The cyclin-dependent kinase inhibitor AT7519 augments cisplatin's efficacy in ovarian cancer via multiple oncogenic signaling pathways

The pathophysiology of the cell cycle in cancer and treatment strategies using various cell cycle checkpoint inhibitors

The cell cycle is the series of events that occur in a cell leading to its division and duplication. It can be divided into two main stages: interphase and mitosis. Interphase is the longest stage of the cell cycle and can be further divided into three phases: G1, S, and G2. During G1, the cell grows and prepares for DNA synthesis. In the S phase, DNA synthesis occurs, leading to the replication of the genetic material. In G2, the cell continues to grow and prepares for mitosis. After mitosis, the cell enters the final stage of the cell cycle, called cytokinesis, during which the cytoplasm is divided, resulting in two separate daughter cells. The cell cycle then begins again with interphase. Cell cycle dysregulation is a hallmark of cancer, and it can have several consequences that contribute to the development and progression of cancer. Cyclin inhibitors and checkpoint activators have shown promise in the treatment of cancer, particularly in combination with other therapies.

The CDK inhibitor AT7519 inhibits human glioblastoma cell growth by inducing apoptosis, pyroptosis and cell cycle arrest

Glioblastoma multiforme (GBM) is the most lethal primary brain tumor with a poor median survival of less than 15 months. However, clinical strategies and effective therapies are limited. Here, we found that the second-generation small molecule multi-CDK inhibitor AT7519 is a potential drug for GBM treatment according to high-throughput screening via the Approved Drug Library and Clinical Compound Library (2718 compounds). We found that AT7519 significantly inhibited the cell viability and proliferation of U87MG, U251, and patient-derived primary GBM cells in a dose-dependent manner. Furthermore, AT7519 also inhibited the phosphorylation of CDK1/2 and arrested the cell cycle at the G1-S and G2-M phases. More importantly, AT7519 induced intrinsic apoptosis and pyroptosis via caspase-3-mediated cleavage of gasdermin E (GSDME). In the glioblastoma intracranial and subcutaneous xenograft assays, tumor volume was significantly reduced after treatment with AT7519. In summary, AT7519 induces cell death through multiple pathways and inhibits glioblastoma growth, indicating that AT7519 is a potential chemical available for GBM treatment.

A pan-cancer analysis of ABI3BP: a potential biomarker for prognosis and immunoinfiltration

Objective

ABI Family Member 3 Binding Protein (ABI3BP) is an extracellular matrix protein that affects the carcinogenesis of lung and esophageal cancer. However, the relevance of ABI3BP in different forms of cancer is uncertain.

Methods

ABI3BP expression was interpreted using the Cancer Genome Atlas (TCGA) database, the Genotype Tissue Expression Atlas (GTEx) database, the Human Protein Atlas (HPA) database, the Cancer Cell Line Encyclopedia (CCLE) database, and immunohistochemistry. The R programming language was used to analyze the association between ABI3BP expression and patient prognosis and evaluate the relationship between ABI3BP and the immune characteristics of tumors. Using the GDSC and CTRP databases, a drug sensitivity analysis of ABI3BP was conducted.

Results

ABI3BP mRNA expression was shown by differential analysis to be down-regulated in 16 tumor types relative to normal tissues, corresponding with its protein expression level as determined by immunohistochemistry. Abnormal expression of ABI3BP accurately predicts the prognosis of patients with renal chromophobe carcinoma (KICH), mesothelioma (MESO), and pancreatic adenocarcinoma (PAAD). Meanwhile, aberrant expression of ABI3BP was associated with immune checkpoints, TMB, MSI, tumor purity, HRD, LOH, and drug sensitivity. A correlation between ABI3BP expression and the amount of infiltration of several immune-related cells in pan-cancer was determined by Immune Score, Stromal Score, and Estimated Score.

Conclusion

Our results show that ABI3BP might be employed as a molecular biomarker to predict prognosis, treatment susceptibility, and immunological response in patients with pan-cancer.

Comprehensive analysis of the glutathione S-transferase Mu (GSTM) gene family in ovarian cancer identifies prognostic and expression significance

Background

Ovarian cancer (OC) is one of the most common types of gynecologic tumor over the world. The Glutathione S-transferase Mu (GSTM) has five members, including GSTM1-5. These GSTMs is involved in cell metabolism and detoxification, but their role in OC remains unknown.

Methods

Data from multiple public databases associated with OC and GSTMs were collected. Expression, prognosis, function enrichment, immune infiltration, stemness index, and drug sensitivity analysis was utilized to identify the roles of GSTMs in OC progression. RT-qPCR analysis confirmed the effect of AICAR, AT-7519, PHA-793887 and PI-103 on the mRNA levels of GSTM3/4.

Results

GSTM1-5 were decreased in OC samples compared to normal ovary samples. GSTM1/5 were positively correlated with OC prognosis, but GSTM3 was negatively correlated with OC prognosis. Function enrichment analysis indicated GSTMs were involved in glutathione metabolism, drug metabolism, and drug resistance. Immune infiltration analysis indicated GSTM2/3/4 promoted immune escape in OC. GSTM5 was significantly correlated with OC stemness index. GSTM3/4 were remarkedly associated with OC chemoresistance, especially in AICAR, AT-7519, PHA-793887 and PI-103.

Conclusion

GSTM3 was negatively correlated with OC prognosis, and associated with OC chemoresistance and immune escape. This gene may serve as potential prognostic biomarkers and therapeutic target for OC patients.

Predicting Chemo-Radiotherapy Sensitivity With Concordant Survival Benefit in Non-Small Cell Lung Cancer via Computed Tomography Derived Radiomic Features

Background

To identify a computed tomography (CT) derived radiomic signature for the options of concurrent chemo-radiotherapy (CCR) in patients with non-small cell lung cancer (NSCLC).

Methods

A total of 226 patients with NSCLC receiving CCR were enrolled from public dataset, and allocated to discovery and validation sets based on patient identification number. Using CT images of 153 patients in the discovery dataset, we pre-selected a list of radiomic features significantly associated with 5-year survival rate and adopted the least absolute shrinkage and selection operator regression to establish a predictive radiomic signature for CCR treatment. We performed transcriptomic analyzes of the signature, and evaluated its association with molecular lesions and immune landscapes in a dataset with matched CT images and transcriptome data. Furthermore, we identified CCR resistant genes positively correlated with resistant scores of radiomic signature and screened essential resistant genes for NSCLC using genome-scale CRIPSR data. Finally, we combined DrugBank and Genomics of Drug Sensitivity in Cancer databases to excavate candidate therapeutic agents for patients with CCR resistance, and validated them using the Connectivity Map dataset.

Results

The radiomic signature consisting of nine features was established, and then validated in the dataset of 73 patients receiving CCR log-rank P = 0.0005, which could distinguish patients into resistance and sensitivity groups, respectively, with significantly different 5-year survival rate. Furthermore, the novel proposed radiomic nomogram significantly improved the predictive performance (concordance indexes) of clinicopathological factors. Transcriptomic analyzes linked our signature with important tumor biological processes (e.g. glycolysis/glucoseogenesis, ribosome). Then, we identified 36 essential resistant genes, and constructed a gene-agent network including 10 essential resistant genes and 35 candidate therapeutic agents, and excavated AT-7519 as the therapeutic agent for patients with CCR resistance. The therapeutic efficacy of AT-7519 was validated that significantly more resistant genes were down-regulated induced by AT-7519, and the degree gradually increased with the enhanced doses.

Conclusions

This study illustrated that radiomic signature could non-invasively predict therapeutic efficacy of patients with NSCLC receiving CCR, and indicated that patients with CCR resistance might benefit from AT-7519 or CCR treatment combined with AT-7519.