or bee venom, synthetic analogues, and chemically synthesized modulators . However, all of these modulators arose as limited in medical use due to their high toxicity or low efficiency. Among the blockers, particularly those targeting SK4 have been suggested as promising for the treatment of various cancers . SpecifiTo overcome therapy resistance , SK3 and2+ signaling, which is crucial for EMT progression, contributing to therapeutic escape [The alkyl-ether lipids edelfosine and Ohmline have emerged as promising lipid-antimetastatic agents. Both block SK3-dependent cancer cell migration and metastasis, likely due to lipid membrane reorganization, which inhibits SK3 channels . Edelfosc escape . Ohmlinec escape  and Enzac escape . Moreovec escape ,323.Overall, alkyl ether lipids appear to be the most promising and selective drug candidates for the treatment of SK3-dependent cancers.+ channels interact with Ca2+ ion channels to control various cellular functions, including also the fine-tuning of the intracellular Ca2+ concentration. Voltage-gated K+ (Kv) and KCa2+ channels have been classified as Ca2+ amplifiers because of their interplay with Ca2+ channels [+ channels, when activated, induce membrane hyperpolarization either by increased intracellular Ca2+ levels in the case of KCa2+ channels or by membrane depolarization in the case of Kv channels, thereby enhancing the driving force for Ca2+ influx. Several studies indicate that co-regulation of K+  and Ca2+ channels  channels) plays a significant role in cancer cell progression, growth, proliferation, and invasion/migration [V3.2, promoting the proliferation of prostate cancer cells [2+ entry [2+ influx through store-independent (SICE) Orai1 activation. This trio complex triggers collagen I-induced proliferation and survival of breast cancer cells [Ca2+ channels, in terms of structural and functional requirements and their role in cancer, represents that of Orai1 and SK3 [In addition to their individual role, Kchannels ,327,360.igration ,327,360.igration  . This suggests, in agreement with previous findings in cancer cells [2+ levels specifically through Orai1, which together with SK3 triggers the positive feedback mechanisms [2+ entry in SK3-Orai1 expressing cells, and NFAT translocation was only marginally enhanced. This indicates that already, very low local alterations in Ca2+ levels are sufficient to trigger the SK3–Orai1 interplay. Moreover, we found that K+ currents in SK3 and Orai1 co-expressing cells could be reduced to the level of SK3-expressing cells not only when the general Ca2+ channel blocker La3+ was applied, but also the CRAC channel-specific inhibitor GSK-7975A [+ currents compared to the presence of wild-type Orai1, despite their co-localization being maintained  or abolished (1000 µM EGTA) SK3 K+ currents, both in the absence and presence of STIM1  and an intact pore geometry, as demonstrated by a set of LoF-Orai1 mutants. They were unable to boost SK3 channel activity without affecting the co-localization with SK3. However, STIM1 coupling to Orai1 or an intact STIM1 coupling site within Orai1 (L273) is not required for intact Orai1-SK3 interplay, as evidenced by the preserved boost of Orai1-mediated SK3 channel activity in CRISPR/Cas9 STIM1/Orai1 DKO HEK 293 cells. In agreement with this, Orai1 L273D was also able to trigger the amplification of SK3 Kcurrents . It is scurrents . This recurrents ), two pucurrents ,386), a currents ), and a currents ). It rem+ current amplification under physiological conditions, as STIM1 activation removes Orai1 from SK3, and locally increased Ca2+ levels cannot affect SK3 channel activity. Indeed, global Ca2+ level increases also enabled the amplification of SK3 K+ currents in the presence of STIM1 and Orai1 [2+ elevations are sufficient to govern the interplay of SK3 and Orai1 in the absence of STIM1 [Interestingly, co-expression of STIM1 with Orai1 and SK3 showed an inhibitory effect on Knd Orai1   and the Akt pathway promotes the activity of Rac1/Calpain, which amplifies SOCE, and consequently Akt. Simply stated, SOCE triggers activation of the SK3 channel and the Akt pathway, which mediates the activity of Rac1/Calpain, which in turn leads to the amplification of SOCE  are not yet elucidated in detail. For instance, proliferation can be directly regulated by Ca2+ via Ca2+-sensing proteins or influence transcriptional activity to modulate the expression of cell cycle effectors. Alternatively, PI3K/Akt or RAS/ERK pathways might be affected by either enhanced expression levels of Ca2+ ion channels and/or the effect of Ca2+ on certain oncogenes in the PI3K/Akt or RAS/ERK pathways. Therefore, it remains open whether Ca2+ modulates only a specific path or multiple ones to impact cancer progression in a given cancer type. In most recent studies, the proliferative activity of related cancer cell lines is monitored upon siRNA-mediated inhibition of ion channels in vitro. Nevertheless, evidence of tumor behaviors in vivo is lacking. At this point, the question arises whether the effects of ion channels on proliferation are not merely coincidental because they interact closely with each other, or, possibly with different more relevant components of the Ca2+ signaling cascade. Concerning the role of CRAC channel proteins in apoptosis, several have been identified to contribute to pro- or anti-apoptotic mechanisms; however, the detailed effects on certain regulators of cell survival/cell death signaling cascades are not yet fully understood. Key questions include how altered STIM/Orai expression might influence the expression of pro/anti-apoptotic factors, and how mitochondrial/ER Ca2+ levels and their interplay are dysregulated. Moreover, the molecular mechanisms of mutations identified to be critical in cancer are only beginning to be deciphered, and their connections to Ca2+ dysregulated signaling pathways remain open. In particular, for SK channels as well as their interplay with STIM1/Orai1, the detailed links to various cancer signaling pathways are insufficiently described.Cell fate is determined by the finely tuned interplay of signaling cascades involving various cellular components such as CRAC and SK channels. However, their dysregulation/-function can be linked to novel biological functions associated with cancer progression. Mechanistically, dysregulation of CRAC and SK channels can lead to altered activity of a number of effectors of distinct signaling pathways, such as CaM/CaMKII/CN ,273,276,The multifaceted interplay of these ion channels with intracellular signaling pathways is extended by their interaction with each other and with a set of other signaling components, as exemplified by Orai1-SK3 and Orai1-SPCA2 interplay. For such scenarios, the formation of macromolecular complexes appears favorable. For example, SK3 and Orai1 colocalized in cholesterol-rich regions in breast cancer cells , the disAltered expression or mutation of CRAC and SK channels is responsible for poor prognosis in cancer patients. Therefore, these channels could serve as suitable prognostic markers as well as attractive targets for cancer therapy, also in an isoform-specific manner. However, of a large number of CRAC and SK channel drugs available, only Ohmline currently has the potential for future clinical use in SK3/Orai1-driven cancer progression. In addition, the expression of CRAC and SK channels increases resistance to chemotherapeutic agents and promotes cell proliferation, necessitating the need to address alternative targets via potential therapeutic strategies.2+ signal transduction apparatus, CRAC and SK channels play critical roles in the development of certain cancers. Their modulatory role in Ca2+ signaling affects proliferation, apoptosis, and/or migration. Knowledge of these ion channels and their associated cancer features is extensive but insufficient to develop appropriate therapeutic strategies. A more detailed understanding of the mechanisms of ion channels and their connection to cancer signaling pathways will provide new targets for future and more specific therapeutic strategies against cancer.Overall, among the various members of the Ca


Background: Cellular metabolism is a tightly controlled process during which cell growth and survival are maintained. Lung cancer is a disease with clear sex differences, where female patients have better survival rates than males. Evidence of sex differences is demonstrated in cancer risk, prognosis and response to different therapies, yet a sex-specific approach to cancer studies is not widely considered. These different tumour characteristics attributed to sex that impact disease outcome, including constitutional genetic and somatic molecular differences, make it essential to assess viral and hormonal influences. Methods: In silico analysis of lung adenocarcinoma (LUAD) TCGA data, including K-means clustering algorithm, dimensional reduction with principal component analysis and differential expression analysis using EdgeR (p < 0.05), were used to explore some robust sex differences in LUAD that exist in core signalling pathways and metabolic processes between males and females. The correlation of differentially expressed genes (DEGs) expression with immune abundance in the LUAD cohort was analysed on TIMER2.0 and adjusted by tumour purity utilising Cox proportional hazard. Multiple factorial analysis heatmap visualisation was used to examine endogenous steroid hormonal effects on LUAD patients with different smoking status and age groups. Results: We found 161 DEGs showing key differences in regulation of immune system and cellular homeostasis, key elements of divergent cancer progression, between the two sexes. We also found male and female LUAD patients to favour different metabolic intermediates for energy production to support tumourigenesis. Additionally, high levels of Tregs accompanied by DEGs correlated with better LUAD prognosis, and circulating hormonal transcriptional targets affect proliferation and progression in males and females differently. Finally, we examined the role of oestrogen protection in men and pre-/postmenopausal women. Conclusions: Further studies should focus on sex-specific changes and investigate sex-specific gene regulatory networks of these DEGs. Several lifestyle factors, including tobacco smoking and diet, differ between males and females. These factors might affect metabolic pathways and can influence the activity of epigenetic regulators, resulting in significant global epigenetic changes. Lung cancer is the major cause of cancer-related deaths worldwide, affecting more males than females, with the latter having better survival . AdditioMoreover, lung adenocarcinoma (LUAD) is considered a different disease in males and females, strongly influenced by oestrogen . OestrogThere is a difference in the mechanism of oestrogen receptor action in premenopausal, postmenopausal women and men. Men have lower circulating oestradiol (E2) concentrations compared to premenopausal women. The ovaries of healthy premenopausal women produce circulating 17β-oestradiol, which acts on distant target tissues through conversion of androstenedione to estrone. In postmenopausal women and men, E2 is produced in extragonadal sites, such as adipose tissue and others, from aromatisation of circulating testosterone, making testosterone a circulating pro-hormone locally converted to E2 acting on ER or converted into a second oestrogen , which acts on ER. In females, androgen receptor (AR) activation is weaker; thus, AR is less important unless concentrations increase to those levels of males; then, it might also lead to metabolic disturbances. Evidence of metabolic differences in relation to oestrogen protection indicates that postmenopausal women have increased risk of developing type 2 diabetes due to higher plasma levels of E2 associated with higher levels of testosterone .Here, we provide molecular insights into the sex-specific genetic and genome-wide impact on LUAD, illustrating how males and females seem to favour different metabolic intermediates for energy production to support tumorigenesis, influencing LUAD biology. Our results show dissimilarities in immune response and cellular homeostasis between the sexes, as well as different signalling pathways and metabolic processes between LUAD male and female patients. We also show different hormonal transcription target regulation among different LUAD smoking groups and present different regulation of sex-specific differentially expressed genes (DEGs) according to different age groups in females compared to males, including the effect of oestrogen protection in premenopausal women.Collection of the expression profile of LUAD TCGA data has been previously described . For valp-values < 0.05 was used to control the false discovery rate (FDR), and generalized linear model glmFit to minimise error function was used to determine differential expression.To find common and unique expression gene profiles showing differentiation between the patient subgroups, we used ExpressCluster software . ClusterGene set enrichment analysis (GSEA)  was alsoEnrichment analysis was performed as previously described  accordinp-values were generated, representing the degree of correlation. We utilised Quantiseq to evaluate the impact of immune factors and the expression of 22 immune-related DEGs on LUAD prognosis. Quantiseq is a validated deconvolution-based algorithm that estimates the absolute proportions of relevant immune cell types from RNA-seq [The correlation of our DEGs expression with immune abundance in our cohort was analysed using Tumor Immune Estimation Resource (TIMER) ,20,21 anTo confirm the DEG obtained, EdgeR was used as stated in TIMER2.0 gene outcome module was employed to evaluate the gene expression association on patient survival in relation to sex utilising Cox proportional hazard model for association evaluation, validating the results from GEPIA2 analyses .p-value < 0.05. We found 71 upregulated genes and 90 downregulated genes (p < 0.05). The magnitude of the differential expression changes was visualized with a fitted model MD plot  with significant fold changes log2FC > 6 and only XIST downregulated in females  with significant fold changes log2FC < −5. We confirmed that these 11 genes differentiate both sexes in relation to LUAD carcinogenesis also by verifying whether other X- or Y-linked genes, termed “control genes”, demonstrate a similar pattern  as well as in regulation of androgen receptor signalling pathway; UTY in dioxygenase activity and histone demethylase activity (H3-K27 specific); ZFY transcriptional activation and RPS4Y1 in RNA binding and ribosomal assembly. USP9Y is an essential component of the BMP/TFG-β signalling cascade, NLGN4Y in cell–cell interactions and cell adhesion and TMSB4Y in cytoskeletal organisation. Finally, PRKY, a pseudogene, is involved in protein phosphorylation and ATP binding, while long non-coding RNA (lncRNA) XIST is a major effector of the X-inactivation process via histone deacetylation and enriching repressive chromatin marks.PFKL, HK1) compared to males. We also found mTOR, MAPK, PI3K-Akt and RAS signalling pathway genes to have higher expression mostly in females and AMPK signalling pathway genes with elevated expression mostly in males , metabolism , DNA repair (GADD45A) and immune responses . Since FOXO signalling genes were upregulated with higher expression mostly in our male cohort while downregulated with lower expression in our female cohort, we speculate that, in our male cohort, FOXO signalling seems to maintain cellular energy homeostasis. Furthermore, we found glycolysis, glucogenesis and fatty acid/lipid synthesis enriched in females, where downregulated genes ACSS1, ACSS2, IL4I1 and XIST were expressed at a higher level compared to males. Meanwhile, oxidative phosphorylation genes ATP1B1, ATP12A, ATP6V0A4, ATP6V1E1, ATP6V1G1, NDUFV2 and pyruvate metabolism PDHB genes demonstrated higher expression in males.Our results seem to indicate the “Warburg effect” is mostly active in females, especially with elevated expression of hexokinase and phosphofructokinase  signalling pathway seemed to be altered in both sexes  , to be uth sexes .ABCC1, G6PD, GLRX2, GSR, HBXIP, MGST1, NDUFB4, PRDX4, PRDX6, SELS and TXNRD2.Moreover, genes involved in ROS pathway were upregulated and had higher expression level in our male cohort, including XRCC5, UBE2N, COPS5, SUMO2, IMPDH2, COPS6, TIPIN, APRT, FANCF, INO80C, GTF2A2, DAD1, RFC3, MNAT1, ALKBH5, GTF2B, TAF9, CHD1L, INO80D, AQR, WDR48, POLR2B, DUT, POLL, POLI and COPS3. However, in our female cohort, we only observed a few downregulated DNA repair genes to have higher expression than in males, including UBE2L6, XAB2, RNF168, ISG15, HMGN1, STX3, GTF2H1 and MRPL40.Additionally, we found several DNA repair genes to be upregulated with higher expression in our male cohort , includiWe attempted to explore the relationship between the mRNA expression of our DEGs and immune cell infiltration levels across all 497 samples using TIMER2.0 (as described in p < 0.0001), B lymphocytes , CD8+ T cells  and macrophages  and mostly correlated negatively with CD4+ T cells  and showed the least correlation with neutrophils  and DC .These genes mostly correlated positively with T-regulatory cells  cell infiltration levels and LUAD prognosis, we found that patients with high Tregs infiltration levels had better prognosis, as verified by Quantiseq . We, theFCER2, FXYD5 and RENBP. Neither was there a significant relationship between Tregs and prognosis regarding the low expression level of GIPR, TNFAIP2 and PRG2. However, under low expression of FCER2 , FXYD5  and RENBP  and high Tregs level predicted favourable prognosis, whereas high Treg level predicted favourable prognosis under high expression of GIPR , PRG2  and TNFAIP2 .As shown in These results suggest that the above-mentioned DEGs are independent favourable prognostic biomarkers and combining them with Tregs would allow a more effective role in prognosis prediction and personalised therapy for LUAD.ATP1B1, CLDN9, SULT2B1 and TFF1 are both ER-α and ER-β transcription targets; ARK1C2 and ATP1B1 are both AR and ER-β transcription targets. Finally, GULP1, ICOSLG, IGFBP1, PDE4D, PPARGC1A, SULT2B1 and TNFAIP2 are AR and ER-α transcription targets.To examine the steroid hormone receptors in LUAD, we investigated the role of DEGs encoding oestrogen receptor-α (ESR1) and β (ESR2) and androgen (AR) transcription targets in both phenotypes. Our results clearly show sex bias . ATP1B1,ATP1B1, ARK1C2, GULP1, HAL, ID1, IGFBP1, PDE4D, PPARGC1A, TFF1, SULT2B1, NLGN4Y, TMSB4Y, SLC25A21, TBL1Y, EIF1AY, GPX2, GULP1, USP9Y, IGFBP1, SLCO1A2, PITX1, RAB3B and FURIN to be upregulated in males  and downregulated in females  in contrast to expression of TNFAIP2, VPREB3, ICOSLG, CLDN9, MAPK11, TIAM1, CD22 and SHC3.We found expression of transcription targets These differences in gene expression amongst the groups seem to be partly attributable to the differential presence of the levels of endogenous sex-related hormones rather than smoking status.ARK1C2, FURIN, ID1, MAPK11, PPARGC1A, TFF1, ICOSLG), PID HIF1 TF pathway , EMT , apoptosis , AMPK-signalling pathway (PPARGC1A), adhesion  and ROS (GPX2).These hormonal transcriptional targets associated mainly with proliferation  and postmenopausal women, whereas, for postmenopausal women, regulation of TSPAN8, UGT2B7 and SULT1B1 could possibly imply that non-sex-hormone mechanisms are involved since their expression is similar to that in males. TFF1, however, seems to show a difference in sex rather than menopausal status.We suspect that pathways responsible for cancer development for TSPAN8 has been associated with increased proliferation, migration and angiogenesis induction [UGT2B7 is involved in oestrogen metabolism regulation, with a protective role from genotoxic oxidative products, which could alter the risk of developing cancer [Indeed, increased expression of nduction , furtherg cancer .Circulating sex hormone actions do not account for all sex differences in cancer as sexual differentiation in normal physiology affects male and female rate of growth, immunity, myelination, aging and metabolism, amongst other physiological changes . StudiesLDHA) to create lactate, which is usually reserved for low oxygen state/aerobic glycolysis.The fundamental nutrient utilisation for metabolism in normal physiology differs between the sexes. In healthy humans, carbohydrate metabolites pathways, including glycolysis, glucogenesis and pyruvate, as well as amino acid metabolites, seem to be enriched in male serum compared to that of females. Furthermore, female embryos seem to favour the pentose phosphate pathway (PPP) and males glycolytic and higher glucose uptake. Additionally, it is reported that females seem to favour fatty acid metabolism . MetabolTP53-induced glycolysis and apoptosis regulator (TIGAR) play a regulatory role in cancer energy metabolism and cause increased NADPH production by PPP . ThroughAMPK, which is upregulated with higher expression in our male cohort to decrease expression of gluconeogenic enzymes, whereas, in our female cohort, the AMPK pathway is attenuated by higher expression of mTOR signalling pathway genes, directly phosphorylating PPARGC1A and resulting in activated mitochondrial biogenesis. Additionally, we observed in our female cohort, following PIK3 activation, that AKT exerts an antagonistic effect to regulate mTOR, promoting glucose transporter activity and stimulating glycolysis through activation of glycolytic enzymes, including hexokinase and phosphofructokinase. This results in overexpression of HK1, PGAM2, PFKL and of GLS, causing enhancement in glutamate metabolism. We propose that shifting of the cell’s metabolic programme from catabolic to anabolic, promoting aerobic glycolysis, is due to its MAPK pathway being amplified in our female cohort.We also identified sex-associated differences in tumour basic energy metabolism, which further highlights signalling cross-talk by nutrient sensing. Nutrient sensing is a crucial part of mTOR and AMPK pathways, affecting their interaction with one another, but it also creates metabolic flexibility to maintain homeostasis . SimilarGSTM4 and GSTA2. GSTs and UGTs are enzymes involved in detoxification of glutathione-S-transferases and UDP-glucuronosyltransferases, respectively, and play a crucial role in drug metabolism [GSTA2 and GSTO2 (log2FC > 1.2) compared to females, whereas, in non-smokers, only females seemed to have a higher expression level of UGT1A9 (log2FC > 1.2)  . This coHLA-DQB1 to be significantly correlated with the levels of infiltrating B cells, macrophages, CD8+ T cells, CD4+ T cells, neutrophils, dendritic cells and Tregs in females. Its expression in LUAD tumour cells was found to be a prognostic marker of overall survival (OS) and to be associated with anti-tumour immunity [Immune responses show significant distinctions between females and males, indicating multiple potential differences in the biology of cancers arising in both sexes . Indeed,immunity . Furtherimmunity  and are immunity . Being aimmunity .FCER2, FXYD5, HMHA1 and RENBP to correlate with better prognosis in males, whereas, in females, higher expression of GIPR, PRG2 and TNFAIP2 correlates with better prognosis. In our female cohort, through MAPK signalling, higher expression of MAPK1/3 could result in anergy via JUN, which is reported to occur in T cells infiltrating tumours. A similar response occurs following overexpression of RELA and MAPK11 and NFATC1/2. Additionally, following indirect JUN activation via EGFR or MAPK1/3, it could result in angiogenesis and immune response. MAPK1/3 and RELA seem to be major players in inflammatory immune response in our female cohort following cytokine receptor interaction of CX3CL1 with CXCR5. We speculate this chemokine signal could correlate with tumour-infiltrating lymphocytes as a cancer immune evasion mechanism against immunosurveillance following altered Warburg effect, whereby glucose consumption and oxidation are dysregulated, enabling rapid proliferation [Tumour cells in the TME outcompete T cells for glucose, which leads to sustained mTOR signalling, glycolysis and proliferation , as obseferation .GSTM3, which had higher expression in males, and EGFR, with higher expression in females. The confounding effect of tobacco exposure could partially explain this difference as heavy smoking was found to overburden the defence mechanisms [It is established that smoking carcinogens contribute to the incidence of lung cancer initiation or progression, yet around 20% of smokers acquire lung cancer, indicating that other factors predispose its development, including, sex, genetic alteration, diet, comorbidities and even second-hand exposure . It is ichanisms . Our resCALCR to be upregulated in male DEGs, with completely contrasting expression profiles in males and females regardless of smoking status . However, we previously investigated the global gene expression in LUAD tumour samples of smokers and non-smokers and highlighted the effect of cigarette smoking on tumour differentiation [There are limitations to this study. First, we were not able to fully exclude the effect of tobacco smoke in examining sex differences due to the small number of non-smokers . In our present study, we also showed that, in lung cancer, environmental factors including diet present as a direct association with cancer progression and prognosis and need to be taken into account.


Uveal melanoma (UM) is a rare eye cancer with a high mortality rate due to metastases, leading to death in up to 50% of patients within 10 years from UM diagnosis. Moreover, patients show a median survival of 6 to 12 months after metastasis diagnosis. UM and cutaneous melanoma (CM) have the same melanocytic origin; however, they are very different in terms of molecular alterations and biological behavior. In this review, we will discuss the complex genetic and non-coding RNA-based epigenetic landscapes underlying the transformation, progression, and dissemination of UM. This knowledge will pave the way for the future identification of new biomarkers of the pathology and therapeutic targets.BAP1, EIF1AX, GNA11, GNAQ, and SF3B1, with mutually exclusive mutations occurring in GNAQ and GNA11, and almost mutually exclusive ones in BAP1 and SF3B1, and BAP1 and EIF1AX. Among chromosomal aberrations, monosomy of chromosome 3 is the most frequent, followed by gain of chromosome 8q, and full or partial loss of chromosomes 1 and 6. In addition, epigenetic mechanisms regulated by non-coding RNAs (ncRNA), namely microRNAs and long non-coding RNAs, have also been investigated. Several papers investigating the role of ncRNAs in UM have reported that their dysregulated expression affects cancer-related processes in both in vitro and in vivo models. This review will summarize current findings about genetic mutations, chromosomal aberrations, and ncRNA dysregulation establishing UM biology.Uveal melanoma (UM) is the most common intraocular malignant tumor and the most frequent melanoma not affecting the skin. While the rate of UM occurrence is relatively low, about 50% of patients develop metastasis, primarily to the liver, with lethal outcome despite medical treatment. Notwithstanding that UM etiopathogenesis is still under investigation, a set of known mutations and chromosomal aberrations are associated with its pathogenesis and have a relevant prognostic value. The most frequently mutated genes are  Uveal melanoma (UM) is the most common primary intraocular malignancy in adults and the most common non-cutaneous melanoma . UM accoWhile the rate of occurrence is relatively low, UM has a high mortality rate due to metastatic spread, with up to 50% of patients dying within 10 years from diagnosis ; indeed,2) and Ki-67  score as a measure of proliferative activity BAP1 mutall lines . BAP1 waed cells ,80. Deplanocytes . No corrterature ,76. In rf tumors .GNAQ and GNA11GNAQ and GNA11 genes map on chromosomes 9q21.2 and 19p13.3, respectively. They are paralogous genes with roughly 90% sequence homology and a coding region of seven exons . Among the potential sponges, PYGB (glycogen phosphorylase B) showed the highest expression in UM and most increased levels after transfection with miR-16 mimic, both as mRNA and protein; non-canonical binding sites found in PYGB sequence may allow the miRNA sponge to interact with miR-16. The fifty-seven potential sponges of miR-16 showed a prognostic value in predicting survival in TCGA patients with unchanged levels of the miRNA. A signature related to miR-16 activity including four mRNAs  was identified and validated in an independent cohort  in choroidal malignant melanoma (CMM) compared to non-tumoral choroidal tissues; the authors demonstrated that both metalloproteases are targeted by miR-296-3p, which showed reduced expression in CMM cell lines compared to normal melanocytes. Ectopic expression of miR-296-3p inhibited cell proliferation, migration, and invasion and enhanced apoptosis in vitro  is a cytoplasmic lncRNA upregulated in UM tissues; its knockdown inhibited cell proliferation, migration, and invasion in vitro and also tumor growth in vivo  in metastatic patients compared to non-metastatic UM patients; follow-up data from TCGA showed the association of the lncRNA with histological type, metastasis, recurrence, and death, with a poorer prognosis in the low expression group. Among the correlated genes, MEGF10 (multiple EGF-like domains 10) showed a high positive expression correlation and a prognostic value consistent with ZNF667-AS1. In vitro experiments showed that both ZNF667-AS1 and MEGF10 modulated cell viability, cell cycle progression, and apoptosis in UM cells [AL589843.1, AC016757.1, LINC00957, AP005121.1, PVT1, AC016747.1) with prognostic value was identified in TGCA and GSE22138 [SOS1-IT1, AC016747.1, AC100791.3, AC018904.1, AC104825.1, AC090617.5) were prognostic for OS in UM patients both individually and in combination [RBM15B (RNA binding motif protein 15B), YTHDF3 (YTH N6-methyladenosine RNA binding protein 3), and IGF2BP2 (insulin-like growth factor 2 mRNA binding protein 2), and their association with immune infiltration in UM. By correlation analysis, a signature of thirty-eight lncRNAs correlated to the three regulators was identified; the expression of the lncRNAs allowed to classify TCGA samples into two clusters differing in immune infiltrate, OS, and progression-free survival. Five lncRNAs  were associated with the prognosis of UM patients. Thirteen immune-related genes showing expression correlation with five lncRNAs and associated with poor prognosis showed differential expression in the two clusters, suggesting they may be downstream effectors of m6A regulators and lncRNAs [ZNF667-AS1, ZNF350-AS1, LINC02572, LINC02367, ACVR2B-AS1, DKFZP434A062, CYTOR, LINC01615) with prognostic value. The authors also suggested a possible application in therapy by identifying potential target genes and specific drugs [SAMMSON  was observed in metastatic patients from the TCGA cohort. Knockdown of the lncRNA impaired cell viability and induced apoptosis in UM cell lines and suppressed tumor growth in vivo. Several interactors of SAMMSON were identified, including p32  and XRN2 (5′-3′ exoribonuclease 2); the lncRNA interactome affected mitochondrial function and protein synthesis [BACE1-AS (BACE1 antisense RNA) in thirty-two cancer models from TCGA: higher expression levels of BACE1-AS were associated with a longer OS and progression-free interval in the TCGA UM dataset [AC136475.3, AC104129.1, PPP1R14B-AS1, LINC00963, ZNF667-AS1) related to ferroptosis was identified, showing a predictive value for mortality risk; tumors classified according to the lncRNA signatures also showed differences in the immune response. Three lncRNAs were further studied through in vitro assays, namely LINC00963 (long intergenic non-protein coding RNA 963), PPP1R14B-AS1 (PPP1R14B antisense RNA 1), and ZNF667-AS1. Knockdown of the three lncRNAs impaired cell migration and invasion; effects on cell proliferation were different for each tested lncRNA [AC104129.1, SOS1-IT1 (SOS1 intronic transcript 1), and DLGAP1AS2 (DLGAP1 antisense RNA 2) were associated with high-risk, while IDI2-AS1 (IDI2 antisense RNA 1) with low-risk [AP005121.1, AC104117.3, and SOX1-OT) able to predict OS was identified [CGREF1, P4HA2, RGMB, PKNOX2, SLC6A6), four miRNAs  and six lncRNAs . Kaplan–Meier survival analysis showed that low expression of EPB41L4A-AS1, BOLA3-AS1, SNHG7, and high levels of PVT1 were associated with low survival rates [Concerning the potential application of lncRNAs as prognostic biomarkers, Xu et al. performed a transcriptome analysis in eleven UM tumors (six metastasized and five non-metastasized), identifying 329 differentially expressed lncRNAs (DELs) and 802 differentially expressed mRNAs (DEMs). time PCR . PVT1, whylation  and was hylation ,289). A hylation ). In theeffector . The samtastasis . LOC1001 in vivo . By re-a in vivo , Yang etUM cells . A signaGSE22138  by compaGSE22138 . Anotherbination . First,  lncRNAs . Classific drugs . Increasynthesis . Wang et dataset . Recentllow-risk . A recenentified . As preval rates .G3BP1 (G3BP stress granule assembly factor 1). G3BP1 was upregulated in metastatic compared to non-metastatic tumors from the GSE44295 dataset and positively regulated cell proliferation and angiogenesis in vitro [A particular class of lncRNAs is represented by circRNAs, including molecules with the peculiar characteristic of the covalent binding between the two ends achieved through a specific splicing mechanism, defined as backsplicing . As wellin vitro .UM generally shows a low mutational burden, and only a few mutually exclusive driver mutations and chromosomal abnormalities with relevant diagnostic/prognostic significance occur in patients. Although the primary oncogenic processes in UM are well understood, a greater comprehension of their succession and biological repercussions is required to reveal the evolution of UM and, accordingly, successfully prevent or treat metastases. Furthermore, the few genetic anomalies cause several dozen heterogeneous molecular alterations reported in UM both in vitro and in vivo, influencing many aspects of the tumor and being related to the prognostic features of patients. These findings depict a concealed complex scenario that combines some homogeneous genetic changes with a cascade of disparate epigenetic dysregulations inducing melanocyte transformation and UM dissemination.To date, these epigenetic alterations, particularly those involving ncRNAs, are being studied in order to discover both therapeutic molecules that can be targeted using RNA-based therapies and new diagnostic and prognostic markers that can be measured in biological fluids in a non-invasive manner ,267,300.