Ferritinophagy-mediated ferroptosis of spermatogonia is involved in busulfan-induced oligospermia in the mice.

Busulfan, a bifunctional alkylated chemotherapeutic agent, has male reproductive toxicity and induce oligospermia, which is associated with ferroptosis. However, the specific target cells of busulfan-induced oligospermia triggered by ferroptosis are largely elusive, and the detailed mechanisms also require further exploration. In the present study, busulfan (0.6, and 1.2 mM, 48 h) causes ferroptosis in GC-1 spg cells through inducing Fe2+, ROS and MDA accumulation and functional inhibition of Xc-GSH-GPX4 antioxidant system. After inhibition of ferroptosis by Fer-1 (1 µM, pretreatment for 2 h) or DFO (10 µM, pretreatment for 2 h) reverses busulfan-induced destructive effects in GC-1 spg cells. Furthermore, using RNA-seq and Western blotting, we found that busulfan promotes autophagy-dependent ferritin degradation, as reflected by enriching in autophagy, increased LC3 II, Beclin1 and NCOA4, as well as decreased P62 and ferritin heavy chain 1 (FTH1). Ultimately, GC-1 spg cells and Balb/c mice were treated with busulfan and/or 3-MA, the inhibitor of autophagy. The results displayed that inhibition of autophagy relieves busulfan-induced FTH1 degradation and then blocks the occurrence of ferroptosis in GC-1 spg cells and testicular spermatogonia, which subsequently alleviates busulfan-caused testicular damage and spermatogenesis disorders. In summary, these data collectively indicated that ferroptosis of spermatogonia is involved in busulfan-induced oligospermia and mediated by autophagy-dependent FTH1 degradation, identifying a new target for the therapy of busulfan-induced male infertility.

Identification of Germline Mutations in East-Asian Young Never-Smokers with Lung Adenocarcinoma by Whole-Exome Sequencing.

Recently, an increasing number of young never-smokers are diagnosed with lung cancer. The aim of this study is to investigate the genetic predisposition of lung cancer in these patients and discover candidate pathogenic variants for lung adenocarcinoma in young never-smokers. Peripheral blood was collected from 123 never-smoking east-Asian patients diagnosed with lung adenocarcinoma before the age of 40. Whole-exome sequencing (WES) was conducted on genomic DNA extracted from peripheral blood cells. As a result, 3,481 single nucleotide variants were identified. By bioinformatical tools and the published gene list associated with genetic predisposition of cancer, pathogenic variants were detected in ten germline genes: ATR, FANCD2, FANCE, GATA2, HFE, MSH2, PDGFRA, PMS2, SDHB, and WAS. Patients with pathogenic variants were more likely to occur in females (9/10, 90.0%) and have stage IV lung adenocarcinoma (4/10, 40%). Furthermore, germline mutations in 17 genes (ASB18, B3GALT5, CLEC4F, COL6A6, CYP4B1, C6orf132, EXO1, GATA4, HCK, KCP, NPHP4, PIGX, PPIL2, PPP1R3G, RRBP1, SALL4, and TTC28), which occurred in at least two patients, displayed potentially pathogenic effects. Gene ontology analysis further showed that these genes with germline mutations were mainly located in nucleoplasm and associated with DNA repair-related biological processes. The study provides spectrum of pathogenic variants and functional explanation for genetic predisposition of lung adenocarcinoma in young never-smokers, which sheds a light on prevention and early diagnosis of lung cancer. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-022-00062-1.

hUMSCs Transplantation Regulates AMPK/NR4A1 Signaling Axis to Inhibit Ovarian Fibrosis in POI Rats.

BACKGROUND: The mechanism of human Umbilical Cord Mesenchymal Stem Cells (hUMSCs) transplantation to improve ovarian function in the rats with Premature Ovarian Insufficiency (POI) is still unclear. The aim of this study is to investigate the signal axis mechanism that is involved in the ovarian function recovery of POI rats following hUMSCs transplantation. METHODS: The rat model with POI was established by intraperitoneal injection of cisplatin. The hUMSCs were transplanted by caudal vein injection into POI rats. Hematoxylin-eosin (H&E) staining was performed to examine the morphology of rat ovarian tissue. Masson staining, Sirus red staining and immunofluorescence were used to observe the fibrosis extent of ovarian tissue. The levels of serum sex hormones and the expression of fibrosis related markers in ovarian tissues were measured by enzyme-linked immunosorbent assay (ELISA). The expression of NR4A1, Phospho-NR4A1 and AMP-activated protein kinase (AMPK) signaling in rat ovarian tissues was measured by immunohistochemistry and immunofluorescence. The role of AMPK/NR4A1 signaling axis in the regulation of ovarian function recovery in POI rats following hUMSCs transplantation was further investigated by adenovirus and siRNA intervention in isolated stromal cells. RESULTS: The results showed that the hUMSCs transplantation significantly inhibited ovarian tissue fibrosis and restored the ovarian function in POI rats. The level of NR4A1 and AMPK expression in ovarian tissue of POI rats after hUMSCs transplantation was significantly increased compared with the control group. In the cultured ovarian stromal cells, the similar results were obtained on the expression of NR4A1 and its regulation on fibrosis related molecular markers in Cisplatin (CDDP) damaged stromal cells following hUMSCs supernatant treatment. Both hUMSCs supernatant treatment and the addition of AMPK inhibitors increased NR4A1 expression in stromal cells. And after NR4A1 molecular intervention, fibrosis-related indicators in stromal cells changed. The data suggests that the AMPK/NR4A1 signaling axis is involved in the ovarian function changes in POI rats following hUMSCs transplantation. CONCLUSION: The data from this study indicate that the inhibition of tissue fibrosis and recovery of ovarian function is regulated by AMPK/NR4A1 signaling axis in POI rats following hUMSCs transplantation.

hUCMSCs reduce theca interstitial cells apoptosis and restore ovarian function in premature ovarian insufficiency rats through regulating NR4A1-mediated mitochondrial mechanisms.

BACKGROUND: Human umbilical cord mesenchymal stem cells (hUCMSCs, retrospectively registered) have a lot of promise for treating theca interstitial cells(TICs) dysfunction in premature ovarian insufficiency (POI). The mechanisms, however, are still unknown. METHODS: To examine the therapeutic and find the cause, we used both in vivo cisplatin-induced POI rat model and in vitro TICs model. HUCMSCs were injected into the tail veins of POI rats in an in vivo investigation. Then, using ELISA, HE staining, TUNEL apoptosis test kit, immunohistochemistry and western blot, researchers examined hormonal levels, ovarian morphology, TICs apoptosis, NR4A1 and Cyp17a1 in response to cisplatin treatment and hUCMSCs. TICs were obtained from the ovaries of rats and treated with the cisplatin, hUCMSCs supernatant, and the antagonist of NR4A1--DIM-C-pPhOH. ELISA, immunofluorescence, flow cytometry, JC-1 labeling and western blot analysis were used to detect T levels, Cyp17a1, NR4A1, and the anti-apoptotic protein Bcl-2, as well as pro-apoptotic proteins Bax, caspase-9, caspase-3, and cytochrome C(cytc). RESULTS: We discovered that hUCMSCs restored the ovarian function, particularly TICs function based on measures of Cyp17a1 and T expression. NR4A1 was found in ovarian TICs of each group and NR4A1 expression was lower in the POI rats but higher following hUCMSCs therapy. The apoptosis of TICs generated by cisplatin was reduced after treatment with hUCMSCs. In vitro, NR4A1 was expressed in the nucleus of TICs, and NR4A1 as well as phospho-NR4A1 were decreased, following the apoptosis of TICs was emerged after cisplatin treatment. Interestingly, the localization of NR4A1 was translocated from the nucleus to the cytoplasm due to cisplatin. HUCMSCs were able to boost NR4A1 and phospho-NR4A1 expression while TICs' apoptosis and JC-1 polymorimonomor fluorescence ratios reduced. Furthermore, Bcl-2 expression dropped following cisplatin treatment, whereas Bax, cytc, caspase-9, and caspase-3 expression rose; however, hUCMSCs treatment reduced their expression. In addition, DIM-C-pPhOH had no effect on the NR4A1 expression, but it did increase the expression of apoptosis-related factors such as Bax, cytc, caspase-9, and caspase-3, causing the apoptosis of TICs. CONCLUSIONS: These data show that hUCMSCs therapy improves ovarian function in POI rats by inhibiting TICs apoptosis through regulating NR4A1 -mediated mitochondrial mechanisms.

Targeting HSPA1A in ARID2-deficient lung adenocarcinoma.

Somatic mutations of the chromatin remodeling gene ARID2 are observed in ∼7% of human lung adenocarcinomas (LUADs). However, the role of ARID2 in the pathogenesis of LUADs remains largely unknown. Here we find that ARID2 expression is decreased during the malignant progression of both human and mice LUADs. Using two KrasG12D -based genetically engineered murine models, we demonstrate that ARID2 knockout significantly promotes lung cancer malignant progression and shortens overall survival. Consistently, ARID2 knockdown significantly promotes cell proliferation in human and mice lung cancer cells. Through integrative analyses of ChIP-Seq and RNA-Seq data, we find that Hspa1a is up-regulated by Arid2 loss. Knockdown of Hspa1a specifically inhibits malignant progression of Arid2-deficient but not Arid2-wt lung cancers in both cell lines as well as animal models. Treatment with an HSPA1A inhibitor could significantly inhibit the malignant progression of lung cancer with ARID2 deficiency. Together, our findings establish ARID2 as an important tumor suppressor in LUADs with novel mechanistic insights, and further identify HSPA1A as a potential therapeutic target in ARID2-deficient LUADs.

SMAD7 and SERPINE1 as novel dynamic network biomarkers detect and regulate the tipping point of TGF-beta induced EMT.

Epithelial-mesenchymal transition (EMT) is a complex nonlinear biological process that plays essential roles in fundamental biological processes such as embryogenesis, wounding healing, tissue regeneration, and cancer metastasis. A hallmark of EMT is the switch-like behavior during state transition, which is characteristic of phase transitions. Hence, detecting the tipping point just before mesenchymal state transition is critical for understanding molecular mechanism of EMT. Through dynamic network biomarkers (DNB) model, a DNB group with 37 genes was identified which can provide the early-warning signals of EMT. Particularly, we found that two DNB genes, i.e., SMAD7 and SERPINE1 promoted EMT by switching their regulatory network which was further validated by biological experiments. Survival analyses revealed that SMAD7 and SERPINE1 as DNB genes further acted as prognostic biomarkers for lung adenocarcinoma.

Branched-Chain Amino Acid Metabolic Reprogramming Orchestrates Drug Resistance to EGFR Tyrosine Kinase Inhibitors.

Drug resistance is a significant hindrance to effective cancer treatment. Although resistance mechanisms of epidermal growth factor receptor (EGFR) mutant cancer cells to lethal EGFR tyrosine kinase inhibitors (TKI) treatment have been investigated intensively, how cancer cells orchestrate adaptive response under sublethal drug challenge remains largely unknown. Here, we find that 2-h sublethal TKI treatment elicits a transient drug-tolerant state in EGFR mutant lung cancer cells. Continuous sublethal treatment reinforces this tolerance and eventually establishes long-term TKI resistance. This adaptive process involves H3K9 demethylation-mediated upregulation of branched-chain amino acid aminotransferase 1 (BCAT1) and subsequent metabolic reprogramming, which promotes TKI resistance through attenuating reactive oxygen species (ROS) accumulation. Combination treatment with TKI- and ROS-inducing reagents overcomes this drug resistance in preclinical mouse models. Clinical information analyses support the correlation of BCAT1 expression with the EGFR TKI response. Our findings reveal the importance of BCAT1-engaged metabolism reprogramming in TKI resistance in lung cancer.

Erratum: Lina Lu et al.; Low-Grade Dysplastic Nodules Revealed as the Tipping Point during Multistep Hepatocarcinogenesis by Dynamic Network Biomarkers. Genes 2017, 8, 268.

The authors wish to make the following correction to their paper [...].

Genome-wide dynamic network analysis reveals a critical transition state of flower development in Arabidopsis.

BACKGROUND: The flowering transition which is controlled by a complex and intricate gene regulatory network plays an important role in the reproduction for offspring of plants. It is a challenge to identify the critical transition state as well as the genes that control the transition of flower development. With the emergence of massively parallel sequencing, a great number of time-course transcriptome data greatly facilitate the exploration of the developmental phase transition in plants. Although some network-based bioinformatics analyses attempted to identify the genes that control the phase transition, they generally overlooked the dynamics of regulation and resulted in unreliable results. In addition, the results of these methods cannot be self-explained. RESULTS: In this work, to reveal a critical transition state and identify the transition-specific genes of flower development, we implemented a genome-wide dynamic network analysis on temporal gene expression data in Arabidopsis by dynamic network biomarker (DNB) method. In the analysis, DNB model which can exploit collective fluctuations and correlations of different metabolites at a network level was used to detect the imminent critical transition state or the tipping point. The genes that control the phase transition can be identified by the difference of weighted correlations between the genes interested and the other genes in the global network. To construct the gene regulatory network controlling the flowering transition, we applied NARROMI algorithm which can reduce the noisy, redundant and indirect regulations on the expression data of the transition-specific genes. In the results, the critical transition state detected during the formation of flowers corresponded to the development of flowering on the 7th to 9th day in Arabidopsis. Among of 233 genes identified to be highly fluctuated at the transition state, a high percentage of genes with maximum expression in pollen was detected, and 24 genes were validated to participate in stress reaction process, as well as other floral-related pathways. Composed of three major subnetworks, a gene regulatory network with 150 nodes and 225 edges was found to be highly correlated with flowering transition. The gene ontology (GO) annotation of pathway enrichment analysis revealed that the identified genes are enriched in the catalytic activity, metabolic process and cellular process. CONCLUSIONS: This study provides a novel insight to identify the real causality of the phase transition with genome-wide dynamic network analysis.

Low-Grade Dysplastic Nodules Revealed as the Tipping Point during Multistep Hepatocarcinogenesis by Dynamic Network Biomarkers.

Hepatocellular carcinoma (HCC) is a complex disease with a multi-step carcinogenic process from preneoplastic lesions, including cirrhosis, low-grade dysplastic nodules (LGDNs), and high-grade dysplastic nodules (HGDNs) to HCC. There is only an elemental understanding of its molecular pathogenesis, for which a key problem is to identify when and how the critical transition happens during the HCC initiation period at a molecular level. In this work, for the first time, we revealed that LGDNs is the tipping point (i.e., pre-HCC state rather than HCC state) of hepatocarcinogenesis based on a series of gene expression profiles by a new mathematical model termed dynamic network biomarkers (DNB)-a group of dominant genes or molecules for the transition. Different from the conventional biomarkers based on the differential expressions of the observed genes (or molecules) for diagnosing a disease state, the DNB model exploits collective fluctuations and correlations of the observed genes, thereby predicting the imminent disease state or diagnosing the critical state. Our results show that DNB composed of 59 genes signals the tipping point of HCC (i.e., LGDNs). On the other hand, there are a large number of differentially expressed genes between cirrhosis and HGDNs, which highlighted the stark differences or drastic changes before and after the tipping point or LGDNs, implying the 59 DNB members serving as the early-warning signals of the upcoming drastic deterioration for HCC. We further identified the biological pathways responsible for this transition, such as the type I interferon signaling pathway, Janus kinase-signal transducers and activators of transcription (JAK-STAT) signaling pathway, transforming growth factor (TGF)-ß signaling pathway, retinoic acid-inducible gene I (RIG-I)-like receptor signaling pathway, cell adhesion molecules, and cell cycle. In particular, pathways related to immune system reactions and cell adhesion were downregulated, and pathways related to cell growth and death were upregulated. Furthermore, DNB was validated as an effective predictor of prognosis for HCV-induced HCC patients by survival analysis on independent data, suggesting a potential clinical application of DNB. This work provides biological insights into the dynamic regulations of the critical transitions during multistep hepatocarcinogenesis.

Local network component analysis for quantifying transcription factor activities.

Transcription factors (TFs) could regulate physiological transitions or determine stable phenotypic diversity. The accurate estimation on TF regulatory signals or functional activities is of great significance to guide biological experiments or elucidate molecular mechanisms, but still remains challenging. Traditional methods identify TF regulatory signals at the population level, which masks heterogeneous regulation mechanisms in individuals or subgroups, thus resulting in inaccurate analyses. Here, we propose a novel computational framework, namely local network component analysis (LNCA), to exploit data heterogeneity and automatically quantify accurate transcription factor activity (TFA) in practical terms, through integrating the partitioned expression sets (i.e., local information) and prior TF-gene regulatory knowledge. Specifically, LNCA adopts an adaptive optimization strategy, which evaluates the local similarities of regulation controls and corrects biases during data integration, to construct the TFA landscape. In particular, we first numerically demonstrate the effectiveness of LNCA for the simulated data sets, compared with traditional methods, such as FastNCA, ROBNCA and NINCA. Then, we apply our model to two real data sets with implicit temporal or spatial regulation variations. The results show that LNCA not only recognizes the periodic mode along the S. cerevisiae cell cycle process, but also substantially outperforms over other methods in terms of accuracy and consistency. In addition, the cross-validation study for glioblastomas multiforme (GBM) indicates that the TFAs, identified by LNCA, can better distinguish clinically distinct tumor groups than the expression values of the corresponding TFs, thus opening a new way to classify tumor subtypes and also providing a novel insight into cancer heterogeneity. AVAILABILITY: LNCA was implemented as a Matlab package, which is available at http://sysbio.sibcb.ac.cn/cb/chenlab/software.htm/LNCApackage_0.1.rar.