Recent developments in MIBC treatment suggest good efficacy of bladder sparing treatment combined with immune checkpoint inhibitor. However, there is no standard treatment mode. A retrospective analysis was conducted to reveal the efficacy and safety of PD-1 inhibitor in combination with radiotherapy or chemoradiotherapy.We retrospectively analyzed 25 patients with MIBC T2-T3N0M0 disease who were unfit or unwilling to undergo RC. These patients underwent the maximum TURBT followed by PD-1 inhibitor  in combination with radiotherapy or chemoradiotherapy (gemcitabine plus cisplatin) between April 2020 and May 2022. The primary outcome was clinical complete response (cCR) rate. The secondary outcomes were disease free survival (DFS) and overall survival (OS).Revised: Of 25 patients, 22 were T2 (88%), while 3 were T3 (12%). The median age is 65 years (51–80). Twenty-one patients had programmed cell death ligand 1 (PD-L1) combined positive score (CPS) of 1 or more, and 4 patients had CPS<1 or unknown. Sixteen patients received chemoradiotherapy. Tislelizumab and Toripalimab were administered to 19 and 6 patients, respectively. The median number of cycles of immunotherapy was 8. Twenty-three patients (92%) achieved cCR. Following a median of 13 months of follow-up , 1-year DFS and OS rate were 92% and 96%, respectively. In the univariate analysis, T stage significantly influenced OS and ORR, and efficacy evaluation significantly influenced OS, DFS, and ORR. The expression of PD-L1 and chemotherapy had no effect on prognosis. In the multivariate analysis, no independent prognostic factors were found. Grade 3 or 4 adverse events (AE) were reported in 35.7% patients.Bladder sparing therapy with PD-1 inhibitor in combination with radiotherapy or chemoradiotherapy is feasible, safe, and highly effective for patients who were unfit or unwilling to undergo RC. Bladder cancer is the tenth most common cancer globally and the second most common genitourinary malignancy . CurrentImmune checkpoint inhibitors (ICIs) have provided new prospects for the treatment of MIBC. Currently, programmed cell death protein-1 (PD-1), programmed death-ligand 1 (PD-L1), and cytotoxic T-lymphocyte-associated antigen 4 inhibitors are the most studied ICIs, and various PD-1/PD-L1 inhibitors have been approved for the treatment of advanced bladder cancer , 10. BecA cohort of patients diagnosed with MIBC was retrospectively examined at the Second Xiangya Hospital of Central South University between April 2020 and May 2022. The inclusion criteria were as follows: (1) those with a pathological diagnosis of T2-T3N0M0 MIBC, (2) those who were ineligible or unwilling to undergo RC surgery and selected TURBT followed by the administration of PD-1 inhibitors in addition to radiotherapy with or without chemotherapy, and (3) those with complete follow-up data. The exclusion criteria were as follows: (1) those with tumors other than MIBC, infectious diseases, hematological diseases, or severe liver or renal dysfunction and (2) those who underwent partial cystectomy. The last follow-up was conducted on October 1, 2022. Disease stage was defined according to the American Joint Committee on Cancer (AJCC) tumor-lymph node-metastasis (TNM) Staging System, 8th edition. The study design was approved by the appropriate ethics review board.Patients first underwent maximum TURBT and received PD-1 inhibitor and radiotherapy with or without chemotherapy 2 to 3 weeks later. PD-1 inhibitors included 200 mg of tirelizumab administered or 240 mg of toripalimab both administered intravenously every 3 weeks for an expected duration of 1 year. Some patients with good tolerance received concurrent chemotherapy with gemcitabine  plus cisplatin (50–75 mg/m2) every three weeks for four cycles. Intensity-modulated radiation therapy was used for external irradiation, which was planned with the Varian Eclipse Treatment Planning System version 11.0  and delivered with 6-MV X-rays using Varian 23EX .Gross tumor volume (GTV) includes bladder tumors and positive lymph nodes, which, was confirmed using computed tomography (CT), magnetic resonance imaging (MRI), cystoscope, or positron-emission tomography (PET), and the clinical target volume (CTV) included the whole bladder and regional-nodal basin. The planning target volume was delineated by margins of 7–10 mm around the GTV and CTV. Cone-beam CT was performed weekly. The CTV dose was 45–50 Gy with 1.8 or 2 Gy administered daily, and the GTV dose was 66 Gy, with 2 Gy administered daily. Imaging  and cystoscopy biopsies were performed 12 weeks after radiotherapy and every three months during follow-up to evaluate the therapeutic effect.Clinical information, including age, sex, physical status, T stage, PD-L1 expression, pathological differentiation, treatment strategy, and imaging results, was collected.SPSS software version 26.0  was used for statistical analysis. The major endpoint was the clinical complete response (cCR) rate 12 weeks after radiotherapy. The secondary endpoints were disease-free survival (DFS), OS, and objective response rate (ORR). cCR was defined as the absence of any tumor during TURBT (12 weeks after radiotherapy) and no evidence of a local tumor, lymph node metastasis, or distant metastasis on CT or MRI. OS was defined as survival from the date of diagnosis to death or final follow-up. DFS was defined as survival from the date of diagnosis to disease recurrence, death (for any reason), or final follow-up. ORR refers to the proportion of patients whose tumors shrank to a certain size and remained at that size for a certain time, including complete remission and partial remission. ORR was evaluated using the evaluation standard of solid tumor efficacy version 1.1 (RECIST v1.1).A Kaplan–Meier univariate analysis was performed to assess the 1-year OS and DFS rates. Statistical differences between survival curves were evaluated using the log-rank test. Multivariate Cox proportional hazard models were created using factors influencing prognosis, as shown in previous studies . Fisher’A total of 25 patients were included in the analysis. The median follow-up time was 13  months. Patient characteristics are summarized in Twenty-five patients underwent bladder-sparing treatment combined with ICI administration, 23 patients (92%) had cCR, and 2 (8%) had PR. The ORR rate was 100%. The 1-year OS and DFS rates were 96% and 92%, respectively Table 2.Among the 25 patients, 3 patients had intravesical recurrence, 2 of whom received systemic treatment, 1 of whom was received TURBT again. In addition, 1 patient died of multiple metastases.In total, 92% of patients in this study experienced AEs. Among these patients, 35.7% experienced grade 3 or 4 AEs, and the common adverse events were fatigue (14.3%), cystitis (7.1%), nausea and vomiting (14.3%), thrombocytopenia (14.3%), and leukopenia (7.1%). Immune-related AEs were mainly fatigue (50%), hypothyroidism (44%), and skin pruritus (40%). Except for fatigue, all AEs were of grade 1 or 2 Table 3.In the field of bladder-conserving therapy, many types of bladder-preserving treatment modes are combined with immunotherapy, including TMT, radiotherapy, and chemotherapy. Among these, immunotherapy combined with TMT is the most widely studied. A study on pembrolizumab combined with CCRT for MIBC included 28 patients, and the CR rate was 88% . AnotherStudies on immunotherapy combined with radiotherapy comprised patients who were unable to tolerate chemotherapy. A study of concurrent nivolumab and radiotherapy for older adult patients with MIBC with a median age of 78 years showed that 6 of 14 patients had CR . AnotherAnyway, compared with traditional bladder-preserving treatment, the preliminary CR rate of immunotherapy combined with TMT was 83–100%, while the CR rate of traditional TMT was approximately 75% . The CR The immune drugs involved in the bladder preservation study included pembrolizumab, nivolumab, ipilimumab, atezolizumab, durvalumab, tremelimumab, tislelizumab, and toripalimab. Until now, to our knowledge, no head-to-head studies have compared the differences between these drugs. This study enrolled patients who received tislelizumab as well as those who received toripalimab and found that there was no difference in efficacy and prognosis between these two drugs. Tislelizumab and toripalimab have been approved by the China Food and Drug Administration for the posterior line treatment of bladder urothelial carcinoma , 25. OneWe aimed to determine the predictive factors for the efficacy of bladder-sparing therapy combined with ICIs. PD-L1 expression is the most widely studied biomarker for immunotherapy. Studies on nivolumab or atezolizumab combined with radiotherapy have shown that PD-L1 expression may be a potential biomarker for ICIs with radiotherapy , 28. HowIn terms of safety, 35.7% of patients enrolled in this study experienced grade 3 or 4 AEs, and 8% experienced grade 3 or 4 IRAEs. Common AEs were fatigue, cystitis, nausea and vomiting, thrombocytopenia, and leukopenia. Hypothyroidism, skin pruritus, and fatigue were the main IRAEs. In bladder preservation studies on pembrolizumab combined with TMT, the incidence of grade 3–4 AEs was 21.4%–40% , 18, whiThis study has some limitations. First, it was a retrospective study performed at a single institution. Second, a relatively small number of patients was included. Future studies should include larger sample size, and randomized clinical studies should be conducted. Third, there is no unified standard for evaluating efficacy. In the existing research, there are many evaluation contents, including cCR, pCR, DFS, BIDFS, PFS, and OS, and a lack of long-term follow-up results. In this study, cCR was selected as the primary endpoint to evaluate short-term efficacy; however, long-term follow-up is needed to understand the long-term prognosis of patients.In this study, the addition of a PD-1 inhibitor improved the efficacy of traditional bladder-preservation therapy (TMT and TURBT plus radiotherapy) for patients with MIBC who are incompatible with RC. The treatment mode is feasible and safe, and chemotherapy and PD-L1 expression do not affect efficacy and prognosis. Despite controversies regarding this type of bladder-preservation therapy, it shows great potential.The original contributions presented in the study are included in the article/The study was conducted in accordance with the Declaration of Hensinki and approved by the appropriate ethics review board of the Second Xiangya Hospital of Central South University, Changsha, China. All methods were performed in accordance with the relevant guidelines and regulations, and informed consent was obtained from all subjects and/or their legal guardian(s).Conceptualization, JW, WZ, and YF; material support, YL; data acquisition, LZ, RX, YL, RZ; statistical analysis, JW; writing—draft, CX; revision, JW; editing, XL and YW; supervision, XL and YW. All authors commented on previous versions of the manuscript. All authors contributed to the article and approved the submitted version.


Arabidopsis. We identified distinct temporal transcriptional signatures and demonstrated the involvement of specific biological pathways. Generation of a large-scale co-expression network followed by network centrality analyses identified 117 TFs that possess critical properties of hubs, bottlenecks, and high clustering coefficient nodes. Dynamic transcriptional regulatory modeling of integrated TF targets and transcriptome datasets uncovered major transcriptional events during the course of drought stress. Mathematical transcriptional simulations allowed us to ascertain the activation status of major TFs, as well as the transcriptional intensity and amplitude of their target genes. Finally, we validated our predictions by providing experimental evidence of gene expression under drought stress for a set of four TFs and their major target genes using qRT-PCR. Taken together, we provided a systems-level perspective on the dynamic transcriptional regulation during drought stress in Arabidopsis and uncovered numerous novel TFs that could potentially be used in future genetic crop engineering programs.Drought is one of the most serious abiotic stressors in the environment, restricting agricultural production by reducing plant growth, development, and productivity. To investigate such a complex and multifaceted stressor and its effects on plants, a systems biology-based approach is necessitated, entailing the generation of co-expression networks, identification of high-priority transcription factors (TFs), dynamic mathematical modeling, and computational simulations. Here, we studied a high-resolution drought transcriptome of  Since the last century, ecological and agricultural systems have been negatively impacted by a wide spectrum of environmental cues, including biotic and abiotic stresses. Among all the abiotic stimuli that limit crop yield, drought is the most threatening environmental constraint that adversely affects plant growth and productivity ,2,3,4. AArabidopsis, it remains to be determined how temporal transcriptomic differences are governed by master regulators, including major TFs. To establish a comprehensive understanding of complex and dynamic host transcriptional regulatory responses to drought stress, a systems-level approach is necessitated that encompasses systematic, time-scale transcriptional response analyses in Arabidopsis that could be later applied to agronomically important crop plants.While diverse plant organs and tissues, including roots, shoots, and leaves, respond to drought stress in both a generalized and specialized manner , roots cArabidopsis and tomato [Arabidopsis TF ANAC016 was shown to coordinate with AREB1 and NAP (NAC-like activated by AP3/PI) TFs through a trifurcate feed-forward regulatory circuitry in response to drought [A Systems Biology-based investigation of transcriptional regulatory networks (TRNs) entails the generation of genome-wide expression networks, identification of highly influential nodes, as well as dynamic mathematical modeling, computational simulations, and probabilistic assessments of transcription ,19,20,21d tomato ,30. Mode drought . iDREM , and performed mathematical simulations that allowed us to decipher the amplitude and duration of target gene expression exerted by these six TFs. To support these computational transcriptional predictions, we provided experimental evidence of the TF-target relationship in a time-course drought qRT-PCR experiment using Arabidopsis plants. Overall, we provided a comprehensive dynamic model of the transcriptional regulatory network in Arabidopsis during drought stress and discovered several novel TFs that can be implicated in future genetic engineering crop enhancement programs. Here, we identified time-point-specific unique and shared Arabidopsis, we built a systems biology-based pipeline , we used WGCNA  [A gene co-expression network is a systems biology-based analysis that isolates and highlights various correlation patterns among a set of genes and identifies diverse modules encompassing clusters of highly correlated genes that are potentially involved in related biological pathways. Such analysis can allow the prediction of gene functions as well as the discovery of functional modules, which may provide further insights into the transcriptional gene regulatory mechanisms. Towards generating an nalysis) . Our ADGArabidopsis drought signaling. To identify the major TFs as well as additional transcriptional signatures that can significantly contribute to gene functions in the above-described molecular pathways, we next performed network architectural and centrality analyses. Since the topology of scale-free networks is largely controlled by highly connected nodes, we focused our analyses on the clustering coefficient, hubs (highly connected nodes), and bottlenecks (high betweenness nodes). Among the 592 TFs discovered in ADGCN, 51, 48, and 37 TFs exhibited high clustering coefficients, bottlenecks, and hub properties, respectively . Given tp-value ≤ 0.05). Overall, we showed that 411, 323, 602, 212, and 546 TFs were modeled in diverse paths on days 1, 3, 5, 7, and 9, respectively , AT1G51140 , AT5G56840 (a MYB-like TF), AT2G36270 , AT3G09600 , and AT2G46590  . InteresArabidopsis wild-type Col-0 plants. We collected leaf samples of drought-stressed or corresponding well-watered control plants daily over a period of ten days. Based on the activation status, transcriptional trajectories, and amplitudes of gene regulation, we further selected four TFs  and four targets for each of these TFs  was shown to be released from the ABA signaling core complex, possibly in the guard cells . MoreoveArabidopsis, and At4G08980; FBW2, a novel negative regulator of AGO1 protein levels that may play a role in ABA signaling) positively co-expressed with ABI5 , encodes a member of the basic leucine zipper TF family that is involved in ABA signaling during seed maturation and germination . The traith ABI5 . On the ith ABI5  were onlith ABI5 N,O. ThesFinally, we examined the expression levels of AT3G09600 (LCL5/RVE8), which encodes an MYB-like TF. LCL5/REV8 was shown to be involved in the regulation of circadian signaling as well as the heat shock response . We demoArabidopsis plants. Taken together, we experimentally characterized the transcriptional regulation patterns of four master TFs and their putative targets over a time course of drought stress in fbh3 mutant. As alluded to above, the transcript levels of the target genes are possibly under the control of FBH3; we tested the expression levels of CPR1, HB40, RAP2.6L, and AGL4. Compared to the Col-0 control, both the basal and MV-induced levels of these four target genes were significantly reduced in fbh3, indicating the positive regulatory control of FBH3 on its target genes  was two-fold and three-fold decreased in the lcl5 mutant compared to Col-0 under mock and oxidative stress conditions, respectively. Further, we observed a significant two-fold decrease in the transcript level of AAE3 in the lcl5 mutant plant compared to Col-0 under stress conditions. The transcript level of BBX31 was also reduced in the lcl5 mutant plants compared to Col-0 under stress conditions. However, no significant change in the transcript level of BBX31 between the Col-0 and lcl5 mutant was observed in the mock condition. We also observed a substantial decrease in the transcript level of XDH1 in the lcl5 mutant under both mock and stress conditions in comparison to Col-0 , CS873827 (ABI5), and CS840385 (LCL5) were purchased from the Arabidopsis Biological Resource Center (ABRC) and reconfirmed the mutant lines through PCR-based genotyping using TDNA insert and respective genes primers. Seeds were sown on Fafard Germination Mix in 90 mm × 68 mm Pöppelmann TEKU® round pots, and cold stratified in the cold room at 4 ℃ for three days. Plants were grown at 23 °C with a 12 h light/12 h dark cycle with a light intensity of 120 µE/m2/s and watered every three days with tap water to keep soil moisture. Ten-day-old seedlings were transplanted to 12 × 6 Landmark Plastic flats with continuous irrigation until day 18. Half of the 18-day-old population was grown without further input of water, while the other half was supplied with 3 mL of tap water per plant 2 h prior to sampling. Samples were collected daily from day 18 to day 28 and flash-frozen in liquid nitrogen followed by storage at −80 ℃. Three leaves were harvested for each replicate, and three biological replicates were prepared. For mutant analyses, samples were harvested for PCR-based genotyping of the mutant plants after 7 days of growing into the flats. Two leaves from six individual plants for each mutant line were collected to extract DNA using Edwards’s buffer. Then, the extracted DNAs were used as the template to perform PCR using the Phire Hot Start II  enzyme. The amplified PCR products were analyzed through gel electrophoresis and documented under the Gel doc . The primer sequences are listed in the All work was performed with Arabidopsis seeds were sterilized using a seed sterilization buffer containing ethanol, 10% Triton 10×, and sterile deionized (DI) water. The sterilized seeds were rinsed with sterile DI water 3–5 times. The sterile seeds were seeded on the ½ MS  media, pH 5.8, containing square plates, and stratified for 3 days at 40C in the cold room. The plates were then transferred to the controlled growth chamber, maintaining a 12 h light/12 h dark cycle and 23 °C temperature conditions for germination. Five days post germination, seedlings of each mutant line, including wild type Col-0, were transplanted to the fresh ½ MS, 2 µM methyl viologen  supplemented MS, and 2 µM paraquat  incorporated MS to simulate oxidative stress under controlled conditions. Seven days post-treatment, the plants were collected to perform anthocyanin measurements.For anthocyanin quantification, 20 mg of fresh-weight leaves from each plant group were collected to extract anthocyanin using a solution containing methanol: hydrochloric acid: water in a 25:5:70 ratio. The whole seedling was incubated in anthocyanin extraction solution in the dark for 4 h, and the samples were centrifuged at 13,000 rpm for 5 min. The supernatant of 200 uL was aliquoted into 96 wells polystyrene plate (Thermo Fisher Scientific) to quantify the absorbance using a microplate reader  at 525 nm and 657 nm and estimated the anthocyanin content using this equation: anthocyanin content = (OD525 − 0.25 × OD657) . For eacLeaf samples of Col-0 were ground with a Bead Ruptor 96-Well Plate Homogenizer. Total RNA was extracted using TRIzol  according to the manufacturer’s protocol. Briefly, 1 mL of TRIzol was used per sample. The RNA pellets were dissolved in 20 μL DEPC-treated water and quantified using BioPhotometer Plus . 10 μg of RNA samples were then treated with DNAse using the TURBO DNA-free™ Kit  in a 20 μL reaction. cDNA was synthesized using SuperScript IV reverse transcriptase first-strand synthesis kit (Invitrogen) with 2 µg DNA-free RNA in a 10 μL reaction, as described previously . PCR proArabidopsis at 0, 1, 3, 5, 7, and 9 days [Drought-related data pertinent to this study were downloaded from the NCBI Gene Expression Omnibus (GEO) database . Specifid 9 days . A custop-value ≤ 0.05) [The processed transcriptome data from GSE76827 were subjected to iDEP , which i ≤ 0.05) .Arabidopsis Drought-specific Gene Co-expression Network (ADGCN), we utilized the GSE76827 dataset that consists of transcriptome pertinent to drought-stressed aerial parts of Arabidopsis at 0, 1, 3, 5, 7, and 9 days. We employed the WGCNA and  R packages, which provide a wide spectrum of R functions and carry out diverse weighted correlation network analyses. Specifically, this package includes functions for the construction of a co-expression network, detection of various modules with different correlation coefficients, analysis of a wide range of network topological features, simulation, and visualization of data and network [Towards generating an  network . WGCNA f network . The dat network . In the  network . The edg network . After n network . Arabidopsis, we performed the Interactive Dynamic Regulatory Events Miner (iDREM) analysis on the drought-specific transcription response in Arabidopsis. The iDREM software employs static protein-DNA interaction data, including Chromatin Immunoprecipitation Sequencing (ChIP-Seq) ChIP-seq etc., and integrates with time-series gene expression data to simulate dynamic regulatory networks [Arabidopsis thaliana Regulatory Network (AtRegNet) [Arabidopsis transcriptional regulatory map (ARTM) [Arabidopsis Information Resource (TAIR) [Arabidopsis expression data were used to perform iDREM analysis. iDREM highlighted major bifurcation events and displayed TFs that exhibited significant feature changes at a given time point. The score threshold was kept as 0.01, and significance was based on path significance conditional on a split, where the minimum split percentage was 50%. On each day of bifurcation, we highlighted the overall TFs expressed; afterward, we selected the top 100 TFs from the list based on a highly regulated quantity of genes and compared them with the Arabidopsis co-expression network. GO term categories were selected with a p-value ≤ 0.05. Finally, 6 TFs were selected from this group based on high network centrality features, including degree, betweenness, and clustering coefficient. Next, we focused on the “water deprivation” functional annotation. Mathematical simulations were performed using SQUAD  [To explore the dynamic behavior of water stress on networks . For thetRegNet) , Plant CtRegNet) , Arabidop (ARTM) , Curatedp (ARTM) , TF2Netwp (ARTM) , and Athp (ARTM) ,82,83,84e (TAIR) , TF-genee (TAIR) , and drosystems) , as descsystems) . Briefly


Cells experience various stress conditions, including replicative stress, oxidative stress, toxin-induced damage, and pathogen exposure. The tumor suppressor p53 initiates intricate cellular responses to mitigate such stress. Sestrins, induced by p53, play a pivotal role in these responses. The Sestrin family has three members, with Sestrin 2 being the most extensively studied. Here, all three Sestrins are considered, with a special focus on Sestrin 2. Sestrins trigger complex signaling cascades involving kinases and kinase complexes such as mTORC, AMP-activated kinase (AMPK), and Unc-51-like protein kinase 1 (ULK1). These kinase-driven responses enable cells to defend against cellular stress, facilitate repairs, and adapt to changing conditions, preventing damage accumulation in macromolecules such as nucleic acids, proteins, and lipids, and thereby averting malignant transformation. Thus, Sestrins essentially contribute to the prevention of cancer development. Because Sestrins also support adaptation to cellular stress and can thereby promote cell survival, these stress responses can also protect malignant tumor cells. Therefore, such anti-stress responses are a double-edged sword—on the one hand they prevent the onset of neoplasia, but on the other hand they can also shield an already established malignancy from the induction of cell death.p53, a crucial tumor suppressor and transcription factor, plays a central role in the maintenance of genomic stability and the orchestration of cellular responses such as apoptosis, cell cycle arrest, and DNA repair in the face of various stresses. Sestrins, a group of evolutionarily conserved proteins, serve as pivotal mediators connecting p53 to kinase-regulated anti-stress responses, with Sestrin 2 being the most extensively studied member of this protein family. These responses involve the downregulation of cell proliferation, adaptation to shifts in nutrient availability, enhancement of antioxidant defenses, promotion of autophagy/mitophagy, and the clearing of misfolded proteins. Inhibition of the mTORC1 complex by Sestrins reduces cellular proliferation, while Sestrin-dependent activation of AMP-activated kinase (AMPK) and mTORC2 supports metabolic adaptation. Furthermore, Sestrin-induced AMPK and Unc-51-like protein kinase 1 (ULK1) activation regulates autophagy/mitophagy, facilitating the removal of damaged organelles. Moreover, AMPK and ULK1 are involved in adaptation to changing metabolic conditions. ULK1 stabilizes nuclear factor erythroid 2-related factor 2 (Nrf2), thereby activating antioxidative defenses. An understanding of the intricate network involving p53, Sestrins, and kinases holds significant potential for targeted therapeutic interventions, particularly in pathologies like cancer, where the regulatory pathways governed by p53 are often disrupted. Protein kinases serve as pivotal regulators within cellular signaling networks . ThroughThe perturbation of kinase activity can lead to profound alterations in cellular signaling, often resulting in deregulated cellular behavior. Consequently, it is not surprising that dysregulated kinases frequently exhibit oncogenic properties and play pivotal roles in promoting both the survival and proliferation of cancer cells ,3,4.There are two main types of protein kinases: (i) serine/threonine kinases and (ii) tyrosine kinases . (i)2+), calmodulin, phosphatidylinositol-3,4,5-trisphosphate (PIP3), and various derivatives of phospholipids). Serine/threonine kinases are critical components in cellular signaling networks, functioning as molecular switches that transmit extracellular signals and govern intracellular responses. Consequently, they are central to comprehending cell physiology and represent potential therapeutic targets for diseases associated with disrupted signaling pathways [Serine/threonine kinases are pivotal components of cellular signaling networks. These kinases catalyze the phosphorylation of hydroxyl groups (OH groups) attached to the amino acid residues serine and threonine. Their activity is typically modulated by second messengers  or cyclic guanosine monophosphate (cGMP), as well as 1,2-diacylglycerol (DAG), calcium ions (Ca(ii)Tyrosine kinases can be classified into two groups: membrane-bound tyrosine kinases , epidermal growth factor (EGF) receptor, insulin receptor, human epidermal growth factor receptor 2 (HER2)) and non-membrane-bound tyrosine kinases , SRC, Janus kinases). Membrane-bound tyrosine kinases include receptors with intrinsic kinase activity  and receptors with associated kinase activity (where the kinase binds to the receptor). Upon ligand binding to a membrane-bound or non-membrane-bound tyrosine kinase, conformational changes occur, promoting the formation of homodimers or heterodimers. This process triggers the autophosphorylation of specific tyrosine residues on the kinase, subsequently enabling the recruitment of additional proteins/kinases and initiating intricate signaling cascades [17, epidePrecise control of protein phosphorylation states is essential for modulating protein function, localization, and signaling, all of which are crucial for cellular homeostasis. The phosphorylation status of a protein is controlled by the finely regulated functions of kinases (phosphorylation) and phosphatases (dephosphorylation). Dysregulation of these processes can lead to diseases, also highlighting the pivotal role of phosphatases in cellular homeostasis . Taken tIn this review article, we summarize the role of kinases in p53/Sestrin-regulated stress responses. Tumor suppressor p53 is induced during cellular stress, and among its target genes are Sestrin 1, 2, and 3. These Sestrins can induce various protective responses, often relying on the activation or inhibition of multiple kinases. We explain the role of these kinases and provide an overview of the role of Sestrins in cancer.p53 is a tumor suppressor protein activated by cellular stressors such as ionizing radiation, hypoxia, carcinogens, and oxidative stress. Upon activation, p53 initiates cell-cycle arrest, promotes DNA repair, or induces apoptosis via multiple pathways ,8. BesidTP53 gene located on the short arm of chromosome 17. The gene comprises 11 exons, resulting in a 43.7 kDa protein. TP53 encompasses three promoters—two upstream of exon 1 for the transcription of full-length p53 (FLp53) and one promoter within the intronic sequence between exon 4 and 5 for the expression of Δ133p53 [p53 is encoded by the  Δ133p53 ,17. Alte Δ133p53 .The N-terminal truncated isoforms Δ40p53 result from alternative splicing of exon 2 and initiation of translation at an ATG start codon at position 40. It lacks a portion of the N-terminal transactivation domain (TAD). Δ160p53 isoforms, which lack amino acids 1–159, arise from translation initiation at an ATG start codon at position 160. To date, a comprehensive repertoire of 13 distinct p53 isoforms has been elucidated, encompassing p53, p53β, p53γ, p53Ψ, Δ40p53α, Δ40p53β, Δ40p53γ, Δ133p53α, Δ133p53β, Δ133p53γ, Δ160p53α, Δ160p53β, and Δ160p53γ ,20,21,22Since cellular stress can arise from different sources, there is also a range of stress response proteins that, alone or in interaction with others, restore cellular homeostasis. Sestrins are one group of such stress response proteins, and their regulation is closely linked to p53.The name “Sestrin” is derived from the term “SEnsor of STRess signals” combined with the suffix “-in”, which is often used in biology to denote a protein. The name reflects the primary function of Sestrins as sensors within cells that are used to detect and respond to various forms of stress. Sestrins are a family of highly conserved proteins initially discovered in the early 2000s and play a crucial role in cellular stress responses and regulation of the metabolism ,36,37,38Taken together, Sestrins are known for regulating various cellular processes, including antioxidant defense, DNA repair, autophagy/mitophagy (a process that removes damaged cellular components), and metabolism. They act as p53-controlled regulators that help cells adapt to different cellular stressors .These anti-stress responses involve two cellular complexes, mTORC1 and mTORC2. In both complexes, the catalytic subunit and central serine/threonine kinase is the target of rapamycin (mTOR). In the mTORC1 complex, the regulatory-associated protein of mTOR (Raptor) serves as a scaffold protein that helps bind substrates and regulatory proteins to mTORC1. The mammalian lethal with SEC13 protein 8 (mLST8) stabilizes the complex, while the proline-rich Akt substrate 40 kDa (PRAS40) and DEP domain-containing mTOR-interacting protein (DEPTOR) regulate the kinase activity of mTOR. In the mTORC2 complex, the rapamycin-insensitive companion of mTOR (Rictor) functions as a scaffold protein, and the protein observed with Rictor (Protor) stabilizes the complex. The mammalian stress-activated protein kinase-interacting protein 1 (mSin1) is the regulator of mTORC2 activity. Both mTORC1 and mTORC2 are crucial in the integration of extracellular signals and energy status to control cell growth and cell survival . When mTORC1 is activated, it promotes protein synthesis by phosphorylating the eukaryotic translation initiation factor 4E-BP1 and the ribosomal protein S6 kinase beta-1 (S6K1), enhancing the translation of mRNAs vital for growth and cell cycle progression. Furthermore, mTORC1 inhibits autophagy, a lysosomal degradation pathway activated during nutrient deficiency. Sestrins inhibit mTORC1 and therefore block cell cycle progression and proliferation . mTORC2,In addition, Sestrins are involved in regulating autophagy/mitophagy, a cellular process that helps remove damaged organelles via activation of Unc-51-like protein kinase 1 (ULK1) ,46,47. MThe ER lumen supports protein maturation, involving tightly regulated folding and assembly of secretory and membrane-bound proteins. Disruptions in protein folding trigger an unfolded protein response (UPR) ,49,50. TThe accumulation of cellular damage, particularly DNA damage, is responsible for the onset of diseases, including cancer. The p53/Sestrin/kinase axis protects against the accumulation of damage, thereby mitigating the development of malignancies .The p53/Sestrin/Kinase axis plays a significant role in preventing cellular stress and averting the accumulation of damage to macromolecules and organelles. Sestrins provide time for repair by modulating proliferation, protein synthesis, and metabolism. They initiate protective mechanisms that safeguard against damage .The mTOR signaling pathway, vital for cell growth and survival, is downregulated during adverse conditions, such as nutrient scarcity, genotoxic stress, and hypoxia, which activate the tumor suppressor p53 ,44,52. TmTORC1 activation is primarily driven by Rheb, a small GTPase that directly binds to mTORC1 in its GTP-bound state. Additionally, a group of small GTPases known as RagA–D further enhances mTORC1 activation . In theiCellular stress triggers the activation of p53, which subsequently induces the expression of its target genes, Sestrin 1, 2, and 3 ,40. SestAs part of p53-activated antioxidant genes, Sestrins play a crucial role in suppressing reactive oxygen species (ROS), protecting against oxidative stress, preventing genomic instability, and inhibiting cellular transformation ,40. TheySestrin 2 forms a complex with ULK1 and the autophagic cargo receptor p62/sequestosome-1 (SQSTM1). This complex facilitates the phosphorylation and degradation of p62/SQSTM1 and its associated substrate, Kelch-like ECH-associated protein 1 (Keap1), which is a major suppressor of Nrf2 . ConsequInterestingly, Sestrin 2 possesses its own cysteine sulfinyl reductase activity, enabling the reduction and recycling of oxidized Peroxiredoxin. Consequently, Sestrin 2 plays a direct role in the elimination of highly reactive hydroperoxides and is thus an essential part of the oxidative response .Autophagy is a lysosome-dependent degradation mechanism responsible for the targeted removal and recycling of cellular components such as proteins and organelles ,58. InitInhibition of mTORC1 by p53-induced Sestrin expression can activate ULK1. Once activated, ULK1 induces autophagy and phosphorylates the autophagy-related proteins 13 (Atg13), the focal adhesion kinase interacting protein of 200 kD (FIP200), and Atg101. These phosphorylation events serve as crucial triggers, initiating and activating lysosomal degradation by autophagosomes . In thisMitophagy, a specialized form of autophagy, selectively degrades damaged or dysfunctional mitochondria. It is primarily regulated by PTEN-induced kinase 1 (PINK1) and Parkin . MitophaParkin is an E3 ubiquitin ligase that plays a crucial role in cellular quality control. Upon mitochondrial damage, Parkin is recruited and undergoes phosphorylation by PINK1. Following phosphorylation, Parkin attaches ubiquitin molecules to various substrates on the mitochondrial outer membrane. This ubiquitination process marks damaged mitochondria for degradation through mitophagy. Sestrin 2 plays a pivotal role in enhancing PINK1/Parkin-mediated mitophagy through two primary mechanisms. Firstly, Sestrin 2 interacts with ULK1, which leads to the phosphorylation of Beclin1 at Ser14. This phosphorylation event promotes the binding of Beclin1 to Parkin and further phosphorylates Parkin itself. These actions facilitate the translocation of Parkin to mitochondria, a critical step in mitophagy ,62. SecoIn summary, the p53 target Sestrin 2, in collaboration with the kinases PINK1 and ULK1, plays an essential role in removing damaged mitochondria. This process prevents the accumulation of ROS and, consequently, oxidative damage to macromolecules such as lipids, proteins, and DNA.The unfolded protein response (UPR) is a cellular stress response mechanism that monitors and manages the folding of proteins within the endoplasmic reticulum (ER). When proteins cannot fold correctly or accumulate within the ER, signaling pathways within the UPR are activated. These pathways aim to restore ER homeostasis by enhancing protein folding, degrading misfolded proteins, and reducing the synthesis of new proteins. However, if the stress is severe or prolonged, the UPR can trigger cell death. The UPR is crucial for maintaining cellular function and is implicated in various diseases ,63,64.The primary transcription factor inducing the UPR is XBP1, which can induce Sestrins, particularly Sestrin 2. Through Sestrin-mediated inhibition of mTORC1, protein synthesis is slowed down, allowing more time for proper protein folding. Additionally, the induction of autophagy helps to remove damaged organelles and proteins, another crucial aspect of the UPR. In this way, Sestrins support the prevention of the accumulation of misfolded proteins and ensure the survival of the cell ,65,66.Sestrins are a group of evolutionarily conserved proteins that play important roles in various cellular processes, including those related to cancer .Sestrins are often considered tumor suppressors because they help protect cells from various forms of stress that can lead to cancer development. Sestrins primarily function by inducing stress responses that protect the cell, particularly against oxidative stress. This induction occurs through the activation of Nrf2 via the kinase ULK1  is essential for cell proliferation due to its detoxification and antioxidant defense functions. Elevated activation of Nrf2 significantly enhances the transcription of the genes responsible for NADPH production, the primary cofactor in GSH synthesis , thus prHence, the Sestrin-mediated induction of Nrf2 displays two sides of the same coin. On the one hand, it prevents the accumulation of mutations, thereby blocking tumorigenesis. On the other hand, an established tumor benefits from Nrf2 activation, as it enhances its survival and shields it from apoptosis induction .Autophagy and mitophagy are also double-edged swords. The housekeeping role of autophagy maintains the turnover of proteins and organelles, ensuring cellular homeostasis and health, thereby preventing disease conditions. In response to stress, autophagy is crucial in removing damaged proteins and organelles. This damage mitigation function of autophagy can be vital for the survival of tumor cells, which are frequently exposed to metabolic stress due to inadequate vascularization ,78. WhilSestrins induce autophagy/mitophagy through the serine/threonine kinases ULK1 and AMPK (as described in Tumor suppressor p53 is activated in response to cellular stress ,8. p53 iThe induction of such stress responses has a dual role in the context of cancer. On one hand, anti-stress responses prevent the formation and accumulation of cellular damage, thereby reducing the risk of cancer development. On the other hand, stress responses also facilitate the survival of tumor cells and complicate the treatment of cancer . Thus, i


What are the main findings?Differentially expressed milk fat QTL genes explored with whole genome se-quencing for variant analysis.Identified non-synonymous SNPs for hub and bottleneck QTL genes associated with milk fat traits.What is the implication of the main finding?Identified differential pattern(s) of SNPs in fat QTLs between high and low milk yield breeds.Impact of the identified SNP pattern(s) on milk fat traits can be further explored.Milk fat is a crucial trait that varies significantly among cattle breeds and determines the milk quality and pricing value. Indigenous breeds have disparity in milk quantity and quality. Our study is one of a kind which helps to decipher the variations at the genetic level correlated with transcriptional level among high and low milk-yielding cattle breeds exploring the fat QTLs. We assessed and unveiled a few key differences between the high and low-milk-yield breeds.GHR, TLR4, LPIN1, CACNA1C, ZBTB16, ITGA1, ANK1, and NTG5E and, vice versa, in the genes MFGE8, FGF2, TLR4, LPIN1, NUP98, PTK2, ZTB16, DDIT3, and NT5E. The identified SNPs were ratified by pyrosequencing to prove that key differences exist in fat QTLs between the high- and low-milk-yielding breeds.The effect of breed on milk components—fat, protein, lactose, and water—has been observed to be significant. As fat is one of the major price-determining factors for milk, exploring the variations in fat QTLs across breeds would shed light on the variable fat content in their milk. Here, on whole-genome sequencing, 25 differentially expressed hub or bottleneck fat QTLs were explored for variations across indigenous breeds. Out of these, 20 genes were identified as having nonsynonymous substitutions. A fixed SNP pattern in high-milk-yielding breeds in comparison to low-milk-yielding breeds was identified in the genes  India has become the largest milk producer in the world . SeveralDGAT1 on chromosome 14 [GHR) on chromosome 20 [ABCG2 [SPP1 (Osteopontin) on chromosome 6 [DGAT1 (K232A) and ABCG2 (Y581S) in Bos taurus have been suggested to be associated with increased fat yield and fat and protein percent in milk with a decrease in milk yield [GHR mutation F279Y has been observed to have a significant effect on milk composition (fat and protein percentage) and milk yield [SPP1 has also been found to have a significant effect on milk production and milk composition [DGAT1 and ABCG2 genes have been found to be fixed among Indian breeds Sahiwal, Rathi, Deoni, Tharparkar, Red Kandhari, and Punganur [Milk being a polygenic trait with medium heritability, the majority of animal breeding research has centered on quantitative trait loci (QTLs) with moderate to large effects on milk production traits. The osome 14 ,6, the gosome 20 , and the0 [ABCG2  or SPP1 mosome 6  are well ABCG2 Y51S in Boslk yield ,11,12,13position . HoweverPunganur . CurrentPunganur .p ≤ 0.0001), protein (p ≤ 0.05), total solids (p ≤ 0.05), fat (p ≤ 0.05), milk urea nitrogen (p ≤ 0.001), and ash (p ≤ 0.0001) content of milk [Milk is the primary source of nutrition for infants, as well as adults. Besides its nutritional value, it has a major role in imparting growth and immunity through intrinsic milk components such as growth factors, chemokines, anti-inflammatory molecules, antioxidants, prebiotics, and probiotics ,9. Milk  of milk .India, with a huge diversity of 50 cattle breeds, forms an ideal ground to study genetic variation at the genomic level vis-à-vis milk traits . The cosBos taurus [QTL genes associated with milk fat traits (milk fat content and percentage) and metabolism were extracted from the Animal QTLdb database , and thes taurus . The ints taurus  considers taurus . A totals taurus .Bos indicus genome (GCF_003369695.1) using STAR Version 2.5.4b with the default parameters [The publicly available milk transcriptome bioproject ID (PRJNA419906) was used to analyze the expression of QTL genes associated with milk fat traits. This bioproject was considered in this study as it has data generated from Jersey (a breed with high fat content ranging from 4.10–4.86%) and Kashmiri (a breed with low fat content ranging from 3.20–3.94%) . The datme GCF_0069695.1 urameters , and diframeters . The difIndigenous cattle breeds for the proposed study were grouped into high- and low-milk-yield-breed groups. The high-milk-yield group (avg milk yield per day 8 kg) included Sahiwal (n = 4) and Gir (n = 4), and the low-milk-yield group (avg milk yield per day 2.5 kg) included 6 animals representing the breeds Gaolao, Deoni, Hallikar, Dangi, Pulikulam, and Amritmahal . AnimalsBos indicus reference genome (Brahman-GCF_003369695.1) using BWA aligner [Sequencing data generated on an Illumina platform were pre-processed for quality assessment and improvement  by FastP . All hig aligner . Variant aligner  and GATK aligner . For the aligner  for Q >  aligner .GHR, LPIN1, and TLR4. GHR was one of the genes having the maximum number of interactions in the network. LPIN1 had the maximum SNP count of 10, whereas TLR4 was one of the top 10 highly upregulated genes. PCR and sequencing primers were designed using PyroMark Assay Design Software 2.0 (Qiagen). The PCR amplification was performed in a 20 µL reaction, with the thermal cycling conditions, which included an initial denaturation of 95 °C for 3 min followed by 40 cycles of 95 °C for 30 s, 65 °C for 30 s, 72 °C for 1 min, and a final extension of 72 °C for 10 min. Sequence analysis was performed by PyroMark Q48 Autoprep software Version 2.4.2 in SNP analysis assay mode for 14 animals.Three nsSNPs that were found to be distinctly different between the high- and low-milk-yield groups were selected for validation and were genotyped in PyroMark Q48 (Qiagen) as per the manufacturer’s protocol. These nsSNPs were found in the differentially expressed hub and bottleneck genes The schematic representation of the study is given in Animal QTLdb was used to extract fat-trait-associated QTL genes. In the QTLdb, after the removal of duplicate genes , 286 andFASN, GPAT4, DGKG, ELOVL6, and LIPIN1  has library sizes ranging from 7764992200–13682843400 bp and 6842583600–12088807400 bp, for Jersey and Kashmiri, respectively . FurtherA total of 70 genes were found to be upregulated and 52 genes downregulated in the Jersey breed in comparison with the Kashmiri breed. Differentially expressed transcripts (DETs) were also explored for fat QTL genes . The volCSN2), and Casein alpha s1 (CSN1S1) were identified to be among the highly expressed top 20 genes , which is more readily recognized by the TLR4 receptor. The list of top 10 upregulated and downregulated DEGs is given in In both the Jersey and Kashmiri breeds, Beta-lactoglobulin (LOC113901792), Casein beta  with a log2 fold change of 1.480587, followed by DGAT1 with a degree of 25 and a log2FC of 0.921104.A protein interaction network analysis was performed among 417 milk fat QTL genes, and the interaction network was generated with 403 nodes and 671 edges. Based on the degree of association, 50 hub and 50 bottleneck genes were selected from the network . A totalck genes . SRC hadIllumina short read (Paired end) data of 14 samples from both groups of high- and-low-milk-yield breeds had 12.77 billion reads. After preprocessing, clean data included 11.02 billion reads, which is ca. 1516 Gb data. Each dataset had a minimum sequencing depth of ≥30x with an average GC content of 45.26%. The processed datasets contained on average 97.91% Q20 bases and 93.97% Q30 bases. The high-quality trimmed data aligned to the Brahman reference genome with an overall alignment rate of >95%. Initial variant calling on the aligned data provided 63,357,363 variants, which were filtered for high quality. After quality filtering on Q20, a total of 33,976,892 SNPs were identified across the genomes . Upon GAGHR, TLR4, LPIN1, CACNA1C, ZBTB16, ITGA1, ANK1, and NTG5E  as against SNPs C/C, C/C, and G/G in the Gir and Sahiwal breed (high-milk-yield), respectively  in the low-milk-yield group. Another LPIN1 variant, g.85205642T>G, was observed in the high-milk-yield group, but was fixed in the low-milk-yield group. LPIN1 and ITGA1 had the maximum SNP count of 10, and the genes PTK2, IGF1R, DDIT3, CXCL8, and LPL had the least SNP count  and low-  milk-yield indigenous breeds. This understanding of low- and high-milk-yield breeds for milk fat quality may help in enhancing the quality of milk in the long run.The CXC motif chemokine ligand 8 was the most-upregulated gene. It is reported to be involved in various biological pathways such as increased insulin resistance, uncoupling of the GH/IGF1 axis, and an increase in mammary cell proliferation to improve metabolic health and milk yield [DGKG), another upregulated gene, is a member of the type I diacylglycerol kinases and is highly upregulated (log2FC = 4.03) in Jersey. It plays a role in lipid metabolism by modulating the balance between diacylglycerol and phosphatidic acid. Phosphatidic acid is a lipid second messenger to activate protein kinase C isoforms, ras guanyl nucleotide-releasing proteins, and some transient receptor potential channels [ETS2) [OLR1, PARM1) [SLC6A9) (log2FC = 4.49) [SLC45A4) [TG) [KCNK9) [UGDH), which is involved in the biosynthesis of glycosaminoglycans, hyaluronan, chondroitin sulfate, and heparan sulfate, has been found (log2FC = 0.75) to be upregulated in the Jersey breed. UGDH’s expression pattern in liver cells has been associated with an indispensable role in the metabolism of carbohydrates, fats, and proteins in dairy cattle [UGDH has been found close to two reported QTLs for fat yield, fat percentage, and protein yield [To explore the fat QTL genes, MEC RNA-seq data were processed and analyzed. The high level of similarity within breeds and relatively low variation between lactation confirmed the selection of RNA-seq data to explore differences between breeds rather than to explore difference in lactation stages of breeds. Among the highly expressed genes identified, it was observed that the Jersey breed has allocated more resources for the immune system, whereas the Kashmiri breed for regulation of ribosomal proteins. Among the top 10 upregulated genes, lk yield . Diacylgchannels . Most ofs [ETS2) , adipocy, PARM1) ,47, gluc = 4.49) , glucoseA4) [TG) , and ald [KCNK9) . The upry cattle . Moreovein yield .GRH13 is a transcription factor that mediates the proliferation of epithelial cells [MTMR3/3-PAP, a catalytically inactive member of the myotubularin gene family that coprecipitates the activity of lipid phosphatidylinositol 3-phosphate-3-phosphatase, is upregulated [MATN2) and prolyl 4 hydroxylase (P4HA3), which are important to maintaining the newly synthesized collagen’s stability, are also upregulated [P4HA3 catalyzes the formation of 4-hydroxyproline (Hyp), which ensures the proper folding of procollagens during post-translational modification. The upregulation of MATN2 and P4HA3 probably may help in increasing the elasticity of the udder gland in Jersey during lactation. Further, the downregulation of MFGE8 and ELOVL16 may be responsible for the high fat content in milk and the shift to C18 from C16 fatty acids, respectively, in Jersey. MFGE8 regulates the absorption of free fatty acids and increases intracellular triglycerides’ hydrolase activity, thereby restricting the storage of fat [ELOVL16) elongates C16 saturated and monounsaturated fatty acids to C18 fatty acids [IDH1, which catalyzes the conversion of isocitrate to α-ketoglutarate and generates the primary source of NADPH for de novo fatty acid synthesis [2FC = −1.632). The dysregulation of the genes MFGE8, EVOLVL16, and IDH1 might be responsible for the variation in the fat yield and composition in Jersey and Kashmiri cows. In addition, the decreased expression of these genes may be linked to the increased expression of genes involved in metabolism, glucose transport, and other transport activities, leading to higher milk production performance in Jersey.During lactation, various morphological changes happen in the mammary tissue to support cellular differentiation, tissue elasticity, and reduced fat storage capacity in the animal. Upregulated al cells . Similaregulated  in Jerseegulated ,57. P4HAe of fat , whereasty acids . Furtherynthesis , has beeSRC was identified as the top hub gene interacting with several genes in the protein–protein interaction network. SRC, a non-receptor tyrosine kinase, performs a wide variety of cellular functions in terms of metabolism and is primarily involved in impaired glucose uptake [DGAT1) and ecto-5′-nucleotidase (NT5E) possess hub and bottleneck gene features. DGAT1 encodes a protein that catalyzes the conversion of diacylglycerol and fatty acyl CoA to triacylglycerol. DGAT1 is one of the highly studied genes for milk yield and fat quality [NT5E gene encodes a plasma membrane protein that catalyzes the conversion of extracellular nucleotides to membrane-permeable nucleosides. SRC and DGAT1 were found to be highly upregulated in Jersey with log2FC = 1.48 and log2FC = 0.92, respectively. In the network, DGAT1 was found to interact with Glycerol-3-phosphate acyltransferase 4 (GPAT4) . This gene has been found to be involved in triglyceride biosynthesis and is comprised of acyltransferase motifs, which are essential for binding to substrates and catalyzing acyltransferase reactions. The AGPAT6 gene, which is highly expressed in mammary gland epithelium during lactation [NT5E was found to interact with BDNF, NTRK2, and ZNRF4. NT5E is involved in various biological process such as adenosine biosynthetic process, AMP catabolic process, leukocyte cell–cell adhesion, and negative regulation of inflammatory response [DGKG, which was upregulated, was found to be a bottleneck gene in the network and had interactions with PRKCG and RNT. Phosphatidate phosphatase (LPIN1), an enzyme involved in lipid metabolism [PPARA and PPARGC1A. LPIN1 is involved in various biological processes related to lipid metabolism such as the triglyceride biosynthetic process, the fatty acid catabolic process, and the regulation of transcription by RNA polymerase II [PTK2 is well known for its association with milk production traits [CACNA1A has a role in hormone regulation of lactation [ZBTB16 is involved in bovine adipogenesis [NUP98 is associated with protein percentage [TLR4 is a mastitis-associated marker [FGF2 expression is reported to be associated with milk production traits [GHR, TLR4, LPIN1, CACNA1C, MFGE8, PTK2, ZBTB16, FGF2, and NUP98) were identified. These fat QTL nsSNPs may have a role in the existing fat and milk yield differences between the breed groups. However, further studies to evaluate the impact of these SNPs on fat yield/percentage or milk yield need to be carried out.Among the ten QTLdb milk and milk trait genes that were differentially expressed and had hub and bottleneck gene characteristics, four genes were found enriched in metabolic pathways . SRC wase uptake . Genes D quality ,63. The actation , was alsresponse . DGKG, wtabolism , was uprerase II . The genn traits , and CACactation . Similarogenesis . NUP98 ircentage . TLR4 isd marker . FGF2 exn traits . In thisGHR, TLR4, LPIN1, CACNA1C, ZBTB16, ITGA1, ANK1, and NTG5E, and the opposite was observed in the genes MFGE8, FGF2, TLR4, LPIN1, NUP98, PTK2, ZTB16, DDIT3, and NT5E. The role of these SNPs needs to be further explored.In this study, initially, DEGs in Jersey epithelial cells were identified, and these were further explored in the QTL database as being the major hub and bottleneck genes. The transcriptome in Jersey indicated higher expression of genes involved in metabolism, glucose transport, and other transport activities, leading to higher milk production performance. The 20 differentially expressed hub and bottleneck fat QTL genes were explored for non-synonymous genomic variants in the whole-genome sequence data, which were generated from fourteen animals. The fixed SNP pattern in high-milk-yield breeds in comparison to low-milk-yield breeds was observed in the genes


Glioma is a mixed solid tumor composed of neoplastic and non-neoplastic components. Glioma-associated macrophages and microglia (GAMs) are crucial elements of the glioma tumor microenvironment (TME), regulating tumor growth, invasion, and recurrence. GAMs are also profoundly influenced by glioma cells. Recent studies have revealed the intricate relationship between TME and GAMs. In this updated review, we provide an overview of the interaction between glioma TME and GAMs based on previous studies. We also summarize a series of immunotherapies targeting GAMs, including clinical trials and preclinical studies. Specifically, we discuss the origin of microglia in the central nervous system and the recruitment of GAMs in the glioma background. We also cover the mechanisms through which GAMs regulate various processes associated with glioma development, such as invasiveness, angiogenesis, immunosuppression, recurrence, etc. Overall, GAMs play a significant role in the tumor biology of glioma, and a better understanding of the interaction between GAMs and glioma could catalyze the development of new and effective immunotherapies for this deadly malignancy. Despite surgical resection, targeted radiotherapy, combined chemotherapy, and newer developed treatments like tumor-treating fields (TTF), the prognosis of GBM patients remains very poor . The medAlthough many types of immune cells within the lymphoid lineages have been detected in the TME, glioma-associated macrophages and microglia (GAMs) are the predominant immune population in the solid GBM, comprising up to one-third of the tumor mass –9. This 2Microglia are a critical innate immune component in the CNS and represent 10-15% of all glial cells . Due to 2.1Microglia derive from hematopoietic precursor cells of the yolk sac during early embryonic development , 21, andin vivo and in vitro experimental models of microglia, the investigation of microglia in the context of tumors remains limited. Alongside primary microglia cells extracted from experimental animals or human brains, immobilized murine (BV-2) and human (HMO6) microglia cell lines have been developed  and infiltrating macrophages (CD45high)  originate from hematopoietic stem cells  and infiD45high) , and in ectively . Howeverectively . To date2.3+ T cell function into T helper (Th) 1 and Th2 lineages (γ (IFN-γ)  and M2 polarization type for anti-inflammatory (protumor), referring to the dichotomy of CD4lineages . Ponomarlineages . Numeroulineages , 45–47.  (IFN-γ) . M1 type (IFN-γ) . In the  (IFN-γ) , 48. Inf (IFN-γ) . M1 micr (IFN-γ) , 50. Typ (IFN-γ) , 52. In  (IFN-γ) . M2-pola (IFN-γ) . We have (IFN-γ) . M2a and (IFN-γ) , 56, whi (IFN-γ) –59.Recent single-cell sequencing studies on GBM suggest that individual cells can express genes promoting inflammation (M1) and genes promoting immunosuppression (M2) , 61. The3Glioma-associated microglia/macrophages (GAMs) are not passive bystanders in the tumor microenvironment, but actively evolve with tumors through feedback and feedforward mechanisms Figure 13.1in vivo and in vitro studies, where the MCP-1 expression level is highly correlated with the grade of glioma -1 ) , MCP-3 , stroma-f glioma . A recenf glioma . M-CSF if glioma . Gliomasf glioma .In recent years, researchers have suggested alternative factors that might impact the recruitment of GAMs and M2 polarization, such as peritumoral hypoxia microenvironment-induced factors and GSCs . Hypoxia3.2in vivo models   and CXCL2 . Depletivessels) . Furthervessels) , 90–93. vessels) . Consistvessels) .3.3In vitro studies have shown that conditioned medium derived from glioma cells can activate the STAT3 pathway of microglia, promoting their polarization towards the M2 subtype and secretion of IL-6 and IL-10 (The immune-escape mechanism of GBM relies on two main factors: the intrinsic characteristics of neoplastic cells and the immunosuppressive TME mediated by GAMs. Glioma cells are difficult to identify by the immune due to their downregulation of human leukocyte antigen (HLA) molecules that cover the surface specific tumor antigen molecules . Howevernd IL-10 .A recent study found that blocking the breakdown of interferon gamma inducible protein 16 (IFI16) with drugs can activate the STAT3 signaling pathway . This pa3.4in vitro and express common markers such as nestin, Sox2, and Musashi-1 -based chemotherapy, and enables them to cause tumor recurrence , 113. Thma cells . These mma cells , 116. GAma cells , 95. GSCma cells , 117. Inreported . These fConversely, GAMs have been shown to play a role in promoting GSCs –122. Res4The rapid development of new tumor treatment technologies and a deeper understanding of CNS have led to significant progress in immunotherapy for glioma . Some ofTable 2Therapeutic drugs targeting GAMs in glioma.in vivo /CSF-1R signal is considered a key factor in GAMs recruitment and M2 polarization. Therefore, researchers have explored drugs targeting this pathway. Treatment with the anti-CSF-1R antibody pexidartinib (PLX3397) significantly reduces GL261-associated GAM infiltration and inhibits M2 polarization, thereby inhibiting glioma growth . PLX3397SDF-1 (CXCL12) is another factor crucial in GAMs recruitment, especially under normoxic conditions. The Food and Drug Administration (FDA)-approved drug for the treatment of multiple myeloma and lymphoma, SDF-1 inhibitor Plerixafor, is currently being evaluated in two clinical trials for its potential therapeutic effect against glioma , 133. AsMicroglia/macrophages exhibit strong phagocytic activity. However, in glioma, the phagocytosis of GAMs is greatly reduced, due to the high expression of CD47 along with signal regulatory protein alpha (SIRPa) on the surface of GAMs , 146. ThRecent studies have shown that olfactomedin Like 3 (OLFML3) exhibits an anti-glioma effect by regulating GAMs infiltration under the influence of the biological clock, and a positive correlation between the survival of GBM patients and the expression level of OLFML3 has been reported .5Although researchers have extensively studied the origin, evolution, recruitment, and other mechanisms of microglia/macrophages, the role of GAMs in TME is still poorly understood. This is because the underlying mechanisms do not act in isolation in the tumor context. Glioma cells and various components of the TME form a complex interaction network. Although novel therapies are being developed, GBM recurrence remains a challenge. A deeper understanding of various aspects of GAM biology may provide useful insights for the development of effective strategies for glioma immunotherapy. Moreover, understanding the role of the TME in the development and evolution of tumorigenic cells from a broader perspective, rather than limiting the focus to glioma cells and their transformation, would provide a holistic perspective. For example, the niche of GSCs, which influences tumor diversity and drug resistance, is of great research significance. In the future, the combined treatment with chemotherapy drugs as well as monotherapies involving immunotherapeutic strategies may prove useful in improving the life quality of glioma patients.Conceived and designed the review: CYX. Wrote and revise the paper: CL and NW. All authors contributed to the article and approved the submitted version.


Microglia, the resident macrophages of the central nervous system, are essential players during physiological and pathological processes. Although they participate in synaptic pruning and maintenance of neuronal circuits, microglia are mainly studied by their activity modulating inflammatory environment and adapting their phenotype and mechanisms to insults detected in the brain parenchyma. Changes in microglial phenotypes are reflected in their morphology, membrane markers, and secreted substances, stimulating neighbor glia and leading their responses to control stimuli. Understanding how microglia react in various microenvironments, such as chronic inflammation, made it possible to establish therapeutic windows and identify synergic interactions with acute damage events like stroke. Obesity is a low-grade chronic inflammatory state that gradually affects the central nervous system, promoting neuroinflammation development. Obese patients have the worst prognosis when they suffer a cerebral infarction due to basal neuroinflammation, then obesity-induced neuroinflammation could promote the priming of microglial cells and favor its neurotoxic response, potentially worsening patients’ prognosis. This review discusses the main microglia findings in the obesity context during the course and resolution of cerebral infarction, involving the temporality of the phenotype changes and balance of pro- and anti-inflammatory responses, which is lost in the swollen brain of an obese subject.1 polarization and priming, which enhances stroke-associated damage, increasing M1 and decreasing M2 responses.Obesity enhances proinflammatory responses during a stroke. Obesity-induced systemic inflammation promotes microglial M Nowadays, urban lifestyle, exposure to hypercaloric food and drinks, and lack of physical activity contribute to overweight and obesity development in the general population worldwide , insulin-like growth factor 1 (IGF-1), and glial cell-derived neurotrophic factor (GDNF), among others  as a response to macrophage colony-stimulating factor CSF-1 or IL-34. This cell division by microglia is a relevant feature in pathology-rich areas where damaged cells need to be replaced   make it challenging to define neuroinflammation in humans with animal models accurately. Nevertheless, there are shared markers among different species, such as the transmembranal protein 119 (TMEM119); this protein is abundant in the prenatal periods 11b, F4/80, CX3CR1, P2Y12R, and TMEM119  microenvironment is needed to keep microglia attenuated  to maintain homeostatic neuronal functions , they trigger an inflammatory state which is strictly regulated and silenced over time. In this state, microglia secrete cytokines to communicate with neighbor cells, alerting and influencing their functions. This state is known as M1 and was named for its analogy with the macrophage activation state, which enhances antigen presentation, produces and secretes proinflammatory cytokines IL-1β, IL-6, IL-12, IL-18, tumor necrosis factor ⍺ (TNF⍺), IFNγ, and chemokines CCL2, CCL5, CCL20, CXCL1, CXCL9, among others , such as lipopolysaccharide (LPS), or cellular damage signals (DAMPs), like membrane lipids or adenosine triphosphate (ATP), using pattern recognition receptors (PRR), mainly Toll-like receptors (TLR) and NOD-like Receptors (NLR), but also purinergic-, Fc-, complement-, scavenger-, chemokine-, and cytokine- receptors, and other recognition proteins that can activate microglia to polarize to a classically activated state   Fig. .1 state, microglia can be stimulated by anti-inflammatory factors and alternatively be activated to perform neuroprotective, neuroregenerative, anti-inflammatory, and tissue reparative responses , TLR4, or Fc receptors, performing enhanced phagocytosis functions, acting as cell debris and immune complexes cleaner; they also secrete anti-inflammatory cytokines. At last, exposure to glucocorticoids, IL-10, and TGFβ promote the Mc2 phenotype, which focuses its mechanisms on immunoregulation, matrix deposition, and tissue remodeling by enhancing arginase 1 (ARG1) activity, secreting chemokine CXCL13 and overregulating scavenger receptors A1 and B1   Fig. .2 phenotype is considered anti-inflammatory and upregulates surface markers such as CD206 and CD163, promotes tissue regeneration, waste removal, neurogenesis, remyelination, and neurite outgrowth through the secretion of IGF-1, BDNF, and miR-124-3P; it also induces autophagy and blood–brain barrier (BBB) repair through the secretion of anti-inflammatory cytokines and growth factors  is considered an endocrine organ due to its adaptability to the body’s energy needs and its production of several proteins that regulate hunger and satiety, including hormones such as leptin and insulin, and cytokines; these factors are known as adipokines and perform several different functions , where the responses to leptin in DVC glia showed that astrocytes and microglia mediate the anorexigenic effects of leptin in lean rats but not in HFD-induced obese rats  inclusions, suggesting an aberrant engulfing capacity. These findings correlate with increased depression and anxiety-like behaviors in HFD-fed mice compared to healthy mice  mice, demonstrated that the KO of NHE1, an essential regulator of aerobic glycolysis in microglia, directly affects the phagocytic functions of these cells resulting in increased microglial phagocytic capacity and helps neuronal remodeling, improving cognitive function after infarction , normal weight (BMI 18.5–24.9 kg/m2), class I obesity—overweight (BMI 25.0–29.9 kg/m2), class II obesity—obesity (BMI 30.0–39.9 kg/m2), class III obesity—extreme obesity (BMI > 40 kg/m2) 5 and lower levels of IRF4; these proteins regulate an inflammatory axis during stroke induced by middle cerebral artery occlusion (MCAO), which comes into detrimental effects in mice, also validated with its transgenic knockout IRF4 and IRF5 variants (Ngwa et al. Even though obesity-related mechanisms for enhancing neurological pathologies are not fully understood, experimental and human studies have shown that obesity and overweight are associated with low-grade systemic chronic inflammation, and microglia-directed proinflammatory responses (Bruce-Keller et al.


In this paper, H2S and ABA crosstalk as well as the underlying mechanism of crosstalk-induced thermotolerance in maize seedlings were investigated. The data show that endogenous levels of H2S and ABA in maize seedlings could be mutually induced by regulating their metabolic enzyme activity and gene expression under non-heat stress (non-HS) and HS conditions. Furthermore, H2S and ABA alone or in combination significantly increase thermotolerance in maize seedlings by improving the survival rate (SR) and mitigating biomembrane damage. Similarly, the activity of the reactive oxygen species (ROS)-scavenging system, including enzymatic antioxidants catalase (CAT), ascorbate peroxidase (APX), guaiacol peroxidase (POD), glutathione reductase (GR), monodehydroascorbate reductase (MDHAR), dehydroascorbate reductase (DHAR), and superoxide dismutase (SOD), as well as the non-enzymatic antioxidants reduced ascorbic acid (AsA), carotenoids (CAR), flavone (FLA), and total phenols (TP), was enhanced by H2S and ABA alone or in combination in maize seedlings. Conversely, the ROS level  was weakened by H2S and ABA alone or in combination in maize seedlings under non-HS and HS conditions. These data imply that the ROS-scavenging system played an essential role in H2S-ABA crosstalk-induced thermotolerance in maize seedlings.Hydrogen sulfide (H Currently, the research on H2S was actively turned to its signaling role from toxic gas molecules in plants [2S, can be rapidly synthesized and triggered by signaling pathways when plants are subjected to environment stimuli, and even stress, but they maintain homeostasis in plant cellular and subcellular compartments under normal physiological conditions [2S homeostasis in plant cells is strictly controlled by anabolic and catabolic enzymes located in the various subcellular compartments. These metabolic enzymes include L-/D-cysteine desulfhydrase (L/DCD), O-acetylserine (thiol)lyase A1 (OAS-TL A1), and L-cysteine desulfhydrase 1  in the cytosol; sulfite reductase (SiR) and OAS-TL B in chloroplast; and β-cyanoalanine synthase (CAS), OAS-TL C, and nitrogenase Fe-S cluster (NifS) in mitochondria [2S signaling or maintain H2S homeostasis in plants [2S, as a novel gasotransmitter, could increase multiple-stress tolerance in plants [2S-induced system tolerance to salt and osmotic stress occurs by minimizing the oxidative  and nitrosative  stress via the transcriptional regulation of the ROS-scavenging system [2S improved the thermotolerance in strawberry plants through regulating the transcription of heat shock proteins (HSPs) and aquaporin (AQP) [Hydrogen sulfide  .Abscisic acid (ABA), a sesquiterpene, is a phytohormone that regulates seed germination, plant growth, development, and response to environmental stress. ABA can be rapidly synthesized under stress conditions, such as extreme temperature (high and low temperature), salt, and drought stress, and thus increases the stress tolerance in plants ,9. There2S and ABA can exert their physiological functions in plants in a synergistic or antagonistic manner. These physiological functions are involved in stomatal movement [2S signaling via activating LCD [2S and ABA alone could improve the multiple-stress tolerance including heat stress tolerance in plants, which has very important significance for agriculture, but the effect of their combined treatment on thermotolerance in maize plants still remains elusive. Hence, understanding the mechanism underlying H2S-ABA interaction-induced thermotolerance in maize is important to breed a climate-resilient and thermotolerant variety for maize production. This paper, using maize as the materials, aims to uncover the mechanism underlying H2S-ABA interaction-induced thermotolerance in maize seedlings.Many studies show that Hmovement ,17, planmovement , and strmovement ,19. Thouting LCD , its phyting LCD ,22,23,242S and ABA alone, or in combination, could induce thermotolerance in maize seedlings.After HS and, subsequent, recovery at 26 °C for one week, the survival rate of the seedlings irrigated with NaHS and ABA alone, or in combination, was counted. The results show that, compared with the control, the survival rate (SR) of the maize seedlings irrigated with NaHS and ABA alone, or in combination, after HS was significantly improved, the SR was increased to 78%, 82%, and 85%, respectively, from 52% in the control, especially irrigation with NaHS and ABA in combination was more significant among the treatments A. Simila2S-ABA crosstalk, before and after HS, the contents of endogenous H2S and ABA, as well as the activities by their metabolic enzymes in seedlings irrigated with NaHS and ABA alone or in combination, NaHS combined with ST or FLU, as well as ABA combined with PAG, HA, or HT, were determined. The data indicate that, before HS, the endogenous H2S content was significantly increased by NaHS and ABA alone, or in combination, and the combination resulted in a more obvious increase  and ABA and its metabolic enzymes  is shown in 2S was positively correlated with ABA, ZEP, NCED, and AAO, as well as with ABA, and AAO, and NCED reached significant levels.After the correlation analysis, the correlation between H2S, as a novel signaling molecule, and ABA, as a stress hormone, can exert their physiological functions in an independent or dependent (antagonistic or synergistic) manner in plants [2S interacts with ABA remains elusive. In this paper, using maize seedlings as the materials, we found that H2S interacted with ABA by mutually modulating their endogenous levels via metabolic enzyme activity and corresponding gene expression  in the maize seedlings, which in turn increased the level of endogenous ABA under both non-HS and HS conditions  in the maize seedlings, followed by increasing the level of endogenous H2S under both non-HS and HS conditions  and very significant (for NCED) difference  in the mesocotyls of the maize seedlings was obviously up-regulated by NaHS and ABA alone or in combination, particularly NaHS combined with ABA had the most significantly molecular effect among the irrigations  seeds were purchased from the Shiling Seed Company, China, as materials. The healthy seeds were selected and sterilized in 5% sodium hypochlorite solution for 10 min, and then washed neatly and soaked at 26 °C for 12 h in distilled water. The soaked seeds were germinated at 26 °C for 2.5 d on six-layer filter papers watered with distilled water in trays with covers (at least 200 seeds per tray). The 2.5 d old seedlings were divided into nine groups and then separately irrigated with 75 mL of the following solutions for 12 h: (1) distilled water , (2) 500 μM NaHS, (3) 50 μM ABA, (4) 50 μM ABA + 500 μM NaHS (ABA + NaHS), (5) 500 μM sodium tungstate + 500 μM NaHS (ST + NaHS), (6) 50 μM fluoridone + 500 μM NaHS (FLU + NaHS), (7) 500 μM propargylglycine + 50 μM ABA (PAG + ABA), (8) 500 μM hydroxylamine + 50 μM ABA (HA + ABA), and (9) 500 μM hypotaurine + 50 μM ABA (HT + ABA). Among the chemicals, NaHS, PAG, HA, and HT are H2S donors, inhibitors, and scavengers [In this study, maize  of the 2S-ABA crosstalk on thermotolerance in maize seedlings, after HS and recovery, the survival rate (SR), tissue viability (TV), biomembrane peroxidation, and electrolyte leakage (EL) of the seedlings irrigated with NaHS and ABA alone or in combination were separately measured, according to the methods reported by Wang et al. [−1 fresh weight (FW), respectively. To study the effect of Hg et al. . The sur2S content and its metabolic enzyme activity, the seedlings were irrigated with NaHS alone or combined with the ABA inhibitors ST and FLU, as well as ABA alone or combined with the H2S scavenger HT and the inhibitors HA and PAG. After irrigation and HS, the H2S content and activity of LCD, DCD, and OAS-TL in seedling mesocotyls were analyzed, as per the procedures by Ye et al. [2S content was expressed in nmol g−1 FW, whereas the LCD, DCD, and OAS-TL activities were indicated as nmol min−1 mg−1 protein. The content of the soluble proteins in the seedling mesocotyls was analyzed using the Bradford method [To investigate the effect of ABA on He et al. . The H2Sd method , using b2S on the ABA content and its metabolic enzyme activity, the seedlings were irrigated with NaHS alone or combined with the ABA inhibitors ST and FLU, as well as ABA alone or combined with the H2S scavenger HT and the inhibitors HA and PAG. After irrigation and HS, the ABA content and activity of ZEP, NCED, and OAA in seedling mesocotyls were determined, as per the procedures in the instruction book for the kits. The ABA content was expressed in μg g−1 FW, whereas the ZEP, NCED, and OAA activities were expressed in nmol min−1 mg−1 protein. Similarly, to explore the effect of H2S-ABA crosstalk-induced thermotolerance in maize seedlings, after irrigation and HS, the ROS-scavenging system activity of the seedlings irrigated with NaHS and ABA alone or in combination were estimated according to Elavarthi et al. [−1 cm−1) at 40 (240 nm), 26.6 (470 nm), 2.8 (290 nm), 21.6 (560 nm), 6.2 (340 nm), 14.0 (265 nm), and 14.0 (265 nm), respectively. Their activities were indicated as nmol min−1 mg−1 protein, except SOD which was indicted as μmol min−1 mg−1 protein. To further understand the mechanism underlying Hi et al.  and Wangi et al. . The act−1 FW, μg g−1 FW, and nmol g−1 FW.Similarly, the non-enzymatic ROS-scavenging system, namely ascorbic acid (AsA), carotenoids (CAR), flavanone (FLA), and total phenols (TP) in the seedling mesocotyls were extracted and estimated as per the reports by Elavarthi et al.  and Wang2S-ABA crosstalk on the ROS level, after irrigation and HS, the generation rate for the superoxide radical (O2.−) and hydrogen peroxide (H2O2) content in seedlings irrigated with NaHS and ABA alone or in combination was determined according to the titanium sulfate method [2.− production and H2O2 content were calculated using the millimolar extinction coefficient at 21.6 and 0.28 mM−1 cm−1, and expressed as nmol min−1 g−1 FW and nmol g−1 FW, respectively.To estimate the effect of He method  and Na,3e method . The O2.2S-ABA crosstalk on the gene expression of the H2S- and ABA-metabolic enzymes and the enzymatic ROS-scavenging system, after irrigation and HS, the genes ZmLCD1, ZmOAS-TL, ZmZEP, ZmNCED, ZmOAA, ZmCAT1, ZmSOD4, ZmGR1, ZmAPX1, ZmDHAR, and ZmMDHAR in the seedling mesocotyls were quantified by qRT-PCR (using Zea mays beta-5 tubulin (ZmTUB) as an internal reference), and the relative expression level was calculated using 2−∆∆CT [To further explore the effect of Hg 2−∆∆CT . For then = 5), and the same and different letters indicate the insignificant and significant difference, respectively. Also, to further estimate the correlation among the parameters, the correlation between H2S and its metabolic enzymes and ABA and its metabolic enzymes, as well as SR and the thermotolerance index, antioxidant enzymes, non-enzymatic antioxidant, and ROS was analyzed using Pearson correlation in SigmaPlot 25 software. In the tables, r represents the correlation coefficient , and the asterisk (*) and double asterisks (**) indicate significant (p < 0.05) and very significant difference (p < 0.01), respectively.The experiments were a random design and the significance analysis between the data was performed as a one-way analysis of variance (ANOVA) and Duncan multiple-range test at the 0.05 level. The data in the figures represent mean ± standard error  and ABA  biosynthesis. The H2S-ABA crosstalk induced the thermotolerance in maize seedlings by improving the survival rate (SR) and tissue viability (TV), as well as relieving electrolyte leakage (EL) and MDA accumulation. In sum, the crosstalk between HZmCAT1, ZmSOD4, ZmGR1, ZmAPX1, ZmDHAR, and ZmMDHAR) in maize seedlings before and after HS. These data indicate the essential role of the ROS-scavenging system in H2S-ABA crosstalk-induced thermotolerance in maize seedlings, which lays the foundation for breeding a heat-resilient crop variety, and are very important for maize production.Also, the ROS-scavenging system was enhanced by NaHS and ABA alone or in combination via activation of the enzymatic system  and the non-enzymatic system , as well as the up-regulation of the gene expression of the corresponding enzymes (i.e.,


The p53 protein is an important tumor suppressor, and TP53 mutations are frequently low survival rates of cancer patients. Mutations in TP53 lead in loss of tumor suppressing functions which result in the development of tumors. Meanwhile, several tripartite motif (TRIM) proteins are known to regulate cell growth and cell cycle transition. However, the relationship between TRIM family genes and TP53 mutations in cancer remains unknown. In this study, we analyzed the links between TP53 mutations and TRIM family proteins and evaluated the role of TRIM family proteins in cancer patients with TP53 mutation. Our findings identified the TRIM family members that are highly expressed in TP53 mutant tumors and important for the cell growth in the context of TP53 mutations. TP53 mutations and TRIM family proteins and evaluated the prognostic significance of TRIM family proteins in cancer patients with P53 mutations. Our findings identified specific TRIM family members that are upregulated in TP53 mutant tumors and are associated with the activation of genes related to a cell-cycle progression in the context of TP53 mutations.The p53 protein is an important tumor suppressor, and TP53 mutations are frequently associated with poor prognosis in various cancers. Mutations in TP53 result in a loss of p53 function and enhanced expression of cell cycle genes, contributing to the development and progression of cancer. Meanwhile, several tripartite motif (TRIM) proteins are known to regulate cell growth and cell cycle transition. However, the prognostic values between TP53 and TRIM family genes in cancer are unknown. In this study, we analyzed the relationship between the  The TP53 gene is a high-frequency target of mutations in human cancers . The p53The tripartite motif (TRIM) proteins belong to a large protein family, which are characterized by the presence of a conserved N-terminal RBCC module consisting of a Really Interesting New Gene (RING) domain, one or two B-Boxes (B1/B2) and a coiled-coil (CC) domain. So far, more than 80 TRIM family members have been identified in humans . These TRecent studies have revealed the interplay between TRIM proteins and p53 levels and activity ,7. The cThe human hepatocellular carcinoma cell line HepG2 was purchased from the ATCC. Cells were cultured in DMEM with 10% FBS. 30% Hydrogen peroxide was purchased from Sigma . Lentiviral vectors for shRNA against human TP53 were a gift from Dr. Dung-Fang Lee. Total RNA was extracted using Direct-zol™ RNA MiniPrep (Zymo Research), and cDNA was synthesized using random hexamers and ImProm-II™ Reverse Transcription System . The synthesized cDNA was diluted 1:10 in nuclease-free water for PCR amplification. Quantitative real-time PCR was performed using SYBR Green MasterMix Plus  on ABI-7900  with an initial temperature of 95 °C for 10 min, followed by 40 cycles of 15 s at 95 °C, 30 s at 60 °C, and 30 s at 72 °C. The primer sequences are described in For immunoblotting, cells were collected and lysed in Laemmli sample buffer. Proteins were separated by SDS-PAGE and transferred onto the PVDF membrane. Anti-p53  and anti-β-actin  antibodies were used to probe the membrane, followed by blotting with ECL reagent. β-actin’s expression levels were set as internal controls to normalize target protein expression.HEK293FT cells were transfected with either shRNA against human TP53 or a lentivirus vector plasmid coupled with pMD2.G and psPAX2 by using calcium phosphate precipitation. Lentiviruses were collected 48 and 72 h post-transfection and concentrated via ultracentrifugation. For transduction, HepG2 cells were treated with 5 μg/mL polybrene and transduced with lentivirus. Medium containing lentivirus particles was replaced with regular medium after 24 h. At 96 h post-transduction, cells were selected with 1 μg/mL puromycin for 7 days, to generate stable cell lines.https://www.gsea-msigdb.org/gsea/msigdb/ assessed on 24 November 2022) , TRIM11 , TRIM24 , TRIM25 , TRIM28 , TRIM32 , TRIM44 , TRIM45 , and TRIM59  were associated with a shorter overall survival time in LIHC patients with TP53 mutations , utations . Howeverutations . p = 0.04], TRIM10 , TRIM27 , TRIM32 , TRIM39 , and TRIM52  were associated with a poorer overall survival time , p < 0.0001], TRIM15 , TRIM28 , and TRIM47  had prognostic values , val time , while ic values .To investigate the clinical relevance of TRIMs in TP53 mutant tumors, we analyzed mRNA expression profiles of tumors from 12 types of cancer. For each type of cancer, we compared the transcriptional levels of TRIM family members in samples with TP53 mutations to those in wild-type TP53 samples . ImportaOn the other hand, except for TRIM39 and TRIM52, there is no difference in the expression levels of TRIM genes between mutant TP53 and wild-type TP53 COAD tumors . Except Altogether, the results showed that the upregulation of the TRIM genes, which are associated with poor prognosis of patients with mutant TP53 tumors, was mainly observed in LIHC.2O2 also decreased the mRNA levels of several TRIM genes including TRIM3, TRIM11, TRIM24, TRIM25, TRIM28, TRIM32, and TRIM44  upregulated in mutant TP53 liver tumors with high expression of TRIM1 D, TRIM25A recent study established the mutant TP53 gene expression signature based on the aggregated expression of four genes, CDC20, PLK1, CENPA, and KIF2C. These four genes were almost invariably significantly overexpressed in all cancer types with mutant TP53. Moreover, these genes have been established as (a) targets of wild-type p53 repression, (b) promoters of cell cycle progression, (c) components of the G2/M checkpoint, and (d) established E2F targets (with the exception of CENPA) . The corTaken together, these results suggest that these TRIM genes are correlated with TP53 signatures, and that TP53 mutation-mediated upregulation of TRIM family members may contribute to the enhanced expression of genes related to a cell-cycle progression in the context of TP53 mutations.Using NetworkAnalyst, we predicted potential miRNAs that may regulate TRIM family members A. SeveraAs a transcription factor, p53 plays a critical role in tumor suppression by binding to p53 DNA-binding elements in its target genes to regulate their expression. Through transcriptional regulation, p53 influences key biological processes, such as apoptosis, cell cycle arrest, senescence, DNA repair, cell metabolism, and antioxidant defense . The majActivation of the p53 tumor suppression function can lead to cell cycle arrest and suppression of a number of E2F target genes. The key mechanism of p53-mediated arrest is the transcriptional downregulation of many cell cycle genes. Notably, mutant TP53 cancer cells exhibit an enhanced expression of cell-cycle progression genes and S-phase-promoting E2F target genes .Some TRIM proteins, when knocked down or silenced, cause an increase in the percentage of cells in G0/G1 and a reduction in the fraction of cells in S or G2 m phases. In particular, TRIM8, TRIM14, TRIM27, TRIM28, TRIM29, TRIM52, TRIM59, TRIM66, and TRIM68 are known to cause cell cycle arrest when depleted or silenced . HoweverThe interactions between p53 and miRNAs were first demonstrated through the identification of several miRNAs as direct targets of p53. As a transcription factor, p53 mainly exerts its function through its transcriptional regulation of protein-coding target genes to initiate cellular responses. Recent studies have revealed a novel mechanism for p53 in tumor suppression: p53 induces the expression of specific miRNAs, which show tumor suppressive functions. miRNAs are responsible for the downregulation of many mRNAs and proteins following p53 activation . A recenAmong the identified miRNAs, mir-34a-5p regulates TRIM25, TRIM11, TRIM32, TRIM28, TRIM3, and TRIM6. Previous studies have shown that p53 directly regulates the expression of the miR-34 family members, which consist of miR-34a, miR-34b, and miR-34c ,29. The In summary, our study demonstrated that upregulation of TRIM11, TRIM25, TRIM28, TRIM32, TRIM44, TRIM45, and TRIM59 is associated with TP53 mutations and may contribute to the activation of the cell cycle. We propose that these TRIM family members may play a crucial role in the TP53-mediated upregulation of cell-cycle-specific progression genes. Furthermore, our findings suggest that p53 may regulate TRIM family members through specific miRNAs. Future investigations are necessary to identify the precise miRNAs that modulate TRIM family members. Our results provide a novel perspective on the TRIM family functions in cancers.