Translational cancer research最新文献

Background: Pheochromocytoma and paraganglioma, collectively known as PPGL, are categorized as neuroendocrine tumors with the potential for malignancy. Plasminogen activator, tissue type (PLAT) is a protein encoding gene that encodes tissue-type plasminogen activator, which converts plasminogen to plasmin. There is limited research on the association between PLAT and PPGL. Previous studies have only found that the expression level of PLAT protein is significantly increased in PPGL with deficient blood supply, and its role in the occurrence and progression of PPGL remains unclear and needs further clarification. The purpose of this study is to provide some new clues to elucidate the role of PLAT in PPGL, in order to better guide future research directions.

Methods: The PC-12 cell line was selected for this study, and lentivirus transfection technology was used to construct control and PLAT overexpression cell models. Transcriptomic information of PLAT regulation in PC-12 cells was obtained through RNA sequencing, and differentially expressed genes (DEGs) were screened using bioinformatics methods. The physiological functions and related signaling pathways of these genes were analyzed.

Results: After validating the overexpression cell model and performing quality control analysis on the transcriptome sequencing data, DEGs were identified. The Gene Ontology (GO) functional enrichment analysis of DEGs revealed significant enrichment in 46 GO functions, while the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed significant enrichment in seven pathways. It was found that these genes were significantly enriched in functional pathways associated with mitochondrial respiratory chain and energy metabolism.

Conclusions: This study provides some insights into the role of PLAT in pheochromocytoma and suggests directions for further research on its involvement in tumor development and angiogenesis. However, the specific regulatory mechanisms still require further validation.

Background: Multiple myeloma (MM) is a type of blood cancer, which rarely infiltrates the central nervous system (CNS) and lacks specific neurological symptoms. The prognosis is often poor, as the disease progresses rapidly. Herein, we present a rare case of MM with CNS involvement.

Case description: A 53-year-old man was admitted to the Neurosurgery Department, Jinhua Hospital Affiliated to Zhejiang University with initial symptoms of "blurred vision for 3 months accompanied by numbness on the right side of the face for 7 days". Enhanced cranial magnetic resonance imaging revealed a tumor deep in the right temporal bone. During exploratory surgery, the "fleshy" mass was completely removed. Postoperative pathology confirmed a diagnosis of "plasmacytoma with intermediate features". The patient received multiple systematic chemotherapy treatments after surgery in the department of hematology of Jinhua Hospital Affiliated to Zhejiang University. During a 10-month follow-up period, the patient's neurological symptoms improved, and his general condition was considered good.

Conclusions: This report summarizes the clinical features, diagnosis, treatment, and prognosis of a patient with MM involving the CNS and examines the relevant literature. This case may serve as a reference for future clinical treatment and diagnosis. Further research on the pathophysiology of such cases is warranted.

Background: Although the therapeutic effects of berberine have received some attention in recent years, its potential mechanisms underlying its action against stomach carcinoma (SC) remain unclear. In this study, we aimed to elucidate the mechanisms underlying the effects of berberine against SC using a network pharmacology and experimental verification approach.

Methods: Several publicly available databases were used to collect the targets of berberine and SC. Protein-protein interaction (PPI) network, enrichment analyses and molecular docking were performed based on the potential targets of berberine against SC. The potential clinical significance and prognostic value of the targets were predicted by using nomogram and receiver operating characteristic (ROC) analyses. Then the viability and apoptosis of SC cells treated with berberine were determined. Moreover, reactive oxygen species (ROS), mitochondrial membrane potential (MMP) and adenosine triphosphate (ATP) measurements and western blot assay were carried out to validate the predicted mechanisms.

Results: Seventy-six potential targets of berberine against SC were identified. The construction of PPI network enabled the identification of hub targets, such as AKT1, TP53, IL6, JUN and MAPK1. Enrichment analyses showed that berberine was involved in apoptosis, mitophagy, ROS metabolic process, AMPK and MAPK signaling pathway. The expression levels of hub targets also contributed to the clinical prognosis of patients with SC. Molecular docking revealed the possible patterns of direct interaction between berberine and target proteins, including AMPK, TP53 and MAPK1. Experimental results showed that berberine reduced SC cell viability, promoted apoptosis and ROS generation, and contributed to reductions in MMP and ATP levels. Western blot assay demonstrated that berberine increased AMPK and TP53 expression, while decreased phosphorylated-MAPK3/1 expression.

Conclusions: We elucidated the potential action mechanisms of berberine against SC using a network pharmacology approach. Some predicted mechanisms underlying the anti-SC effects were verified based on experimental approaches. Our findings provide a meaningful foundation for berberine as a cellular apoptosis-inducing and energy metabolism-regulating agent against SC. However, in vivo experiments and clinical studies need to be further carried out. Moreover, it is necessary to study the potential negative effects of berberine thoroughly.

Background: Bladder cancer (BC) is a life-threatening malignancy with high mortality rates. Current prognostic models are insufficient in accurately predicting clinical outcomes, impeding personalized treatment strategies. This study aimed to identify BC subtypes and prognostic gene sets by analyzing changes in immune and hallmark gene sets activity in tumor and adjacent non-tumor tissues to enhance patient outcomes.

Methods: Utilizing data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), gene set variation analysis (GSVA) was applied to C7 immune-related and hallmark gene sets from the Molecular Signatures Database (MSigDB). The CancerSubtype R package was utilized for clustering these gene sets into three categories, from which 109 candidate sets were identified using Venn diagrams. A refined subset of seven gene sets was selected through least absolute shrinkage and selection operator (LASSO) regression for the construction of a risk model. Model validity was confirmed with receiver operating characteristic (ROC) and calibration curves, and a nomogram was constructed to integrate risk scores with clinical parameters. Finally, genes from the gene sets of the model were acquired and analyzed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and protein-protein interactions (PPI) via plugin Molecular Complex Detection (MCODE) and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) in Cytoscape in both tumor and non-tumor tissues.

Results: Three BC subtypes were characterized by immunologic and hallmark gene sets, with subtype 1 patients showing worse survival. The prognostic model, based on seven gene sets, effectively stratified risk, with high-risk patients having significantly shorter survival. GO, KEGG, and PPI analyses indicated distinct influences of non-tumor and tumor tissues on the prognosis of BC patients.

Conclusions: We constructed and validated a novel prognostic model for risk stratification in BC based on immunologic and hallmark genes sets, which presents a novel perspective on rational treatment approaches and accurate prognostic evaluations for BC by considering both tumor and adjacent non-tumor tissues. This highlights the importance of focusing on alterations in both tumor and adjacent non-tumor tissues, rather than solely on the tumor itself.

Background: Bladder cancer is one of the most commonly diagnosed urinary cancers worldwide. Although muscle-invasive bladder cancer (MIBC) accounts for only 25% of bladder cancer cases, it has a high recurrence rate and poor prognosis, especially among high-grade cases. Despite the existence of some molecular markers, there is a clear clinical need for a robust recurrence prediction model that can assist in patient management and therapeutic decision-making. Therefore, we aimed to use public databases to develop such an effective assessment model.

Methods: We developed a recurrence risk assessment model for high-grade bladder cancer based on the clinical information of 217 cases from The Cancer Genome Atlas (TCGA) and profiles of 87 samples from GSE31684 in the Gene Expression Omnibus (GEO) database. Edge R was used to analyze differences between RNAs of bladder cancer in the TCGA database, with thresholds of P<0.05 and |log₂(fold change)| >1; least absolute shrinkage and selection operator (LASSO) Cox regression models were used to screen the RNAs significantly related to recurrence with minimum λ. Survival receiver operating characteristic (ROC) and area under the curve (AUC) was used to assess the predictive accuracy of the model in the training and validation sets of GSE31684.

Results: There were 2,876 differential RNAs obtained from TCGA data. Among a total of 284 RNAs identified as significantly related to recurrence of bladder cancer, 49 were obtained by LASSO regression, and 30 were finally obtained by multifactor risk regression to construct a risk assessment model. The model was found to predict the prognosis of bladder cancer recurrence well, with an AUC of 0.911 in the TCGA training set and an adjusted AUC value of 0.839 in the GEO validation set.

Conclusions: The recurrence assessment model is a relatively accurate recurrence prediction tool for high-grade bladder cancer and could provide a guidance for the treatment of bladder cancer.

Background and objective: Head and neck malignancies encompass a spectrum of malignant tumors occurring in the head and neck region, characterized by rapid progression, high recurrence rates, and dismal prognoses. Despite significant advancements in comprehensive surgery-based therapies, the 5-year survival rate for patients has not shown substantial improvement. There is an urgent need to investigate novel targeted therapies. With the advancements in epigenetics, RNA 5-methylcytosine (m⁵C) methylation, a prevalent form of RNA modification, has been identified by numerous studies as playing a pivotal role in the pathological processes of tumorigenesis and development. However, a comprehensive review within the realm of head and neck malignancies is currently lacking. This study aims to comprehensively review the biological implications of RNA m⁵C methylation regulators in the pathogenesis and progression of various systemic malignant tumors, with a specific focus on exploring the potential impact of RNA m⁵C methylation on head and neck malignancies.

Methods: A literature search on RNA m⁵C methylation and head and neck malignancies was conducted using PubMed, resulting in the inclusion of 46 relevant articles. The Cancer Genome Atlas (TCGA) database was utilized to analyze the correlation between m⁵C regulatory factors and clinicopathological features in patients with head and neck squamous cell carcinoma (HNSCC).

Key content and findings: Aberrant expression of RNA m⁵C methylation regulators is observed in head and neck malignancies, displaying a correlation with the clinicopathological grading of tumors.

Conclusions: RNA m⁵C methylation may contribute to the progression of head and neck malignancies and could be associated with an unfavorable prognosis for patients. These findings offer valuable insights for the development of targeted treatments for head and neck malignancies.

Background: Telomere-related genes (TRGs) are important in many different types of cancers. However, there is a lack of research on the relationship between their expression and prognosis in lung adenocarcinoma (LUAD) patients. This study is to investigate the prognostic value of TRGs in LUAD and to develop a TRG signature that can predict patient survival.

Methods: A total of 2,086 TRGs were obtained from a database of genes involved in telomere maintenance (TelNet), while the clinical information and tumor RNA expression profiles of 513 LUAD patients were acquired from The Cancer Genome Atlas (TCGA) database. Statistical methodologies, such as least absolute shrinkage and selection operator (LASSO)-Cox, were employed to construct a prognostic model with predictive capabilities.

Results: We analyzed 1,339 telomere-associated differentially expressed genes and identified a ten-gene predictive signature for LUAD. This signature exhibited effective prognostic classification capabilities across multiple datasets, including GSE3141 (58 samples), GSE8894 (63 samples), GSE50081 (127 samples), and GSE72094 (398 samples). Furthermore, we screened tumor-sensitive drugs targeting this signature. High telomere levels were associated with reduced survival in lung cancer patients who underwent surgery. Compared to the traditional TNM (tumor node metastasis classification) grading method, our telomere-associated gene panel demonstrated superior prediction accuracy. Notably, patients in the high-risk group, defined by the telomere-associated signature, exhibited improved responses to immunotherapy, suggesting potential benefits for this subgroup of patients.

Conclusions: This study presents a comprehensive molecular signature comprising TRGs, which holds potential for functional and therapeutic investigations. Additionally, it serves as an integrated tool to identify crucial molecules for immunotherapy in lung cancer.

Background: Association between plasma metabolites and pan-cancer remains controversial. Herein, we performed a two-sample Mendelian randomization (MR) analysis to verify whether there is a causal relationship between the two and to point the way for cancer metabolism research.

Methods: In our research, we downloaded 1,400 plasma metabolites from a large genome-wide association study (GWAS). We also obtained GWAS summary statistics for 24 types of cancers from the publicly available GWAS database, totaling 5,003,410 European individuals. We mainly used the fixed/random-effects inverse variance-weighted (IVW) method for two-sample MR analysis.

Results: In a combined sample of 291,202 cancer cases and 4,712,208 controls, a total of 55 plasma metabolites were identified as causally associated with nine types of cancer as a result of our MR analysis [P<0.05, false discovery rate (FDR) <0.2], including methionine sulfone, gamma-glutamylcitrulline, alliin, tetradecanedioate, hexadecanedioate, glutarate, ceramide, linolenoylcarnitine, hydroxypalmitoyl sphingomyelin, 1-palmitoyl-2-linoleoyl-glycerylphosphorylcholine (1-palmitoyl-2-linoleoyl-GPC), 3-acetylphenol sulfate, retinol (vitamin a) to linoleoyl-arachidonoyl-glycerol (18:2 to 20:4) ratio, etc. Reverse MR analysis revealed a causal relationship between lung cancer and the only plasma metabolite, 1-palmitoyl-2-linoleoyl-GPC (P<0.05, FDR <0.2).

Conclusions: Our study provides a comprehensive atlas of cancer-related plasma metabolites, offering possible targets for cancer detection, as well as a reference for future research on tumorigenesis mechanisms and therapeutic targets.

Background: Differences in patient populations and outcomes by hospital type are becoming increasingly relevant as health care systems shift to value-based care models. There is a paucity of literature on patient-level and hospital-level differences for patients with head and neck squamous cell carcinoma (HNSCC). The objective of this study was to examine differences in patient characteristics, surgical margins, and adjuvant therapy patterns for surgically treated HNSCC across different hospital types.

Methods: A statewide retrospective cohort study was conducted to examine differences in surgically treated patients with HNSCC by hospital type.

Results: A total of 579 surgically treated HNSCC patients with a mean age of 58.5 [standard deviation (SD) 10.7] years were included. There were 152 patients (26%) treated at academic hospitals, 205 (35%) at community cancer centers, and 222 (38%) at community hospitals. Patients at academic hospitals were more likely to travel farther for surgery (mean distance 43.6 miles for academic centers vs. 12.7 miles for community cancer centers vs. 12.6 miles for community hospitals; P<0.001) and have advanced T stage (T3-T4) at diagnosis (38% academic, 26% community cancer center, 26% community hospital; P=0.003). There was no significant difference in the positive surgical margin rate by hospital type (32.0% for academic hospitals, 32.1% for community cancer centers, and 35.0% for community hospitals; P=0.79). However, patients at academic hospitals were more likely to receive adjuvant chemoradiation even after adjusting for tumor stage and site [odds ratio (OR) 2.4, 95% confidence interval (CI): 1.2-5.0].

Conclusions: There are important patient-level and hospital-level differences for head and neck cancer management in academic versus community hospitals.

Background: Colorectal cancer (CRC) is a common malignancy, with high incidence and high mortality rates. Cuproptosis, a novel form of copper-induced programmed cell death, contributes to tumor progression. However, whether cuproptosis-related genes (CRGs) play a role in CRC remains unclear. This study aims to elucidate the role of CRGs in CRC development, patient prognosis, and immune response.

Methods: We performed bioinformatics analysis of the differential expression of CRGs between CRC and normal tissues. Least absolute shrinkage and selection operator (LASSO), and univariate and multivariate Cox analyses were employed to identify risk factors, which were used to construct a risk score model. Patients with CRC were categorized into high- and low-risk groups based on their median risk scores. Receiver operating characteristic curve analysis was used to verify the predictive accuracy of the risk model. A nomogram was developed for CRC through univariate and multivariate Cox regression analyses. The chemotherapeutic drug sensitivity was compared between patients with high and low CDKN2A/DLAT expression using the Wilcoxon rank-sum test. Spearman's correlation and TISIDB database analyses were conducted to determine relationships between CDKN2A or DLAT and immune cell infiltration.

Results: Eight of ten identified CRGs exhibited significant differential expression between CRC and normal tissues. Among the eight significant differential expression CRGs, CDKN2A and DLAT were identified as independent risk factors for predicting overall survival (OS) in CRC. Patients with CRC in the low-risk group had longer OS than those in the high-risk group. The risk score model had good predictive accuracy for OS. Based on CDKN2A, DLAT and some clinical characteristics, a prognostic nomogram was developed to predict OS for CRC patients and showed good predictive ability. CDKN2A and DLAT expressions were significantly associated with chemotherapeutic drug sensitivity and immune cell infiltration in CRC, and the molecular subtypes and immune subtypes differed between CDKN2A and DLAT.

Conclusions: Our research revealed the prognostic value of CRGs, particularly CDKN2A and DLAT, in CRC and demonstrated the relationship between CDKN2A/DLAT and immune infiltration in CRC, thereby contributing to the outcome evaluation of patients with CRC and identifying novel targets for CRC immunotherapy.