Single-cell data revealed exhaustion of characteristic NK cell subpopulations and T cell subpopulations in hepatocellular carcinoma.

BACKGROUND: The treatment and prognosis of patients with advanced hepatocellular carcinoma (HCC) have been a major medical challenge. Unraveling the landscape of tumor immune infiltrating cells (TIICs) in the immune microenvironment of HCC is of great significance to probe the molecular mechanisms. METHODS: Based on single-cell data of HCC, the cell landscape was revealed from the perspective of TIICs. Special cell subpopulations were determined by the expression levels of marker genes. Differential expression analysis was conducted. The activity of each subpopulation was determined based on the highly expressed genes. CTLA4+ T-cell subpopulations affecting the prognosis of HCC were determined based on survival analysis. A single-cell regulatory network inference and clustering analysis was also performed to determine the transcription factor regulatory networks in the CTLA4+ T cell subpopulations. RESULTS: 10 cell types were identified and NK cells and T cells showed high abundance in tumor tissues. Two NK cells subpopulations were present, FGFBP2+ NK cells, B3GNT7+ NK cells. Four T cells subpopulations were present, LAG3+ T cells, CTLA4+ T cells, RCAN3+ T cells, and HPGDS+ Th2 cells. FGFBP2+ NK cells, and CTLA4+ T cells were the exhaustive subpopulation. High CTLA4+ T cells contributed to poor prognostic outcomes and promoted tumor progression. Finally, a network of transcription factors regulated by NR3C1, STAT1, and STAT3, which were activated, was present in CTLA4+ T cells. CONCLUSION: CTLA4+ T cell subsets in HCC exhibited functional exhaustion characteristics that probably inhibited T cell function through a transcription factor network dominated by NR3C1, STAT1, and STAT3.

Targeting Mitochondrial Complex I Deficiency in MPP+/MPTP-induced Parkinson's Disease Cell Culture and Mouse Models by Transducing Yeast NDI1 Gene.

BACKGROUND: MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine), original found in synthetic heroin, causes Parkinson's disease (PD) in human through its metabolite MPP+ by inhibiting complex I of mitochondrial respiratory chain in dopaminergic neurons. This study explored whether yeast internal NADH-quinone oxidoreductase (NDI1) has therapeutic effects in MPTP- induced PD models by functionally compensating for the impaired complex I. MPP+-treated SH-SY5Y cells and MPTP-treated mice were used as the PD cell culture and mouse models respectively. The recombinant NDI1 lentivirus was transduced into SH-SY5Y cells, or the recombinant NDI1 adeno-associated virus (rAAV5-NDI1) was injected into substantia nigra pars compacta (SNpc) of mice. RESULTS: The study in vitro showed NDI1 prevented MPP+-induced change in cell morphology and decreased cell viability, mitochondrial coupling efficiency, complex I-dependent oxygen consumption, and mitochondria-derived ATP. The study in vivo revealed that rAAV-NDI1 injection significantly improved the motor ability and exploration behavior of MPTP-induced PD mice. Accordingly, NDI1 notably improved dopaminergic neuron survival, reduced the inflammatory response, and significantly increased the dopamine content in striatum and complex I activity in substantia nigra. CONCLUSIONS: NDI1 compensates for the defective complex I in MPP+/MPTP-induced models, and vastly alleviates MPTP-induced toxic effect on dopaminergic neurons. Our study may provide a basis for gene therapy of sporadic PD with defective complex I caused by MPTP-like substance.

METTL16 promotes liver cancer stem cell self-renewal via controlling ribosome biogenesis and mRNA translation.

BACKGROUND: While liver cancer stem cells (CSCs) play a crucial role in hepatocellular carcinoma (HCC) initiation, progression, recurrence, and treatment resistance, the mechanism underlying liver CSC self-renewal remains elusive. We aim to characterize the role of Methyltransferase 16 (METTL16), a recently identified RNA N6-methyladenosine (m6A) methyltransferase, in HCC development/maintenance, CSC stemness, as well as normal hepatogenesis. METHODS: Liver-specific Mettl16 conditional KO (cKO) mice were generated to assess its role in HCC pathogenesis and normal hepatogenesis. Hydrodynamic tail-vein injection (HDTVi)-induced de novo hepatocarcinogenesis and xenograft models were utilized to determine the role of METTL16 in HCC initiation and progression. A limiting dilution assay was utilized to evaluate CSC frequency. Functionally essential targets were revealed via integrative analysis of multi-omics data, including RNA-seq, RNA immunoprecipitation (RIP)-seq, and ribosome profiling. RESULTS: METTL16 is highly expressed in liver CSCs and its depletion dramatically decreased CSC frequency in vitro and in vivo. Mettl16 KO significantly attenuated HCC initiation and progression, yet only slightly influenced normal hepatogenesis. Mechanistic studies, including high-throughput sequencing, unveiled METTL16 as a key regulator of ribosomal RNA (rRNA) maturation and mRNA translation and identified eukaryotic translation initiation factor 3 subunit a (eIF3a) transcript as a bona-fide target of METTL16 in HCC. In addition, the functionally essential regions of METTL16 were revealed by CRISPR gene tiling scan, which will pave the way for the development of potential inhibitor(s). CONCLUSIONS: Our findings highlight the crucial oncogenic role of METTL16 in promoting HCC pathogenesis and enhancing liver CSC self-renewal through augmenting mRNA translation efficiency.

Analysis and Validation of Tyrosine Metabolism-related Prognostic Features for Liver Hepatocellular Carcinoma Therapy.

AIMS: To explore tyrosine metabolism-related characteristics in liver hepatocellular carcinoma (LIHC) and to establish a risk signature for the prognostic prediction of LIHC. Novel prognostic signatures contribute to the mining of novel biomarkers, which are essential for the construction of a precision medicine system for LIHC and the improvement of survival. BACKGROUND: Tyrosine metabolism plays a critical role in the initiation and development of LIHC. Based on the tyrosine metabolism-related characteristics in LIHC, this study developed a risk signature to improve the prognostic prediction of patients with LIHC. OBJECTIVE: To investigate the correlation between tyrosine metabolism and progression of LIHC and to develop a tyrosine metabolism-related prognostic model. METHODS: Gene expression and clinicopathological information of LIHC were obtained from The Cancer Genome Atlas (TCGA) database. Distinct subtypes of LIHC were classified by performing consensus cluster analysis on the tyrosine metabolism-related genes. Univariate and Lasso Cox regression were used to develop a RiskScore prognosis model. Kaplan-Meier (KM) survival analysis with log-rank test and area under the curve (AUC) of receiver operating characteristic (ROC) were employed in the prognostic evaluation and prediction validation. Immune infiltration, tyrosine metabolism score, and pathway enrichment were evaluated using single-sample gene set enrichment analysis (ssGSEA). Finally, a nomogram model was developed with the RiskScore and other clinicopathological features. RESULTS: Based on the tyrosine metabolism genes in the TCGA cohort, we identified 3 tyrosine metabolism-related subtypes showing significant prognostic differences. Four candidate genes selected from the common differentially expressed genes (DEGs) between the 3 subtypes were used to develop a RiskScore model, which could effectively divide LIHC patients into high- and lowrisk groups. In both the training and validation sets, high-risk patients tended to have worse overall survival, less active immunotherapy response, higher immune infiltration and clinical grade, and higher oxidative, fatty, and xenobiotic metabolism pathways. Multivariate analysis confirmed that the RiskScore was an independent indicator for the prognosis of LIHC. The results from pan-- cancer analysis also supported that the RiskScore had a strong prognostic performance in other cancers. The nomogram demonstrated that the RiskScore contributed the most to the prediction of LIHC prognosis. CONCLUSION: Our study developed a tyrosine metabolism-related risk model that performed well in survival prediction, showing the potential to serve as an independent prognostic predictor for LIHC treatment.

Changes in oscillatory patterns of microstate sequence in patients with first-episode psychosis.

We aimed to utilize chaos game representation (CGR) for the investigation of microstate sequences and explore its potential as neurobiomarkers for psychiatric disorders. We applied our proposed method to a public dataset including 82 patients with first-episode psychosis (FEP) and 61 control subjects. Two time series were constructed: one using the microstate spacing distance in CGR and the other using complex numbers representing the microstate coordinates in CGR. Power spectral features of both time series and frequency matrix CGR (FCGR) were compared between groups and employed in a machine learning application. The four canonical microstates (A, B, C, and D) were identified using both shared and separate templates. Our results showed the microstate oscillatory pattern exhibited alterations in the FEP group. Using oscillatory features improved machine learning performance compared with classical features and FCGR. This study opens up new avenues for exploring the use of CGR in analyzing EEG microstate sequences. Features derived from microstate sequence CGR offer fine-grained neurobiomarkers for psychiatric disorders.

PRRG4 regulates mitochondrial function and promotes migratory behaviors of breast cancer cells through the Src-STAT3-POLG axis.

BACKGROUND: Breast cancer is the leading cause of cancer death for women worldwide. Most of the breast cancer death are due to disease recurrence and metastasis. Increasingly accumulating evidence indicates that mitochondria play key roles in cancer progression and metastasis. Our recent study revealed that transmembrane protein PRRG4 promotes the metastasis of breast cancer. However, it is not clear whether PRRG4 can affect the migration and invasion of breast cancer cells through regulating mitochondria function. METHODS: RNA-seq analyses were performed on breast cancer cells expressing control and PRRG4 shRNAs. Quantitative PCR analysis and measurements of mitochondrial ATP content and oxygen consumption were carried out to explore the roles of PRRG4 in regulating mitochondrial function. Luciferase reporter plasmids containing different lengths of promoter fragments were constructed. Luciferase activities in breast cancer cells transiently transfected with these reporter plasmids were analyzed to examine the effects of PRRG4 overexpression on promoter activity. Transwell assays were performed to determine the effects of PRRG4-regulated pathway on migratory behaviors of breast cancer cells. RESULTS: Analysis of the RNA-seq data revealed that PRRG4 knockdown decreased the transcript levels of all the mitochondrial protein-encoding genes. Subsequently, studies with PRRG4 knockdown and overexpression showed that PRRG4 expression increased mitochondrial DNA (mtDNA) content. Mechanistically, PRRG4 via Src activated STAT3 in breast cancer cells. Activated STAT3 in turn promoted the transcription of mtDNA polymerase POLG through a STAT3 DNA binding site present in the POLG promoter region, and increased mtDNA content as well as mitochondrial ATP production and oxygen consumption. In addition, PRRG4-mediated activation of STAT3 also enhanced filopodia formation, migration, and invasion of breast cancer cells. Moreover, PRRG4 elevated migratory behaviors and mitochondrial function of breast cancer cells through POLG. CONCLUSION: Our results indicate that PRRG4 via the Src-STAT3-POLG axis enhances mitochondrial function and promotes migratory behaviors of breast cancer cells.

High sensitivity composite F-P cavity fiber optic sensor based on MEMS for temperature and salinity measurement of seawater.

We proposed an optical fiber salinity sensor with a composite Fabry-Perot (F-P) cavity structure for simultaneous measurement of temperature and salinity based on microelectromechanical system (MEMS) technology. The sensor contains two sensing cavities. The silicon cavity is used for temperature sensing, and the seawater cavity processed by the glass microstructure is sensitive to the refractive index of seawater for salinity sensing. At the same time, the influence of the salinity-temperature cross-sensitivity error of the seawater cavity is effectively compensated by using the temperature single parameter sensitivity characteristics of the silicon cavity. The structural design of the sensor seawater cavity includes a cross-shaped groove and a cylindrical fluid cavity. The surface hydrophilicity treatment was performed on the interior of the cavity to solve the effect of no water injection in the cavity caused by the miniaturization of the sensor. The optical path difference (OPD) demodulation method is used to demodulate the two F-P cavities with large dynamic range and high resolution. In the range of 5∼40°C and 5∼ 40 ‰, the temperature and salinity sensitivity of the sensor can reach 110.25 nm/°C and 178.75 nm/‰, respectively, and the resolution can reach 5.02 × 10-3°C and 0.0138‰. It has the advantages of mass production, high stability, and small size, which give it great potential for marine applications.

Lightweight Differentiated Transmission Based on Fuzzy and Random Modeling in Underwater Acoustic Sensor Networks.

Energy-efficient and reliable underwater acoustic communication attracts a lot of research due to special marine communication conditions with limited resources in underwater acoustic sensor networks (UASNs). In their final analysis, the existing studies focus on controlling redundant communication and route void that greatly influence UASNs' comprehensive performances. Most of them consider directional or omnidirectional transmission for partial optimization aspects, which still have many extra data loads and performance losses. This paper analyzes the main issue sources causing redundant communication in UASNs, and proposes a lightweight differentiated transmission to suppress extra communication to the greatest extent as well as balance energy consumption. First, the layered model employs layer ID to limit the scale of the data packet header, which does not need depth or location information. Second, the layered model, fuzzy-based model, random modeling and directional-omnidirectional differentiated transmission mode comb out the forwarders step by step to decrease needless duplicated forwarding. Third, forwarders are decided by local computation in nodes, which avoids exchanging controlling information among nodes. Simulation results show that our method can efficiently reduce the network load and improve the performance in terms of energy consumption balance, network lifetime, data conflict and network congestion, and data packet delivery ratio.

Small molecule targeting of transcription-replication conflict for selective chemotherapy.

Targeting transcription replication conflicts, a major source of endogenous DNA double-stranded breaks and genomic instability could have important anticancer therapeutic implications. Proliferating cell nuclear antigen (PCNA) is critical to DNA replication and repair processes. Through a rational drug design approach, we identified a small molecule PCNA inhibitor, AOH1996, which selectively kills cancer cells. AOH1996 enhances the interaction between PCNA and the largest subunit of RNA polymerase II, RPB1, and dissociates PCNA from actively transcribed chromatin regions, while inducing DNA double-stranded breaks in a transcription-dependent manner. Attenuation of RPB1 interaction with PCNA, by a point mutation in RPB1's PCNA-binding region, confers resistance to AOH1996. Orally administrable and metabolically stable, AOH1996 suppresses tumor growth as a monotherapy or as a combination treatment but causes no discernable side effects. Inhibitors of transcription replication conflict resolution may provide a new and unique therapeutic avenue for exploiting this cancer-selective vulnerability.

Design, Synthesis, Computational and Biological Evaluation of Novel Structure Fragments Based on Lithocholic Acid (LCA).

The regulation of bile acid pathways has become a particularly promising therapeutic strategy for a variety of metabolic disorders, cancers, and diseases. However, the hydrophobicity of bile acids has been an obstacle to clinical efficacy due to off-target effects from rapid drug absorption. In this report, we explored a novel strategy to design new structure fragments based on lithocholic acid (LCA) with improved hydrophilicity by introducing a polar "oxygen atom" into the side chain of LCA, then (i) either retaining the carboxylic acid group or replacing the carboxylic acid group with (ii) a diol group or (iii) a vinyl group. These novel fragments were evaluated using luciferase-based reporter assays and the MTS assay. Compared to LCA, the result revealed that the two lead compounds 1a-1b were well tolerated in vitro, maintaining similar potency and efficacy to LCA. The MTS assay results indicated that cell viability was not affected by dose dependence (under 25 µM). Additionally, computational model analysis demonstrated that compounds 1a-1b formed more extensive hydrogen bond networks with Takeda G protein-coupled receptor 5 (TGR5) than LCA. This strategy displayed a potential approach to explore the development of novel endogenous bile acids fragments. Further evaluation on the biological activities of the two lead compounds is ongoing.

Targeted screening and identification of chlorhexidine as a pro-myogenic circadian clock activator.

BACKGROUND: The circadian clock is an evolutionarily conserved mechanism that exerts pervasive temporal control in stem cell behavior. This time-keeping machinery is required for orchestrating myogenic progenitor properties in regenerative myogenesis that ameliorates muscular dystrophy. Here we report a screening platform to discover circadian clock modulators that promote myogenesis and identify chlorhexidine (CHX) as a clock-activating molecule with pro-myogenic activities. METHODS: A high-throughput molecular docking pipeline was applied to identify compounds with a structural fit for a hydrophobic pocket within the key circadian transcription factor protein, Circadian Locomotor Output Cycles Kaput (CLOCK). These identified molecules were further screened for clock-modulatory activities and functional validations for pro-myogenic properties. RESULTS: CHX was identified as a clock activator that promotes distinct aspects of myogenesis. CHX activated circadian clock that reduced cycling period length and augmented amplitude. This action was mediated by the targeted CLOCK structure via augmented interaction with heterodimer partner Bmal1, leading to enhanced CLOCK/Bmal1-controlled transcription with upregulation of core clock genes. Consistent with its clock-activating function, CHX displayed robust effects on stimulating myogenic differentiation in a clock-dependent manner. In addition, CHX augmented the proliferative and migratory activities of myoblasts. CONCLUSION: Our findings demonstrate the feasibility of a screening platform to discover clock modulators with myogenic regulatory activities. Discovery of CHX as a pro-myogenic molecule could be applicable to promote regenerative capacities in ameliorating dystrophic or degenerative muscle diseases.

Electrical Stimulation for Children with Cerebral Palsy: A Meta-analysis for Randomized Controlled Trials.

BACKGROUND: Different types of electrical stimulation (ES) showed diverse effects on children with cerebral palsy (CP). Previous studies reported inconsistent results for effects of ES on children with CP. The present study aimed to conduct a meta-analysis to summarize these diverse results. METHODS: We searched for studies exploring effects of ES on children with CP in databases (PubMed and Web of Science) from their inception until December 2022. Standard mean differences (SMDs) and 95% confidence intervals (CIs) were computed using STATA 12.0 software. RESULTS: The meta-analysis included 19 randomized controlled trials (including 265 CP patients in test group and 263 CP patients in corresponding control group). The study showed an increased improvement in gross motor function, walking speed, step length, and daily living activities in ES group compared with corresponding control group with random effects models (gross motor function: SMD = 2.04, 95% CI = 1.43-2.65; walking speed: SMD = 3.71, 95% CI = 1.49-5.92; step length: SMD = 1.89, 95% CI = 0.65-3.13; daily living activities: SMD = 5.18, 95% CI = 3.04-7.31), whereas the study showed no significant difference in change of muscle strength between ES group and the corresponding control group with a random effects model (SMD = 0.42, 95% CI = -0.12 to 0.97). CONCLUSION: The study demonstrated that ES might be used as therapy to improve gross motor function, gait, and daily living activities in children with CP.

TFRegNCI: Interpretable Noncovalent Interaction Correction Multimodal Based on Transformer Encoder Fusion.

The interpretability is an important issue for end-to-end learning models. Motivated by computer vision algorithms, an interpretable noncovalent interaction (NCI) correction multimodal (TFRegNCI) is proposed for NCI prediction. TFRegNCI is based on RegNet feature extraction and a transformer encoder fusion strategy. RegNet is a network design paradigm that mainly focuses on local features. Meanwhile, the Vision Transformer is also leveraged for feature extraction, because it can capture global features better than RegNet while lowering the computational cost. Using a transformer encoder as the fusion strategy rather than multilayer perceptron can enhance model performance, due to its emphasis on important features with less parameters. Therefore, the proposed TFRegNCI achieved high accurate prediction (mean absolute error of ∼0.1 kcal/mol) comparing with the coupled cluster single double (triple) (CCSD(T)) benchmark. To further improve the model efficiency, TFRegNCI applies two-dimensional (2D) inputs transformed from three-dimensional (3D) electron density cubes, which saves time (30%), while the model accuracy remains. To improve model interpretability, a visualization module, Gradient-weighted Regression Activation Mapping (Grad-RAM) has been embedded. Grad-RAM is promoted from the classification algorithm, Gradient-weighted Class Activation Mapping, to perform feature visualization for the regression task. With Grad-RAM, the visual location map for features in deep learning models can be displayed. The feature map visualizations suggest that the 2D model has the similar performance as the 3D model, because of equally effective feature extractions from electron density. Moreover, the valid feature region on the location map by the 3D model is consistent with the NCIPLOT NCI isosurface. It is confirmed that the model does extract significant features related to the NCI interaction. The interpretable analyses are carried out through molecular orbital contribution on effective features. Thereby, the proposed model is likely to be a promising tool to reveal some essential information on NCIs, with regard to the level of electronic theory.

Therapeutic effect of a MUC1-specific monoclonal antibody-drug conjugates against pancreatic cancer model.

BACKGROUND: Pancreatic cancer is one of the most aggressive malignancies without effective targeted therapies. MUC1 has emerged as a potential common target for cancer therapy because it is overexpressed in a variety of different cancers including the majority of pancreatic cancer. However, there are still no approved monoclonal antibody drugs targeting MUC1 have been reported. Recently, we generated a humanized MUC1 antibody (HzMUC1) specific to the interaction region between MUC1-N and MUC1-C. In this study, we generated the antibody drug conjugate (ADC) by conjugating HzMUC1 with monomethyl auristatin (MMAE), and examined the efficacy of HzMUC1-MMAE against the MUC1-positive pancreatic cancer in vitro and in vivo. METHODS: Western blot and immunoprecipitation were used to detect MUC1 in pancreatic cancer cells. MUC1 localization in pancreatic cancer cells was determined by confocal microscopy. HzMUC1 was conjugated with the monomethyl auristatin (MMAE), generating the HzMUC1-MMAE ADC. Colony formation assay and flow cytometry were used to assess the effects of the HzMUC1-MMAE cell viability, cell cycle progression and apoptosis. Capan-2 and CFPAC-1 xenograft model were used to test the efficacy of HzMUC1-MMAE against pancreatic cancer. RESULTS: HzMUC1 antibody binds to MUC1 on the cell surface of pancreatic cancer cells. HzMUC1-MMAE significantly inhibited cell growth by inducing G2/M cell cycle arrest and apoptosis in pancreatic cancer cells. Importantly, HzMUC1-MMAE significantly reduced the growth of pancreatic xenograft tumors by inhibiting cell proliferation and enhancing cell death. CONCLUSION: Our results indicate that HzMUC1-ADC is a promising novel targeted therapy for pancreatic cancer. HzMUC1-ADC should also be an effective drug for the treatment of different MUC1-positive cancers.

The m6A reader IGF2BP2 regulates glutamine metabolism and represents a therapeutic target in acute myeloid leukemia.

N6-Methyladenosine (m6A) modification and its modulators play critical roles and show promise as therapeutic targets in human cancers, including acute myeloid leukemia (AML). IGF2BP2 was recently reported as an m6A binding protein that enhances mRNA stability and translation. However, its function in AML remains largely elusive. Here we report the oncogenic role and the therapeutic targeting of IGF2BP2 in AML. High expression of IGF2BP2 is observed in AML and associates with unfavorable prognosis. IGF2BP2 promotes AML development and self-renewal of leukemia stem/initiation cells by regulating expression of critical targets (e.g., MYC, GPT2, and SLC1A5) in the glutamine metabolism pathways in an m6A-dependent manner. Inhibiting IGF2BP2 with our recently identified small-molecule compound (CWI1-2) shows promising anti-leukemia effects in vitro and in vivo. Collectively, our results reveal a role of IGF2BP2 and m6A modification in amino acid metabolism and highlight the potential of targeting IGF2BP2 as a promising therapeutic strategy in AML.

Erratum: Overcome trastuzumab resistance of breast cancer using anti-HER2 chimeric antigen receptor T cells and PD1 blockade.

[This corrects the article on p. 688 in vol. 10, PMID: 32195036.].

Asymmetric Ferroelectric-Gated Two-Dimensional Transistor Integrating Self-Rectifying Photoelectric Memory and Artificial Synapse.

Ferroelectric field-effect transistors (Fe-FET) are promising candidates for future information devices. However, they suffer from low endurance and short retention time, which retards the application of processing memory in the same physical processes. Here, inspired by the ferroelectric proximity effects, we design a reconfigurable two-dimensional (2D) MoS2 transistor featuring with asymmetric ferroelectric gate, exhibiting high memory and logic ability with a program/erase ratio of over 106 and a self-rectifying ratio of 103. Interestingly, the robust electric and optic cycling are obtained with a large switching ratio of 106 and nine distinct resistance states upon optical excitation with excellent nonvolatile characteristics. Meanwhile, the operation of memory mimics the synapse behavior in response to light spikes with different intensity and number. This design realizes an integration of robust processing memory in one single device, which demonstrates a considerable potential of an asymmetric ferroelectric gate in the development of Fe-FETs for logic processing and nonvolatile memory applications.

Inhibition of the CDK2 and Cyclin A complex leads to autophagic degradation of CDK2 in cancer cells.

Cyclin-dependent kinase 2 (CDK2) complex is significantly over-activated in many cancers. While it makes CDK2 an attractive target for cancer therapy, most inhibitors against CDK2 are ATP competitors that are either nonspecific or highly toxic, and typically fail clinical trials. One alternative approach is to develop non-ATP competitive inhibitors; they disrupt interactions between CDK2 and either its partners or substrates, resulting in specific inhibition of CDK2 activities. In this report, we identify two potential druggable pockets located in the protein-protein interaction interface (PPI) between CDK2 and Cyclin A. To target the potential druggable pockets, we perform a LIVS in silico screening of a library containing 1925 FDA approved drugs. Using this approach, homoharringtonine (HHT) shows high affinity to the PPI and strongly disrupts the interaction between CDK2 and cyclins. Further, we demonstrate that HHT induces autophagic degradation of the CDK2 protein via tripartite motif 21 (Trim21) in cancer cells, which is confirmed in a leukemia mouse model and in human primary leukemia cells. These results thus identify an autophagic degradation mechanism of CDK2 protein and provide a potential avenue towards treating CDK2-dependent cancers.

Targeting MYC and BCL2 by a natural compound for "double-hit" lymphoma.

Concurrent translocations of MYC and BCL2 lead to abnormal expression of both oncoproteins, which contribute to the aggressive clinical characteristics of double-hit lymphoma (DHL). An effective therapy for DHL remains an unmet clinical need. In this study, we showed that both Ca2+ /calmodulin-dependent protein kinase II δ (CAMKIIδ) and γ (CAMKIIγ) were highly expressed in DHL. Both isoforms of CAMKII stabilize c-Myc protein by phosphorylating it at Ser62, increase BCL2 expression, and promote DHL tumor growth. Inhibition of CAMKIIδ and CAMKIIγ by either berbamine (BBM) or one of its derivatives (PA4) led to the down regulation of c-Myc and BCL2 proteins. BBM/PA4 also exhibited anti-tumor efficacy in DHL cell lines and NSG xenograft models. Altogether, CAMKIIδ and CAMKIIγ appear to be critical for DHL tumor development and are promising therapeutic targets for DHL.

Correction: 2'-Hydroxyflavanone effectively targets RLIP76-mediated drug transport and regulates critical signaling networks in breast cancer.

[This corrects the article DOI: 10.18632/oncotarget.24720.].