Objective: This study aimed to identify specific dysregulated genes with potential diagnostic and predictive values for JAK2V617F+ myelofibrosis.Methods: Two gene expression datasets of CD34+ hematopoietic stem and progenitor cells (HSPCs) from patients with JAK2V617F+ myeloproliferative neoplasm (MPN)  and healthy controls (HC) (n = 30) were acquired from the GEO (Gene Expression Omnibus) database. The differentially expressed genes (DEGs) were screened between each JAK2V617F+ MPN entity and HC. Subsequently, functional enrichment analyses, including Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Set Enrichment Analysis (GSEA), were conducted to decipher the important biological effects of DEGs. Protein–protein interaction (PPI) networks of the DEGs were constructed to identify hub genes and significant modules. Another two gene expression profiles of patients with JAK2V617F+ MPN  and HC (n = 6) from GEO were used as external validation datasets to prove the reliability of the identified signatures.Results: KEGG analysis revealed the upregulated genes in three JAK2V617F+ MPN entities compared with HC were essentially enriched in inflammatory pathways and immune response signaling pathways, and the number of these pathways enriched in PMF was obviously more than that in PV and ET. Following the PPI analysis, 10 genes primarily related to inflammation and immune response were found upregulated in different JAK2V617F+ MPN entities. In addition, Reactome enrichment analysis indicated that interferon signaling pathways were enriched specifically in PMF but not in PV or ET. Furthermore, several interferon (IFN)-stimulated genes were identified to be uniquely upregulated in JAK2V617F+ PMF. The external datasets validated the upregulation of four interferon-related genes  in JAK2V617F+ myelofibrosis. The receiver operating characteristic (ROC) curves indicate that the four genes have high area under the ROC curve (AUC) values when distinguishing JAK2V617F+ myelofibrosis from PV or ET.Conclusion: Four interferon-stimulated genes  exclusively upregulated in JAK2V617F+ myelofibrosis might have the potential to be the auxiliary molecular diagnostic and predictive indicators of myelofibrosis. JAK2V617F, which could be observed in the great majority of patients with PV and most patients with ET or PMF , essential thrombocythemia (ET), and primary myelofibrosis (PMF) are a range of heterogeneous hematopoietic diseases classified as Philadelphia chromosome-negative myeloproliferative neoplasms (Ph- MPNs), which also include chronic neutrophilic leukemia (CNL), chronic eosinophilic leukemia not otherwise specified (CEL-NOS), and unclassifiable MPN according to 2016 WHO classification . PV, ET,T or PMF . Althougytopenia . Among tytopenia . Howeverytopenia .JAK2V617F acquired by the hematopoietic stem cell (HSC) plays an essential role in MPN pathogenesis  has been used as first-line treatment of PMF; however, the disease course was not improved . JAK2 infibrosis . Unfortufibrosis . Also, t+ HSPCs from patients with JAK2V617F+ MPN  and healthy controls (HC) were analyzed to identify important genes specifically dysregulated in JAK2V617F+ PMF. Another two external datasets [GSE174060 , JAK2V617F+ ET (n = 17), JAK2V617F+ PMF (n = 23), and HC (n = 30) were selected for analysis. The gene expression profile from the peripheral blood/bone marrow CD34+ cells was annotated by the data of the GPL13667 platform.Two microarray datasets [GSE103237  and GSE5JAK2V617F+ PV (n = 8), JAK2V617F+ ET (n = 2), JAK2V617F+ SMF , JAK2V617F+ PMF (n = 10), and HC (n = 6), which came from GSE174060  and HC. The adjusted p-value less than 0.05 and |log2 fold change (logFC)| more than 1 were regarded as significant DEGs for downstream analysis. Heatmaps were performed with the pheatmap package  (The clusterProfiler package (version 4.2.0)  was util 1.14.1) .p-value less than 0.05 was regarded as statistically significant.GSEA software was utilized to run GSEA, using reference gene sets from the Molecular Signatures Database . The expProtein–protein interaction (PPI) analysis of DEGs was constructed based on the STRING database . Cytoscan = 6), JAK2V617F+ PV (n = 8), JAK2V617F+ ET (n = 2), JAK2V617F+ SMF (n = 3), and JAK2V617F+ PMF (n = 10), were selected for external validation. The gene expression matrix of CD34+ HSPCs from bone marrow/peripheral blood was annotated by the GPL17586 platform data. The pipeline of data processing is similar to the methods described above. The expression levels of DEGs between patients with MPN and HC were compared with Wilcoxon rank-sum test from the ggpubr package (version 0.4.0)  was used to calculate the value of AUC and draw the ROC curve.Another two datasets [GSE174060  and GSE1n 0.4.0) . The p vp value less than 0.05 at two-sided was regarded as statistically significant. “*” denotes “p < 0.05”, “**” denotes “p < 0.01”, “***” denotes “p < 0.001”, “****” denotes “p < 0.0001”, and “ns” denotes “not significant”.R software and GraphPad Prism were utilized for data processing and statistical analysis. The ggpubr package in R software was applied to draw boxplots and perform statistical analysis. The Wilcoxon rank-sum test was applied to compare the difference in expression levels between distinct groups. The n = 30), JAK2V617F+ PV (n = 26), JAK2V617F+ ET (n = 17), and JAK2V617F+ PMF (n = 23), were collected from two datasets [GSE103237  and HC (n = 30) was processed to discover the differentially expressed genes (DEGs). A total of 265 DEGs were identified from the matrix, including 171 upregulated genes and 94 downregulated genes in patients with JAK2V617F+ PV compared to HC (JAK2V617F+ ET (n = 17) and JAK2V617F+ PMF (n = 23). A total of 213 upregulated DEGs and 112 downregulated DEGs were found in patients with JAK2V617F+ ET relative to HC  exclusively dysregulated in PMF  were shown  in three JAK2V617F+ MPN subtypes, the STRING database was utilized to conduct the analysis. The results indicated that, in total, 405 edges (protein interaction pairs) and 78 nodes (encoded proteins) were included. Ten hub genes of overlapping upregulated genes in three JAK2V617F+ MPN subtypes were obtained by the cytoHubba plugin from the PPI network , and S100 family genes (S100A8/9/12), were related to inflammatory pathways and immune response signaling pathways  in three JAK2V617F+ MPN subtypes were significantly higher than those in HC , JAK2V617F+ ET (n = 2), JAK2V617F+ SMF (n = 3), JAK2V617F+ PMF (n = 10), and HC (n = 6) included. Due to the paucity of CD34+ samples in patients with JAK2V617F+ ET, we integrated the samples of JAK2V617F+ PV and JAK2V617F+ ET into one group named JAK2V617F+ PV/ET, reflecting the chronic and indolent stage of MPN. The expression levels of these inflammation- and immune-related genes  were significantly higher in both chronic and aggressive fibrotic phases of JAK2V617F+ MPN than those in HC  (n = 21) in PMF  uniquely in PMF to perform the Reactome enrichment analysis, interferon signaling pathways were also enriched significantly, such as interferon signaling, interferon-alpha/beta signaling, and interferon-gamma signaling  , most of) in PMF . InteresPV or ET . In addiignaling . FurtherPV or ET , corrobo7F+ PMF .Therefore, the upregulation of interferon signaling pathways might participate in the pathogenesis of myelofibrosis.n = 182) exclusively in JAK2V617F+ PMF was constructed with 179 nodes (encoded proteins) and 322 edges (protein interaction pairs). Through the PPI network, the top 10 hub genes were discovered, namely, MX1, IFIT1, IFIT3, OAS1, RSAD2, XAF1, MX2, ISG15, IFI6, and IRF9, most of which were strongly associated with interferon-gamma signaling  were upregulated in JAK2V617F+ PMF compared to not only HC but also JAK2V617F+ PV and ET  with increased expression levels not only in JAK2V617F+ PMF but also in JAK2V617F+ SMF in comparison with HC and PV/ET  for patients with myelofibrosis, the ROC curves and AUC were performed. In the ROC curves here, the true positive rate means the percentage of that a JAK2V617F+ myelofibrosis patient is correctly predicted as JAK2V617F+ myelofibrosis, while the false positive rate is the proportion of that a JAK2V617F+ PV or ET individual is classified falsely as JAK2V617F+ myelofibrosis. The AUC represents the area under the ROC curve, indicating the accuracy and reliability of diagnostic prediction. The results showed high AUC values of the four genes  when distinguishing JAK2V617F+ myelofibrosis from JAK2V617F+ PV or ET , especially OAS1, might possess the potential to be novel auxiliary diagnostic and predictive indicators of myelofibrosis, but further research is still necessary in the future.To investigate the differential diagnostic ability of the four genes  to provide new information on pathogenesis and identify novel indicators for diagnosis and prediction of myelofibrosis.Although abundant research about Ph- MPNs has been performed, the mechanisms of disease onset and progression in myelofibrosis are still not fully understood. Considering there are significantly diverse manifestations and prognoses between the chronic stage and aggressive stage of MPN, it is urgently needed to identify some reliable biomarkers to predict myelofibrosis as early as possible, which could also contribute to early intervention and treatment. Here, we precisely analyzed the gene expression profiles in different subtypes of JAK2V617F in HSPCs, leading to the cytokine-independent activation of JAK-STAT signaling, may occur even during early childhood and in utero, and there is a very long asymptomatic period , which were undetected in previously published studies, were also identified in distinct JAK2V617F+ MPN subtypes in comparison with HC. Additionally, among three subtypes, JAK2V617F+ PMF has more numbers of inflammation-related upregulated pathways and genes, suggesting that the more prominent inflammatory condition is a pronounced feature of myelofibrosis.Inflammation could be an important determinant that promotes the development and progression of MPN. Recent studies found that the acquisition of c period . Chronicc period . Here, wfindings . Some inOAS1, IFITM3, GBP1, and GBP2) that were upregulated uniquely in myelofibrosis. These genes belong to interferon-stimulated genes, related closely to interferon signaling (OAS1 and IFI44) were found to be positively correlated with progressive lung fibrosis in patients with systemic sclerosis (SSc)–related interstitial lung disease (ILD) -biased hematopoiesis  exclusively upregulated in myelofibrosis might not only provide important novel clues to the MPN field but also offer special insights into the effects of IFN signaling on the pathogenesis of myelofibrosis.Furthermore, we identified four potentially important genes  . Additios in AML . Howeveropoiesis . There w-1 cells , which w-1 cells . These rJAK2V617F, other somatic mutations, disease duration, and treatment, which remains to be further investigated.Inevitably, this study has limitations. Though quite large numbers of samples and repeated validations from multiple datasets were applied to minimalize the individual variation, this study was limited by the lack of detailed clinical information in these GEO datasets such as variant allele frequency (VAF) of + HSPCs across the different JAK2V617F+ MPN subtypes. The gene expression signatures in JAK2V617F+ PMF were to a large extent distinct from those in JAK2V617F+ PV or ET, although there were also similar features among them. The upregulation of inflammation- and immune-related signature genes and especially IFN signaling might be involved in the pathogenesis and progression of myelofibrosis. Additionally, the four genes  we identified in this study might have the potential to be auxiliary diagnostic and predictive indicators of myelofibrosis, but further investigations are still necessary in the future.In summary, our study precisely analyzed the gene expression profiles of CD34


The aim of the current study is to further examine the effects of endogenous and exogenous H2S on UII-induced cardiovascular effects by using an integrated physiology approach. We also use cell culture and molecular biological techniques to explore the inhibitory role of H2S on UII-induced cardiovascular effects. In this study, we found that cystathionine-β-synthase (CBS), the main H2S synthesizing enzyme in CNS, was expressed in neuronal cells of the rostral ventrolateral medulla (RVLM) area. Cellular distribution of CBS and urotensin II receptor (UT) in SH-SY5Y cells that are confirmed as glutamatergic were identified by immunofluorescent and Western blots assay. In Sprague–Dawley rats, administration of UII into the RVLM resulted in an increase in mean arterial pressure (MAP), heart rate (HR), ROS production, nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activity, and phosphorylation of p47phox, extracellular signal-regulated protein kinase (ERK)1/2 and p38MAPK, but not stress-activated protein kinase/Jun N-terminal kinase (SAPK/JNK). These effects of UII were attenuated by application into the RVLM of endogenous  or exogenous (NaHS) H2S. These results were confirmed in SH-SY5Y cells. UII-induced cardiovascular effects were also significantly abolished by pretreatment with microinjection of Tempol, Apocynin, SB203580, or PD98059 into the RVLM. Preincubated SH-SY5Y cells with Apocynin before administration of UII followed by Western blots assay showed that ROS is in the upstream of p38MAPK/ERK1/2. Gao activation assay in SH-SY5Y cells suggested that H2S may exert an inhibitory role on UII-induced cardiovascular effects by inhibiting the activity of Gαo. These results suggest that both endogenous and exogenous H2S attenuate UII-induced cardiovascular effects via Gαo-ROS-p38MAPK/ERK1/2 pathway.Urotensin II (UII) could increase blood pressure and heart rate via increased central reactive oxygen species (ROS) levels. We reported previously that hydrogen sulfide (H Urotensin II (UII), a cyclic neuropeptide, was originally found in teleost fish and later characterized in mammals . It exer2−, activated ERK1/2 and p38MAPK. Thus, decreased ROS generation may be an important target of antihypertension therapy.Oxidative stress is a significant feature of hypertension . A growi2S), a gasotransmitter, was reported to have various physiological effects on the cardiovascular system, nervous system, and metabolism, such as antioxygen, antihypertensive, vascular relaxation, and maintaining blood pressure homeostasis [2S also impacts transcriptional factors such as NF-Kappa B and modulates T cell inflammation and immunosuppression [2S is endogenously synthesized by cystathionine-β-synthase (CBS), cystathionine-γ-lyase (CSE), and 3-mercaptopyruvate sulfurtransferase (3-MST), with 3-MST and CBS expressed in the CNS, while the expression of CBS is predominant. Chronic intracerebroventricular infusion of NaHS, the donor of H2S, can alleviate angiotensin II-induced hypertension [2S could reduce MAP and HR and the level of ROS in the RVLM of SHR rats [2S can decrease ROS generation and NADPH oxidase activity via inhibition of ERK1/2. However, the mechanisms underlying the central cardiovascular effects of H2S remain largely unknown.Hydrogen sulfide  [Based on the above research, UII exerts its pressor effect through coupling to the UT receptor, a G-protein coupled receptor. In the pathological conditions of hypertension, G-protein coupled receptor involves cross talk between various signaling pathways, including mitogen-activated protein kinases (MAPK) . It has (ERK1/2) . On the (ERK1/2) .2S may exert an antihypertensive effect induced by UII by decreasing ROS production. Furthermore, we identified that the MAPK signaling pathway and Gαi/o protein might also be involved in the mechanisms of the antihypertensive effect of H2S. Our study may lead to a potential novel therapeutic strategy for hypertension.In the present study, we tested the hypothesis that HAdult male Sprague–Dawley rats weighing 280–310 g were purchased from Shanghai SLAC laboratory animal company. All experiments were approved by the animal experimental Ethics Committee of Fudan University (20210302-038).2) at 37 °C.SH-SY5Y cells were cultured with 10% fetal bovine serum (FBS) and 1% penicillin–streptomycin in Dulbecco’s Modified Eagle’s Medium (DMEM) under 95% air and 5% carbon dioxide  and urethane (700 mg/kg) and perfused transcardially with saline (150 mL) followed by 4% paraformaldehyde (250 mL) in 0.1 M sodium phosphate buffer . Brains were rapidly removed and post-fixed in the same fixative at 4 °C overnight, followed by transfer into 20% and 30% sucrose sequentially in 0.1 M PB for at least 3 days. According to Paxinos and Watson’s atlas, coronal medullary sections at 30 μm thick were cut with a microtome  1.5–1.7 mm rostral to the obex. For cells, 4% paraformaldehyde was performed for 30 min after the cells were treated with UII or NaHS. After washing in 0.01 M phosphate-buffered saline  and absorption in 2% BSA, and 0.2% Triton X-100 in PBS, the sections or the cells were incubated with primary antibodies at 4 °C overnight. Anti-MAP-2 and anti-CBS antibodies were purchased from Abcam . Anti-glutamate antibody was purchased from Sigma-Aldrich. Sections or the cells were then washed in PBS and incubated with fluorescent secondary antibodies for 2 h. The sections or the cells were observed using confocal microscopy .After the rats were anesthetized, a hole  was made in the skull. A stainless steel guide cannula  and a stainless steel injector, which was introduced through the guide cannula, were inserted into the hole. A total of 10 μL was delivered over 10 min into the ICV.Animals were anesthetized with a mixture of chloralose (35 mg/kg) and urethane (700 mg/kg) and intubated to facilitate ventilation. Blood pressure and heart rate were recorded by inserting a cannula into the left femoral artery. Body temperature was maintained with a temperature-controlled table between 37 °C and 37.5 °C. Rats were then mounted in a stereotaxic frame, and microinjection was carried out with a micropipette tip . A total of 0.1 μL was delivered over 1 min into the RVLM . The injection sites were confirmed by histological examination. The test agents, including L-cysteine (a CBS substrate), S-adenosyl-l-methionine , HA, Tempol, Apocynin, SB203580, PD98059, and NaHS, were purchased from Sigma Aldrich . UII was synthesized in GL biochemistry. BIM23127 was purchased from Tocris . Microinjection of artificial cerebral spinal fluid (aCSF) was used as vehicle control and volume.2− measurement. O2− production was expressed as the mean light unit per mg protein.As described previously , superoxSuperoxide production in SH-SY5Y cells was detected using ROS fluorescent probe, dihydroethidium . Cells were treated with various agents, followed by incubation with 2 μmol/L DHE for 30 min. ROS production was analyzed by measuring the absorbance at 480 nm and 590 nm.2− production in the incubation medium was measured.In the ventrolateral medulla, NADPH oxidase activity was analyzed by a luminescence assay. The assay was performed in PBS buffer containing EGTA (0.01 M/L) and lucigenin (5 μmol/L) as the electron acceptor and NADPH (100 mM/L) as the substrate. Background counts were recorded after dark adaptation, followed by the addition of a tissue homogenate (1 μL protein sample). The chemiluminescence value was recorded at 1 min intervals for 30 min. After the addition of NADPH, Ophox antibody was purchased from Sigma-Aldrich . Anti-total or phosphorylated ERK1/2, p38MAPK, or JNK and phosphorylated p-p47phox antibodies were purchased from Cell Signaling . Protein bands were visualized by ECL . The intensity (area × density) of the detected protein on Western blots was quantified by Image J software and was expressed as the ratio to the total protein amount.As described previously, tissue homogenates or cell lysates were subjected to Western blot analysis. BCA protein assay reagent  was used to assay protein content. Protein was resolved by SDS-PAGE in equal amounts and transferred to the PVDF membrane. Blots were incubated with primary antibody followed by horseradish peroxidase-conjugated secondary antibody. Anti-CBS antibodies were purchased from Abcam . Anti-UT antibody was purchased from Santa Cruz Biotechnology . Anti-total p472 incubator. Cells were treated with different concentrations of UII and NaHS at different times. Then 10 μL CCK-8 solution was added to each well of plates then incubated for 2 h at 37 °C, 5% CO2. The cell viability was analyzed by measuring the absorbance at 450 nm. Cell Counting Kit-8  was used to determine cell viability. The SH-SY5Y cells were cultured in 96-well plates at 37 °C in a 5% COo was determined using Gαo Activation Assay Kit  according to the manufacturer’s instructions.The activity of Gat-test for parametric data. Statistical significance was assumed when p-values below 0.05.Data are expressed as mean ± SEM. Differences between groups were compared using one-way ANOVA associated with Tukey-Kramer post hoc comparison or the unpaired Student’s 2S synthesizing enzymes and UT, we performed an immunofluorescent stain coupled with laser confocal microscopy on the RVLM area of SD rats and SH-SY5Y cells. The results confirmed that CBS, the main H2S synthesizing enzyme in CNS, was expressed in neuronal cells of the RVLM area  into the RVLM of SD rats. The results showed that the MAP and HR of SD rats were increased within 5 min, while coadministration of NaHS (400 pmol/0.1 μL), an exogenous Hd by UII . Further2S into the RVLM of SHR rats decreased the level of superoxide anion (O2−) and NADPH oxidase activity. To further identify the underlying mechanism of the inhibitory effect of H2S on UII-induced cardiovascular effect, ROS production and NADPH oxidase activity were detected.We reported previously  that mic2−) production in the RVLM was significantly enhanced upon UII administration, and this effect of UII was blocked by pretreatment with NaHS (400 pmol/0.1 μL) into the RVLM . The results revealed that the superoxide anions  into the RVLM C. PhosphVLM area D or SH-SVLM area E with UITo further confirm the effects of ROS on UII-induced hypertension, we performed the microinjection into the RVLM area of SD rats. Microinjection of UII (0.5 nmol/0.1 μL) into the RVLM evoked an appreciable increase in MAP and HR that lasted for 10 min. This pressor response was significantly inhibited by pretreatment with microinjection of Tempol  with various doses of NaHS  and SAM  pretreatment can also significantly inhibit the increase in ROS level caused by UII, while pretreatment with HA  had no effect on ROS production  into the RVLM resulted in the activation of p38MAPK or ERK1/2 but not SAPK/JNK. The UII–induced p38MAPK or ERK1/2 phosphorylation was significantly antagonized by coadministration of NaHS  into the RVLM can significantly attenuate the increase in MAP and HR induced by UII  The metabolic system of H2S was present in the RVLM of SD rat and SH-SY5Y cells. Pretreatment with microinjection of H2S into the RVLM significantly attenuated UII-induced MAP and HR rise. (2) H2S decreased the UII-induced MAP and HR by inhibiting the activity of NADPH oxidase, phosphorylation of its subunit, p47phox, and ROS production. (3) Decreased phosphorylation of p38MAPK and ERK1/2 plays an active role in the inhibitory role of H2S on UII-induced cardiovascular effects, and p38MAPK/ERK1/2 pathway is in the downstream of ROS. (4) The activity of Gαo was also involved in the inhibitory role of H2S on UII-induced cardiovascular effects  for 10 min  signaling pathway, are associated with ROS actions in the RVLM. The activities of MAPK  are strengthened by angiotensin II through an AT1R-dependent ROS production in CNS [2O2-induced apoptotic cardiomyocytes, UII promotes the phosphorylation of ERK1/2 and increases H2S production via upregulating CSE levels [2S. In the present study, the detection of the phosphorylation of the MAPK family in the RVLM revealed that UII potentiated the activation of p38MAPK and ERK1/2 but not JNK. Pretreated with H2S significantly suppressed UII-induced enhanced phosphorylation of p38MAPK and ERK1/2. This result was further confirmed by microinjection of selective p38MAPK or ERK1/2 inhibitor into RVLM. Similarly, we also found in SH-SY5Y cells that H2S inhibits UII-induced activation of p38MAPK and ERK1/2  significantly prevented the UII-induced cardiovascular effects. Our results further indicated that UII significantly increased the activity of Gαo, while pretreated with H2S attenuated the activity of Gαo. The protein expression of Gαo remains unchanged in each group (2S may exert an inhibitory role in UII-induced cardiovascular effects via Gαo-ROS-p38MAPK/ERK1/2 pathway, and Gαo might be the potential target of H2S.As we all know, Hch group . These o2S attenuate UII-induced cardiovascular effects through Gαo-ROS-p38MAPK/ERK1/2 pathway. This may provide a novel approach to counteract sympathoexcitation in cardiovascular disorders that are associated with enhanced brain UII. Our study revealed the important value of H2S as a new potential therapeutic pathway against hypertension.In summary, the present study indicated that both endogenous and exogenous H


RPL and RPS) genes in the previously established TOR overexpressing transgenic lines of rice  and of Arabidopsis thaliana . The mRNA levels of RP genes from this study were compared with those previously available in transcriptomic datasets on the expression of RPs in relation to TOR inhibitor and in the TOR-RNAi lines of Arabidopsis thaliana. We further analyzed TOR activity, i.e., S6K1 phosphorylation in SALK lines of Arabidopsis with mutation in rpl6, rpl18, rpl23, rpl24 and rps28C, where the rpl18 mutant showed inactivation of S6K1 phosphorylation. We also predicted similar putative Ser/Thr phosphorylation sites for ribosomal S6 kinases (RSKs) in the RPs of Oryza sativa ssp. indica and Arabidopsis thaliana. The findings of this study indicate that the TOR pathway is possibly interlinked in a cyclic manner via the phosphorylation of S6K1 as a modulatory step for the regulation of RP function to switch ‘on’/‘off’ the translational regulation for balanced plant growth.The target of rapamycin (TOR) protein phosphorylates its downstream effector p70kDa ribosomal protein S6 kinases (S6K1) for ribosome biogenesis and translation initiation in eukaryotes. However, the molecular mechanism of TOR-S6K1-ribosomal protein (RP) signaling is not well understood in plants. In the present study, we report the transcriptional upregulation of ribosomal protein large and small subunit ( The TOR is a central regulator of ribosome biogenesis and protein synthesis in eukaryotes ,2. SeverRP genes are also reported as 5′TOP mRNAs, which are regulated by either TOR-LARP1 or TOR-S6K1 signaling [TOR also plays a crucial role in the transcription of nuclear-encoded mRNAs coding for plastidic RPs in Arabidopsis [TOR-RNAi lines of Arabidopsis resulted in a coordinated decrease in transcription and translation of plastidic ribosomal protein genes, whereas the genes coding for cytosolic ribosomal proteins were interestingly upregulated [Saccharomyces cerevisiae, the mechanism of TOR-mediated regulated RP genes is well studied. The TOR controls the Forkhead transcription factor (FHL1) along with its co-activator, IFH1, and a repressor, CRF1, and triggers the transcription of RP genes under nutrient availability and nutrient-deprived conditions in yeast [TOR in the homologous and heterologous systems in Arabidopsis and rice, respectively, on the changes in the expression levels of RP genes. Multisite phosphorylation fully activates S6K1, which further phosphorylates several targets including ribosomal protein S6 in 40S ribosome. After the assembly of 40S with 60 S converts into an 80S ribosome, S6K is dephosphorylated and dissociated from the complex allowing the ribosome to proceed for the peptide elongation step . Global ignaling . Howeverbidopsis . The inaegulated . In Saccin yeast ,21. DespArabidopsis thaliana TOR (AtTOR) exhibited enhanced growth, increased seed yield, leaf size and improved stress tolerance [TOR overexpressing lines of Oryza sativa ssp. indica var. BPT-5204 and Arabidopsis thaliana for analyzing the mRNA levels of ribosomal proteins encoding genes. The lines represented with TR are TOR overexpressing lines of rice and the lines represented with ATR are TOR overexpressing lines of Arabidopsis thaliana [RP genes, the results from a Western blot analysis in this study also show that TOR-mediated S6K1 phosphorylation is affected by a loss of RP function in Arabidopsis.We have also previously reported that rice and Arabidopsis plants ectopically overexpressing olerance ,23,24,25RP genes transcription has been demonstrated previously in Arabidopsis [TOR-overexpressing crop-plants. We, therefore, performed an expression analysis of RPL and RPS genes in two high AtTOR-expressing rice lines, TR-2.24 and TR-15.1, and two Arabidopsis lines, ATR-1.4.27 and ATR-3.7.32 [AtTOR on the regulation of RP transcription in both of the species. In the present study, the paralogs of RPL and RPS genes were selected based on their expression levels in various developmental stages of shoots and roots of rice and Arabidopsis plants. The transcript levels of the RP genes were significantly upregulated in the rice transgenic lines. The genes RPL4, RPL14, RPL18A, RPL19.3, RPL36.2, RPL51, RPS3A, RPS6, RPS6A, RPS25A and RPS30 display upregulation in the rice transgenic plants that expressed AtTOR ectopically  and Dobrenel et al. (2016) in TOR-RNAi lines of Arabidopsis  and in Arabidopsis (73 RP genes), AtTOR-OE lines TR-2.24, TR-15.1, ATR-1.4.27 and ATR-3.7.32, the transcript levels of the 28 overlapping RP genes were significantly upregulated by more than 2-fold  RPS6A/B proteins from ssp. japonica shared the highest similarity with Arabidopsis thaliana RPS6A/B proteins in their Ser/Thr phosphorylation sites in similar amino acid positions  family proteins are serine/threonine kinases that regulate cell growth and proliferation. The two subfamilies of RSKs, p90 RSK and p70 S6K, phosphorylate RPS6 in Ser/Thr residues for the modulation of ribosome biogenesis and protein translation ,28,29. Tositions . The OsRhttp://signal.salk.edu/tdna_FAQs.html accessed on 14 March 2019 (T-DNA insertions in the Arabidopsis mutants were detected by performing PCRs using the left border-specific primer (LB) and the corresponding gene specific right primer primer to identify homozygous or hemizygous lines and using the Left Primer + Right Primer combination for gene-specific amplification in each mutant following the protocol described at rch 2019 . rpl23aA mutant was observed in the third exon and the rpl6 (emb2394) mutant had the T-DNA insertion in the first intron of the RPL6 gene (At1g05190). The homozygous lines of the rpl23aA knockouts were shown earlier to have embryo lethality [rpl6 (emb2394) mutant lines displayed yellow–green cotyledons [tor/tor homozygous allele showed the earliest insertion in the 47th exon of the kinase domain. The homozygous tor knockout lines also showed embryo lethality and the embryo growth was arrested at the 16–32 cell stage as previously reported [rpl24 mutant was observed in the third intron of the RPL24 gene, the rpl18 mutant line had insertion in the third exon, the rps28 had insertion in the second exon and the s6k1 mutant line had insertion in the fourth exon of the gene , rpl18 (880bp), rpl23 (789bp), rpl24 (853bp), rps28 (894bp), s6k1 (752bp) and tor (730bp). The WT Arabidopsis genome showed no amplification with LB + Right gene specific Primers, showing the specificity by depicting the absence of T-DNA. In each case, the gene-specific Left Primers + Right Primers were used to amplify the RPL6 (1201bp), RPL18 (1194bp), RPL23 (1156bp), RPL24 (1200bp), RPS28 (1271bp), S6K1 (1105bp) and TOR (1054bp) genes without T-DNA insertion in the WT, whereas the primers had no amplification in the mutant lines  of Arabidopsis when compared to the WT (Col0) and was increased in the TOR-overexpressing line G548, suggesting that TOR kinase expression levels are major effectors of regulating the S6K1 phosphorylation in Arabidopsis [RPL and RPS genes in Arabidopsis corroborated the differential regulation of S6K1 phosphorylation in Arabidopsis. Simultaneously, the mutation in RPs also resulted in the loss of total S6K1 stability besides its phosphorylation. The TOR and S6K1 mutants were used as negative controls and both mutants showed inhibited S6K1 phosphorylation and reduced stability of total S6K1 protein. However, the TOR mutant showed slight phosphorylation of the S6K1 protein in comparison with the S6K1 mutant, in which the phosphorylation was completely inhibited. The rpl6 mutants had an equally phosphorylated S6K1 protein, whereas the phosphorylation of S6K1 in rpl23a, rpl24, rpl24a and rps28a mutants was reduced to some extent. The stability of total S6K1 protein in rpl6, rpl18a and rpl23a was almost similar to that in the WT sample, whereas the rpl6, rpl18a and rpl23a mutants had increased stability of total S6K1 protein. The mutation of rpl18 had completely inhibited S6K1 phosphorylation and the rpl24a mutant had moderate inhibition, whereas the mutation in rpl23 and rps28 had no effect on S6K1 phosphorylation  which encodes a universal cytoplasmic ribosomal protein uL3 family. RPL18 (AT1G29965) also interacts with RPL24 (AT2G36620) and RPS28C (AT5G64140). The RPL23 (AT2G39460) protein interacts with proteins essential for ribosome assembly, such as RPL24 (AT2G36620), RPS17 (AT3G10610), ATARCA , RACK1B_AT , and the RACK1 subfamily translation elongation factor EF1B/ribosomal protein S6 family protein, which binds together with S18 to 16S ribosomal RNA (AT1G64510), and also binds to a S6K1 homolog (AT3G08850.1). Similarly, RPL24 and RPS28C (AT5G64140) interact with ribosomal constituent 40S RPSa-1, which is required for the 40S ribosome subunit assembly and processing of the 20S rRNA- precursor to mature 18S rRNA, RPuS2 family protein P40 (AT1G72370.1), LOS1 , EIF3G1  complex, which is involved in the protein synthesis of a specialized repertoire of mRNAs and, together with other initiation factors, stimulates the binding of mRNA and methionyl-tRNAi to the 40S ribosome), ATARCA (AT1G18080.1), RPL10 (AT3G11250.1), zinc-binding ribosomal protein family protein (AT3G10950), RPS17 (AT3G10610), RPS26e (AT2G40590), RPS5 (AT2G41840), RPL16A (AT2G42740.1) and RPL18e/L15 (AT2G47570). The S6K1 and S6K2 proteins also interact with the LOS1 protein with a confidence level of 0.499. The LOS1 appears to be a downstream effector of the TOR signaling pathway via interaction with the S6K1 or S6K2 protein (RPL23 (At4g18520) containing a pentatricopeptide repeat (PPR) protein. The binding of the S6K1 protein with the RPL23 having the ≥0.90 confidence level in the predicted PPI showed a possible feedback regulation of S6K1 via direct binding of the RPs. The protein–protein interactions (PPI) network were predicted between TOR, S6K1, S6K2, RPL6, RPL18, RPL23, RPL24 and RPS28 using the STRING v11 database search tool . STRING richment . The 50S protein . The S6KRP genes are multigene families of more than two members [RP genes of a family is required for high translational demand during plant development. We performed a comparative analysis of transcriptional regulation of RPs via the TOR pathway in rice and Arabidopsis. Our expression analysis of RP genes clearly suggested that TOR overexpression significantly upregulates the transcription of RP genes in two diverse plant species  and that these genes were downregulated in the Arabidopsis seedlings treated with active site TOR inhibitors (asTORis) and AZD-8055, except for one RP gene which showed upregulation [TOR-RNAi Arabidopsis lines resulted in a coordinated downregulation of the transcription and translation of nuclear-encoded mRNAs coding for plastidic RPs and a lower phosphorylation of the conserved Ser240 residue in the C-terminal region of the 40S ribosomal protein S6 (RPS6) [TOR acts differently in the regulation of RP genes’ transcription when overexpressed or inhibited.Arabidopsis  members . The exp species a,b. Donggulation . The TOR6 (RPS6) . These rrpl6, rpl23 and rpl24 mutant lines, except for in the rpl18 mutant line which showed inactivation of S6K1 phosphorylation in Thr-449. Previous studies in plants and animals suggest the importance of extra-ribosomal association of RPs with RNAs and other proteins and provide a link for the possible interaction with the S6K1 for translational control [TOR-RNAi showed decreased cytoplasmic RPL18a- transcript levels [rpl mutants could be the occurrence of the dose compensation effect via the function of other paralogs of these genes. The second possibility could be the mutation in the rpl18 protein function which might be reflected in the feedback regulation of S6K1 phosphorylation in Thr-449 residue, also suggesting a possible interaction between the other 60S large ribosomal subunit RPs and the S6K1 protein. Additionally, a third possibility of impaired ribosome biogenesis and improper association in the rpl18 mutant line might lead to the dephosphorylation of S6K1. However, further investigation about plant RPs’ structures and binding partners will uncover their association with various pathways  was amplified from Arabidopsis thaliana (Col 0) and cloned into pEarleyGate-203 [Arabidopsis thaliana TOR (AtTOR) gene in rice  and Arabidopsis thaliana (Col 0 ecotype) were developed using an in-planta transformation and floral dip method, respectively [TOR-expressing transgenic lines of rice (TR-15.1 and TR-2.24) and Arabidopsis (ATR-1.4.27 and ATR-3.7.32) were used in the expression analysis of RP genes [The full-length ectively ,25. The RP genes ,25.TOR-OE lines, TR-2.24, TR-15.1 and ATR-1.4.27, ATR-3.7.32, respectively, and their corresponding wild type controls (WTs) were surface sterilized with 4% sodium hypochlorite for 20 min followed by three washes with sterile double-distilled water. The rice seeds were germinated on solid Murashige and Skoog (MS) medium and were grown at 28 ± 2 °C in 16 h light/8 h dark photoperiods. The seeds of Arabidopsis thaliana SALK-T-DNA mutant lines, TOR-OE lines (ATR-1.4.27 and ATR-3.7.32) and WT plants were surface sterilized and grown on solid ½ strength of MS medium at 22 ± 2 °C of temperature and 100–150 μmol m−2 s−1 of light intensity following 16/8 h of light/dark photoperiods. Seven-day-(7 d)-old rice and Arabidopsis TOR-OE transgenic lines and their corresponding WT control counterparts were used for the expression analysis of RP genes. The heterozygous T-DNA mutant lines were grown in a growth chamber and seeds were harvested. The seeds of rice and Arabidopsis RPL and RPS) were retrieved from RGAP-DB. The sequences were validated using RAP-DB, NCBI and various other databases to ensure that the sequences were gene specific as described by Moin et al. (2016 and 2017) and Saha et al. (2017) [Arabidopsis thaliana RPL and RPS gene sequences were retrieved from Ensemble and the NCBI database and validated using the TAIR database. The sequences of ribosomal protein large and small subunit genes of rice (. (2017) ,36,37. TTOR-OE rice transgenic lines TR-2.24 and TR-15.1 [TOR-OE transgenic lines ATR-1.4.27 and ATR-3.7.32 [TM MMLV Reverse Transcriptase . The Actin1 and β-tubulin genes were used as endogenous reference genes in RT-qPCR analysis of RP genes in the rice transgenic lines, whereas the Actin2 and α-tubulin genes were used as endogenous reference genes for normalization of RT-qPCR analysis of RP genes in TOR-OE Arabidopsis lines. Specific primers were designed for studying the expression of RP genes in Arabidopsis and rice lines using primer3 (v.0.4.0) online tool . The multiple sequence alignment was performed using Clustal Omega  with the selected RPL and RPS proteins to check the similarity between various serine/threonine phosphorylation sites , rpl18 (SALK_134424), rpl23A (SALK_091329), rpl24a (SALK_064513), rps28A (SALK_094189), s6k1 (SALK_113295) and tor (SALK_138622) in the Col 0 background were obtained in a heterozygous condition from Arabidopsis Biological Resource Center . The T-DNA insertions in the mutant lines were confirmed using PCR. These lines were grown by successive inbreeding  up to T3-generation until they became homozygous insertion lines. As these lines are reported to be embryo lethal when they achieve homozygosity [2 generation (their homozygosity was confirmed through genotyping) to check the mRNA levels of the mutated genes in these lines and for protein extraction to detect the S6K1 phosphorylation. The transcript accumulation of genes in the SALK lines was analyzed using RT-qPCR. The mature seeds obtained in T3 generation of each SALK line were used to extract total RNA [s6k1−/−, tor−/−, rpl6−/−, rpl18−/−, rpl23−/−, rpl24−/− and rps28−/−  SALK lines. The Actin2 and α-tubulin genes were used as endogenous reference genes for normalization and WT was used as the control. The primers used in genotyping and RT-qPCR are detailed in the The SALK_13444, rpl23A SALK_0919, rpl24azygosity , this shotal RNA . The cDNrpl6 , rpl18 (SALK_134424C), rpl23A (SALK_091329), rpl24a (SALK_064513), rps28A (SALK_094189), Ats6k1 (SALK_113295) and tor (SALK_138622), in T3-generation using a standard phenol extraction method. As reported earlier, the homozygous tor−/− and rpl23aA−/− knockout mutants had defective embryo development [2 plants for S6K1 phosphorylation assay. The protein sample from the WT-Col 0 was used as a positive control, whereas protein samples from tor and s6k1 mutants were used as negative controls in the phosphorylation assay. The protein precipitate was dissolved in rehydration buffer  and quantified using the Bradford method with BSA standards. About 30 μg of total protein was loaded in SDS-PAGE and Western blot analysis. The phosphorylation site of human and Arabidopsis p70kDa-S6K1 proteins is homologous and conserved for Thr-389 and Thr-449 residues [rpl6−/−, rpl18−/−, rpl23A−/−, rpl24a−/−, rps28A−/−, s6k1−/− and tor−/− to determine the cross-link between TOR and RPs. The anti-human S6K1 antibody raised in mice (anti phospho70kDa-S6K1-Thr(P)-389)  was used for detecting S6K1 phosphorylation in the mutants, and WT control, the anti-70kDa S6K1  and anti-GAPDH  were used as loading controls. The membrane was incubated with secondary HRP-conjugated antibodies and signals were detected using a chemi-luminescence method .Total protein was extracted from the mature seeds of Arabidopsis WT plants and homozygous T-DNA insertion mutants of Arabidopsis RP genes:  SALK_0919, rpl24ahttps://string-db.org/ accessed on 24 July 2021) identifies the interaction based on the evidence from Arabidopsis homologs in other species. The search tool of STRING v11 was used for the retrieval of interacting genes/proteins associated with TOR and ribosomal proteins and to construct the PPI network. The TOR and RP genes used in the study were listed as inputs in the STRING dB and were searched for their neighbor interactors at a high level of confidence .A protein–protein interactions (PPI) between the TOR protein and RPs were identified through the bioinformatic approach using STRING v11 . The STRhttps://software.broadinstitute.org/morpheus/ accessed on 24 November 2020). Venn diagrams were depicted using VENNY 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/index.html accessed on 17 November 2020). Quantification of phosphorylation of S6K1 protein in the Western blot analysis was performed using Image J software (https://imagej.nih.gov/ij/index.html accessed on 17 November 2020). The putative Ser/Thr phosphopeptide sequences were identified using NetPhos 3.1 Server (http://www.cbs.dtu.dk/services/NetPhos/ accessed on 22 November 2019) and STRING v11 (https://string-db.org/ accessed on 24 July 2021) was used to predict protein–protein interactions.The results from expression analyses of RP genes were depicted as heatmaps using the MORPHEUS program  with the significance level


Lung adenocarcinoma (LUAD) causes severe cancer death worldwide. E2F2 is a canonical transcription factor implicated in transcription regulation, cell cycle and tumorigenesis. The role of E2F2 as well as its transcription regulatory network in LUAD remains obscure. In this study, we constructed a weighted gene co-expression network and identified several key modules and networks overrepresented in LUAD, including the E2F2-centered transcription regulatory network. Function analysis revealed that E2F2 overexpression accelerated cell growth, cell cycle progression and cell motility in LUAD cells whereas E2F2 knockdown inhibited these malignant phenotypes. Mechanistic investigations uncovered various E2F2-regulated downstream genes and oncogenic signaling pathways. Notably, three core transcription factors of E2F2, B-Myb and FOXM1 from the LUAD transcription regulatory network exhibited positive expression correlation, associated with each other, mutually transactivated each other, and regulated similar downstream gene cascades, hence constituting a consolidated core transcription regulatory circuitry. Moreover, E2F2 could promote and was essentially required for LUAD growth in orthotopic mouse models. Prognosis modeling revealed that a two-gene signature of E2F2 and PLK1 from the transcription regulatory circuitry remarkably stratified patients into low- and high-risk groups. Collectively, our results clarified the critical roles of E2F2 and the exquisite core transcription regulatory circuitry of E2F2/B-Myb/FOXM1 in LUAD progression. Lung cancer accounts for the highest cancer incidence and mortality around the world early region 2 binding factor) family of transcription factors consists of eight members (E2F1-E2F8), and is classified into activators (E2F1-E2F3), repressors (E2F4-E2F6), and atypical repressors  on the basis of transcriptional function The E2F  data portal Construction of co-expression networks and identification of co-expression modules were conducted by using the WGCNA R package in R 3.6.2 where lij is defined as the dot product on row i and column j in adjacency matrix, and ki (the connectivity) is the summation of row i in adjacency matrix. 1-Tom was hierarchically clustered by using the “average” clustering method, and the module was identified by using the dynamic tree cutting method.The genes in the turquoise module were screened based on the weight value  greater than 0.2. The LUAD module total network was constructed in Cytoscape3.6.1 software The clinical data of LUAD include sex, age, tumor pathologic stage, lymph node pathologic stage, metastasis stage, sample type, vital status, etc. The association between each module and each trait was first represented by the average gene expression level of the module gene members, and then the module average was associated with the observed phenotypic traits using Pearson correlation analysis. Modules with significant association to phenotype were obtained. Finally, in order to further confirm the modules that are significantly related to the phenotype, the labeled heatmap function was used to calculate the correlation coefficient between module membership (gene expression level) and gene significance .To better explore the biological significance of the LUAD module key network, the DAVID v6.8  TM (TaKaRa) as previously described Total RNA was extracted from cells by using Trizol reagent (Invitrogen) and qRT-PCR was performed by using SYBR PremixEx TaqpCDH-puro-HA-E2F2 lentiviral expression vector was previously constructed 7 U/L) and streptomycin (10 mg/L) in a humidified incubator containing 5% CO2 at 37 °C. Cell lines were routinely tested for short tandem repeat authentication and mycoplasma contamination Human LUAD cell lines, A549 and H1975, were obtained from Chinese Academy of Sciences Shanghai cell bank . Human embryonic kidney cell line 293Ta was purchased from FulenGen . Cells were routinely maintained in DMEM, MEM, or RPMI1940 medium (Hyclone) supplemented with 10% of fetal bovine serum (Hyclone), penicillin  following the manufacturer's instructions. Briefly, the exponentially growing cells were seeded on 96-well plates and then sequentially labelled with 10 μM EdU for 2h, fixed, stained with Apollo488 and Hoechst 33342 (DNA dye for nuclei staining), and finally observed under fluorescence microscope .EdU labelling assays were conducted by using Cell-Light EdU Apollo488 The indirect immunofluorescence assays were conducted as described previously with minor modifications Co-IP assays were carried out as described previously The 3D structures of E2F2 and FOXM1 were predicted and downloaded with high model confidence (≥70) from the AlphaFold Protein Structure Database 6 cells were injected subcutaneously into the mice. Tumor volume was calculated using the equation L × W2/ 2 . After 32 days, the mice were sacrificed and the tumor tissues were harvested and frozen in liquid nitrogen or fixed in formalin and embedded in paraffin using the routine method. All procedures conformed to the legal mandates and guidelines of the Laboratory Animal Center of Chongqing Medical University for the care and maintenance of laboratory animals.BALB/c-nude mice  were randomly distributed into the indicated groups (n=5), and 2× 10The promoter reporter E2F2-P1314(-984/+329) and B-Myb-P1064(-916/+148) were constructed previously ChIP assays were carried out using the EZ ChIP™ Chromatin Immunoprecipitation kit  as described in the previous study Based on the cut-off value of the median survival time, LUAD patients were divided into high-risk (n=252) and low-risk (n=252) groups, and Kaplan-Meier survival curve was generated to predict cases with low or high risk. Univariate Cox regression was used to estimate the association between the expression level of each gene of the LUAD module TF network and patient's overall survival (OS). Multivariate Cox regression with stepwise regression method was conducted to screen and eliminate the variables causing multicollinearity within the genes of LUAD module TF network. The formula based on gene expression level to calculate the risk score for predicting prognosis was finally established as following:ExpmRNA represents the expression level of each gene, and βmRNA denotes the regression coefficient of the gene in the multifactor cox regression model Routine statistical analyses were conducted using SPSS  version 21 software package . The difference between different groups was quantitatively estimated by t-test. Statistical tests with P values less than 0.05 were considered significant. As for routine bioinformatic analysis, R software (version 3.6.2 and 4.1.0), the DESeq2 package, the survival package and the corrr package were utilized to identify the differentially expressed genes, survival estimation and gene expression correlation analysis, respectively. The pheatmap package of R3.6.2 was used to construct heat maps that visualize the differential gene expression.Hierarchical clustering of the LUAD samples was conducted based on Euclidean distance computed on gene expression data, and integrated with the clinical information of patients Fig. A. Four oTo screen and identify potential hub oncogenic driver genes in LUAD, we selected the turquoise module, which shows significant positive correlation with the phenotype of tumor vs normal and contains the largest number of genes, for further deep network analysis in combination with LUAD differential expressed genes (DEGs) analysis Fig. B. The LUTo gain an insight into the driving force in the “LUAD module key network”, a total of 11 genes encoding three human transcription factors and cofactors were identified and used to finally construct the “LUAD module TF network” Fig. A. Among in vitro.To better understand the function of E2F2 in lung adenocarcinoma progress, two different LUAD cell lines A549, H1975) were used to generate stable E2F2 overexpression or knockdown cells. E2F2 overexpression and knockdown effects were verified by qRT-PCR and immunoblotting analyses  were found after E2F2 knockdown (1955 genes down-regulated and 2537 genes up-regulated) Fig. . FurtherThe “LUAD module TF network” we obtained Fig. A stronglin vivo  and Gene Expression Omnibus (GEO) lung cancer datasets To date, E2F2 as well as its activator counterparts of E2F1 and E2F3 has been demonstrated to exert functions mainly via two mechanisms. Firstly, E2F2 directly binds to the target gene promoters and transactivates the expression of downstream target genes that regulate cell cycle progression, apoptosis, and metastasis Recently, we have demonstrated that E2F2 associate with B-Myb, and more intriguingly both transcription factors mutually regulate each other, thus forming an exquisite reciprocal feed-forward loop which plays a vital role in accelerating colorectal cancer progression in vivo binding of E2F2, B-Myb and FOXM1 to these elements. Co-IP assays demonstrated the molecular association among these three transcription factors. Thus, the data suggest that E2F2, B-Myb and FOXM1 might work as a complex to regulate each other as well as their target genes. E2F2 and B-Myb regulate target gene transcription through binding to the consensus E2F-binding sites and Myb-binding sites and/or interacting with other transcription factors/cofactors It is important to note that the promoter regions of E2F2, B-Myb and FOXM1 as well as their target genes such as PLK1 all contain binding sites for E2F2, B-Myb and FOXM1. ChIP assays revealed the Our results highly suggest that the E2F2-centered transcriptional regulatory network plays a pivotal role in LUAD progression and might serve as a promising diagnostic and therapeutic target for the treatment of LUAD. However, as a transcription factor, E2F2 as well as B-Myb and FOXM1 is currently undruggable. Our prognostic analysis on the E2F2-centered network genes revealed that a E2F2/PLK1 two-gene signature remarkably stratified LUAD patients into low- and high-risk groups, suggesting that PLK1 might act as a pivotal regulator in the E2F2-centered network.Previous reports showed that E2F1 could directly regulate the expression of PLK1 In summary, our results clarified that E2F2 essentially contributes to LUAD progression by promoting cell cycle progression, cell proliferation and motility, and further unraveled an exquisite core transcription regulatory circuitry of E2F2/B-Myb/FOXM1 that contributes to the malignant progression of human LUAD.Supplementary figures and tables.Click here for additional data file.


Ubiquitin-conjugating enzymes E2S (UBE2S) and E2C (UBE2C), which mediate the biological process of ubiquitination, have been widely reported in various cancers. Numb, the cell fate determinant and tumor suppressor, was also involved in ubiquitination and proteasomal degradation. However, the interaction between UBE2S/UBE2C and Numb and their roles in the clinical outcome of breast cancer (BC) are not widely elucidated.Oncomine, Cancer Cell Line Encyclopedia (CCLE), the Human Protein Atlas (HPA) database, qRT-PCR, and Western blot analyses were utilized to analyze UBE2S/UBE2C and Numb expression in various cancer types and their respective normal controls, breast cancer tissues, and breast cancer cell lines. The expression of UBE2S, UBE2C, and Numb in BC patients with different ER, PR, and HER2 status, grades, stages, and survival status was compared. By Kaplan–Meier plotter, we further evaluated the prognostic value of UBE2S, UBE2C, and Numb in BC patients. We also explored the potential regulatory mechanisms underlying UBE2S/UBE2C and Numb through overexpression and knockdown experiments in BC cell lines and performed growth and colony formation assays to assess cell malignancy.In this study, we showed that UBE2S and UBE2C were overexpressed while Numb was downregulated in BC, and in BC of higher grade, stage, and poor survival. Compared to hormone receptor negative (HR−) BC cell lines or tissues, HR+ BC demonstrated lower UBE2S/UBE2C and higher Numb, corresponding to better survival. We also showed that increased UBE2S/UBE2C and reduced Numb predicted poor prognosis in BC patients, as well as in ER+ BC patients. In BC cell lines, UBE2S/UBE2C overexpression decreased the level of Numb and enhanced cell malignancy, while knocking down UBE2S/UBE2C demonstrated the opposite effects.UBE2S and UBE2C downregulated Numb and enhanced BC malignancy. The combination of UBE2S/UBE2C and Numb could potentially serve as novel biomarkers for BC. The The ubiquitination-proteasome pathway is a post-translational modification of the protein degradation system discovered in 2005 , 7. Thisvia ubiquitination , which provides visualization and analysis of large-scale cancer genomics in the TCGA database, was used for coexpression analysis. In this study, the Breast Invasive Carcinoma  cohort was analyzed to compare the correlation between Numb and UBE2S or UBE2C. Pearson’s correlation score and Spearman score were calculated with default software parameters.The cBioPortal  database (2.2Oncomine database (www.oncomine.org). Besides, we also compared the overexpression or underexpression pattern of UBE2S, UBE2C, and Numb mRNA levels in nine independent datasets of breast cancer specimens and their matched normal tissues. Furthermore, the expression levels of UBE2S, UBE2C, and Numb were compared according to different clinical outcomes or survival statuses of breast cancer patients, providing evidence for potential predictors of prognosis.We analyzed the differential mRNA expression of UBE2S, UBE2C, and Numb in a variety of major cancer subtypes and their respective normal controls using the 2.3https://portals.broadinstitute.org/ccle), which contains massive RNA, whole exome, and whole genome sequencing data for nearly 1,000 cancer cell lines, was applied to analyze the copy number of UBE2S, UBE2C, and Numb in certain major cancer cell lines, including breast cancer.The CCLE public project (2.4www.proteinatlas.org), which contains pathological information based on protein expression data from various forms of human cancer, including breast cancer, together with in-house generated immunohistochemically stained tissue section images.Representative immunohistochemical staining of UBE2S, UBE2C, and Numb was retrieved from the Human Protein Atlas database  web service to evaluate the correlation between prognostic values  and investigated genes  mRNA expression in breast cancer and the ER+ subtype based on the hazard ratios (HR) and logrank p-values. The high and low groups of UBE2S, UBE2C, and Numb were defined based on a 50% cutoff or the cutoff with the most significant p-value.We utilized the Kaplan–Meier plotter . MDA-MB-468 cells were cultured in a humidified atmosphere of 0.03% CO2 at 37°C while all other cell lines were cultured in the same conditions except that the CO2 concentration was 5%.All cell lines were obtained from the American Type Culture Collection . MCF10A cells were grown in DMEM/F12  supplemented with 10% horse serum (Invitrogen), EGF , hydrocortisone , insulin (Sigma), and 1% penicillin–streptomycin (Invitrogen). MDA-MB-231, MCF7, and T47D cells were grown in DMEM (Invitrogen). MDA-MB-468 and SK-BR-3 cells were cultured with Leibovitz’s L-15  and McCoy’s 5A (Gibco), respectively. Except for MDF10A medium, all growth media were supplemented with 10% fetal bovine serum (Invitrogen), 100 Uml2.7−ΔΔCt method. The primer sequences (5’–3’):Total RNA was extracted with TRIzol reagent following the manufacturer’s instructions (Invitrogen) and proceeded to reverse transcription and real-time PCR with SYBR Premix Ex Taq . The expression levels of UBE2S, UBE2C, and Numb were normalized to ACTIN and calculated using the 2UBE2S-forward: CCGACACGTACTGCTGACC;UBE2S-reverse: GCCGCATACTCCTCGTAGTTC;UBE2C-forward: AGTGGCTACCCTTACAATGCG;UBE2C-reverse: TTACCCTGGGTGTCCACGTT;NUMB-forward: TCAGCAGATGGACTCAGAGTT;NUMB-reverse: AGGCTCTATCAAAGTTCCTGTCT;ACTIN-forward: GCACAGAGCCTCGCCTT;ACTIN-reverse: GTTGTCGACGACGAGCG.2.8MCF10A protein was extracted using M-PER containing an EDTA-free Halt Protease Inhibitor Cocktail , while proteins from all other cell lines were extracted using RIPA lysis buffer. Protein transfer was performed on a nitrocellulose membrane . Primary antibodies include: UBE2S , UBE2C , Numb , and ACTIN . Protein was visualized with the ECL Western Blotting Detection System , and a densitometry value was determined in terms of pixel intensity by ImageJ.2.9MCF7 and MDA-MB-231 cells were seeded in 6-well plates and cultured to 70%–80%. For transient overexpression (OE), cells were transfected with a constructed plasmid  overexpressing UBE2S/UBE2C or a negative control using Lipofectamine 3000 (Invitrogen). Gene sequences were obtained from the Ensembl human genome assembly (Genome Reference Consortium GRCh38). For transient knockdown, cells were transfected with small interfering RNAs (siRNAs) targeting UBE2S/UBE2C or a negative control :si-UBE2S-1: GAUCCUGCUUUGUGCUAAAGA;si-UBE2S-2: GAAUCAGACAACCUUGUCAAA;si-UBE2C-1: UGAAAAGGUUGUCUGAUUCAG;si-UBE2C-2: GGAAAGACAAGGGAAGAAACC.After 4-hour incubation, the medium was replaced with DMEM containing 10% fetal bovine serum. Transfection efficiency was determined 48 h later using RT-qPCR and Western blotting.2.10MCF7 and MDA-MB-231 cells were seeded in 6-well plates at a concentration of 1,000 cells per well and cultured for 10–14 days. Colonies were fixed and stained using 0.2% crystal violet.2.11For the CCK-8 cell proliferation assay, MCF7 and MDA-MB-231 cells were seeded in 96-well plates at a concentration of 3,000 cells per well. The absorbance at 450 nm was determined at the indicated time points using a microplate reader two hours after adding 10 μl of CCK-8 solution  to each well.2.12Oncomine database were presented using Prism GraphPad software (LaJolla) and analyzed using a Student’s t-test. A statistical difference was determined two-sidedly with P-values less than 0.05, which are indicated with the following asterisks: *P <0.05, **P <0.01, **P <0.001, ****P <0.0001. For the rest of the study’s data, statistical analyses were calculated with default software parameters. All experiments were performed in three biological replicates.In this study, data obtained from the 33.1Oncomine microarray datasets to determine the mRNA levels of UBE2S, UBE2C, and Numb in a variety of malignant tumor types, including breast cancer. As shown in Oncomine datasets regarding breast cancer and found that there was evidently higher mRNA expression of UBE2S and UBE2C but lower Numb expression in breast cancer samples than their respective normal controls . More specifically, the comparison of UBE2S, UBE2C, and Numb mRNA expression across nine independent analyses demonstrated that UBE2S and UBE2C were markedly elevated and Numb was significantly reduced in breast cancer . It is widely known that breast cancer is classified into different subtypes according to ER, PR (progesterone receptor), and HER2  status. Apart from ER+ and ER− breast cancers, we also compared the expression of UBE2S, UBE2C, and Numb in PR positive (PR+) and PR negative (PR−) breast cancers as well as in HER2 positive (HER2+) and HER2 negative (HER2−) breast cancers. As shown in ER+ breast cancer is the most common pathological subtype and accounts for over 70% of breast cancer . As the 3.3Oncomine data analysis and Kaplan–Meier plotter survival analysis, we further analyzed the prognostic effects of UBE2S, UBE2C, and Numb in breast cancer patients. In . In other words, high levels of UBE2S and UBE2C and decreased Numb expression were associated with a shorter lifespan in breast cancer patients. Next, we evaluated the impact of differential mRNA expression of UBE2S, UBE2C, and Numb on the clinical survival of breast cancer patients. We found that higher levels of UBE2S and UBE2C and lower expression of Numb were correlated with shorter overall survival (OS) and relapse-free survival (RFS) in breast cancer patients (By using ents. In . In otheents. In . In otheents. In . In otheents. In . In otheents. In . In othe3.4P <0.05). Among these genes, UBE2S ranked first and UBE2C ranked 526th based on Spearman’s Correlation Score. By cBioPortal regression analysis, highly negative relevant coefficients were revealed between Numb and UBE2S  and a moderately negative correlation between Numb and UBE2C   S5A, C, 4With the increasing incidence of breast cancer all over the world, it is vital to explore the underlying molecular mechanism of this tumor, which jeopardizes women’s lives. Different from other common cancers, breast cancer was divided into four molecular subtypes according to the status of HR, HER-2, and Ki-67, accounting for different therapeutic strategies and prognosis . Due to Ubiquitin signaling plays an important role in protein degradation by post-translational modification, involving the multistep enzymatic actions of ubiquitin activating enzyme E1, ubiquitin conjugating enzyme E2, and ubiquitin ligase E3 . A growiNumb was widely reported as a tumor suppressor in various cancers, and low expression of Numb was related to highly malignant tumor cells , 50, 51.via downregulation of Numb. We reported overexpression of UBE2S and UBE2C and downregulation of Numb in breast cancer compared with normal breast tissue at both mRNA and protein levels. In a paired analysis of breast cancer and adjacent normal tissue, higher levels of UBE2S and UBE2C and lower Numb expression were found in the former. UBE2S and UBE2C also demonstrated increased expression in breast cancer with a more advanced grade and stage, while Numb showed the opposite trend. Since HR+ BC is the most common subtype with a better prognosis than HR− BC, we also found that ER or PR-negative breast cancer tissues or cells had higher levels of UBE2S and UBE2C and lower expression of Numb compared with HR+ breast cancer, providing evidence for the promoting roles of UBE2S and UBE2C and the suppressive role of Numb in breast cancer malignancy. For survival analysis, patients with a higher level of UBE2S or UBE2C had a shorter lifespan than those with a lower expression of UBE2S or UBE2C. Meanwhile, lower Numb expression was accompanied by a worse prognosis in breast cancer patients as well as in ER+ BC patients. Specifically, by combining UBE2S or UBE2C together with Numb, we found patients with low UBE2S or UBE2C and high Numb expression demonstrated a more favorable prognosis. In contrast, patients with high UBE2S or UBE2C and low Numb levels showed a worse outcome. Therefore, we propose that combining UBE2S or UBE2C with Numb may serve as an effective predictor of breast cancer survival.In the present study, we first proposed that UBE2S and UBE2C confer poor prognosis in breast cancer Mechanically, a notably negative correlation was found between the ubiquitin-conjugating enzymes and Numb through bioinformatic analyses. We further elucidated the underlying mechanisms through gain-and-loss-of-function studies in breast cancer cell lines. It is revealed that overexpression of UBE2S or UBE2C results in decreased Numb expression. However, a significant increase in Numb expression was observed by silencing UBE2S or UBE2C expression in breast cancer cells at both protein and mRNA levels. This confirms the downregulating roles of UBE2S and UBE2C in Numb expression. In addition, we found that overexpression of UBE2S or UBE2C led to increased capabilities of colony formation and cell proliferation while silencing of UBE2S or UBE2C displayed opposite trends in breast cancer cells, indicating the tumor-promoting effect of elevated UBE2S or UBE2C expression.via downregulation of Numb. Breast cancer with higher UBE2S or UBE2C levels and lower Numb expression is correlated with a worse prognosis, providing potential biomarkers for BC therapeutics. It is speculated that UBE2S and UBE2C may work together to regulate Numb expression. However, further validation of the function and regulatory mechanism between UBE2S/UBE2C and Numb is necessary in future work to provide more effective therapeutic interventions.Taken together, we uncover that UBE2S and UBE2C confer a poor prognosis for breast cancer The original contributions presented in the study are included in the article/XH, XZ, and YG conceptualized and designed the study. YG and XC contributed to the data acquisition and interpretation as well as in methodology and analysis. YG, XZ, and XH were major contributors in writing, review and editing the manuscript. All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.


Dear Editor,+ tumor-infiltrating lymphocytes (TILs) and PD-L1 expression has been associated with the efficacy of immune checkpoint inhibitors (ICIs). In our previous studies, we have demonstrated that psoriasin, also known as S100 calcium-binding protein A7 (S100A7), not only accelerates tumor progression via the activation of the p-Erk pathway in LUSC and the p-Erk and p-FAK pathways in esophageal squamous cell carcinomas (ESCC) but also remodels the tumor microenvironment by promoting angiogenesis and M2 macrophage infiltration in ESCC.2 However, the role of S100A7 in the TIME and immunotherapy efficacy in LUSC remains to be elucidated.In recent years, the rapid development of immunotherapy has brought survival benefits for lung squamous cell carcinoma (LUSC) patients who have rare treatment options. Nevertheless, there are still some patients with immunotherapy resistance, which is the root cause of the low benefit rate and disease progression of the overall population, and it is an urgent problem to be solved. Except for tumor mutation burden, the tumor immune microenvironment (TIME) as characterized by infiltration of CD8+ TILs infiltration and PD-L1 expression using immunohistochemistry. The results showed that S100A7 expression was negatively related with both PD-L1 expression  database. A negative association between S100A7 and CXCL9 expression was observed , S100A7 expression also negatively correlated with M1 macrophage infiltration  (Supplementary Fig. r = −0.45, p < 0.001; Fig. + M1 macrophages infiltration (r = −0.27, p = 0.006; Fig. + macrophages as a major source of CXCL9.4In this study, a cohort of 102 LUSC resected specimens from the Cancer Hospital and Institution, Chinese Academy of Medical Sciences was collected to determine the correlation between S100A7 expression and TIME based on CD82 Consistently, in our study, overexpression or exogenous introduction of S100A7 protein activated the p-Erk and p-AKT pathways (Fig. 5 Notably, our study demonstrated that PD-L1 expression could be partly abrogated by either S100A7 knockdown or treatment with the RAGE or AKT inhibitor (Fig. + macrophages and CXCL9 level in the tumor cell. These mechanisms further down-regulated the infiltration of CD8+ TILs, which in turn built up an immunosuppressive TIME that was primarily resistant to ICIs.Given that CXCL9 was also found in tumor cells (Supplementary Fig. ays Fig. . Moreoveays Fig. . Previoutor Fig. . Based op < 0.001; Fig. p < 0.001; Fig. + T cells and CD68+ macrophage infiltration in mouse tumor specimens with S100A7a-knockdown (Fig. + T cell infiltration compared to other groups (Fig. Considering the relationship between S100A7 expression and an immunosuppressive TIME, we wanted to determine the effect of dysregulating S100A7 on the immunotherapy response observed in LUSC. For this, we used a murine model bearing the mouse homolog of human S100A7, S100A7a, in subsequent experiments (Supplementary Figs. own Fig. . More imups Fig. .2 a cohort of 27 LUSC patients treated with ICIs was enrolled to investigate the association between baseline plasma levels of S100A7 and the efficacy of ICIs (Supplementary Table p = 0.039; Fig. p = 0.005; Fig. Based on previous reports that S100A7 can be secreted outside the cell and detected in plasma,+ TILs infiltration via the downregulation of CXCL9 expression (Fig. Taken together, we demonstrated that the upregulation of S100A7 could result in ICIs resistance due to a remodeled immunosuppressive TIME characterized by a decreased PD-L1 expression via the activation of the p-AKT pathway, and decreased CD8ion Fig. . We alsoSupplementary_Materials


Several metabolic disorders and malignancies are directly related to abnormal mitochondrial solute carrier family 25 (SLC25A) members activity. However, its biological role in pancreatic cancer (PC) is not entirely understood.SLC25A11, SLC25A29, and SLC25A44. Single-cell RNA sequencing (ScRNA-seq) revealed the distribution of gene expression in PC. Tumor immune infiltration was examined with the TIMER database. Lastly, drug sensitivity was investigated, and co-transcriptional factors were predicted.The lasso method was used to create a novel prognostic risk model for PC based on SLC25A members, and its roles in tumor immunology and energy metabolism were explored. Furthermore, co-expression networks were constructed for SLC25A11, SLC25A29, and SLC25A44 were involved in the energy metabolism of PC and prevented tumor growth, invasion, and metastasis. ScRNA-seq research also pointed to their contribution to the tumor microenvironment. Moreover, the recruitment of numerous immune cells was positively correlated with SLC25A11 and SLC25A44 but negatively correlated with SLC25A29. Additionally, the sensitivity to 20 Food and Drug Administration-approved antineoplastic medicines was strongly linked to the aforementioned genes, where cisplatin sensitivity increased with the up-regulation of SLC25A29. Finally, the Scleraxis BHLH Transcription Factor (SCX) and other proteins were hypothesized to co-regulate the mRNA transcription of the genes.In the present study, a novel prognostic risk model was established and validated for PC based on SLC25A members. The high-risk group had a lower activation of oxidative phosphorylation and a more abundant immune infiltration phenotype than the low-risk group. According to co-expression network studies, SLC25A11, SLC25A29, and SLC25A44 can be used as favorable prognostic markers. The use of these markers will provide new directions to unravel their action mechanisms in PC.SLC25A members are crucial for tumor immune and energy metabolism in PC, and The online version contains supplementary material available at 10.1186/s12967-022-03756-2. Pancreatic cancer (PC) is one of the most malignant cancers. According to GLOBOCAN, nearly 466,000 people die from PC annually, which is almost equal to the number of diagnosed cases . The 5-year survival rate is < 8%, which makes PC the seventh most important cause of cancer-related death worldwide . The deeMitochondria are biological organelles with self-replicable and transcribable DNA, and mitochondrial DNA (mtDNA) lesions are an important cause of disease . FurtherSLC25A11, SLC25A29, and SLC25A44) in PC were explored, and transcription factor (TF) networks were created based on them. Considering the heterogeneity of the tumor cells, the role of SLC25A members in the tumor microenvironment (TME) was also analyzed using single-cell RNA-seq (scRNA) data.In the present study, differences in the expression and function of SLC25A members in PC and its correlation with tumor immune infiltration were analyzed. Furthermore, a prognostic risk model was constructed using public databases. In addition, the functions of the identified SLC25A members  from the TCGA database, and 167 normal pancreatic tissue samples were pooled from the GTEx database. By analyzing the differential expression of genes between PC tumor tissue and normal tissue, a total of 19,712 differentially expressed genes (DEGs) were identified . Finally, 38 DEGs of SLC25A members were screened using the Venn diagram , SLC25A11 (P < 0.0001), SLC25A24 (P < 0.01), SLC25A37 (P < 0.01), SLC25A42 (P < 0.01), SLC25A43 (P < 0.0001), SLC25A44 (P < 0.05) and SLC25A45 (P < 0.05) were significantly different , SLC25A6 (P = 3.9e−3), SLC25A11 (P = 3.9e−5), SLC25A14 (P = 1.8e−3), SLC25A27 (P = 1.5e−3), SLC25A29 (P = 3.6e−4), SLC25A34 (P = 8.9e−4), SLC25A42 (P = 9.7e−3), SLC25A44 (P = 3.8e−4), SLC25A45 (P = 4.1e−3) and SLC25A53 (P = 6.3e−5) had better prognosis. In contrast, those with low expressions of SLC25A24 (P = 9.3e−3), SLC25A37 (P = 0.02) and SLC25A43 (P = 3.63e−3) had longer survival . Survival analysis revealed that survival was significantly longer in the TCGA-PAAD cohort in Cluster 1 (blue) than in Cluster 2 (red)  was an independent factor for predicting PC prognosis Fig. B. CalculSLC25A11, SLC25A29, and SLC25A44 were screened for differential expression in PC, with significant prognostic value, in previous univariate and multifactorial Cox regression analyses. Subsequently, separate in-depth analyses of the genes were conducted to explore their functions in PC. Functional module analysis based on LinkedOmics indicated that the transcriptome expression level of SLC25A11 in PC was positively correlated with the expression of 5057 genes but negatively correlated with the expression of 5069 genes (FDR < 0.05); the expression level of SLC25A29 was positively correlated with the expression of 4960 genes and negatively correlated with the expression of 5937 genes (FDR < 0.05); the expression level of SLC25A44 was positively correlated with the expression of 2106 genes and negatively correlated with the expression of 1835 genes (FDR < 0.05)  pathway analysis showed that the co-expressed positively correlated genes SLC25A11 and SLC25A29 were predominantly enriched in the ribosome and OxPhos pathways. SLC25A44 and its positively correlated genes, on the contrary, were enriched in pathways related to the synaptic vesicle cycle, nicotine addiction, maturity-onset diabetes of the young, and synaptic vesicle recycling. The negatively correlated genes SLC25A11, SLC25A29, and SLC25A44 were enriched in adherens junction, focal adhesion, and ECM-receptor interaction. Furthermore, SLC25A29 expression was negatively associated with various pathways, such as Th17, Th1, and Th2 cell differentiation. Additionally, SLC25A44 and its negatively correlated genes were involved in PC, cell cycle, HIF-1, P53, and Hippo pathways , CD8 + T cells , macrophages  and DC cells . Moreover, a significant positive correlation was observed with the abundance of CD4 + T cells   Fig. b. SLC25Ated Fig. c with B SLC25A11, SLC25A29 and SLC25A44 affect the TME in PC, their expression levels were analyzed in the TME of different cell types using a common scRNA dataset. SLC25A11 and SLC25A29 were noted to be expressed in stromal cells, malignant cells, and immune cells. SLC25A44 was chiefly expressed in stromal cells   Fig. b. These SLC25A11, SLC25A29, and SLC25A44, three common TFs were predicted using the CHEA3 database, namely, Top10 TFs of Mean Rank  et al.), which are most likely to be involved in the TFs of the above mRNA  contributes significantly to the above phases in two different mechanisms . The samples with incomplete clinical data were censored.We collected RNA-Seq (FPKM) and somatic mutation data on PC samples (TCGA-PAAD) from the TCGA database  [ANOVA or two-sided Wilcoxon rank-sum test. Finally, according to the median expression level of DEGs, the SLC25A members were assigned to 2 groups: high and low—and their prognostic value in TCGA-PAAD was analyzed by Kaplan–Meier analysis.Interactions between the protein levels of DEGs of SLC25A members were assessed using STRING (-db.org) . DEGs amFirst, we used the R package NMF  to underBased on Bindea's research, we collected 29 gene sets that marked different tumor-infiltrating immune cell types . The sinTo validate the clinical efficacy of the prognostic risk model for DEGs, we evaluated the risk scores in the TCGA-PAAD cohort through univariate and multivariate Cox regression analyses, and nomograms were constructed to assess the prognostic significance of these features. In addition, we built a dynamic nomogram based on the R package Dynnom, which forms an interactive interface for clinical applications, and deployed it on web pages . The ROChttps://discover.nci.nih.gov/cell-miner/home.do) to investigate the expression levels of gene transcriptomes in NCI-60 cell lines and their sensitivity to antitumor drugs [We used the CellMiner database (or drugs .http://www.linkedomics.org/login.php) functional module. Then, we used Gene Set Variation Analysis (GSVA) to analyze the biological processes and signaling pathways, where the DEGs were concentrated.We analyzed the DEGs associated with the key SLC25A members transcription in PC based on the LinkedOmics (http://cistrome.shinyapps.io/timer/) database (purity-corrected) [http://tisch.comp-genomics.org/) is a comprehensive scRNA dataset that enables interactive single-cell transcriptome visualization of the tumor microenvironment [We also analyzed the differences in the expression levels of SLC25A11, SLC25A29, SLC25A44, and the Spearman correlation of different immune-cell infiltration levels in PC using the TIMER (rrected) . The Tumironment . In the https://maayanlab.cloud/chea3/) [TFs prediction was performed by ChIP-X enrichment analysis 3 (ChEA3) (/chea3/) . The ChEANOVA was used to estimate the statistical significance of differences between the different tumor tissue stages for DEGs that conformed to a normal distribution or a two-sided Wilcoxon rank-sum test for non-normal distribution. The Chi-square test or Fisher's exact test was performed to investigate the statistical significance of differences between the categorical variables. Spearman's correlation test was employed to assess two gene correlations as well as gene and drug correlations. One-way and multi-way Cox regression analyses were performed to determine independent prognostic factors. The survival outcomes were assessed using Kaplan–Meier curves, with a two-sided P < 0.05 considered as the threshold of significance.Data were analyzed using R v 4.0.3. Additional file 1: Table. S1. Mitochondrial solute transporter family 25 differentially expressed genes in pancreatic cancer. Table. S2. 10 SLC25A genes by Lasso-cox. Table. S3. The top 10 most relevant transcription factors for SLC25A11, SLC25A29 and SLC25A44.Additional file 2: Fig. S1. Exploration of the mRNA and protein level relationships as well as the prognostic value of differentially expressed SLC25A members in PC. (A) Using the string platform, DEGs of SLC25A members were examined for interactions at the protein level. Nodes denote proteins and edges denote specific functional associations between the predicted nodes. (B) The co-expression relationship of DEGs of SLC25A members at the mRNA level was assessed using Spearman’s rank correlation , . (C) According to Kaplan–Meier analysis, seven SLC25 high expressions had a better prognosis, while three SLC25A members low expressions had a better prognosis.Additional file 3: Fig. S2. A new classification based on non-negative matrix decomposition of DEGs and Lasso regression analysis. (A) Non-negative matrix factorization (NMF) clusters were employed to screen for molecular classification, and the results of the ranking survey revealed the optimal grouping of the two subgroups. (B) The heatmap of the consensus matrix of two subgroups. (C) Lasso analysis was used to evaluate 10 candidates’ genes with minimal Lambda.Additional file 4: Fig. S3. Comprehensive analysis of SLC25A11, SLC25A29, and SLC25A44. (A) Co-expressed genes with SLC25A11, SLC25A29, and SLC25A44, respectively, in PC (LinkedOmics). (B) Heatmap displaying the top 50 positively associated genes and the top 50 negatively associated genes co-transcribed with SLC25A11 in PC. (C) SLC25A29, (D) SLC25A44.