Translational cancer research最新文献

{"title":"Pathomics signatures and cuproptosis-related genes signatures for prediction of prognosis in patients with hepatocellular carcinoma.","authors":"Xiaoliang Li, Lina Li, Nan He, Dan Kou, Shizhao Chen, Hui Song, Xiang Yan","doi":"10.21037/tcr-24-350","DOIUrl":"https://doi.org/10.21037/tcr-24-350","url":null,"abstract":"<p><strong>Background: </strong>Hepatocellular carcinoma (HCC) is a common malignant tumor with high heterogeneity and poor prognosis, so early prediction and treatment are still difficult. Cuproptosis is a newly discovered type of programmed cell death that has been shown to be closely related to the occurrence and progression of HCC. Cancer morphology is influenced by genetic drivers, and computational pathology methods typically use tissue images such as entire slide images as input to predict clinical or genetic features. Therefore, the comprehensive analysis of pathological features and genomic data provides a feasible way to explore the potential mechanism of the tumor. The objective of this study was to develop a prediction model for HCC prognosis based on the pathomics signatures (PS) and the genomics signatures (GS).</p><p><strong>Methods: </strong>A dataset comprising 315 HCC patients was randomly divided into a training set (n=200) and a validation set (n=115). Prognostic models related to PS and GS were constructed by univariate and multivariate Cox regression analyses and least absolute shrinkage and selection operator (LASSO) regression analysis. Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curve, univariate and multivariate Cox analyses, and nomogram were used to evaluate the predictive performance of the prognostic model. The prognostic value of the model was internally validated.</p><p><strong>Results: </strong>A prognostic model incorporating clinical features, PS, and GS was developed using Cox regression analysis and LASSO regression analyses. Kaplan-Meier survival analysis revealed statistically significant differences in survival time between high-risk and low-risk subgroups in both the training and validation datasets (PS: P=0.003 and <0.001, respectively; GS: P=0.008 and 0.004, respectively). The time-dependent ROC curve showed favorable predictive value for survival in both the training and validation sets. The area under the ROC curves at 1, 3, and 5 years was 0.750, 0.830, and 0.870 in the training set, and 0.780, 0.810, and 0.760 in the validation set, respectively. A nomogram model based on the risk model score could effectively predict the survival probability of HCC patients. The calibration curves further demonstrated the good predictive capability of the nomogram model.</p><p><strong>Conclusions: </strong>The prognostic model incorporating PS and GS could effectively predict the prognosis of HCC patients.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 10","pages":"5473-5483"},"PeriodicalIF":1.5,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11543060/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142628705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Establishment and verification of a prognostic immune cell signature-based model for breast cancer overall survival.","authors":"Hailong Liu, Hongguang Bao, Jingying Zhao, Fangxu Zhu, Chunlei Zheng","doi":"10.21037/tcr-24-1829","DOIUrl":"https://doi.org/10.21037/tcr-24-1829","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Breast cancer (BRCA) is a prevalent and aggressive disease. Despite various treatments being applied, a significant number of patients continue to experience unfavorable prognoses. Accurate prognosis prediction in BRCA is crucial for tailoring individualized treatment plans and improving patient outcomes. Recent studies have highlighted the significance of immune cell infiltration in the tumor microenvironment (TME), but predicting survival remains challenging due to the heterogeneity of BRCA. The aim of this study was thus to produce an immune cell signature-based framework capable of predicting the prognosis of patients with BRCA.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The GSE169246 dataset was from the Gene Expression Omnibus (GEO) database, comprising single-cell RNA sequencing (scRNA-seq) data from 95 individuals with BRCA. Seurat, principal component analysis (PCA), the unified matrix polynomial approach (UMAP) algorithm, and linear dimensionality reduction were used to determine the heterogeneity of T cells. Overlapping analysis of differentially expressed genes (DEGs), genes associated with prognosis, and T-cell pharmacodynamics-related genes were used to obtain the T-cell core pharmacodynamics-related genes. The dimensionality of the T-cell core pharmacodynamics-related genes was reduced employing the least absolute shrinkage and selection operator (LASSO) Cox regression model and the LASSO model. The prognostic model was built via a Cox analysis of the overall survival (OS) information. The clinical sample included 95 patients with BRCA who underwent surgical treatment from October 2018 to October 2021 at the Second Affiliated Hospital of Qiqihar Medical University. Patients were divided into a good prognosis group and a poor prognosis group based on their prognostic outcomes. The predictive value of tumor characteristics and immune responses was validated through correlation analysis, logistic regression analysis, and receiver operating characteristic (ROC) analysis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A group of 95 genes was used to establish a prognostic model. In the GEO clinical sample, with a high-risk group demonstrating shorter median survival times (2,447 &lt;i&gt;vs&lt;/i&gt;. 6,498 days, P=4.733e-12). Area under the curve (AUC) values of 0.75, 0.75, and 0.72 were obtained for 2-, 4-, and 6-year OS predictions, respectively. Clinical validation found that the 6-year OS of the favorable prognosis group was significantly higher than that of the unfavorable prognosis group (92.06% &lt;i&gt;vs&lt;/i&gt;. 65.62%; P=0.005). Poor prognosis was positively correlated with age, tumor size, B-cell level, and CTLA4 level and negatively correlated with tumor stage (T1/T2), lymph node metastasis stage (N0), clinical stage I-II, CD3&lt;sup&gt;+&lt;/sup&gt;T-cell, CD4&lt;sup&gt;+&lt;/sup&gt;T-cell, CD8&lt;sup&gt;+&lt;/sup&gt;T-cell, neutrophil, lymphocyte, natural kill cell, TIGIT expression and OS. The combined model of clinical parameters had an AUC value of 0.898.&lt;/p&gt;&lt;p&gt;&lt;strong","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 10","pages":"5600-5615"},"PeriodicalIF":1.5,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11543049/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142627302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prognostic impact of concordant and discordant bone marrow involvement on diffuse large B-cell lymphoma.","authors":"Huaqin Zuo, Xiaoyan Xie, Xing Sun, Hanxue Shi, Xiaoping Pei, Mei Sun","doi":"10.21037/tcr-24-238","DOIUrl":"https://doi.org/10.21037/tcr-24-238","url":null,"abstract":"<p><strong>Background: </strong>In diffuse large B-cell lymphoma (DLBCL), bone marrow (BM) involvement includes two types that are concordant involvement and discordant involvement. It has been reported that concordant BM involvement has a worse prognosis than discordant involvement in previous studies. However, the prognostic effects of concordant or discordant BM involvement on DLBCL still need further research. In this work, DLBCL cases with BM involvement were collected and analyzed to better reflect the prognostic implications of concordant and discordant BM involvement.</p><p><strong>Methods: </strong>We reviewed the cases with newly diagnosed DLBCL and BM involvement from April 2018 to April 2022 in Northern Jiangsu People's Hospital. Overall survival (OS) and progression-free survival (PFS) were accessed by the Kaplan-Meier method and compared between groups by the log-rank test. A multivariate regression analysis based on Cox proportional hazard model was used to test the independent effect of each variable on survival.</p><p><strong>Results: </strong>In total, 32 patients were included and 15 (46.9%) patients had concordant BM involvement and 17 (53.1%) patients had discordant BM involvement. Compared with the discordant group, the concordant group tended to be older and had elevated lactate dehydrogenase level. The outcome of patients with concordant BM involvement was worse than the discordant subset, including OS (P=0.04) and PFS (P=0.03). Furthermore, the discordant BM involvement was excluded to acquire a BM-adjusted International Prognostic Index (IPI) score. The significance of BM-adjusted IPI scores to predict OS was improved greatly compared with the previous IPI scores (P=0.053 <i>vs.</i> P=0.16). Multivariate analysis showed that the BM-adjusted IPI was an independent predictor for OS [hazard ratio =3.406; 95% confidence interval (CI): 1.145-10.127; P=0.03].</p><p><strong>Conclusions: </strong>These results highlight the requirement for identifying BM infiltration type accurately and then adjusting the IPI score by excluding discordant BM involvement since concordant involvement can partly predict a poor prognosis of DLBCL with BM involvement other than discordant involvement.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 10","pages":"5339-5346"},"PeriodicalIF":1.5,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11543059/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142628707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Harnessing transcriptomics and immune cell biology to predict response to checkpoint blockade.","authors":"Akshay J Patel","doi":"10.21037/tcr-24-1322","DOIUrl":"https://doi.org/10.21037/tcr-24-1322","url":null,"abstract":"","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 10","pages":"5162-5164"},"PeriodicalIF":1.5,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11543028/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142628026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"HDAC1: a promising target for cancer treatment: insights from a thorough analysis of tumor functions.","authors":"Jiaojiao Xie, Rui Liu, Ying Cai, Dina Liu","doi":"10.21037/tcr-24-23","DOIUrl":"https://doi.org/10.21037/tcr-24-23","url":null,"abstract":"<p><strong>Background: </strong>Many significant findings from recent studies have revealed the significance of histone deacetylase 1 (HDAC1) in the development of tumors and its strong association with tumor prognosis; these studies have mainly focused on one single cancer such as in lung cancer, breast cancer, and hepatocellular carcinoma (HCC). To date, there has been no comprehensive analysis and pan-analysis conducted from the overall perspective of cancer across all types. Hence, we analyzed public databases, conducted tube formation assay, and immunohistochemistry (IHC) staining of HDAC1 on six kinds of clinical samples to explore the prognostic and oncogenic effects of HDAC1 on 33 tumors for the first time. There currently remains a lack of efficient testing methods, therapies, and diagnostic and prognostic markers of tumor formation and development in different tumors.</p><p><strong>Methods: </strong>Our initial objective was to investigate the possible cancer-causing functions of HDAC1 in 33 different types of tumors by utilizing The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and many different online websites, such as Tumor IMmune Estimation Resource 2 (TIMER2), Gene Expression Profiling Interactive Analysis 2 (GEPIA2), Genotype Tissue Expression (GTEx) database, Clinical Proteomic Tumor Analysis Consortium (CPTAC) dataset, and University of ALabama at Brimingham CANcer data analysis portal (UALCAN) tool, and so on. We even used small interfering RNA (siRNA) to knock down HDAC2 in HCC cell lines. IHC of HDAC1 was performed.</p><p><strong>Results: </strong>HDAC1 exhibited high expression in numerous tumors, and strong correlations were observed between the messenger RNA (mRNA) levels of HDAC1 and the prognosis of individuals diagnosed with tumors. Human umbilical vein endothelial cells (HUVECs) tube formation and migration were significantly inhibited by conditioned media from HCC cells treated with siRNA of HDAC1. Several types of cancer have been found to exhibit elevated levels of phosphorylation at S421. Furthermore, as in bladder urothelial carcinoma (BLCA), breast invasive carcinoma (BRCA), and kidney renal papillary cell carcinoma (KIRP), HDAC1 expression was found to be correlated with inflammatory cell infiltration.</p><p><strong>Conclusions: </strong>The levels of HDAC1 are expected to adapt to clinical adjuvant targeted therapy in most types of solid cancer.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 10","pages":"5300-5315"},"PeriodicalIF":1.5,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11543092/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142628029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Up-regulation of MSMO1 was associated with poor survival in cervical cancer.","authors":"Jing Zou, Sha Liu, Jian Long","doi":"10.21037/tcr-24-243","DOIUrl":"https://doi.org/10.21037/tcr-24-243","url":null,"abstract":"<p><strong>Background: </strong>Methylsterol monooxygenase 1 (MSMO1) catalyzes C4-methylsterols demethylation in cholesterol biosynthesis pathway. MSMO1 is increased and up-regulation of MSMO1 is correlated with progression of some tumor. But the correlation of MSMO1 to cervical cancer is unknown. The current study aimed to explore the expression pattern of MSMO1 in cervical cancer and its correlation to clinical characteristics.</p><p><strong>Methods: </strong>In this study, 306 cervical cancer cases and 13 non-tumor cases were included. We compared MSMO1 expression level in non-tumor cervical tissues and cervical cancer samples using the Wilcoxon rank sum test. Univariate regression was used to investigate the correlation between MSMO1 expression as well as other clinical characteristics and prognosis. Clinical characteristics associated with prognosis in univariate analysis were used as adjustments for multivariate analysis to further validate the relationship between MSMO1 expression and cervical cancer prognosis. Patients' survival in different subgroups was compared by Kaplan-Meier (KM) method. The potential protein interaction was analyzed. T cell infiltration level in MSMO1 high and low group patients was compared.</p><p><strong>Results: </strong>MSMO1 expression level was up-regulated in cervical cancer (P<0.001). Patients who had stage III-IV diseases (P=0.04) and did not achieve complete response after primary treatment had higher MSMO1 expression (P<0.001). High MSMO1 expression patients showed a lower overall survival (OS) (P=0.004), disease-specific survival (DSS) (P=0.004) and progression-free survival (PFS) (P=0.002). High MSMO1 expression was a risk factor to OS (P=0.01), DSS (P=0.009) and PFS (P=0.009). Multiple variate analysis showed that high MSMO1 expression was an independent risk factor to OS [hazard ratio (HR) =1.902, 95% confidence interval (CI): 1.156-3.129, P=0.01], DSS (HR =2.172, 95% CI: 1.210-3.897, P=0.009) and PFS (HR =1.975, 95% CI: 1.189-3.282, P=0.009) in cervical squamous cell carcinoma (CESC). The prognostic value of high MSMO1 expression was further examined in other databases, including KM-plotter, Gene Expression Profiling Interactive Analysis (GEPIA) and Gene Expression Omnibus (GEO) database.</p><p><strong>Conclusions: </strong>The current research showed that MSMO1 was increased and was associated with poor prognosis in CESC.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 10","pages":"5316-5327"},"PeriodicalIF":1.5,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11543037/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142628800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Screening of potential key pathogenic and intervention targets of low-grade glioma based on bioinformatics.","authors":"Lizhi Yi, Wenlong Kong, Zhisong Jiu, Zhengxian Huang, Peng Na, Wei Chen, Xilong Yin","doi":"10.21037/tcr-24-1662","DOIUrl":"https://doi.org/10.21037/tcr-24-1662","url":null,"abstract":"<p><strong>Background: </strong>Sialic acid-binding immunoglobulin-like lectin 8 (<i>SIGLEC8</i>) is involved in the progression of numerous diseases. This study aimed to examine the relationship between <i>SIGLEC8</i> and the prognosis of patients with low-grade glioma (LGG) and the related mechanisms.</p><p><strong>Methods: </strong>First, screening of the differentially expressed genes (DEGs) <i>SIGLEC8</i> in The Cancer Genome Atlas (TCGA) database was performed. The expression was then correlated with the prognosis of patients with LGG and then verified using the Tumor Immune Estimation Resource (TIMER) and TCGA databases. Cox regression was employed to conduct multifactorial analysis and was followed by the construction of an internally validated nomogram based on these results. To investigate the possible mechanisms, we used gene set enrichment analysis (GSEA). We conducted a retrospective analysis of the clinical information of patients with LGG who were treated at Longgang Central Hospital of Shenzhen from January 2018 to December 2020 and from whom tumor and peritumoral tissues were taken during surgery. Expression of essential genes was identified by employing quantitative real-time polymerase chain reaction (qRT-PCR). Multivariate analysis, via Cox regression, was employed to determine the prognostic factors for patients with LGG.</p><p><strong>Results: </strong>The transcriptional activity of <i>SIGLEC8</i> was found to be elevated in LGG neoplastic tissues compared to neighboring nonneoplastic tissues. Overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) were improved in patients with LGG with reduced expression of <i>SIGLEC8</i> as compared to those with increased expression of <i>SIGLEC8</i>. The nomogram's C-index is 0.804 (0.781-0.827). indicating good predictive accuracy. GSEA revealed that <i>SIGLEC8</i> might influence LGG biological events by participating in the PD-1, IL3, JAK/STAT, and PI3KCI signal transduction pathways, as well as cytokine and inflammatory response, cell cycle, homeostasis, and extracellular matrix. This study included 72 patients with LGG. qRT-PCR showed upregulated <i>SIGLEC8</i> expression in LGG tumor tissues, which was significantly associated with tumor number and metastasis to the lymph nodes (P<0.05). Multivariate analysis using Cox regression identified the high expression of <i>SIGLEC8</i> as an independent risk factor in LGG prognosis (P<0.05).</p><p><strong>Conclusions: </strong>For the prognosis of patients with LGG, the transcriptional activity of <i>SIGLEC8</i> is increased in LGG tissues and is an independent risk factor. Interference with <i>SIGLEC8</i> could promote tumor progression by regulating the JAK/STAT signaling pathway, indicating that <i>SIGLEC8</i> may function as a distinctive predictive biomarker for patients with LGG.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 10","pages":"5563-5573"},"PeriodicalIF":1.5,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11543039/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142628723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"<i>PYGL</i> regulation of glycolysis and apoptosis in glioma cells under hypoxic conditions via HIF1α-dependent mechanisms.","authors":"Tingyu Cao, Jinchun Wang","doi":"10.21037/tcr-24-1974","DOIUrl":"https://doi.org/10.21037/tcr-24-1974","url":null,"abstract":"<p><strong>Background: </strong>Gliomas are highly aggressive brain tumors with complex metabolic and molecular alterations. The role of glycolysis in glioma progression and its regulation by hypoxia remain poorly understood. This study investigated the function of glycogen phosphorylase L (<i>PYGL</i>) in glioma and its interaction with glycolytic pathways under hypoxic conditions.</p><p><strong>Methods: </strong>Differential expression analysis was conducted using The Cancer Genome Atlas (TCGA) glioma and GSE67089 datasets, revealing significant changes in the expression of genes. A prognostic risk model incorporating <i>PYGL</i> was built by univariate and multivariate Cox regression analyses. The impacts of <i>PYGL</i> on glioma cell proliferation, glycolysis, apoptosis, and metabolic activities were evaluated by <i>in vitro</i> assays. Additionally, the influences of hypoxia and hypoxia-inducible factor 1-alpha (<i>HIF1α</i>) on <i>PYGL</i> expression were evaluated.</p><p><strong>Results: </strong>Our prognostic prediction model showed a C-index of 0.76 [95% confidence interval (CI): 0.70-0.82], indicating a good predictive accuracy of the model. In addition, genetic predictors included in the nomogram included PYGL, HIF1α, and other genes associated with the glycolytic pathway. Differential expression analysis identified <i>PYGL</i> as a key gene associated with glioma survival. <i>PYGL</i> expression was significantly upregulated in glioma cells. <i>PYGL</i> knockdown inhibited cell invasion, proliferation, migration, and colony formation and enhanced apoptosis via modulation of Bcl-2, caspase-3, and Bax. Glycolysis was impaired in <i>PYGL</i>-knockdown cells, as indicated by increased glycogen levels and a reduced extracellular acidification rate (ECAR), adenosine triphosphate (ATP) levels, lactate levels, and PKM2 and LDHA expression. <i>PYGL</i> overexpression promoted glycolysis and cell viability, which was counteracted by 2-deoxy-D-glucose (2-DG). Hypoxia-induced <i>PYGL</i> expression was regulated by <i>HIF1α</i>, underscoring the interplay between the hypoxia and glycolysis pathways.</p><p><strong>Conclusions: </strong><i>PYGL</i> is a crucial regulator of glycolysis in gliomas and contributes to tumor progression under hypoxic conditions. Targeting <i>PYGL</i> and its associated metabolic pathways may offer new therapeutic strategies for glioma treatment.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 10","pages":"5627-5648"},"PeriodicalIF":1.5,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11543057/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142628838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the key pathogenic mechanisms and potential intervention targets for <i>Sophorae Flavescentis radix</i> in managing bone metastasis of lung cancer based on network pharmacology and molecular docking techniques.","authors":"Yan Gao, Meng Wu, Syed A A Rizvi, Qiang Wei","doi":"10.21037/tcr-24-1947","DOIUrl":"https://doi.org/10.21037/tcr-24-1947","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Lung cancer often metastasizes to the bone, which significantly complicates treatment and worsens patient prognosis. Thus, new therapeutic strategies need to be established. Using network pharmacology and bioinformatics analysis, this study sought to determine the molecular targets and associated mechanisms of the traditional Chinese medicine (TCM) &lt;i&gt;Sophorae Flavescentis radix&lt;/i&gt; in the treatment of lung cancer bone metastasis.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The active components of &lt;i&gt;Sophorae Flavescentis radix&lt;/i&gt; were screened using the TCM Systems Pharmacology (TCMSP) platform based on drug-likeness and oral bioavailability. The target genes of these active compounds were obtained from the DrugBank database. Differentially expressed genes (DEGs) between primary and bone metastatic lung cancer samples were screened in the GSE175601 dataset from the Gene Expression Omnibus (GEO) database using GEO2R. The intersecting DEGs from both groups were used to construct a Venn diagram to identify the candidate target genes. The expression and prognostic relevance of these genes were validated in The Cancer Genome Atlas (TCGA) database. The GeneMania and Search Tool for Recurring Instances of Neighbouring Genes (STRING) databases were used to generate the protein-protein interaction networks. Molecular docking was performed using the PubChem, Protein Data Bank (PDB), and CB-DOCK2 databases. A Gene Set Enrichment Analysis (GSEA) was conducted to explore the possible mechanisms of action.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In the TCMSP database, 28 active compounds and 227 target genes of the &lt;i&gt;Sophorae Flavescentis radix&lt;/i&gt; were identified. In total, 952 DEGs related to lung cancer bone metastasis were found in the GSE175601 dataset from the GEO database. Five common DEGs were identified via Venn diagram construction (i.e., &lt;i&gt;F10, JUN, AKR1B1, MMP1,&lt;/i&gt; and &lt;i&gt;CCND1&lt;/i&gt;). &lt;i&gt;MMP1&lt;/i&gt; was selected as the candidate gene. &lt;i&gt;MMP1&lt;/i&gt; was upregulated in lung cancer tissues, and patients with low &lt;i&gt;MMP1&lt;/i&gt; expression had better survival rates than those with high &lt;i&gt;MMP1&lt;/i&gt; expression (P&lt;0.05). &lt;i&gt;MMP1&lt;/i&gt; has an affinity of -8.9 with luteolin. The GSEA results suggested that &lt;i&gt;MMP1&lt;/i&gt; might influence biological processes in lung cancer by participating in pathways such as chemokine signaling, apoptosis, Wingless/Integrated (Wnt) signaling, tumor protein p53-regulated cell cycle arrest, Hedgehog signaling, and mitogen-activated protein kinase signaling.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Patients with lower &lt;i&gt;MMP1&lt;/i&gt; levels had prolonged overall survival and may serve as a novel predictive biomarker for lung cancer. &lt;i&gt;Sophorae Flavescentis radix&lt;/i&gt; appears to exert therapeutic effects on lung cancer bone metastasis by inhibiting &lt;i&gt;MMP1&lt;/i&gt; expression and modulating the abnormal activation of the Wnt pathway. Our findings further extend the understanding of the pathogenic mechanisms and potential therapeutic inter","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 10","pages":"5616-5626"},"PeriodicalIF":1.5,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11543056/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142628033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nomogram for predicting 10-year postoperative recurrence of stage I gastric cancer.","authors":"Tong-Dan Lyu, Ming-Peng Luo, Hao-Wei Hu","doi":"10.21037/tcr-24-692","DOIUrl":"https://doi.org/10.21037/tcr-24-692","url":null,"abstract":"<p><strong>Background: </strong>With the advancement of various auxiliary examination techniques, the detection rate of stage I gastric cancer has gradually increased, and its clinical first-choice treatment is surgery. Although patients with stage I gastric cancer generally have a good postoperative survival rate, there is still a certain probability of recurrence. Given the large number of gastric cancer cases, there is a vast population of patients with stage I disease. We are aiming to identify the risk factors for postoperative recurrence of stage I gastric cancer and to establish a reliable predictive model to assess the risk of recurrence in the population for clinical practice.</p><p><strong>Methods: </strong>In this retrospective cohort study, we utilized the Surveillance, Epidemiology, and End Results (SEER) database to investigate predictive factors for recurrence among stage I gastric cancer patients who underwent curative gastrectomy between 2000 and 2018. The cohort was divided into training and validation sets for the development and validation of a nomogram. Prognostic factors were evaluated through univariate and multivariate Cox regression analyses. Significant variables identified by the concordance index (C-index) and calibration plots were used to construct nomograms predicting the probability of 5- and 10-year recurrence.</p><p><strong>Results: </strong>Risk factors for recurrence included sex, age, race, histology, tumor size, American Joint Committee on Cancer Tumor (AJCC T) and primary site, which were used to construct the nomogram. The C-index for both the training and validation cohorts indicated that the nomogram possessed good calibration and discrimination abilities in predicting the probability of 5- and 10-year recurrence after curative surgery for stage I gastric cancer.</p><p><strong>Conclusions: </strong>This study established a reliable predictive model for recurrence following curative gastrectomy in stage I gastric cancer based on a population cohort. The findings of this study have the potential to significantly impact clinical practice by providing clinicians with tools for personalized risk assessment and for making informed treatment decisions.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 10","pages":"5497-5508"},"PeriodicalIF":1.5,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11543093/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142628539","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}