To analyze and identify the core genes related to the expression and prognosis of lung cancer including lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) by bioinformatics technology, with the aim of providing a reference for clinical treatment. Five sets of gene chips, GSE7670, GSE151102, GSE33532, GSE43458, and GSE19804, were obtained from the Gene Expression Omnibus (GEO) database. After using GEO2R to analyze the differentially expressed genes (DEGs) between lung cancer and normal tissues online, the common DEGs of the five sets of chips were obtained using a Venn online tool and imported into the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database for Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The protein-protein interaction (PPI) network was constructed by STRING online software for further study, and the core genes were determined by Cytoscape software and KEGG pathway enrichment analysis. The clustering heat map was drawn by Excel software to verify its accuracy. In addition, we used the University of Alabama at Birmingham Cancer (UALCAN) website to analyze the expression of core genes in P53 mutation status, confirmed the expression of crucial core genes in lung cancer tissues with Gene Expression Profiling Interactive Analysis (GEPIA) and GEPIA2 online software, and evaluated their prognostic value in lung cancer patients with the Kaplan-Meier online plotter tool. CHEK1, CCNB1, CCNB2, and CDK1 were selected. The expression levels of these four genes in lung cancer tissues were significantly higher than those in normal tissues. Their increased expression was negatively correlated with lung cancer patients (including LUAD and LUSC) prognosis and survival rate. CHEK1, CCNB1, CCNB2, and CDK1 are the critical core genes of lung cancer and are highly expressed in lung cancer. They are negatively correlated with the prognosis of lung cancer patients (including LUAD and LUSC) and closely related to the formation and prediction of lung cancer. They are valuable predictors and may be predictive biomarkers of lung cancer.
FOXD2-AS1 is known to promote the development of several cancers. However, its role in pancreatic adenocarcinoma (PAAD) is unclear.Expression of FOXD2-AS1 and miR-30a-3p in PAAD patients was analyzed with RT-qPCR. A follow-up study was performed to analyze the prognostic value of FOXD2-AS1 for PAAD. Overexpression assays were performed to analyze the crosstalk between FOXD2-AS1 and miR-30a-3p. Cell invasion and migration were analyzed by transwell assays.Analysis of the TCGA dataset revealed that FOXD2-AS1 was upregulated in PAAD tissues compared to the non-cancer tissues (1.89 vs. 0.2 TPM), indicating potential involvement of FOXD2-AS1 in PAAD. Our own data also showed FOXD2-AS1 was overexpressed in PAAD. Moreover, high FOXD2-AS1 levels predicted poor survival. It is predicted that miR-30a-3p can bind FOXD2-AS1, while their overexpression did not affect each other's expression. Correlation analysis revealed a significant correlation between FOXD2-AS1 and COX-2. In addition, FOXD2-AS1 overexpression increased COX-2 level, while miR-30a-3p played an opposite role. FOXD2-AS1 and COX-2 overexpression increased PAAD cell invasion and migration. MiR-30a-3p played an opposite role and inhibited the effects of FOXD2-AS1 and COX-2 overexpression.FOXD2-AS1 may promote PAAD cell invasion and migration by sponging miR-30a-3p to upregulate COX-2.
Underwater image enhancement (UIE) is a highly challenging task due to the complexity of underwater environment and the diversity of underwater image degradation. Due to the application of deep learning, current UIE methods have made significant progress. Most of the existing deep learning-based UIE methods follow a single-stage network which cannot effectively address the diverse degradations simultaneously. In this paper, we propose to address this issue by designing a two-stage deep learning framework and taking advantage of cascaded contrastive learning to guide the network training of each stage. The proposed method is called CCL-Net in short. Specifically, the proposed CCL-Net involves two cascaded stages, i.e., a color correction stage tailored to the color deviation issue and a haze removal stage tailored to improve the visibility and contrast of underwater images. To guarantee the underwater image can be progressively enhanced, we also apply contrastive loss as an additional constraint to guide the training of each stage. In the first stage, the raw underwater images are used as negative samples for building the first contrastive loss, ensuring the enhanced results of the first color correction stage are better than the original inputs. While in the second stage, the enhanced results rather than the raw underwater images of the first color correction stage are used as the negative samples for building the second contrastive loss, thus ensuring the final enhanced results of the second haze removal stage are better than the intermediate color corrected results. Extensive experiments on multiple benchmark datasets demonstrate that our CCL-Net can achieve superior performance compared to many state-of-the-art methods. The source code of CCL-Net will be released at https://github.com/lewis081/CCL-Net.
Ru(II)-polypyridyl complexes are of increasing interest in photodynamic therapy (PDT) due to their easily tunable photophysical and photochemical properties. However, short-wavelength absorption of Ru(II)-polypyridyl complexes has limited their penetration depth in PDT. Herein, the series of Ru(II)-polypyridyl complexes 1–4 was designed by replacing one bipyridine in [Ru(bpy)3]Cl2 with Schiff bases (iminopyridine or iminoquinoline analogues) to achieve red-shifted absorption of Ru(II)-polypyridyl photosensitizers. To further shift the absorption to longer wavelength and improve the photobiological activity of Ru(II)-polypyridyl complexes, the three tris-heteroleptic Ru(II) complexes 5–7 with benzo[i]dipyrido[3,2-a:2′,3′-c]phenazine (dppn) as a ligand were designed to achieve long-lived intraligand (3IL) excited states. Cytotoxicity data against A549 and HepG2 cells revealed that complex 7 showed extraordinarily high cytotoxicity under 650 nm irradiation, resulting in IC50 values of 56 and 63 nM with exceptionally large phototoxicity index (PI) values of 763 and 613, respectively. Thus, the resulting complex 7 with considerable red-light photocytotoxicity and high PI values shows a promising potential for therapeutic applications, which represents a new scaffold of Ru(II)-polypyridyl photosensitizers for PDT in the "therapeutic window". This study delivers a rational strategy for the design of tris-heteroleptic Ru(II) complexes as promising photosensitizers for cancer therapy.
Abstract Stomach cancer involves hypoxia-specific microenvironments. Stoichiogenomics explores environmental resource limitation on biological macromolecules in terms of element usages. However, the patterns of oxygen usage by proteins and the ways that proteins adapt to a cancer hypoxia microenvironment are still unknown. Here we compared the oxygen and carbon contents ([C]) between proteomes of stomach cancer (hypoxia) and two stomach glandular cells (normal). Key proteins, genome locations, pathways, and functional dissection associated with stomach cancer were also studied. An association of oxygen content ([O]) and protein expression level was revealed in stomach cancer and stomach glandular cells. For differentially expressed proteins (DEPs), oxygen contents in the up regulated proteins were3.2%higherthan that in the down regulated proteins in stomach cancer. A total of 1,062 DEPs were identified; interestingly none of these proteins were coded on Y chromosome. The up regulated proteins were significantly enriched in pathways including regulation of actin cytoskeleton, cardiac muscle contraction, pathway of progesterone-mediated oocyte maturation, etc. Functional dissection of the up regulated proteins with high oxygen contents showed that most of them were cytoskeleton, cytoskeleton associated proteins, cyclins and signaling proteins in cell cycle progression. Element signature of resource limitation could not be detected in stomach cancer for oxygen, just as what happened in plants and microbes. Unsaved use of oxygen by the highly expressed proteins was adapted to the rapid growth and fast division of the stomach cancer cells. In addition, oxygen usage bias, key proteins and pathways identified in this paper laid a foundation for application of stoichiogenomics in precision medicine.
Abstract Prostate cancer (PCa) is the most diagnosed worldwide. PCa development and progression require androgen receptor (AR) signaling, which stimulates its downstream gene expressions and cancer progression. While second-generation anti-androgen drugs plus androgen deprivation therapy (ADT) remains the first-line treatment for advanced prostate cancer patients, around one-third of patients will relapse in a short period. Advanced prostate cancer results in more mortalities than primary PCa patients. Evidence shows that the recurrence is caused by AR overexpression, AR variants, AR mutations, and signaling crosstalk. Thus, it is urgently needed to discover a novel therapeutic strategy for treating advanced prostate cancer. The heat shock protein family (HSP), including HSP90 and HSP70, play important roles in refolding aggregated protein for cancer cell proteomic equilibrium. HSP is induced primarily by heat shock factor (HSF1). As AR’s chaperone protein, HSP70 and HSP90 increase AR transcription activity. Inhibiting HSP70 and HSP90 promotes STUB1, an E3 ligase, binding to AR and AR - V7, and ubiquitination. Artesunate (ART) is a semi-synthetic ingredient from Artemisia annua and is the most common treatment for malaria throughout the world. It was approved for medical use by the FDA (Food and Drug Administration) (Food and Drug Administration). Recently ART has been unveiled for its anticancer properties. However, the efficacy of ART treatment in advanced prostate cancer and the direct target of ART have not been investigated yet. Herein, we have examined the efficacy of combining Enzalutamide (Enza) and ART in advanced prostate cancer cell lines. We also performed unbiased bioinformatics analysis using RNA seq results in enzalutamide-resistant cell line C4-2R cells and 22RV1 cells to investigate the cell response toward ART treatment. We identified ART could downregulate of AR signaling pathway. Moreover, we determined that ART treatment induces AR degradation in proteasome dependent manner. Interestingly, we found HSP70 and HSP90 are also decreased in RNA seq results. Taking these together suggests that ART may target HSF1 directly. Our results suggest ART induced AR degradation could be a promising clinical strategy for advanced prostate cancer. Citation Format: Xinyi Wang, Fengyi Mao, Jinghui Liu, Yifan Kong, Dang he, Chi Wang, Zhiguo Li, Xiaoqi Liu. Artesunate increases enzalutamide efficacy in advanced prostate cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5508.
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