The Role of Erastin in Ferroptosis and Its Prospects in Cancer Therapy

Erastin was initially discovered as a small molecule compound that selectively kills tumor cells expressing ST and RASV12 and was later widely investigated as an inducer of ferroptosis. Ferroptosis is a recently discovered form of cell death caused by peroxidation induced by the accumulation of intracellular lipid reactive oxygen species (L-ROS) in an iron-dependent manner. Erastin can mediate ferroptosis through a variety of molecules including the cystine-glutamate transport receptor (system XC -), the voltage-dependent anion channel (VDAC), and p53. Erastin is able to enhance the sensitivity of chemotherapy and radiotherapy, suggesting a promising future in cancer therapy. We hope that this review will help to better understand the role of erastin in ferroptosis and lay the foundation for further research and the development of erastin-based cancer therapies in the future.

Clinical characteristics and prognostic value of MEX3A mRNA in liver cancer

BACKGROUND

MEX3A is an RNA-binding proteins (RBPs) that promotes the proliferation, invasion, migration and viability of cancer cells. The aim of this study was to explore the clinicopathological characteristics and prognostic significance of MEX3A mRNA expression in liver cancer.

METHODS

RNA-Seq and clinical data were collected from The Cancer Genome Atlas (TCGA). Boxplots were used to represent discrete variables of MEX3A. Chi-square tests were used to analyze the correlation between clinical features and MEX3A expression. Receiver operating characteristic (ROC) curves were used to confirm diagnostic ability. Independent prognostic ability and values were assessed using Kaplan-Meier curves and Cox analysis.

RESULTS

We acquired MEX3A RNA-Seq from 50 normal liver tissues and 373 liver cancer patients along with clinical data. We found that MEX3A was up-regulated in liver cancer which increased according to histological grade (p < 0.001). MEX3A showed moderate diagnostic ability for liver cancer (AUC = 0.837). Kaplan-Meier curves and Cox analysis revealed that the high expression of MEX3A was significantly associated with poor survival (OS and RFS) (p < 0.001). Moreover, MEX3A was identified as an independent prognostic factor of liver cancer (p < 0.001).

CONCLUSIONS

MEX3A expression shows promise as an independent predictor of liver cancer prognosis.

Glucometabolic Reprogramming in the Hepatocellular Carcinoma Microenvironment: Cause and Effect

Hepatocellular carcinoma (HCC) is a tumor that exhibits glucometabolic reprogramming, with a high incidence and poor prognosis. Usually, HCC is not discovered until an advanced stage. Sorafenib is almost the only drug that is effective at treating advanced HCC, and promising metabolism-related therapeutic targets of HCC are urgently needed. The "Warburg effect" illustrates that tumor cells tend to choose aerobic glycolysis over oxidative phosphorylation (OXPHOS), which is closely related to the features of the tumor microenvironment (TME). The HCC microenvironment consists of hypoxia, acidosis and immune suppression, and contributes to tumor glycolysis. In turn, the glycolysis of the tumor aggravates hypoxia, acidosis and immune suppression, and leads to tumor proliferation, angiogenesis, epithelial-mesenchymal transition (EMT), invasion and metastasis. In 2017, a mechanism underlying the effects of gluconeogenesis on inhibiting glycolysis and blockading HCC progression was proposed. Treating HCC by increasing gluconeogenesis has attracted increasing attention from scientists, but few articles have summarized it. In this review, we discuss the mechanisms associated with the TME, glycolysis and gluconeogenesis and the current treatments for HCC. We believe that a treatment combination of sorafenib with TME improvement and/or anti-Warburg therapies will set the trend of advanced HCC therapy in the future.

Investigation of the Clinical Significance and Prognostic Value of the lncRNA ACVR2B-As1 in Liver Cancer

A refined liver cancer staging system and effective prognostic prediction can help clinicians make optimized treatment decisions, which is essential in our fight against cancer and for improving the unsatisfying survival rate of liver cancer globally. The prognosis of liver cancer is not only related to tumor status, it is also affected by the patients' liver functions and the chosen treatment. Currently, several staging systems are being tested. Herein, we analyzed RNA-seq data from the TCGA database and identified a newly annotated lncRNA, ACVR2B-AS1, whose expression is upregulated in liver cancer. Higher ACVR2B-AS1 expression is an independent adverse prognostic factor for overall survival (OS) and relapse-free survival (RFS) in liver cancer patients. Our work suggests that the lncRNA ACVR2B-AS1 could be a candidate biomarker for liver cancer prognosis. Furthermore, ACVR2B-AS1 might serve as a potential therapeutic target, which is a possibility that is worthy of further study.

Lipocalin-1 Expression as a Prognosticator Marker of Survival in Breast Cancer Patients

PURPOSE

LCN1 (lipocalin-1), a gene that encodes tear lipocalin (or von Ebner's gland protein), is mainly expressed in secretory glands and tissues, such as the lachrymal and lingual gland, and nasal, mammary, and tracheobronchial mucosae. Analysis of the Cancer Genome Atlas (TCGA) Breast Carcinoma (BRCA) level 3 data revealed a relationship between LCN1 expression and survival in breast cancer patients.

METHODS

The χ2 test and Fisher exact test were applied to analyze the clinical data and RNA sequencing expression data, and the association between LCN1 expression and clinicopathologic features was determined. The receiver-operating characteristic (ROC) curve of LCN1 was drawn to assess its ability as a diagnostic marker, and the optimal cutoff value was obtained from the ROC curve to distinguish groups with high and low LCN1 expression. Cox regression was used to compare both groups, and a log-rank test was applied to calculate p values and compare the -Kaplan-Meier curves. Furthermore, GEO datasets were employed for external data validation.

RESULTS

Analysis of 1,104 breast cancer patients with a primary tumor revealed that LCN1 was overexpressed in breast cancer. High LCN1 expression was associated with clinicopathologic features and poor survival. Analyzing the area under the ROC curve (AUC) of LCN1, it was found that its diagnostic ability was limited. Multivariate analysis indicated that LCN1 expression is an independent predictor of survival in breast cancer patients. Through validation in GEO datasets, LCN1 expression was higher in tumor than normal tissue of the breast. High LCN1 expression was associated with poor survival in breast cancer patients.

CONCLUSIONS

High LCN1 expression is an independent prognosticator of a poor prognosis in breast cancer.

HN1 as a diagnostic and prognostic biomarker for liver cancer

BACKGROUND

The present study aimed to examine the diagnostic and prognostic value of HN1 in terms of overall survival (OS) and recurrence-free survival (RFS) in liver cancer and its potential regulatory signaling pathway.

METHODS

We obtained clinical data and HN1 RNA-seq expression data of liver cancer patients from The Cancer Genome Atlas database, and analyzed the differences and clinical association of HN1 expression in different clinical features. We uesd receiver-operating characteristic curve to evaluate the diagnosis capability of HN1. We analyzed and evaluated the prognostic significance of HN1 by Kaplan-Meier curves and Cox analysis. Gene Set Enrichment Analysis (GSEA) was used to identify signaling pathways related to HN1 expression.

RESULTS

HN1 mRNA was up-regulated in liver cancer, and was associated with age, histologic grade, stage, T classification, M classification, and vital status. HN1 mRNA had ideal specificity and sensitivity for the diagnosis (AUC = 0.855). Besides, the analysis of Kaplan-Meier curves and Cox model showed that HN1 mRNA was strongly associated with the overall survival and could be well-predicted liver cancer prognosis, as an independent prognostic variable. GSEA analysis identified three signaling pathways that were enriched in the presence of high HN1 expression.

CONCLUSION

HN1 serves as a biomarker of diagnosis and prognosis in liver cancer.

PVT1 Expression Is a Predictor for Poor Survival of Prostate Cancer Patients

OBJECTIVE

Dysregulation of long noncoding RNA is associated with a variety of cancers and LncRNA has anticancer or carcinogenic activities. PVT1, as a long noncoding RNA, plays an important role in the development of cancer.

METHODS

We use R to download and analyze the data in TCGA database. ROC curve is generated to evaluate the significance of PVT1 expression for the diagnosis of prostate cancer. Chi-square test is used to test correlation between PVT1 expression and clinical pathological features. Survival curve and univariate and multivariate cox regression analysis is performed to compare differences in the effect on the survival rate between PVT1 high expression and low expression.

RESULTS

The expression of PTV1 in tumor tissues was significantly higher than that in normal tissues(P<2.2e-16). The difference of PTV1 expression was observed according to vital status (P = 0.0051) and Gleason score (P = 0.0012). The expression of PTV1 is significantly associated with T classification (P < 0.0001), N classification (P = 0.0499), PSA (P = 0.0001), Gleason Score (P < 0.0001), targeted molecular therapy (P = 0.0264) and vital status(P = 0.0036). The area under the ROC curve (AUC) was 0.860, which revealed PTV1 expression has excellent diagnostic value in prostate cancer. Patients with high PVT1 expression had a worse prognosis.

CONCLUSIONS

PVT1 expression may be a biomarker for the diagnosis and prognosis of prostate cancer.

Long non-coding RNA BACE1-AS is an independent unfavorable prognostic factor in liver cancer

Liver cancer is one of the leading causes of cancer-associated deaths with incidence rates continuously on the rise. Biomarkers are urgently required for early diagnosis and better prognostic classification, which is essential for risk stratification and optimizing treatment strategies in clinical settings. By analyzing the data extracted from The Cancer Genome Atlas database using R, the long noncoding RNA (lncRNA) β-site APP-cleaving enzyme 1 antisense (BACE1-AS) was discovered to have both high diagnostic and prognostic values in liver cancer, which could serve as a promising biomarker in clinical settings. Precisely, lncRNA BACE1-AS is significantly overexpressed in liver cancer and its levels vary within different subgroups, suggesting its tumorigenic role. Furthermore, higher BACE1-AS predicts poorer overall survival and relapse-free survival outcomes. Overall, the present study demonstrated that BACE1-AS may be involved in liver cancer progression and could serve as a promising biomarker for diagnosis and prognostic evaluation.

GPSM2 Serves as an Independent Prognostic Biomarker for Liver Cancer Survival

BACKGROUND AND OBJECTIVE

Liver cancer is a malignancy with a poor prognosis. G protein signaling modulator 2 is mainly related to cell division and cell cycle regulation. In this review, the relationship between G protein signaling modulator 2 and clinical characteristics of patients with liver cancer has been explored, especially with respect to its prognostic value.

METHODS

G protein signaling modulator 2 messenger RNA expression and clinicopathological characteristics of patients with liver cancer were obtained from The Cancer Genome Atlas. The expression level of G protein signaling modulator 2 RNA-Seq was validated by using Gene Expression Omnibus. Chi-square test was performed to evaluate the relationship between G protein signaling modulator 2 expression and clinical characteristics. The threshold value of G protein signaling modulator 2 in the diagnosis of liver cancer was evaluated by a receiver-operating characteristic curve. Cox regression analysis and Kaplan-Meier curves were performed to evaluate the relationship between G protein signaling modulator 2 and liver cancer prognosis, which included overall and residual-free survival, and explored the prognostic value of G protein signaling modulator 2. Liver cancer survival analyses were validated by using the data of G protein signaling modulator 2 RNA-Seq from the International Cancer Genome Consortium.

RESULTS

The expression level of G protein signaling modulator 2 messenger RNA was remarkably higher in liver cancer than that in healthy tissues (P < 2.2 × e-16), which was also validated by data from the GSE14520 database. In addition, high G protein signaling modulator 2 expression significantly correlated with histological grade (P = .020), vital status (P < .001), clinical (P = .001), and T stage (P = .001). The receiver-operating characteristic curves showed G protein signaling modulator 2 to be an advantageous diagnostic molecule for liver cancer (area under curve = 0.893). Furthermore, the results of Cox analysis and Kaplan-Meier curves suggested that the upregulation of G protein signaling modulator 2 expression is linked to poor prognosis and G protein signaling modulator 2 messenger RNA could be an independent predictor for liver cancer, which was validated by data from the International Cancer Genome Consortium database.

CONCLUSIONS

G protein signaling modulator 2 messenger RNA was overexpressed in liver cancer, and G protein signaling modulator 2 is an independent prognostic factor. G protein signaling modulator 2 is expected to be a treatment target for cancer.

Ubiquitin-like modifier-activating enzyme 7 as a marker for the diagnosis and prognosis of breast cancer

Ubiquitin-like modifier-activating enzyme 7 (UBA7) is a specific E1-like ubiquitin-activating enzyme involved in interferon-stimulated gene 15 (ISG15) conjugation. UBA7 expression has been reported to be notably decreased in lung cancer. The present study aimed to investigate the changes in UBA7 expression in breast cancer and the association between UBA7 expression and clinical characteristics, and to elucidate the diagnostic and prognostic significance of UBA7 in breast cancer. The clinical data and RNA-sequencing expression values of 1,104 patients with breast cancer were downloaded from The Cancer Genome Atlas database. The associations between UBA7 expression and clinical characteristics were determined using χ2 and Fisher's exact tests. UBA7 expression values were divided into low and high groups using the optimal cut-off value, as determined by the overall survival (OS) value identified via a receiver operating characteristic (ROC) curve analysis, to further study the association between UBA7 expression and clinical characteristics. The diagnostic capability of UBA7 was assessed via ROC analysis, and Kaplan-Meier curve and Cox regression analyses were performed to determine the prognostic value of UBA7. The results demonstrated that UBA7 expression was decreased in breast cancer, and significant differences were observed between groups with regards to vital status, tumor classification, metastasis classification, histological type, sex, molecular subtype, and expression levels of progesterone receptor, estrogen receptor (ER) and human epidermal growth factor receptor 2. Low and high UBA7 expression levels were associated with age, ER expression, menopause status, Tumor-Node-Metastasis classification stage, margin status, vital status, radiation therapy use, OS and relapse-free survival. Furthermore, patients with low UBA7 expression levels had a poor prognosis. UBA7 expression also demonstrated an ability to diagnose patients at all clinical stages. Taken together, the results indicated that UBA7 expression was significantly decreased in breast cancer, and was associated with clinical characteristics and prognosis. Thus, UBA7 can be deemed as a potential biomarker in breast cancer, and may serve as a target in treatment.

Downregulated mRNA Expression of ZNF385B Is an Independent Predictor of Breast Cancer

BACKGROUND

ZNF385B, a zinc finger protein, has been known as a potential biomarker in some neurological and hematological studies recently. Although numerous studies have demonstrated the potential function of zinc finger proteins in tumor progression, the effects of ZNF385B in breast cancer (BC) are less studied.

METHODS

The Oncomine database and "ESurv" tool were used to explore the differential expression of ZNF385B in pan-cancer. Furthermore, data of patients with BC were downloaded from The Cancer Genome Atlas (TCGA). The receiver operating characteristic (ROC) curve of ZNF385B expression was established to explore the diagnostic value of ZNF385B and to obtain the cut-off value of high or low ZNF385B expression in BC. The chi-square test as well as Fisher exact test was used for identification of the relationships between clinical features and ZNF385B expression. Furthermore, the effects of ZNF385B on BC patients' survival were evaluated by the Kaplan-Meier and Cox regression. Data from the Gene Expression Omnibus (GEO) database were employed to validate the results of TCGA. Protein expression of ZNF385B in BC patient specimens was detected by immunohistochemistry (IHC) staining.

RESULTS

ZNF385B expression was downregulated in most types of cancer including BC. Low ZNF385B expression was related with survival status, overall survival (OS), and recurrence of BC. ZNF385B had modest diagnostic value, which is indicated by the area under the ROC curve (AUC = 0.671). Patients with lower ZNF385B expression had shorter OS and RFS (relapse-free survival). It had been demonstrated that low ZNF385B expression represented independent prognostic value for OS and RFS by multivariate survival analysis. The similar results were verified by datasets from the GEO database as well. The protein expression of ZNF385B was decreased in patients' samples compared with adjacent tissues by IHC.

CONCLUSIONS

Low ZNF385B expression was an independent predictor for worse prognosis of BC patients.

SLC25A11 serves as a novel prognostic biomarker in liver cancer

Liver cancer is a disease with high mortality; it is often diagnosed at intermediate and advanced stages and has a high recurrence rate. ROS restriction and adequate energy supply play significant roles in liver cancer. SLC25A11, a member of the malate-aspartate shuttle (MAS), regulates electroneutral exchange between 2-oxoglutarate and other dicarboxylates. It transports glutathione (GSH) from the cytoplasm into mitochondria to maintain GSH levels to limit ROS production. Moreover, SLC25A11 is essential for ATP generation in cancers as it regulates NADH transportation from the cytoplasm to mitochondria. The purpose of this research was to investigate the prognostic value of SLC25A11 in liver cancer. The Cancer Genome Atlas database was used to analyze the levels of SLC25A11 in liver cancer. Fisher's exact and chi-square tests were used to evaluate the relationship between SLC25A11 expression and clinical characteristics. Finally, we explored the value of SLC25A11 in prognosis by Cox analysis and Kaplan-Meier curves. Our results revealed that SLC25A11 was downregulated in liver cancer compared to normal controls. Low expression of SLC25A11 was associated with clinical stage, vital status, histologic grade, overall survival (OS) and relapse-free survival (RFS). Liver cancer patients with low SLC25A11 expression had shorter OS and RFS than patients with high SLC25A11 expression. Multivariate analysis showed that the expression of SLC25A11 was an independent predictor of RFS and OS. In conclusion, this study identified that SLC25A11 serves as a new prognostic marker for liver cancer.

Expression and clinical significance of BDH1 in liver cancer

Liver cancer is a deadly disease with generally poor patient outcomes. BDH1 is a key enzyme that regulates the metabolism and synthesis of ketone bodies. This study sought to explore the prognostic relevance of BDH1 mRNA expression in liver cancer.We utilized the Cancer Genome Atlas datasets to analyze the relationship between BDH1 expression and clinical outcomes. We used Kaplan-Meier curves and Cox analyses to explore the relevance of BDH1 mRNA levels to patient prognosis. Further gene set enrichment analysis was conducted as a means of comparing differences in gene expression as a function of BDH1 expression.Liver cancer samples exhibited significantly decreased BDH1 mRNA expression, and that this downregulation was correlated with a number of clinicopathological variables including gender, histologic grade, stage, TNM classification, and both overall and relapse-free survival. We further determined that BDH1 mRNA expression was an independent predictor of liver cancer patient prognosis. A subsequent gene set enrichment analysis found genes affected by BDH1 expression to be those enriched in pathways relating to MYC and wnt/β-catenin signaling.Our preliminary findings demonstrate for the first time that low expression of BDH1 mRNA is a potentially valuable independent prognostic indicator for liver cancer detection.

Risk and management of adverse events in minimally invasive esophagectomy

Minimally invasive esophagectomy (MIE) has transformed esophageal surgery by reducing morbidity, accelerating recovery, and improving postoperative outcomes compared to traditional open esophagectomy. By utilizing techniques such as laparoscopic, thoracoscopic, and robotic-assisted approaches, MIE minimizes surgical trauma while maintaining oncological thoroughness. However, it also presents unique challenges, including risks of complications such as anastomotic leakage, pulmonary complications, and atrial fibrillation. Zhong et al developed and validated a risk stratification model for predicting surgical adverse events after MIE, enhancing preoperative assessment and patient management. This editorial further examines the advantages of MIE, its comparable oncological and long-term outcomes, as well as the incidence and contributing factors of postoperative complications. Emerging technologies, including machine learning models, intraoperative nerve monitoring, and robotic-assisted surgery, are highlighted as innovative solutions for risk prediction and prevention. Strategies such as enhanced recovery after surgery protocols and multidisciplinary collaboration are emphasized for their critical roles in minimizing complications and optimizing patient outcomes. By addressing these aspects, this editorial provides guidance to surgical teams in maximizing the benefits of MIE while effectively managing its associated risks.

Biomaterial-based drug delivery: evaluating the safety profiles of liposomal Vyxeos

Vyxeos, a liposomal combination of cytarabine and daunorubicin, has improved survival outcomes for patients with high-risk acute myeloid leukemia (AML). However, its safety profile in real-world settings requires comprehensive evaluation. This study aims to assess the adverse event profiles associated with Vyxeos using data from the U.S. FDA's Adverse Event Reporting System (FAERS). A retrospective analysis of adverse event reports from the FAERS database was conducted for Vyxeos from January 2017 to June 2024. Reports were analyzed to assess patient demographics, system organ classes (SOCs), and preferred terms (PTs). Signal detection analysis was performed using disproportionality metrics, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS). A total of 1,036 reports were analyzed. The most frequently reported adverse events were hematologic (37.73%), infectious (28.42%), and cardiac disorders (13.22%). Febrile neutropenia, neutropenic sepsis, and pneumonia fungal were the most commonly reported events, with febrile neutropenia showing a strong association (ROR = 92.18). Males had a higher frequency of infectious events, while females reported more cardiac events. Most adverse events occurred within 30 days of treatment initiation, and 16.92% of reports involved hospitalization, while 18.33% reported death. Vyxeos is associated with significant hematologic, infectious, and cardiac adverse events. Close monitoring, infection prophylaxis, and cardiac assessments are recommended for patients receiving Vyxeos. Further research is needed to validate these findings and explore the mechanisms underlying the observed toxicities.

Mendelian randomization study on the causal relationship between food and cholelithiasis

BACKGROUND

Cholelithiasis, commonly referred to as gallstones, is a prevalent medical condition influenced by a combination of genetic factors, lifestyle choices, and dietary habits. Specific food items have been associated with an increased susceptibility to cholelithiasis, whereas others seem to offer a protective effect against its development.

METHODS

In this study, we conducted a Mendelian randomization (MR) analysis using a large-scale genetic dataset comprising individuals with European ancestry to explore the potential causal relationship between diet and cholelithiasis. The analysis incorporated 17 food-related variables, which were considered as potential factors influencing the occurrence of this condition.

RESULTS

Our findings indicate that a higher consumption of cooked vegetables, dried fruit, and oily fish is associated with a reduced risk of cholelithiasis. Conversely, a higher consumption of lamb is associated with an increased risk of developing the condition. Importantly, these associations proved robust to sensitivity and heterogeneity tests, and the pleiotropic test results further supported the hypothesis of a causal relationship between diet and cholelithiasis.

CONCLUSION

Through our study, we provide compelling evidence for the existence of a causal relationship between diet and cholelithiasis. Adopting a dietary pattern enriched with cooked vegetables, dried fruit, and oily fish, while minimizing lamb intake, may contribute to the prevention of cholelithiasis. Recognizing diet as a modifiable risk factor in the prevention and management of this condition is of paramount importance, and our study offers valuable insights in this regard.

Genetic and environmental factors influencing Crohn's disease

This editorial discusses Pellegrino and Gravina's essay. Crohn's disease (CD) is a complex and multifactorial disease that is influenced by a combination of genetic and environmental factors. While genetic factors play a key role in the development of the disease, environmental factors also play a significant role in influencing the risk of developing CD. By looking at present understanding of CD pathogenesis, we emphasize the important factors involved in the development of this illness, such as nucleotide-binding oligomerization domain-2, smoking, and vitamin D. Understanding the interplay between genetic and environmental factors is crucial for developing effective strategies for preventing and treating this chronic inflammatory bowel disease.