Cancer Translational Medicine

Original Research | Open Access

Vol.9 (2023) | Issue-1 | Page No: 19-31

DOI: https://doi-ds.org/doilink/03.2023-44395193/A2

Cuproptosis-related Genes in Glioblastoma as Potential Therapeutic Targets

Zhiyu Xia1,2, Haotian Tian1, Lei Shu1,2, Guozhang Tang3, Zhenyu Han4, Yangchun Hu1*, Xingliang Dai1*

Affiliations  

1. Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China

2. Department of Clinical Medicine, The First Clinical College of Anhui Medical University, Hefei, Anhui, China

3. Department of Clinical Medicine, The Second Clinical College of Anhui Medical University, Hefei, Anhui, China

4. Department of Medical Imaging Technology, The First Clinical College of Anhui Medical University, Hefei, Anhui, China

*Corresponding Author

Address for correspondence: Dr. Xingliang Dai, Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, No. 218 Jixi Road, Shushan District, Hefei 230022, Anhui, China. E-mail: daixingliang@ahmu.edu.cn

Dr. Yangchun Hu, Department of Neurosurgery, The First Affiliated Hospital of Anhui Medical University, No. 218 Jixi Road, Shushan District, Hefei 230022, Anhui, China. E-mail: hmchyczsl@126.com


Important Dates  

Date of Submission:   16-Jan-2023

Date of Acceptance:   21-Mar-2023

Date of Publication:   31-Mar-2023

ABSTRACT

Aim: To improve the prognosis of glioblastoma through the mechanism of copper-dependent cell death.

Methods: Glioblastoma (GBM) datasets were obtained from the GEO database to clarify the differentially-expressed genes (DEGs) in the carcinoma and paracancerous tissues. The molecular functions (MF) and signaling pathways of enriched DEGs were analyzed by the GO and KEGG analyses. The STRING database and Cytoscape software were used to construct the PPI network. The transcription expression and prognosis of genes were analyzed using the GEPIA 2 database to screen genes to focus on genes with clinical significance. Single Cell RNAseq (scRNAseq) analysis was used to observe the expression of cuproptosis-related genes in GBM tissues. Finally, the affinity of copper ionophore and its targets were verified by molecular docking.

Results: We obtained 1,226 DEGs, including 1,027 up-regulated and 199 down-regulated genes, and screened two genes related to copper-dependent cell death, CDKN2A, and LIPT1, which were found to be highly expressed in glioblastoma. Molecular docking showed that the binding of CDKN2A and LIPT1 to the copper ionophore resveratrol is stable, which can induce targeted copper-dependent cell death.

Conclusions: Resveratrol potentially inhibits glioblastoma proliferation and migration by acting on CDKN2A and LIPT1 through the mechanism of copper-dependent cell death. Research on resveratrol and other ionophores will affect the prognosis of GBM patients and provide new ideas for clinical targeted therapy and new drug development.

Keywords: Glioblastoma, bioinformatics, copper-dependent cell death, differentially-expressed genes, single-cell RNA seq analysis


INTRODUCTION

Glioblastoma (GBM) is the most frequent and aggressive malignant tumor of the intracranial central nervous system with the highest classification (Grade IV) of glioma. It is common in adults, and tends to occur in the cerebral hemisphere.[1],[2],[3],[4] At present, the treatment of GBM patients is complicated, with an incidence rate of about 3.2/100,000, a median survival period of about 19 months, and a 5-year survival period of less than 5%.[5],[6] Because of its heterogeneity and permeability, GBM's response to most treatments is unpredictable, and the complexity of the disease has become a major obstacle to the development of effective treatments. Glioblastoma occurs in the brain parenchyma, and it is common in genotype insensitivity (MGMT nonmethylation).[7] Therefore, it is of great clinical significance to find the key genes affecting the prognosis of glioblastoma and analyze the potential targets of traditional Chinese medicine for the treatment of glioblastoma.

According to the latest research report, Peter Tsvetkov et al.[8],[9] found that copper-dependent cell death occurs through the direct combination of copper and the fatty acylated component of the tricarboxylic acid (TCA) cycle, which leads to a series of reactions such as the aggregation of fatty acylated proteins, thus causing protein toxicity stress and eventually leading to cell death. Whole genome CRISPR-Cas9 function deletion screening was performed to identify genes associated with copper ionophore-induced cell death: FDX1, LIAS, LIPT1, DLD, DLAT, PDHA1, PDHB, MTF1, GLS, and CDKN2A. These findings may help to explain the mechanism of copper homeostasis in cells. Through this mechanism, we may be able to induce copper-dependent cell death, so as to play a therapeutic effect on tumors. At present, there is still a lack of effective treatment to combat this stubborn cancer. Therefore, traditional surgical and radiotherapy methods are difficult to completely and effectively remove tumor lesions. At present, GBM is mostly treated by surgery followed by the use of temozolomide (TMZ) for concurrent radiotherapy and chemotherapy.[10],[11],[12] In recent decades, many therapeutic drugs for GBM, such as carmustine and lomustine, have been approved for marketing.[13] However, the blood-brain barrier restricts the effective distribution of therapeutic drugs in the central system, and temozolomide also faces the same problem of chemotherapy tolerance playing a therapeutic role in anti-infection, anti-tumor, and other aspects. This study is intended to focus on the above ten genes related to copper-dependent cell death and research to build a prognosis model on the basis of bioinformatics analysis, so as to inhibit the occurrence and progression of glioblastoma, in order to find new drugs or treatment methods to improve the prognosis of glioblastoma, and lay a theoretical foundation for subsequent research.


METHODS

Data resources

Three groups of GBM-related clinical data and gene expression profiles (GSE29796, GSE50161 and GSE66354) were obtained from the Gene Expression Omnibus Database (GEO, https://www.ncbi.nlm.nih.gov/geo/). Downloaded the RNA sequencing (RNA seq) data and corresponding clinical information of GBM patients from The Cancer Genome Atlas (TCGA) Database (https://portal.gdc.cancer.gov/repository).

Data processing

Using the online analysis software GEO2R, the sample data were divided into cancer tissue and normal brain tissue according to the tissue source to set the control, and the differentially expressed genes between glioblastoma and normal tissue were obtained. The criteria for genes with significant expression differences were set and the screening conditions were as follows: | log FC | ≥ 1 and the corrected P value (adj.P.Val) was less than 0.01. The differentially expressed genes were imported into the Venn map tool for the intersection to obtain common differentially expressed genes.

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis

Enrichment analyses of GO and KEGG pathways of differentially expressed genes were obtained by DAVID bioinformatics resources (https://david.ncifcrf.gov/tools.jsp). GO enrichment analysis includes biological pathway (BP), cellular component (CC), and molecular function (MF). KEGG analysis provides the annotation information of gene signal transduction and disease pathway, which provides the basis for gene function and pathway research. For it to be considered statistically significant, the functions and approaches were screened with a count ≥ 10 and a False discovery rate (FDR)<0.01, and the visualization of GO and KEGG was realized in Bioinformatics (http://www.bioinformatics.com.cn).

Screening of differentially expressed genes involved in copper-dependent cell death

As mentioned in the previous content, the differentially expressed genes that may be closely related to the occurrence and development of glioblastoma were obtained. Based on the genes related to the death induced by copper ionophore: FDX1, LIAS, LIPT1, DLD, DLAT, PDHA1, PDHB, MTF1, GLS, CDKN2A, a heat map was drawn based on their expression in glioblastoma. The PPI network information was imported into Cytoscape 3.8.2 software and searched for genes that are differentially expressed in glioblastoma tissue and closely related to copper ion transport, and their interactive nodes were extracted to construct the key interactive network.

Differential expression of key differentially expressed genes

​We used GraphPad Prism 8 to analyze RNA seq data from glioblastoma based on the TCGA database to plot boxplots and thus to judge the differential expression of differentially expressed genes in normal and glioblastoma tissues.

Immune infiltration in cancer

TIMER 2.0 is an interactive web service database that comprehensively assesses and visualizes tumor infiltrating immune cells. TIMER2.0 is an interactive web service database for assessing and visualizing tumor immune cell infiltration by using RNA-Seq expression profile data. Analyzing the relationship between genes and tumor immune infiltration is helpful to explore the relationship between gene expression and prognosis. We used it to draw the immune infiltration maps.

Single cell RNAseq (scRNAseq) analysis

The transcriptome expression profiles of single cells in glioblastoma tissue and adjacent normal tissues were obtained by the microporous BD Rhapsody system (BD, San Jose, CA). The final library was generated by using single cell transcriptome captured by Microbeads, BD Rhapsody cDNA Kit (BD Biosciences, 633773) and BD Rhipsody Targeted mRNA & Abseq Amplification Kit (BD Biosciences, 633774). The library was sequenced in X Ten instrument (Illumina, San Diego, CA) using PE150 mode (Pair-End for 150 bp read). The original reading of single cell RNAseq (scRNAseque) analysis was processed, and the single cell gene expression matrix was generated by BD Rhapsody full transcriptome analysis pipeline. Seurat (version 3.0.1) software was used for downstream clustering and visualization. In the filtering step, less than 0.1% of the expressed genes in the cells are removed. If there are more than 35% unique molecular identifiers (UMIs) in the mitochondrial genome, the cells will also be removed. Canonical correlation analysis (CCA) integration was performed between the two batches. TIMER 2.0 is an interactive web service database that comprehensively assesses and visualizes tumor infiltrating immune cells. A total of 19 clusters were identified as the default resolution.

Immunohistochemistry

We analyzed the expression level of protein and DNA methylation level of genes in different cancers and the sections of normal and pathological tissues of related cancers by Human Protein Atlas (www.proteinatlas.org).

Molecular docking

Peter Tsvetkov et al. pointed out that FDX1 is a key regulator of cell death induced by copper ionophores. Copper ionophores can orientally bind to FDX1 to induce cell death. We focusd on resveratrol and used AutoDockTools-1.5.6 and PyMol software to dock the molecules respectively for molecular interaction recognition and to predict the stable binding conformation of molecules and proteins. Downloaded the three-dimensional structures of protein and resveratrol through Protein Data Bank (PDB) database and ZINC database respectively. The former is regarded as a receptor and the latter as a ligand, which can identify the interaction between molecules, predict the stable binding conformation of molecule and protein, and evaluate the binding strength and activity.


RESULTS

Acquisition of target gene set and screening of differentially expressed genes

The DEGs screened from GEO database were imported into Venn diagram software, and 1,226 common differentially expressed genes were obtained (1,027 up-regulated genes and 199 down-regulated genes). The volcano maps and Venn maps of GSE104291, GSE29796 and GSE35493 datasets are shown in Figures 1A and 1B.

Figure 1.
Figure 1. DEGs obtained from GEO database analysis: (A) DEGs volcano map of GSE29796, GSE50161 and GSE66354; (B) the Venn maps of up-regulated and down-regulated genes; (C) Functional enrichment analysis of GO and KEGG of DEGs; (D, E) Heatmap plot and PPI network of cuproptosis-related genes.

GO and KEGG enrichment analysis and visualization

The GO and KEGG enrichment analyses of DEGs using the DAVID functional annotation tool were visualized through the enrichment dot bubble function. As illustrated in Figure 1C, these DEGs are enriched at most in the nucleus in BP, mainly in the nucleus in CC, and mainly in the protein binding in MF. The KEGG enrichment results show that it mainly involves human papillomavirus infection, cell cycle, and ECM-receptor interaction.

Heat map and PPI network of cuproptosis-related genes

The heat map of cuproptosis-related genes is drawn based on their expression [Figure 1D]. We found that LIPT1, CDKN2A, and GLS were differentially expressed in glioblastoma tissues, and were closely related to copper ion transport and cell death. The PPI network of DEGs was constructed using the STRING database. We imported the STRING tabular text into Cytoscape 3.8.2 software to retrieve and extract the node network diagrams of cuproptosis-related genes and their interactions with the help of the cytoHubba plug-in, so as to draw the protein-protein interaction network of copper death gene. Get connectivity and other network topology parameters to further realize visualization. The red line connecting the two proteins suggests a positive correlation in protein expression, while the blue line suggests a positive correlation, as shown in Figure 1E.

Differential expression and immune infiltration

The box plots of genes in normal and GBM tissues of different levels are shown in Figure 2A. Compared with normal brain tissues, the expression of CDKN2A, LIPT1, and GLS was statistically different in GBM (P <​ 0.001). Two up-regulated genes: CDKN2A and LIPT1, are focused on to improve the prognosis of glioblastoma. The immune infiltration maps of the genes are shown in Figure 2B. Generally speaking, CDKN2A is correlated with the immune infiltration level of several immune cells, including CD8+ T cells, macrophages and dendritic cells (DC). LIPT1 is also correlated with the infiltration level of B cells, CD8+ T cells, and neutrophil cells. We noticed that the level of CD8+ immune infiltration was positively correlated with both CDKN2A and LIPT1, which suggested that CD8+ T cells participated in the process of immune infiltration to some extent and played an important role in immune tumor interaction.

Figure 2.
Figure 2. Important information of genes: (A) Expression of the genes in normal and glioma tissues (Box Plot); (B)The infiltration level of different immune cells under various copy numbers of genes.

The scRNA sequence analysis identified the cell types and subclusters in GBM and brain cells. We used the BD Rhapsody system to analyze GBM samples and normal tissue, which were collected from areas near the tumor. After separation, dead cells and denucleated cell fragments were discarded. Fluorescent activated cell sorting (FACS) was used, cell selection was calculated, and live intact cells were isolated by filtration. After scRNA sequence analysis, 12,118 cells were isolated and about 500 genes and UMI were detected in each cell. After removing the batch effect, the cells were divided into 19 clusters [Figure 3A]. According to gene expression, we divided the cells into 19 clusters [Figure 3B]. Fractional differences between normal and cancer cells in each cell cluster were evaluated [Figure 3C]. And the distribution of cells was shown by t-Distributed Stochastic Neighbor Embedding (t-SNE), the expression of CDKN2A and LIPT1 in each cell subgroup in normal group and control group is shown [Figure 3D-3F].

Figure 3.
Figure 3. CDKN2A and LIPT1 expression in GBM: (A)Relative expression of CDKN2A and LIPT1 in all clusters; (B) tSNE plots show cells are classified into all cell clusters and labeled with different colors; (C) Relative proportions of the 19 cell clusters; (D-F) Relative expression of CDKN2A and LIPT1 in normal and tumor tissue.

Immunohistochemistry

We found sections of normal tissues and tumor tissues in the Human Protein Atlas (https://www.proteinatlas.org/) to show the expression of CDKN2A and LIPT1 [Figure 3F].

Molecular docking

​Molecular docking verified that resveratrol, as a copper ionophore, can act directly or indirectly on key potential target proteins such as CDKN2A, and LIPT1, forming a relatively stable complex as shown in Figure 4A, 4B and Table 1. This could serve as the key evidence for the induction of resveratrol on CDKN2A and LIPT1, which may be similar to the induction of elesclomol on FDX1 and may inhibit the malignant transformation of glioblastoma. The possible mechanism of copper-dependent cell death in glioblastoma can be referred to in Figure 4C. Under the mediation of resveratrol, copper ions can produce superoxide anion and hydrogen peroxide in the tumor microenvironment. At the same time, copper ions bind to overexpressed CDKN2A and LIPT1 in a targeted way, and ultimately affect the cell tricarboxylic acid cycle by regulating their signal pathways, leading to copper-dependent cell death, thus achieving targeted therapy for tumors.

Figure 4.
Figure 4. Molecular docking: (A) CDKN2A & resveratrol; (B) LIPT1 & resveratrol; (C) mechanism of copper dependent cell death.

Table 1.
Table 1. Molecular docking prediction of bine energy and hydrogen bond


DISCUSSION

Glioblastoma is an extremely malignant tumor that afflicts humans. Most low grade glioma will recur within 5 to 10 years and then develop into GBM. Malignant transformation of GBM is a complex process. The formation and increase of malignant degree are caused by the accumulation of many gene changes, involving abnormalities of a variety of gene mutations and cell pathways.[14] Many factors affecting survival have been identified, including age, Karnofsky physical status (KPS), nervous system defects, resection range, tumor multifocal and location, etc.[15],[16],[17] At present, the methylation of O6- methylguanine-DNA methyltransferase (MGMT) promoter, EGFR change and isocitrate dehydrogenase 1, 2 (IDH1, IDH2) mutations have been identified as molecular markers of glioblastoma. Clinical practice shows that GBM patients with MGMT promoter methylation and IDH1 mutations have a better prognosis than those without mutations.[18],[19] Therefore, it is of great importance to identify molecular biomarkers associated with GBM. This research is dedicated to the discovery of such pivotal genes and the exploration of their differential molecular mechanisms and biological functions in normal and cancerous tissues, which could benefit the diagnosis and treatment of glioblastoma.​

Recent studies have pointed to the presence of regulatory cell death modes in glioblastoma, including apoptosis and iron death. The former induces the cleavage and activation of promoter Caspase through the death receptor pathway and mitochondrial pathway.[20],[21],[22] The latter destroys the system cystine/glutamic acid reverse transporter (xCT) or glutathione peroxidase 4 (GPX4)[23],[24] through excessive iron ion, and these findings have great potential for chemotherapy of drug-resistant malignant tumors. Lots of evidence shows that there is an abnormal accumulation of copper in the process of cell apoptosis and reactive oxygen species (ROS).[25],[26],[27],[28],[29],[30]

Copper ions are an important trace element in the human body, playing a regulatory role in a variety of life activities. Copper concentration is often out of balance in tumors.[31] In gallbladder cancer,[32] breast cancer,[33],[34] colorectal cancer,[35],[36] and bladder cancer,[37],[38] the level of copper ion in serum and tumor tissue was significantly increased. As mentioned above, copper dependent cell death as a new cell death mechanism has broad prospects in cancer chemotherapy.[39],[40]

A large number of experiments have proved that drugs that can bind copper ions, such as disulfiram (DSF), tetrathiomolybdate (TM), and penicillamine, can significantly affect the cell life cycle and cancer progression, and their common feature is that they are all effective carriers of copper ions.[40],[41],[42],[43],[44],[45],[46],[47] This suggests that finding suitable carriers to alter the distribution and concentration of copper ions may be an effective way to treat glioblastoma.[48]

Inspired by such studies, we hope to find a carrier that can efficiently bind copper ions to target proteins. This would further improve the possibility of achieving targeted and efficient copper dependent cell death in glioblastoma tissue. Significant copper dependent cell death in glioblastoma tissue is expected to be triggered by the addition of appropriate biocatalysts, inducers, or intermediate carrier compounds. In addition, there may still be some mechanisms that have not been clarified yet. As research deepens, more ways to inhibit the occurrence and progression of glioblastoma will be discovered in the future to improve the therapeutic effect of GBM and benefit more patients.

Research shows that nanomaterials can produce reactive oxygen species in cells through heterogeneous reactions on particle surfaces or dissolved copper.[49],[50] Therefore, nanomaterials undergo a chemical transformation in the environment or human body, which will considerably affect the bioavailability of metals, thus affecting the occurrence and progression of cytotoxicity and cancer.[51] Resveratrol (3,4', 5-Trihydroxysilbene), as a classical copper ionophore, plays the role of anti-oxidation[52] and anti-aging,[53] catalyzes DNA degradation[54] and improves mitochondrial function.[55] Resveratrol is also considered as a cancer chemopreventive agent, which can inhibit all three stages of chemical carcinogenesis, namely the initiation, promotion, and progression of tumors,[56] and has been proven to induce apoptosis of human tumor cells.[57],[58],[59] It has been proved that resveratrol forms a complex with Cu (Ⅱ), reducing it to Cu (Ⅰ),[60] and molecular oxygen is reduced to superoxide anion. This process may even occur outside cells, leading to the formation of H2O2. Cu (I) can be oxidized to Cu (Ⅱ) again by H2O2[61] and combined with polyphenols to form the above cycle, while resveratrol is converted into quinones. H2O2, Cu (Ⅰ), free radicals, and other substances cause damage to various cell components.[62] Based on the above considerations, we speculate that the possible mechanism of the complex of resveratrol and copper ions is shown in Figure 5.

Figure 5.
Figure 5. Mechanism of the complexation of resveratrol with copper(Ⅱ)

To sum up, the DNA breakage mechanism induced by resveratrol Cu (Ⅱ) through the production of reactive oxygen species may be an important way to kill cancer cells. As a leading compound, resveratrol Cu (Ⅱ) is of great significance in developing new anti-tumor and cancer chemopreventive agents.

Related studies have identified genes associated with cuproptosis as being responsible for copper induced cell death. Based on the above assumption, we combined the existing analysis data results and literature to conduct a detailed and in-depth study on the role of glioblastoma and copper ions on the cell life cycle, and we screened two DEGs closely related to GBM malignant transformation, which are copper ion targets and participate in copper-dependent cell death: CDKN2A and LIPT1.

CDKN2A/P16 is an important tumor suppressor gene. The phosphorylation of Rb leads to the increase of CDKN2A expression, which inhibits CDK4/6 and increases the level of low phosphorylated Rb, which leads to the decrease of CDKN2A expression.[63] In addition, exposure to ionizing radiation or DNA damage agents have also been shown to increase the expression of CDKN2A, leading to aging.[64],[65] P16/Rb pathway cascades with a mitotic signal to induce ROS (reactive oxygen species) and then activates protein kinase C delta (PKC delta).[66] This in turn enhances the generation of ROS, forming a positive feedback loop for ROS-PKC delta signal conduction.

Normal cell survival depends on integrin-mediated adhesion between the cell and the extracellular matrix, which triggers anti-apoptotic and survival-promoting signals. There are key apoptosis promoting factors in the mitochondrial membrane space (IMS), such as cytochrome C, which will trigger apoptosis if released into the cytoplasm.[67] Therefore, the isolation of cells from the matrix can significantly stimulate the production of ROS, especially in the mitochondria of isolated cells.[68],[69] As a byproduct of the electron transport chain (ETC), ROS has a dual function. Low-level ROS can activate various signal pathways to stimulate cell proliferation and survival, such as MAP kinase and HIF,[70],[71] while excessive ROS will irreversibly destroy cellular macromolecular components (protein, lipid, nucleic acid) and cause cell death (including apoptosis).

The P16/Rb pathway cascades with mitotic signals to induce the production of a large number of ROS, some of which activate the intrinsic mitochondrial apoptosis pathway through lipid peroxidation: ROS peroxycardiolipin (a mitochondrial specific anionic phospholipid), leading to the release of cytochrome C,[72] triggering the activation of apoptotic bodies and caspases in the cytosol, leading to cell death,[73],[74] as shown in Figure 6.

Figure 6.
Figure 6. Mechanism of CDKN2A affecting cell cycle

LIPT1 (Lipoyltransferase 1, fatty acyltransferase), which encodes lipoyltransferase, participates in the synthesis of lipoic acid from octanoic acid and is believed to catalyze the attachment of lipoic acid to pyruvate dehydrogenase complex (PDHc) and α-Ketoglutarate dehydrogenase (α-KGDHc).[75] Lipoic acid is an essential cofactor in several cellular redox reactions. In humans, lipoic acid only exists in mitochondria, and it is a crucial cofactor of four different enzyme complexes: PDHc, α-KGDH, 2-oxo adipate dehydrogenase (2-OADH), and branched chain keto dehydrogenase (BCKDH).[76],[77],[78],[79] Our study found that LIPT1 expression was up-regulated, which increased the level of lipoacylated TCA enzyme (especially PDHc complex) and caused the lipoacylation of its E3 binding protein (E3BP). The liberal part acts as a direct copper binder, leading to the aggregation of the listed proteins. Lipoic acid reduced the number of proteins containing Fe-S clusters, which affected their participation in electron transfer reaction and complexes Ⅰ, Ⅱ, and Ⅲ, reflecting acute protein toxicity stress,[80] as shown in Figure 7.

Figure 7.
Figure 7. Mechanism of LIPT1 affecting aerobic respiration of cells

Based on bioinformatics methods, we initially identified and validated genes with abnormally high expression in glioblastoma, and further screened CDKN2A, and LIPT1 through a copper dependent cell death mechanism. Further in vitro and in vivo studies are needed to explore a new treatment scheme for glioblastoma patients based on the copper-dependent death pathway, so as to clarify the potential mechanism and verify its clinical applicability, so as to inhibit the occurrence and progression of tumors and lay the foundation for the development of new drugs for GBM targeted therapy.

 

FINANCIAL SUPPORT AND SPONSORSHIP 

This work was supported by the grants from Anhui Provincial Natural Science Foundation  (No.2208085MH251) (to Xingliang Dai), Scientific Research Fund Project of Anhui Medical University (No.2021xkj131 and No.2021xkj135) (to Xingliang Dai and Yangchun Hu) and Natural Science Research Project of Colleges and Universities in Anhui Province (No.KJ2021A0293) (to Yangchun Hu).

 

CONFLICTS OF INTEREST 

The authors have no conflicts of interest to declare. 

 

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

Not applicable. 

 

AUTHOR CONTRIBUTIONS

(I) Conception and design: Z Xia and H Tian; (II) Administrative support: Y Hu; (III) Provision of study materials or patients: L Shu and Z Han; (IV) Collection and assembly of data: G Tang and Z Xia; (V) Data analysis and interpretation: X Dai and Z Xia; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.


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Imaging‑driven Digital Biomarkers

Enrico Capobianco


Target‑Matching Accuracy in Stereotactic Body Radiation Therapy of Lung Cancer: An Investigation Based on Four‑Dimensional Digital Human Phantom

Jing Cai1,2, Kate Turner2, Xiao Liang2, W. Paul Segars2,3, Chris R. Kelsey1, David Yoo1, Lei Ren1,2, Fang‑Fang Yin1,2


Downregulation of Death‑associated Protein Kinase 3 and Caspase‑3 Correlate to the Progression and Poor Prognosis of Gliomas

Ye Song, Tianshi Que, Hao Long, Xi’an Zhang, Luxiong Fang, Zhiyong Li, Songtao Qi


Hyaluronic Acid in Normal and Neoplastic Colorectal Tissue: Electrospray Ionization Mass Spectrometric and Fluor Metric Analysis

Ana Paula Cleto Marolla1, Jaques Waisberg2, Gabriela Tognini Saba2, Demétrius Eduardo Germini2, Maria Aparecida da Silva Pinhal1


Melanoma Antigen Gene Family in the Cancer Immunotherapy

Fengyu Zhu1, Yu Liang1, Demeng Chen2, Yang Li1


Combined Chronic Lymphocytic Leukemia and Pancreatic Neuroendocrine Carcinoma: A Collision Tumor Variation

Kaijun Huang1, Panagiotis J. Vlachostergios1, Wanhua Yang2, Rajeev L. Balmiki3


Antiproliferative and Apoptotic Effect of Pleurotus ostreatus on Human Mammary Carcinoma Cell Line (Michigan Cancer Foundation‑7)

Krishnamoorthy Deepalakshmi, Sankaran Mirunalini


Impact of Age on the Biochemical Failure and Androgen Suppression after Radical Prostatectomy for Prostate Cancer in Chilean Men

Nigel P. Murray1,2, Eduardo Reyes1,3, Nelson Orellana1, Cynthia Fuentealba1, Omar Jacob1


Carcinoma of Unknown Primary: 35 Years of a Single Institution’s Experience

Rana I. Mahmood1,2, Mohammed Aldehaim1,3, Fazal Hussain4, Tusneem A. Elhassan4,
Zubeir A. Khan5, Muhammad A. Memon6


Metformin in Ovarian Cancer Therapy: A Discussion

Yeling Ouyang1, Xi Chen2, Chunyun Zhang1, Vichitra Bunyamanop1, Jianfeng Guo3


The Progress in Molecular Biomarkers of Gliomas

Jing Qi1, Hongwei Yang2, Xin Wang2, Yanyang Tu1


Correlation between Paclitaxel Tc > 0.05 and its Therapeutic Efficacy and Severe Toxicities in Ovarian Cancer Patients

Shuyao Zhang1*, Muyin Sun2*, Yun Yuan3*, Miaojun Wang4*, Yuqi She1*, Li Zhou5, Congzhu Li5, Chen Chen1, Shengqi Zhang4


Identifying Gaps and Relative Opportunities for Discovering Membrane Proteomic Biomarkers of Triple‑negative Breast Cancer as a Translational Priority

Bhooma Venkatraman


The Molecular Mechanism and Regulatory Pathways of Cancer Stem Cells

Zhen Wang1, Hongwei Yang2, Xin Wang2, Liang Wang3, Yingduan Cheng4, Yongsheng Zhang5, Yanyang Tu1,2


Nanoparticle Drug Delivery Systems and Three‑dimensional Cell Cultures in Cancer Treatments and Research

Wenjin Shi1, Ding Weng2,3, Wanting Niu2,3


Choline Kinase Inhibitors Synergize with TRAIL in the Treatment of Colorectal Tumors and Overcomes TRAIL Resistance

Juan Carlos Lacal1, Ladislav Andera2


MicroRNA Regulating Metabolic Reprogramming in Tumor Cells: New Tumor Markers

Daniel Otero‑Albiol, Blanca Felipe‑Abrio


Biomarkers of Colorectal Cancer: A Genome‑wide Perspective

José M. Santos‑Pereira1, Sandra Muñoz‑Galván2


Nicotinamide Adenine Dinucleotide+ Metabolism Biomarkers in Malignant Gliomas

Manuel P. Jiménez‑García, Eva M. Verdugo‑Sivianes, Antonio Lucena‑Cacace


Patient-derived Xenografts as Models for Personalized Medicine Research in Cancer

Marco Perez, Lola Navas, Amancio Carnero


Genome‑wide Transcriptome Analysis of Prostate Cancer Tissue Identified Overexpression of Specific Members of the Human Endogenous Retrovirus‑K Family

Behnam Sayanjali1,2


Clinical Utility of Interleukin‑18 in Breast Cancer Patients: A Pilot Study

Reecha A. Parikh, Toral P. Kobawala, Trupti I. Trivedi, Mahnaz M. Kazi, Nandita R. Ghosh


Current and Future Systemic Treatment Options for Advanced Soft‑tissue Sarcoma beyond Anthracyclines and Ifosfamide

Nadia Hindi1,2, Javier Martin‑Broto1,2


The Genomic Organization and Function of IRX1 in Tumorigenesis and Development

Pengxing Zhang1, Hongwei Yang2, Xin Wang2, Liang Wang3, Yingduan Cheng4, Yongsheng Zhang5, Yanyang Tu1,2


Stem Cell‑based Approach in Diabetes and Pancreatic Cancer Management

Yi‑Zhou Jiang1, Demeng Chen2


Mutation Detection with a Liquid Biopsy 96 Mutation Assay in Cancer Patients and Healthy Donors

Aaron Yun Chen, Glenn D. Braunstein, Megan S. Anselmo, Jair A. Jaboni, Fernando Troy Viloria, Julie A. Neidich, Xiang Li, Anja Kammesheidt


The Application of Estrogen Receptor‑1 Mutations’ Detection through Circulating Tumor DNA in Breast Cancer

Binliang Liu, Yalan Yang, Zongbi Yi, Xiuwen Guan, Fei Ma


Circulating MicroRNAs and Long Noncoding RNAs: Liquid Biomarkers in Thoracic Cancers

Pablo Reclusa1, Anna Valentino1, Rafael Sirera1,2, Martin Frederik Dietrich3, Luis Estuardo Raez3, Christian Rolfo1


Exosomes Biology: Function and Clinical Implications in Lung Cancer

Martin Frederik Dietrich1, Christian Rolfo2, Pablo Reclusa2, Marco Giallombardo2, Anna Valentino2, Luis E. Raez1


Circulating Tumor DNA: A Potential Biomarker from Solid Tumors’ Monitor to Anticancer Therapies

Ting Chen1,2, Rongzhang He1,3, Xinglin Hu1,3,4, Weihao Luo1, Zheng Hu1,3, Jia Li1, Lili Duan1, Yali Xie1,2, Wenna Luo1,2, Tan Tan1,2, Di‑Xian Luo1,2


Novel Molecular Multilevel Targeted Antitumor Agents

Poonam Sonawane1, Young A. Choi1, Hetal Pandya2, Denise M. Herpai1, Izabela Fokt3,
Waldemar Priebe3, Waldemar Debinski1


Fish Oil and Prostate Cancer: Effects and Clinical Relevance

Pei Liang, Michael Gao Jr.


Stemness‑related Markers in Cancer

Wenxiu Zhao1, Yvonne Li2, Xun Zhang1


Autophagy Regulated by miRNAs in Colorectal Cancer Progression and Resistance

Andrew Fesler1, Hua Liu1, Ning Wu1,2, Fei Liu3, Peixue Ling3, Jingfang Ju1,3


Gastric Metastases Mimicking Primary Gastric Cancer: A Brief Literature Review

Simona Gurzu1,2,3, Marius Alexandru Beleaua1, Laura Banias2, Ioan Jung1


Possibility of Specific Expression of the Protein Toxins at the Tumor Site with Tumor‑specialized Promoter

Liyuan Zhou1,2, Yujun Li1,2, Changchen Hu3, Binquan Wang1,2


SKI‑178: A Multitargeted Inhibitor of Sphingosine Kinase and Microtubule Dynamics Demonstrating Therapeutic Efficacy in Acute Myeloid Leukemia Models

Jeremy A. Hengst1,2, Taryn E. Dick1,2, Arati Sharma1, Kenichiro Doi3, Shailaja Hegde4, Su‑Fern Tan5, Laura M. Geffert1,2, Todd E. Fox5, Arun K. Sharma1, Dhimant Desai1, Shantu Amin1, Mark Kester5, Thomas P. Loughran5, Robert F. Paulson4, David F. Claxton6, Hong‑Gang Wang3, Jong K. Yun1,2


A T‑cell Engager‑armed Oncolytic Vaccinia Virus to Target the Tumor Stroma

Feng Yu1, Bangxing Hong1, Xiao‑Tong Song1,2,3


Real‑world Experience with Abiraterone in Metastatic Castration‑resistant Prostate Cancer

Yasar Ahmed1, Nemer Osman1, Rizwan Sheikh2, Sarah Picardo1, Geoffrey Watson1


Combination of Interleukin‑11Rα Chimeric Antigen Receptor T‑cells and Programmed Death‑1 Blockade as an Approach to Targeting Osteosarcoma Cells In vitro

Hatel Rana Moonat, Gangxiong Huang, Pooja Dhupkar, Keri Schadler, Nancy Gordon,
Eugenie Kleinerman


Efficacy and Safety of Paclitaxel‑based Therapy and Nonpaclitaxel‑based Therapy in Advanced Gastric Cancer

Tongwei Wu, Xiao Yang, Min An, Wenqin Luo, Danxian Cai, Xiaolong Qi


Motion Estimation of the Liver Based on Deformable Image Registration: A Comparison Between Four‑Dimensional‑Computed Tomography and Four‑Dimensional-Magnetic Resonance Imaging

Xiao Liang1, Fang‑Fang Yin1,2, Yilin Liu1, Brian Czito2, Manisha Palta2, Mustafa Bashir3, Jing Cai1,2


A Feasibility Study of Applying Thermal Imaging to Assist Quality Assurance of High‑Dose Rate Brachytherapy

Xiaofeng Zhu1, Yu Lei1, Dandan Zheng1, Sicong Li1, Vivek Verma1, Mutian Zhang1, Qinghui Zhang1, Xiaoli Tang2, Jun Lian2, Sha X. Chang2, Haijun Song3, Sumin Zhou1, Charles A. Enke1


Role of Exosome microRNA in Breast Cancer

Wang Qu, Ma Fei, Binghe Xu


Recent Progress in Technological Improvement and Biomedical Applications of the Clustered Regularly Interspaced Short Palindromic Repeats/Cas System

Yanlan Li1,2*, Zheng Hu1*, Yufang Yin3, Rongzhang He1, Jian Hu1, Weihao Luo1, Jia Li1, Gebo Wen2, Li Xiao1, Kai Li1, Duanfang Liao4, Di-Xian Luo1,5


The Significance of Nuclear Factor‑Kappa B Signaling Pathway in Glioma: A Review

Xiaoshan Xu1, Hongwei Yang2, Xin Wang2, Yanyang Tu1


Markerless Four‑Dimensional‑Cone Beam Computed Tomography Projection‑Phase Sorting Using Prior Knowledge and Patient Motion Modeling: A Feasibility Study

Lei Zhang1,2, Yawei Zhang2, You Zhang1,2,3, Wendy B. Harris1,2, Fang‑Fang Yin1,2,4, Jing Cai1,4,5, Lei Ren1,2


The Producing Capabilities of Interferon‑g and Interleukin‑10 of Spleen Cells in Primary and Metastasized Oral Squamous Cell Carcinoma Cells-implanted Mice

Yasuka Azuma1,2, Masako Mizuno‑Kamiya3, Eiji Takayama1, Harumi Kawaki1, Toshihiro Inagaki4, Eiichi Chihara2, Yasunori Muramatsu5, Nobuo Kondoh1


“Eating” Cancer Cells by Blocking CD47 Signaling: Cancer Therapy by Targeting the Innate Immune Checkpoint

Yi‑Rong Xiang, Li Liu


Glycosylation is Involved in Malignant Properties of Cancer Cells

Kazunori Hamamura1, Koichi Furukawa2


Biomarkers in Molecular Epidemiology Study of Oral Squamous Cell Carcinoma in the Era of Precision Medicine

Qing‑Hao Zhu1*, Qing‑Chao Shang1*, Zhi‑Hao Hu1*, Yuan Liu2, Bo Li1, Bo Wang1, An‑Hui Wang1


I‑Kappa‑B Kinase‑epsilon Activates Nuclear Factor‑kappa B and STAT5B and Supports Glioblastoma Growth but Amlexanox Shows Little Therapeutic Potential in These Tumors

Nadège Dubois1, Sharon Berendsen2, Aurélie Henry1,2, Minh Nguyen1, Vincent Bours1,
Pierre Alain Robe1,2


Suppressive Effect of Mesenchymal Stromal Cells on Interferon‑g‑Producing Capability of Spleen Cells was Specifically Enhanced through Humoral Mediator(s) from Mouse Oral Squamous Cell Carcinoma Sq‑1979 Cells In Vitro

Toshihiro Inagaki1,2, Masako Mizuno‑Kamiya3, Eiji Takayama1, Harumi Kawaki1, Eiichi Chihara4, Yasunori Muramatsu5, Shinichiro Sumitomo5, Nobuo Kondoh1


An Interplay Between MicroRNA and SOX4 in the Regulation of Epithelial–Mesenchymal Transition and Cancer Progression

Anjali Geethadevi1, Ansul Sharma2, Manish Kumar Sharma3, Deepak Parashar1


MicroRNAs Differentially Expressed in Prostate Cancer of African‑American and European‑American Men

Ernest K. Amankwah


The Role of Reactive Oxygen Species in Screening Anticancer Agents

Xiaohui Xu1, Zilong Dang2, Taoli Sun3, Shengping Zhang1, Hongyan Zhang1


Panobinostat and Its Combination with 3‑Deazaneplanocin‑A Induce Apoptosis and Inhibit In vitro Tumorigenesis and Metastasis in GOS‑3 Glioblastoma Cell Lines

Javier de la Rosa*, Alejandro Urdiciain*, Juan Jesús Aznar‑Morales, Bárbara Meléndez1,
Juan A. Rey2, Miguel A. Idoate3, Javier S. Castresana


Cancer Stem‑Like Cells Have Cisplatin Resistance and miR‑93 Regulate p21 Expression in Breast Cancer

Akiko Sasaki1, Yuko Tsunoda2, Kanji Furuya3, Hideto Oyamada1, Mayumi Tsuji1, Yuko Udaka1, Masahiro Hosonuma1, Haruna Shirako1, Nana Ichimura1, Yuji Kiuchi1


The Contribution of Hexokinase 2 in Glioma

Hui Liu1, Hongwei Yang2, Xin Wang3, Yanyang Tu1


The Mechanism of BMI1 in Regulating Cancer Stemness Maintenance, Metastasis, Chemo‑ and Radiation Resistance

Xiaoshan Xu, Zhen Wang, Nan Liu, Pengxing Zhang, Hui Liu, Jing Qi, Yanyang Tu


A Multisource Adaptive Magnetic Resonance Image Fusion Technique for Versatile Contrast Magnetic Resonance Imaging

Lei Zhang1,2, Fang‑Fang Yin1,2,3, Brittany Moore1,2, Silu Han1,2, Jing Cai1,2,4


Senescence and Cancer

Sulin Zeng1,2, Wen H. Shen2, Li Liu1


The “Wild”‑type Gastrointestinal Stromal Tumors: Heterogeneity on Molecule Characteristics and Clinical Features

Yanhua Mou1, Quan Wang1, Bin Li1,2


Retreatment with Cabazitaxel in a Long‑Surviving Patient with Castration‑Resistant Prostate Cancer and Visceral Metastasis

Raquel Luque Caro, Carmen Sánchez Toro, Lucia Ochoa Vallejo


Therapy‑Induced Histopathological Changes in Breast Cancers: The Changing Role of Pathology in Breast Cancer Diagnosis and Treatment

Shazima Sheereen1, Flora D. Lobo1, Waseemoddin Patel2, Shamama Sheereen3,
Abhishek Singh Nayyar4, Mubeen Khan5


Glioma Research in the Era of Medical Big Data

Feiyifan Wang1, Christopher J. Pirozzi2, Xuejun Li1


Transarterial Embolization for Hepatocellular Adenomas: Case Report and Literature Review

Jian‑Hong Zhong1,2, Kang Chen1, Bhavesh K. Ahir3, Qi Huang4, Ye Wu4, Cheng‑Cheng Liao1, Rong‑Rong Jia1, Bang‑De Xiang1,2, Le‑Qun Li1,2


Nicotinamide Phosphoribosyltransferase: Biology, Role in Cancer, and Novel Drug Target

Antonio Lucena‑Cacace1,2,3, Amancio Carnero1,2


Enhanced Anticancer Effect by Combination of Proteoglucan and Vitamin K3 on Bladder Cancer Cells

Michael Zhang, Kelvin Zheng, Muhammad Choudhury, John Phillips, Sensuke Konno


Molecular Insights Turning Game for Management of Ependymoma: A Review of Literature

Ajay Sasidharan, Rahul Krishnatry


IDH Gene Mutation in Glioma

Leping Liu1, Xuejun Li1,2


Challenges and Advances in the Management of Pediatric Intracranial Germ Cell Tumors: A Case Report and Literature Review

Gerard Cathal Millen1, Karen A. Manias1,2, Andrew C. Peet1,2, Jenny K. Adamski1


Assessing the Feasibility of Using Deformable Registration for Onboard Multimodality‑Based Target Localization in Radiation Therapy

Ge Ren1,2,3, Yawei Zhang1,2, Lei Ren1,2


Research Advancement in the Tumor Biomarker of Hepatocellular Carcinoma

Qing Du1, Xiaoying Ji2, Guangjing Yin3, Dengxian Wei3, Pengcheng Lin1, Yongchang Lu1,
Yugui Li3, Qiaohong Yang4, Shizhu Liu5, Jinliang Ku5, Wenbin Guan6, Yuanzhi Lu7


Novel Insights into the Role of Bacterial Gut Microbiota in Hepatocellular Carcinoma

Lei Zhang1, Guoyu Qiu2, Xiaohui Xu2, Yufeng Zhou3, Ruiming Chang4


Central Odontogenic Fibroma with Unusual Presenting Symptoms

Aanchal Tandon, Bharadwaj Bordoloi, Safia Siddiqui, Rohit Jaiswal


The Prognostic Role of Lactate in Patients Who Achieved Return of Spontaneous Circulation after Cardiac Arrest: A Systematic Review and Meta‑analysis

Dongni Ren1, Xin Wang2, Yanyang Tu1,2


Inhibitory Effect of Hyaluronidase‑4 in a Rat Spinal Cord Hemisection Model

Xipeng Wang1,2, Mitsuteru Yokoyama2, Ping Liu3


Research and Development of Anticancer Agents under the Guidance of Biomarkers

Xiaohui Xu1, Guoyu Qiu1, Lupeng Ji2, Ruiping Ma3, Zilong Dang4, Ruling Jia1, Bo Zhao1


Idiopathic Hypereosinophilic Syndrome and Disseminated Intravascular Coagulation

Mansoor C. Abdulla


Phosphorylation of BRCA1‑Associated Protein 1 as an Important Mechanism in the Evasion of Tumorigenesis: A Perspective

Guru Prasad Sharma1, Anjali Geethadevi2, Jyotsna Mishra3, G. Anupa4, Kapilesh Jadhav5,
K. S. Vikramdeo6, Deepak Parashar2


Progress in Diagnosis and Treatment of Mixed Adenoneuroendocrine Carcinoma of Biliary‑Pancreatic System

Ge Zengzheng1, Huang-Sheng Ling2, Ming-Feng Li2, Xu Xiaoyan1, Yao Kai1, Xu Tongzhen3,
Ge Zengyu4, Li Zhou5


Surface-Enhanced Raman Spectroscopy to Study the Biological Activity of Anticancer Agent

Guoyu Qiu1, Xiaohui Xu1, Lupeng Ji2, Ruiping Ma3, Zilong Dang4, Huan Yang5


Alzheimer’s Disease Susceptibility Genes in Malignant Breast Tumors

Steven Lehrer1, Peter H. Rheinstein2


OSMCC: An Online Survival Analysis Tool for Merkel Cell Carcinoma

Umair Ali Khan Saddozai1, Qiang Wang1, Xiaoxiao Sun1, Yifang Dang1, JiaJia Lv1,2, Junfang Xin1, Wan Zhu3, Yongqiang Li1, Xinying Ji1, Xiangqian Guo1


Protective Activity of Selenium against 5‑Fluorouracil‑Induced Nephrotoxicity in Rats

Elias Adikwu, Nelson Clemente Ebinyo, Beauty Tokoni Amgbare


Advances on the Components of Fibrinolytic System in Malignant Tumors

Zengzheng Ge1, Xiaoyan Xu1, Zengyu Ge2, Shaopeng Zhou3, Xiulin Li1, Kai Yao1, Lan Deng4


A Patient with Persistent Foot Swelling after Ankle Sprain: B‑Cell Lymphoblastic Lymphoma Mimicking Soft‑tissue Sarcoma

Crystal R. Montgomery‑Goecker1, Andrew A. Martin2, Charles F. Timmons3, Dinesh Rakheja3, Veena Rajaram3, Hung S. Luu3


Coenzyme Q10 and Resveratrol Abrogate Paclitaxel‑Induced Hepatotoxicity in Rats

Elias Adikwu, Nelson Clemente Ebinyo, Loritta Wasini Harris


Progress in Clinical Follow‑up Study of Dendritic Cells Combined with Cytokine‑Induced Killer for Stomach Cancer

Ling Wang1,2, Run Wan1,2, Cong Chen1,2, Ruiliang Su1,2, Yumin Li1,2


Supraclavicular Lymphadenopathy as the Initial Manifestation in Carcinoma of Cervix

Priyanka Priyaarshini1, Tapan Kumar Sahoo2


ABO Typing Error Resolution and Transfusion Support in a Case of an Acute Leukemia Patient Showing Loss of Antigen Expression

Debasish Mishra1, Gopal Krushna Ray1, Smita Mahapatra2, Pankaj Parida2


Protein Disulfide Isomerase A3: A Potential Regulatory Factor of Colon Epithelial Cells

Yang Li1, Zhenfan Huang2, Haiping Jiang3


Clinicopathological Association of p16 and its Impact on Outcome of Chemoradiation in Head‑and‑Neck Squamous Cell Cancer Patients in North‑East India

Srigopal Mohanty1, Yumkhaibam Sobita Devi2, Nithin Raj Daniel3, Dulasi Raman Ponna4,
Ph. Madhubala Devi5, Laishram Jaichand Singh2


Potential Inhibitor for 2019‑Novel Coronaviruses in Drug Development

Xiaohui Xu1, Zilong Dang2, Lei Zhang3, Lingxue Zhuang4, Wutang Jing5, Lupeng Ji6, Guoyu Qiu1


Best‑Match Blood Transfusion in Pediatric Patients with Mixed Autoantibodies

Debasish Mishra1, Dibyajyoti Sahoo1, Smita Mahapatra2, Ashutosh Panigrahi3


Characteristics and Outcome of Patients with Pheochromocytoma

Nadeema Rafiq1, Tauseef Nabi2, Sajad Ahmad Dar3, Shahnawaz Rasool4


Comparison of Histopathological Grading and Staging of Breast Cancer with p53‑Positive and Transforming Growth Factor‑Beta Receptor 2‑Negative Immunohistochemical Marker Expression Cases

Palash Kumar Mandal1, Anindya Adhikari2, Subir Biswas3, Amita Giri4, Arnab Gupta5,
Arindam Bhattacharya6


Chemical Compositions and Antiproliferative Effect of Essential Oil of Asafoetida on MCF7 Human Breast Cancer Cell Line and Female Wistar Rats

Seyyed Majid Bagheri1,2, Davood Javidmehr3, Mohammad Ghaffari1, Ehsan Ghoderti‑Shatori4


Cyclooxygenase‑2 Contributes to Mutant Epidermal Growth Factor Receptor Lung Tumorigenesis by Promoting an Immunosuppressive Environment

Mun Kyoung Kim1, Aidin Iravani2, Matthew K. Topham2,3


Potential role of CircMET as A Novel Diagnostic Biomarker of Papillary Thyroid Cancer

Yan Liu1,2,3,4#, Chen Cui1,2,3,4#, Jidong Liu1,2,3,4, Peng Lin1,2,3,4,Kai Liang1,2,3,4, Peng Su5, Xinguo Hou1,2,3,4, Chuan Wang1,2,3,4, Jinbo Liu1,2,3,4, Bo Chen6, Hong Lai1,2,3,4, Yujing Sun1,2,3,4* and Li Chen 1,2,3,4*


Cancer Diagnosis and Treatments by Porous Inorganic Nanocarriers

Jianfeng Xu1,2, Hanwen Zhang1,2, Xiaohui Song1,2, Yangong Zheng3, Qingning Li1,2,4*


Delayed (20 Years) post-surgical Esophageal Metastasis of Breast Cancer - A Case Report

Bowen Hu1#, Lingyu Du2#, Hongya Xie1, Jun Ma1, Yong Yang1*, Jie Tan2*


Subtyping of Undifferentiated Pleomorphic Sarcoma and Its Clinical Meaning

Umair Ali Khan Saddozai, Zhendong Lu, Fengling Wang, Muhammad Usman Akbar, Saadullah Khattak, Muhammad Badar, Nazeer Hussain Khan, Longxiang Xie, Yongqiang Li, Xinying Ji, Xiangqian Guo


Construction of Glioma Prognosis Model and Exploration of Related Regulatory Mechanism of Model Gene

Suxia Hu, Abdusemer Reyimu, Wubi Zhou, Xiang Wang, Ying Zheng, Xia Chen, Weiqiang Li, Jingjing Dai


ESRP2 as a Non-independent Potential Biomarker-Current Progress in Tumors

Yuting Chen, Yuzhen Rao, Zhiyu Zeng, Jiajie Luo, Chengkuan Zhao, Shuyao Zhang


Resection of Bladder Tumors at the Ureteral Orifice Using a Hook Plasma Electrode: A Case Report

Jun Li, Ziyong Wang, Qilin Wang


Structural Characterization and Bioactivity for Lycium Barbarum Polysaccharides

Jinghua Qi1,2,  Hangping Chen3,Huaqing Lin2,4,Hongyuan Chen1,2,5* and Wen Rui2,3,5,6*


The Role of IL-22 in the Prevention of Inflammatory Bowel Disease and Liver Injury

Xingli Qi1,2, Huaqing Lin2,3, Wen Rui2,3,4,5 and Hongyuan Chen1,2,3


RBM15 and YTHDF3 as Positive Prognostic Predictors in ESCC: A Bioinformatic Analysis Based on The Cancer Genome Atlas (TCGA)

Yulou Luo1, Lan Chen2, Ximing Qu3, Na Yi3, Jihua Ran4, Yan Chen3,5*


Mining and Analysis of Adverse Drug Reaction Signals Induced by Anaplastic Lymphoma Kinase-Tyrosine Kinase Inhibitors Based on the FAERS Database

Xiumin Zhang1,2#, Xinyue Lin1,3#, Siman Su1,3#, Wei He3, Yuying Huang4, Chengkuan Zhao3, Xiaoshan Chen3, Jialin Zhong3, Chong Liu3, Wang Chen3, Chengcheng Xu3, Ping Yang5, Man Zhang5, Yanli Lei5*, Shuyao Zhang1,3*


Advancements in Immunotherapy for Advanced Gastric Cancer

Min Jiang1#, Rui Zheng1#, Ling Shao1, Ning Yao2, Zhengmao Lu1*


Tumor Regression after COVID-19 Infection in Metastatic Adrenocortical Carcinoma Treated with Immune Checkpoint Blockade: A Case Report

Qiaoxin Lin1, Bin Liang1, Yangyang Li2, Ling Tian3*, Dianna Gu1*


Mining and Analysis of Adverse Events of BRAF Inhibitors Based on FDA Reporting System

Silan Peng1,2#, Danling Zheng1,3#, Yanli Lei4#, Wang Chen3, Chengkuan Zhao3, Xinyue Lin1, Xiaoshan Chen3, Wei He3, Li Li3, Qiuzhen Zhang5*, Shuyao Zhang1,3*


Malignant Phyllodes Tumor with Fever, Anemia, Hypoproteinemia: A Rare and Strange Case Report and Literature Review

Zhenghang Li1, Yuxian Wei1*


Construction of Cuproptosis-Related LncRNA Signature as a Prognostic Model Associated with Immune Microenvironment for Clear-Cell Renal Cell Carcinoma

Jiyao Yu1#, Shukai Zhang2#, Qingwen Ran3, Xuemei Li4,5,6*


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