Cuproptosis was a copper-dependent and unique kind of cell death that was separate from existing other forms of cell death. The last decade has witnessed a considerable increase in investigations of programmed cell death, and whether copper induced cell death was an independent form of cell death has long been argued until mechanism of cuproptosis has been revealed. After that, increasing number of researchers attempted to identify the relationship between cuproptosis and the process of cancer. Thus, in this review, we systematically detailed the systemic and cellular metabolic processes of copper and the copper-related tumor signaling pathways. Moreover, we not only focus on the discovery process of cuproptosis and its mechanism, but also outline the association between cuproptosis and cancers. Finally, we further highlight the possible therapeutic direction of employing copper ion ionophores with cuproptosis-inducing functions in combination with small molecule drugs for targeted therapy to treat specific cancers. 

/pdf/cuproptosis-mechanisms-and-links-with-cancers-18vfyq1k.pdf

Cuproptosis: mechanisms and links with cancers

Glucose-6-phosphate dehydrogenase (G6PD) is the only rate-limiting enzyme in the pentose phosphate pathway (PPP). Rapidly proliferating cells require metabolites from PPP to synthesize ribonucleotides and maintain intracellular redox homeostasis. G6PD expression can be abnormally elevated in a variety of cancers. In addition, G6PD may act as a regulator of viral replication and vascular smooth muscle function. Therefore, G6PD-mediated activation of PPP may promote tumor and non-neoplastic disease progression. Recently, studies have identified post-translational modifications (PTMs) as an important mechanism for regulating G6PD function. Here, we provide a comprehensive review of various PTMs (e.g., phosphorylation, acetylation, glycosylation, ubiquitination, and glutarylation), which are identified in the regulation of G6PD structure, expression and enzymatic activity. In addition, we review signaling pathways that regulate G6PD and evaluate the role of oncogenic signals that lead to the reprogramming of PPP in tumor and non-neoplastic diseases as well as summarize the inhibitors that target G6PD.

/pdf/recent-findings-in-the-regulation-of-g6pd-and-its-role-in-h2hzbzcd.pdf

Recent findings in the regulation of G6PD and its role in diseases

Eph receptors and ephrins in cancer progression.

Accumulating studies have suggested the airway microbiota in lung cancer patients is significantly different from that of healthy controls. However, little is known about the relationship between airway microbiota and important clinical parameters of lung cancer. In this study, we aimed to explore the association between sputum microbiota and lung cancer stage, lymph node metastasis, intrathoracic metastasis, and epidermal growth factor receptor (EGFR) gene mutation.

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/1759-7714.14340

The airway microbiota of non‐small cell lung cancer patients and its relationship to tumor stage and EGFR gene mutation

The current diagnosis and treatment of sarcoma continue to show limited timeliness and efficacy. In order to enable the early detection and management of sarcoma, increasing attentions have been given to the tumor microenvironment (TME). TME is a dynamic network composed of multiple cells, extracellular matrix, vasculature, and exosomes. Exosomes are nano-sized extracellular vesicles derived from various cells in the TME. The major function of exosomes is to promote cancer progress and metastasis through mediating bidirectional cellular communications between sarcoma cells and TME cells. Due to the content specificity, cell tropism, and bioavailability, exosomes have been regarded as promising diagnostic and prognostic biomarkers, and therapeutic vehicles for sarcoma. This review summarizes recent studies on the roles of exosomes in TME of sarcoma, and explores the emerging clinical applications. 

/pdf/exosomes-in-the-tumor-microenvironment-of-sarcoma-from-27190ck3.pdf

Exosomes in the tumor microenvironment of sarcoma: from biological functions to clinical applications

Chemoresistance is the crux of clinical treatment failure of small‐cell lung cancer (SCLC). Cancer stem cells play a critical role in therapeutic resistance of malignant tumors. Studies have shown that the role of erythropoietin‐producing hepatocellular A2 (EphA2) in tumors is complex. This study aimed to test the hypothesis that ligand‐independent activation of EphA2 modulates chemoresistance by enhancing stemness in SCLC. We verified that EphA2 was activated in chemoresistance sublines in a ligand‐independent manner rather than a ligand‐dependent manner. Ligand‐independent EphA2 enhanced the expression of stemness‐associated biomarkers (CD44, Myc, and SOX2), accelerated epithelial–mesenchymal transition (EMT) and reinforced self‐renewal to drive the chemoresistance of SCLC, while the P817H mutant EphA2 neutralized intrinsic function. Co‐immunoprecipitation (co‐IP) and GST‐pull down experiments were conducted to verify that EphA2 directly interacted with PRMT1. Moreover, EphA2 increased the expression and activity of PRMT1. Whereafter, PRMT1 interacted with and methylated SOX2 to induce stemness and chemoresistance in SCLC. Pharmacological inhibition of EphA2 showed a synergistic anti‐tumor effect with chemotherapy in preclinical models, including patient‐derived xenograft (PDX) models. These findings highlight, for the first time, that the EphA2/PRMT1/SOX2 pathway induces chemoresistance in SCLC by promoting stemness. EphA2 is a potential therapeutic target in SCLC treatment.

Ligand‐independent EphA2 contributes to chemoresistance in small‐cell lung cancer by enhancing PRMT1‐mediated SOX2 methylation

Osteosarcoma (OS) is rare cancer with bimodal age distribution with peaks observed in children and young adults. Typically, OS is treated with pre-surgery neoadjuvant therapy, surgical excision, and post-surgery chemotherapy. However, the efficacy of treatment on disease prognosis and objective response is not currently optimal, often resulting in drug resistance; in turn, highlighting the need to understand mechanisms driving resistance to therapy in OS patients. Using Doxycycline (Dox)-sensitive and resistant variants of OS cells lines KHOS and U2OS, we found that the resistant variants KHOS-DR and U2OS-DR have significantly higher in vitro proliferation. Treating the Dox-sensitive KHOS/U2OS cells with exosomes isolated from KHOS-DR/U2OS-DR made them resistant to treatment with Dox in vitro and in vivo and enhanced tumor growth and progression, while decreasing overall survival. Expression of the long non-coding RNA (lncRNA) ANCR was significantly higher in the KHOS-DR and U2OS-DR variants. SiRNA-mediated knockdown of ANCR decreased in vitro proliferation, while increasing sensitivity to Dox treatment in the KHOS-DR/U2OS-DR cells. Expression of the exosomal lncRNA ANCR was critical for drug resistance and OS tumor progression in xenografts and was correlated to resistance to Adriamycin and overall survival is patients with OS. These results establish lncRNA ANCR as a critical mediator of resistance to therapy in OS patients, highlighting it as a potential therapeutic target in OS patients.

https://www.frontiersin.org/articles/10.3389/fonc.2021.735254/pdf

Exosomal Long Non-Coding RNA ANCR Mediates Drug Resistance in Osteosarcoma

Background Lung cancer is the most morbid and fatal cancer in the world, and nearly 85% of lung cancer is non-small cell lung cancer (NSCLC). Besides traditional chemotherapies, molecular targeted therapies and immunotherapies are increasing rapidly, but the treatment is still unsatisfactory. The study is to identify a new diagnostic and prognostic biomarker. Methods Data including mRNA expression and clinical information of lung adenocarcinoma (LUAD) patients were downloaded from The Cancer Genome Atlas (TCGA) database. Receiver operating characteristic (ROC) curve was constructed to assess the diagnostic value of syntrophin-γ2 (SNTG2) expression and Kaplan–Meier (KM) survival curves were used to compare the survival disparities. The protein–protein interaction (PPI) network was analysed by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the connections between SNTG2 and immune cell infiltration were found with Tumor Immunoassay Resource (TIMER). Genetic mutation in SNTG2 and its association with overall survival (OS) were evaluated by cBioPortal. The relationship between SNTG2 and methylation and its association with overall survival were evaluated by MethSurv. Chi square and Mann–Whitney tests were used for statistical analyses. Xiantao Academic Online Website was used for online analysis. Results Our results revealed that SNTG2 mRNA expression was lower in LUAD tissues than in both adjacent and non-adjacent normal tissues and low SNTG2 mRNA expression was verified to be correlated with histological grade, clinical stage, first therapy outcome and poor overall survival of LUAD. Next, ROC curve revealed diagnostic and prognostic value of SNTG2 for LUAD patients. Moreover, SNTG2 presented correlation with immune cell infiltration and immune checkpoints. Then, we revealed CC chemokine ligand 14 (CCL14), a co-expression gene with SNTG2, which has consistent influence with SNTG2. Furthermore, hypomethylation was found to be associated with high SNTG2 expression. Conclusion We revealed a potential diagnostic and prognostic indicator in LUAD and analyzed its influence on immunotherapy.

Bioinformatic Analysis of Prognostic Value of SNTG2 with Immune Implications in Lung Adenocarcinoma

Background Small cell lung cancer (SCLC), the most malignant of all the lung cancer subtypes, is characterized by drug resistance. This study sought to explore the key genes and pathways associated with the chemoresistance of SCLC. Methods The drug sensitivity of chemosensitive and chemoresistance SCLC cell lines was measured by Cell Counting Kit-8 assays. The total RNA from chemosensitive cell line H69 and chemoresistance cell line H69AR cells was extracted and subjected to messenger RNA (mRNA) and long non-coding RNA (lncRNA) microarray analyses. The differentially expressed genes (DEGs) and the differentially expressed lncRNAs (DELs) were screened out with a threshold of a |log fold change | ≥1 and an adjusted P value <0.05. A protein-protein interaction network was constructed, and hub genes were screened out. A lncRNA-mRNA co-expression network was also constructed. Gene Ontology and Kyoto Encyclopedia of Genes, Genomes enrichment analyses and Cis-regulatory element analyses were conducted on the DEGs and the top 10 upregulated DEL-co-expressed DEGs. The expression of the key genes was further analyzed in the GSE149507 data set and validated in H69/H69AR and H446/H446DDP cells by quantitative polymerase chain reaction assays. Results The microarray results showed that a total of 609 mRNAs and 394 lncRNAs were differentially expressed in the chemoresistant SCLC cells. The mammalian target of rapamycin (mTOR) signaling pathway was enriched among the DEGs, the top 10 upregulated DEL-co-expressed DEGs, and the NCRNA00173-co-expressed DEGs, which included IGF1, INS, WNT6, WNT11, WNT2B, and SESN2. IGF1, WNT2B, and SESN2 were downregulated, and WNT11 was upregulated in the SCLC tumor tissues in the GSE149507 data set. Further, IGF1, WNT6, WNT11, and WNT2B were lowlier expressed and SESN2 and NCRNA00173 were more highly expressed in the chemoresistant cells than sensitive cells. Conclusions The top 10 upregulated DELs containing NCRNA00173 may be involved in the regulation of drug resistance in SCLC. These DELs may regulate the genes related to the mTOR signaling pathway. These genes may also be biomarkers and potential targets for the treatment of SCLC.

/pdf/identification-of-key-genes-and-pathway-related-to-4spxg2gh.pdf

Identification of key genes and pathway related to chemoresistance of small cell lung cancer through an integrative bioinformatics analysis

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Yang Wen

Author Tools

Chat about Author