Core Circadian Clock Genes Regulate Leukemia Stem Cells in AML.

Leukemia stem cells (LSCs) have the capacity to self-renew and propagate disease upon serial transplantation in animal models, and elimination of this cell population is required for curative therapies. Here, we describe a series of pooled, in vivo RNAi screens to identify essential transcription factors (TFs) in a murine model of acute myeloid leukemia (AML) with genetically and phenotypically defined LSCs. These screens reveal the heterodimeric, circadian rhythm TFs Clock and Bmal1 as genes required for the growth of AML cells in vitro and in vivo. Disruption of canonical circadian pathway components produces anti-leukemic effects, including impaired proliferation, enhanced myeloid differentiation, and depletion of LSCs. We find that both normal and malignant hematopoietic cells harbor an intact clock with robust circadian oscillations, and genetic knockout models reveal a leukemia-specific dependence on the pathway. Our findings establish a role for the core circadian clock genes in AML.

Prognosis Prediction of Disulfidptosis-Related Genes in Bladder Cancer and a Comprehensive Analysis of Immunotherapy.

As a newly discovered mechanism of cell death, disulfidptosis is expected to help diagnose and treat bladder cancer patients. First, data obtained from public databases were analyzed using bioinformatics techniques. SVA packages were used to combine data from different databases to remove batch effects. Then, the differential analysis and COX regression analysis of ten disulfidptosis-related genes identified four prognostically relevant differentially expressed genes which were subjected to Lasso regression for further screening to obtain model-related genes and output model formulas. The predictive power of the prognostic model was verified and the immunohistochemistry of model-related genes was verified in the HPA database. Pathway enrichment analysis was performed to identify the mechanism of bladder cancer development and progression. The tumor microenvironment and immune cell infiltration of bladder cancer patients with different risk scores were analyzed to personalize treatment. Then, information from the IMvigor210 database was used to predict the responsiveness of different risk patients to immunotherapy. The oncoPredict package was used to predict the sensitivity of patients at different risk to chemotherapy drugs, and its results have some reference value for guiding clinical use. After confirming that our model could reliably predict the prognosis of bladder cancer patients, the risk scores were combined with clinical information to create a nomogram to accurately calculate the patient survival rate. A prognostic model containing three disulfidptosis-related genes (NDUFA11, RPN1, SLC3A2) was constructed. The functional enrichment analysis and immune-related analysis indicated patients in the high-risk group were candidates for immunotherapy. The results of drug susceptibility analysis can guide more accurate treatment for bladder cancer patients and the nomogram can accurately predict patient survival. NDUFA11, RPN1, and SLC3A2 are potential novel biomarkers for the diagnosis and treatment of bladder cancer. The comprehensive analysis of tumor immune profiles indicated that patients in the high-risk group are expected to benefit from immunotherapy.

RGA1 alleviates low-light-repressed pollen tube elongation by improving the metabolism and allocation of sugars and energy.

Low-light stress compromises photosynthetic and energy efficiency and leads to spikelet sterility; however, the effect of low-light stress on pollen tube elongation in the pistil remains poorly understood. The gene RGA1, which encodes a Gα-subunit of the heterotrimeric G-protein, enhanced low-light tolerance at anthesis by preventing the cessation of pollen tube elongation in the pistil of rice plants. In this process, marked increases in the activities of acid invertase (INV), sucrose synthase (SUS) and mitochondrial respiratory electron transport chain complexes, as well as the relative expression levels of SUTs (sucrose transporter), SWEETs (sugars will eventually be exported transporters), SUSs, INVs, CINs (cell-wall INV 1), SnRK1A (sucrose-nonfermenting 1-related kinase 1) and SnRK1B, were observed in OE-1 plants. Accordingly, notable increases in contents of ATP and ATPase were presented in OE-1 plants under low-light conditions, while they were decreased in d1 plants. Importantly, INV and ATPase activators (sucrose and Na2 SO3 , respectively) increased spikelet fertility by improving the energy status in the pistil under low-light conditions, and the ATPase inhibitor Na2 VO4 induced spikelet sterility and decreased ATPase activity. These results suggest that RGA1 could alleviate the low-light stress-induced impairment of pollen tube elongation to increase spikelet fertility by promoting sucrose unloading in the pistil and improving the metabolism and allocation of energy.

Acid invertase confers heat tolerance in rice plants by maintaining energy homoeostasis of spikelets.

Heat stress impairs both pollen germination and pollen tube elongation, resulting in pollination failure caused by energy imbalance. Invertase plays a critical role in the maintenance of energy homoeostasis; however, few studies investigated this during heat stress. Two rice cultivars with different heat tolerance, namely, TLY83 (heat tolerant) and LLY722 (heat susceptible), were subjected to heat stress. At anthesis, heat stress significantly decreased spikelet fertility, accompanied by notable reductions in pollen germination on stigma and pollen tube elongation in ovule, especially in LLY722. Acid invertase (INV), rather than sucrose synthase, contributed to sucrose metabolism, which explains the different tolerances of both cultivars. Under heat stress, larger enhancements in NAD(H), ATP, and antioxidant capacity were found in TLY83 compared with LLY722, whereas a sharp reduction in poly(ADP-ribose) polymerase (PARP) activity was found in the former compared with the latter. Importantly, exogenous INV, 3-aminobenzamide (a PARP inhibitor), sucrose, glucose, and fructose significantly increased spikelet fertility under heat stress, where INV activity was enhanced and PARP activity was inhibited. Therefore, INV can balance the energy production and consumption to provide sufficient energy for pollen germination and pollen tube growth under heat stress.

The EMT regulator ZEB2 is a novel dependency of human and murine acute myeloid leukemia.

Acute myeloid leukemia (AML) is a heterogeneous disease with complex molecular pathophysiology. To systematically characterize AML's genetic dependencies, we conducted genome-scale short hairpin RNA screens in 17 AML cell lines and analyzed dependencies relative to parallel screens in 199 cell lines of other cancer types. We identified 353 genes specifically required for AML cell proliferation. To validate the in vivo relevance of genetic dependencies observed in human cell lines, we performed a secondary screen in a syngeneic murine AML model driven by the MLL-AF9 oncogenic fusion protein. Integrating the results of these interference RNA screens and additional gene expression data, we identified the transcription factor ZEB2 as a novel AML dependency. ZEB2 depletion impaired the proliferation of both human and mouse AML cells and resulted in aberrant differentiation of human AML cells. Mechanistically, we showed that ZEB2 transcriptionally represses genes that regulate myeloid differentiation, including genes involved in cell adhesion and migration. In addition, we found that epigenetic silencing of the miR-200 family microRNAs affects ZEB2 expression. Our results extend the role of ZEB2 beyond regulating epithelial-mesenchymal transition (EMT) and establish ZEB2 as a novel regulator of AML proliferation and differentiation.

Identification and verification of anoikis-related gene markers to predict the prognosis of patients with bladder cancer and assist in the diagnosis and treatment of bladder cancer.

Background: The recurrence and mortality rates of bladder cancer are extremely high, and its diagnosis and treatment are global concerns. The mechanism of anoikis is closely related to tumor metastasis. Methods: First, we obtained all the data needed for this study from a public database through a formal operational process. The data were then analyzed by bioinformatics technology. Through the limma package, we screened and obtained 313 anoikis-related genes [false discovery rate (FDR) <0.05, |log fold change (FC) | >0.585]. Then, through univariate independent prognostic analysis, we further screened 146 genes (P<0.05) related to the prognosis of bladder cancer from 313 differential genes. These 146 prognostically relevant differential genes were used for least absolute shrinkage and selection operator (LASSO) regression for further screening to obtain model-related genes and output model formulas. Through the nomogram, we can calculate the survival rate of patients more accurately. The accuracy of the nomogram was also confirmed by calibration curves, independent prognostic analysis, receiver operating characteristic (ROC) curves, decision curve analysis (DCA) curves. We then analysed the sensitivity of immunotherapy in bladder cancer patients with different risk scores via Tumor Immune Dysfunction and Exclusion (TIDE). Results: Through bioinformatics technology and public databases, a prognostic model including 9 anoikis-related genes (KLF12, INHBB, CASP6, TGFBR3, FASN, TPM1, OGT, RAC3, ID4) was obtained. Integrating risk scores with clinical information, we obtained a nomogram that can accurately predict patient survival. By querying the immunohistochemical results of the Human Protein Atlas database, two of the nine model-related genes (FASN, RAC3) have the value of further research and are expected to become new biomarkers to assist the diagnosis and treatment of bladder cancer. Through immune-related analysis, we found that patients in the low-risk group appeared to be more suitable for immunotherapy, while drug sensitivity analysis showed that bladder cancer patients in the high-risk group were more sensitive to common chemotherapy drugs. Conclusions: In this study, a prognostic model that can accurately predict the prognosis of patients with bladder cancer was constructed. FASN and RAC3 are expected to become a new biomarker for the diagnosis and treatment of bladder cancer.

Multiple databases analyzed the prognosis prediction of renin secretion pathway-related genes in renal clear cell carcinoma and immunotherapy.

Background: Clear cell renal cell carcinoma (ccRCC) is a malignant kidney tumour and its progression is associated with the renin secretion pathway, so this study aimed to develop a prognostic model based on renin secretion pathway-related genes. Methods: First, 453 renin secretion pathway-related genes were acquired [|log fold change (FC)| >1.5, false discovery rate (FDR) <0.05] from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The data were combined and further screened for 188 genes associated with ccRCC prognosis (P<0.05) by univariate independent prognostic analysis. These genes were subjected to least absolute shrinkage and selection operator regression to identify potential prognostic genes to construct the prognostic model. The stability of the model was externally validated. Combined risk scores and clinical information were used to create nomograms to accurately reflect patient survival. The model-related genes were further mined for subsequent analysis. Results: A prognostic model of six renin secretion pathway genes (IGFBP3, PLAUR, CHKB-CPT1B, HOXA13, CDH13, and CDC20) was developed. Its reliability in predicting disease prognosis was confirmed by survival analysis, receiver operating characteristic (ROC) curve analysis and a risk curve. The nomogram and calibration curve showed good accuracy. The immune-related analyses revealed that the low-risk group would benefit more from immunotherapy. Conclusions: The prognostic model of ccRCC based on six renin secretion pathway-related genes can be used to guide the precise treatment of ccRCC patients.

Multiomics combined with single-cell analysis shows that mitophagy-related genes could accurately predict the prognosis of patients with clear cell renal cell carcinoma.

Background: Clear cell renal cell carcinoma (ccRCC) is a heterogeneous tumor that accounts for a large proportion of kidney cancer, It is prone to recurrence and metastasis, and has a high mortality rate. Although mitophagy is important for metastasis and the recurrence of various tumors, its effect on renal clear cell carcinoma is poorly understood. Methods: Mitophagy-related genes were obtained through the GeneCards database. We normalised the data from different sources by removing the batch effect. Next, we conducted a preliminary screening of mitophagy-related genes and obtained prognosis-related genes from differentially expressed genes. We constructed a prognostic model using least absolute shrinkage and selection operator (LASSO) regression with data from The Cancer Genome Atlas (TCGA) and GSE29609 datasets and validated it internally. International Cancer Genome Consortium (ICGC) and E-MTAB-1980 cohorts also provided double external validation. In addition, we combined multi-omics and single-cell data to comprehensively analyse mitophagy-related gene model signature (MRGMS). Combined with the mitophagy-related gene model (MRGM) score, we constructed a nomogram. Finally, we performed pathway enrichment analysis using a variety of methods. Results: Multiomics and single-cell data analysis showed that the MRGMS is important for patients with ccRCC and is expected to become a new biomarker. The construction of a nomogram was conducive to accurately predicting patient survival. Conclusions: Mitophagy-related genes are important for predicting the prognosis of ccRCC and are conducive to the development of more personalised treatment plans for patients.

RGA1 Negatively Regulates Thermo-tolerance by Affecting Carbohydrate Metabolism and the Energy Supply in Rice.

BACKGROUND: Signal transduction mediated by heterotrimeric G proteins, which comprise the α, ß, and γ subunits, is one of the most important signaling pathways in rice plants. RGA1, which encodes the Gα subunit of the G protein, plays an important role in the response to various types of abiotic stress, including salt, drought, and cold stress. However, the role of RGA1 in the response to heat stress remains unclear. RESULTS: The heat-resistant mutant ett1 (enhanced thermo-tolerance 1) with a new allele of the RGA1 gene was derived from an ethane methyl sulfonate-induced Zhonghua11 mutant. After 45 °C heat stress treatment for 36 h and recovery for 7 d, the survival rate of the ett1 mutants was significantly higher than that of wild-type (WT) plants. The malondialdehyde content was lower, and the maximum fluorescence quantum yield of photosystem II, peroxidase activity, and hsp expression were higher in ett1 mutants than in WT plants after 12 h of exposure to 45 °C. The RNA-sequencing results revealed that the expression of genes involved in the metabolism of carbohydrate, nicotinamide adenine dinucleotide, and energy was up-regulated in ett1 under heat stress. The carbohydrate content and the relative expression of genes involved in sucrose metabolism indicated that carbohydrate metabolism was accelerated in ett1 under heat stress. Energy parameters, including the adenosine triphosphate (ATP) content and the energy charge, were significantly higher in the ett1 mutants than in WT plants under heat stress. Importantly, exogenous glucose can alleviate the damages on rice seedling plants caused by heat stress. CONCLUSION: RGA1 negatively regulates the thermo-tolerance in rice seedling plants through affecting carbohydrate and energy metabolism.

Genes associated with inflammation for prognosis prediction for clear cell renal cell carcinoma: a multi-database analysis.

Background: Clear cell renal cell carcinoma (ccRCC) is the largest subtype of kidney tumour, with inflammatory responses characterising all stages of the tumour. Establishing the relationship between the genes related to inflammatory responses and ccRCC may help the diagnosis and treatment of patients with ccRCC. Methods: First, we obtained the data for this study from a public database. After differential analysis and Cox regression analysis, we obtained the genes for the establishment of a prognostic model for ccRCC. As we used data from multiple databases, we standardized all the data using the surrogate variable analysis (SVA) package to make the data from different sources comparable. Next, we used a least absolute shrinkage and selection operator (LASSO) regression to construct a prognostic model of genes related to inflammation. The data used for modelling and internal validation came from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) series (GSE29609) databases. ccRCC data from the International Cancer Genome Consortium (ICGC) database were used for external validation. Tumour data from the E-MTAB-1980 cohort were used for external validation. The GSE40453 and GSE53757 datasets were used to verify the differential expression of inflammation-related gene model signatures (IRGMS). The immunohistochemistry of IRGMS was queried through the Human Protein Atlas (HPA) database. After the adequate validation of the IRGM, we further explored its application by constructing nomograms, pathway enrichment analysis, immunocorrelation analysis, drug susceptibility analysis, and subtype identification. Results: The IRGM can robustly predict the prognosis of samples from patients with ccRCC from different databases. The verification results show that nomogram can accurately predict the survival rate of patients. Pathway enrichment analysis showed that patients in the high-risk (HR) group were associated with a variety of tumorigenesis biological processes. Immune-related analysis and drug susceptibility analysis suggested that patients with higher IRGM scores had more treatment options. Conclusions: The IRGMS can effectively predict the prognosis of ccRCC. Patients with higher IRGM scores may be better candidates for treatment with immune checkpoint inhibitors and have more chemotherapy options.