Fatty acid metabolism, including β-oxidation (βOX), plays an important role in human physiology and pathology. βOX is an essential process in the energy metabolism of most human cells. Moreover, βOX is also the source of acetyl-CoA, the substrate for (a) ketone bodies synthesis, (b) cholesterol synthesis, (c) phase II detoxication, (d) protein acetylation, and (d) the synthesis of many other compounds, including N-acetylglutamate—an important regulator of urea synthesis. This review describes the current knowledge on the importance of the mitochondrial and peroxisomal βOX in various organs, including the liver, heart, kidney, lung, gastrointestinal tract, peripheral white blood cells, and other cells. In addition, the diseases associated with a disturbance of fatty acid oxidation (FAO) in the liver, heart, kidney, lung, alimentary tract, and other organs or cells are presented. Special attention was paid to abnormalities of FAO in cancer cells and the diseases caused by mutations in gene-encoding enzymes involved in FAO. Finally, issues related to α- and ω- fatty acid oxidation are discussed. Fatty acids (FAs) are critical compounds for the health control and development of the human body due to their participation in cellular metabolism, especially energy production (ATP synthesis), metabolism regulation, and cell proliferation. They are (a) building blocks for complex lipids in cellular membranes, (b) precursors for signaling molecules, such as eicosanoids, (c) allosteric regulators of metabolic pathways, (d) substrates for protein acylation, and (e) ligands for transcription factors. FAs are also responsible for lipotoxicity and contribute to the release of proinflammatory molecules, which play an important role in many diseases. Moreover, an increase in citrate, isocitrate, and malate production associated with free fatty acid (FFA) β-oxidation (βOX) leads to increased NADPH levels in some cells. Cytosolic isocitrate dehydrogenase  and a cytosolic malic enzyme (ME)  play an important role in NADPH homeostasis.The most important sources of FAs found in humans include dietary supply, mainly triacylglycerols, and de novo synthesis, mainly from glucose .As already mentioned, FAs serve a predominant role as substrates for ATP production in many human and animal organs, including the heart, skeletal muscle, kidney, and liver. Over 20 proteins are involved in the uptake, activation, transport into the organelles (mainly mitochondria and peroxisomes), and finally, fatty acid oxidation (FAO). The most important process of FAO-βOX occurs primarily in the mitochondria of many organs and, to a lesser extent, in peroxisomes, mainly in the liver and kidney. In peroxisomes, not only βOX but also α-oxidation takes place. Alfa oxidation produces a fatty acyl CoA, one carbon shorter . ω-oxidaα is expressed at the highest level in hepatocytes, cardiomyocytes, enterocytes, and kidney proximal tubule cells, which are involved in the increased FAO . It. It67]. CAC (SLC25A20) transfers acylcarnitines across the inner mitochondrial membrane . CAC for2S, nonenzymatic acetylations, β-lactam antibiotics, omeprazole (proton pump inhibitor), and heavy metals inhibit CAC .,83.+ accFive ADs found in human cells are involved in the first step of βOX. Characteristics of ADs are presented in Oxidation of long-chain acyl-CoA is catalyzed by one of three ADs: a) very-long-chain acyl-CoA dehydrogenase (VLCAD), b) acyl-CoA dehydrogenase DH-9 (ACAD9), and c) long-chain acyl-CoA dehydrogenase (LCAD). VLCAD oxidizes most LCFAs entering mitochondria. This enzyme, bound to the inner mitochondrial membrane, oxidizes C14:0–C22:0 acyl-CoA, although the preferred substrate is palmitoyl-CoA. The presence of an unsaturated bond in FFAs decreases the efficiency of the reaction catalyzed by this enzyme. PPARα is the most important VLCAD regulator, increasing its gene expression. Sirtuins  may also activate VLCAD through deacetylation ,86,87,882O2. Its function in organs other than the lungs has not been estimated ..2+, and Deficiency of the phytanoyl-CoA 2-hydroxylase impairs the conversion of phytanic acid to pristanic acid (2-methyl BCFAs) and leads to Refsum disease (type IV motor and sensory neuropathy) ,125. TheVLCFAs are also oxidized in microsomes via ω-oxidation. In humans, the first step of ω-oxidation is catalyzed by CYP (CYP4F2 or CYP4F3B). Omega-hydroxy-VLCFAs, formed by CYP4F2 or CYP4F3B, can be oxidized to ω-HOOC-VLCFA (dicarboxylic-VLCFA) by alcohol dehydrogenase and subsequently by aldehyde dehydrogenase. Formed HOOC-VLCFA is then oxidized by βOX in peroxisomes. Importantly, the βOX of HOOC-VLCFA is not affected in X-ALD (X-linked adrenoleukodystrophy) patients [Peroxisomal βOX is necessary for the oxidation of VLCFAs (≥22 carbons), both saturated and mono- and polyunsaturated ,113. TheAbnormalities in the biogenesis of peroxisomes are the cause of Zellweger syndrome. This rare familial disease is characterized by muscle weakness, hepatomegaly, and brain and kidney dysfunction. Goldfischer et al. reported that peroxisomes are absent in the liver and kidney of patients with this syndrome . ConsequSubfamily D of ABC transporters (ATP-binding cassette transporters) in mammals comprises four distinct proteins, namely ABCD1 (adrenoleukodystrophy protein), ABCD2 (adrenoleukodystrophy-related protein), ABCD3 , and ABCD4 . Three of these, ABCD1-3, are localized solely in peroxisomes and mediate the uptake of substrates into the peroxisome for βOX .Abcd genes are under complex regulation at the transcriptional level. The transcription of Abcd1, Abcd2, and Abcd3 genes is regulated by PPARα [Abcd2 and Abcd3, but not Abcd1 and Abcd4, exhibits a high degree of sensitivity toward dietary PUFA intake [ABCD1 and ABCD2 facilitate the transport of VLCFAs or their CoA derivatives into peroxisomes. Interestingly, ABCD1 has a higher specificity for saturated VLCFA-CoA. In contrast, ABCD2 prefers to transport PUFAs, such as C22:6-CoA and C24:6-CoA . Howeverby PPARα ,134. LecA intake .Acetyl-CoA formed during FAO in peroxisomes can be used for synthesizing cholesterol and phospholipids  . For insLipophagy involves the encapsulation of lipid droplets into the autophagosome, which fuses with the lysosome, resulting in the hydrolysis of triacylglycerols catalyzed by lysosomal acid lipase A ,140,141.+ ratio, which inhibits the SIRT1/AMPK pathway. The inhibition of that pathway leads to increased ACC activity. It causes elevation of malonyl-CoA levels in the cytosol, inhibiting CPT1 and the transport of LCFAs into mitochondria, decreasing mitochondrial βOX [Peroxisomal βOX increases the cellular NADH/NADrial βOX ,142.2 formed during βOX is involved in H2O2 production. H2O2 is an important signaling molecule that regulates many cellular processes by modulating the activity of several proteins via cysteine oxidation [2O2 formed during peroxisomal βOX to H2O and O2 [2O2 formed via peroxisomal βOX diffuses out the peroxisome (it is a relatively stable ROS) and may modulate the activity of redox-sensitive protein, which in turn triggers a complex network of signaling processes leading to regulation of (a) NF-ϰB activation, (b) E cadherin expression, (c) the secretion of matrix metalloproteinases, (d) mTORC activity, and (e) autophagy [2O2 can be converted to highly reactive hydroxyl radicals, causing damage to proteins, lipids, and DNA, leading to many diseases, including atherosclerosis, cancer, diabetes, and rheumatoid arthritis [2O2 production, may affect aging processes and aging-related diseases.As mentioned above, peroxisomal FADHxidation . Under pO and O2 . Howeverutophagy ,145. Howutophagy . H2O2 carthritis . Thus, i2. Formed ω-hydroxy-FFAs are oxidized to ω-oxo-FFAs by cytosolic alcohol dehydrogenase. Finally, ω-oxo-FFAs are oxidized by cytosolic aldehyde dehydrogenase to carboxy-FFAs. Formed carboxy-FFAs (dicarboxylic-FAs) can be excreted into the urine or transported into mitochondria or peroxisomes, where they are metabolized via βOX. It should be noted that phytanic acid (described above) can also be oxidized via ω-oxidation [Under physiological conditions, FA ω-oxidation accounts for no more than 10% of total fatty oxidation in the liver . In thisIn the liver, FAO takes place in mitochondria and peroxisomes . In a co+ equilibrium [When intensive FAO occurs in the liver, acetyl-CoA and acetoacetyl-CoA (products of FAO) are used in the mitochondrial matrix to synthesize KBs. Acetoacetyl-CoA can also be formed by condensing two acetyl-CoA molecules in a reaction catalyzed by acetyl-CoA acetyltransferase 1. Subsequently, mitochondrial 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2) catalyzes the condensation of acetoacetyl-CoA and acetyl-CoA, generating 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA), which is cleaved by HMG-CoA lyase (HMGCL), yielding acetoacetate (AcAc) and acetyl-CoA. AcAc can be reduced to D-β-hydroxybutyrate (BHB) by D-β-hydroxybutyrate dehydrogenase 1 (BDH1). In addition, AcAc can undergo spontaneous decarboxylation to acetone ,154. Theilibrium . The forilibrium . The maiilibrium ,152. KBsIn carbohydrate-deficient states, gluconeogenesis is the primary source of blood glucose. The stimulation of gluconeogenesis is attributed to mitochondrial FAO in connection with the production of acetyl-CoA and NADH. Acetyl-CoA is an allosteric activator of pyruvate carboxylase, a key gluconeogenic enzyme, whereas NADH is used to form 3-phosphate glyceraldehyde (precursor of glucose) from 1,3-bisphosphoglycerate . Further+-dependent protein deacetylase [Protein acetylation is a reversible post-translational modification of proteins, which involves the transfer of the acetyl group from acetyl-CoA to the ε-amino group of lysine . Acetylacetylase . MCAD iscetylase . It shoucetylase ,164,165.Human adults produce approximately 1 mol (approx. 17 g) of toxic ammonia daily, most of which, via carbamoyl phosphate, is converted to nontoxic urea  in the urea cycle . It is wThe liver requires a lot of ATP to perform detoxication of xenobiotics and endogenously produced substances . ATP is needed mainly to synthesize uridine diphosphate glucuronic acid, glutathione, 3′-phosphoadenosine-5′-phosphosulfate, and S-adenosylmethionine, compounds playing a key role in phase II of detoxication. Energy can be provided by βOX. Moreover, acetyl-CoA in phase II detoxication can be formed during liver mitochondrial βOX. N-acetyl transferases (NATs), also known as arylamine N-acetyl transferases, play an important role in the phase II detoxication of xenobiotics, including drugs and detoxication . In humaOne of the frequent manifestations in patients with FAOD is liver dysfunction. It is mainly associated with deficiencies of VLCAD, LCHAD, MCAD, CPT1, CPT2, and CAC ,170. SymThe heart requires enormous quantities of ATP to maintain its contraction capacity and ion homeostasis. ATP and phosphocreatine stored in cardiomyocytes ensure the heart works properly for only a few seconds. Therefore, ATP must be constantly synthesized (from ADP and Pi), mainly through oxidative phosphorylation, providing approx. 95% of ATP, with anaerobic glycolysis providing the rest. A healthy subject’s heart is metabolically flexible and readily shifts between energetic substrates . In the Significant changes in heart mitochondrial energy metabolism are related to pathological conditions. In diabetes, the ratio of FAO to glucose oxidation is increased due to elevated FAO and lowered glucose oxidation . The inhHowever, the downregulation of LCAD or MCAD in patients with HF and animals during HF progression was detected. Moreover, impaired FAO contributes to the progression of HF by altering cardiac energy metabolism after myocardial infarction . Thus, tInconsistent results have also been reported regarding the level of malonyl-CoA  and its role in cardiac function. The inhibition of MCD, increasing the malonyl-CoA level , improved cardiac function by increasing cardiac output. The promising results of MCD inhibition were associated with the reduced production of protons due to enhanced coupling between glycolysis and glucose oxidation . HoweverACC2 deletion) did not induce cardiac dysfunction [Animal studies showed that increased FAO , which provided the MCFA source (mainly octanoate), did not eliminate symptoms of LC-FAO defects due to a deficit of TCA intermediates . TriheptFAODs with skeletal myopathy occur most frequently in LCHAD, MTP, VLCAD, and CPT2 defects. Lack of energy production during the FAO process in skeletal muscles results in fatigue, which manifests as myalgia, muscle weakness, myoglobinuria, physical intolerance, and episodes of rhabdomyolysis. Myopathy usually begins due to excessive endurance exercise, anesthesia, or a viral illness in adolescents or adults but can also appear earlier. A significant deficiency of ATP in muscle cells leads to rhabdomyolysis, which, consequently, causes the release of myoglobin into the extracellular fluid and circulation . It was Increased skeletal muscle FAO has been proposed as a potential mechanism leading to impaired muscle insulin sensitivity . Gavin aFAO is also dysregulated in the skeletal muscles of obese individuals. Several studies comparing metabolism in the muscles of obese and lean individuals demonstrated that in obesity, the skeletal muscle metabolic capacity is primarily involved in FA esterification and storage rather than oxidation ,203. In Removing waste from the blood, reabsorbing glucose and other nutrients, regulating the balance of electrolytes and fluid, maintaining acid-base homeostasis, and regulating blood pressure by the kidney requires the continuous synthesis of ATP. FFAs serve as key substrates for energy production in the kidney . Low βOXThe system of delivering FFAs to kidney cells is generally similar to other organs (presented above). Briefly, FFAs can be taken up by the proximal tubular cells by special FFA transporters  or reabsorbed from the glomerular filtrate by the endocytosis of receptor-mediated FA-bound albumin ,211.CPT1 expression significantly ameliorated FAO metabolism in the kidney [CPT1 and decreases FFA catabolism. Moreover, TGF-β1 also represses the synthesis of mRNA encoding the upstream regulators of CPT1, namely PPARα and PPARγ coactivator-1α (PGC1α) [The downregulation or deficiency of CPT is crucial to impaired FAO in experimental models of acute kidney injury or diabetic nephropathy ,212,213.e kidney . In gene (PGC1α) ,217. Gen (PGC1α) . In addiCpt1, 2 and Acox1, 2). Mice with kidney insufficiency injected with fenofibrate demonstrated a decreased expression of caspase 3, a reduced apoptosis rate, reduced fibrosis, reduced kidney injury, and improved renal function. This suggests that fenofibrate treatment restores FAO-related enzyme expression and may prevent lipid metabolism abnormalities in kidney diseases [It has been postulated that restoring FAO by regulating the level or activity of PPARα and TGF-β may improve the treatment of kidney disorders . PPARs adiseases ,220. Thediseases ,221. Alsdiseases . Overalldiseases .Recent studies indicate that βOX can also play an important role in pulmonary fibrosis, especially idiopathic pulmonary fibrosis (IPF), a fatal fibrotic disorder of unknown etiology . IncreasGlutamine and glutamate are the main energetic substrates for enterocytes. However, enterocytes can also oxidize FFAs entering the cells from the plasma and intestinal lumen. FFAs derived from the intestinal lumen  provide more energy to enterocytes (approx. 60%) than FFAs derived from the plasma (approx. 40%) . A high-Colonocytes mainly oxidize SCFAs, including acetate, propionate, and butyrate, which are produced by gut microbiota. Butyrate is the main energy source of colonocytes and uses more than 70% oxygen for butyrate oxidation . Any impIt was suggested that increased FAO in adipocytes might be a promising therapeutic strategy for chronic inflammatory diseases, including obesity and T2D . An expeIt is generally believed that glucose and KBs during starvation, but not FFAs, are energy substrates for the brain. It has been suggested that a lack of active βOX in neurons may protect these cells against excessive ROS production and hypoxia . As was Endothelial cells (ECs) produce more than 85% of the energy needed in anaerobic glycolysis . HoweverA very early work from our department demonstrated palmitoyl–carnitine oxidation in mitochondria isolated from the human term placenta . Later, Glycolysis and glutaminolysis provide enough ATP for the normal function of peripheral white blood cells . HoweverIt has been shown that FAO is also active in steroidogenic tissues. Moreover, it has been demonstrated that FAO activity in steroidogenic cells is regulated by translocator protein (TSPO), also known as the peripheral benzodiazepine receptor . This prBone formation by osteoblasts and bone resorption by osteoclasts play a crucial role in skeletal remodeling. These processes require a large amount of ATP produced by glucose, FA, and amino acid oxidation ,260. SevCPT1A gene or the inhibition of CPT1A activity by etomoxir  blocked osteoclastogenesis. Based on these data, the authors conclude that increasing FAO in osteoclast precursors participates in joint destruction in patients with rheumatoid arthritis [Recent studies showed (a) a significant increase in LCFA oxidation during osteoclast differentiation. This was associated with increased mRNA and protein levels of enzymes involved in βOX . Thus, mrthritis . The res2+ channels) raises intracellular Ca2+ concentration and triggers exocytosis of insulin-containing granules [2+ lead to insulin secretion by pancreatic β-cells mediated by PKC [2+, leading to insulin secretion by pancreatic β-cells. As mentioned, all these complex processes (two intracellular and one extracellular) stimulate insulin secretion by pancreatic β-cells.FAO in the pancreatic β-cell is involved in the regulation of insulin secretion . Many yegranules . FFAs hagranules . Howevergranules . In a nugranules . The secd by PKC . The thiIdx-1 by saturated FFAs and the suppression of genes transactivated by IDX-1, including GLUT2, glucokinase, and insulin [The effect of FFAs on insulin secretion by pancreatic β-cells depends on exposure time, concentration, and the type of FFA ,273. Acu insulin . The inh insulin .Overall, the results discussed above indicate that mitochondrial βOX occurs in pancreatic β-cells and plays an important role in regulating insulin secretion.2O2 (formed during peroxisome βOX) degradation, is practically not detectable in pancreatic β-cells, which might contribute to the development of T2D due to increased plasma FFA concentrations [2O2-mediated lipotoxicity) (a) decreased the H2O2 level and (b) protected the cells against FFA-induced toxicity. Based on these data, it was postulated that peroxisomal βOX is involved in lipotoxicity via the synthesis of H2O2 [In the pancreatic β-cells, similar to other organs, FAO occurs in mitochondria and peroxisomes ,276. HowOne of the distinctive features of cancer cells is a significant increase in ATP production. In cancer cells, ATP is needed to synthesize many micro- and macromolecules  that are essential for cell division and proliferation . In mostOn this basis, it is conceivable that under conditions in which cancer cells require an additional amount of ATP, FAO can play an important role in ATP synthesis. Indeed, it has been shown that activated FAO increases ATP levels and promote cell survival in breast cancer cells and other tumor cells ,339,340.2O2 to H2O. A disturbance in NADPH production in the cells increases sensitivity to ROS and, consequently, cell death [In cancer cells (similar to noncancer), NADPH is required for the generation of new building blocks, mainly FFAs (necessary for membrane phospholipids synthesis) and cholesterol (an important element of cells membranes), to sustain cell growth and proliferation ,279,342.ll death . Overcomll death . Similarll death ,340,342.CPT1A in prostate cancer tumor cells. The knockdown of CTP1A diminishes prostate cancer cells’ proliferation and invasiveness capacity. Furthermore, patients with the highest osteopontin gene (SPP1) expression had the worst prognostic outcome [CPT1A, CPT1B, and ACAD9 was elevated in recurrent gliomas compared to primary tumors, whereas there was no difference in the expression of VLCAD and SCAD between primary and recurrent GBM. Moreover, the overexpression of CPT1B, LCAD, and MCAD was associated with lower overall survival of patients with GBM [ACSL isoforms are overexpressed in colorectal, breast, prostate, and other cancers [Several other data also suggest the contribution of FAO to cancer cell function. For instance, the uptake of FFAs from surrounding adipocytes promoted FAO in breast and colorectal cancers ,346,347. outcome . Some FA outcome . The expwith GBM . Various cancers ,350.FAO may also increase the drug resistance of cancer cells, which was proven for dexamethasone, L-asparaginase, and tamoxifen ,352,353.LCAD expression level was proposed as a hepatocellular carcinoma (HCC) patient mortality predictor [ACSL in tumors of colorectal cancer patients is associated with a poorer prognosis [Moreover, the redictor ,354. Therognosis . OverallThe above-presented data suggest that FAO could be a potential therapeutic target, and its inhibition may reduce cancer cell proliferation, metastasis, and drug resistance. Using different cell lines, attempts have been made to inhibit the transformation at the stage catalyzed by ACSL. The inhibition of ACSL in cancer cells is associated with cell growth inhibition . As CPT1It has been shown that a ketogenic diet or fasting limits tumor progression by different mechanisms, such as (a) lowering blood glucose and insulin concentrations, altering lipid metabolism, and (c) increasing BHB concentrations ,376,377.It suggests that KB oxidation can increase ATP production for the growth of cancer cells. Thus, one can suppose that FAO via an increase in KB synthesis may support cancer growth. The inhibition of SCOT may cause (a) a decrease in ATP synthesis and (b) an increase in BHB (precursor of acetoacetate) concentrations. Both a decrease in ATP synthesis and an increase in BHB may limit tumor progression by a different mechanism  .Together, the results presented above suggest that FAO may promote tumor growth, whereas the inhibition of FAO can lead to a reduction in tumor growth.ACSL expression, most genes encoding enzymes involved in FAO were significantly downregulated [MCAD and LCAD enhances tumor proliferation and aggressiveness. Also, ACSL1 is reported to be downregulated in non-small-cell lung cancer [However, it should be emphasized that the involvement of FAO in cancer cells’ growth and function is still a debated issue because some data suggest that FAO is not necessarily relevant for ATP synthesis in certain cancer cells. The data presented in egulated . Similarg cancer .The diseases caused by mutations in gene-encoding FAO enzymes are rare or even very rare  is diagnosed when a mutation in the alpha subunit of mitochondrial trifunctional protein (HADHA) causes an isolated deficiency of LCHAD. The most abundant pathogenic mutation is c.1528-G > C. This missense variation causes a loss of enzyme activity without changing the conformation and assembly of the MTP complex ,395. AltMitochondrial trifunctional protein deficiency (MTPD) is diagnosed when mutations in HADHA or HADHB  genes lead to a deficiency of all enzyme activities in the MTP complex. According to the Orphanet database, MTPD has been reported in less than 100 cases (Orphanet). Although the clinical manifestations of pathogenic variants of HADHA and HADHB are similar, it is more likely that patients with HADHA mutations will have a severe/lethal phenotype . MoreoveMost of the pathogenic variants of CPT1A result in undetectable or extremely low enzymatic activity ,403. AltCPT2 deficiency has three clinical forms: lethal neonatal, severe infantile, and myopathic (which may manifest from infancy to adulthood). The myopathic form is the most common and the least severe ,409. In A lack of a functional OCTN2 carnitine transporter in cell membranes leads to primary carnitine deficiency, an autosomal recessive disorder of FAO, which has a frequency of 1:40,000–1:100,000 in newborns. The absence of the cell membrane carnitine transporter causes (a) urinary carnitine wasting, (b) a significant decrease in intracellular carnitine concentration, and (c) decreased plasma-free carnitine  and acylated carnitine . YoungerIn SCAD deficiency (SCADD), mild, moderate, and severely decreased enzyme function can be observed despite no correlation between the clinical phenotype and the degree of SCAD dysfunction. The most common variations in SCADD patients, c.511C > T and c.625G > A, are also present in approximately 14% of the general population. The rarity of ACADS inactivating variants and the lack of clinical significance in many patients lead to questions regarding the clinical relevance of SCADD as a hereditary disease ,414,415.Upon closer examination, all patients diagnosed with LCAD dehydrogenase deficiency before 1992 were shown to have a defect in VLCAD ,417,418.The prevalence of mitochondrial short-chain enoyl-CoA hydratase 1 deficiency (ECHS1D) remains unknown since it is a sporadic disease with less than 50 cases worldwide (data until 2020) ,421. PatFanconi renotubular syndrome is a family of related diseases characterized by the dysfunction of proximal tubular epithelial cells, leading to the urinary leak of essential metabolites, and the different syndrome types indicate in which gene the mutation occurred. In Fanconi renotubular syndrome type 3, a single base substitution in enoyl-CoA hydratase and 3-hydroxyacyl CoA dehydrogenase (EHHADH) leads to a missense mutation. Mutated EHHADH can localize mainly in mitochondria rather than peroxisomes and functionally disrupt the MTP complex ,432. EHHAs a consequence of a better understanding of the biochemical traits  of mitochondrial types of HAD, many patients initially diagnosed with SCHAD deficiency based on their symptoms were suffering from HAD deficiency (HADD) ,435. PatPeroxisomal acyl-CoA oxidase deficiency occurs due to the defects in ACOX1. As a consequence of clinical and biochemical features resembling neonatal adrenoleukodystrophy, this disorder is also known as pseudoneonatal adrenoleukodystrophy (pseuso-NALD). Until 2022, only around 30 patients with pseudo-NALD were reported in the literature . Pseudo-ABCD1 gene located on the X-chromosome [ABCD1 gene (approx. 600 different mutations have been identified so far) cause the absence or dysfunction of this transporter.X-ALD is an X-linked inherited disease associated with severe morbidity and mortality in most affected subjects. It is characterized by impaired peroxisomal βOX of VLCFAs (C22 and more), which is reduced to approx. 30% of healthy subjects . It is aromosome ,446. Mutabcd2 or abcd3 may restore peroxisomal VLCFA β-oxidation [Consequently, the accumulation of VLCFAs in plasma and tissues/organs, including the brain’s white matter, the spinal cord, and the adrenal cortex, occurs. Accumulated VLCFAs in tissue/organs are toxic because they disrupt cell membranes’ structure, stability, and function. So far, there is no treatment for most patients with X-ALD . Howeverxidation .The data presented in this review indicate the importance of βOX in an increasing number of tissues and organs, even those previously not considered important. Disturbances in βOX and the α- and ω-oxidation of FAs, including those caused by genetic defects, play an important role in developing various diseases. Several studies also indicate that carcinogenesis is associated with significant disturbances in βOX. Thus, deeper knowledge of the mechanisms linking a disturbance in βOX to several pathologies, including carcinogenesis, is needed to identify novel diagnostic markers and potential therapeutic interventions that may optimize the clinical management of patients with βOX and the α- and ω-oxidation of FA-related disorders.


M35027, seven common coding differences were revealed, including an intact copy of the vaccinia virus immunomodulator A46R in both Cop and vP811.The coding-complete genomes of laboratory vaccinia virus strain Copenhagen and the Copenhagen-derived deletion strain, vP811, were determined by short-read sequencing. Relative to the NCBI reference genome  Orthopoxvirus genus and Poxviridae family, was used to eradicate smallpox and vaccinate against monkeypox (M35027.1). The Cop deletion mutant vP811 was generated by deleting genes J2R, A26L, and A56R, replacing the region between the left inverted terminal repeat (ITR) and F4L with the Escherichia coli xanthine-guanine phosphoribosyltransferase gene, and swapping the region from B13L to the right ITR with Cop C7L (Vaccinia virus (VACV), a member of the onkeypox . The linonkeypox   were infected at a multiplicity of infection of 0.02, and genomic viral DNA was obtained by phenol-chloroform extraction 3 days postinfection as described previously .Purified DNA was subjected to short-read sequencing . This included library preparation (NEBNext Ultra II DNA library preparation kit), sequencing with Illumina NovaSeq6000 using 2 × 150 paired-end configuration, and conversion of raw data into demultiplexed FASTQ files (bcl2fasq).de novo assembly in SPAdes v3.13.0 (M35027 (Geneious Prime version 2022.1.1). The coding-complete Cop genome was assembled manually by adding ITR coding regions to the central genome. The assembly of vP811 reads resulted in a 134,690-nt contig with 20.7× average sequencing coverage. M35027 was used to annotate assemblies using the transfer annotation function and manually curated where necessary (Geneious).Default software parameters were used in the following procedures. Totals of 22,559,466 and 27,604,708 paired-end Cop and vP811 reads were randomly subsampled to 50,000 and 100,000 (Seqtk) /6 (vP811) intergenic or silent mutations, 14 (Cop)/11 (vP811) missense mutations, and frameshifts  indicated that all differences in the Cop sample were present in the Cop virus used by Mehta et al.  and 134,690 bp (33.4% GC), with 261 versus 184 predicted genes, respectively. Pairwise alignment with meshifts . A 41-amminimap2 , SAMtoolminimap2 , and paia et al. , 16.OP868847 and OP868848. The raw reads were deposited in the NCBI Sequence Read Archive (SRA) under the accession numbers PRJNA902654, SRR22318734, and SRR22318733.Sequences have been deposited in GenBank under accession numbers


These results resolve the molecular identity of prepubertal human SSCs, define novel pathways that could be leveraged for advancing their selection and propagation in vitro, and confirm that the human SSC pool resides entirely within Adark spermatogonia.Antineoplastic treatments for cancer and other non-malignant disorders can result in long-term or permanent male infertility by ablating spermatogonial stem cells (SSCs). SSC transplantation using testicular tissue harvested before a sterilizing treatment is a promising approach for restoring male fertility in these cases, but a lack of exclusive biomarkers to unequivocally identify prepubertal SSCs limits their therapeutic potential. To address this, we performed single-cell RNA-seq on testis cells from immature baboons and macaques and compared these cells with published data from prepubertal human testis cells and functionally-defined mouse SSCs. While we found discrete groups of human spermatogonia, baboon and rhesus spermatogonia appeared less heterogenous. A cross-species analysis revealed cell types analogous to human SSCs in baboon and rhesus germ cells, but a comparison with mouse SSCs revealed significant differences with primate SSCs. Primate-specific SSC genes were enriched for components and regulators of the actin cytoskeleton and participate in cell-adhesion, which may explain why the culture conditions for rodent SSCs are not appropriate for primate SSCs. Furthermore, correlating the molecular definitions of human SSC, progenitor and differentiating spermatogonia with the histological definitions of A Cancer survivors are often faced with negative side-effects of their life-saving treatments, which impact their quality of life and one of the most devastating is the loss of spermatogenesis and the resulting permanent infertility . Spermat0/A1 model based on 3H-thymidine-labeled whole mount preparations of rat seminiferous tubules ..BCL6B, DDDX4  and differentiated (DMRT1 and SOHLH1) spermatogonial markers  and cluster 2 (SOHLH1)  H. Moreovluster 2 H, suggesluster 2 E,H.DDX4 and performed iterative re-clustering of these cells, yielding six spermatogonial clusters (clusters 0–5) distinguished based on 1382 differentially expressed genes between all clusters  and differentiating spermatogonia . We also observed species-specific features, including the absence of FGFR3, PIWIL4, and TSPAN33 expression in rhesus spermatogonia. Furthermore, the expression of meiosis-related genes  was essentially absent in rhesus spermatogonia, indicating the absence of late differentiating spermatogonia. Thus, rhesus spermatogonia were clustered together and exhibited gradual transitions in marker expression, making it difficult to distinguish spermatogonial subtypes.  to merge the gene expression data for 1451 human, 233 baboon, 599 rhesus, and 10,012 mouse germ cells . Co. CoPMAIPer 2022) . Howeverer 2022) . In cont, Rpl32) .RPL32, RPL18, RPS12;RPL32, RPL11, RPSA, RPL18, RPS12; RPS4X, RPS9, RPL32, RPL18, RPS12; Rpl4, Rps4x, Rps28, Rps27, Rps29, Rpl37, Rpl39, Uba52; Gene ontology analyses indicated that the 32 conserved primate SSC markers were enriched for genes involved in “Cytoplasmic Ribosomal Proteins”  that were conserved in the SSCs of all three primates were also involved in numerous pathways, including “Pancreatic adenocarcinoma pathway”, “Integrin-mediated Cell Adhesion”, “Regulation of Actin Cytoskeleton”, and “Ras signaling”  exhibited a conserved expression pattern in the SSCs from all three primates and are also involved in integrin-mediated cell adhesion, the regulation of the actin cytoskeleton, and cell migration. Among these genes, MAP2K2, or mitogen-activated protein kinase kinase 2, is already known to be involved in cell fate determination, cell growth, and differentiation , n = 18,131), human vs. rhesus , and human vs. mouse  were retrieved separately. These pairwise orthologues were used to subset each of the baboon, rhesus, and mice datasets separately in Seurat using the human Ensembl gene ID as reference. Subsequently, a merged dataset of all 4 species was produced using the merge function in Seurat, with expression data for one-to-one-to-one-to-one orthologues only for further analysis. Subsequently, the correlation coefficients were calculated between the clusters or cell types using the AverageExpression function in Seurat and the R package tidyr (v1.1.4) [Orthologues were retrieved from Ensembl Biomart . The pairwise orthologues for human vs. baboon ((v1.1.4) . The R p(v1.1.4) . Gene on(v1.1.4) ,73.


Despite the frequency of total knee arthroplasty (TKA) and clinical impact of prosthetic joint infections (PJIs), the incidence and microbiology of these infections in the United States remains unclear. Our objective was to determine the incidence of PJI occurring ≤ 3 months (early), between > 3 and ≤ 12 months (delayed), and > 12 months (late) after primary TKA and to identify the organisms isolated from microbiologic cultures during each of these periods.We conducted a retrospective study of patients in the Veterans Aging Cohort Study- National Cohort who underwent elective primary TKA in the VA between October 1, 1999 to September 30, 2019. The primary outcome was incident hospitalization with PJI. We estimated incidence rates  with 95% confidence intervals (CIs) of early, delayed, and late PJI. Poisson regression was used to estimate the incidence rate ratio (IRR) with 95% CI of early and delayed PJI compared to late PJI. The Kaplan-Meier method was used to demonstrate the cumulative incidence of PJI at 3, 12 and 24 months. We measured the frequency of Gram-positive, Gram-negative, fungal, polymicrobial, and culture-negative PJI occurring within each of the three time periods and compared frequencies of interest using Pearson’s chi-squared tests.Figure 1). Staphylococcus aureus was the most common organism isolated (33.2%) across the periods. Gram-negative bacteria were isolated in 11.1% of all infections, and 15.1% of early PJIs (Table 1).Among 82,401 VHA patients who underwent primary TKA, a total of 1,605 incident PJIs (1.9%) were identified. The incidence rate of PJI was higher in the first 12 months after primary TKA surgery, with an IRR of 20.4  for early and 4.2  for delayed periods when compared to late. The cumulative incidence of PJI at 3 months was 0.77% , at 12 months was 1.25% (95% CI 1.17-1.33%), and at 24 months was 1.56% (95% CI 1.48-1.65%)  as well as the first 24 months (lower panel) following primary total knee arthroplasty.Abbreviations: PJI, prosthetic joint infection; CI, confidence interval.aAmong the 1,605 PJIs in the Overall Cohort, the microbiology data for 103 were missing and 1,502 PJIs with available microbiology data were included in these results. bPolymicrobial defined by multiple genera of organisms identified cIncludes: Micrococcus species, diphtheroids dIncludes: Salmonella, Pasteurella, Citrobacter, Morganella, Acinetobacter, Pasteurella, Burkholderia species, and Gram-negative organisms not otherwise specified eAll fungal infections were identified as Candida species fNumbers may not sum to group totals or percentages as polymicrobial infections with more than one organism were possible Abbreviations: PJI, prosthetic joint infection.Incidence rates of early and delayed PJI were significantly higher than late PJI following primary TKA. Gram-negative organisms were more prevalent in early compared to delayed or late PJI. Empiric Gram-negative antibiotic therapy should be considered with a suspected PJI within 3 months after elective primary TKA.Alisa Stephens-Shields, PhD, Gilead Sciences: Advisor/Consultant Charles Nelson, MD, Stryker: Advisor/Consultant|Zimmer-Biomet: Advisor/Consultant|Zimmer-Biomet: Grant/Research Support


Leiocassis longirostris), comparing Aeromonas hydrophila-infected subjects to healthy control subjects. A total of 19,581 single nuclei cells were sequenced using 10x Genomics . Based on expressed unique transcriptional profiles, 33 cell clusters were identified and classified into 12 cell types including keratinocyte (KC), fibroblast (FB), endothelial cells (EC), secretory cells (SC), immune cells, smooth muscle cells (SMC), and other cells such as pericyte (PC), brush cell (BC), red blood cell (RBC), neuroendocrine cell (NDC), neuron cells (NC), and melanocyte (MC). Among these, three clusters of KCs, namely, KC1, KC2, and KC5 exhibited significant expansion after A. hydrophila infection. Analysis of pathway enrichment revealed that KC1 was primarily involved in environmental signal transduction, KC2 was primarily involved in endocrine function, and KC5 was primarily involved in metabolism. Finally, our findings suggest that neutrophils may play a crucial role in combating A. hydrophila infections. In summary, this study not only provides the first detailed comprehensive map of all cell types present in the skin of teleost fish but also sheds light on the immune response mechanism of the skin following A. hydrophila infection in Chinese longsnout catfish.As the primary natural barrier that protects against adverse environmental conditions, the skin plays a crucial role in the innate immune response of fish, particularly in relation to bacterial infections. However, due to the diverse functionality and intricate anatomical and cellular composition of the skin, deciphering the immune response of the host is a challenging task. In this study, single nuclei RNA-sequencing (snRNA-seq) was performed on skin biopsies obtained from Chinese longsnout catfish ( Aeromonas hydrophila is a significant gram-negative opportunistic pathogen that is widely distributed in aquatic environments , and crucian carp Carassius auratus from the Cyprinidae family were examined upon A. hydrophila infection. This analysis revealed that differentially expressed genes (DEGs) in the skin were primarily associated with immune regulation responses  skin. By employing established cell lineage markers, a comprehensive map was constructed to identify all cell types in the skin under both conditions. Furthermore, the cellular composition and gene expression profiles were examined, and pathway enrichment analysis was conducted on different cell populations. Notably, the findings highlight the potential significance of neutrophils in defense against A. hydrophila infections. The datasets generated in this study serve as a valuable resource for in-depth investigations into L. longirostris skin and lay the groundwork for further exploration into the mechanisms of bacterial infections in teleost skin.This study presents an analysis of snRNA-seq data from 19,581 cells collected from healthy controls and A. hydrophila was obtained from the germ bank of the Sichuan Academy of Agricultural Sciences and cultured on Todd-Hewitt agar (THA) at a temperature of 25°C with shaking at 150 rpm. The adult L. longirostris used in this study were 1 year old . These specimens were obtained from the breeding and releasing station affiliated with the Fisheries Institute of the Sichuan Academy of Agricultural Sciences. Following a previously established testing method, five fish were subjected to a 30-minute soaking period in 5 L of 106 CFU A. hydrophila at a temperature of 26.0 ± 1°C. Subsequently, the fish were transferred to a freshwater tank maintained at the same temperature  for pooling and thorough mincing. Next, 500 μL of pre-cooled cracking buffer was added to the homogenizer to extract the nuclei, following the previously described method  in accordance with the manufacturer’s instructions. Subsequently, quantitative analysis of the barcoded sequencing libraries was performed using the Agilent Bioanalyzer 2100 system . Finally, the resulting libraries were sequenced on an Illumina 10× Genomics Chromium platform (10× GENOMICS) in a paired-end sequencing mode.L. longirostris (accession number: PRJNA692071) using the STAR aligner with default parameters. Through the initial quality control, barcodes and UMIs that did not meet the requirements were excluded. The CellRanger count algorithm was then utilized to generate single-cell gene counts for each library . To identify the pathways associated with DEGs in neutrophils, KC1, KC2, and KC5, we performed a KEGG enrichment analysis using the phyper function. False discovery rate (FDR) was used to determine the threshold of q value, and KEGG terms (FDR ≤ 0.05) were considered significantly enriched.To cluster cells, Principal Component (PC) Analysis was conducted on the normalized and filtered gene-barcode matrix. The top five PCs were selected for conversion into Uniform Manifold Approximation and Projection (UMAP), enabling visualization of cell clustering in two dimensions . Graph-bA. hydrophila infection, we conducted snRNA-seq analysis on skin samples obtained from both uninfected and infected fish. The snRNA-seq workflow consists of five main steps: sample preparation, single nuclei capture, library preparation, sequencing, and visualization   were identified by the expression of ker gene Table S3kdr, pde2a, fgd5, and ptprb. However, they can be further distinguished based on the expression of additional markers. For instance, EC1 is characterized by the expression of flt4, prox1, exoc3l2, stab2, vwf, and znf521, while EC2 is characterized by the expression of cdh5, flt1, podxl, abcg2, mmrn2, sema3g, ldb2, and arhgap31 , neuroendocrine cells (NDC), and neuronal cells (NC) are also recognized by specific marker genes. Melanocytes are characterized by the expression of several marker genes, including  slc35f1 Table S3dock2, which further separated into microglial cells, monocytes/macrophages (Mφ/Mon), neutrophils, myeloid cell, dendritic cell, T cell, and B cell by expression of pag1, csf1r, mmp9, ctss, znf366, satb1 and itgb3, and igkv4-1, respectively  (A. hydrophila infection (4.65 folds). To further investigate the transcriptomic changes of KC1, KC2, and KC5 after A. hydrophila infection, we compared the expression patterns of control and A. hydrophila-infected fish. A total of 428, 372, and 70 differentially expressed unigenes (DEUs) (probability ≥0.8 and relative change ≥2) were identified from KC1, KC2, and KC5, respectively  Table S4A. hydrophila-infected samples than in samples from the control group  infected with A. hydrophila. Through the single nuclei cell collection, we successfully sequenced a total of 10,400 cells from the control group and 9,181 cells from the A. hydrophila-infected group of fish skin. In addition, we have successfully identified cell type-specific markers, which will facilitate a clear and unequivocal definition of cell types. This achievement sets the stage for the future development of genetic tools that enable precise labeling and manipulation of specific cell types. This capability is crucial for analyzing the specific functions of each cell type within the intricate skin region. In mammals, cells clustered in different skin regions have been identified based on their distinct expression of marker genes. These cell types include KC, FB, EC, and PC, as well as nerve-related and immunity-related cells (fat2 + ndrg2) (col6a3+ dcn) (ptprb+ pde2a) (muc5b + sytl2 + slitrk6) (tnnt3+ tnni1+ mylpf) (dock2 + fyb1) (kcnma1+ pclo)  , fibrobla3+ dcn) , 54, end+ pde2a) , 56, secslitrk6) , 57, 58,+ mylpf) –61, immu + fyb1) , 63, and1+ pclo) , 64. Thi1+ pclo) . In most1+ pclo) Table S3A. hydrophila infection. However, it is challenging to obtain a comprehensive understanding of the cellular and molecular immune responses in fish infected with A. hydrophila. In this study, we examined the immunological response in Chinese longsnout catfish infected with A. hydrophila at a single-cell resolution. The purpose was to identify the specific region responsible for antibacterial immunity in the infected fish. In human inflammatory skin diseases, it is well-known that there are often phenomena such as excessive proliferation of epidermal keratinocytes and abnormal keratinization or terminal differentiation of the epidermis   (shtn1+ znf366) (csf1r + slc2a6) (mmp9+ adam8)  , 75, B c, igll5) , 77, DC  znf366) , Mo/MΦ ( slc2a6) , 79, and+ adam8) , 80, and+ adam8) –84. HereA. hydrophila infections. By elucidating these mechanisms, we contribute to a greater understanding of host-pathogen interactions in fish skin and pave the way for future research in this area. Using snRNA-seq analysis, we identified 12 cell types, including KC, FB, EC, and IM. Numerous new pathogenesis-related phenomena, including epidermal hyperplasia and keratinocyte differentiation disruption, were triggered by A. hydrophila infection in Chinese longsnout catfish. Based on the increase in cell proportion and KEGG pathway enrichment analysis, we concluded that neutrophils may be the key cell type required for A. hydrophila eradication. This study resulted in a detailed cellular atlas of fish skin and a greater comprehension of how A. hydrophila attacks the skin and how the skin resists bacteria.Our research represents the first comprehensive comparative transcriptomic analysis of non-lesional skin from Chinese longsnout catfish, comparing infected samples with healthy controls. Moreover, this analysis has provided valuable insights into the complex interplay between different cell types and the changes in gene expressions associated with https://www.ncbi.nlm.nih.gov/bioproject/PRJNA991636.The original contributions presented in the study are publicly available. This data can be found here: The animal study was approved by the Animal Care and Use Committee of the Fishery Institute of the Sichuan Academy of Agricultural Sciences (20170226001A). The study was conducted in accordance with the local legislation and institutional requirements.CM: Writing – original draft, Writing – review & editing. LZ: Investigation, Methodology, Writing – review & editing. HZ: Formal Analysis, Validation, Writing – review & editing. ZH: Methodology, Resources, Writing – original draft. YD: Conceptualization, Supervision, Writing – review & editing. ZZ: Software, Visualization, Writing – original draft. HK: Investigation, Resources, Writing – review & editing. JD: Funding acquisition, Resources, Writing – review & editing. QL: Project administration, Resources, Supervision, Writing – review & editing. JZ: Funding acquisition, Project administration, Supervision, Writing – review & editing.


Notably, patients with melanoma, lung, and kidney cancer with high NUSAP1 expression levels have shorter survival times and lower immunotherapy response rates. Using Cmap analysis, we identify Entinostat and AACOCF3 as potential inhibitors of NUSAP1-mediated pro-oncogenic effects. In vitro and in vivo experiments further confirm that NUSAP1 knockdown significantly reduces the proliferation ability of A549 and MCF-7 cells. Overall, our study highlights the potential of NUSAP1 expression as a novel biomarker for predicting prognosis and immuno-therapeutic efficacy across different human cancers and suggests its potential for developing novel antitumor drugs or improving immunotherapy.Nucleolar and spindle-associated protein 1 (NUSAP1) is a microtubule-associated protein that plays a crucial role in mitosis. Despite initial reports suggesting a potential involvement of NUSAP1 in tumor progression and malignant cell regulation, there has been no systematic analysis of its role in the tumor immune microenvironment, nor its predictive value for prognosis and immunotherapy response across different cancer types. In this study, we analyze NUSAP1 mRNA and protein expression levels in various human normal and tumor tissues, using data from TCGA, GTEx, CPTAC, HPA databases, and clinical samples. Our findings reveal that NUSAP1 is highly expressed in multiple tumor tissues across most cancer types and is primarily expressed in malignant and immune cells, according to single-cell sequencing data from the TISCH database. Prognostic analysis based on curated survival data from the TCGA database indicates that NUSAP1 expression levels can predict clinical outcomes for 26 cancer types. Furthermore, Gene Set Enrichment Analysis (GSEA) suggests that NUSAP1 promotes cell proliferation, tumor cell invasion, and regulation of anti-tumor response. Analysis of immune score, immune cell infiltration, and anti-cancer immunity cycle using ESTIMATE, TIMER, and TIP databases show that high NUSAP1 levels are associated with low CD4 According to recent data on population-based cancer data reported by the American Cancer Society, cancer is a major public health problem worldwide, with persistently increasing numbers of new cancer cases and cancer deaths each year Nucleolar and spindle-associated protein 1 (NUSAP1), a well-conserved protein in vertebrates, possesses a typical cell cycle-dependent localization and microtubule-binding properties in vitro cellular experiments to validate the regulatory function of NUSAP1 on cell proliferation using breast cancer and lung adenocarcinoma cell lines. Therefore, our systematical analysis indicates that NUSAP1 could serve a reliable predictive biomarker for prognosis and tumor immunotherapy response. Furthermore, considering that NUSAP1 is a critical microtubule stabilizer In this study, we utilize various public databases and our collected cancer samples to investigate the differential expression levels of NUSAP1 in cancer and normal tissues. Additionally, we characterize the potential function of NUSAP1 and its influence on immune cell infiltration in pan-cancer. Furthermore, we disclose the predictive value of NUSAP1 for tumor prognosis and response to immune checkpoint blockade therapy based on survival data from TCGA and GEO databases. We also conduct a connectivity map analysis to search for candidate compounds that could target the NUSAP1-mediated pro-oncogenic effect. Moreover, we perform NUSAP1 in human normal tissues, including bulk and single tissues, was downloaded from the Genotype-Tissue Expression Project (GTEx) database . To compare the expression levels of NUSAP1 in normal and 31 pan-cancer tissues of the Cancer Genome Atlas (TCGA) database, the TIMER 2.0 online tool (http://timer.comp-genomics.org/) was utilized. For statistical analysis and graphical presentation of the normalized gene expression data of NUSAP1 in cancer and normal tissues from TCGA, GTEx, and UCSC Xena databases, the R package UCSCXenaShiny (v1.1.8) was used. As supplementary data, the expression levels of NUSAP1 in normal and tumor tissues of breast cancer (BRCA), colorectal cancer (Colorectum), liver cancer (LIHC), lung adenocarcinoma (LUAD), prostate cancer (PRAD), and stomach cancer (STAD) were downloaded from the Gene Expression Omnibus (GEO) database and analyzed. The levels of NUSAP1 transcripts were obtained from the Ensemble website (https://www.ensembl.org/index.html) and the UCSC Xena database, respectively.The mRNA expression data of Ten paired normal and tumor tissues were collected from breast and lung adenocarcinoma patients who underwent surgical excision at either Southwest Hospital or Xinqiao Hospital of the Army Medical University, China  was utilized. Histochemical staining images depicting NUSAP1 in normal and tumor tissues of COAD, GBM, LIHC, OV, pancreatic cancer (PAAD), PRAD, melanoma (SKCM), and STAD were obtained from the Human Protein Atlas database.The protein levels of NUSPA1 in several cancer types, including breast cancer (BRCA), colon cancer (COAD), glioblastoma (GBM), head and neck squamous cell carcinoma (HNSCC), kidney clear cell carcinoma (KIRC), liver cancer (LIHC), lung adenocarcinoma (LUAD), and ovarian cancer (OV), were analyzed using data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC). For phosphorylation site analysis of NUSAP1 in normal and tumor tissues, the bie tool  database (http://tisch.comp-genomics.org/home/). The expression data of NUSAP1 mRNA in different cell types of 79 datasets were downloaded and presented graphically using the R package pHeatmap (v1.0.12). In addition, Umap plots showing the expression pattens of NUSAP1 in different cell types were obtained from the TISCH database.The single-cell expression levels of NUSAP1 and curated survival data of 31 cancer types from the TCGA database were downloaded from UCSC Xena. The data were then matched and analyze. Four types of outcomes, namely overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (DFI) were analyzed to evaluate the prognostic and predictive value of NUSAP1 levels for each cancer type. Survival analysis was performed using two methods: the Kaplan-Meier method implemented in R packages survival (v3.3-1) and survminer (v0.4.9), and univariate Cox regression analysis using SPSS software . The results of analysis were graphically presented using the R package pHeatmap (v1.0.12). For clinical data analysis, expression data of NUSAP1 and clinical phenotype data were also downloaded from UCSC Xena and matched accordingly. Based on the cutoff value of NUSAP1 level determined in the OS or DSS analysis, patients in each cancer type were divided into NUSAP1-high and -low groups. Related clinical data, including age, sex, T, N, M status, TNM stage, and recurrence status, were compared between these two groups using the chi-square test. Analyzed results were collated and presented graphically using the R package pHeatmap (v1.0.12). To further validate the prognostic value of NUSAP1, outcomes analysis of GEO datasets was performed. Kaplan-Meier plots were generated using the KM plot online tool Expression data of  NUSAP1, and the differentially expressed genes (DEG) between these two groups were used for GSEA. The cancer-related hallmark gene set file  was downloaded from the Molecular Signatures Database (https://www.gsea-msigdb.org/gsea/msigdb). Normalized Enrichment Score (NES) and False Discovery Rate (FDR) were calculated using the DEGs utilizing the hallmark gene set, utilizing the R package GSEA (v1.38.2). The analyzed results were summarized and graphically presented in the bubble plot using the R package ggplot2 (v3.3.6).The TCGA patients in each cancer type were divided into high and low groups based on the expression level ofhttps://bioinformatics.mdanderson.org/estimate/). The immune score between NUSAP1-high and -low patients  was compared and graphically presented using the R package ggplot2 (v3.3.6). To analyze the influence of NUSAP1 expression and mutant status on immune cell infiltration in 40 cancer types, the TIMER 2.0 database was utilized. The correlation between NUSAP1 expression and infiltration degree of 15 immune cell types, including CD4+T, CD8+T, B, follicular helper T cell (TFH), dendritic cell (DC), macrophage, regulatory T cell (Treg), natural killer (NK), NKT, γδT, myeloid-derived suppressor cell (MDSC), monocyte (Mono), MAST, neutrophils (Neut), and eosinophils (Eosi), two stromal cells (carcinoma-associated fibroblast (CAF) and endothelial cell), and three progenitor types was explored using spearman correlation analysis.Immune score data for each patient in 18 cancer types were downloaded from the ESTIMATE database  database (http://biocc.hrbmu.edu.cn/TIP) NUSAP1-high and -low samples were compared using either Student's t test or Mann-Whitney U test. The analyzed results for the 22 cancer types were summarized and graphically presented using the R package pHeatmap (v1.0.12) and ggplot2 (v3.3.6).The impact of NUSAP1 and 75 immune-related regulators in 31 cancer types was analyzed using cor.test function in RStudio (v1.3.1093) with TCGA expression data. The results were summarized and presented visually using the R package pHeatmap (v1.0.12). Moreover, the correlation between NUSAP1 expression and tumor mutation burden (TMB) or microsatellite instability (MSI) was analyzed using UCSCXenaTools (v1.4.7) online tool (https://shiny.hiplot.com.cn/ucsc-xena-shiny) NUSAP1 expression and related pathological data from anti-PD-1/PDL-1-treated LUAD patients, anti-PD-L1-treated kidney cancer patients, and anti-PD-1-treated melanoma patients were obtained from the GSE135222, IMvigor210, and GSE91061 datasets, respectively. Survival analysis was performed using the survival (v3.3-1) and survminer (v0.4.9) packages in R.The expression correlation between NUSAP1-high and -low samples in each cancer type were obtained from the previous GSVA analysis in this study. The 500 most upregulated or downregulated genes were collected and utilized as the NUSAP1-related signature. The CMAP_gene_signatures. RData file, which contains 1288 compounds-related signatures, was downloaded from the database website (https://www.pmgenomics.ca/bhklab/sites/default/files/downloads), and used for calculating the matching score. The analysis process was followed the methodology outlined in previous publications Differentially expressed genes between NuSAP1 shRNA was obtained from clone ID: TRCN0000136422. The NUSAP1 targeting sequence was 5'-CCTCAGGTAACAGAGATTC-3' and the control shRNA sequence was 5'- GCAGTTATCTGGAAGATCAGG-3'. The NUSAP1 and control shRNA sequence were subcloned into the pLV-H1-EF1α-puro vector, respectively. To package virus, HEK293 cells were transfected with the pLV-H1-EF1α-puro-NUSAP1/control shRNA plasmid, along with Gag-Pol, Rev, and VSV-G plasmids, in a ratio of 1:0.45:0.18:0.27. The transfection was carried out for 72 hours. Subsequently, MCF-7 and A549 cells were infected with NUSAP1/control shRNA viruses for 48h in the presence of 8 μg/mL of polybrene . Stable A549 and MCF-7 cells were generated under the selection of 2 μg/mL puromycin (Sigma). The efficiency of interference was assessed by western blotting with 1:1000 dilution of rabbit anti-NUSAP1  and mouse anti-GAPDH antibodies .HEK293, MCF-7, and A549 cell lines were purchased from the American Type Culture Collection (ATCC). 4 cells were plated in each well of a 96-well plate and 20 μL of CellTiter 96 AQueous One Solution reagent was added to each well containing 100 μL of medium. After 1 hour incubation in humidified 5% CO2 incubator, the absorbance at 490 nm was measured using an Hidex Sense microplate reader. For the proliferation experiment, 5 x 104 cells were seeded in 24-well plates, and the cell count was determined at 24h, 48h, 72h, respectively.MTS assay and cell counting were performed to assess the impact of NUSAP1 on the cell viability and proliferation ability of A549 and MCF-7 cells. For MTS assays, the CellTiter 96 AQueous One Solution Cell Proliferation Assay system (Promega) was used according to the manufacturer's instructions. A total of 1 × 103 control or NUSAP1-knockdown A549 and MCF-7 cells were seeded in six-well plates. The medium was replaced every three days to maintain the cell's normal growth state. The cells were then cultured for 14 days, and then the colonies were washed with PBS, fixed in 4% paraformaldehyde for 15 mins, and stained with crystal violet (0.1%) for 30-40 min. Finally, colonies were photographed and counted.To evaluate the impact of NUSAP1 on long-term proliferation ability, 1 × 10in vivo, 1 × 107 control or NUSAP1-knockdown A549 and MCF-7 cells were subcutaneously inoculated in the underarm region of the right foreleg of each mouse (5 mice for per group). The tumor diameter and weight of tumor-bearing mice were measured at 3, 6, 9, 12, 16, 20, and 22 days respectively after inoculated. Tumor volume was calculated using the formula: volume = (long diameter) × (short diameter)2/2. After 20 days, the mice were euthanized, and the tumors were isolated, weighted, photographed. The tumors were then lysed and total protein was extracted for western blotting analysis to assess the levels of NUSAP1 and KI67 proteins in each tumor. Antibodies used for western blotting was rabbit anti-NUSAP1  at a 1:1000 dilution, rabbit anti-KI67  at a 1:1000 dilution, and mouse anti-β-Actin  at a 1:20000 dilution.All mice experiments were conducted in accordance with the protocols approved by the Ethical Committee for Animal Experimentation of the Army Medical University. SPF grade female nude mice (5 weeks old with a mean body weight of 20 g) were purchased from Vital River Laboratory Animal Technology . To evaluate the effect of NUSAP1 on the cell proliferation ability NUSAP1 level. Spearman correlation analysis was employed to analyze the expression correlation between NUSAP1 and immune-related regulators. Statistical significance was set at P < 0.05.Statistical analysis in this study was performed using SPSS  and Graphpad Prism  software. For comparisons of continuous variables, Student's t-test for two groups was used if the data were normally distributed, and the Mann-Whitney U test was used when the data were not normally distributed. Chi-square and Fisher's exact test were used for comparisons of categorical data. Univariate Cox regression analysis and Kaplan-Meier method were employed to assess the prognostic value of NUSAP1 in human normal tissues, we employed the GTEx database. As shown in Figure NUSAP1 were found in testis and numerous organs, including esophagus, adrenal gland, skin, ovary, colon, lung, stomach, liver, kidney, cervix, breast, and prostate, which are known to be susceptible to cancer development. In contrast, NUSAP1 was expressed at low levels in non-proliferative tissues such as heart and brain , with particularly high expression observed in proliferating T cell (T-proli)  in ACC, KIRC, KIRP, LUAD, and PARD. Additionally, patients with high NUSAP1 expression in KICH, KIRC, KIRP, LUAD, LUSC, PARD and SKCM were more prone to lymph node metastasis (N status), and NUSAP1 levels positively correlated with distant metastases (M status) in patients with KIRC, KIRP, LIHC, and LUAD. NUSAP1-high patients with ACC, KIRC, KIRP, LUAD, and SKCM also showed a significant trend towards higher TNM stages. Furthermore, patients with high NUSAP1 expression in ACC, KICH, KIRP, LGG, PAAD, and PARD had a higher risk of recurrence compared to those with low NUSAP1 levels  was conducted. This analysis examined differentially expressed genes between s Figure . This fiNUSAP1 exhibited a positive correlation with epithelial-mesenchymal transition (EMT) in ACC, KICH, KIRC, KIRP, LGG, and PAAD patients. This correlation may explain why patients with high NUSAP1 levels in these cancer types are prone to lymph node and distant metastasis, as well as recurrence. Interestingly, the enrichment of the EMT pathway was not significant in HNSC and STAD patients with high NUSAP1 levels, consistent with the analysis of N and M status in these two cancers -gamma, IFN-α, inflammatory, IL-6, IL-12, complement, and allograft rejection pathways Figure . These pt Figure . In concNUSAP1 expression can influence the immune cell infiltration in human cancers, we first analyzed the ESTIMATE database to compare immune scores between NUSAP1-high and NUSAP1-low expressing patients in 18 cancer types. The immune scores of the high NUSAP1 expression in GBM, LUAD, LUSC, SKCM, and STAD were significantly lower than that of patients with low NUSAP1 expression. However, the immune scores appeared to be positively correlated with NUSAP1 levels in KIRC and LGG patients  To explore which immune cell types could be influenced by NUSAP1 expression levels, we also observed the effect of NUSAP1 mutations on the infiltration of six immune cells  into the TME of 31 cancer types. The results revealed that both four different types of NUSAP1 gene mutations, including deep deletion, arm-level deletion, arm-level gain, and high amplification, could decrease the infiltration of six immune cells in most cancer types , recruitment of Th1 cell (Step 4) and recognition of cancer cell by T cells (Step 6). However, a negative correlation was observed between high NUSAP1 levels and immune cell infiltration into tumors (Step 5) in most cancer types, further indicating the immunosuppressive effect of NUSAP1 in TME.Given the results of our previous analysis, which demonstrated the regulatory role of NUSAP1 expression exhibited lower immune activity scores in most steps compared to those with low NUSAP1 expression, including T and CD4+T cell recruiting (Step 4). Additionally, a positive association was observed between activity scores of Th2, Treg, MDSC recruitment (Step 4) and NUSAP1 levels in KIRC  in most cancer types, However, in KIRC and THCA, NUSAP1 exhibited a positive correlation with the majority of immune-related molecules. Notably, high expression levels of NUSAP1 were positively correlated with various immune checkpoint molecules, including CD274 (PD-L1), CD276, TIGHT, PDCD1 (PD-1), CTLA4, LAG3, IDO1 in BRCA, GBM, KICH, KIRC, KIRP, LGG, PAAD, LUAD, STAD, and THCA. Furthermore, VEGFA NUSAP1 in GBM, KICH, KIRC, KIRP, LUAD, PAAD, SARC, and SKCM. Similarly, evaluated levels of TGF-β1 was also observed in NUSAP1 highly expressing patients with GBM, KICH, KIRC, KIRP, LGG, and THCA  and OS in kidney cancer and SKCM when treated with anti-PD-1/PD-L1 therapy, compared to those with high NUSAP1 levels , an optimal signature matching method, we compared the NUSAP1-related signature with CMap gene signatures, resulting in similarity scores for 1288 compounds. Heatmap clustering analysis showed the enrichment of 23 compounds with |Xsum score| ≥ 0.3 across the 31 cancer types. Notably, four compounds, namely MS-275 (Entinostat), 4,5-dianilinophthalimide (DAPH), W-13, and arachidonyl-trifluoromethane (AACOCF3), exhibited significantly lower scores in most cancer types, indicating their potential to inhibit pro-oncogenic effects mediated by NUSAP1  and MCF-7 (BRCA) cell lines. The efficiency of NUSAP1 knockdown was confirmed by Western blot -2 in inducing T cell exhaustion, establishing a link between cell proliferation and the regulation of immune cell function Analysis of public databases and immunohistochemistry (IHC) results confirmed the high expression of NUSAP1 in tumor tissues across various cancer types. This elevated mRNA level was primarily attributed to the upregulation of two protein-encoding transcripts, indicating their potential as targets for NUSAP1 expression level and prognosis in 26 cancer types. High NUSAP1 expression was identified as a risk factor in tumorigenesis and progression, especially in four types of kidney cancer , as well as LGG, LIHC, LUAD, PAAD, PCPG, PRAD, and SARC. However, NUSAP1 expression showed a positive correlation with a favorable prognosis in CESC, COAD, GBM, HNSC, LUSC, STAD, TGCT, and THYM, indicating a protective role of NUSAP1 in the progression of these cancer types. This finding is also supported by published evidence In the analysis of prognostic predictive power using OS, DSS, DFI, and PFI, we observed a significant association between NUSAP1 expression level and clinical features in these cancer types. Consistent with the survival analysis results, patients with high NUSAP1 expression in HNSC and STAD exhibited fewer lymph node and distant metastases, as well as lower TNM stage. On the other hand, kidney cancer and LUAD patients with high NUSAP1 are more prone to metastasis and disease progression. The results from GESA and in vitro cell experiments further support this conclusion  and cytosolic Phospholipase A2 (cPLA2) and have shown high efficacy in inhibiting tumor growth Our previous findings primarily focus on investigating the mechanistic role of NUSAP1 in regulating cell cycle, especially during mitosis. We have demonstrated that NUSAP1 functions as a microtubule spindle stabilizer and an essential regulator of chromosome oscillation during metaphase. NUSAP1 stabilizes mitotic spindle by negatively regulating Mitotic Centromere-Associated Kinesin (MCAK), a microtubule depolymerizer, through its regulation of both the localization and depolymerization activity of MCAK NUSAP1 exhibits significant upregulation in most cancer tissues compared to normal tissues, with predominant expression in malignant and immune cells, particularly proliferative T cells. NUSAP1 appears to play a role in promoting cell proliferation and EMT in various cancer types, excluding CESC, HNSC, and STAD. Notably, the expression level of NUSAP1 holds substantial promise as a valuable biomarker for predicting prognosis and assessing the effectiveness of immunotherapy in human cancers. However, further exploration and verification through additional basic experiments and clinical trials are necessary to elucidate the precise molecular mechanism underlying NUSAP1-mediated functions in tumorigenesis and immunotherapy. These future endeavors will enhance our understanding of NUSAP1's role and its potential as a therapeutic target in cancer treatment.In conclusion, our study reveals that Supplementary figures.Click here for additional data file.Supplementary tables.Click here for additional data file.


This Special Issue (SI), titled “Recent Advances in Breast Cancer Research”, covers 12 research articles and 1 communication in the field of breast cancer (BC) research. It includes publications reporting the results of cell biological, animal, and human studies.BC is the second most common cancer in females, with skin cancer being the most prevalent cancer. BC accounts for about 30% or 1 in 3) of new female cancers each year  in 3 of ,3, and 6BC exhibits seven molecular BC subtypes with varying characteristic morphologies, treatment strategies, and future outcomes ,5. PatieThe main BC treatment strategies are surgery and radiation-based treatment. Typical BC therapies include chemotherapy, immunotherapy, hormone therapy, and drug-targeted treatment strategies . HoweverThis SI covers several human studies (patients and specimens derived from human tissues) that used modern molecular biological technologies in BC research ,10,11,12In addition, this SI includes seven cell culture studies ,17,18,19In total, this SI comprises 12 research articles ,17,18,19Fischer et al.  investigA further article reports the results of a retrospective histological analysis of 113 cases of male BC, focusing on sTILs and programmed cell death ligand-1 (PD-L1) expression . The autSokolenko et al.  investigZaib et al.  investigA further human study published as a communication focused on gene expression profiling of fibro-epithelial lesions (FELs) in the breast . The autMoreover, this SI covers several in vitro studies that investigated different human cell types ,17,18,19Two studies focused on BC cells exposed to simulated microgravity conditions using an RPM, which is a device designed to create conditions of weightlessness on Earth ,14. KnowWise et al.  analyzedERK1, AKT1, MAPK14, EGFR, CTNNA1, CTNNB1, ITGB1, COL4A5, ACTB, and TUBB genes of MCSs were differentially regulated in both cell lines. Bioinformatic analyses revealed a positive association between the real metastatic microtumor environment and MCSs regarding EGF/MAP signaling, focal adhesion, cytoskeleton, and the ECM, depending on the BC type. This long-term investigation improved pre-existing knowledge of tumor spheroid formation and growth [Another microgravity experiment studied MCF-7 and MDA-MB-231 BC cells for 14 days using an RPM [GRHL2) gene in luminal and basal BC [GRHL2 gene silencing performed via a mouse model revealed a decrease in primary tumor growth and reduced the number and size of lung colonies. Altogether, GRHL2 influences growth and motility. It is negatively associated with patient survival and growth suppression.The third cell culture study applied different types of BC cells and reported distinct roles for the Grainyhead-like 2  create a gene expression signature that specified the therapeutic response of ERβ1-expressing and ERα-positive BC cells to 4-hydroxytamoxifen and ATRA therapy [Meligova et al.  conducte therapy .Moreover, a BC cell study showed that NUF2 promotes BC development and, thus, serves as a new tumor stem cell indicator . The finPiasna-Słupecka et al.  found thCCL2’s role in mediating stromal interactions [CCL2 in the mammary glands were analyzed for global gene expression via RNAseq, showing upregulation of cancer-associated gene pathways. The CCL2-overexpressing mice showed enhanced macrophage infiltration and tumorigenesis [A combined cell culture and animal study (mice) investigated ractions . THP-1-digenesis .Taken together, these 13 publications demonstrate novel findings in the field of BC research. The authors investigated several genes and molecular pathways, increasing our understanding of BC to aid improved diagnosis and the development of novel therapies. Studies that applied modern molecular biological approaches and bioinformatic analyses were published in this SI.I wish to thank all of the authors who contributed to this SI. I am convinced that application of modern molecular biological technologies, together with a personalized medicine, will enable prevention and diagnosis of and new therapies for BC. Currently, many investigations are applying OMICS technologies and bioinformatics to identify new proteins that may serve as new mortality-decreasing drug targets or detect novel biomarkers that aid improved diagnosis of BC.


TMEM150A) in GBM. Data on patients with GBM were collected from The Cancer Genome Atlas and Xena databases. The objective was to identify the expression levels of TMEM150A in patients with GBM, and evaluate its diagnostic and prognostic values, accomplished using the receiver operating characteristic and survival analyses. On a cellular level, Cell Counting Kit-8, Wound healing, and Transwell experiments were performed to gauge the impact of TMEM150A on cell growth and migration. The study further investigated the correlation between TMEM150A expression and immune status, along with ribonucleic acid (RNA) modifications in GBM. The findings demonstrated TMEM150A overexpression in the cancerous tissues of patients with GBM, with an area under the curve value of 0.95. TMEM150A overexpression was significantly correlated with poor prognostic indicators. TMEM150A overexpression and isocitrate dehydrogenase (IDH) mutation status were predictive of poor survival time among patients with GBM. In vitro experiments indicated that suppressing TMEM150A expression could inhibit GBM cell proliferation, migration, and invasion. Moreover, TMEM150A overexpression was associated with stromal, immune, and estimate scores, immune cells (such as the T helper (Th) 17 cells, Th2 cells, and regulatory T cells), cell markers, and RNA modifications. Therefore, TMEM150A overexpression might serve as a promising biomarker for predicting poor prognosis in patients with GBM. Inhibiting TMEM150A expression holds the potential for improving the survival time of patients with GBM.Transmembrane proteins have exhibited a significant correlation with glioblastoma multiforme (GBM). The current study elucidates the roles of transmembrane protein 150A ( CLCF1) overexpression in GBM tissues, which was associated with an unfavourable prognosis. Inhibiting CLCF1 expression significantly reduced cell proliferation and migration, induced apoptosis, and prompted cell cycle arrest in GBM [Glioblastoma multiforme (GBM) is a highly malignant astrocytoma with limited treatment options. Currently, the preferred approaches for managing GBM involve surgical resection of tumour tissues followed by radiotherapy and chemotherapy. However, the prognosis of patients with GBM patients is significantly poor, with less than 6% of patients surviving beyond 5 years . Improvit in GBM . These fTMEM229A) is significantly underexpressed, and this underexpression is associated with poor prognosis in patients with cancer. Conversely, TMEM229A overexpression can inhibit NSCLC cell proliferation, migration, and invasion while promoting E-cadherin overexpression and N-cadherin and matrix metalloproteinase 2 underexpression [TMEM168 is overexpressed in GBM and is associated with shorter survival in patients with GBM. Inhibiting TMEM168 expression can impede the viability of GBM cancer cells, induce cell cycle arrest, and enhance apoptosis, which are mechanisms associated with the obstruction of the WNT/β-catenin pathway [TMEM150A, plays a role in cell homeostasis by regulating cytokine secretion and transcription. Decreased TMEM150A expression could result in increased lipopolysaccharide (LPS)-induced cytokine secretion [TMEM150A in GBM progression, alongside assessing the relationship between TMEM150A and the immune microenvironment and RNA modifications to provide a new candidate molecule for treating patients with GBM.Transmembrane proteins serve as channels that control the entry and exit of various substances across cellular membranes. Several investigations have linked transmembrane proteins with cancer –8. For i pathway . Anotherecretion –12. For ecretion . In addiecretion . TherefoTMEM150A expression, clinicopathological features, and prognostic data of the patients with GBM were obtained from TCGA.TCGA stands as an open-access cancer database comprising transcriptional data from patients with cancer. In contrast, the Xena database comprises transcription data from normal tissues of patients. In this study, transcription data was obtained from five normal tissues and 166 cancer tissues of patients with GBM, within the confines of TCGA. In parallel, the Xena database yielded access to transcription data from 1152 normal tissues, sourced from the genome-tissue expression (GTEx) database. Furthermore, data pertaining to TMEM150A expression levels were analysed in normal and cancer tissues. Subsequently, the TMEM150A expression data was integrated with clinical data from patients with GBM, encompassing variables such as age, sex, tumour grade, and survival status. The clinical characteristics of the patient groups were assessed and patients were categorised based on median TMEM150A expression levels, comparing the differences between high- and low-TMEM150A expression groups.TMEM150A in cancerous and normal tissues obtained from patients with GBM. The area under the ROC curve was used as the evaluation index. Additionally, data on TMEM150A expression and prognosis of patients with GBM were merged to examine the association between high- and low-TMEM150A expression levels and overall survival (OS) time, disease-specific survival (DSS), and progression-free interval (PFI) among patients with GBM. The patient groups were categorised based on median TMEM150A expression levels.Receiver operating characteristic (ROC) analysis was used to determine the diagnostic significance of TMEM150A expression and survival time in various subgroups of patients with GBMAssociation between TMEM150A expression data was combined with clinical characteristics and prognostic information from patients with cancer. This investigation was undertaken to explore the relationship between TMEM150A expression levels and OS, DSS, and PFI of patients with GBM across subgroups based on age, sex, race, isocitrate dehydrogenase (IDH) status, and Karnofsky performance score (KPS). Patient groups were categorised based on median TMEM150A expression levels.TMEM150A expression level, and poor prognostic indicators in patients with GBM. Variables with a significance level of P<0.05 were further subjected to multivariate Cox regression analysis. Additionally, nomograms were used as a tool to evaluate the prognosis of patients with cancer [Univariate Cox regression analysis was performed to assess the correlation between sex, age (≤60 or >60 years), KPS (<80 or ≥80), IDH status, h cancer –16. ThusTMEM150A expression across various cancer tissues. This aimed to elucidate the relationship between TMEM150A expression and tumour purity, immune cells, and immune cell markers.The TIMER database, an online cancer immune database, facilitates the visualisation of the correlation between gene expression and cancer immune cells, along with cellular markers. In this study, the TIMER database was used to explore TMEM150A expression data and immune cell markers were extracted from these cancer tissues using the Perl programming language, and correlation analysis was performed to investigate the association between TMEM150A expression and the infiltration of various immune cells and specific immune markers. Patients with GBM were classified into two groups based on the median TMEM150A expression to further examine the relationship between TMEM150A expression and immune infiltration.The single-sample Gene Set Enrichment Analysis (GSEA) and ESTIMATE methods were used to analyse the tumour microenvironment within the cancerous tissues obtained from patients with GBM sourced from TCGA. TMEM150A expression and poor prognosis in patients with GBM.The GEPIA database comprised tissue samples from patients with cancer and healthy individuals obtained from TCGA and GTEx databases. This study used the GEPIA database to establish the correlation between TMEM150A, with a significance threshold set at P < 0.05.Using the CAMOIP database, the cancerous tissues obtained from patients with GBM in TCGA were subjected to GSEA . AdditioTMEM150A was specifically identified and the RM2TARGET database was used to identify its associated RNA modifications. Subsequently, using the TIMER database, the correlation between TMEM150A expression levels and RNA modifications was explored. This was corroborated through an examination of RNA sequencing data sourced from tumour tissues of patients with GBM in TCGA.The RM2TARGET database systematically collected relevant literature and publicly available RNA modification gene datasets, encompassing informative target gene associations and annotations such as m6A, m1A, m5C, and m7G modifications for human genes. From this repository, the human target gene TMEM150A levels in the control group and the group with inhibited TMEM150A expression were examined using standard reverse transcription-polymerase chain reaction (RT-PCR) and Western blotting [GBM U118 cells were cultured in Dulbecco’s Modified Eagle Medium with 10% foetal bovine serum. Following this, the cells were transfected within a six-well plate, and cell proteins and RNA were collected after 24 h. Subsequently, the blotting .TMEM150A expression was measured and statistically analysed at 24, 48, and 72 h.Ninety-six-well plates were arranged with cells in an optimal growth state. Following cell adhesion, a 10μL solution of CCK-8 was added, and the cells were incubated for 1 h to measure cell activity, denoting this time point as 0 h. The cell activity of the control group and the group with inhibited The U118 cell suspension was introduced into a six-well plate, and upon cell adhesion, a linear scratch was created across the cell monolayer using the tip of a 200 μL pipette. The subsequent step involved the removal of any cellular debris. Following this, the culture medium was supplemented, and micrographs were taken to document the state. Finally, the process of cellular migration in response to the scratch was closely monitored under a microscope.The lower compartment of the Transwell plate was filled with the culture medium, while the Transwell membranes were positioned in the upper compartment. A serum-free suspension of U118 cells was then prepared, and the Transwell apparatus was incubated at a controlled temperature to culture the cells under optimal conditions. Subsequently, the cell invasion capabilities were assessed and compared at distinct time intervals. Following this, the cells were fixed with an appropriate volume of formaldehyde. After thorough washing, staining and visualisation were performed.TMEM150A expression levels between normal and cancerous tissues. The t-test was used to determine the statistical significance of the growth and migration capabilities of two distinct U118 cell groups. The chi-square test was used to examine the relationship between TMEM150A levels and the clinical characteristics of cancer patients. Additionally, the diagnostic and prognostic capability of TMEM150A was explored using ROC and survival analyses. Spearman correlation analysis was performed to understand the relationship between TMEM150A, immune microenvironment, and RNA modifications. Statistical significance was set at P<0.05.The Wilcoxon signed-rank test was used to identify differences in TMEM150A was 0.95, indicating that TMEM150A overexpression serves as an effective diagnostic biomarker for GBM  in patients with GBM  status in patients with GBM  1 cells, natural killer (NK) cells, NK cells expressing cluster of differentiation (CD) 56 surface antigen in low density (NK CD56dim cells), cytotoxic cells, T cells, activated dendritic cells (aDCs), dendritic cells (DCs), eosinophils, interstitial DCs (iDCs), macrophages, neutrophils, memory T cells (Tems), Th17 cells, Th2 cells, and regulatory T cells (Tregs)  . Moreovee showed . Additio and DCs .TMEM150A overexpression was significantly correlated with immune cell markers, including signal transducer and activator of transcription (STAT) 5A, integrin alpha M chain (ITGAM), chemokine ligand 2 (CCL2), transforming growth factor beta 1 (TGFB1), interferon regulatory factor 5 (IRF5), forkhead box protein 3 gene (FOXP3), CD68, colony stimulating factor 1 receptor (CSF1R), STAT6, human leukocyte antigen (HLA)-class II histocompatibility antigen, DP(W2) beta chain (DPB1), GATA binding protein 3 (GATA3), HLA-class II DP alpha 1 (DPA1), CD163, STAT3, CD86, interleukin (IL)-10, HLA-class II histocompatibility antigen, DR alpha chain (DRA), CD3-epsilon CD-3E, integrin subunit alpha X (ITGAX), membrane spanning 4-domains A4A (MS4A4A), killer cell immunoglobulin like receptor, two immunoglobulin domains and long cytoplasmic tail 4 (KIR2DL4), hepatitis A virus cellular receptor 2 (HAVCR2), CD2, CD3-delta (CD3D), and cytotoxic T-lymphocyte-associated protein 4 (CTLA4)  . MoreoveTMEM150A, including alkB homolog (ALKBH) 5, METTL16, METTL14, Wilms tumour 1 associated protein (WTAP), adenosine deaminase, adenosine deaminase RNA specific B1, zinc finger CCHC-type containing 4, fat mass and obesity-associated protein, vir-like m6A methyltransferase associate, nucleolar protein 58, heterogeneous nuclear ribonucleoproteins A2/B1, insulin-like growth factor 2 mRNA-binding protein (IGF2BP) 1, YTH N6-methyladenosine RNA binding protein C1, METTL3, zinc finger CCCH-type containing 13, WD repeat domain 4, METTL5, METTL1, YTH N6-methyladenosine RNA binding protein 2, ALKBH1, IGF2BP3, THO complex subunit 4, heterogeneous nuclear ribonucleoproteins C1/C2 (HNRNPC), fibrillarin (FBL), TruB pseudouridine synthase family member 2 (TRUB2), and RNA binding motif protein X-linked (RBMX). TMEM150A expression levels were correlated with RBMX, TRUB2, FBL, HNRNPC, ALKBH5, and WTAP in TIMER and TCGA databases.The RM2Target database revealed several RNA modification factors that were associated with TMEM150A was associated with several key signalling pathways such as IL-17, tumour necrosis factor (TNF), nuclear factor-kappa B (NF-κB), nucleotide oligomerisation domain-like receptor, chemokine, Toll-like receptor, Th17 cell differentiation, cell cycle, B cell receptor, Janus kinase/STAT (JAK/STAT), cyclic adenosine monophosphate (cAMP), Th1 and Th2 cell differentiation, ferroptosis, deoxyribonucleotide replication, calcium, and T cell receptor pathways  expression inhibited GBM cell proliferation and tumour formation in nude mice. COPZ1 knockdown resulted in increased nuclear receptor coactivator 4, ferritin degradation, and elevated intracellular ferrous levels, resulting in ferroptosis [TMEM150A expression could delay U118 cell proliferation, migration, and invasion in GBM. Additionally, TMEM150A was strongly associated with IL-17, TNF, NF-κB, Toll-like receptor, cell cycle, JAK-STAT, cAMP, ferroptosis, and other pathways. However, our study did not investigate the relationship between TMEM150A and these mechanisms, which warrants further exploration in the future.It was well established that f cancer –29. For em cells . Similarroptosis . It was TMEM150A overexpression and the immune microenvironment in GBM. Our findings revealed that TMEM150A overexpression in GBM tissues was strongly correlated with immune, estimate, and stromal scores, and significantly correlated with tumour purity, Th1 cells, NK cells, NK CD56dim cells, cytotoxic cells, CD4+ T cells, T cells, aDCs, DCs, eosinophils, iDCs, macrophages, neutrophils, Tmems, Th17 cells, Th2 cells, and Tregs. Moreover, TMEM150A expression levels were correlated with immune cell markers such as STAT5A, ITGAM, CCL2, TGFB1, IRF5, FOXP3, CD68, CSF1R, STAT6, HLA-DPB1, GATA3, HLA-DPA1, CD163, STAT3, CD86, IL10, HLA-DRA, CD3-E, ITGAX, MS4A4A, KIR2DL4, HAVCR2, CD2, CD3-D, CTLA4, and others. Additionally, RNA modification genes, such as RBMX, HNRNPC, ALKBH5, and WTAP, play a crucial role in cancer biology [ALKBH5 expression in GSCs significantly down-regulated stem cell survival and invasion after irradiation and mediated the radioresistant properties of stem cells [ALKBH5 and ALKBH6 to bind to SOX2 and demethylate the SOX2 transcript and subsequent SOX2 up-regulation, thereby regulating tumour cell apoptosis, cell proliferation, and TMZ resistance [TMEM150A expression levels were significantly correlated with RNA modification genes, namely RBMX, TRUB2, FBL, HNRNPC, ALKBH5, and WTAP, suggesting that TMEM150A plays crucial biological roles in GBM progression.Diverse strategies exist for treating patients with cancer, and among these, immunotherapy has emerged as a crucial aspect of cancer treatment , 31. Thi biology –38. For em cells . Similarsistance . Our stuTMEM150A plays a crucial role in GBM and offers significant advantages concerning high reliability and large sample sizes in GBM data. However, moving forward, the verification of TMEM150A expression in GBM tissues through clinical sampling remains a crucial avenue to explore, thereby substantiating its potential clinical significance. Furthermore, the establishment of cell models designed to inhibit TMEM150A expression to investigate its roles and signalling mechanisms involved in GBM cell growth and migration. In summary, TMEM150A was overexpressed in GBM tissues and was significantly correlated with diagnosis, poor prognosis, immune status, and RNA modifications in GBM. Inhibition of TMEM150A expression could inhibit GBM cell proliferation, migration, and invasion. Thus, TMEM150A overexpression could be a potential biomarker for poor prognosis in patients with GBM.This study revealed that TMEM150A overexpression was associated with diagnosis, poor prognosis, immune status, and RNA modifications in GBM. Inhibiting TMEM150A expression could inhibit GBM cell proliferation, migration, and invasion. TMEM150A might serve as a biomarker of poor prognosis in patients with GBM.S1 FigNote: TMEM, transmembrane protein; OS, overall survival; DFS, disease-free survival; GBM, glioblastoma multiforme.(TIF)Click here for additional data file.S2 FigNote: TMEM, transmembrane protein; DSS, disease-specific survival; PFI, progression-free interval; GBM, glioblastoma multiforme.(TIF)Click here for additional data file.S3 FigNote: TMEM, transmembrane protein.(TIF)Click here for additional data file.