ADAR1-mediated RNA editing of SCD1 drives drug resistance and self-renewal in gastric cancer

Comprehensive analysis of stearoyl-coenzyme A desaturase in prostate adenocarcinoma: insights into gene expression, immune microenvironment and tumor progression

Prostate adenocarcinoma (PRAD) is a prevalent global malignancy which depends more on lipid metabolism for tumor progression compared to other cancer types. Although Stearoyl-coenzyme A desaturase (SCD) is documented to regulate lipid metabolism in multiple cancers, landscape analysis of its implications in PRAD are still missing at present. Here, we conducted an analysis of diverse cancer datasets revealing elevated SCD expression in the PRAD cohort at both mRNA and protein levels. Interestingly, the elevated expression was associated with SCD promoter hypermethylation and genetic alterations, notably the L134V mutation. Integration of comprehensive tumor immunological and genomic data revealed a robust positive correlation between SCD expression levels and the abundance of CD8+ T cells and macrophages. Further analyses identified significant associations between SCD expression and various immune markers in tumor microenvironment. Single-cell transcriptomic profiling unveiled differential SCD expression patterns across distinct cell types within the prostate tumor microenvironment. The Gene Ontology and Kyoto Encyclopedia of Genes and Genome analyses showed that SCD enriched pathways were primarily related to lipid biosynthesis, cholesterol biosynthesis, endoplasmic reticulum membrane functions, and various metabolic pathways. Gene Set Enrichment Analysis highlighted the involvement of elevated SCD expression in crucial cellular processes, including the cell cycle and biosynthesis of cofactors pathways. In functional studies, SCD overexpression promoted the proliferation, metastasis and invasion of prostate cancer cells, whereas downregulation inhibits these processes. This study provides comprehensive insights into the multifaceted roles of SCD in PRAD pathogenesis, underscoring its potential as both a therapeutic target and prognostic biomarker.

NFS1 inhibits ferroptosis in gastric cancer by regulating the STAT3 pathway

Cysteine desulfurase (NFS1) is highly expressed in a variety of tumors, which is closely related to ferroptosis of tumor cells and affects prognosis. The relationship between NFS1 and the development of gastric cancer (GC) remains unknown. Here we showed that NFS1 expression was significantly higher in GC tissues compared to adjacent normal tissues. Patients with high expression of NFS1 in GC tissues had a lower overall survival rate than those with low expression. NFS1 was highly expressed in cultured GC cells compared to normal gastric cells. Knockdown of NFS1 expression reduced the viability, migration and invasion of GC cells. In cultured GC cells, NFS1 deficiency promoted ferroptosis. Mechanistically, NFS1 inhibited ferroptosis by upregulating the signal transduction and activator of transcription 3 (STAT3) signaling pathway in cultured GC cells. NFS1 knockdown using siRNA inhibited the STAT3 pathway, reduced the expression of glutathione peroxidase 4 (GPX4) and solute carrier family 7 member 11 (SLC7A11), and elevated intracellular levels of reactive oxygen species (ROS), ferrous ion (Fe2+), and malondialdehyde (MDA) in cultured GC cells. A specific STAT3 activator significantly reversed the inhibitory effect of NFS1 deficiency on ferroptosis in cultured GC cells. These in vitro results were further confirmed by experiments in vivo using a mouse xenograft tumor model. Collectively, THESE RESULTS INDICATE THAT NFS1 is overexpressed in human GC tissues and correlated with prognosis. NFS1 inhibits ferroptosis by activating the STAT3 pathway in GC cells. These results suggest that NFS1 may be a potential prognostic biomarker and therapeutic target to treat GC.

Cancer plasticity in therapy resistance: Mechanisms and novel strategies

Therapy resistance poses a significant obstacle to effective cancer treatment. Recent insights into cell plasticity as a new paradigm for understanding resistance to treatment: as cancer progresses, cancer cells experience phenotypic and molecular alterations, corporately known as cell plasticity. These alterations are caused by microenvironment factors, stochastic genetic and epigenetic changes, and/or selective pressure engendered by treatment, resulting in tumor heterogeneity and therapy resistance. Increasing evidence suggests that cancer cells display remarkable intrinsic plasticity and reversibly adapt to dynamic microenvironment conditions. Dynamic interactions between cell states and with the surrounding microenvironment form a flexible tumor ecosystem, which is able to quickly adapt to external pressure, especially treatment. Here, this review delineates the formation of cancer cell plasticity (CCP) as well as its manipulation of cancer escape from treatment. Furthermore, the intrinsic and extrinsic mechanisms driving CCP that promote the development of therapy resistance is summarized. Novel treatment strategies, e.g., inhibiting or reversing CCP is also proposed. Moreover, the review discusses the multiple lines of ongoing clinical trials globally aimed at ameliorating therapy resistance. Such advances provide directions for the development of new treatment modalities and combination therapies against CCP in the context of therapy resistance.

Unraveling the secrets: Evolution of resistance mediated by membrane proteins

Membrane protein-mediated resistance is a multidisciplinary challenge that spans fields such as medicine, agriculture, and environmental science. Understanding its complexity and devising innovative strategies are crucial for treating diseases like cancer and managing resistant pests in agriculture. This paper explores the dual nature of resistance mechanisms across different organisms: On one hand, animals, bacteria, fungi, plants, and insects exhibit convergent evolution, leading to the development of similar resistance mechanisms. On the other hand, influenced by diverse environmental pressures and structural differences among organisms, they also demonstrate divergent resistance characteristics. Membrane protein-mediated resistance mechanisms are prevalent across animals, bacteria, fungi, plants, and insects, reflecting their shared survival strategies evolved through convergent evolution to address similar survival challenges. However, variations in ecological environments and biological characteristics result in differing responses to resistance. Therefore, examining these differences not only enhances our understanding of adaptive resistance mechanisms but also provides crucial theoretical support and insights for addressing drug resistance and advancing pharmaceutical development.

RNA epigenetic modifications in digestive tract cancers: Friends or foes

Digestive tract cancers are among the most common malignancies worldwide and have high incidence and mortality rates. Thus, the discovery of more effective diagnostic and therapeutic targets is urgently required. The development of technologies to accurately detect RNA modification has led to the identification of numerous RNA chemical modifications in humans (epitranscriptomics) that are involved in the occurrence and development of digestive tract cancers. RNA modifications can cooperatively regulate gene expression to facilitate normal physiological functions of the digestive system. However, the dysfunction of relevant RNA-modifying enzymes ("writers," "erasers," and "readers") can lead to the development of digestive tract cancers. Consequently, targeting dysregulated enzyme activity could represent a potent therapeutic strategy for the treatment of digestive tract cancers. In this review, we summarize the most widely studied roles and mechanisms of RNA modifications (m6A, m1A, m5C, m7G, A-to-I editing, pseudouridine [Ψ]) in relation to digestive tract cancers, highlight the crosstalk between RNA modifications, and discuss their roles in the interactions between the digestive system and microbiota during carcinogenesis. The clinical significance of novel therapeutic methods based on RNA-modifying enzymes is also discussed. This review will help guide future research into digestive tract cancers that are resistant to current therapeutics.

RNA modification Regulators' Co-Expression Score (RMRCoeS) predicts biochemical recurrence and therapy response in prostate cancer: A multi-omics and experimental validation study

BACKGROUND

Owing to the heterogeneity of prostate cancer (PCa), the clinical indicators traditionally fall short of meeting the requirements for personalized medicine. The realm of RNA modification has emerged as an increasingly relevant domain, shedding light on its pivotal role in tumor heterogeneity. However, the specific contributions of RNA modification regulators within the context of PCa remain largely unexplored.

METHODS

In this study, we undertook a literature review to summarize the common 8 types of RNA modifications (ac4c, AI, APA, m1A, m5c, m6A, m7G, Ψ) encompassing a total of 84 regulators. Moreover, we integrated multi-center cohorts with Ridge regression to develop the Regulators' Co-Expression Score (RMRCoeS). Then we assessed the role of RMRCoeS in several clinical aspects such as biochemical recurrence (BCR), responses to chemotherapy, androgen receptor signaling inhibitor (ARSI) therapy and immunotherapy in PCa. Finally, we validated the cancer-promoting performance of five hub genes through immunohistochemistry and in vitro assays.

RESULTS

Within the mutation landscape of RNA modification regulators, we observed a relatively low overall mutation rate. Remarkably, RMRCoeS, comprising 81 RNA modification regulators, exhibited a notable capability for accurately predicting the prognosis and therapeutic responses in PCa patients subjected to BCR, chemotherapy, ARSI therapy, and immunotherapy. A high RMRCoeS was indicative of a poor prognosis and unfavorable therapy responses. Functional enrichment analysis unveiled that RMRCoeS may exert its influence on PCa progression through various metabolic pathways. Furthermore, a higher RMRCoeS showed a positive correlation with elevated CNV mutations. Lastly, we validated the oncogene effects of CPSF4, WBSCR22, RPUSD3, TRMT61A, and NSUN5-five hub regulators-within the context of PCa.

CONCLUSION

The function of different RNA modifications is interconnected. Comprising eight distinct RNA modifications' regulators, RMRCoeS exhibits multifaceted roles in various aspects of PCa, including disease progression, prognosis, and responses to multiple therapies. Furthermore, we provide the initial validation of the oncogene effect associated with WBSCR22, RPUSD3, TRMT61A and NSUN5 in PCa. Our findings offer novel insights into the significance of RNA modifications in PCa personalized medicine.

ADAR-Mediated A>I(G) RNA Editing in the Genotoxic Drug Response of Breast Cancer

Epitranscriptomics is a field that delves into post-transcriptional changes. Among these modifications, the conversion of adenosine to inosine, traduced as guanosine (A>I(G)), is one of the known RNA-editing mechanisms, catalyzed by ADARs. This type of RNA editing is the most common type of editing in mammals and contributes to biological diversity. Disruption in the A>I(G) RNA-editing balance has been linked to diseases, including several types of cancer. Drug resistance in patients with cancer represents a significant public health concern, contributing to increased mortality rates resulting from therapy non-responsiveness and disease progression, representing the greatest challenge for researchers in this field. The A>I(G) RNA editing is involved in several mechanisms over the immunotherapy and genotoxic drug response and drug resistance. This review investigates the relationship between ADAR1 and specific A>I(G) RNA-edited sites, focusing particularly on breast cancer, and the impact of these sites on DNA damage repair and the immune response over anti-cancer therapy. We address the underlying mechanisms, bioinformatics, and in vitro strategies for the identification and validation of A>I(G) RNA-edited sites. We gathered databases related to A>I(G) RNA editing and cancer and discussed the potential clinical and research implications of understanding A>I(G) RNA-editing patterns. Understanding the intricate role of ADAR1-mediated A>I(G) RNA editing in breast cancer holds significant promise for the development of personalized treatment approaches tailored to individual patients' A>I(G) RNA-editing profiles.

Molecular mechanisms of non-genetic aberrant peptide production in cancer

The cancer peptidome has long been known to be altered by genetic mutations. However, more recently, non-genetic polypeptide mutations have also been related to cancer cells. These non-genetic mutations occur post-t30ranscriptionally, leading to the modification of the peptide primary structure, while the corresponding genes remain unchanged. Three main processes participate in the production of these aberrant proteins: mRNA alternative splicing, mRNA editing, and mRNA aberrant translation. In this review, we summarize the molecular mechanisms underlying these processes and the recent findings on the functions of the aberrant proteins, as well as their exploitability as new therapeutic targets due to their specific enrichment in cancer cells. These non-genetic aberrant polypeptides represent a source of novel cancer cell targets independent from their level of mutational burden, still to be exhaustively explored.

The predictive accuracy of machine learning for the risk of death in HIV patients: a systematic review and meta-analysis

BACKGROUND

Early prediction of mortality in individuals with HIV (PWH) has perpetually posed a formidable challenge. With the widespread integration of machine learning into clinical practice, some researchers endeavor to formulate models predicting the mortality risk for PWH. Nevertheless, the diverse timeframes of mortality among PWH and the potential multitude of modeling variables have cast doubt on the efficacy of the current predictive model for HIV-related deaths. To address this, we undertook a systematic review and meta-analysis, aiming to comprehensively assess the utilization of machine learning in the early prediction of HIV-related deaths and furnish evidence-based support for the advancement of artificial intelligence in this domain.

METHODS

We systematically combed through the PubMed, Cochrane, Embase, and Web of Science databases on November 25, 2023. To evaluate the bias risk in the original studies included, we employed the Predictive Model Bias Risk Assessment Tool (PROBAST). During the meta-analysis, we conducted subgroup analysis based on survival and non-survival models. Additionally, we utilized meta-regression to explore the influence of death time on the predictive value of the model for HIV-related deaths.

RESULTS

After our comprehensive review, we analyzed a total of 24 pieces of literature, encompassing data from 401,389 individuals diagnosed with HIV. Within this dataset, 23 articles specifically delved into deaths during long-term follow-ups outside hospital settings. The machine learning models applied for predicting these deaths comprised survival models (COX regression) and other non-survival models. The outcomes of the meta-analysis unveiled that within the training set, the c-index for predicting deaths among people with HIV (PWH) using predictive models stands at 0.83 (95% CI: 0.75-0.91). In the validation set, the c-index is slightly lower at 0.81 (95% CI: 0.78-0.85). Notably, the meta-regression analysis demonstrated that neither follow-up time nor the occurrence of death events significantly impacted the performance of the machine learning models.

CONCLUSIONS

The study suggests that machine learning is a viable approach for developing non-time-based predictions regarding HIV deaths. Nevertheless, the limited inclusion of original studies necessitates additional multicenter studies for thorough validation.

Hallmarks of cancer stemness

Cancer stemness is recognized as a key component of tumor development. Previously coined "cancer stem cells" (CSCs) and believed to be a rare population with rigid hierarchical organization, there is good evidence to suggest that these cells exhibit a plastic cellular state influenced by dynamic CSC-niche interplay. This revelation underscores the need to reevaluate the hallmarks of cancer stemness. Herein, we summarize the techniques used to identify and characterize the state of these cells and discuss their defining and emerging hallmarks, along with their enabling and associated features. We also highlight potential future directions in this field of research.

RNA editing enzymes: structure, biological functions and applications

With the advancement of sequencing technologies and bioinformatics, over than 170 different RNA modifications have been identified. However, only a few of these modifications can lead to base pair changes, which are called RNA editing. RNA editing is a ubiquitous modification in mammalian transcriptomes and is an important co/posttranscriptional modification that plays a crucial role in various cellular processes. There are two main types of RNA editing events: adenosine to inosine (A-to-I) editing, catalyzed by ADARs on double-stranded RNA or ADATs on tRNA, and cytosine to uridine (C-to-U) editing catalyzed by APOBECs. This article provides an overview of the structure, function, and applications of RNA editing enzymes. We discuss the structural characteristics of three RNA editing enzyme families and their catalytic mechanisms in RNA editing. We also explain the biological role of RNA editing, particularly in innate immunity, cancer biogenesis, and antiviral activity. Additionally, this article describes RNA editing tools for manipulating RNA to correct disease-causing mutations, as well as the potential applications of RNA editing enzymes in the field of biotechnology and therapy.

Global characterization of RNA editing in genetic regulation of multiple ovarian cancer subtypes

RNA editing plays an extensive role in the initiation and progression of cancer. However, the overall profile and molecular functions of RNA editing in different ovarian cancer subtypes have not been fully characterized and elucidated. Here, we conducted a study on RNA editing in four cohorts of ovarian cancer subtypes through large-scale parallel reporting and bioinformatics analysis. Our findings revealed that RNA editing patterns exhibit subtype-specific characteristics within cancer subtypes. The expression pattern of ADAR and the number of differential editing sites varied under different conditions. CCOC and EOC exhibited significant editing deficiency, whereas HGSC and MOC displayed significant editing excess. The sites within the turquoise module of the coedited network also revealed their correlation with ovarian cancer. In addition, we identified an average of over 40,000 cis-edQTLs in the four subtypes. Finally, we explored the association between RNA editing and drug response, uncovering several potentially effective editing-drug pairs (EDP) and suggesting the conceivable utility of RNA editing sites as therapeutic targets for cancer treatment. Overall, our comprehensive study has identified and characterized RNA editing events in various subtypes of ovarian cancer, providing a new perspective for ovarian cancer research and facilitating the development of medical interventions and treatments.

Metabolic reprogramming based on RNA sequencing of gemcitabine-resistant cells reveals the FASN gene as a therapeutic for bladder cancer

Bladder cancer (BLCA) is the most frequent malignant tumor of the genitourinary system. Postoperative chemotherapy drug perfusion and chemotherapy are important means for the treatment of BLCA. However, once drug resistance occurs, BLCA develops rapidly after recurrence. BLCA cells rely on unique metabolic rewriting to maintain their growth and proliferation. However, the relationship between the metabolic pattern changes and drug resistance in BLCA is unclear. At present, this problem lacks systematic research. In our research, we identified and analyzed resistance- and metabolism-related differentially expressed genes (RM-DEGs) based on RNA sequencing of a gemcitabine-resistant BLCA cell line and metabolic-related genes (MRGs). Then, we established a drug resistance- and metabolism-related model (RM-RM) through regression analysis to predict the overall survival of BLCA. We also confirmed that RM-RM had a significant correlation with tumor metabolism, gene mutations, tumor microenvironment, and adverse drug reactions. Patients with a high drug resistance- and metabolism-related risk score (RM-RS) showed more active lipid synthesis than those with a low RM-RS. Further in vitro and in vivo studies were implemented using Fatty Acid Synthase (FASN), a representative gene, which promotes gemcitabine resistance, and its inhibitor (TVB-3166) that can reverse this resistance effect.

Human organoids-on-chips for biomedical research and applications

Human organoids-on-chips (OrgOCs) are the synergism of human organoids (HOs) technology and microfluidic organs-on-chips (OOCs). OOCs can mimic extrinsic characteristics of organs, such as environmental clues of living tissue, while HOs are more amenable to biological analysis and genetic manipulation. By spatial cooperation, OrgOCs served as 3D organotypic living models allowing them to recapitulate critical tissue-specific properties and forecast human responses and outcomes. It represents a giant leap forward from the regular 2D cell monolayers and animal models in the improved human ecological niche modeling. In recent years, OrgOCs have offered potential promises for clinical studies and advanced the preclinical-to-clinical translation in medical and industrial fields. In this review, we highlight the cutting-edge achievements in OrgOCs, introduce the key features of OrgOCs architectures, and share the revolutionary applications in basic biology, disease modeling, preclinical assay and precision medicine. Furthermore, we discuss how to combine a wide range of disciplines with OrgOCs and accelerate translational applications, as well as the challenges and opportunities of OrgOCs in biomedical research and applications.

Emerging roles of 3D-culture systems in tackling tumor drug resistance

Drug resistance that affects patients universally is a major challenge in cancer therapy. The development of drug resistance in cancer cells is a multifactor event, and its process involves numerous mechanisms that allow these cells to evade the effect of treatments. As a result, the need to understand the molecular mechanisms underlying cancer drug sensitivity is imperative. Traditional 2D cell culture systems have been utilized to study drug resistance, but they often fail to mimic the 3D milieu and the architecture of real tissues and cell-cell interactions. As a result of this, 3D cell culture systems are now considered a comprehensive model to study drug resistance in vitro. Cancer cells exhibit an in vivo behavior when grown in a three-dimensional environment and react to therapy more physiologically. In this review, we discuss the relevance of main 3D culture systems in the study of potential approaches to overcome drug resistance and in the identification of personalized drug targets with the aim of developing patient-specific treatment strategies that can be put in place when resistance emerges.

ALKBH5 enhances lipid metabolism reprogramming by increasing stability of FABP5 to promote pancreatic neuroendocrine neoplasms progression in an m6A-IGF2BP2-dependent manner

The process of post-transcriptional regulation has been recognized to be significantly impacted by the presence of N6-methyladenosine (m6A) modification. As an m6A demethylase, ALKBH5 has been shown to contribute to the progression of different cancers by increasing expression of several oncogenes. Hence, a better understanding of the key targets of ALKBH5 in cancer cells could potentially lead to the development of new therapeutic targets. However, the specific role of ALKBH5 in pancreatic neuroendocrine neoplasms (pNENs) remains largely unknown. Here, we demonstrated that ALKBH5 was up-regulated in pNENs and played a critical role in tumor growth and lipid metabolism. Mechanistically, ALKBH5 over-expression was found to increase the expression of FABP5 in an m6A-IGF2BP2 dependent manner, leading to disorders in lipid metabolism. Additionally, ALKBH5 was found to activate PI3K/Akt/mTOR signaling pathway, resulting in enhanced lipid metabolism and proliferation abilities. In conclusion, our study uncovers the ALKBH5/IGF2BP2/FABP5/mTOR axis as a mechanism for aberrant m6A modification in lipid metabolism and highlights a new molecular basis for the development of therapeutic strategies for pNENs treatment.

Lipid metabolism as a target for cancer drug resistance: progress and prospects

Cancer is the world's leading cause of human death today, and the treatment process of cancer is highly complex. Chemotherapy and targeted therapy are commonly used in cancer treatment, and the emergence of drug resistance is a significant problem in cancer treatment. Therefore, the mechanism of drug resistance during cancer treatment has become a hot issue in current research. A series of studies have found that lipid metabolism is closely related to cancer drug resistance. This paper details the changes of lipid metabolism in drug resistance and how lipid metabolism affects drug resistance. More importantly, most studies have reported that combination therapy may lead to changes in lipid-related metabolic pathways, which may reverse the development of cancer drug resistance and enhance or rescue the sensitivity to therapeutic drugs. This paper summarizes the progress of drug design targeting lipid metabolism in improving drug resistance, and providing new ideas and strategies for future tumor treatment. Therefore, this paper reviews the issues of combining medications with lipid metabolism and drug resistance.

The role of organoids in cancer research

Organoids are established through in vitro 3D culture, and they can mimic the structure and physiological functions of organs or tissues in vivo. Organoids have attracted much attention in recent years. They can provide a reliable technology platform for cancer research and treatment and are a valuable preclinical model for academic research and personalized medicine. A number of studies have confirmed that organoids have great application prospects in new drug development, drug screening, tumour mechanism research, and precision medicine. In this review, we mainly focus on recent advances in the application of organoids in cancer research. We also discussed the opportunities and challenges facing organoids, hoping to indicate directions for the development of organoids in the future.