Serum hydroxycotinine was associated with chronic kidney disease (CKD): a cross-sectional study based on NHANES

OBJECTIVE

Smoking has been suggested as a modifiable and cardiovascular risk factor for chronic kidney disease (CKD). Although long-term smoking has been associated with CKD, the potential relationship between its metabolite hydroxycotinine and CKD has not been clarified.

METHODS

A total of 8,544 participants aged 20 years and above from the National Health and Nutrition Examination Survey (NHANES) 2017 - March 2020 were enrolled in our study. CKD was defined by estimated glomerular filtration rate (eGFR) < 60 mL/(min*1.73 m2). Serum hydroxycotinine was measured by an isotope-dilution high-performance liquid chromatography/atmospheric pressure chemical ionization tandem mass spectrometric (ID HPLC-APCI MS/MS) method with a lower limit of detections (LLOD) at 0.015 ng/mL. The non-linear relationship was explored with restricted cubic splines (RCS). Pearson's correlation coefficient and a multivariate logistic regression model were used for correlation analysis.

RESULTS

Serum hydroxycotinine and eGFR were negatively correlated in both non-CKD group (r= -0.05, p < 0.001) and CKD group (r= -0.04, p < 0.001). After serum hydoxycotinine dichotominzed with LLOD, serum hydroxycotinine ≥ 0.015 ng/mL was negatively correlated with eGFR not only in non-CKD group (r = -0.05, p < 0.001) but also in CKD group (r = -0.09, p < 0.001). After adjusting for comprehensive confounders, results from the multivariate logistic regression analysis showed that participants with serum hydroxycotinine ≥ 0.015 ng/mL had increased odds of CKD (OR = 1.505, p < 0.001).

CONCLUSIONS

Serum hydroxycotinine might be positively associated with CKD. Further study is warranted to find the right concentration of hydroxycotinine to measure the CKD.

Simulation- and AI-directed optimization of 4,6-substituted 1,3,5-triazin-2(1H)-ones as inhibitors of human DNA topoisomerase IIα

The 4,6-substituted-1,3,5-triazin-2(1H)-ones are promising inhibitors of human DNA topoisomerase IIα. To further develop this chemical class targeting the enzyme´s ATP binding site, the triazin-2(1H)-one substitution position 6 was optimized. Inspired by binding of preclinical substituted 9H-purine derivative, bicyclic substituents were incorporated at position 6 and the utility of this modification was validated by a combination of molecular simulations, dynamic pharmacophores, and free energy calculations. Considering also predictions of Deepfrag, a software developed for structure-based lead optimization based on deep learning, compounds with both bicyclic and monocyclic substitutions were synthesized and investigated for their inhibitory activity. The SAR data showed that the bicyclic substituted compounds exhibited good inhibition of topo IIα, comparable to their mono-substituted counterparts. Further evaluation on a panel of human protein kinases showed selectivity for the inhibition of topo IIα. Mechanistic studies indicated that the compounds acted predominantly as catalytic inhibitors, with some exhibiting topo IIα poison effects at higher concentrations. Integration of STD NMR experiments and molecular simulations, provided insights into the binding model and highlighted the importance of the Asn120 interaction and hydrophobic interactions with substituents at positions 4 and 6. In addition, NCI-60 screening demonstrated cytotoxicity of the compounds with bicyclic substituents and identified sensitive human cancer cell lines, underlining the translational relevance of our findings for further preclinical development of this class of compounds. The study highlights the synergy between simulation and AI-based approaches in efficiently guiding molecular design for drug optimization, which has implications for further preclinical development of this class of compounds.

Integrated noninvasive diagnostics for prediction of survival in immunotherapy

Background

Integrating complementary diagnostic data sources promises enhanced robustness in the predictive performance of artificial intelligence (AI) models, a crucial requirement for future clinical validation/implementation. In this study, we investigate the potential value of integrating data from noninvasive diagnostic modalities, including chest computed tomography (CT) imaging, routine laboratory blood tests, and clinical parameters, to retrospectively predict 1-year survival in a cohort of patients with advanced non-small-cell lung cancer, melanoma, and urothelial cancer treated with immunotherapy.

Patients and methods

The study included 475 patients, of whom 444 had longitudinal CT scans and 475 had longitudinal laboratory data. An ensemble of AI models was trained on data from each diagnostic modality, and subsequently, a model-agnostic integration approach was adopted for combining the prediction probabilities of each modality and producing an integrated decision.

Results

Integrating different diagnostic data demonstrated a modest increase in predictive performance. The highest area under the curve (AUC) was achieved by CT and laboratory data integration (AUC of 0.83, 95% confidence interval 0.81-0.85, P < 0.001), whereas the performance of individual models trained on laboratory and CT data independently yielded AUCs of 0.81 and 0.73, respectively.

Conclusions

In our retrospective cohort, integrating different noninvasive data modalities improved performance.

DataXflow: Synergizing data-driven modeling with best parameter fit and optimal control - An efficient data analysis for cancer research

Building data-driven models is an effective strategy for information extraction from empirical data. Adapting model parameters specifically to data with a best fitting approach encodes the relevant information into a mathematical model. Subsequently, an optimal control framework extracts the most efficient targets to steer the model into desired changes via external stimuli. The DataXflow software framework integrates three software pipelines, D2D for model fitting, a framework solving optimal control problems including external stimuli and JimenaE providing graphical user interfaces to employ the other frameworks lowering the barriers for the need of programming skills, and simultaneously automating reoccurring modeling tasks. Such tasks include equation generation from a graph and script generation allowing also to approach systems with many agents, like complex gene regulatory networks. A desired state of the model is defined, and therapeutic interventions are modeled as external stimuli. The optimal control framework purposefully exploits the model-encoded information by providing those external stimuli that effect the desired changes most efficiently. The implementation of DataXflow is available under https://github.com/MarvelousHopefull/DataXflow. We showcase its application by detecting specific drug targets for a therapy of lung cancer from measurement data to lower proliferation and increase apoptosis. By an iterative modeling process refining the topology of the model, the regulatory network of the tumor is generated from the data. An application of the optimal control framework in our example reveals the inhibition of AURKA and the activation of CDH1 as the most efficient drug target combination. DataXflow paves the way to an agile interplay between data generation and its analysis potentially accelerating cancer research by an efficient drug target identification, even in complex networks.

Advances in targeted therapy of cholangiocarcinoma

Cholangiocarcinoma (CCA) is a malignant tumor originating in the bile duct and its branching epithelium. Due to its high heterogeneity, there are no specific clinical indications at the early stage, the diagnosis is often in advanced CCA. With surgical resection, the 5-year postoperative survival rate (long-term survival rate) is very poor. The regimen of gemcitabine combined with platinum has been used as the first-line chemotherapy for advanced patients. In recent years, targeted therapy for a variety of malignant tumors has made great progress, showing good efficacy and safety in advanced CCA. However, the current targeted therapy of CCA still has many challenges, such as adverse reactions, drug resistance, and individual differences. Therefore, the researches need to further explore the targeted therapy mechanism of CCA malignancies in depth, develop more effective and safe drugs, and accurately formulate plans based on patient characteristics to further improve patient prognosis in the future. This article reviews the recent progress of targeted therapy for CCA, aiming to provide a strategy for the research and clinical work of targeted therapy for CCA.

Single-cell multi-omics in the study of digestive system cancers

Digestive system cancers are prevalent diseases with a high mortality rate, posing a significant threat to public health and economic burden. The diagnosis and treatment of digestive system cancer confront conventional cancer problems, such as tumor heterogeneity and drug resistance. Single-cell sequencing (SCS) emerged at times required and has developed from single-cell RNA-seq (scRNA-seq) to the single-cell multi-omics era represented by single-cell spatial transcriptomics (ST). This article comprehensively reviews the advances of single-cell omics technology in the study of digestive system tumors. While analyzing and summarizing the research cases, vital details on the sequencing platform, sample information, sampling method, and key findings are provided. Meanwhile, we summarize the commonly used SCS platforms and their features, as well as the advantages of multi-omics technologies in combination. Finally, the development trends and prospects of the application of single-cell multi-omics technology in digestive system cancer research are prospected.

Integration of single-nucleus and exosome RNA sequencing dissected inter-cellular communication and biomarkers in pancreatic ductal adenocarcinoma

Background

Mounting evidence underscores the importance of cell communication within the tumor microenvironment, which is pivotal in tumor proliferation, invasion, and metastasis. Exosomes play a crucial role in cell-to-cell communication. Although single-cell RNA sequencing (scRNA-seq) provides insights into individual cell transcriptional characteristics, it falls short of comprehensively capturing exosome-mediated intercellular communication.

Method

We analyzed Pancreatic Ductal Adenocarcinoma (PDAC) tissues, separating supernatant and precipitate for exosome purification and single-cell nucleus suspension. We then constructed Single-nucleus RNA sequencing (snRNA-seq) and small RNA-seq libraries from these components. Our bioinformatic analysis integrated these sequences with ligand-receptor analysis and public miRNA data to map the cell communication network.

Results

We established intercellular communication networks using bioinformatic analysis to track exosome miRNA effects and ligand-receptor pairs. Significantly, hsa-miR-1293 emerged as a prognostic biomarker for pancreatic cancer, linked to immune evasion, increased myeloid-derived suppressor cells, and poorer prognosis. Targeting this miRNA may enhance anti-tumor immunity and improve outcomes.

Conclusion

Our study offers a novel approach to constructing intercellular communication networks using snRNA-seq and exosome-small RNA sequencing. By integrating miRNA tracing with ligand-receptor analysis, we illuminate the complex interactions in the pancreatic cancer microenvironment, highlighting the pivotal role of miRNAs and identifying potential biomarkers and therapeutic targets.

Systematic data analysis pipeline for quantitative morphological cell phenotyping

Quantitative morphological phenotyping (QMP) is an image-based method used to capture morphological features at both the cellular and population level. Its interdisciplinary nature, spanning from data collection to result analysis and interpretation, can lead to uncertainties, particularly among those new to this actively growing field. High analytical specificity for a typical QMP is achieved through sophisticated approaches that can leverage subtle cellular morphological changes. Here, we outline a systematic workflow to refine the QMP methodology. For a practical review, we describe the main steps of a typical QMP; in each step, we discuss the available methods, their applications, advantages, and disadvantages, along with the R functions and packages for easy implementation. This review does not cover theoretical backgrounds, but provides several references for interested researchers. It aims to broaden the horizons for future phenome studies and demonstrate how to exploit years of endeavors to achieve more with less.

Camouflaging nanoreactor traverse the blood-brain barrier to catalyze redox cascade for synergistic therapy of glioblastoma

The blood-brain barrier (BBB) is a complex and highly restrictive barrier that prevents most biomolecules and drugs from entering the brain. However, effective strategies for delivering drugs to the brain are urgently needed for the treatment of glioblastoma. Based on the efficient BBB penetration properties of exosomes derived from brain metastatic breast cancer cells (EB), this work prepared a nanoreactor (denoted as MAG@EB), which was constructed by self-assembly of Mn2+, arsenate and glucose oxidase (GOx) into nanoparticles wrapped with EB. MAG@EB can enhance the efficiency of traversing the BBB, target and accumulate at in situ glioblastoma sites. The GOx-driven glycolysis effectively cuts off the glucose supply while also providing an abundance of H2O2 and lowering pH. Meanwhile, the released Mn2+ mediated Fenton-like reaction converts elevated H2O2 into highly toxic ·OH. Besides, AsV was reduced to AsIII by glutathione, and the tumor suppressor gene P53 was activated by AsIII to kill glioblastoma cells. Glioblastoma succumbed to the redox cascade triggered by MAG@EB, as the results demonstrated in vivo and in vitro, yielding a remarkable therapeutic effect. This work provides a promising therapeutic option mediated by cascaded nanoreactors for the future treatment of glioblastoma.

Exploring the molecular mechanisms of asthma across multiple datasets

BACKGROUND

Asthma, a prevalent chronic respiratory disorder, remains enigmatic, notwithstanding considerable advancements in our comprehension. Continuous efforts are crucial for discovering novel molecular targets and gaining a comprehensive understanding of its pathogenesis.

MATERIALS AND METHODS

In this study, we analyzed gene expression data from 212 individuals, including asthma patients and healthy controls, to identify 267 differentially expressed genes, among which C1orf64 and C7orf26 emerged as potential key genes in asthma pathogenesis. Various bioinformatics tools, including differential gene expression analysis, pathway enrichment, drug target prediction, and single-cell analysis, were employed to explore the potential roles of the genes.

RESULTS

Quantitative PCR demonstrated differential expression of C1orf64 and C7orf26 in the asthmatic airway epithelial tissue, implying their potential involvement in asthma pathogenesis. GSEA enrichment analysis revealed significant enrichment of these genes in signaling pathways associated with asthma progression, such as ABC transporters, cell cycle, CAMs, DNA replication, and the Notch signaling pathway. Drug target prediction, based on upregulated and downregulated differential expression, highlighted potential asthma treatments, including Tyrphostin-AG-126, Cephalin, Verrucarin-a, and Emetine. The selection of these drugs was based on their significance in the analysis and their established anti-inflammatory and antiviral invasion properties. Utilizing Seurat and Celldex packages for single-cell sequencing analysis unveiled disease-specific gene expression patterns and cell types. Expression of C1orf64 and C7orf26 in T cells, NK cells, and B cells, instrumental in promoting hallmark features of asthma, was observed, suggesting their potential influence on asthma development and progression.

CONCLUSION

This study uncovers novel genetic aspects of asthma, highlighting potential therapeutic pathways. It exemplifies the power of integrative bioinformatics in decoding complex disease patterns. However, these findings require further validation, and the precise roles of C1orf64 and C7orf26 in asthma warrant additional investigation to validate their therapeutic potential.

The perinucleolar compartment: structure, function, and utility in anti-cancer drug development

The perinucleolar compartment (PNC) was initially identified as a nuclear structure enriched for the polypyrimidine tract-binding protein. Since then, the PNC has been implicated in carcinogenesis. The prevalence of this compartment is positively correlated with disease progression in various types of cancer, and its expression in primary tumors is linked to worse patient outcomes. Using the PNC as a surrogate marker for anti-cancer drug efficacy has led to the development of a clinical candidate for anti-metastasis therapies. The PNC is a multicomponent nuclear body situated at the periphery of the nucleolus. Thus far, several non-coding RNAs and RNA-binding proteins have been identified as the PNC components. Here, we summarize the current understanding of the structure and function of the PNC, as well as its recurrent links to cancer progression and metastasis.

Enhancing Mass spectrometry-based tumor immunopeptide identification: machine learning filter leveraging HLA binding affinity, aliphatic index and retention time deviation

Accurately identifying neoantigens is crucial for developing effective cancer vaccines and improving tumor immunotherapy. Mass spectrometry-based immunopeptidomics has emerged as a promising approach to identifying human leukocyte antigen (HLA) peptides presented on the surface of cancer cells, but false-positive identifications remain a significant challenge. In this study, liquid chromatography-tandem mass spectrometry-based proteomics and next-generation sequencing were utilized to identify HLA-presenting neoantigenic peptides resulting from non-synonymous single nucleotide variations in tumor tissues from 18 patients with renal cell carcinoma or pancreatic cancer. Machine learning was utilized to evaluate Mascot identifications through the prediction of MS/MS spectral consistency, and four descriptors for each candidate sequence: the max Mascot ion score, predicted HLA binding affinity, aliphatic index and retention time deviation, were selected as important features in filtering out identifications with inadequate fragmentation consistency. This suggests that incorporating rescoring filters based on peptide physicochemical characteristics could enhance the identification rate of MS-based immunopeptidomics compared to the traditional Mascot approach predominantly used for proteomics, indicating the potential for optimizing neoantigen identification pipelines as well as clinical applications.

Glycan-Lectin interactions between platelets and tumor cells drive hematogenous metastasis

Glycosylation is a ubiquitous cellular or microenvironment-specific post-translational modification that occurs on the surface of normal cells and tumor cells. Tumor cell-associated glycosylation is involved in hematogenous metastasis. A wide variety of tumors undergo aberrant glycosylation to interact with platelets. As platelets have many opportunities to engage circulating tumor cells, they represent an important avenue into understanding the role glycosylation plays in tumor metastasis. Platelet involvement in tumor metastasis is evidenced by observations that platelets protect tumor cells from damaging shear forces and immune system attack, aid metastasis through the endothelium at specific sites, and facilitate tumor survival and colonization. During platelet-tumor-cell interactions, many opportunities for glycan-ligand binding emerge. This review integrates the latest information about glycans, their ligands, and how they mediate platelet-tumor interactions. We also discuss adaptive changes that tumors undergo upon glycan-lectin binding and the impact glycans have on targeted therapeutic strategies for treating tumors in clinical settings.

Novel insights into voltage-gated ion channels: Translational breakthroughs in medical oncology

Preclinical evidence suggests that voltage gradients can act as a kind of top-down master regulator during embryogenesis and orchestrate downstream molecular-genetic pathways during organ regeneration or repair. Moreover, electrical stimulation shifts response to injury toward regeneration instead of healing or scarring. Cancer and embryogenesis not only share common phenotypical features but also commonly upregulated molecular pathways. Voltage-gated ion channel activity is directly or indirectly linked to the pathogenesis of cancer hallmarks, while experimental and clinical studies suggest that their modulation, e.g., by anesthetic agents, may exert antitumor effects. A large recent clinical trial served as a proof-of-principle for the benefit of preoperative use of topical sodium channel blockade as a potential anticancer strategy against early human breast cancers. Regardless of whether ion channel aberrations are primary or secondary cancer drivers, understanding the functional consequences of these events may guide us toward the development of novel therapeutic approaches.

A shared mechanism for TNP-ATP recognition by members of the P2X receptor family

P2X receptors (P2X1-7) are non-selective cation channels involved in many physiological activities such as synaptic transmission, immunological modulation, and cardiovascular function. These receptors share a conserved mechanism to sense extracellular ATP. TNP-ATP is an ATP derivative acting as a nonselective competitive P2X antagonist. Understanding how it occupies the orthosteric site in the absence of agonism may help reveal the key allostery during P2X gating. However, TNP-ATP/P2X complexes (TNP-ATP/human P2X3 (hP2X3) and TNP-ATP/chicken P2X7 (ckP2X7)) with distinct conformations and different mechanisms of action have been proposed. Whether these represent species and subtype variations or experimental differences remains unclear. Here, we show that a common mechanism of TNP-ATP recognition exists for the P2X family members by combining enhanced conformation sampling, engineered disulfide bond analysis, and covalent occupancy. In this model, the polar triphosphate moiety of TNP-ATP interacts with the orthosteric site, while its TNP-moiety is deeply embedded in the head and dorsal fin (DF) interface, creating a restrictive allostery in these two domains that results in a partly enlarged yet ion-impermeable pore. Similar results were obtained from multiple P2X subtypes of different species, including ckP2X7, hP2X3, rat P2X2 (rP2X2), and human P2X1 (hP2X1). Thus, TNP-ATP uses a common mechanism for P2X recognition and modulation by restricting the movements of the head and DF domains which are essential for P2X activation. This knowledge is applicable to the development of new P2X inhibitors.

Advances in therapeutic cancer vaccines: Harnessing immune adjuvants for enhanced efficacy and future perspectives

Preventive cancer vaccines are highly effective in preventing viral infection-induced cancer, but advances in therapeutic cancer vaccines with a focus on eliminating cancer cells through immunotherapy are limited. To develop therapeutic cancer vaccines, the integration of optimal adjuvants is a potential strategy to enhance or complement existing therapeutic approaches. However, conventional adjuvants do not satisfy the criteria of clinical trials for therapeutic cancer vaccines. To improve the effects of adjuvants in therapeutic cancer vaccines, effective vaccination strategies must be formulated and novel adjuvants must be identified. This review offers an overview of the current advancements in therapeutic cancer vaccines and highlights in situ vaccination approaches that can be synergistically combined with other immunotherapies by harnessing the adjuvant effects. Additionally, the refinement of adjuvant systems using cutting-edge technologies and the elucidation of molecular mechanisms underlying immunogenic cell death to facilitate the development of innovative adjuvants have been discussed.

Insulin-related traits and prostate cancer: A Mendelian randomization study

Investigating the causal relationship between insulin secretion and prostate cancer (PCa) development is challenging due to the multifactorial nature of PCa, which complicates the isolation of the specific impact of insulin-related factors. We conducted a Mendelian randomization (MR) study to investigate the associations between insulin secretion-related traits and PCa. We used 36, 60, 56, 23, 48, and 49 single nucleotide polymorphisms (SNPs) as instrumental variables for fasting insulin, insulin sensitivity, proinsulin, and proinsulin in nondiabetic individuals, individuals with diabetes, and individuals receiving exogenous insulin, respectively. These SNPs were selected from various genome-wide association studies. To clarify the causal relationship between insulin-related traits and PCa, we utilized a multivariable MR analysis to adjust for obesity and body fat percentage. Additionally, two-step Mendelian randomization was conducted to assess the role of insulin-like growth factor 1 (IGF-1) in the relationship between proinsulin and PCa. Two-sample MR analysis revealed strong associations between genetically predicted fasting insulin, insulin sensitivity, proinsulin, and proinsulin in nondiabetic individuals and the development of PCa. After adjustment for obesity and body fat percentage using multivariable MR analysis, proinsulin remained significantly associated with PCa, whereas other factors were not. Furthermore, two-step MR analysis demonstrated that proinsulin acts as a negative factor in prostate carcinogenesis, largely independent of IGF-1. This study provides evidence suggesting that proinsulin may act as a negative factor contributing to the development of PCa. Novel therapies targeting proinsulin may have potential benefits for PCa patients, potentially reducing the need for unnecessary surgical treatments.

eIF4E orchestrates mRNA processing, RNA export and translation to modify specific protein production

The eukaryotic translation initiation factor eIF4E acts as a multifunctional factor that simultaneously influences mRNA processing, export, and translation in many organisms. Its multifactorial effects are derived from its capacity to bind to the methyl-7-guanosine cap on the 5'end of mRNAs and thus can act as a cap chaperone for transcripts in the nucleus and cytoplasm. In this review, we describe the multifactorial roles of eIF4E in major mRNA-processing events including capping, splicing, cleavage and polyadenylation, nuclear export and translation. We discuss the evidence that eIF4E acts at two levels to generate widescale changes to processing, export and ultimately the protein produced. First, eIF4E alters the production of components of the mRNA processing machinery, supporting a widescale reprogramming of multiple mRNA processing events. In this way, eIF4E can modulate mRNA processing without physically interacting with target transcripts. Second, eIF4E also physically interacts with both capped mRNAs and components of the RNA processing or translation machineries. Further, specific mRNAs are sensitive to eIF4E only in particular mRNA processing events. This selectivity is governed by the presence of cis-acting elements within mRNAs known as USER codes that recruit relevant co-factors engaging the appropriate machinery. In all, we describe the molecular bases for eIF4E's multifactorial function and relevant regulatory pathways, discuss the basis for selectivity, present a compendium of ~80 eIF4E-interacting factors which play roles in these activities and provide an overview of the relevance of its functions to its oncogenic potential. Finally, we summarize early-stage clinical studies targeting eIF4E in cancer.

DNA methylation markers for risk of metastasis in a cohort of men with localized prostate cancer

Accurately identifying life-threatening prostate cancer (PCa) at time of diagnosis remains an unsolved problem. We evaluated whether DNA methylation status of selected candidate genes can predict the risk of metastasis beyond clinical risk factors in men with untreated PCa. A nested case-control study was conducted among men diagnosed with localized PCa at Kaiser Permanente California between 01/01/1997-12/31/2006 who did not receive curative treatments. Cases were those who developed metastasis within 10 years from diagnosis. Controls were selected using density sampling. Ninety-eight candidate genes were selected from functional categories of cell cycle control, metastasis/tumour suppressors, cell signalling, cell adhesion/motility/invasion, angiogenesis, and immune function, and 41 from pluripotency genes. Cancer DNA from diagnostic biopsy blocks were extracted and analysed. Associations of methylation status were assessed using CpG site level and principal components-based analysis in conditional logistic regressions. In 215 cases and 404 controls, 27 candidate genes were found to be statistically significant in at least one of the two analytical approaches. The agreement between the methods was 25.9% (7 candidate genes, including 2 pluripotency markers). The DNA methylation status of several candidate genes was significantly associated with risk of metastasis in untreated localized PCa patients. These findings may inform future risk prediction models for PCa metastasis beyond clinical characteristics.

The bioinfomatics analysis of the M1 macrophage-related gene CXCL9 signature in cervical cancer

BACKGROUND

The expression and function of coexpression genes of M1 macrophage in cervical cancer have not been identified. And the CXCL9-expressing tumour-associated macrophage has been poorly reported in cervical cancer.

METHODS

To clarify the regulatory gene network of M1 macrophage in cervical cancer, we downloaded gene expression profiles of cervical cancer patients in TCGA database to identify M1 macrophage coexpression genes. Then we constructed the protein-protein interaction networks by STRING database and performed functional enrichment analysis to investigate the biological effects of the coexpression genes. Next, we used multiple bioinformatics databases and experiments to overall investigate coexpression gene CXCL9, including western blot assay and immunohistochemistry assay, GeneMANIA, Kaplan-Meier Plotter, Xenashiny, TISCH2, ACLBI, HPA, TISIDB, GSCA and cBioPortal databases.

RESULTS

There were 77 positive coexpression genes and 5 negative coexpression genes in M1 macrophage. The coexpression genes in M1 macrophage participated in the production and function of chemokines and chemokine receptors. Especially, CXCL9 was positively correlated with M1 macrophage infiltration levels in cervical cancer. CXCL9 expression would significantly decrease and high CXCL9 levels were linked to good prognosis in the cervical cancer tumour patients, it manifestly expressed in blood immune cells, and was positively related to immune checkpoints. CXCL9 amplification was the most common type of mutation. The CXCL9 gene interaction network could regulate immune-related signalling pathways, and CXCL9 amplification was the most common mutation type in cervical cancer. Meanwhile, CXCL9 may had clinical significance for the drug response in cervical cancer, possibly mediating resistance to chemotherapy and targeted drug therapy.

CONCLUSION

Our findings may provide new insight into the M1 macrophage coexpression gene network and molecular mechanisms in cervical cancer, and indicated that M1 macrophage association gene CXCL9 may serve as a good prognostic gene and a potential therapeutic target for cervical cancer therapies.

Interaction of noncoding RNAs with hippo signaling pathway in cancer cells and cancer stem cells

The Hippo signaling pathway has a regulatory function in the organogenesis process and cellular homeostasis, switching the cascade reactions of crucial kinases acts to turn off/on the Hippo pathway, altering the downstream gene expression and thereby regulating proliferation, apoptosis, or stemness. Disruption of this pathway can lead to the occurrence of various disorders and different types of cancer. Recent findings highlight the importance of ncRNAs, such as microRNA, circular RNA, and lncRNAs, in modulating the Hippo pathway. Defects in ncRNAs can disrupt Hippo pathway balance, increasing tumor cells, tumorigenesis, and chemotherapeutic resistance. This review summarizes ncRNAs' inhibitory or stimulatory role in - Hippo pathway regulation in cancer and stem cells. Identifying the relation between ncRNAs and the components of this pathway could pave the way for developing new biomarkers in the treatment and diagnosis of cancers.

Next generation sequencing reveals the mutation landscape of Chinese MDS patients and the association between mutations and AML transformations

BACKGROUND/OBJECTIVE

Approximately 30% of patients with MDS eventually develop to acute myeloid leukemia (AML). Our study aimed to investigate the mutation landscape of Chinese MDS patients and identify the mutated genes which are closely implicated in the transformation of MDS to AML.

METHODS

In total, 412 sequencing data collected from 313 patients were used for analysis. Mutation frequencies between different groups were compared by Fisher's exact. A predictive model for risk of transformation/death of newly diagnosed patients was constructed by logistic regression.

RESULTS

The most frequently mutated genes in newly diagnosed patients were TP53, TET2, RUNX1, PIGA, and BCOR and mutations of RUNX1, TP53, BCORL1, TET2, and BCOR genes were more common in the treated MDS patients. Besides, we found that the mutation frequencies of IDH2, TET2, and EZH2 were significantly higher in MDS patients aged over 60 years. Moreover, two mutation sites, KRASG12A and TP53H140N were detected only at transformation in one patient, while not detected at diagnosis. In addition, the mutation frequencies of EZH2 V704F and TET2 I1873N were stable from diagnosis to transformation in two patients. Finally, we constructed a predictive model for risk of transformation/death of newly diagnosed patients combing detected data of 10 genes and the number of to leukocyte, with a sensitivity of 63.3% and a specificity of 84.6% in distinguishing individuals with and without risk of transformation/death.

CONCLUSION

In summary, our study found several mutations associated with the transformation from MDS to AML, and constructed a predictive model for risk of transformation/death of MDS patients.

Plasma methylated GNB4 and Riplet as a novel dual-marker panel for the detection of hepatocellular carcinoma

Early detection of hepatocellular carcinoma (HCC) can greatly improve the survival rate of patients. We aimed to develop a novel marker panel based on cell-free DNA (cfDNA) methylation for the detection of HCC. The differentially methylated CpG sites (DMCs) specific for HCC blood diagnosis were selected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, then validated by the whole genome bisulphite sequencing (WGBS) of 12 paired HCC and paracancerous tissues. The clinical performance of the panel was evaluated using tissue samples [32 HCC, chronic liver disease (CLD), and healthy individuals] and plasma cohorts (173 HCC, 199 CLD, and 98 healthy individuals). The combination of G protein subunit beta 4 (GNB4) and Riplet had the optimal area under the curve (AUC) in seven candidates through TCGA, GEO, and WGBS analyses. In tissue validation, the GNB4 and Riplet showed an AUC of 100% with a sensitivity and specificity of 100% for detecting any-stage HCC. In plasma, it demonstrated a high sensitivity of 84.39% at 91.92% specificity, with an AUC of 92.51% for detecting any-stage HCC. The dual-marker panel had a higher sensitivity of 78.26% for stage I HCC than alpha-fetoprotein (AFP) of 47.83%, and a high sensitivity of 70.27% for detecting a single tumour (size ≤3 cm). In conclusion, we developed a novel dual-marker panel that demonstrates high accuracy in detecting HCC, surpassing the performance of AFP testing.

Splicing inhibition mediated by reduced splicing factors and helicases is associated with the cellular response of lung cancer cells to cisplatin

Lung cancer's mortality is predominantly linked to post-chemotherapy recurrence, driven by the reactivation of dormant cancer cells. Despite the critical role of these reactivated cells in cancer recurrence and metastasis, the molecular mechanisms governing their therapeutic selection remain poorly understood. In this study, we conducted an integrative analysis by combining PacBio single molecule real-time (SMRT) sequencing with short reads Illumina RNA-seq. Our study revealed that cisplatin-induced dormant and reactivated cancer cells exhibited a noteworthy reduction in gene transcripts and alternative splicing events. Particularly, the differential alternative splicing events were found to be overlapping with the differentially expression genes and enriched in genes related to cell cycle and cell division. Utilizing ENCORI database and correlation analysis, we identified key splicing factors, including SRSF7, SRSF3, PRPF8, and HNRNPC, as well as RNA helicase such as EIF4A3, DDX39A, DDX11, and BRIP1, which were associated with the observed reduction in alternative splicing and subsequent decrease in gene expression. Our study demonstrated that lung cancer cells reduce gene transcripts through diminished alternative splicing events mediated by specific splicing factors and RNA helicase in response to the chemotherapeutic stress. These findings provide insights into the molecular mechanisms underlying the therapeutic selection and reactivation of dormant cancer cells. This discovery opens a potential avenue for the development of therapeutic strategies aimed at preventing cancer recurrence following chemotherapy.

Discovery of novel and potent dual-targeting AXL/HDAC2 inhibitors for colorectal cancer treatment via structure-based pharmacophore modelling, virtual screening, and molecular docking, molecular dynamics simulation studies, and biological evaluation

Colorectal cancer (CRC) is one of the most common cancers worldwide. Nowadays, owing to the complex mechanism of tumorigenesis, simultaneous inhibition of multiple targets is an important anticancer strategy. Recent studies have demonstrated receptor tyrosine kinase AXL (AXL) and histone deacetylase 2 (HDAC2) are closely associated with colorectal cancer. Herein, we identified five hit compounds concurrently targeting AXL and HDAC2 using virtual screening. Inhibitory experiments revealed these hit compounds potently inhibited AXL and HDAC2 in the nanomolar range. Among them, Hit-3 showed the strongest inhibitory effects which were better than that of the positive control groups. Additionally, MD assays showed that Hit-3 could bind stably to the AXL and HDAC2 active pockets. Further MTT assays demonstrated that Hit-3 showed potent anti-proliferative activity. Most importantly, Hit-3 exhibited significant in vivo antitumor efficacy in xenograft models. Collectively, this study is the first discovery of dual-targeting AXL/HDAC2 inhibitors for colorectal cancer treatment.

Functional roles of conserved lncRNAs and circRNAs in eukaryotes

Long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) have emerged as critical regulators in essentially all biological processes across eukaryotes. They exert their functions through chromatin remodeling, transcriptional regulation, interacting with RNA-binding proteins (RBPs), serving as microRNA sponges, etc. Although non-coding RNAs are typically more species-specific than coding RNAs, a number of well-characterized lncRNA (such as XIST and NEAT1) and circRNA (such as CDR1as and ciRS-7) are evolutionarily conserved. The studies on conserved lncRNA and circRNAs across multiple species could facilitate a comprehensive understanding of their roles and mechanisms, thereby overcoming the limitations of single-species studies. In this review, we provide an overview of conserved lncRNAs and circRNAs, and summarize their conserved roles and mechanisms.

Knockdown of S100A2 inhibits the aggressiveness of endometrial cancer by activating STING pathway

BACKGROUND

Endometrial cancer is a kind of gynaecological cancer. S100A2 is a newfound biomarker to diagnose endometrial cancer. This study was to investigate the role of S100A2 on regulating migration and invasion of endometrial cancer.

METHODS

The mRNA and protein levels of S100A2 were obtained by quantitative real-time polymerase chain reaction, immunohistochemistry and western blot methods. Cell viability was measured by the Cell Counting Kit-8 assay. Cell migration and invasion were quantified using transwell assays. Western blot assay was conducted to quantify protein expressions of epithelial to mesenchymal transition-related proteins (N-cadherin and E-cadherin). Furthermore, in vivo tumour formation experiments were performed to evaluate the role of S100A2 on tumour xenografts.

RESULTS

S100A2 was significantly up-regulated in endometrial cancer tissues. Knockdown of S100A2 inhibited cell viability, migration and invasion of endometrial cancer cells. Meanwhile, STING pathway was activated by the inhibited S100A2. STING inhibitor C-176 significantly reversed the effects of S100A2 knockdown on aggressive behaviours of endometrial cancer cells. Inhibition of S100A2 dramatically suppresses the tumour growth in vivo.

CONCLUSIONS

S100A2 functions as an oncogene in endometrial cancer. Targeting S100A2 may be a promising therapeutic method to treat endometrial carcinoma.

One-carbon metabolism nutrients impact the interplay between DNA methylation and gene expression in liver, enhancing protein synthesis in Atlantic salmon

Supplementation of one-carbon (1C) metabolism micronutrients, which include B-vitamins and methionine, is essential for the healthy growth and development of Atlantic salmon (Salmo salar). However, the recent shift towards non-fish meal diets in salmon aquaculture has led to the need for reassessments of recommended micronutrient levels. Despite the importance of 1C metabolism in growth performance and various cellular regulations, the molecular mechanisms affected by these dietary alterations are less understood. To investigate the molecular effect of 1C nutrients, we analysed gene expression and DNA methylation using two types of omics data: RNA sequencing (RNA-seq) and reduced-representation bisulphite sequencing (RRBS). We collected liver samples at the end of a feeding trial that lasted 220 days through the smoltification stage, where fish were fed three different levels of four key 1C nutrients: methionine, vitamin B6, B9, and B12. Our results indicate that the dosage of 1C nutrients significantly impacts genetic and epigenetic regulations in the liver of Atlantic salmon, particularly in biological pathways related to protein synthesis. The interplay between DNA methylation and gene expression in these pathways may play an important role in the mechanisms underlying growth performance affected by 1C metabolism.

Novel DNA methylation changes in mouse lungs associated with chronic smoking

Smoking is a potent cause of asthma exacerbations, chronic obstructive pulmonary disease (COPD) and many other health defects, and changes in DNA methylation (DNAm) have been identified as a potential link between smoking and these health outcomes. However, most studies of smoking and DNAm have been done using blood and other easily accessible tissues in humans, while evidence from more directly affected tissues such as the lungs is lacking. Here, we identified DNAm patterns in the lungs that are altered by smoking. We used an established mouse model to measure the effects of chronic smoke exposure first on lung phenotype immediately after smoking and then after a period of smoking cessation. Next, we determined whether our mouse model recapitulates previous DNAm patterns observed in smoking humans, specifically measuring DNAm at a candidate gene responsive to cigarette smoke, Cyp1a1. Finally, we carried out epigenome-wide DNAm analyses using the newly released Illumina mouse methylation microarrays. Our results recapitulate some of the phenotypes and DNAm patterns observed in human studies but reveal 32 differentially methylated genes specific to the lungs which have not been previously associated with smoking. The affected genes are associated with nicotine dependency, tumorigenesis and metastasis, immune cell dysfunction, lung function decline, and COPD. This research emphasizes the need to study CS-mediated DNAm signatures in directly affected tissues like the lungs, to fully understand mechanisms underlying CS-mediated health outcomes.

Identification and validation of protein biomarkers for predicting gastrointestinal stromal tumor recurrence

We conducted a proteomic analysis using mass spectrometry to identify and validate protein biomarkers for accurately predicting recurrence risk in gastrointestinal stromal tumors (GIST) patients, focusing on differentially expressed proteins in metastatic versus primary GIST tissues. We selected five biomarkers-GPX4, RBM4, TPM3, PFKFB2, and PGAM5-and validated their expressions in primary tumors of recurrent and non-recurrent GIST patients via immunohistochemistry. Our analysis of the association between these biomarkers with recurrence-free survival (RFS) and overall survival (OS), along with their interrelationships, revealed that immunohistochemistry confirmed significantly higher expressions of these biomarkers in primary GIST tissues of recurrent patients. Kaplan-Meier survival analysis showed that high expressions of GPX4, RBM4, TPM3, PFKFB2, and PGAM5 correlated with lower RFS, and GPX4 and RBM4 with lower OS. All biomarker pairs showed positive associations, with high expressions correlating with increased recurrence rates, and GPX4 and RBM4 with higher mortality rates. In conclusion, the biomarkers GPX4, RBM4, TPM3, PFKFB2, and PGAM5 are clinically relevant for predicting GIST recurrence, with their high expressions in primary tumors linked to poorer RFS and OS. They serve as potential prognostic indicators, enabling early treatment and improved outcomes. The observed interrelationships among these biomarkers further validate their accuracy in predicting GIST recurrence.

In the weeds: A comprehensive review of cannabis; its chemical complexity, biosynthesis, and healing abilities

For millennia, various cultures have utilized cannabis for food, textile fiber, ethno-medicines, and pharmacotherapy, owing to its medicinal potential and psychotropic effects. An in-depth exploration of its historical, chemical, and therapeutic dimensions provides context for its contemporary understanding. The criminalization of cannabis in many countries was influenced by the presence of psychoactive cannabinoids; however, scientific advances and growing public awareness have renewed interest in cannabis-related products, especially for medical use. Described as a 'treasure trove,' cannabis produces a diverse array of cannabinoids and non-cannabinoid compounds. Recent research focuses on cannabinoids for treating conditions such as anxiety, depression, chronic pain, Alzheimer's, Parkinson's, and epilepsy. Additionally, secondary metabolites like phenolic compounds, terpenes, and terpenoids are increasingly recognized for their therapeutic effects and their synergistic role with cannabinoids. These compounds show potential in treating neuro and non-neuro disorders, and studies suggest their promise as antitumoral agents. This comprehensive review integrates historical, chemical, and therapeutic perspectives on cannabis, highlighting contemporary research and its vast potential in medicine.

Evaluation of the anticancer effects exerted by 5-fluorouracil and heme oxygenase-1 inhibitor hybrids in HTC116 colorectal cancer cells

Colon cancer remains a clinical challenge in industrialised countries. Its treatment with 5-Flurouracil (5-FU) develops many side effects and resistance. Thus, several strategies have been undertaken so far, including the use of drug cocktails and polypharmacology. Heme oxygenase-1 (HO-1) is an emerging molecular target in the treatment of various cancers. We recently demonstrated that a combination of HO-1 inhibitors with 5-FU and the corresponding hybrids SI1/17, SI1/20, and SI1/22, possessed anticancer activity against prostate and lung cancer cells. In this work, we evaluated these hybrids in a model of colon cancer and found that SI1/22 and the respective combo have greater potency than 5-FU. Particularly, compounds inhibit HO-1 activity in cell lysates, increase ROS and the expression of HO-1, SOD, and Nrf2. Moreover, we observed a decrease of pro-caspase and an increase in cleaved PARP-1 and p62, suggesting apoptotic and autophagic cell death and potential application of these drugs as anticancer agents.

The activity of pyrazolo[4,3-e][1,2,4]triazine and pyrazolo[4,3-e]tetrazolo[1,5-b][1,2,4]triazine sulphonamide derivatives in monolayer and spheroid breast cancer cell cultures

In the last decade, an increasing interest in compounds containing pyrazolo[4,3-e][1,2,4]triazine moiety is observed. Therefore, the aim of the research was to synthesise a novel sulphonyl pyrazolo[4,3-e][1,2,4]triazines (2a, 2b) and pyrazolo[4,3-e]tetrazolo[1,5-b][1,2,4]triazine sulphonamide derivatives (3a, 3b) to assess their anticancer activity. The MTT assay showed that 2a, 2b, 3a, 3b have stronger cytotoxic activity than cisplatin in both breast cancer cells (MCF-7 and MDA-MB-231) and exhibited weaker effect on normal breast cells (MCF-10A). The obtained results showed that the most active compound 3b increased apoptosis via caspase 9, caspase 8, and caspase 3/7. It is worth to note that compound 3b suppressed NF-κB expression and promoted p53, Bax, and ROS which play important role in activation of apoptosis. Moreover, our results confirmed that compound 3b triggers autophagy through increased formation of autophagosomes, expression of beclin-1 and mTOR inhibition. Thus, our study defines a possible mechanism underlying 3b-induced anti-cancer activity against breast cancer cell lines.

Identification of new hub- ferroptosis-related genes in Lupus Nephritis

Background: Lupus Nephritis (LN) is the primary causation of kidney injury in systemic lupus erythematosus (SLE). Ferroptosis is a programmed cell death. Therefore, understanding the crosstalk between LN and ferroptosis is still a significant challenge. Methods: We obtained the expression profile of LN kidney biopsy samples from the Gene Expression Omnibus database and utilised the R-project software to identify differentially expressed genes (DEGs). Then, we conducted a functional correlation analysis. Ferroptosis-related genes (FRGs) and differentially expressed genes (DEGs) crossover to select FRGs with LN. Afterwards, we used CIBERSORT to assess the infiltration of immune cells in both LN tissues and healthy control samples. Finally, we performed immunohistochemistry on LN human renal tissue. Results: 10619 DEGs screened from the LN biopsy tissue were identified. 22 hub-ferroptosis-related genes with LN (FRGs-LN) were screened out. The CIBERSORT findings revealed that there were significant statistical differences in immune cells between healthy control samples and LN tissues. Immunohistochemistry further demonstrated a significant difference in HRAS, TFRC, ATM, and SRC expression in renal tissue between normal and control groups. Conclusion: We developed a signature that allowed us to identify 22 new biomarkers associated with FRGs-LN. These findings suggest new insights into the pathology and therapeutic potential of LN ferroptosis inhibitors and iron chelators.

A review on dendrimer-based nanoconjugates and their intracellular trafficking in cancer photodynamic therapy

Nanotechnology-based cancer treatment has received considerable attention, and these treatments generally use drug-loaded nanoparticles (NPs) to target and destroy cancer cells. Nanotechnology combined with photodynamic therapy (PDT) has demonstrated positive outcomes in cancer therapy. Combining nanotechnology and PDT is effective in targeting metastatic cancer cells. Nanotechnology can also increase the effectiveness of PDT by targeting cells at a molecular level. Dendrimer-based nanoconjugates (DBNs) are highly stable and biocompatible, making them suitable for drug delivery applications. Moreover, the hyperbranched structures in DBNs have the capacity to load hydrophobic compounds, such as photosensitizers (PSs) and chemotherapy drugs, and deliver them efficiently to tumour cells. This review primarily focuses on DBNs and their potential applications in cancer treatment. We discuss the chemical design, mechanism of action, and targeting efficiency of DBNs in tumour metastasis, intracellular trafficking in cancer treatment, and DBNs' biocompatibility, biodegradability and clearance properties. Overall, this study will provide the most recent insights into the application of DBNs and PDT in cancer therapy.

Bifunctional black phosphorus quantum dots platform: Delivery and remarkable immunotherapy enhancement of STING agonist

Cancer immunotherapy has been developed to improve therapeutic effects for patients by activating the innate immune stimulator of interferon gene (STING) pathway. However, most patients cannot benefit from this therapy, mainly due to the problems of excessively low immune responses and lack of tumor specificity. Herein, we report a solution to these two problems by developing a bifunctional platform of black phosphorus quantum dots (BPQDs) for STING agonists. Specifically, BPQDs could connect targeted functional groups and regulate surface zeta potential by coordinating metal ions to increase loading (over 5 times) while maintaining high universality (7 STING agonists). The controlled release of STING agonists enabled specific interactions with their proteins, activating the STING pathway and stimulating the secretion release of immunosuppressive factors by phosphorylating TBK1 and IFN-IRF3 and secreting high levels of immunostimulatory cytokines, including IL-6, IFN-α, and IFN-β. Moreover, the immunotherapy was enhanced was enhanced mild photothermal therapy (PTT) of BPQDs platform, producing enough T cells to eliminate tumors and prevent tumor recurrence. This work facilitates further research on targeted delivery of small-molecule immune drugs to enhance the development of clinical immunotherapy.

Tension directs cancer cell migration over fiber alignment through energy minimization

Cell migration during many fundamental biological processes including metastasis requires cells to traverse tissue with heterogeneous mechanical cues that direct migration as well as determine force and energy requirements for motility. However, the influence of discrete structural and mechanical cues on migration remains challenging to determine as they are often coupled. Here, we decouple the pro-invasive cues of collagen fiber alignment and tension to study their individual impact on migration. When presented with both cues, cells preferentially travel in the axis of tension against fiber alignment. Computational and experimental data show applying tension perpendicular to alignment increases potential energy stored within collagen fibers, lowering requirements for cell-induced matrix deformation and energy usage during migration compared to motility in the direction of fiber alignment. Energy minimization directs migration trajectory, and tension can facilitate migration against fiber alignment. These findings provide a conceptual understanding of bioenergetics during migration through a fibrous matrix.

Chirality-driven strong thioredoxin reductase inhibition

Overexpression of thioredoxin reductase (TXNRD) plays crucial role in tumorigenesis. Therefore, designing TXNRD inhibitors is a promising strategy for targeted anticancer drug development. However, poor selectivity has always been a challenge, resulting in unavoidable toxicity in clinic. Herein we demonstrate a strategy to develop highly selective chiral metal complexes-based TXNRD inhibitors. By manipulating the conformation of two distinct weakly interacting groups, we optimize the compatibility between the drug and the electrophilic group within the active site of TXNRD to enhance their non-covalent interaction, thus effectively avoids the poor selectivity deriving from covalent drug interaction, on the basis of ensuring the strong inhibition. Detailed experimental and computational results demonstrate that the chiral isomeric drugs bind to the active site of TXNRD, and the interaction strength is well modulated by chirality. Especially, the meso-configuration, in which the two large sterically hindered active groups are positioned on opposite sides of the drug, exhibits the highest number of non-covalent interactions and most effective inhibition on TXNRD. Taken together, this work not only provides a novel approach for developing highly selective proteinase inhibitors, but also sheds light on possible underlying mechanisms for future application.

In situ hydrogel based on Cu-Fe3O4 nanoclusters exploits oxidative stress and the ferroptosis/cuproptosis pathway for chemodynamic therapy

Chemodynamic therapy (CDT) involving the use of metal nanozymes presents new opportunities for the treatment of deep-seated tumors. However, the lower ROS catalytic rate and dependence on high H2O2 concentrations affect therapeutic efficacy. To address this issue, a hydrogel was constructed for the treatment of osteosarcoma by combining Cu-Fe3O4 nanozymes (NCs) and artemisinin (AS) coencapsulated in situ with sodium alginate (ALG) and calcium ions. This hydrogel can release nanoparticles and AS within tumor tissue for an extended period of time, utilizing the multienzyme activity of NCs to achieve ROS accumulation. The carbon radicals (•C) generated from the interaction of Fe2+/Cu2+ with AS amplify oxidative stress, leading to tumor cell damage. Simultaneously, the NCs activate ferroptosis via the GPX4 pathway by depleting GSH and activate cuproptosis via the DLAT pathway by causing intracellular copper overload, enhancing therapeutic efficacy. In vitro experiments confirmed that the NCs-AS-ALG hydrogel has an excellent tumor cell killing effect, while in vivo experimental results demonstrated that it can effectively eliminate tumors with excellent biocompatibility, providing a new approach for osteosarcoma treatment.

Prognostic iron-metabolism signature robustly stratifies single-cell characteristics of hepatocellular carcinoma

Cancer immunotherapy has shown to be a promising method in treating hepatocellular carcinoma (HCC), but suboptimal responses in patients are attributed to cellular and molecular heterogeneity. Iron metabolism-related genes (IRGs) are important in maintaining immune system homeostasis and have the potential to help develop new strategies for HCC treatment. Herein, we constructed and validated the iron-metabolism gene prognostic index (IPX) using univariate Cox proportional hazards regression and LASSO Cox regression analysis, successfully categorizing HCC patients into two groups with distinct survival risks. Then, we performed single-sample gene set enrichment analysis, weighted correlation network analysis, gene ontology enrichment analysis, cellular lineage analysis, and SCENIC analysis to reveal the key determinants underlying the ability of this model based on bulk and single-cell transcriptomic data. We identified several driver transcription factors specifically activated in specific malignant cell sub-populations to contribute to the adverse survival outcomes in the IPX-high subgroup. Within the tumor microenvironment (TME), T cells displayed significant diversity in their cellular characteristics and experienced changes in their developmental paths within distinct clusters identified by IPX. Interestingly, the proportion of Treg cells was increased in the high-risk group compared with the low-risk group. These results suggest that iron-metabolism could be involved in reshaping the TME, thereby disrupting the cell cycle of immune cells. This study utilized IRGs to construct a novel and reliable model, which can be used to assess the prognosis of patients with HCC and further clarify the molecular mechanisms of IRGs in HCC at single-cell resolution.

BioPrediction-RPI: Democratizing the prediction of interaction between non-coding RNA and protein with end-to-end machine learning

Machine Learning (ML) algorithms have been important tools for the extraction of useful knowledge from biological sequences, particularly in healthcare, agriculture, and the environment. However, the categorical and unstructured nature of these sequences requiring usually additional feature engineering steps, before an ML algorithm can be efficiently applied. The addition of these steps to the ML algorithm creates a processing pipeline, known as end-to-end ML. Despite the excellent results obtained by applying end-to-end ML to biotechnology problems, the performance obtained depends on the expertise of the user in the components of the pipeline. In this work, we propose an end-to-end ML-based framework called BioPrediction-RPI, which can identify implicit interactions between sequences, such as pairs of non-coding RNA and proteins, without the need for specialized expertise in end-to-end ML. This framework applies feature engineering to represent each sequence by structural and topological features. These features are divided into feature groups and used to train partial models, whose partial decisions are combined into a final decision, which, provides insights to the user by giving an interpretability report. In our experiments, the developed framework was competitive when compared with various expert-created models. We assessed BioPrediction-RPI with 12 datasets when it presented equal or better performance than all tools in 40% to 100% of cases, depending on the experiment. Finally, BioPrediction-RPI can fine-tune models based on new data and perform at the same level as ML experts, democratizing end-to-end ML and increasing its access to those working in biological sciences.

Knockdown of PIK3R6 impedes the onset and advancement of clear cell renal cell carcinoma

In this research, we investigated the role of PIK3R6, a regulatory subunit of PI3Kγ, known for its tumor-promoting properties, in clear cell renal cell carcinoma (CCRCC). Utilizing the UALCAN website, we found PIK3R6 upregulated in CCRCC, correlating with lower survival rates. We compared PIK3R6 expression in CCRCC tumor tissues and adjacent normal tissues using immunohistochemistry. Post RNA interference-induced knockdown of PIK3R6 in 786-O and ACHN cell lines, we performed CCK-8, colony formation, Edu staining, flow cytometry, wound healing, and transwell assays. Results showed that PIK3R6 silencing reduced cell proliferation, migration, and invasion, and induced G0/G1 phase arrest and apoptosis. Molecular analysis revealed decreased CDK4, Cyclin D1, N-cadherin, Vimentin, Bcl-2, p-PI3K and p-AKT, with increased cleaved caspase-3, Bax, and E-cadherin levels in CCRCC cells. Moreover, inhibiting PIK3R6 hindered tumor growth. These findings suggest a significant role for PIK3R6 in CCRCC cell proliferation and metastasis, presenting it as a potential therapeutic target.

Advances in cell membrane-based biomimetic nanodelivery systems for natural products

Active components of natural products, which include paclitaxel, curcumin, gambogic acid, resveratrol, triptolide and celastrol, have promising anti-inflammatory, antitumor, anti-oxidant, and other pharmacological activities. However, their clinical application is limited due to low solubility, instability, low bioavailability, rapid metabolism, short half-life, and strong off-target toxicity. To overcome these drawbacks, cell membrane-based biomimetic nanosystems have emerged that avoid clearance by the immune system, enhance targeting, and prolong drug circulation, while also improving drug solubility and bioavailability, enhancing drug efficacy, and reducing side effects. This review summarizes recent advances in the preparation and coating of cell membrane-coated biomimetic nanosystems and in their applications to disease for targeted natural products delivery. Current challenges, limitations, and prospects in this field are also discussed, providing a research basis for the development of multifunctional biomimetic nanosystems for natural products.

Dickopff 1 inhibits cancer stem cell properties and promotes neuronal differentiation of human neuroblastoma cell line SH-SY5Y

Neuroblastomas are pediatric tumors arising from undifferentiated cells of neural crest origin with stem cell-like characteristics. Dysregulation of Wnt/β-catenin signaling has been shown to be linked to the development of various tumors. Activated Wnt signaling results in β-catenin accumulation in the nucleus to support pro-neoplastic traits. DKK1, a secreted glycoprotein, is an inhibitor of Wnt signaling, and the addition of DKKI to the culture medium has been used to suppress the Wnt pathway. This study aimed to analyze the role of Dickopff-1 as a potential differentiating agent for the neuroblastoma cell line SH-SY5Y and neurospheres derived from it. The treatment of SH-5Y5Y derived neurospheres by DKK1 resulted in their disintegration and reduced proliferation markers like Ki67, PCNA. DKK1 treatment to the neurospheres also resulted in the loss of cancer stem cell markers like CD133, KIT and pluripotency markers like SOX2, OCT4, NANOG. DKK1 treatment caused reduction in mRNA expression of β-catenin and TCF genes like TCF4, TCF12. When the SH-SY5Y cancer cells were grown under differentiating conditions, DKKI caused neuronal differentiation by itself, and in synergy with retinoic acid. This was verified by the expression of markers like MAPT, DCX, GAP43, ENO2 and also with changes in neurite length. We concluded that Wnt inhibition, as exemplified by DKK1 treatment, is therefore a possible differentiating condition and also suppresses the proliferative and cancer stemness related properties of SH-SY5Y neuroblastoma cells.

Case report: TP53 c.848G>A germline mutation as a possible screening target at initial diagnosis for acute lymphoblastic leukemia

BACKGROUD

Li-Fraumeni syndrome is a hereditary tumor syndrome characterized by an elevated risk of malignancy, particularly acute lymphoblastic leukemia (ALL), which can be caused by the heterozygous germline mutation. TP53 gene germline mutation is considered a potential risk factor and crucial prognostic parameter for acute leukemia development and diagnosis, but rarely occurs in adults, and its specific pathogenic significance in acute leukemia is unclear.

CASE PRESENTATION

We describes a case of a 45-year-old woman diagnosed with ALL. Whole-exome sequencing approach identified one of the TP53 germline mutations from her bone marrow sample with possible pathogenic significance, c.848G>A (p.Arg283His) heterozygous missense mutation located on exon 8, which was further verified in her hair, oral mucous and nail samples. Family pedigree screening revealed that the same TP53 genetic variant was present in the patient's father and non-donor son, whereas not in the donor. Digital PCR observed that this point mutation frequency dropped post-transplantation but remained low during maintenance therapy when the patient was leukemia-free.

CONCLUSION

This suspected Li-Fraumeni syndrome case report with a likely pathogenic heterozygous TP53 variant expands the cancer genetic spectrum. Screening her family members for mutations facilitates identifying the optimal relative donor and avoids unnecessary treatment by monitoring TP53 germline mutations for minimal residual disease following hematopoietic stem cell transplantation. Its potential roles in hematological malignant tumor development and clinical pathogenic implications necessitate further probing.

Design, synthesis, and biological evaluation of (thio)urea derivatives as potent Escherichia coli β-glucuronidase inhibitors

EcGUS has drawn considerable attention for its role as a target in alleviating serious GIAEs. In this study, a series of 72 (thio)urea derivatives were designed, synthesised, and biologically assayed. The bioassay results revealed that E-9 (IC50 = 2.68 μM) exhibited a promising inhibitory effect on EcGUS, surpassing EcGUS inhibitor D-saccharic acid-1,4-lactone (DSL, IC50 = 45.8 μM). Additionally, the inhibitory kinetic study indicated that E-9 (Ki = 1.64 μM) acted as an uncompetitive inhibitor against EcGUS. The structure-activity relationship revealed that introducing an electron-withdrawing group into the benzene ring at the para-position is beneficial for enhancing inhibitory activity against EcGUS. Furthermore, molecular docking analysis indicated that E-9 has a strong affinity to EcGUS by forming interactions with residues Asp 163, Tyr 472, and Glu 504. Overall, these results suggested that E-9 could be a potent EcGUS inhibitor, providing valuable insights and guidelines for the development of future inhibitors targeting EcGUS.

Effectiveness of digital tools for smoking cessation in Asian countries: a systematic review

AIM

The use of tobacco is responsible for many preventable diseases and deaths worldwide. Digital interventions have greatly improved patient health and clinical care and have proven to be effective for quitting smoking in the general population due to their flexibility and potential for personalization. However, there is limited evidence on the effectiveness of digital interventions for smoking cessation in Asian countries.

METHODS

Three major databases - Web of Science (WOS), Scopus, and PubMed - for relevant studies published between 1 January 2010 and 12 February 2023 were searched for studies evaluating the effectiveness of digital intervention for smoking cessation in Asian countries.

RESULTS

A total of 25 studies of varying designs were eligible for this study collectively involving a total of n = 22,005 participants from 9 countries. Among different digital tools for smoking cessation, the highest abstinence rate (70%) was reported with cognitive behavioural theory (CBT)-based smoking cessation intervention via Facebook followed by smartphone app (60%), WhatsApp (59.9%), and Pharmacist counselling with Quit US smartphone app (58.4%). However, WhatsApp was preferred over Facebook intervention due to lower rates of relapse. WeChat was responsible for 15.6% and 41.8% 7-day point prevalence abstinence. For telephone/text messaging abstinence rate ranged from 8-44.3% and quit rates from 6.3% to 16.8%. Whereas, no significant impact of media/multimedia messages and web-based learning on smoking cessation was observed in this study.

CONCLUSION

Based on the study findings the use of digital tools can be considered an alternative and cost-effective smoking cessation intervention as compared to traditional smoking cessation interventions.

Design, synthesis, and bioevaluation of 1h-pyrrolo[3,2-c]pyridine derivatives as colchicine-binding site inhibitors with potent anticancer activities

A new series of 1H-pyrrolo[3,2-c]pyridine derivatives were designed and synthesised as colchicine-binding site inhibitors. Preliminary biological evaluations showed that most of the target compounds displayed moderate to excellent antitumor activities against three cancer cell lines (HeLa, SGC-7901, and MCF-7) in vitro. Among them, 10t exhibited the most potent activities against three cancer cell lines with IC50 values ranging from 0.12 to 0.21 μM. Tubulin polymerisation experiments indicated that 10t potently inhibited tubulin polymerisation at concentrations of 3 μM and 5 μM, and immunostaining assays revealed that 10t remarkably disrupted tubulin microtubule dynamics at a concentration of 0.12 μM. Furthermore, cell cycle studies and cell apoptosis analyses demonstrated that 10t at concentrations of 0.12 μM, 0.24 μM, and 0.36 μM significantly caused G2/M phase cell cycle arrest and apoptosis. The results of molecular modelling studies suggested that 10t interacts with tubulin by forming hydrogen bonds with colchicine sites Thrα179 and Asnβ349. In addition, the prediction of physicochemical properties disclosed that 10t conformed well to the Lipinski's rule of five.

Metagenomic shotgun sequencing reveals the enrichment of Salmonella and Mycobacterium in larynx due to prolonged ethanol exposure

The exposure of ethanol increases the risk of head and neck inflammation and tumor progression. However, limited studies have investigated the composition and functionality of laryngeal microbiota under ethanol exposure. We established an ethanol-exposed mouse model to investigate the changes in composition and function of laryngeal microbiota using Metagenomic shotgun sequencing. In the middle and late stages of the experiment, the laryngeal microbiota of mice exposed to ethanol exhibited obvious distinguished from that of the control group on principal-coordinate analysis (PCoA) plots. Among the highly abundant species, Salmonella enterica and Mycobacterium marinum were likely to be most impacted. Our findings indicated that the exposure to ethanol significantly increased their abundance in larynxes in mice of the same age, which has been confirmed through FISH experiments. Among the species-related functions and genes, metabolism is most severely affected by ethanol. The difference was most obvious in the second month of the experiment, which may be alleviated later because the animal established tolerance. Notable enrichments concerning energy, amino acid, and carbohydrate metabolic pathways occurred during the second month under ethanol exposure. Finally, based on the correlation between species and functional variations, a network was established to investigate relationships among microbiota, functional pathways, and related genes affected by ethanol. Our data first demonstrated the continuous changes of abundance, function and their interrelationship of laryngeal microbiota under ethanol exposure by Metagenomic shotgun sequencing.

Importance

Ethanol may participate in the inflammation and tumor progression by affecting the composition of the laryngeal microbiota. Here, we applied the metagenomic shotgun sequencing instead of 16 S rRNA sequencing method to identify the laryngeal microbiota under ethanol exposure. Salmonella enterica and Mycobacterium marinum are two dominant species that may play a role in the reconstruction of the laryngeal microenvironment, as their local abundance increases following exposure to ethanol. The metabolic function is most evidently impacted, and several potential metabolic pathways could be associated with alterations in microbiota composition. These findings could help us better understand the impact of prolonged ethanol exposure on the microbial composition and functionality in the larynx.

IL-10+CD19+ regulatory B cells induce CD4+Foxp3+regulatory T cells in serum of cervical cancer patients

Increase of regulatory T cells (Tregs) in the tumour microenvironment predicts worse survival of patients with various types of cancer. Recently, B cells play a significant role in the maintenance of Treg cells. However, the relevance of regulatory B cells (Bregs) to tumour immunity in humans remains elusive. Flow cytometry analysis was used to detect the Bregs and Tregs. Double staining results illustrated that the proportion of Bregs and Tregs were prominently higher in cervical cancer than normal tissues. Increase of Bregs and Tregs in cervical cancer microenvironment was associated with poor survival. Furthermore, Bregs cocultured with cervical cancer cell lines increased and induced Tregs. To sum up, the increased expression of Bregs contributes to the differentiation of CD4+ T cells into Tregs in the cervical cancer.