Phase Separation: "The Master Key" to Deciphering the Physiological and Pathological Functions of Cells

Coacervates Composed of Low-Molecular-Weight Compounds- Molecular Design, Stimuli Responsiveness, Confined Reaction

The discovery of coacervation within living cells through liquid-liquid phase separation has inspired scientists to investigate its fundamental principles and significance. Indeed, coacervates composed of low-molecular-weight compounds based on supramolecular strategy can offer valuable models for biomolecular condensates and useful tools. This mini-review highlights recent findings and advances in coacervates (artificial condensates), primarily composed of low-molecular-weight compounds, with focuses on their molecular design, stimuli responsiveness, and controlled reactions within or leading to the coacervates.

Genome wide identification and characterization of Bax inhibitor-1 gene family in cucumber (Cucumis sativus) under biotic and abiotic stress

In plants, the BAX inhibitor-1 (BI-1) gene plays a crucial part in controlling cell death under stress conditions. This mechanism of Programmed Cell Death (PCD) is genetically regulated and is crucial for the elimination of unwanted or damaged cells in a controlled manner, which is essential for normal development and tissue maintenance. A study on cucumber identified and characterized five BI-1 genes: CsBI1, CsBI2, CsBI3, CsBI4, and CsBI5. These genes share conserved domains, indicating common evolutionary history and function. Physicochemical analysis revealed their molecular weights and isoelectric points, while subcellular localization showed their presence in different cellular compartments. The phylogenetic analysis highlighted evolutionary relationships with related crops. Chromosomal distribution and synteny analysis suggested segmental or tandem duplications within the gene family. Protein-protein interaction analysis revealed extensive interactions with other cucumber proteins. Cis-regulatory elements in the promoter regions provided insights into potential functions and transcriptional regulation. miRNAs showed diverse regulatory mechanisms, including mRNA cleavage and translational inhibition. The CsBI3, CsBI4 and CsBI5 genes exhibit elevated expression levels during cold stress, suggesting their vital involvement in cucumber plant defense mechanisms. The application of chitosan oligosaccharides externally confirms their distinct expression patterns. The qRT-PCR confirms the upregulation of CsBI genes in ToLCNDV-infected plants, indicating their potential to mitigate biotic and abiotic stresses. The comprehensive genome-wide exploration provides opportunities for the development of cold-tolerant and virus-resistant cucumber variants by traditional breeding or gene.

The role of liquid-liquid phase separation in the disease pathogenesis and drug development

Misfolding and aggregation of specific proteins are associated with liquid-liquid phase separation (LLPS), and these protein aggregates can interfere with normal cellular functions and even lead to cell death, possibly affecting gene expression regulation and cell proliferation. Therefore, understanding the role of LLPS in disease may help to identify new mechanisms or therapeutic targets and provide new strategies for disease treatment. There are several ways to disrupt LLPS, including screening small molecules or small molecule drugs to target the upstream signaling pathways that regulate the LLPS process, selectively dissolve and destroy RNA droplets or protein aggregates, regulate the conformation of mutant protein, activate the protein degradation pathway to remove harmful protein aggregates. Furthermore, harnessing the mechanism of LLPS can improve drug development, including preparing different kinds of drug delivery carriers (microneedles, nanodrugs, imprints), regulating drug internalization and penetration behaviors, screening more drugs to overcome drug resistance and enhance receptor signaling. This review initially explores the correlation between aberrant LLPS and disease, highlighting the pivotal role of LLPS in preparing drug development. Ultimately, a comprehensive investigation into drug-mediated regulation of LLPS processes holds significant scientific promise for disease management.

Construction of a tumor mutational burden-derived LncRNA prognostic computational framework associated with therapy sensitivity in skin cutaneous melanoma

BACKGROUND

Skin cutaneous melanoma (SKCM) poses a significant public health challenge due to its aggressive nature and limited treatment options. To address this, the study introduces the Tumor Mutational Burden-Derived Immune lncRNA Prognostic Index (TILPI) as a potential prognostic tool for SKCM.

METHODS

TILPI was developed using a combination of gene set variation analysis, differential expression analysis, and COX regression analysis. Additionally, functional experiments were conducted to validate the findings, focusing on the effects of STARD4-AS1 knockdown on SKCM tumor cell behavior. These experiments encompassed assessments of tumor cell proliferation, gene and protein expression, migration, invasion, and in vivo tumor growth.

RESULTS

The results demonstrated that knockdown of STARD4-AS1 led to a significant reduction in tumor cell proliferation and impaired migration and invasion abilities. Moreover, it resulted in the downregulation of ADCY4, PRKACA, and SOX10 gene expression, as well as decreased protein expression of ADCY4, PRKACA, and SOX10. In vivo experiments further confirmed the efficacy of STARD4-AS1 knockdown in reducing tumor growth.

CONCLUSIONS

This study elucidates the mechanistic role of STARD4-AS1 and its downstream targets in SKCM progression, highlighting the importance of the ADCY4/PRKACA/SOX10 pathway. The integration of computational analysis with experimental validation enhances the understanding of TILPI and its clinical implications. Overall, the findings underscore the potential of novel computational frameworks like TILPI in predicting and managing SKCM, particularly through targeting the ADCY4/PRKACA/SOX10 pathway.

A tumor mutational burden-derived immune computational framework selects sensitive immunotherapy/chemotherapy for lung adenocarcinoma populations with different prognoses

Background

Lung adenocarcinoma (LUAD) kills millions of people every year. Recently, FDA and researchers proved the significance of high tumor mutational burden (TMB) in treating solid tumors. But no scholar has constructed a TMB-derived computing framework to select sensitive immunotherapy/chemotherapy for the LUAD population with different prognoses.

Methods

The datasets were collected from TCGA, GTEx, and GEO. We constructed the TMB-derived immune lncRNA prognostic index (TILPI) computing framework based on TMB-related genes identified by weighted gene co-expression network analysis (WGCNA), oncogenes, and immune-related genes. Furthermore, we mapped the immune landscape based on eight algorithms. We explored the immunotherapy sensitivity of different prognostic populations based on immunotherapy response, tumor immune dysfunction and exclusion (TIDE), and tumor inflammation signature (TIS) model. Furthermore, the molecular docking models were constructed for sensitive drugs identified by the pRRophetic package, oncopredict package, and connectivity map (CMap).

Results

The TILPI computing framework was based on the expression of TMB-derived immune lncRNA signature (TILncSig), which consisted of AC091057.1, AC112721.1, AC114763.1, AC129492.1, LINC00592, and TARID. TILPI divided all LUAD patients into two populations with different prognoses. The random grouping verification, survival analysis, 3D PCA, and ROC curve (AUC=0.74) firmly proved the reliability of TILPI. TILPI was associated with clinical characteristics, including smoking and pathological stage. Furthermore, we estimated three types of immune cells threatening the survival of patients based on multiple algorithms. They were macrophage M0, T cell CD4 Th2, and T cell CD4 memory activated. Nevertheless, five immune cells, including B cell, endothelial cell, eosinophil, mast cell, and T cell CD4 memory resting, prolonged the survival. In addition, the immunotherapy response and TIDE model proved the sensitivity of the low-TILPI population to immunotherapy. We also identified seven intersected drugs for the LUAD population with poor prognosis, which included docetaxel, gemcitabine, paclitaxel, palbociclib, pyrimethamine, thapsigargin, and vinorelbine. Their molecular docking models and best binding energy were also constructed and calculated.

Conclusions

We divided all LUAD patients into two populations with different prognoses. The good prognosis population was sensitive to immunotherapy, while the people with poor prognosis benefitted from 7 drugs.

Development and application of oncolytic viruses as the nemesis of tumor cells

Viruses and tumors are two pathologies that negatively impact human health, but what occurs when a virus encounters a tumor? A global consensus among cancer patients suggests that surgical resection, chemotherapy, radiotherapy, and other methods are the primary means to combat cancer. However, with the innovation and development of biomedical technology, tumor biotherapy (immunotherapy, molecular targeted therapy, gene therapy, oncolytic virus therapy, etc.) has emerged as an alternative treatment for malignant tumors. Oncolytic viruses possess numerous anti-tumor properties, such as directly lysing tumor cells, activating anti-tumor immune responses, and improving the tumor microenvironment. Compared to traditional immunotherapy, oncolytic virus therapy offers advantages including high killing efficiency, precise targeting, and minimal side effects. Although oncolytic virus (OV) therapy was introduced as a novel approach to tumor treatment in the 19th century, its efficacy was suboptimal, limiting its widespread application. However, since the U.S. Food and Drug Administration (FDA) approved the first OV therapy drug, T-VEC, in 2015, interest in OV has grown significantly. In recent years, oncolytic virus therapy has shown increasingly promising application prospects and has become a major research focus in the field of cancer treatment. This article reviews the development, classification, and research progress of oncolytic viruses, as well as their mechanisms of action, therapeutic methods, and routes of administration.

Genomic instability drives tumorigenesis and metastasis and its implications for cancer therapy

Genetic instability can be caused by external factors and may also be associated with intracellular damage. At the same time, there is a large body of research investigating the mechanisms by which genetic instability occurs and demonstrating the relationship between genomic stability and tumors. Nowadays, tumorigenesis development is one of the hottest research areas. It is a vital factor affecting tumor treatment. Mechanisms of genomic stability and tumorigenesis development are relatively complex. Researchers have been working on these aspects of research. To explore the research progress of genomic stability and tumorigenesis, development, and treatment, the authors searched PubMed with the keywords "genome instability" "chromosome instability" "DNA damage" "tumor spread" and "cancer treatment". This extracts the information relevant to this study. Results: This review introduces genomic stability, drivers of tumor development, tumor cell characteristics, tumor metastasis, and tumor treatment. Among them, immunotherapy is more important in tumor treatment, which can effectively inhibit tumor metastasis and kill tumor cells. Breakthroughs in tumorigenesis development studies and discoveries in tumor metastasis will provide new therapeutic techniques. New tumor treatment methods can effectively prevent tumor metastasis and improve the cure rate of tumors.

Prognostic model and immunotherapy prediction based on molecular chaperone-related lncRNAs in lung adenocarcinoma

Introduction: Molecular chaperones and long non-coding RNAs (lncRNAs) have been confirmed to be closely related to the occurrence and development of tumors, especially lung cancer. Our study aimed to construct a kind of molecular chaperone-related long non-coding RNAs (MCRLncs) marker to accurately predict the prognosis of lung adenocarcinoma (LUAD) patients and find new immunotherapy targets.

Methods: In this study, we acquired molecular chaperone genes from two databases, Genecards and molecular signatures database (MsigDB). And then, we downloaded transcriptome data, clinical data, and mutation information of LUAD patients through the Cancer Genome Atlas (TCGA). MCRLncs were determined by Spearman correlation analysis. We used univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to construct risk models. Kaplan-meier (KM) analysis was used to understand the difference in survival between high and low-risk groups. Nomogram, calibration curve, concordance index (C-index) curve, and receiver operating characteristic (ROC) curve were used to evaluate the accuracy of the risk model prediction. In addition, we used gene ontology (GO) enrichment analysis and kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses to explore the potential biological functions of MCRLncs. Immune microenvironmental landscapes were constructed by using single-sample gene set enrichment analysis (ssGSEA), tumor immune dysfunction and exclusion (TIDE) algorithm, “pRRophetic” R package, and “IMvigor210” dataset. The stem cell index based on mRNAsi expression was used to further evaluate the patient’s prognosis.

Results: Sixteen MCRLncs were identified as independent prognostic indicators in patients with LUAD. Patients in the high-risk group had significantly worse overall survival (OS). ROC curve suggested that the prognostic features of MCRLncs had a good predictive ability for OS. Immune system activation was more pronounced in the high-risk group. Prognostic features of the high-risk group were strongly associated with exclusion and cancer-associated fibroblasts (CAF). According to this prognostic model, a total of 15 potential chemotherapeutic agents were screened for the treatment of LUAD. Immunotherapy analysis showed that the selected chemotherapeutic drugs had potential application value. Stem cell index mRNAsi correlates with prognosis in patients with LUAD.

Conclusion: Our study established a kind of novel MCRLncs marker that can effectively predict OS in LUAD patients and provided a new model for the application of immunotherapy in clinical practice.

The Mechanisms of Ferroptosis and the Applications in Tumor Treatment: Enemies or Friends?

Ferroptosis, as a newly discovered non-apoptotic cell death mode, is beginning to be explored in different cancer. The particularity of ferroptosis lies in the accumulation of iron dependence and lipid peroxides, and it is different from the classical cell death modes such as apoptosis and necrosis in terms of action mode, biochemical characteristics, and genetics. The mechanism of ferroptosis can be divided into many different pathways, so it is particularly important to identify the key sites of ferroptosis in the disease. Herein, based on ferroptosis, we analyze the main pathways in detail. More importantly, ferroptosis is linked to the development of different systems of the tumor, providing personalized plans for the examination, treatment, and prognosis of cancer patients. Although some mechanisms and side effects of ferroptosis still need to be studied, it is still a promising method for cancer treatment.

Identified Gefitinib Metabolism-Related lncRNAs can be Applied to Predict Prognosis, Tumor Microenvironment, and Drug Sensitivity in Non-Small Cell Lung Cancer

Gefitinib has shown promising efficacy in the treatment of patients with locally advanced or metastatic EGFR-mutated non-small cell lung cancer (NSCLC). Molecular biomarkers for gefitinib metabolism-related lncRNAs have not yet been elucidated. Here, we downloaded relevant genes and matched them to relevant lncRNAs. We then used univariate, LASSO, and multivariate regression to screen for significant genes to construct prognostic models. We investigated TME and drug sensitivity by risk score data. All lncRNAs with differential expression were selected for GO/KEGG analysis. Imvigor210 cohort was used to validate the value of the prognostic model. Finally, we performed a stemness indices difference analysis. lncRNA-constructed prognostic models were significant in the high-risk and low-risk subgroups. Immune pathways were identified in both groups at low risk. The higher the risk score the greater the value of exclusion, MDSC, and CAF. PRRophetic algorithm screened a total of 58 compounds. In conclusion, the prognostic model we constructed can accurately predict OS in NSCLC patients. Two groups of low-risk immune pathways are beneficial to patients. Gefitinib metabolism was again validated to be related to cytochrome P450 and lipid metabolism. Finally, drugs that might be used to treat NSCLC patients were screened.