KDM1A, a potent and selective target, for the treatment of DNMT3A-deficient non-small cell lung cancer.

BACKGROUND: DNMT3A is a crucial epigenetic regulation enzyme. However, due to its heterogeneous nature and frequent mutation in various cancers, the role of DNMT3A remains controversial. Here, we determine the role of DNMT3A in non-small cell lung cancer (NSCLC) to identify potential treatment strategies. METHODS: To investigate the role of loss-of-function mutations of DNMT3A in NSCLC, CRISPR/Cas9 was used to induce DNMT3A-inactivating mutations. Epigenetic inhibitor library was screened to find the synthetic lethal partner of DNMT3A. Both pharmacological inhibitors and gene manipulation were used to evaluate the synthetic lethal efficacy of DNMT3A/KDM1A in vitro and in vivo. Lastly, MS-PCR, ChIP-qPCR, dual luciferase reporter gene assay and clinical sample analysis were applied to elucidate the regulation mechanism of synthetic lethal interaction. RESULTS: We identified DNMT3A is a tumour suppressor gene in NSCLC and KDM1A as a synthetic lethal partner of DNMT3A deletion. Both chemical KDM1A inhibitors and gene manipulation can selectively reduce the viability of DNMT3A-KO cells through inducing cell apoptosis in vitro and in vivo. We clarified that the synthetic lethality is not only limited to the death mode, but also involved into tumour metastasis. Mechanistically, DNMT3A deficiency induces KDM1A upregulation through reducing the methylation status of the KDM1A promoter and analysis of clinical samples indicated that DNMT3A expression was negatively correlated with KDM1A level. CONCLUSION: Our results provide new insight into the role of DNMT3A in NSCLC and elucidate the mechanism of synthetic lethal interaction between KDM1A and DNMT3A, which might represent a promising approach for treating patients with DNMT3A-deficient tumours.

Accurate Early Detection and EGFR Mutation Status Prediction of Lung Cancer Using Plasma cfDNA Coverage Patterns: A Proof-of-Concept Study.

Lung cancer is a major global health concern with a low survival rate, often due to late-stage diagnosis. Liquid biopsy offers a non-invasive approach to cancer detection and monitoring, utilizing various features of circulating cell-free DNA (cfDNA). In this study, we established two models based on cfDNA coverage patterns at the transcription start sites (TSSs) from 6X whole-genome sequencing: an Early Cancer Screening Model and an EGFR mutation status prediction model. The Early Cancer Screening Model showed encouraging prediction ability, especially for early-stage lung cancer. The EGFR mutation status prediction model exhibited high accuracy in distinguishing between EGFR-positive and wild-type cases. Additionally, cfDNA coverage patterns at TSSs also reflect gene expression patterns at the pathway level in lung cancer patients. These findings demonstrate the potential applications of cfDNA coverage patterns at TSSs in early cancer screening and in cancer subtyping.

Progressive Dual Priori Network for Generalized Breast Tumor Segmentation.

To promote the generalization ability of breast tumor segmentation models, as well as to improve the segmentation performance for breast tumors with smaller size, low-contrast and irregular shape, we propose a progressive dual priori network (PDPNet) to segment breast tumors from dynamic enhanced magnetic resonance images (DCE-MRI) acquired at different centers. The PDPNet first cropped tumor regions with a coarse-segmentation based localization module, then the breast tumor mask was progressively refined by using the weak semantic priori and cross-scale correlation prior knowledge. To validate the effectiveness of PDPNet, we compared it with several state-of-the-art methods on multi-center datasets. The results showed that, comparing against the suboptimal method, the DSC and HD95 of PDPNet were improved at least by 5.13% and 7.58% respectively on multi-center test sets. In addition, through ablations, we demonstrated that the proposed localization module can decrease the influence of normal tissues and therefore improve the generalization ability of the model. The weak semantic priors allow focusing on tumor regions to avoid missing small tumors and low-contrast tumors. The cross-scale correlation priors are beneficial for promoting the shape-aware ability for irregular tumors. Thus integrating them in a unified framework improved the multi-center breast tumor segmentation performance. The source code and open data can be accessed at https://github.com/wangli100209/PDPNet.

2,2- dimethylbenzopyran derivatives containing pyridone structural fragments as selective dual-targeting inhibitors of HIF-1α and EZH2 for the treatment of lung cancer.

We formerly reported that EZH2 inhibitors sensitized HIF-1 inhibitor-resistant cells and inhibited HIF-1α to promote SUZ12 transcription, leading to enhanced EZH2 enzyme activity and elevated H3K27me3 levels, and conversely, inhibition of EZH2 promoted HIF-1α transcription. HIF-1α and EZH2 interacted to form a negative feedback loop that reinforced each other's activity. In this paper, a series of 2,2- dimethylbenzopyran derivatives containing pyridone structural fragments were designed and synthesized with DYB-03, a HIF-1α inhibitor previously reported by our group, and Tazemetostat, an EZH2 inhibitor approved by FDA, as lead compounds. Among these compounds, D-01 had significant inhibitory activities on HIF-1α and EZH2. In vitro experiments showed that D-01 significantly inhibited the migration of A549 cells, clone, invasion and angiogenesis. Moreover, D-01 had good pharmacokinetic profiles. All the results about compound D-01 could lay a foundation for the research and development of HIF-1α and EZH2 dual-targeting compounds.

PD-L2 drives resistance to EGFR-TKIs: dynamic changes of the tumor immune environment and targeted therapy.

There is a lack of effective treatments to overcome resistance to EGFR-TKIs in EGFR mutant tumors. A deeper understanding of resistance mechanisms can provide insights into reducing or eliminating resistance, and can potentially deliver targeted treatment measures to overcome resistance. Here, we identified that the dynamic changes of the tumor immune environment were important extrinsic factors driving tumor resistance to EGFR-TKIs in EGFR mutant cell lines and syngeneic tumor-bearing mice. Our results demonstrate that the acquired resistance to EGFR-TKIs is accompanied by aberrant expression of PD-L2, leading a dynamic shift from an initially favorable tumor immune environment to an immunosuppressive phenotype. PD-L2 expression significantly affected EGFR mutant cell apoptosis that depended on the proportion and function of CD8+ T cells in the tumor immune environment. Combined with single-cell sequencing and experimental results, we demonstrated that PD-L2 specifically inhibited the proliferation of CD8+ T cells and the secretion of granzyme B and perforin, leading to reduced apoptosis mediated by CD8+ T cells and enhanced immune escape of tumor cells, which drives EGFR-TKIs resistance. Importantly, we have identified a potent natural small-molecule inhibitor of PD-L2, zinc undecylenate. In vitro, it selectively and potently blocks the PD-L2/PD-1 interaction. In vivo, it abolishes the suppressive effect of the PD-L2-overexpressing tumor immune microenvironment by blocking PD-L2/PD-1 signaling. Moreover, the combination of zinc undecylenate and EGFR-TKIs can synergistically reverse tumor resistance, which is dependent on CD8+ T cells mediating apoptosis. Our study uncovers the PD-L2/PD-1 signaling pathway as a driving factor to mediate EGFR-TKIs resistance, and identifies a new naturally-derived agent to reverse EGFR-TKIs resistance.

EHMT2-mediated transcriptional reprogramming drives neuroendocrine transformation in non-small cell lung cancer.

The transformation of lung adenocarcinoma to small cell lung cancer (SCLC) is a recognized resistance mechanism and a hindrance to therapies using epidermal growth factor receptor tyrosine kinase inhibitors (TKIs). The paucity of pretranslational/posttranslational clinical samples limits the deeper understanding of resistance mechanisms and the exploration of effective therapeutic strategies. Here, we developed preclinical neuroendocrine (NE) transformation models. Next, we identified a transcriptional reprogramming mechanism that drives resistance to erlotinib in NE transformation cell lines and cell-derived xenograft mice. We observed the enhanced expression of genes involved in the EHMT2 and WNT/ß-catenin pathways. In addition, we demonstrated that EHMT2 increases methylation of the SFRP1 promoter region to reduce SFRP1 expression, followed by activation of the WNT/ß-catenin pathway and TKI-mediated NE transformation. Notably, the similar expression alterations of EHMT2 and SFRP1 were observed in transformed SCLC samples obtained from clinical patients. Importantly, suppression of EHMT2 with selective inhibitors restored the sensitivity of NE transformation cell lines to erlotinib and delayed resistance in cell-derived xenograft mice. We identify a transcriptional reprogramming process in NE transformation and provide a potential therapeutic target for overcoming resistance to erlotinib.

Vasorin promotes endothelial differentiation of glioma stem cells via stimulating the transcription of VEGFR2.

Gliomas are highly vascularized malignancies, but current anti-angiogenic treatments have not demonstrated practical improvements in patient survival. Studies have suggested that glioma-derived endothelial cell (GdEC) formed by glioma stem cell (GSC) differentiation may contribute to the failure of this treatment. However, the molecular mechanisms involved in GSC endothelial differentiation remain poorly understood. We previously reported that vasorin (VASN) is highly expressed in glioma and promotes angiogenesis. Here, we show that VASN expression positively correlates with GdEC signatures in glioma patients. VASN promotes the endothelial differentiation capacity of GSC in vitro and participates in the formation of GSC-derived vessels in vivo. Mechanistically, vascular endothelial growth factor receptor 2 (VEGFR2) is a critical factor that mediates the regulation of VASN on GSC endothelial differentiation. Separation of cell chromatin fractionation and chromatin immunoprecipitation-sequencing analysis show that VASN interacts with Notch1 and co-translocates into the cell nuclei, where VASN binds to the VEGFR2 gene promoter to stimulate its transcription during the progression of GSC differentiation into GdEC. Together, these findings elucidate the role and mechanisms of VASN in promoting the endothelial differentiation of GSC and suggest VASN as a potential target for anti-angiogenic therapy based on intervention in GdEC formation in gliomas.

Endometrial stem cells alleviate cisplatin-induced ferroptosis of granulosa cells by regulating Nrf2 expression.

BACKGROUND: Premature ovarian failure (POF) caused by cisplatin is a severe and intractable sequela for young women with cancer who received chemotherapy. Cisplatin causes the dysfunction of granulosa cells and mainly leads to but is not limited to its apoptosis and autophagy. Ferroptosis has been also reported to participate, while little is known about it. Our previous experiment has demonstrated that endometrial stem cells (EnSCs) can repair cisplatin-injured granulosa cells. However, it is still unclear whether EnSCs can play a repair role by acting on ferroptosis. METHODS: Western blotting and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) were applied to detect the expression levels of ferroptosis-related genes. CCK-8 and 5-Ethynyl-2'-deoxyuridine (EdU) assays were used to evaluate cell viability. Transmission electron microscopy (TEM) was performed to detect ferroptosis in morphology. And the extent of ferroptosis was assessed by ROS, GPx, GSSG and MDA indicators. In vivo, ovarian morphology was presented by HE staining and the protein expression in ovarian tissue was detected by immunohistochemistry. RESULTS: Our results showed that ferroptosis could occur in cisplatin-injured granulosa cells. Ferroptosis inhibitor ferrostatin-1 (Fer-1) and EnSCs partly restored cell viability and mitigated the damage of cisplatin to granulosa cells by inhibiting ferroptosis. Moreover, the repair potential of EnSCs can be markedly blocked by ML385. CONCLUSION: Our study demonstrated that cisplatin could induce ferroptosis in granulosa cells, while EnSCs could inhibit ferroptosis and thus exert repair effects on the cisplatin-induced injury model both in vivo and in vitro. Meanwhile, Nrf2 was validated to participate in this regulatory process and played an essential role.

Characterization of the prognostic, diagnostic, and immunological roles of DSCC1 and its genomic alteration and instability in human cancers.

DNA replication and sister chromatid cohesion 1 (DSCC1) exerts various functions including sister chromatid cohesion. DSCC1 overexpression plays an important role in cancer development, such as in colorectal, breast, and hepatocellular cancers. The specific role of DSCC1 in tumor progression remains largely unknown, necessitating a pan-cancer investigation to understand the potential function of DSCC1 in various cancers. In this study, we obtained data on physiological conditions, transcriptional expression, survival prognosis, genomic alteration, genomic instability, enriched pathways, immune infiltration, and immunotherapy from The Cancer Genome Atlas, The Genotype-Tissue Expression, cBioPortal, and other publicly available databases to systematically characterize the oncogenic and immunological roles of DSCC1 in 33 different cancers. We found that DSCC1 expression was upregulated at both mRNA and protein levels in various cancers. Additionally, DSCC1 expression was associated with higher tumor stage and grade in specific cancers. DSCC1 was a potential pan-cancer prognostic biomarker for its close association with patient prognosis and a diagnostic biomarker for its high predictive value in distinguishing tumor tissues from normal tissues. DSCC1 was universally amplified across different cancers and tightly associated with genomic instability. Moreover, DSCC1 had a close relationship with tumor immune cell infiltration; thus, it could be used as a potential biomarker for predicting the response and survival of patients with cancer who receive immune checkpoint blockade treatment. To sum up, our study revealed that DSCC1 is a promising target for tumor therapy.

FGF2 promotes the proliferation of injured granulosa cells in premature ovarian failure via Hippo-YAP signaling pathway.

Young women undergoing anticancer treatment are at risk of premature ovarian failure (POF). Endometrial-derived stem cells (EnSCs) have demonstrated significant therapeutic potential for treating ovarian insufficiency, although the underlying mechanisms remain to be fully understood. This study aims to further investigate the therapeutic effects of EnSCs, particularly through the paracrine action of fibroblast growth factor 2 (FGF2), on POF. The findings show that exogenous FGF2 enhances the survival of ovarian granulosa cells damaged by cisplatin. FGF2 stimulates the proliferation of these damaged cells by suppressing the Hippo signaling pathway and activating YAP expression. In vivo experiments also revealed that FGF2 treatment significantly improves ovarian reserve and endocrine function in mice with POF. These results suggest that FGF2 can boost the proliferative capacity of damaged ovarian granulosa cells through the Hippo-YAP signaling pathway, providing a theoretical foundation for using EnSCs and FGF2 in clinical treatments for POF.

Vasorin Exocytosed from Glioma Cells Facilitates Angiogenesis via VEGFR2/AKT Signaling Pathway.

Glioma is a highly vascularized tumor of the central nervous system. Angiogenesis plays a predominant role in glioma progression and is considered an important therapeutic target. Our previous study showed that vasorin (VASN), a transmembrane protein, is overexpressed in glioma and promotes angiogenesis; however, the potential mechanism remains unclear. In this study, we found that human vascular endothelial cells (hEC) co-cultured with VASN-overexpressing glioma cells exhibited accelerated migration ability and increased expression of VASN originated from glioma cells. VASN was found in exosomes secreted by glioma cells and could be taken up by hECs. hECs showed more edge filopodia and significantly upregulated expression of endothelial tip cell marker gene and protein levels after co-culture with VASN-overexpressing glioma cells. In clinical glioma tissue and orthotopic transplantation glioma tissue, the vascular density and the number of vascular endothelial cells with a tip cell phenotype in VASN-overexpressed tissues were significantly higher than in tissues with low expression. At the molecular level, VASN interacted with VEGFR2 and caused internalization and autophosphorylation of VEGFR2 protein, and then activated the AKT signaling pathway. Our study collectively reveals the function and mechanism of VASN in facilitating angiogenesis in glioma, providing a new therapeutic target for glioma. IMPLICATIONS: These findings demonstrate that VASN exocytosed from glioma cells enhanced the migration of vascular endothelial cells by VEGFR2/AKT signaling pathway.

Glioma segmentation based on dense contrastive learning and multimodal features recalibration.

Accurate segmentation of different regions of gliomas from multimodal magnetic resonance (MR) images is crucial for glioma grading and precise diagnosis, but many existing segmentation methods are difficult to effectively utilize multimodal MR image information to recognize accurately the lesion regions with small size, low contrast and irregular shape. To address this issue, this work proposes a novel 3D glioma segmentation model DCL-MANet. DCL-MANet has an architecture of multiple encoders and one single decoder. Each encoder is used to extract MR image features of a given modality. To overcome the entangle problems of multimodal semantic features, a dense contrastive learning (DCL) strategy is presented to extract the modality-specific and common features. Following that, feature recalibration block (RFB) based on modality-wise attention is used to recalibrate the semantic features of each modality, enabling the model to focus on the features that are beneficial for glioma segmentation. These recalibrated features are input into the decoder to obtain the segmentation results. To verify the superiority of the proposed method, we compare it with several state-of-the-art (SOTA) methods in terms of Dice, average symmetric surface distance (ASSD), HD95 and volumetric similarity (Vs). The comparison results show that the average Dice, ASSD, HD95 and Vs of DCL-MANet on all tumor regions are improved at least by 0.66%, 3.47%, 8.94% and 1.07% respectively. For small enhance tumor (ET) region, the corresponding improvement can be up to 0.37%, 7.83%, 11.32%, and 1.35%, respectively. In addition, the ablation results demonstrate the effectiveness of the proposed DCL and RFB, and combining them can significantly increase Dice (1.59%) and Vs (1.54%) while decreasing ASSD (40.51%) and HD95 (45.16%) on ET region. The proposed DCL-MANet could disentangle multimodal features and enhance the semantics of modality-dependent features, providing a potential means to accurately segment small lesion regions in gliomas.

The regulatory relationship between NAMPT and PD-L1 in cancer and identification of a dual-targeting inhibitor.

Cancer is a heterogeneous disease. Although both tumor metabolism and tumor immune microenvironment are recognized as driving factors in tumorigenesis, the relationship between them is still not well-known, and potential combined targeting approaches remain to be identified. Here, we demonstrated a negative correlation between the expression of NAMPT, an NAD+ metabolism enzyme, and PD-L1 expression in various cancer cell lines. A clinical study showed that a NAMPTHigh PD-L1Low expression pattern predicts poor prognosis in patients with various cancers. In addition, pharmacological inhibition of NAMPT results in the transcription upregulation of PD-L1 by SIRT-mediated acetylation change of NF-κB p65, and blocking PD-L1 would induce NAMPT expression through a HIF-1-dependent glycolysis pathway. Based on these findings, we designed and synthesized a dual NAMPT/PD-L1 targeting compound, LZFPN-90, which inhibits cell growth in a NAMPT-dependent manner and blocks the cell cycle, subsequently inducing apoptosis. Under co-culture conditions, LZFPN-90 treatment contributes to the proliferation and activation of T cells and blocks the growth of cancer cells. Using mice bearing genetically manipulated tumors, we confirmed that LZFPN-90 exerted target-dependent antitumor activities, affecting metabolic processes and the immune system. In conclusion, our results demonstrate the relevance of NAD+-related metabolic processes in antitumor immunity and suggest that co-targeting NAD+ metabolism and PD-L1 represents a promising therapeutic approach.

The functional significance of circRNA/miRNA/mRNA interactions as a regulatory network in lung cancer biology.

Lung cancer, the leading cause of cancer-related deaths, presents significant challenges to patients due to its poor prognosis. Recent research has increasingly implicated circular RNAs in the development and progression of lung cancer. These circular RNAs have been found to impact various aspects of tumor behavior, including proliferation, metastasis, cell cycle regulation, apoptosis, cancer stem cells, therapy response, and the tumor microenvironment. One of the key mechanisms by which circular RNAs exert their influence is through their ability to act as miRNA sponges, sequestering microRNAs and preventing them from targeting other RNA molecules. Accumulating evidence suggests that circular RNAs can function as competing endogenous RNAs, affecting the expression of target mRNAs by sequestering microRNAs. Dysregulation of competing endogenous RNAs networks involving circular RNAs, microRNAs, and mRNAs leads to the aberrant expression of oncogenes and tumor suppressors involved in lung cancer pathogenesis. Understanding the dynamic interplay and molecular mechanisms among circular RNAs, microRNAs, and mRNAs holds great promise for advancing early diagnosis, personalized therapeutic interventions, and improved patient outcomes in lung cancer. Therefore, this study aims to provide an in-depth exploration of the executive roles of circular RNAs/microRNAs/ mRNAs interactions in lung cancer pathogenesis and their potential utility for diagnosing lung cancer, predicting patient prognosis, and guiding targeted therapies. By offering a comprehensive overview of the dysregulation of the axes as driving factors in lung cancer, we aim to pave the way for their translation into clinical practice in the future.

From genomic spectrum of NTRK genes to adverse effects of its inhibitors, a comprehensive genome-based and real-world pharmacovigilance analysis.

Introduction: The discovery of neurotrophic tyrosine receptor kinase (NTRK) gene fusions has facilitated the development of precision oncology. Two first-generation NTRK inhibitors (larotrectinib and entrectinib) are currently approved for the treatment of patients with solid tumors harboring NTRK gene fusions. Nevertheless, comprehensive NTRK profiling at the pan-cancer genomic level and real-world studies pertaining to the adverse events of NTRK inhibitors are lacking. Methods: We characterize the genome of NTRK at the pan-cancer level through multi-omics databases such as The Cancer Genome Atlas (TCGA). Through the FDA Adverse Event Reporting System (FAERS) database, we collect reports of entrectinib and larotrectinib-induced adverse events and perform a pharmacovigilance analysis using various disproportionality methods. Results: NTRK1/2/3 expression is lower in most tumor tissues, while they have higher methylation levels. NTRK gene expression has prognostic value in some cancer types, such as breast invasive carcinoma (BRCA). The cancer type with highest NTRK alteration frequency is skin cutaneous melanoma (SKCM) (31.98%). Thyroid carcinoma (THCA) has the largest number of NTRK fusion cases, and the most common fusion pair is ETV6-NTRK3. Adverse drug events (ADEs) obtained from the FAERS database for larotrectinib and entrectinib are 524 and 563, respectively. At the System Organ Class (SOC) level, both drugs have positive signal value for "nervous system disorder". Other positive signals for entrectinib include "cardiac disorders", "metabolism and nutrition disorders", while for larotrectinib, it is "hepatobiliary disorders". The unexpected signals are also listed in detail. ADEs of the two NTRK inhibitors mainly occur in the first month. The median onset time of ADEs for entrectinib and larotrectinib was 16 days (interquartile range [IQR] 6-86.5) and 44 days ([IQR] 7-136), respectively. Conclusion: Our analysis provides a broad molecular view of the NTRK family. The real-world adverse drug event analysis of entrectinib and larotrectinib contributes to more refined medication management.

EZH2/G9a interact to mediate drug resistance in non-small-cell lung cancer by regulating the SMAD4/ERK/c-Myc signaling axis.

Drug resistance is the leading problem in non-small-cell lung cancer (NSCLC) therapy. The contribution of histone methylation in mediating malignant phenotypes of NSCLC is well known. However, the role of histone methylation in NSCLC drug-resistance mechanisms remains unclear. Here, our data show that EZH2 and G9a, two histone methyltransferases, are involved in the drug resistance of NSCLC. Gene manipulation results indicate that the combination of EZH2 and G9a promotes tumor growth and mediates drug resistance in a complementary manner. Importantly, clinical study demonstrates that co-expression of both enzymes predicts a poor outcome in patients with NSCLC. Mechanistically, G9a and EZH2 interact and promote the silencing of the tumor-suppressor gene SMAD4, activating the ERK/c-Myc signaling pathway. Finally, SU08, a compound targeting both EZH2 and G9a, is demonstrated to sensitize resistant cells to therapeutic drugs by regulating the SMAD4/ERK/c-Myc signaling axis. These findings uncover the resistance mechanism and a strategy for reversing NSCLC drug resistance.

Multiple strategies, including 6mA methylation, affecting plant alternative splicing in allopolyploid peanut.

Alternative splicing (AS), an important post-transcriptional regulation mechanism in eukaryotes, can significantly increase transcript diversity and contribute to gene expression regulation and many other complicated developmental processes. While plant gene AS events are well described, few studies have investigated the comprehensive regulation machinery of plant AS. Here, we use multi-omics to analyse peanut AS events. Using long-read isoform sequencing, 146 464 full-length non-chimeric transcripts were obtained, resulting in annotation corrections for 1782 genes and the identification of 4653 new loci. Using Iso-Seq RNA sequences, 271 776 unique splice junctions were identified, 82.49% of which were supported by transcriptome data. We characterized 50 977 polyadenylation sites for 23 262 genes, 12 369 of which had alternative polyadenylation sites. AS allows differential regulation of the same gene by miRNAs at the isoform level coupled with polyadenylation. In addition, we identified many long non-coding RNAs and fusion transcripts. There is a suppressed effect of 6mA on AS and gene expression. By analysis of chromatin structures, the genes located in the boundaries of topologically associated domains, proximal chromosomal telomere regions, inter- or intra-chromosomal loops were found to have more unique splice isoforms, higher expression, lower 6mA and more transposable elements (TEs) in their gene bodies than the other genes, indicating that chromatin interaction, 6mA and TEs play important roles in AS and gene expression. These results greatly refine the peanut genome annotation and contribute to the study of gene expression and regulation in peanuts. This work also showed AS is associated with multiple strategies for gene regulation.

De Novo Generation and Identification of Novel Compounds with Drug Efficacy Based on Machine Learning.

One of the main challenges in small molecule drug discovery is finding novel chemical compounds with desirable activity. Traditional drug development typically begins with target selection, but the correlation between targets and disease remains to be further investigated, and drugs designed based on targets may not always have the desired drug efficacy. The emergence of machine learning provides a powerful tool to overcome the challenge. Herein, a machine learning-based strategy is developed for de novo generation of novel compounds with drug efficacy termed DTLS (Deep Transfer Learning-based Strategy) by using dataset of disease-direct-related activity as input. DTLS is applied in two kinds of disease: colorectal cancer (CRC) and Alzheimer's disease (AD). In each case, novel compound is discovered and identified in in vitro and in vivo disease models. Their mechanism of actionis further explored. The experimental results reveal that DTLS can not only realize the generation and identification of novel compounds with drug efficacy but also has the advantage of identifying compounds by focusing on protein targets to facilitate the mechanism study. This work highlights the significant impact of machine learning on the design of novel compounds with drug efficacy, which provides a powerful new approach to drug discovery.

ALKBH5 regulates paclitaxel resistance in NSCLC via inhibiting CEMIP-mediated EMT.

N6-methyladenosine (m6A) is the most prevalent mRNA modification, and it is verified to be closely correlated with cancer occurrence and progression. The m6A demethylase ALKBH5 (alkB homolog 5) is dysregulated in various cancers. However, the role and underlying mechanism of ALKBH5 in the pathogenesis and especially the chemo-resistance of non-small cell lung cancer (NSCLC) is poorly elucidated. The current study shows that ALKBH5 expression is reduced in paclitaxel (PTX) resistant NSCLC cells and down-regulation of ALKBH5 usually implies poor prognosis of NSCLC patients. Over-expression of ALKBH5 in PTX-resistant cells can suppress cell proliferation and enhance chemo-sensitivity, while knockdown of ALKBH5 exerts the opposite effect, which further supports the tumor suppressive role of ALKBH5. Over-expression of ALKBH5 can also reverse the epithelial-mesenchymal transition (EMT) process in PTX-resistant cancer cells. Mechanistically, data from RNA-seq, real-time PCR and western blotting indicate that CEMIP (cell migration inducing hyaluronidase 1), also known as KIAA1199, may be the downstream target of ALKBH5. Furthermore, ALKBH5 negatively regulates the CEMIP level by reducing the stability of CEMIP mRNA. Collectively, the current data demonstrate that the ALKBH5/CEMIP axis modulates the EMT process in NSCLC, which in turn regulates the chemo-sensitivity of cancer cells to PTX.