Bcl2-induced DNA replication stress promotes lung carcinogenesis in response to space radiation

Cell cycle dysregulation in cancer

Cancer is a systemic manifestation of aberrant cell cycle activity and dysregulated cell growth. Genetic mutations can determine tumor onset by either augmenting cell division rates or restraining normal controls such as cell cycle arrest or apoptosis. As a result, tumor cells not only undergo uncontrolled cell division but also become compromised in their ability to exit the cell cycle accurately. Regulation of cell cycle progression is enabled by specific surveillance mechanisms known as cell cycle checkpoints, and aberrations in these signaling pathways often culminate in cancer. For instance, DNA damage checkpoints, which preclude the generation and augmentation of DNA damage in the G1, S, and G2 cell cycle phases, are often defective in cancer cells, allowing cell division in spite of the accumulation of genetic errors. Notably, tumors have evolved to become dependent on checkpoints for their survival. For example, checkpoint pathways such as the DNA replication stress checkpoint and the mitotic checkpoint rarely undergo mutations and remain intact because any aberrant activity could result in irreparable damage or catastrophic chromosomal missegregation leading to cell death. In this review, we initially focus on cell cycle control pathways and specific functions of checkpoint signaling involved in normal and cancer cells and then proceed to examine how cell cycle control and checkpoint mechanisms can provide new therapeutic windows that can be exploited for cancer therapy. SIGNIFICANCE STATEMENT: DNA damage checkpoints are often defective in cancer cells, allowing cell division in spite of the accumulation of genetic errors. Conversely, DNA replication stress and mitotic checkpoints rarely undergo mutations because any aberrant activity could result in irreparable damage or catastrophic chromosomal missegregation, leading to cancer cell death. This review focuses on the checkpoint signaling mechanisms involved in cancer cells and how an emerging understanding of these pathways can provide new therapeutic opportunities for cancer therapy.

MicroRNA Monitoring in Human Alveolar Macrophages from Patients with Smoking-Related Lung Diseases: A Preliminary Study

Chronic obstructive pulmonary disease (COPD) is a progressive lung disease that is commonly considered to be a potent driver of non-small cell lung cancer (NSCLC) development and related mortality. A growing body of evidence supports a role of the immune system, mainly played by alveolar macrophages (AMs), in key axes regulating the development of COPD or NSCLC phenotypes in response to harmful agents. MicroRNAs (miRNAs) are small non-coding RNAs that influence most biological processes and interfere with several regulatory pathways. The purpose of this study was to assess miRNA expression patterns in patients with COPD, NSCLC, and ever- or never-smoker controls to explore their involvement in smoking-related diseases. Bronchoalveolar lavage (BAL) specimens were collected from a prospective cohort of 43 sex-matched subjects to determine the expressions of hsa-miR-223-5p, 16-5p, 20a-5p, -17-5p, 34a-5p and 106a-5p by RT-PCR. In addition, a bioinformatic analysis of miRNA target genes linked to cancer was performed. Distinct and common miRNA expression levels were identified in each pathological group, suggesting their possible role as an index of NSCLC or COPD microenvironment. Moreover, we identified miRNA targets linked to carcinogenesis using in silico analysis. In conclusion, this study identified miRNA signatures in AMs, allowing us to understand the molecular mechanisms underlying smoking-related conditions and potentially providing new insights for diagnosis or pharmacological treatment.

A perspective on tumor radiation resistance following high-LET radiation treatment

High-linear energy transfer (LET) radiation is a promising alternative to conventional low-LET radiation for therapeutic gain against cancer owing to its ability to induce complex and clustered DNA lesions. However, the development of radiation resistance poses a significant barrier. The potential molecular mechanisms that could confer resistance development are translesion synthesis (TLS), replication gap suppression (RGS) mechanisms, autophagy, epithelial-mesenchymal transition (EMT) activation, release of exosomes, and epigenetic changes. This article will discuss various types of complex clustered DNA damage, their repair mechanisms, mutagenic potential, and the development of radiation resistance strategies. Furthermore, it highlights the importance of careful consideration and patient selection when employing high-LET radiotherapy in clinical settings.

Long-term space missions' effects on the human organism: what we do know and what requires further research

Space has always fascinated people. Many years have passed since the first spaceflight, and in addition to the enormous technological progress, the level of understanding of human physiology in space is also increasing. The presented paper aims to summarize the recent research findings on the influence of the space environment (microgravity, pressure differences, cosmic radiation, etc.) on the human body systems during short-term and long-term space missions. The review also presents the biggest challenges and problems that must be solved in order to extend safely the time of human stay in space. In the era of increasing engineering capabilities, plans to colonize other planets, and the growing interest in commercial space flights, the most topical issues of modern medicine seems to be understanding the effects of long-term stay in space, and finding solutions to minimize the harmful effects of the space environment on the human body.

Comprehensive analysis of novel prognosis-related proteomic signature effectively improve risk stratification and precision treatment for patients with cervical cancer

OBJECTIVE

Cervical cancer (CC) is one of the most common types of malignant female cancer, and its incidence and mortality are not optimistic. Protein panels can be a powerful prognostic factor for many types of cancer. The purpose of our study was to investigate a proteomic panel to predict the survival of patients with common CC.

METHODS AND RESULTS

The protein expression and clinicopathological data of CC were downloaded from The Cancer Proteome Atlas and The Cancer Genome Atlas database, respectively. We selected the prognosis-related proteins (PRPs) by univariate Cox regression analysis and found that the results of functional enrichment analysis were mainly related to apoptosis. We used Kaplan-Meier analysis and multivariable Cox regression analysis further to screen PRPs to establish a prognostic model, including BCL2, SMAD3, and 4EBP1-pT70. The signature was verified to be independent predictors of OS by Cox regression analysis and the area under curves. Nomogram and subgroup classification were established based on the signature to verify its clinical application. Furthermore, we looked for the co-expressed proteins of three-protein panel as potential prognostic proteins.

CONCLUSION

A proteomic signature independently predicted OS of CC patients, and the predictive ability was better than the clinicopathological characteristics. This signature can help improve prediction for clinical outcome and provides new targets for CC treatment.

Robust meta-analysis for large-scale genomic experiments based on an empirical approach

Background

Recent high-throughput technologies have opened avenues for simultaneous analyses of thousands of genes. With the availability of a multitude of public databases, one can easily access multiple genomic study results where each study comprises of significance testing results of thousands of genes. Researchers currently tend to combine this genomic information from these multiple studies in the form of a meta-analysis. As the number of genes involved is very large, the classical meta-analysis approaches need to be updated to acknowledge this large-scale aspect of the data.

Methods

In this article, we discuss how application of standard theoretical null distributional assumptions of the classical meta-analysis methods, such as Fisher’s p-value combination and Stouffer’s Z, can lead to incorrect significant testing results, and we propose a robust meta-analysis method that empirically modifies the individual test statistics and p-values before combining them.

Results

Our proposed meta-analysis method performs best in significance testing among several meta-analysis approaches, especially in presence of hidden confounders, as shown through a wide variety of simulation studies and real genomic data analysis.

Conclusion

The proposed meta-analysis method produces superior meta-analysis results compared to the standard p-value combination approaches for large-scale simultaneous testing in genomic experiments. This is particularly useful in studies with large number of genes where the standard meta-analysis approaches can result in gross false discoveries due to the presence of unobserved confounding variables.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01530-y.

A proteomic analysis of Bcl-2 regulation of cell cycle arrest: insight into the mechanisms

B cell lymphoma 2 (Bcl-2) is an important antiapoptotic gene that plays a dual role in the maintenance of the dynamic balance between the survival and death of cancer cells. In our previous study, Bcl-2 was shown to delay the G0/G1 to S phase entry by regulating the mitochondrial metabolic pathways to produce lower levels of adenosine triphosphate (ATP) and reactive oxygen species (ROS). However, the detailed molecular mechanisms or pathways by which Bcl-2 regulates the cell cycle remain unknown. Here, we compared the effects of Bcl-2 overexpression with an empty vector control in the NIH3T3 cell line synchronized by serum starvation, and evaluated the effects using proteomic analysis. The effect of Bcl-2 on cell cycle regulation was detected by monitoring Bcl-2 and p27 expression. The result of subsequent proteomic analysis of Bcl-2 overexpressing cells identified 169 upregulated and 120 downregulated proteins with a 1.5-fold change. These differentially expressed proteins were enriched in a number of signaling pathways predominantly involving the ribosome and oxidative phosphorylation, according to the data of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. These results indicated that Bcl-2 potentially acts at the translation level to influence proteins or enzymes of the respiratory chain or in the ribosome, and thereby regulates the cell cycle. Additionally, differentially expressed proteins involved in oxidative phosphorylation were determined to account for most of the effects of Bcl-2 on the cell cycle mediated by the mitochondrial pathway investigated in our previous study. These results can provide assistance for additional in-depth studies on the regulation of the cell cycle by Bcl-2. The results of the proteomic analysis determined the mechanism of Bcl-2-dependent delay of the cell cycle progression. In summary, the results of this study provide a novel mechanistic basis for identifying the key proteins or pathways for designing and developing precisely targeted cancer drugs.