Journal of Cancer最新文献

{"title":"Development and validation of an explainable machine learning model to predict Delphian lymph node metastasis in papillary thyroid cancer: a large cohort study.","authors":"Jie Cui, Genglong Liu, Kai Yue, Yansheng Wu, Yuansheng Duan, Minghui Wei, Xudong Wang","doi":"10.7150/jca.110141","DOIUrl":"https://doi.org/10.7150/jca.110141","url":null,"abstract":"<p><p><b>Background:</b> The occurrence of papillary thyroid cancer (PTC) has risen substantially and tends to exhibit early-stage lymph node metastasis (LNM), increasing the risk of postoperative recurrence and decreasing survival. There is a lack of a machine learning (ML) model to predict delphian LNM (DLNM) in PTC. This investigation seeks to comprehensively assess the significance of standard clinical indicators for DLNM prediction, while constructing a dependable and widely applicable ensemble ML framework to support surgical planning and therapeutic decision-making. <b>Methods:</b> This investigation incorporated 1993 sequential PTC patients who underwent curative surgical procedures from 2020 to 2023. Based on the time to surgery, we divided the cohort into the training cohort (n=1395) and the validation cohort (n=598). The Boruta algorithm was applied to select feature variables, succeeded by the development of an innovative ML structure combining 12 ML techniques across 113 permutations to create a unified prediction model (DLNM index). ROC analysis, calibration curve, Bootstrapping, 10-fold cross validation, restricted cubic spline (RCS) regression, multivariable logistic regression, and subgroup analysis were utilised to evaluate the predictive accuracy and discriminative ability of the DLNM index. Model interpretation and feature impact visualisation were accomplished through the Shapley Additive Explanations (SHAP) methodology. <b>Results:</b> Based on 14 features via the Boruta algorithm selection, we integrated them into 12 ML approaches, yielding 113 permutations, from which we identified the superior algorithm to establish a consensus ML-derived diagnostic model (DLNM index). The DLNM index exhibited excellent diagnostic values with a mean AUC of 0.763 in two cohorts and discriminative ability, serving as an independent risk factor (<i>P</i> < 0.001). It performed better in predicting performance and yielded a larger net benefit than the published model (<i>P</i> < 0.05). Bootstrapping and 10-fold cross validation, and subgroup analysis showed that the DLNM index was generally robust and generalisable. SHAP explains the importance of ranking features (tumour size, right 4 region LN, FT4, TG, and T3) and visualises global and individual risk prediction. RCS regression suggested a nonlinear link between the DLNM index, TG, tumour size, FT3, and DLNM risk. <b>Conclusion:</b> An optimised explainable model (DLNM index) comprising 12 clinical features based on multiple ML algorithms was constructed and validated to provide an economical, readily available, and precise diagnostic instrument for DLNM in PTC, which has potential implications for clinical practice. The SHAP explanation and RCS regression quantify and visualise tumour size and FT4 as the most important variables that increase DLNM risk.</p>","PeriodicalId":15183,"journal":{"name":"Journal of Cancer","volume":"16 6","pages":"2041-2061"},"PeriodicalIF":3.3,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905415/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 Causal Relationship Between Lipid Profiles and Colorectal Cancer Through Mendelian Randomization: A Multidimensional Plasma Lipid Composition Perspective.","authors":"Hailan Wu, Jialin Gu, Yun He, Yi Ji, Wen Cao, Rongrong Li, Zhancheng Gu, Guoli Wei, Jiege Huo","doi":"10.7150/jca.103247","DOIUrl":"https://doi.org/10.7150/jca.103247","url":null,"abstract":"<p><p><b>Background:</b> The causal relationship between blood lipids and colorectal cancer (CRC) risk has been preliminarily explored in previous Mendelian randomization (MR) studies, but these investigations were limited to conventional or partial metabolic lipid profiles. Recent advancements in genome-wide association studies of plasma lipidomics have expanded our understanding of lipid categories, underscoring the need to evaluate the causal associations between a broader range of lipid types and CRC risk to enhance risk assessment. <b>Methods:</b> This MR study utilized 179 lipid phenotypes across 13 lipid classes to investigate their causal associations with CRC risk. Genetic variants significantly associated with lipid traits at the genome-wide level (<i>P</i><5×10^-8) were used as instrumental variables for MR analysis. Initial analyses were conducted using a discovery dataset (n=321,040), followed by validation in an independent replication dataset (n=185,616). Meta-analysis was then employed to determine the strength of causal evidence. The inverse-variance weighted (IVW) method and Wald ratio were the primary MR approaches, complemented by up to nine methods for multidimensional validation. Sensitivity analyses included tests for pleiotropy, heterogeneity, Steiger directionality, and Bayesian colocalization analysis, among others. <b>Results:</b> After Bonferroni correction and rigorous validations, 9 significant causal associations were identified. Specifically, genetically predicted levels of sterol ester (27:1/20:5) (OR_IVW = 1.214, 95% CI 1.119-1.317), phosphatidylcholine (20:4_0:0) (OR_IVW = 1.147, 95% CI 1.077-1.222), phosphatidylcholine (16:0_22:4) (OR_IVW = 1.312, 95% CI 1.170-1.472), phosphatidylcholine (16:0_22:5) (OR_IVW =1.181, 95% CI 1.093-1.277), and phosphatidylcholine (18:0_20:5) (OR_IVW = 1.198, 95% CI 1.104-1.300) were significantly associated with an increased risk of CRC. Conversely, levels of phosphatidylcholine (18:1_20:2) (OR_IVW = 0.832, 95% CI 0.771-0.898), phosphatidylethanolamine (18:2_0:0) (OR_IVW = 0.804, 95% CI 0.732-0.882), phosphatidylcholine (16:0_18:0) (OR_{Wald ratio} = 0.611, 95% CI 0.481-0.777), and phosphatidylcholine (O-18:1_18:2) (OR_{Wald ratio} = 0.723, 95% CI 0.620-0.840) were significantly associated with a decreased risk of CRC. Colocalization analysis revealed posterior probabilities for hypothesis 4 exceeding 90%, identifying rs174546 and rs28456 as shared causal variants. Additionally, 14 suggestive causal associations were observed. <b>Conclusions:</b> This study establishes a causal link between specific lipid species and CRC risk. These findings suggest new avenues for CRC prevention and treatment strategies.</p>","PeriodicalId":15183,"journal":{"name":"Journal of Cancer","volume":"16 6","pages":"1848-1859"},"PeriodicalIF":3.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905406/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Omics Profiling Identifies a High-Risk Subgroup of Breast Cancer Stem Cells for Prognostic Stratification and Personalized Treatment.","authors":"Guixin Wang, Ziyi Chen, Yao Tian, Yuxin Zhu, Shuo Wang, Wenbin Song, Xin Wang, Yingxi Li","doi":"10.7150/jca.109589","DOIUrl":"https://doi.org/10.7150/jca.109589","url":null,"abstract":"<p><p><b>Background:</b> Breast cancer is the most prevalent malignancy among females worldwide. Extensive research has highlighted cancer stem cells (CSCs) as critical drivers of tumor initiation, progression, recurrence, and therapy resistance. However, the heterogeneity of breast cancer stem cells (BCSCs) and their dynamic roles within the tumor microenvironment remain inadequately understood. <b>Methods:</b> This study utilized the single-cell RNA sequencing dataset to categorize BCSCs into two subgroups within the breast cancer microenvironment and investigate their pseudo-time developmental dynamics. Bulk transcriptomic data from TCGA-BRCA were integrated to assess the prognostic significance and infiltration abundance of the BCSCs-2 subgroup. Functional enrichment, co-expression network analysis, and somatic mutation profiling were performed to elucidate key biological pathways and genetic features. Additionally, drug sensitivity analyses were conducted using the Connectivity Map database to identify potential therapeutic strategies. <b>Results:</b> A total of 459 BCSCs were identified and further classified into two distinct subpopulations: BCSCs-1 and BCSCs-2. High infiltration of BCSCs-2 was associated with poor prognosis and an immunosuppressive tumor microenvironment. Co-expression network analysis identified 16 key genes linked to BCSCs-2, while somatic mutation analysis revealed distinct mutation patterns associated with its infiltration. Drug sensitivity analysis suggested that patients with high BCSCs-2 infiltration could benefit from classical chemotherapy agents, such as Cisplatin, and other novel therapeutic compounds. <b>Conclusions:</b> This study offers novel insights into the heterogeneity and functional roles of BCSCs in breast cancer. The findings highlight the prognostic and therapeutic importance of the BCSCs-2 subgroup, providing potential biomarkers and therapeutic targets for precision medicine in breast cancer management.</p>","PeriodicalId":15183,"journal":{"name":"Journal of Cancer","volume":"16 6","pages":"1860-1872"},"PeriodicalIF":3.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905410/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143647429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Both consolidation and maintenance treatment improve outcomes in primary central nervous system lymphoma: real-world evidence from a tertiary medical center.","authors":"Chieh-Lung Cheng, Chang-Tsu Yuan, Wei-Quan Fang, Po-Hao Huang, Hsin-An Hou, Cheng-Hong Tsai, Ming Yao, Wen-Chien Chou, Hwei-Fang Tien","doi":"10.7150/jca.107661","DOIUrl":"https://doi.org/10.7150/jca.107661","url":null,"abstract":"<p><p><b>Background:</b> Intensive consolidation treatment following high-dose methotrexate (HDMTX)-based chemotherapy is recommended for fit patients with primary central nervous system lymphoma (PCNSL). Otherwise, HDMTX maintenance might be a useful alternative to consolidation approach in certain circumstances. However, the real-world evidence supporting the beneficial role of consolidation treatment or HDMTX maintenance in PCNSL is limited. <b>Methods:</b> We retrospectively analyzed the clinical efficacy and survival impact of consolidation treatment or HDMTX maintenance on patients with PCNSL treated with HDMTX-based induction chemotherapy. <b>Results:</b> A total of 109 patients were evaluated, with a median age at diagnosis being 63 years. Among them, 69 received induction therapy with HDMTX monotherapy and 40 with HDMTX-based polychemotherapies. In total, 67 (61.5%) patients responded to treatment, of whom 56 (51.4%) had complete response. After a 58.9-month median follow-up, overall survival (OS) at 2 and 5 years was 69% and 45%, respectively. The types of induction regimen or frontline rituximab had no survival impact (<i>P</i> = 0.364 and 0.328, respectively). Among the 67 responding patients, 51 received the consolidation/maintenance therapy. Compared to the patients without consolidation/maintenance, those being treated had lower relapse/PD rates (2-year cumulative incidence of relapse/PD, 39.5% vs. 63.6%, <i>P</i> <0.001) and a significantly better OS (5-year survival rate, 63.8% vs. 27.2%, <i>P</i> = 0.016). Multivariate analysis revealed consolidation/maintenance treatment strikingly reduced mortality risk. Notably, HDMTX maintenance had similar efficacy comparable to consolidative whole-brain radiotherapy. Moreover, consolidation treatment was conducive to prolonging remission duration in the later-line settings of patients who responded to subsequent salvage therapies. <b>Conclusion</b>: This real-world evidence provides clear insight that consolidation/maintenance treatment could prolong OS in PCNSL, emphasizing its critical and indispensable role in treating PCNSL.</p>","PeriodicalId":15183,"journal":{"name":"Journal of Cancer","volume":"16 6","pages":"1836-1847"},"PeriodicalIF":3.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905409/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"RNF114 Interacts with EWSR1 to Regulate VEGFR2 in HER2-positive Breast Cancer.","authors":"Yingchuan Zhu, Yue Song, Yilu Lu, Wenhao Jiang, Jingfei Zhang, Lan Yin, Xinyu Lin, Dachang Tao, Yongxin Ma","doi":"10.7150/jca.106001","DOIUrl":"https://doi.org/10.7150/jca.106001","url":null,"abstract":"<p><p>RNF114, a member of the E3 ubiquitin ligase family, was first identified as a zinc-binding protein that exhibits frequent genomic amplification across various cancers. Previous studies have shown that inhibition of RNF114 E3 ligase activity by Nimbolide treatment can result in trapping of PARP1 and synthetic lethality in BRCA-mutated cancers, suggesting its E3 ligase role in tumor progress. However, it's important to reveal novel functions and interacting molecules of RNF114. Here, we first described that RNF114 promotes tumor proliferation and autophagy by interacting with EWSR1 and regulating VEGFR2 expression in HER2-positive breast cancer (BC). Our results also showed that RNF114 is significantly overexpressed in BC and is associated with TNM stage and poor prognosis in BC patients. And knockdown of RNF114 suppresses proliferation, migration, invasion, and autophagy of HER2-positive BC cells. Our findings highlight the transcriptional regulatory function of RNF114 in BC, offering new insights into its oncogenic role and contribution to HER2-positive BC progression.</p>","PeriodicalId":15183,"journal":{"name":"Journal of Cancer","volume":"16 6","pages":"1888-1904"},"PeriodicalIF":3.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905403/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of M2 macrophage markers for predicting outcome and therapeutic response in osteosarcoma: Integrated analysis of single-cell and bulk RNA-sequencing.","authors":"Yang Liu, Liwei Liu, Xianpeng Wei, Yan Xiong, Qifang Han, Tianhui Gong, Fuzhou Tang, Kaide Xia, Shuguang Zheng","doi":"10.7150/jca.104855","DOIUrl":"https://doi.org/10.7150/jca.104855","url":null,"abstract":"<p><p>Identification of effective biomarkers is crucial to improve the efficacy of immunotherapy in patients with osteosarcoma. Tumor-associated M2 macrophages, an important immune cell type in the tumor immune microenvironment, are closely related to the formation and progression of tumors. However, the relationships of M2 macrophages and prognosis and the immunotherapy response to osteosarcoma remain unclear. In this study, we obtained single-cell RNA sequencing (scRNA-seq) data of osteosarcoma from the gene expression omnibus (GEO) database and performed trajectory analysis and cell communication analysis. We then identified M2 macrophage marker genes based on scRNA-seq data of osteosarcoma, and constructed a risk-score model using these genes. Next, we compared the survival status and immune features of patients with high and low risk scores. Based on scRNA-seq data, we found that macrophages were the major immune cell type in the osteosarcoma microenvironment, and the high proportion of M2 macrophages might result from the transition of macrophages M1 to M2. M2 macrophages communicated with osteoblastic cells via the APP, MIF, and SPP1 signaling pathways, facilitating osteosarcoma development. Moreover, we identified 189 osteosarcoma-related M2 macrophage marker genes and screened out 10 key genes used for model constrcution. These 10 genes consisted of two known M2 macrophage markers and eight novel M2 macrophage marker genes. Low-risk patients have a statistically significant survival advantage, which was verified in the four GEO datasets. Low-risk patients also displayed a high abundance of tumor-infiltrating immune cells, indicative of an \"hot\" immune phenotype, while high-risk patients displayed an opposite immunologic feature. Notably, our analysis of two independent immunotherapy cohorts revealed that low-risk patients had good immunotherapy responses and outcomes. Additionally, we determined 32 evidently correlated pairs between risk score and drug sensitivity. This study reveals a new prognostic signature based on M2 macrophage marker genes that can help optimize personalized prognosis and improve immunotherapy outcomes in patients with osteosarcoma and also provides a method for identifying effective biomarkers based on integrated analysis of single-cell and bulk RNA sequencing.</p>","PeriodicalId":15183,"journal":{"name":"Journal of Cancer","volume":"16 6","pages":"1873-1887"},"PeriodicalIF":3.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905420/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mitoxantrone-liposome Sensitizes <i>FLT3-ITD</i> Acute Myeloid Leukemia to Gilteritinib Treatment.","authors":"Shiyi Yuan, Ying Zhou, Yifei Li, Zhe Chen, Wenrui Xiao, Danqing Jiang, Ping Zhang, Ying Zhang, Fengxia Bai, Jianchuan Deng, Shifeng Lou","doi":"10.7150/jca.105557","DOIUrl":"https://doi.org/10.7150/jca.105557","url":null,"abstract":"<p><p>FMS-like tyrosine kinase 3 (<i>FLT3</i>) is the most frequently mutated gene in acute myeloid leukemia (AML), and is associated with poor prognosis and a high relapse rate. Gilteritinib, a second-generation FLT3 inhibitor, is an important target drug for treating patients with <i>FLT3</i>-internal tandem duplication (ITD) AML, is approved for the treatment of relapsed/refractory <i>FLT3</i>-mutant acute myeloid leukemia, although challenges such as drug resistance and reduced potency remain. Herein, mitoxantrone-liposomes sensitized <i>FLT3-ITD</i> AML cells to gitretinib both <i>in vivo</i> and <i>in vitro</i>. RNA-sequencing revealed that combination treatment resulted in specific changes in gene expression as well as predicted the mechanism. Primary AML cells harvested from patients with <i>FLT3-ITD</i> AML showed a significant response to combination treatment <i>in vitro.</i> Our data suggests a novel and promising therapeutic strategy for patients with <i>FLT3-ITD</i> AML and relapsed/refractory FTL3-ITD AML.</p>","PeriodicalId":15183,"journal":{"name":"Journal of Cancer","volume":"16 6","pages":"1905-1917"},"PeriodicalIF":3.3,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905413/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-omics analysis reveals lysosome-associated molecular subtype characterization and prognostic modeling system in lung adenocarcinoma.","authors":"Zhanmei Wang, Yan Wang, Jinxiang Wang","doi":"10.7150/jca.105351","DOIUrl":"https://doi.org/10.7150/jca.105351","url":null,"abstract":"<p><p><b>Background:</b> Lung adenocarcinoma (LUAD) poses a significant challenge in current treatments due to its high recurrence and metastasis rates. Despite preliminary evidence suggesting the role of lysosomes in LUAD, it remains unclear whether lysosome-related functions can be effectively used for risk stratification of LUAD patients and involved lysosome-related functional targets are still needed to be explored. <b>Method:</b> An integrated analysis of TCGA and GEO databases was conducted to explore the potential role of lysosome-related genes (LRGs) in LUAD. Unsupervised consensus clustering analysis was utilized to explore the LRG molecular subtypes in LUAD. ESTIMATE and ssGSEA algorithms were performed to evaluate the immune infiltration characterization of LUAD samples. LASSO-univariate and multivariate Cox analysis were used to construct the LRG score model. Single-cell sequencing analysis was performed to reveal the distribution characteristics in different cell subpopulations of selected LRGs. <i>In vitro</i> experiments including western blotting, PCR, colony formation assays, and Transwell assays were used to verify the expression and biological functions of the selected target in LUAD. <b>Results:</b> Through multi-omics integration analysis algorithms, we successfully developed a prognostic risk stratification system based on LRG scoring in LUAD and constructed a nomogram diagnostic model. Various bioinformatics analyses indicated the potential clinical value of the LRG scoring system. Single-cell sequencing analysis further revealed the composition of cell subpopulations and the expression characteristics of prognostic signatures. SLC2A1, one of the selected targets, was validated through <i>in vitro</i> experiments to regulate the proliferation and migration of LUAD cells, thereby confirming the reliability of the bioinformatics results. <b>Conclusion:</b> Our results demonstrate that effective risk stratification of LUAD patients can be achieved through LRGs by multi-omics analysis integration. Furthermore, we validated key prognostic targets <i>in vitro</i>, providing new ideas for future clinical treatment.</p>","PeriodicalId":15183,"journal":{"name":"Journal of Cancer","volume":"16 6","pages":"1794-1813"},"PeriodicalIF":3.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905399/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648750","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Drugging the tumor microenvironment epigenome for therapeutic interventions in NSCLC.","authors":"Kostas A Papavassiliou, Amalia A Sofianidi, Vassiliki A Gogou, Athanasios G Papavassiliou","doi":"10.7150/jca.111023","DOIUrl":"https://doi.org/10.7150/jca.111023","url":null,"abstract":"","PeriodicalId":15183,"journal":{"name":"Journal of Cancer","volume":"16 6","pages":"1832-1835"},"PeriodicalIF":3.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905414/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of GPX3 and JUN as Tumor Suppressors in Thyroid Cancer through Integrated WGCNA and Mendelian Randomization.","authors":"Renjie Zhang, Yutao Chen, Sha Xu, Xue Gu, Hui Ye","doi":"10.7150/jca.104687","DOIUrl":"https://doi.org/10.7150/jca.104687","url":null,"abstract":"&lt;p&gt;&lt;p&gt;&lt;b&gt;Background:&lt;/b&gt; Thyroid cancer (TC) ranks among the most common malignancies globally, with an increasing incidence among younger populations. While papillary thyroid carcinoma (PTC) generally has a favorable prognosis, other forms of TC, such as anaplastic thyroid carcinoma (ATC), are associated with poor outcomes. Although specific mutations, such as BRAF&lt;sup&gt;V600E&lt;/sup&gt;, have been identified in certain types of TC, the underlying mechanisms remain largely unclear. Therefore, there is a critical need to further explore therapeutic targets associated with malignant tumors to improve treatment outcomes. &lt;b&gt;Method:&lt;/b&gt; We integrated eQTL data from European populations with RNA-Seq data from TC patients obtained from TCGA and multiple GEO databases. Through differential expression analysis, WGCNA, and Mendelian randomization (MR) analysis, we sought to identify potential gene therapy targets in TC. Additionally, we explored the biological behaviors of these targets using various cellular biology assays, such as MTT, colony formation, wound healing, and Transwell assays. Molecular biology techniques, including Western blot, were employed to investigate the underlying mechanisms. &lt;b&gt;Result:&lt;/b&gt; Differential expression analysis across six GEO datasets identified 649 genes associated with TC. Subsequent WGCNA analysis of the GSE6339 dataset revealed 2,739 genes, and MR analysis further identified 189 genes. The intersection of these datasets highlighted four key genes: TIAM1, RAP1GAP, GPX3, and JUN. GO analysis linked these genes to \"response to oxidative stress\" and \"regulation of GTPase activity\". KEGG pathway analysis demonstrated significant enrichment in pathways including \"Glutathione metabolism\", \"cAMP signaling pathway\", \"Rap1 signaling pathway\", \"Tight junction\", and \"Thyroid hormone synthesis\". Further, single-gene GSEA analyses suggested distinct pathways through which each gene may influence TC progression. Immune profiling revealed marked differences in immune cell populations, notably CD8+ T cells, monocytic lineage cells, neutrophils, NK cells, and T cells, between normal and cancerous thyroid tissues. Notably, RAP1GAP, GPX3, and JUN were implicated in the regulation of Treg and follicular helper T cell functions. The differential expression of these genes was rigorously validated using TCGA dataset and six additional GEO datasets. While the tumor-suppressive roles of TIAM1 and RAP1GAP have been previously established, our findings reveal that the overexpression of GPX3 and JUN significantly impairs the proliferative and migratory capacities of TC cells, underscoring their potential as therapeutic targets. &lt;b&gt;Conclusion:&lt;/b&gt; This study identifies GPX3 and JUN as critical tumor suppressor genes in TC, with their function closely linked to T regulatory cells and follicular helper T cells. The overexpression of GPX3 and JUN demonstrates significant tumor-suppressive activity, highlighting their potential as effective therapeutic ta","PeriodicalId":15183,"journal":{"name":"Journal of Cancer","volume":"16 6","pages":"1814-1831"},"PeriodicalIF":3.3,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11905407/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143648746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}