CD44 and its implication in neoplastic diseases.

CD44, a nonkinase single span transmembrane glycoprotein, is a major cell surface receptor for many other extracellular matrix components as well as classic markers of cancer stem cells and immune cells. Through alternative splicing of CD44 gene, CD44 is divided into two isoforms, the standard isoform of CD44 (CD44s) and the variant isoform of CD44 (CD44v). Different isoforms of CD44 participate in regulating various signaling pathways, modulating cancer proliferation, invasion, metastasis, and drug resistance, with its aberrant expression and dysregulation contributing to tumor initiation and progression. However, CD44s and CD44v play overlapping or contradictory roles in tumor initiation and progression, which is not fully understood. Herein, we discuss the present understanding of the functional and structural roles of CD44 in the pathogenic mechanism of multiple cancers. The regulation functions of CD44 in cancers-associated signaling pathways is summarized. Moreover, we provide an overview of the anticancer therapeutic strategies that targeting CD44 and preclinical and clinical trials evaluating the pharmacokinetics, efficacy, and drug-related toxicity about CD44-targeted therapies. This review provides up-to-date information about the roles of CD44 in neoplastic diseases, which may open new perspectives in the field of cancer treatment through targeting CD44.

Predicting maximum occlusal force and tongue pressure using decision tree analysis in patients diagnosed with head and neck tumors.

STATEMENT OF PROBLEM: Preserving and restoring oral functions, especially mastication and swallowing, is important to the quality of life of patients being treated for head and neck tumors. Studies that help predict maximum occlusal force and tongue pressure during prosthetic treatment, necessary for providing comprehensive, appropriate treatment and encouraging patient adherence and confidence are lacking. PURPOSE: The purpose of this clinical study was to develop a decision tree model for predicting maximum occlusal force and tongue pressure in patients diagnosed with head and neck tumors that could help both experienced and less experienced prosthodontists and oral surgeons optimize the treatment plan and support patient compliance and their quality of life. MATERIAL AND METHODS: A total of 80 patients who had been treated for head and neck tumors were enrolled in the study. Their maximum occlusal force was measured using a pressure-sensitive film and tongue pressure using a tongue pressure measurement device. Data, including basic characteristics, were transferred to a comma separated values file, which was then imported into a statistical software package to produce a decision tree. The classification and regression tree method was used to construct a predictive model. RESULTS: The number of occlusal contacts associated with not wearing a prosthesis, flap reconstruction, radiotherapy, chemotherapy, the number of teeth present, age, tumor stage, and tumor type were found to be associated with maximum occlusal force, with a prediction accuracy of 96.3%, area under the receiver operating characteristic curve of 0.99, sensitivity of 97%, and specificity of 94%. The number of occlusal contacts associated with wearing and not wearing a prosthesis, tumor stage, age, radiotherapy, and surgery type were found to be associated with tongue pressure, with a prediction accuracy of 96.3%, area under the receiver operating characteristic curve of 0.97, sensitivity of 97%, and specificity of 93%. CONCLUSIONS: The decision tree model can be an effective tool for the prediction of maximum occlusal force and tongue pressure in patients diagnosed with head and neck tumors, helping both experienced and less experienced prosthodontists and oral surgeons to provide early, appropriate, and necessary treatment before starting prosthetic treatment and helping patients with treatment compliance and communication with medical staff.

Machine Learning Prediction of Tongue Pressure in Elderly Patients with Head and Neck Tumor: A Cross-Sectional Study.

Background: This investigation sought to cross validate the predictors of tongue pressure recovery in elderly patients' post-treatment for head and neck tumors, leveraging advanced machine learning techniques. Methods: By employing logistic regression, support vector regression, random forest, and extreme gradient boosting, the study analyzed an array of variables including patient demographics, surgery types, dental health status, and age, drawn from comprehensive medical records and direct tongue pressure assessments. Results: Among the models, logistic regression emerged as the most effective, demonstrating an accuracy of 0.630 [95% confidence interval (CI): 0.370-0.778], F1 score of 0.688 [95% confidence interval (CI): 0.435-0.853], precision of 0.611 [95% confidence interval (CI): 0.313-0.801], recall of 0.786 [95% confidence interval (CI): 0.413-0.938] and an area under the receiver operating characteristic curve of 0.626 [95% confidence interval (CI): 0.409-0.806]. This model distinctly highlighted the significance of glossectomy (p = 0.039), the presence of functional teeth (p = 0.043), and the patient's age (p = 0.044) as pivotal factors influencing tongue pressure, setting the threshold for statistical significance at p < 0.05. Conclusions: The analysis underscored the critical role of glossectomy, the presence of functional natural teeth, and age as determinants of tongue pressure in logistics regression, with the presence of natural teeth and the tumor site located in the tongue consistently emerging as the key predictors across all computational models employed in this study.

Event Graph Guided Compositional Spatial-Temporal Reasoning for Video Question Answering.

Video question answering (VideoQA) is challenging since it requires the model to extract and combine multi-level visual concepts from local objects to global actions from complex events for compositional reasoning. Existing works represent the video with fixed-duration clip features that make the model struggle in capturing the crucial concepts in multiple granularities. To overcome this shortcoming, we propose to represent the video with an Event Graph in a hierarchical structure whose nodes correspond to visual concepts of different levels (object, relation, scene and action) and edges indicate their spatial-temporal relationships. We further propose a H ierarchical S patial- T emporal T ransformer (HSTT) which takes nodes from the graph as visual input to realize compositional reasoning guided by the event graph. To fully exploit the spatial-temporal context delivered from the graph structure, on the one hand, we encode the nodes in the order of their semantic hierarchy (depth) and occurrence time (breadth) with our improved graph search algorithm; On the other hand, we introduce edge-guided attention to combine the spatial-temporal context among nodes according to their edge connections. HSTT then performs QA by cross-modal interactions guaranteed by the hierarchical correspondence between the multi-level event graph and the cross-level question. Experiments on the recent challenging AGQA and STAR datasets show that the proposed method clearly outperforms the existing VideoQA models by a large margin, including those pre-trained with large-scale external data. Our code is available at https://github.com/ByZ0e/HSTT.

Case report of a patient with mandibulectomy followed up for 11 years.

Mandibular deviation and rotation following mandibulectomy can significantly impact oral function and quality of life. The postoperative course of a 57-year-old patient who underwent mandibulectomy for oral cancer and findings over 11 years of follow-up observation to monitor changes in the mandibular position are described here. Based on the observations, it is important to raise awareness regarding the necessity of continued monitoring of mandible position and regular adjustments of prostheses for patients who have undergone mandibulectomy.

Cisplatin-induced oxPAPC release enhances MDSCs infiltration into LL2 tumour tissues through MCP-1/CCL2 and LTB4/LTB4R pathways.

Lung cancer is the leading global cause of cancer-related death, however, resistance to chemotherapy drugs remains a huge barrier to effective treatment. The elevated recruitment of myeloid derived suppressor cells (MDSCs) to tumour after chemotherapy has been linked to resistance of chemotherapy drugs. Nevertheless, the specific mechanism remains unclear. oxPAPC is a bioactive principal component of minimally modified low-density lipoproteins and regulates inflammatory response. In this work, we found that cisplatin, oxaliplatin and ADM all increased oxPAPC release in tumour. Treating macrophages with oxPAPC in vitro stimulated the secretion of MCP-1 and LTB4, which strongly induced monocytes and neutrophils chemotaxis, respectively. Injection of oxPAPC in vivo significantly upregulated the percentage of MDSCs in tumour microenvironment (TME) of wild-type LL2 tumour-bearing mice, but not CCL2-/- mice and LTB4R-/- mice. Critically, oxPAPC acted as a pro-tumor factor in LL2 tumour model. Indeed, cisplatin increased oxPAPC level in tumour tissues of WT mice, CCL2-/- and LTB4R-/- mice, but caused increased infiltration of Ly6Chigh monocytes and neutrophils only in WT LL2-bearing mice. Collectively, our work demonstrates cisplatin treatment induces an overproduction of oxPAPC and thus recruits MDSCs infiltration to promote the tumour growth through the MCP-1/CCL2 and LTB4/LTB4R pathways, which may restrict the effect of multiple chemotherapy. This provides evidence for a potential strategy to enhance the efficacy of multiple chemotherapeutic drugs in the treatment of lung cancer by targeting oxPAPC.

Unveiling lignin structures and lignin-carbohydrate complex (LCC) linkages of bamboo (Phyllostachys pubescens) fibers and parenchyma cells.

Bamboo (Phyllostachys pubescens) is an attractive biomass block to develop biorefining industry, however, less emphasis has been placed on elucidating the chemical linkage variations of lignin and LCC between different bamboo cell walls. Here, purified milled wood lignin (MWLp) and lignin-carbohydrate complex (LCC) were isolated from bamboo (Phyllostachys pubescens) fibers (BF) and parenchyma cells (PC), respectively. The variations of structure features and chemical linkages of lignin and LCC were investigated via FT-IR, 2D HSQC NMR, and 31P NMR techniques. 2D HSQC NMR revealed that ß-O-4 alkyl-aryl ether linkages and resinol (ß-ß) substructure were the main substructures in BF-MWLp and PC-MWLp. ß-1 linkages existed in the PC-MWLp (3.18/100 Ar), but not in BF-MWLp. Moreover, tricin, as a flavonoid compound, was only detected in the BF-MWLp. The amount of the syringyl (S) units of PC-MWLp was higher than BF-MWLp. The results indicated that phenyl glycoside (PhGlc) bonds (mainly lignin and xylan) were the predominant chemical linkage type of LCC bonds in BF-LCC and PC-LCC, and the high contents of PhGlc bonds (45.53/100 Ar) were presented in PC. Our finding can provide a reference for the structural variations of lignin and LCC between the different bamboo cell walls.

ERK inhibitor: A candidate enhancing therapeutic effects of conventional chemo-radiotherapy in esophageal squamous cell carcinoma.

For patients with esophageal squamous cell carcinoma (ESCC), standard therapeutic methods (cisplatin and radiotherapy) have been found to be ineffective and severely toxic. Targeted therapy emerges as a promising solution for this dilemma. It has been reported that targeted therapies are applied alone or in combination with standard conventional therapies for the treatment of a variety of cancers. To the best of our knowledge, in patients with ESCC, the combinational methods containing standard therapy and ERK-targeted therapy have yet to be explored. To analyze the prognostic role of p-ERK in ESCC patients, the Kaplan-Meier analysis and Cox regression model were used. To assess the effects of ERK-targeted therapy (GDC0994) on ESCC cells, in vitro studies including CCK-8 assay, colony formation assay, and scratch wound healing assay were conducted. In addition, the changes in cell cycle distribution and apoptosis were analyzed by flow cytometry. Besides, to assess the efficacy of different therapies in vivo, the xenograft tumor models were established by subcutaneously inoculating tumor cells into the flank/leg of mice. In patients with ESCC, a strong correlation between the high expression level of p-ERK and the poor prognosis (p < 0.01, Log-Rank test) has been identified. By analyzing the results from CCK-8 and scratch wound healing assays, we demonstrated that the ERK inhibitor repressed the viability and migration of ESCC cells. In addition, following the treatment of GDC0994, the volumes of xenograft tumors significantly decreased (p < 0.001, one-way ANOVA). Furthermore, blocking the mitogen-activated protein kinase (MAPK/ERK) pathway enhanced the therapeutic efficacy of both cisplatin and radiotherapy (p < 0.05). These findings imply the role of p-ERK in the prognosis of ESCC patients and the therapeutic value of ERK inhibitors in ESCC.

Effect of dimethyl alpha-ketoglutarate supplementation on the in vitro developmental competences of ovine oocytes.

The supplementation of dimethyl alpha-ketoglutarate (DMKG) during the in vitro maturation (IVM) process has been shown to improve the in vitro developmental competences of porcine oocytes. Here, the effects of DMKG supplementation in IVM medium on the development competencies of ovine oocytes were investigated by analyzing the nuclear maturation rate to metaphase II (MII) stage, ATP synthesis, cortical granules (CGs) dynamic, F-actin polymerization, mitochondrial activity, mitochondrial damage, reactive oxygen species (ROS) production, intracellular glutathione (GSH) production, DNA damage, cellular apoptosis, fertilization capacity and blastocyst development potential of ovine oocytes. In addition, the oxidative stress damage model induced by H2O2 treatment was applied to confirm the antioxidative effect of DMKG supplementation on the development of ovine oocytes. The results showed that compared with MII oocytes without DMKG supplementation (Control group), 3 mM DMKG supplementation during IVM significantly (P < 0.05) increased nuclear maturation rate, ATP synthesis, CGs dynamic, F-actin polymerization, mitochondrial activity, GSH production and embryonic developmental competence and decreased ROS production, mitochondrial damage, DNA damage and cellular apoptosis level of ovine MII oocytes. Moreover, the reductions in the developmental competences of ovine MII oocytes caused by H2O2 induced oxidative stress damages were effectively ameliorated by the co-supplementation in IVM of 3 mM DMKG (P < 0.05). Our results demonstrate the promising effect of DMKG supplementation on the in vitro developmental competence of ovine oocytes via the reduction of oxidative stress damages and indicates further research into the clinical applications of DMKG and the development of ovine breeding technologies is warranted.

Time-ordered dysregulated ceRNA networks reveal disease progression and diagnostic biomarkers in ischemic and dilated cardiomyopathy.

Ischemic cardiomyopathy (ICM) and dilated cardiomyopathy (DCM) are the two main causes of heart failure (HF). Despite similar clinical characteristics and common "HF pathways", ICM and DCM are expected to have different personalized treatment strategies. The underlying mechanisms of ICM and DCM have yet to be fully elucidated. The present study developed a novel computational method for identifying dysregulated long noncoding RNA (lncRNA)-microRNA (miRNA)-mRNA competing endogenous RNA (ceRNA) triplets. Time-ordered dysregulated ceRNA networks were subsequently constructed to reveal the possible disease progression of ICM and DCM based on the method. Biological functional analysis indicated that ICM and DCM had similar features during myocardial remodeling, whereas their characteristics differed during progression. Specifically, disturbance of myocardial energy metabolism may be the main characteristic during DCM progression, whereas early inflammation and response to oxygen are the characteristics that may be specific to ICM. In addition, several panels of diagnostic biomarkers for differentiating non-heart failure (NF) and ICM (NF-ICM), NF-DCM, and ICM-DCM were identified. Our study reveals biological differences during ICM and DCM progression and provides potential diagnostic biomarkers for ICM and DCM.

Tumor-Infiltrating Lymphocytes in Colorectal Cancer: The Fundamental Indication and Application on Immunotherapy.

The clinical success of immunotherapy has revolutionized the treatment of cancer patients, bringing renewed attention to tumor-infiltrating lymphocytes (TILs) of various cancer types. Immune checkpoint blockade is effective in patients with mismatched repair defects and high microsatellite instability (dMMR-MSI-H) in metastatic colorectal cancer (CRC), leading the FDA to accelerate the approval of two programmed cell death 1 (PD-1) blocking antibodies, pembrolizumab and nivolumab, for treatment of dMMR-MSI-H cancers. In contrast, patients with proficient mismatch repair and low levels of microsatellite stability or microsatellite instability (pMMR-MSI-L/MSS) typically have low tumor-infiltrating lymphocytes and have shown unsatisfied responses to the immune checkpoint inhibitor. Different TILs environments reflect different responses to immunotherapy, highlighting the complexity of the underlying tumor-immune interaction. Profiling of TILs fundamental Indication would shed light on the mechanisms of cancer-immune evasion, thus providing opportunities for the development of novel therapeutic strategies. In this review, we summarize phenotypic diversities of TILs and their connections with prognosis in CRC and provide insights into the subsets-specific nature of TILs with different MSI status. We also discuss current clinical immunotherapy approaches based on TILs as well as promising directions for future expansion, and highlight existing clinical data supporting its use.

ncDRMarker: a computational method for identifying non-coding RNA signatures of drug resistance based on heterogeneous network.

BACKGROUND: Drug resistance is the primary cause of failure in the treatment of cancer. Identifying signatures of chemoresistance will help to overcome this problem. Current drug resistance studies focus on protein-coding genes and ignore non-coding RNAs (ncRNAs), rendering it a challenging task to systematically identify ncRNAs involved in drug resistance. METHODS: In this study, protein-protein, miRNA-target gene, miRNA-lncRNA interactions were integrated to construct a mRNA-miRNA-lncRNA network. Then, the random walk with restart (RWR) method was extended to the network for identifying ncRNA signatures of drug resistance. The leave-one-out cross validation (LOOCV) and receiver operating characteristic curve (ROC) were used to estimate the performance of ncDRMarker. Wilcoxon rank-sum test was used to validate the identified ncRNAs in NCI-60 cancer cell lines. KEGG pathway enrichment analysis was implemented to characterize the biological function of some identified ncRNAs. RESULTS: We performed this method on ten common clinical chemotherapy drugs and analyzed the results in detail. The region beneath the ROC was up to 0.881-0.951, which did not change significantly in the incomplete network, indicating the high performance and robustness of the method. Further, we confirmed the role of the identified ncRNAs in drug resistance, i.e., miR-92a-3p, a candidate chemoresistance ncRNA of tamoxifen and paclitaxel, can significantly classify cancer cell lines into sensitive or resistant to tamoxifen (or paclitaxel). We also dissected the mRNA-miRNA-lncRNA composite network and found that some hub ncRNAs, such as miR-124-3p, were involved in resistance of multiple drugs and engaged in many significant cancer-related pathways. Lastly, we have provided a ncDRMarker platform for users to identify candidate ncRNAs of drug resistance, which is available at http://bio-bigdata.hrbmu.edu.cn/ncDRMarker/index. CONCLUSIONS: Our findings suggest that ncDRMarker is an effective computational technique for prioritizing candidate ncRNAs of drug resistance. Additionally, the identified ncRNAs could be targeted to overcome drug resistance and help realize individualized treatment.

Systematic analysis of lncRNA and microRNA dynamic features reveals diagnostic and prognostic biomarkers of myocardial infarction.

Analyses of long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) implicated in myocardial infarction (MI) have increased our understanding of gene regulatory mechanisms in MI. However, it is not known how their expression fluctuates over the different stages of MI progression. In this study, we used time-series gene expression data to examine global lncRNA and miRNA expression patterns during the acute phase of MI and at three different time points thereafter. We observed that the largest expression peak for mRNAs, lncRNAs, and miRNAs occurred during the acute phase of MI and involved mainly protein-coding, rather than non-coding RNAs. Functional analysis indicated that the lncRNAs and miRNAs most sensitive to MI and most unstable during MI progression were usually related to fewer biological functions. Additionally, we developed a novel computational method for identifying dysregulated competing endogenous lncRNA-miRNA-mRNA triplets (LmiRM-CTs) during MI onset and progression. As a result, a new panel of candidate diagnostic biomarkers defined by seven lncRNAs was suggested to have high classification performance for patients with or without MI, and a new panel of prognostic biomarkers defined by two lncRNAs evidenced high discriminatory capability for MI patients who developed heart failure from those who did not.

Effective enmein-type mimics of clinical candidate HAO472: Design, synthesis and biological evaluation.

A series of enmein-type diterpenoid amino acid ester derivatives (14-22) were designed and synthesized according to l-alanine-(14-oridonin) ester trifluoroacetate (clinical candidate HAO472). Their antiproliferative activities were tested against SGC-7901, Bel-7402, HL-60, PC-3, A549 and K562 cancer cell lines and L-02 normal liver cells. The results showed that compound 19 possessed the most potent cytotoxicity with IC50 s at sub-micromolar level against human hepatoma Bel-7402 and chronic myelogenous leukemia K562 cells and more potent than l-alanine-(14-oridonin) ester (23). More importantly, 19 displayed 70-fold less cytotoxicity than parent 3 (IC50 = 25.47 µM) against L-02 cells, which exhibited certain selectivity. Further mechanism study in Bel-7402 cells revealed that 19 could induce apoptosis, G1 phase cell cycle arrest and mitochondrial dysfunction. Western blot results of caspase-3, Bax and cytochrome c upregulation and pro-caspase-3, Bcl-2 and Bcl-xL downregulation confirmed the intrinsic pathways. Overall, these data collectively demonstrated the high efficiency and selectivity of 19, l-phenylalanine-enmein-type diterpenoid ester, which inspires further and effective application as a potential antitumor candidate.