Cellular Senescence and Anti-Cancer Therapy

Identification and validation of aging-related genes in heart failure based on multiple machine learning algorithms

Background

In the face of continued growth in the elderly population, the need to understand and combat age-related cardiac decline becomes even more urgent, requiring us to uncover new pathological and cardioprotective pathways.

Methods

We obtained the aging-related genes of heart failure through WGCNA and CellAge database. We elucidated the biological functions and signaling pathways involved in heart failure and aging through GO and KEGG enrichment analysis. We used three machine learning algorithms: LASSO, RF and SVM-RFE to further screen the aging-related genes of heart failure, and fitted and verified them through a variety of machine learning algorithms. We searched for drugs to treat age-related heart failure through the DSigDB database. Finally, We use CIBERSORT to complete immune infiltration analysis of aging samples.

Results

We obtained 57 up-regulated and 195 down-regulated aging-related genes in heart failure through WGCNA and CellAge databases. GO and KEGG enrichment analysis showed that aging-related genes are mainly involved in mechanisms such as Cellular senescence and Cell cycle. We further screened aging-related genes through machine learning and obtained 14 key genes. We verified the results on the test set and 2 external validation sets using 15 machine learning algorithm models and 207 combinations, and the highest accuracy was 0.911. Through screening of the DSigDB database, we believe that rimonabant and lovastatin have the potential to delay aging and protect the heart. The results of immune infiltration analysis showed that there were significant differences between Macrophages M2 and T cells CD8 in aging myocardium.

Conclusion

We identified aging signature genes and potential therapeutic drugs for heart failure through bioinformatics and multiple machine learning algorithms, providing new ideas for studying the mechanism and treatment of age-related cardiac decline.

Synthesis of New Chromene Derivatives Targeting Triple-Negative Breast Cancer Cells

Breast cancer continues to be the leading cause of cancer-related deaths among women worldwide. The most aggressive type of breast cancer is triple-negative breast cancer (TNBC). Indeed, not only does TNBC not respond well to several chemotherapeutic agents, but it also frequently develops resistance to various anti-cancer drugs, including taxane mitotic inhibitors. This necessitates the search for newer, more efficacious drugs. In this study, we synthesized two novel chromene derivatives (C1 and C2) and tested their efficacy against a battery of luminal type A and TNBC cell lines. Our results show that C1 and C2 significantly and specifically inhibited TNBC cell viability but had no effect on the luminal A cell type. In addition, these novel compounds induced mitotic arrest, cell multinucleation leading to senescence, and apoptotic cell death through the activation of the extrinsic pathway. We also showed that the underlying mechanisms for these actions of C1 and C2 involved inhibition of microtubule polymerization and disruption of the F-actin cytoskeleton. Furthermore, both compounds significantly attenuated migration of TNBC cells and inhibited angiogenesis in vitro. Finally, we performed an in silico analysis, which revealed that these novel variants bind to the colchicine binding site in β-tubulin. Taken together, our data highlight the potential chemotherapeutic properties of two novel chromene compounds against TNBC.

Combination therapy of cisplatin and resveratrol to induce cellular aging in gastric cancer cells: Focusing on oxidative stress, and cell cycle arrest

Background: As a medical dilemma, gastric cancer will have 7.3 million new cases in 2040. Despite the disease's high economic and global burden, conventional chemotherapy regimens containing cisplatin have insufficient effectiveness and act non-specifically, leading to several adverse drug reactions To address these issues, the biological efficacy of the cisplatin-resveratrol combination was tested. Methods: To find IC50, gastric adenocarcinoma cells (AGS) were exposed to different concentrations of resveratrol and cisplatin. Anti-cancer and anti-metastatic effects of 100 M resveratrol with concentrations of cisplatin (25, 50, and 100 g/ml) were studied by assessing ß-galactosidase and telomerase activities, senescence and migration gene expression, reactive oxygen species (ROS) level, and cell cycle arrest. Results: Co-administration of cisplatin and resveratrol increased ß-galactosidase activity, ROS level as a key marker of oxidative stress, p53, p38, p16, p21, and MMP-2 gene expression, and induced G0/G1 cell cycle arrest. Additionally, telomerase activity, pro-inflammatory gene expression, and cell invasion were suppressed. The best results were achieved with 100 g/ml cisplatin co-administered with resveratrol. Conclusion: The current study proved the synergistic effect of the cisplatin-resveratrol combination on suppressing metastasis and inducing apoptosis and cell senescence through targeting P38/P53 and P16/P21 pathways. Such promising results warrant translation to animal models and the clinic. This may lead to cost-effective, available, and accessible treatment regimens with targeted action and the fewest ADRs.

A novel prognostic model based on cellular senescence-related gene signature for bladder cancer

Background

Cellular senescence plays crucial role in the progression of tumors. However, the expression patterns and clinical significance of cellular senescence-related genes in bladder cancer (BCa) are still not clearly clarified. This study aimed to establish a prognosis model based on senescence-related genes in BCa.

Methods

The transcriptional profile data and clinical information of BCa were downloaded from TCGA and GEO databases. The least absolute shrinkage and selection operator (LASSO), univariate and multivariate Cox regression analyses were performed to develop a prognostic model in the TCGA cohort. The GSE13507 cohort were used for validation. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) were performed to investigate underlying mechanisms.

Results

A six-gene signature (CBX7, EPHA3, STK40, TGFB1I1, SREBF1, MYC) was constructed in the TCGA databases. Patients were classified into high risk and low risk group in terms of the median risk score. Survival analysis revealed that patients in the higher risk group presented significantly worse prognosis. Receiver operating characteristic (ROC) curve analysis verified the moderate predictive power of the risk model based on the six senescence-related genes signature. Further analysis indicated that the clinicopathological features analysis were significantly different between the two risk groups. As expected, the signature presented prognostic significance in the GSE13507 cohort. Functional analysis indicated that immune-related pathways activity, immune cell infiltration and immune-related function were different between two risk groups. In addition, risk score were positively correlated with multiple immunotherapy biomarkers.

Conclusion

Our study revealed that a novel model based on senescence-related genes could serve as a reliable predictor of survival for patients with BCa.

Erdafitinib Inhibits Tumorigenesis of Human Lung Adenocarcinoma A549 by Inducing S-Phase Cell-Cycle Arrest as a CDK2 Inhibitor

Lung adenocarcinoma (LADC) is the most prevalent lung cancer sub-type, and targeted therapy developed in recent years has made progress in its treatment. Erdafitinib, a potent and selective pan-FGFR tyrosine kinase inhibitor, has been confirmed to be effective for the treatment of LADC; however, the molecular mechanism responsible for this effect is unclear. The in vitro study showed that erdafitinib exhibited an outstanding anti-cancer activity in human LADC cell line A549 by inducing S-phase cell-cycle arrest and cell apoptosis. The mechanistic study based on the transcriptomic data revealed that erdafitinib exerted its anti-cancer effect by affecting the cell cycle-related pathway, and CDK2 was the regulatory target of this drug. In addition, CDK2 overexpression significantly attenuated the anti-cancer effect of erdafitinib by affecting the transcriptional activity and expression of E2F1, as well as the expression of CDK1. The in vivo study showed that erdafitinib presented an obvious anti-cancer effect in the A549 xenograft mice model, which was accompanied by the reduced expression of CDK2. Thus, this study demonstrates the anti-cancer effect of erdafitinib against LADC for the first time based on in vitro and in vivo models, whose activity is achieved by targeting CDK2 and regulating downstream E2F1-CDK1 signaling. This study may be helpful for expanding the clinical application of erdafitinib in treating LADC.

Identification of cell senescence molecular subtypes in prediction of the prognosis and immunotherapy of hepatitis B virus-related hepatocellular carcinoma

Hepatitis B virus (HBV)-infected hepatocellular carcinoma (HCC) has a high incidence and fatality rate worldwide, being among the most prevalent cancers. The growing body of data indicating cellular senescence (CS) to be a critical factor in hepatocarcinogenesis. The predictive value of CS in HBV-related HCC and its role in the immune microenvironment are unknown. To determine the cellular senescence profile of HBV-related HCC and its role in shaping the immune microenvironment, this study employed a rigorous evaluation of multiple datasets encompassing 793 HBV-related HCC samples. Two novel distinct CS subtypes were first identified by nonnegative matrix factorization, and we found that the senescence-activated subgroup had the worst prognosis and correlated with cancer progression. C1 and C2 were identified as the senescence-suppressed and senescence-activated subgroups. The immune microenvironment indicated that C2 exhibited a relatively low immune status, higher tumor purity, and lower immune scores and estimated scores, while the C1 subgroup possessed a better prognosis. The CS score signature based on five genes (CENPA, EZH2, G6PD, HDAC1, and PRPF19) was established using univariate Cox regression and the lasso method. ICGC-LIRI and GSE14520 cohorts were used to validate the reliability of the CS scoring system. In addition, we examined the association between the risk score and hallmark pathways through gene set variation analysis and gene set enrichment analysis. The results revealed a high CS score to be associated with the activation of cell senescence-related pathways. The CS score and other clinical features were combined to generate a CS dynamic nomogram with a better predictive capacity for OS at 1, 2, and 3 years than other clinical parameters. Our study demonstrated that cellular senescence patterns play a non-negligible role in shaping the characteristics of the immune microenvironment and profoundly affecting tumor prognosis. The results of this study will help predict patient prognosis more accurately and may assist in development of personalized immunotherapy for HBV-related HCC patients.

Construction of Molecular Subtype and Prognosis Prediction Model of Osteosarcoma Based on Aging-Related Genes

Background

Osteosarcoma (OS) is a rare form of malignant bone cancer that is usually detected in young adults and adolescents. This disease shows a poor prognosis owing to its metastatic status and resistance to chemotherapy. Hence, it is necessary to design a risk model that can successfully forecast the OS prognosis in patients.

Methods

The researchers retrieved the RNA sequencing data and follow-up clinical data related to OS patients from the TARGET and GEO databases, respectively. The coxph function in R software was used for carrying out the Univariate Cox regression analysis for deriving the aging-based genes related sto the OS prognosis. The researchers conducted consistency clustering using the ConcensusClusterPlus R package. The R software package ESTIMATE, MCPcounter, and GSVA packages were used for assessing the immune scores of various subtypes using the ssGSEA technique, respectively. The Univariate Cox and Lasso regression analyses were used for screening and developing a risk model. The ROC curves were constructed, using the pROC package. The performance of their developed risk model and designed survival curve was conducted, with the help of the Survminer package.

Results

The OS patients were classified into 2 categories, as per the aging-related genes. The results revealed that the Cluster 1 patients showed a better prognosis than the Cluster 2 patients. Both clusters showed different immune microenvironments. Additional screening of the prognosis-associated genes revealed the presence of 5 genes, i.e., ERCC4, GPX4, EPS8, TERT, and STAT5A, and these data were used for developing the risk model. This risk model categorized the training set samples into the high- and low-risk groups. The patients classified into the high-risk group showed a poor OS prognosis compared to the low-risk patients. The researchers verified the reliability and robustness of the designed 5-gene signature using the internal and external datasets. This risk model was able to effectively predict the prognosis even in the samples having differing clinical features. Compared with other models, the 5- gene model performs better in predicting the risk of osteosarcoma.

Conclusion

The 5-gene signature developed by the researchers in this study could be effectively used for forecasting the OS prognosis in patients.

A protocol for rapid construction of senescent cells

Aging may be the largest factor for a variety of chronic diseases that influence survival, independence, and wellbeing. Evidence suggests that aging could be thought of as the modifiable risk factor to delay or alleviate age-related conditions as a group by regulating essential aging mechanisms. One such mechanism is cellular senescence, which is a special form of most cells that are present as permanent cell cycle arrest, apoptosis resistance, expression of anti-proliferative molecules, acquisition of pro-inflammatory, senescence-associated secretory phenotype (SASP), and others. Most cells cultured in vitro or in vivo may undergo cellular senescence after accruing a set number of cell divisions or provoked by excessive endogenous and exogenous stress or damage. Senescent cells occur throughout life and play a vital role in various physiological and pathological processes such as embryogenesis, wound healing, host immunity, and tumor suppression. In contrast to the beneficial senescent processes, the accumulation of senescent also has deleterious effects. These non-proliferating cells lead to the decrease of regenerative potential or functions of tissues, inflammation, and other aging-associated diseases because of the change of tissue microenvironment with the acquisition of SASP. While it is understood that age-related diseases occur at the cellular level from the cellular senescence, the mechanisms of cellular senescence in age-related disease progression remain largely unknown. Simplified and rapid models such as in vitro models of the cellular senescence are critically needed to deconvolute mechanisms of age-related diseases. Here, we obtained replicative senescent L02 hepatocytes by culturing the cells for 20 weeks. Then, the conditioned medium containing supernatant from replicative senescent L02 hepatocytes was used to induce cellular senescence, which could rapidly induce hepatocytes into senescence. In addition, different methods were used to validate senescence, including senescence-associated β-galactosidase (SA-β-gal), the rate of DNA synthesis using 5-ethynyl-2′-deoxyuridine (EdU) incorporation assay, and senescence-related proteins. At last, we provide example results and discuss further applications of the protocol.

Metallothionein-3 promotes cisplatin chemoresistance remodelling in neuroblastoma

Metallothionein-3 has poorly characterized functions in neuroblastoma. Cisplatin-based chemotherapy is a major regimen to treat neuroblastoma, but its clinical efficacy is limited by chemoresistance. We investigated the impact of human metallothionein-3 (hMT3) up-regulation in neuroblastoma cells and the mechanisms underlying the cisplatin-resistance. We confirmed the cisplatin-metallothionein complex formation using mass spectrometry. Overexpression of hMT3 decreased the sensitivity of neuroblastoma UKF-NB-4 cells to cisplatin. We report, for the first time, cisplatin-sensitive human UKF-NB-4 cells remodelled into cisplatin-resistant cells via high and constitutive hMT3 expression in an in vivo model using chick chorioallantoic membrane assay. Comparative proteomic analysis demonstrated that several biological pathways related to apoptosis, transport, proteasome, and cellular stress were involved in cisplatin-resistance in hMT3 overexpressing UKF-NB-4 cells. Overall, our data confirmed that up-regulation of hMT3 positively correlated with increased cisplatin-chemoresistance in neuroblastoma, and a high level of hMT3 could be one of the causes of frequent tumour relapses.

Fibronectin in Cancer: Friend or Foe

The role of fibronectin (FN) in tumorigenesis and malignant progression has been highly controversial. Cancerous FN plays a tumor-suppressive role, whereas it is pro-metastatic and associated with poor prognosis. Interestingly, FN matrix deposited in the tumor microenvironments (TMEs) promotes tumor progression but is paradoxically related to a better prognosis. Here, we justify how FN impacts tumor transformation and subsequently metastatic progression. Next, we try to reconcile and rationalize the seemingly conflicting roles of FN in cancer and TMEs. Finally, we propose future perspectives for potential FN-based therapeutic strategies.