ac4C-AFL: A high-precision identification of human mRNA N4-acetylcytidine sites based on adaptive feature representation learning.

RNA N4-acetylcytidine (ac4C) is a highly conserved RNA modification that plays a crucial role in controlling mRNA stability, processing, and translation. Consequently, accurate identification of ac4C sites across the genome is critical for understanding gene expression regulation mechanisms. In this study, we have developed ac4C-AFL, a bioinformatics tool that precisely identifies ac4C sites from primary RNA sequences. In ac4C-AFL, we identified the optimal sequence length for model building and implemented an adaptive feature representation strategy that is capable of extracting the most representative features from RNA. To identify the most relevant features, we proposed a novel ensemble feature importance scoring strategy to rank features effectively. We then used this information to conduct the sequential forward search, which individually determine the optimal feature set from the 16 sequence-derived feature descriptors. Utilizing these optimal feature descriptors, we constructed 176 baseline models using 11 popular classifiers. The most efficient baseline models were identified using the two-step feature selection approach, whose predicted scores were integrated and trained with the appropriate classifier to develop the final prediction model. Our rigorous cross-validations and independent tests demonstrate that ac4C-AFL surpasses contemporary tools in predicting ac4C sites. Moreover, we have developed a publicly accessible web server at https://balalab-skku.org/ac4C-AFL/.

Establishment of canine mammary gland tumor cell lines harboring PI3K/Akt activation as a therapeutic target.

Canine mammary gland tumors (MGT) have a poor prognosis in intact female canines, posing a clinical challenge. This study aimed to establish novel canine mammary cancer cell lines from primary tumors and characterize their cellular and molecular features to find potential therapeutic drugs. The MGT cell lines demonstrated rapid cell proliferation and colony formation in an anchorage-independent manner. Vimentin and α-SMA levels were significantly elevated in MGT cell lines compared to normal canine kidney (MDCK) cells, while CDH1 expression was either significantly lower or not detected at all, based on quantitative real-time PCR (qRT-PCR) analysis. Functional annotation and enrichment analysis revealed that epithelial-mesenchymal transition (EMT) phenotypes and tumor-associated pathways, particularly the PI3K/Akt signaling pathway, were upregulated in MGT cells. BYL719 (Alpelisib), a PI3K inhibitor, was also examined for cytotoxicity on the MGT cell lines. The results show that BYL719 can significantly inhibit the proliferation of MGT cell lines in vitro. Overall, our findings suggest that the MGT cell lines may be valuable for future studies on the development, progression, metastasis, and management of tumors.

3-fucosyllactose-mediated modulation of immune response against virus infection.

Viral pathogens, particularly influenza and SARS-CoV-2, pose a significant global health challenge. Given the immunomodulatory properties of human milk oligosaccharides, in particular 2'-fucosyllactose and 3-fucosyllactose (3-FL), we investigated their dietary supplementation effects on antiviral responses in mouse models. This study revealed distinct immune modulations induced by 3-FL. RNA-sequencing data showed that 3-FL increased the expression of interferon receptors, such as Interferon Alpha and Beta Receptor (IFNAR) and Interferon Gamma Receptor (IFNGR), while simultaneously downregulating interferons and interferon-stimulated genes, an effect not observed with 2'-fucosyllactose supplementation. Such modulation enhanced antiviral responses in both cell culture and animal models while attenuating pre-emptive inflammatory responses. Nitric oxide concentrations in 3-FL-supplemented A549 cells and mouse lung tissues were elevated exclusively upon infection, reaching 5.8- and 1.9-fold increases over control groups, respectively. In addition, 3-FL promoted leukocyte infiltration into the site of infection upon viral challenge. 3-FL supplementation provided protective efficacy against lethal influenza challenge in mice. The demonstrated antiviral efficacy spanned multiple influenza strains and extended to SARS-CoV-2. In conclusion, 3-FL is a unique immunomodulator that helps protect the host from viral infection while suppressing inflammation prior to infection.

MiR-29 and MiR-140 regulate TRAIL-induced drug tolerance in lung cancer.

Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) has chemotherapeutic potential as a regulator of an extrinsic apoptotic ligand, but its effect as a drug is limited by innate and acquired resistance. Recent findings suggest that an intermediate drug tolerance could mediate acquired resistance, which has made the main obstacle for limited utility of TRAIL as an anti-cancer therapeutics. We propose miRNA-dependent epigenetic modification drives the drug tolerant state in TRAIL-induced drug tolerant (TDT). Transcriptomic analysis revealed miR-29 target gene activation in TDT cells, showing oncogenic signature in lung cancer. Also, the restored TRAIL-sensitivity was associated with miR-29ac and 140-5p expressions, which is known as tumor suppressor by suppressing oncogenic protein RSK2 (p90 ribosomal S6 kinase), further confirmed in patient samples. Moreover, we extended this finding into 119 lung cancer cell lines from public data set, suggesting a significant correlation between TRAIL-sensitivity and RSK2 mRNA expression. Finally, we found that increased RSK2 mRNA is responsible for NF-κB activation, which we previously showed as a key determinant in both innate and acquired TRAIL-resistance. Our findings support further investigation of miR-29ac and -140-5p inhibition to maintain TRAIL-sensitivity and improve the durability of response to TRAIL in lung cancer.

The impact of MEIS1 TALE homeodomain transcription factor knockdown on glioma stem cell growth.

Myeloid ecotropic virus insertion site 1 (MEIS1) is a HOX co-factor necessary for organ development and normal hematopoiesis. Recently, MEIS1 has been linked to the development and progression of various cancers. However, its role in gliomagenesis particularly on glioma stem cells (GSCs) remains unclear. Here, we demonstrate that MEIS1 is highly upregulated in GSCs compared to normal, and glioma cells and to its differentiated counterparts. Inhibition of MEIS1 expression by shRNA significantly reduced GSC growth in both in vitro and in vivo experiments. On the other hand, integrated transcriptomics analyses of glioma datasets revealed that MEIS1 expression is correlated to cell cycle-related genes. Clinical data analysis revealed that MEIS1 expression is elevated in high-grade gliomas, and patients with high MEIS1 levels have poorer overall survival outcomes. The findings suggest that MEIS1 is a prognostic biomarker for glioma patients and a possible target for developing novel therapeutic strategies against GBM.

Advancing the accuracy of SARS-CoV-2 phosphorylation site detection via meta-learning approach.

The worldwide appearance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has generated significant concern and posed a considerable challenge to global health. Phosphorylation is a common post-translational modification that affects many vital cellular functions and is closely associated with SARS-CoV-2 infection. Precise identification of phosphorylation sites could provide more in-depth insight into the processes underlying SARS-CoV-2 infection and help alleviate the continuing COVID-19 crisis. Currently, available computational tools for predicting these sites lack accuracy and effectiveness. In this study, we designed an innovative meta-learning model, Meta-Learning for Serine/Threonine Phosphorylation (MeL-STPhos), to precisely identify protein phosphorylation sites. We initially performed a comprehensive assessment of 29 unique sequence-derived features, establishing prediction models for each using 14 renowned machine learning methods, ranging from traditional classifiers to advanced deep learning algorithms. We then selected the most effective model for each feature by integrating the predicted values. Rigorous feature selection strategies were employed to identify the optimal base models and classifier(s) for each cell-specific dataset. To the best of our knowledge, this is the first study to report two cell-specific models and a generic model for phosphorylation site prediction by utilizing an extensive range of sequence-derived features and machine learning algorithms. Extensive cross-validation and independent testing revealed that MeL-STPhos surpasses existing state-of-the-art tools for phosphorylation site prediction. We also developed a publicly accessible platform at https://balalab-skku.org/MeL-STPhos. We believe that MeL-STPhos will serve as a valuable tool for accelerating the discovery of serine/threonine phosphorylation sites and elucidating their role in post-translational regulation.

7ß-22 Dihydroxyhopane, Isolated from the Sub-Antarctic Lichen, Inhibits the Viability and Stemness in Glioma Stem Like Cells.

Background: Glioma stem cells (GSCs) have been reported to contribute to tumor initiation and relapse, therapy resistance, and intra-tumoral heterogeneity of glioblastoma multiforme. Therefore, inhibiting GSCs presents a critical therapeutic tactic to suppress the aggressiveness of tumors. Methods: In this study, we examined the effects of 7ß-22 dihydroxyhopane (AP 18), isolated from the sub-Antarctic lichen, Pseudocyphellaria freycinetii. The cytotoxic effect of AP 18 and its effects on cell proliferation were assessed by alamarBlue assay and 5-ethynyl-2'-deoxyuridine (EdU) assay. Real-time confluence analysis was performed with a Celloger automatic live cell imaging system. Western Blotting and 3-D optical diffraction tomography (ODT) imaging were performed to determine whether apoptosis was triggered by AP 18. A Limiting dilution assay and qRT-PCR were performed to investigate the impact of AP 18 on GSC stemness. Results: AP 18 significantly reduced GSCs viability and proliferation, inducing programmed cell death identified by Annexin V/PI staining and had effects on morphologic features determined by 3-D ODT. Interestingly, treatment with AP 18 suppressed stemness features. Conclusion: Taken together, our results suggest that AP 18 might be a potential therapeutic agent to target GSCs.

Lucidumol A, Purified Directly from Ganoderma lucidum, Exhibits Anticancer Effect and Cellular Inflammatory Response in Colorectal Cancer.

Colorectal cancer (CRC) is a deadly disease regardless of sex, and a few therapeutic approaches have been fully developed at advanced stages, even if some strategies have durable clinical benefits, such as immunotherapy and chemotherapy. Ganoderma lucidum has been recognized as an organism that suppresses tumors and inflammation; however, the molecular mechanisms induced by a triterpenoid in Ganoderma lucidum, Lucidumol A, have not yet been fully explored in CRC and inflammatory responses. To this end, we extracted Lucidumol A from Ganoderma lucidum and analyzed its anticancer effect and anti-inflammatory potential in CRC cell lines and RAW264.7 macrophage-derived cell lines, respectively. A series of in vitro experiments including cell survival, wound healing, and migration assays were performed to determine the role of Lucidumol A in the CRC cell line. We also analyzed inflammatory responses using qRT-PCR, Western Blot, and ELISA in RAW 264.7 macrophaged-derived cell lines exposed to various concentrations of Lucidumol A. Lucidumol A efficiently suppressed the metastatic potential of CRC at very low concentrations. Furthermore, significant anti-inflammatory activities were observed in Lucidumol A-treated RAW264.7 cells through modulation of inflammation-associated marker genes and cytokines. In conclusion, Lucidumol A plays an important role in Ganoderma lucidum-dependent tumor suppression and anti-inflammation, suggesting different strategies to treat CRC patients, and other diseases evoked by proinflammatory cytokines, despite the need to explore further its mechanism of action.

MLACP 2.0: An updated machine learning tool for anticancer peptide prediction.

Anticancer peptides are emerging anticancer drug that offers fewer side effects and is more effective than chemotherapy and targeted therapy. Predicting anticancer peptides from sequence information is one of the most challenging tasks in immunoinformatics. In the past ten years, machine learning-based approaches have been proposed for identifying ACP activity from peptide sequences. These methods include our previous method MLACP (developed in 2017) which made a significant impact on anticancer research. MLACP tool has been widely used by the research community, however, its robustness must be improved significantly for its continued practical application. In this study, the first large non-redundant training and independent datasets were constructed for ACP research. Using the training dataset, the study explored a wide range of feature encodings and developed their respective models using seven different conventional classifiers. Subsequently, a subset of encoding-based models was selected for each classifier based on their performance, whose predicted scores were concatenated and trained through a convolutional neural network (CNN), whose corresponding predictor is named MLACP 2.0. The evaluation of MLACP 2.0 with a very diverse independent dataset showed excellent performance and significantly outperformed the recent ACP prediction tools. Additionally, MLACP 2.0 exhibits superior performance during cross-validation and independent assessment when compared to CNN-based embedding models and conventional single models. Consequently, we anticipate that our proposed MLACP 2.0 will facilitate the design of hypothesis-driven experiments by making it easier to discover novel ACPs. The MLACP 2.0 is freely available at https://balalab-skku.org/mlacp2.

The EEF1AKMT3/MAP2K7/TP53 axis suppresses tumor invasiveness and metastasis in gastric cancer.

The importance of methylation in the tumorigenic responses of nonhistone proteins, such as TP53, PTEN, RB1, AKT, and STAT3, has been emphasized in numerous studies. In parallel, the corresponding nonhistone protein methyltransferases have been acknowledged in the pathophysiology of cancer. Thus, this study aimed to explore the pathological role of a nonhistone methyltransferase in gastric cancer (GC), identify nonhistone substrate protein, and understand the underlying mechanism. Interestingly, among the 24 methyltransferases and methyltransferase family 16 (MTF16) proteins, EEF1AKMT3 (METTL21B) expression was prominently lower in GC tissues than in normal adjacent tissues and was associated with a worse prognosis. In addition, EEF1AKMT3-knockdown induced gastric tumor invasiveness and migration. Through gain and loss-of-function studies, mass spectrometry analysis, RNA-seq, and phospho-antibody array, we identified EEF1AKMT3 as a novel tumor-suppressive methyltransferase that catalyzes the monomethylation of MAP2K7 (MKK7) at K296, thereby decreasing the phosphorylation, ubiquitination, and degradation of TP53. Furthermore, EEF1AKMT3, p-MAP2K7, and TP53 protein levels were positively correlated in GC tissues. Collectively, our results delineate the tumor-suppressive function of the EEF1AKMT3/MAP2K7/TP53 signaling axis and suggest the dysregulation of the signaling axis as potential targeted therapy in GC.

TACOS: a novel approach for accurate prediction of cell-specific long noncoding RNAs subcellular localization.

Long noncoding RNAs (lncRNAs) are primarily regulated by their cellular localization, which is responsible for their molecular functions, including cell cycle regulation and genome rearrangements. Accurately identifying the subcellular location of lncRNAs from sequence information is crucial for a better understanding of their biological functions and mechanisms. In contrast to traditional experimental methods, bioinformatics or computational methods can be applied for the annotation of lncRNA subcellular locations in humans more effectively. In the past, several machine learning-based methods have been developed to identify lncRNA subcellular localization, but relevant work for identifying cell-specific localization of human lncRNA remains limited. In this study, we present the first application of the tree-based stacking approach, TACOS, which allows users to identify the subcellular localization of human lncRNA in 10 different cell types. Specifically, we conducted comprehensive evaluations of six tree-based classifiers with 10 different feature descriptors, using a newly constructed balanced training dataset for each cell type. Subsequently, the strengths of the AdaBoost baseline models were integrated via a stacking approach, with an appropriate tree-based classifier for the final prediction. TACOS displayed consistent performance in both the cross-validation and independent assessments compared with the other two approaches employed in this study. The user-friendly online TACOS web server can be accessed at https://balalab-skku.org/TACOS.

Correction: MiR-34a/c-Dependent PDGFR-α/ß Downregulation Inhibits Tumorigenesis and Enhances TRAIL-Induced Apoptosis in Lung Cancer.

[This corrects the article DOI: 10.1371/journal.pone.0067581.].

Promyelocytic Leukemia Proteins Regulate Fanconi Anemia Gene Expression.

Promyelocytic leukemia (PML) protein is the core component of subnuclear structures called PML nuclear bodies that are known to play important roles in cell survival, DNA damage responses, and DNA repair. Fanconi anemia (FA) proteins are required for repairing interstrand DNA crosslinks (ICLs). Here we report a novel role of PML proteins, regulating the ICL repair pathway. We found that depletion of the PML protein led to the significant reduction of damage-induced FANCD2 mono-ubiquitination and FANCD2 foci formation. Consistently, the cells treated with siRNA against PML showed enhanced sensitivity to a crosslinking agent, mitomycin C. Further studies showed that depletion of PML reduced the protein expression of FANCA, FANCG, and FANCD2 via reduced transcriptional activity. Interestingly, we observed that damage-induced CHK1 phosphorylation was severely impaired in cells with depleted PML, and we demonstrated that CHK1 regulates FANCA, FANCG, and FANCD2 transcription. Finally, we showed that inhibition of CHK1 phosphorylation further sensitized cancer cells to mitomycin C. Taken together, these findings suggest that the PML is critical for damage-induced CHK1 phosphorylation, which is important for FA gene expression and for repairing ICLs.

MicroRNA-138 suppresses glioblastoma proliferation through downregulation of CD44.

Tumor suppressive microRNAs (miRNAs) are increasingly implicated in the development of anti-tumor therapy by reprogramming gene network that are aberrantly regulated in cancer cells. This study aimed to determine the therapeutic potential of putative tumor suppressive miRNA, miR-138, against glioblastoma (GBM). Whole transcriptome and miRNA expression profiling analyses on human GBM patient tissues identified miR-138 as one of the significantly downregulated miRNAs with an inverse correlation with CD44 expression. Transient overexpression of miR-138 in GBM cells inhibited cell proliferation, cell cycle, migration, and wound healing capability. We unveiled that miR-138 negatively regulates the expression of CD44 by directly binding to the 3' UTR of CD44. CD44 inhibition by miR-138 resulted in an inhibition of glioblastoma cell proliferation in vitro through cell cycle arrest as evidenced by a significant induction of p27 and its translocation into nucleus. Ectopic expression of miR-138 also increased survival rates in mice that had an intracranial xenograft tumor derived from human patient-derived primary GBM cells. In conclusion, we demonstrated a therapeutic potential of tumor suppressive miR-138 through direct downregulation of CD44 for the treatment of primary GBM.

miR-106a-363 cluster in extracellular vesicles promotes endogenous myocardial repair via Notch3 pathway in ischemic heart injury.

Endogenous capability of the post-mitotic human heart holds great promise to restore the injured myocardium. Recent evidence indicates that the extracellular vesicles (EVs) regulate cardiac homeostasis and regeneration. Here, we investigated the molecular mechanism of EVs for self-repair. We isolated EVs from human iPSC-derived cardiomyocytes (iCMs), which were exposed to hypoxic (hEVs) and normoxic conditions (nEVs), and examined their roles in in vitro and in vivo models of cardiac injury. hEV treatment significantly improved the viability of hypoxic iCMs in vitro and cardiac function of severely injured murine myocardium in vivo. Microarray analysis of the EVs revealed significantly enriched expression of the miR-106a-363 cluster (miR cluster) in hEVs vs. nEVs. This miR cluster preserved survival and contractility of hypoxia-injured iCMs and maintained murine left-ventricular (LV) chamber size, improved LV ejection fraction, and reduced myocardial fibrosis of the injured myocardium. RNA-Seq analysis identified Jag1-Notch3-Hes1 as a target intracellular pathway of the miR cluster. Moreover, the study found that the cell cycle activator and cytokinesis genes were significantly up-regulated in the iCMs treated with miR cluster and Notch3 siRNA. Together, these results suggested that the miR cluster in the EVs stimulated cardiomyocyte cell cycle re-entry by repressing Notch3 to induce cell proliferation and augment myocardial self-repair. The miR cluster may represent an effective therapeutic approach for ischemic cardiomyopathy.

Targeting Non-Oncogene Addiction for Cancer Therapy.

While Next-Generation Sequencing (NGS) and technological advances have been useful in identifying genetic profiles of tumorigenesis, novel target proteins and various clinical biomarkers, cancer continues to be a major global health threat. DNA replication, DNA damage response (DDR) and repair, and cell cycle regulation continue to be essential systems in targeted cancer therapies. Although many genes involved in DDR are known to be tumor suppressor genes, cancer cells are often dependent and addicted to these genes, making them excellent therapeutic targets. In this review, genes implicated in DNA replication, DDR, DNA repair, cell cycle regulation are discussed with reference to peptide or small molecule inhibitors which may prove therapeutic in cancer patients. Additionally, the potential of utilizing novel synthetic lethal genes in these pathways is examined, providing possible new targets for future therapeutics. Specifically, we evaluate the potential of TONSL as a novel gene for targeted therapy. Although it is a scaffold protein with no known enzymatic activity, the strategy used for developing PCNA inhibitors can also be utilized to target TONSL. This review summarizes current knowledge on non-oncogene addiction, and the utilization of synthetic lethality for developing novel inhibitors targeting non-oncogenic addiction for cancer therapy.

Fhit induces the reciprocal suppressions between Lin28/Let-7 and miR-17/92miR.

Objective: Fhit gene is known as a genome "caretaker" and frequently inactivated by deletion or hypermethylation on the promoter in several cancers. In spite of several lines of evidence, the exact mechanism underlying Fhit-induced biology is relatively less studied. This study will focus the role of Fhit in regulating Lin28 and microRNAs (miRNAs) loop. Material and Methods: To this end, we employed Fhit overexpressing isogenic cell lines to conduct miRNA nanostring array, and differentially expressed miRNAs were identified. Using real-time PCR and Western blot analysis, expression levels of Lin28b or miRNAs were investigated in response to the overexpression of Fhit gene in H1299 lung cancer cells. Results: A series of in vitro including gene nanostring analyses revealed that Lin28B protein was induced by Fhit gene overexpression, which consequently suppressed Let-7 miRNAs. Also, we found that miRNAs in miR-17/92 clusters are redundantly increased and there is an inverse correlation between Let-7 and miR-17/92 clusters in Fhit-expressing cells. Also, a series of in vitro experiments suggests that ELF-1- and/or STAT1-dependent Lin28b regulation is responsible for Let-7 induction in Fhit-expressing cancer cells. Conclusions: Based on the same experimental system proving that Fhit gene has a robust role in suppressing tumor progression and epithelial-mesenchymal transition, our data show that Fhit mediates the negative feedback between Lin28/Let-7 axis and miR-17/-92 miRNA although the physiological relevance of current interesting observation should be further investigated.

Noninvasive Early Identification of Therapeutic Benefit from Immune Checkpoint Inhibition.

Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we demonstrate that pre-treatment circulating tumor DNA (ctDNA) and peripheral CD8 T cell levels are independently associated with DCB. We further show that ctDNA dynamics after a single infusion can aid in identification of patients who will achieve DCB. Integrating these determinants, we developed and validated an entirely noninvasive multiparameter assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA-On-treatment) that robustly predicts which patients will achieve DCB with higher accuracy than any individual feature. Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICIs.

KEAP1/NFE2L2 Mutations Predict Lung Cancer Radiation Resistance That Can Be Targeted by Glutaminase Inhibition.

Tumor genotyping is not routinely performed in localized non-small cell lung cancer (NSCLC) due to lack of associations of mutations with outcome. Here, we analyze 232 consecutive patients with localized NSCLC and demonstrate that KEAP1 and NFE2L2 mutations are predictive of high rates of local recurrence (LR) after radiotherapy but not surgery. Half of LRs occurred in tumors with KEAP1/NFE2L2 mutations, indicating that they are major molecular drivers of clinical radioresistance. Next, we functionally evaluate KEAP1/NFE2L2 mutations in our radiotherapy cohort and demonstrate that only pathogenic mutations are associated with radioresistance. Furthermore, expression of NFE2L2 target genes does not predict LR, underscoring the utility of tumor genotyping. Finally, we show that glutaminase inhibition preferentially radiosensitizes KEAP1-mutant cells via depletion of glutathione and increased radiation-induced DNA damage. Our findings suggest that genotyping for KEAP1/NFE2L2 mutations could facilitate treatment personalization and provide a potential strategy for overcoming radioresistance conferred by these mutations. SIGNIFICANCE: This study shows that mutations in KEAP1 and NFE2L2 predict for LR after radiotherapy but not surgery in patients with NSCLC. Approximately half of all LRs are associated with these mutations and glutaminase inhibition may allow personalized radiosensitization of KEAP1/NFE2L2-mutant tumors.This article is highlighted in the In This Issue feature, p. 1775.