Translational cancer research最新文献

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Postexercise downregulation of NUP155 in regulating non-small cell lung cancer progression via the PTEN/AKT signaling pathway. 运动后下调NUP155通过PTEN/AKT信号通路调节非小细胞肺癌的进展。
IF 1.5 4区 医学
Translational cancer research Pub Date : 2024-11-30 Epub Date: 2024-11-27 DOI: 10.21037/tcr-24-1619
Jiangang Xu, Liyin Zhang, Menghui Feng, Weijun Hong, Xinming Ye
{"title":"Postexercise downregulation of <i>NUP155</i> in regulating non-small cell lung cancer progression via the PTEN/AKT signaling pathway.","authors":"Jiangang Xu, Liyin Zhang, Menghui Feng, Weijun Hong, Xinming Ye","doi":"10.21037/tcr-24-1619","DOIUrl":"10.21037/tcr-24-1619","url":null,"abstract":"<p><strong>Background: </strong>Research interest into regulation of gene expression by physical activity and its effect on cancer prognosis has intensified. This study investigated the role of an exercise-related gene, <i>NUP155</i>, in the progression of non-small cell lung cancer (NSCLC) and its potential as therapy target.</p><p><strong>Methods: </strong>Using the GSE41914 dataset, which includes data related to exercise, and the Cancer Genome Atlas (TCGA)-NSCLC dataset, we identified differentially expressed genes (DEGs) and selected <i>NUP155</i> as a hub gene for further analysis. <i>NUP155</i> expression levels were measured in NSCLC cell lines and normal lung cells using <i>in vitro</i> assays. The functional roles of <i>NUP155</i> were investigated through small interfering RNA (siRNA) knockdown experiments, assessing effects on migration, cell proliferation, invasion, and apoptosis. The involvement of the PTEN/AKT signaling pathway was examined using the PTEN inhibitor SF1670.</p><p><strong>Results: </strong><i>NUP155</i> was downregulated in postexercise samples and upregulated in NSCLC samples, indicating its association with poor prognosis in NSCLC. Knockdown of <i>NUP155</i> in NSCLC cell lines resulted in reduced cell viability, migration, and invasion, alongside increased apoptosis. Western blotting revealed that <i>NUP155</i> knockdown upregulated PTEN levels and downregulated phosphorylated AKT (p-AKT), without altering total AKT levels. The addition of SF1670 partially reversed the effects of <i>NUP155</i> knockdown, indicating the involvement of the signaling pathway PTEN/AKT in <i>NUP155</i>-mediated tumorigenesis.</p><p><strong>Conclusions: </strong><i>NUP155</i> is upregulated in NSCLC, which promotes cell invasion and migration via the PTEN/AKT signaling pathway. Targeting <i>NUP155</i>, potentially influenced by exercise, could be a promising therapy. Combining exercise with targeted treatments may enhance patient outcomes.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 11","pages":"6323-6335"},"PeriodicalIF":1.5,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651763/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855548","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}
引用次数: 0
Integrating artificial intelligence in renal cell carcinoma: evaluating ChatGPT's performance in educating patients and trainees. 在肾细胞癌中整合人工智能:评估ChatGPT对患者和学员的教育效果。
IF 1.5 4区 医学
Translational cancer research Pub Date : 2024-11-30 Epub Date: 2024-05-21 DOI: 10.21037/tcr-23-2234
J Patrick Mershon, Tasha Posid, Keyan Salari, Richard S Matulewicz, Eric A Singer, Shawn Dason
{"title":"Integrating artificial intelligence in renal cell carcinoma: evaluating ChatGPT's performance in educating patients and trainees.","authors":"J Patrick Mershon, Tasha Posid, Keyan Salari, Richard S Matulewicz, Eric A Singer, Shawn Dason","doi":"10.21037/tcr-23-2234","DOIUrl":"10.21037/tcr-23-2234","url":null,"abstract":"<p><strong>Background: </strong>OpenAI's ChatGPT is a large language model-based artificial intelligence (AI) chatbot that can be used to answer unique, user-generated questions without direct training on specific content. Large language models have significant potential in urologic education. We reviewed the primary data surrounding the use of large language models in urology. We also reported findings of our primary study assessing the performance of ChatGPT in renal cell carcinoma (RCC) education.</p><p><strong>Methods: </strong>For our primary study, we utilized three professional society guidelines addressing RCC to generate fifteen content questions. These questions were inputted into ChatGPT 3.5. ChatGPT responses along with pre- and post-content assessment questions regarding ChatGPT were then presented to evaluators. Evaluators consisted of four urologic oncologists and four non-clinical staff members. Medline was reviewed for additional studies pertaining to the use of ChatGPT in urologic education.</p><p><strong>Results: </strong>We found that all assessors rated ChatGPT highly on the accuracy and usefulness of information provided with overall mean scores of 3.64 [±0.62 standard deviation (SD)] and 3.58 (±0.75) out of 5, respectively. Clinicians and non-clinicians did not differ in their scoring of responses (P=0.37). Completing content assessment improved confidence in the accuracy of ChatGPT's information (P=0.01) and increased agreement that it should be used for medical education (P=0.007). Attitudes towards use for patient education did not change (P=0.30). We also review the current state of the literature regarding ChatGPT use for patient and trainee education and discuss future steps towards optimization.</p><p><strong>Conclusions: </strong>ChatGPT has significant potential utility in medical education if it can continue to provide accurate and useful information. We have found it to be a useful adjunct to expert human guidance both for medical trainee and, less so, for patient education. Further work is needed to validate ChatGPT before widespread adoption.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 11","pages":"6246-6254"},"PeriodicalIF":1.5,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651803/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855295","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}
引用次数: 0
Identification of the CD8+ T-cell exhaustion signature of hepatocellular carcinoma for the prediction of prognosis and immune microenvironment by integrated analysis of bulk- and single-cell RNA sequencing data. 通过对大细胞和单细胞RNA测序数据的综合分析,鉴定肝癌的CD8+ t细胞耗竭特征,以预测预后和免疫微环境。
IF 1.5 4区 医学
Translational cancer research Pub Date : 2024-11-30 Epub Date: 2024-11-20 DOI: 10.21037/tcr-24-650
Jianhui Fan, Qinghua Zhang, Tiancong Huang, Haitao Li, Guoxu Fang
{"title":"Identification of the CD8<sup>+</sup> T-cell exhaustion signature of hepatocellular carcinoma for the prediction of prognosis and immune microenvironment by integrated analysis of bulk- and single-cell RNA sequencing data.","authors":"Jianhui Fan, Qinghua Zhang, Tiancong Huang, Haitao Li, Guoxu Fang","doi":"10.21037/tcr-24-650","DOIUrl":"10.21037/tcr-24-650","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Hepatocellular carcinoma (HCC) is a prevalent type of cancer with high incidence and mortality rates. It is the third most common cause of cancer-related deaths. CD8&lt;sup&gt;+&lt;/sup&gt; T cell exhaustion (TEX) is a progressive decline in T cell function due to sustained T cell receptor stimulation from continuous antigen exposure. Studies have shown that CD8&lt;sup&gt;+&lt;/sup&gt; TEX plays an important role in the anti-tumor immune process and is significantly correlated with patient prognosis. The aim of the research is to establish a reliable CD8&lt;sup&gt;+&lt;/sup&gt; TEX-based signature using single-cell RNA sequencing (scRNA-seq) and high-throughput RNA sequencing (RNA-seq), providing a new approach to evaluate HCC patient prognosis and immune microenvironment.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The RNA-seq data of HCC patients were download from three different databases: The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and the International Cancer Genome Consortium (ICGC). HCC's 10× scRNA data were acquired from GSE149614. Based on single-cell sequencing data, CD8&lt;sup&gt;+&lt;/sup&gt; TEX-related genes were identified using uniform manifold approximation and projection (UMAP) algorithm, singleR, and marker gene methods. Afterwards, we proceeded to construct CD8&lt;sup&gt;+&lt;/sup&gt; TEX signature using differential gene analysis, univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analysis. We also validated the CD8&lt;sup&gt;+&lt;/sup&gt; TEX signature in GEO and ICGC external cohorts and investigated clinical characteristics, chemotherapy sensitivity, mutation landscape, functional analysis, and immune cell infiltration in different risk groups.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The CD8&lt;sup&gt;+&lt;/sup&gt; TEX signature, consisting of 13 genes (&lt;i&gt;HSPD1&lt;/i&gt;, &lt;i&gt;UBB&lt;/i&gt;, &lt;i&gt;DNAJB4,&lt;/i&gt; &lt;i&gt;CALM1&lt;/i&gt;, &lt;i&gt;LGALS3&lt;/i&gt;, &lt;i&gt;BATF&lt;/i&gt;, &lt;i&gt;COMMD3&lt;/i&gt;, &lt;i&gt;IL7R&lt;/i&gt;, &lt;i&gt;FDPS&lt;/i&gt;, &lt;i&gt;DRAP1&lt;/i&gt;, &lt;i&gt;RPS27L&lt;/i&gt;, &lt;i&gt;PAPOLA&lt;/i&gt;, &lt;i&gt;GPR171&lt;/i&gt;), was found to have a strong predictive effect on the prognosis of HCC. The Kaplan-Meier (KM) analysis showed that the overall survival (OS) rate of patients in the low-risk group was higher than that of patients in the high-risk group across different datasets and specific populations. The research findings suggested that the risk score was an independent predictor of HCC prognosis. The model based on clinical features and risk score has a strong predictive effect. We observed significant differences among various risk groups in terms of clinical characteristics, functional analysis, mutation landscape, chemotherapy sensitivity, and immune cell infiltration.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;We constructed a CD8&lt;sup&gt;+&lt;/sup&gt; TEX signature to predict the survival probability of patients with HCC. We also found that the model could predict the sensitivity of targeted drugs and immune cell infiltration, and the risk score was negatively correlated with CD8&lt;sup","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 11","pages":"5856-5872"},"PeriodicalIF":1.5,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651828/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855262","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}
引用次数: 0
Therapy-related myeloid neoplasms in Korean patients with ovarian or primary peritoneal cancer treated with poly(ADP-ribose) polymerase inhibitors. 用聚(adp -核糖)聚合酶抑制剂治疗的韩国卵巢癌或原发性腹膜癌患者的治疗相关髓系肿瘤
IF 1.5 4区 医学
Translational cancer research Pub Date : 2024-11-30 Epub Date: 2024-11-12 DOI: 10.21037/tcr-24-1131
Yoon Jung Jang, Heyjin Kim, Sang-Young Ryu, Moon-Hong Kim, Beob-Jong Kim, Hee Jung Jung, Jisik Kang, Sung Hyun Yang, Im Il Na, Hyo-Rak Lee, Hye Jin Kang
{"title":"Therapy-related myeloid neoplasms in Korean patients with ovarian or primary peritoneal cancer treated with poly(ADP-ribose) polymerase inhibitors.","authors":"Yoon Jung Jang, Heyjin Kim, Sang-Young Ryu, Moon-Hong Kim, Beob-Jong Kim, Hee Jung Jung, Jisik Kang, Sung Hyun Yang, Im Il Na, Hyo-Rak Lee, Hye Jin Kang","doi":"10.21037/tcr-24-1131","DOIUrl":"10.21037/tcr-24-1131","url":null,"abstract":"<p><strong>Background: </strong>Prior prospective studies have demonstrated the efficacy of poly(adenosine diphosphate-ribose) polymerase inhibitors (PARPis) in various cancers with mutations in the breast cancer gene (<i>BRCA</i>), such as ovarian and breast cancers. However, PARPi have also been associated with an increased incidence of therapy-related myeloid neoplasms (t-MNs). This study aimed to investigate the incidence of t-MNs following PARPi therapy in patients with ovarian or primary peritoneal cancer in Korea and to identify related risk factors.</p><p><strong>Methods: </strong>We retrospectively analyzed data of patients with ovarian or primary peritoneal cancer who received PARPi therapy between January 2015 and June 2023.</p><p><strong>Results: </strong>Among 52 patients treated with PARPi, four were diagnosed with t-MNs. All four patients had <i>BRCA</i> mutations, and two of them had breast cancer with no evidence of disease (NED) status following treatment. All patients received radiotherapy and at least one granulocyte-colony stimulating factor (G-CSF) application. The median duration of PARPi therapy was 16.3 (range, 6.2-48.8) months. At the time of analysis, three patients had metastatic ovarian cancer and one maintained the NED status. Next-generation sequencing (NGS) performed in four patients revealed <i>TP</i>53 mutations and complex karyotypes in all tested patients. Among the four patients, three received only supportive care, and one was actively undergoing t-MN treatment.</p><p><strong>Conclusions: </strong>The incidence of t-MNs after PARPi therapy in the current study was higher than that of overall t-MNs, which is consistent with the results of previous studies on t-MNs after PARPi therapy. Further international studies are needed to elucidate the mechanism and clinical characteristics of t-MNs associated with PARPi therapy.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 11","pages":"6018-6027"},"PeriodicalIF":1.5,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651792/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855242","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}
引用次数: 0
Immunogenic cell death-related signature predicts prognosis and immunotherapy efficacy in bladder cancer. 免疫原性细胞死亡相关特征预测膀胱癌预后和免疫治疗效果。
IF 1.5 4区 医学
Translational cancer research Pub Date : 2024-11-30 Epub Date: 2024-11-27 DOI: 10.21037/tcr-24-533
Long Guo, Na Chen, Mei Qiu, Juliang Yang, Min Zhou, Fei Liu
{"title":"Immunogenic cell death-related signature predicts prognosis and immunotherapy efficacy in bladder cancer.","authors":"Long Guo, Na Chen, Mei Qiu, Juliang Yang, Min Zhou, Fei Liu","doi":"10.21037/tcr-24-533","DOIUrl":"10.21037/tcr-24-533","url":null,"abstract":"<p><strong>Background: </strong>Immunogenic cell death (ICD) has been verified as a modality of regulated cell death (RCD). Bladder cancer (BC) is a common malignant tumor and ranks tenth in the incidence of global tumor epidemiology. We conducted this study to understand the relationship between ICD and BC and benefit clinical practice.</p><p><strong>Methods: </strong>Transcriptome and clinical profiling, mutational data of patients were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. BC patients were divided into ICD-high and -low risk subgroups via consensus clusters. Functional enrichment, somatic mutation analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to explore the potential mechanism. An ICD-related risk signature was constructed via least absolute shrinkage and selection operator (LASSO) regression analysis. Immune infiltration was investigated and multiplexed immunofluorescence staining was used to validate the BC microenvironment. Immune landscape was summarized to show the potential of immunotherapy.</p><p><strong>Results: </strong>A total of 18 differentially expressed ICD-related genes in BC were distinguished from normal tissue. We identified two clusters and BC patients were divided into ICD-high and -low subgroups in the TCGA BC cohort. The ICD-high subgroup exhibited worse clinical outcomes, different mutation profiles, different functional enrichment, higher immune infiltration, and better immunotherapy response. An ICD-related risk signature made of seven ICD-related genes was established and shown to have outstanding predictive power of prognosis via LASSO Cox regression.</p><p><strong>Conclusions: </strong>An ICD-related risk signature was established that provides a promising classification system to predict the prognosis in BC patients accurately. The signature provides a novel strategy for immunotherapy of BC.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 11","pages":"5801-5814"},"PeriodicalIF":1.5,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651764/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855269","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}
引用次数: 0
Construction and validation of a novel prognostic model with palmitoylation-related genes for glioblastoma. 棕榈酰化相关基因对胶质母细胞瘤的新型预后模型的构建和验证。
IF 1.5 4区 医学
Translational cancer research Pub Date : 2024-11-30 Epub Date: 2024-11-27 DOI: 10.21037/tcr-24-787
Guowen Qin, Gang Pang, Shuaishuai Wu, Shuiqing Bi, Shengyong Lan, Xiuwen Tang, Beiquan Hu, Junlin Zhou, Fengning Shi, Chengjian Qin
{"title":"Construction and validation of a novel prognostic model with palmitoylation-related genes for glioblastoma.","authors":"Guowen Qin, Gang Pang, Shuaishuai Wu, Shuiqing Bi, Shengyong Lan, Xiuwen Tang, Beiquan Hu, Junlin Zhou, Fengning Shi, Chengjian Qin","doi":"10.21037/tcr-24-787","DOIUrl":"10.21037/tcr-24-787","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Glioblastoma multiforme (GBM), the most prevalent and aggressive primary brain tumor, poses substantial challenges in both treatment and prognosis. Post-translational modifications, like palmitoylation, are known to have critical roles in the development and progression of glioma. Yet, the molecular mechanisms involved in palmitoylation and its prognostic significance in GBM are still not fully understood. This study aimed to explore prognostic biomarkers for GBM based on palmitoylation-related genes and to construct a prognostic risk model.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;The messenger ribonucleic acid (mRNA) expressions data and the clinical information were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to explore palmitoylation-related mechanisms in GBM. The Cox regression analysis was performed to identify prognostic palmitoylation-related genes and the consensus clustering was used for molecular classification. The package \"limma\" was used for differential gene expression analysis and the least absolute shrinkage and selection operator (LASSO) regression was applied to construct a risk signature. A nomogram model was established using the risk score and clinical variables. Receiver operating characteristic (ROC), calibration curve, and decision curve analysis (DCA) were used to assess the predicted accuracy and clinical benefit of the model. The difference in immune cell infiltration was compared between different risk groups. The drug susceptibility analysis and immunotherapy response prediction were conducted to access the ability of the risk signature in predicting the therapeutic effect.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Based on datasets from TCGA, five palmitoylation-related genes were identified as prognostic markers, allowing for the categorization of GBM patients into two subtypes with differing survival rates. Through differential expression analysis, 570 specific genes linked to GBM advancement were uncovered. A total of seven signature genes (&lt;i&gt;COL22A1&lt;/i&gt;, &lt;i&gt;IGFBP6&lt;/i&gt;, &lt;i&gt;SOD3&lt;/i&gt;, &lt;i&gt;UPP1&lt;/i&gt;, &lt;i&gt;CA14&lt;/i&gt;, &lt;i&gt;TIMP4&lt;/i&gt; and &lt;i&gt;FERMT1&lt;/i&gt;) were applied to establish a prognostic risk model, which was demonstrated to be an independent prognostic indicator for patients with GBM. Kaplan-Meier analysis indicted that the GBM patients in low-risk group exhibited a better survival outcome compared the patients in high-risk group. The ROC curve analyses demonstrated that the risk score model was reliable. The nomograms showed excellent predictive ability. Two external cohort of patients from the GSE74187 and GSE83300 in the GEO database confirmed the model's strong predictive performance. The immune infiltration, drug sensitivity and immunotherapy responses were significantly different between the low- and high-risk groups.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Our study offers insights into the molecular classification and prognostic assessment of GBM, focusing on palmitoy","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 11","pages":"6117-6135"},"PeriodicalIF":1.5,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651772/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855433","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}
引用次数: 0
Copper metabolism-related lncRNAs predict prognosis and immune landscape in liver cancer patients. 铜代谢相关lncrna预测肝癌患者预后和免疫景观
IF 1.5 4区 医学
Translational cancer research Pub Date : 2024-11-30 Epub Date: 2024-11-20 DOI: 10.21037/tcr-24-611
Rui Luo, Shu Huang, Xiaomin Shi, Huan Xu, Jieyu Peng, Wenjie Lei, Shiqi Li, Wei Zhang, Lei Shi, Yan Peng, Xiaowei Tang
{"title":"Copper metabolism-related lncRNAs predict prognosis and immune landscape in liver cancer patients.","authors":"Rui Luo, Shu Huang, Xiaomin Shi, Huan Xu, Jieyu Peng, Wenjie Lei, Shiqi Li, Wei Zhang, Lei Shi, Yan Peng, Xiaowei Tang","doi":"10.21037/tcr-24-611","DOIUrl":"10.21037/tcr-24-611","url":null,"abstract":"<p><strong>Background: </strong>Characterized by its high mortality and easy recurrence, hepatocellular carcinoma (HCC) poses significant clinical challenges. The association between copper metabolism and development of cancer has been identified. However, the underlying mechanisms of copper metabolism-related long non-coding RNAs (CMRLs) in HCC remain elusive. To address the gap, our study analyzed the prognostic and immuno-therapeutic value of CMRLs in HCC.</p><p><strong>Methods: </strong>This research utilized The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) data (n=424) for analysis, applying the \"limma\" package in R software for differential gene analysis and construction of a prognostic signature. We validated the signature using training and validation groups stochastically divided at a ratio of 1:1 and assessed prognostic value via Kaplan-Meier, C-index, and receiver operating characteristic (ROC) curves. By multivariate Cox regression, independent prognostic indicators were identified, and a nomogram was formulated for survival forecasting. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses elucidated biological pathways, and the immune landscape was examined through multiple algorithms. Finally, drug sensitivity was determined from Genomics of Drug Sensitivity in Cancer (GDSC), with mutation analysis conducted via maftools.</p><p><strong>Results: </strong>In this study, a predictive model based on four pivotal CMRLs (<i>PRRT3-AS1</i>, <i>AC108752.1</i>, <i>AC092115.3</i>, <i>AL031985.3</i>) significantly associated with HCC progression and prognosis was constructed and validated with the overall survival (OS) prediction area under the curve (AUC) values for 1, 3, and 5 years of 0.718, 0.688, and 0.669, respectively. The calibration curves and C-index values showed a solid prognostic ability of the nomogram. The high-risk group was notably higher than the low-risk group both in OS and tumor mutational burdens (TMBs). Moreover, functional annotation enrichment analysis of CMRLs revealed that the signature was mainly associated with mitotic function, chromosome, kinetochore, cell cycle, and oocyte meiosis. Furthermore, therapeutic drugs, including fluorouracil, afatinib, alpelisib, cedranib, crizotinib, erlotinib, gefitinib, and ipatasertib, were found to induce higher sensitivity in high-risk group.</p><p><strong>Conclusions: </strong>The prognostic signature consisting of four CMRLs displays an outstanding predictive performance and improves the precision of immuno-oncology.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 11","pages":"5784-5800"},"PeriodicalIF":1.5,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651766/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855484","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}
引用次数: 0
The usefulness of Hinotori™ which is a surgical support robot system developed in Japan and a challenging case of robot-assisted surgery. Hinotori™是日本开发的手术支持机器人系统,是机器人辅助手术的一个具有挑战性的案例。
IF 1.5 4区 医学
Translational cancer research Pub Date : 2024-11-30 Epub Date: 2024-11-12 DOI: 10.21037/tcr-24-1735
Takuya Koie
{"title":"The usefulness of Hinotori™ which is a surgical support robot system developed in Japan and a challenging case of robot-assisted surgery.","authors":"Takuya Koie","doi":"10.21037/tcr-24-1735","DOIUrl":"10.21037/tcr-24-1735","url":null,"abstract":"","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 11","pages":"5723-5724"},"PeriodicalIF":1.5,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651814/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855191","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}
引用次数: 0
Integrative multi-omics and machine learning approach reveals tumor microenvironment-associated prognostic biomarkers in ovarian cancer. 综合多组学和机器学习方法揭示卵巢癌肿瘤微环境相关的预后生物标志物。
IF 1.5 4区 医学
Translational cancer research Pub Date : 2024-11-30 Epub Date: 2024-11-07 DOI: 10.21037/tcr-24-539
Wenzhi Jiao, Shasha Yang, Yue Li, Yu Li, Shanshan Liu, Jianwei Shi, Minmin Yu
{"title":"Integrative multi-omics and machine learning approach reveals tumor microenvironment-associated prognostic biomarkers in ovarian cancer.","authors":"Wenzhi Jiao, Shasha Yang, Yue Li, Yu Li, Shanshan Liu, Jianwei Shi, Minmin Yu","doi":"10.21037/tcr-24-539","DOIUrl":"10.21037/tcr-24-539","url":null,"abstract":"<p><strong>Background: </strong>Ovarian cancer (OC) is a globally prevalent malignancy with significant morbidity and mortality, yet its heterogeneity poses challenges in treatment and prognosis. Recognizing the crucial role of the tumor microenvironment (TME) in OC progression, this study leverages integrative multi-omics and machine learning to uncover TME-associated prognostic biomarkers, paving the way for more personalized therapeutic interventions.</p><p><strong>Methods: </strong>Employing a rigorous multi-omics approach, this study analyzed single-cell RNA sequencing (scRNA-seq) data from OC and normal tissue samples, including high-grade serous OC (HGSOC) from the Gene Expression Omnibus (GEO: GSE184880) and The Cancer Genome Atlas (TCGA) OC cohort, utilizing the Seurat package to annotate 700 TME-related genes. A prognostic model was developed using the least absolute shrinkage and selection operator (LASSO) regression and independently validated against similarly composed HGSOC datasets. Comprehensive gene expression and immune cell infiltration analyses were conducted, employing advanced algorithms like xCell to delineate the immune landscape of HGSOC.</p><p><strong>Results: </strong>Our investigation unveiled distinctive immune cell infiltration patterns and gene expression profiles within the TME of HGSOC. Notably, the prevalence of exhausted CD8<sup>+</sup> T cells in high-risk patient samples emerged as a critical finding, underscoring the dualistic nature of the immune response in OC. The developed prognostic model, incorporating immune cell markers, exhibited robust predictive accuracy for patient outcomes, showing significant correlations with immunotherapy responses and drug sensitivities.</p><p><strong>Conclusions: </strong>This study presents a groundbreaking exploration of the OC TME, offering vital insights into its molecular intricacies. By systematically deciphering the TME-associated gene signatures, the research illuminates the potential of these biomarkers in refining patient prognosis and guiding treatment strategies. Our findings underscore the necessity for personalized medicine in OC treatment, potentially enhancing patient survival rates and quality of life. This study marks a significant stride in understanding and combatting the complexities of OC.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 11","pages":"6182-6200"},"PeriodicalIF":1.5,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651752/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855375","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}
引用次数: 0
Prognostic signature detects homologous recombination deficient in glioblastoma. 胶质母细胞瘤的预后特征检测同源重组缺陷。
IF 1.5 4区 医学
Translational cancer research Pub Date : 2024-11-30 Epub Date: 2024-11-21 DOI: 10.21037/tcr-23-2077
Dongdong Luo, Aiping Luo, Su Hu, Hailin Zhao, Xuefeng Yao, Dan Li, Biao Peng
{"title":"Prognostic signature detects homologous recombination deficient in glioblastoma.","authors":"Dongdong Luo, Aiping Luo, Su Hu, Hailin Zhao, Xuefeng Yao, Dan Li, Biao Peng","doi":"10.21037/tcr-23-2077","DOIUrl":"10.21037/tcr-23-2077","url":null,"abstract":"<p><strong>Background: </strong>Glioblastoma (GBM) is a frequent malignant tumor in neurosurgery characterized by a high degree of heterogeneity and genetic instability. DNA double-strand breaks generated by homologous recombination deficiency (HRD) are a well-known contributor to genomic instability, which can encourage tumor development. It is unknown, however, whether the molecular characteristics linked with HRD have a predictive role in GBM. The study aims to assess the extent of genomic instability in GBM using HRD score and investigate the prognostic significance of HRD-related molecular features in GBM.</p><p><strong>Methods: </strong>The discovery cohort comprised 567 GBM patients from The Cancer Genome Atlas (TCGA) database. We established HRD scores using the single nucleotide polymorphism (SNP) array data and analyzed transcriptomic data from patients with different HRD scores to identify biomarkers associated with HRD. A prognostic model was built by using HRD-related differentially expressed genes (DEGs) and validated in a distinct cohort from the Chinese Glioma Genome Atlas (CGGA) database.</p><p><strong>Results: </strong>Based on the SNP array data, the gene expression profile data, and the clinical characteristics of GBM patients, we found that patients with a high HRD score had a better prognosis than those with a low HRD score. The DNA damage repair (DDR) signaling pathways were notably enriched in the HRD-positive subgroup. The prognostic model was developed by including HRD-related DEGs that could evaluate the clinical prognosis of patients more efficiently than the HRD score. In addition, patients with a low-risk score had a considerably augmented signature of γδT cells. Finally, through univariate and multivariate Cox regression analyses, it was demonstrated that the prognostic model was superior to other prognostic markers.</p><p><strong>Conclusions: </strong>In conclusion, our research has not only demonstrated that a high HRD score is a valid prognostic biomarker in GBM patients but also built a stable prognosis model [odds ratio (OR) 0.18, 95% confidence interval (CI): 0.11-0.23, P<0.001] that is more accurate than conventional prognostic markers such as O6-methylguanine-DNA methyltransferase (MGMT) methylation (OR 0.55, 95% CI: 0.33-0.91, P=0.02).</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"13 11","pages":"5883-5897"},"PeriodicalIF":1.5,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651736/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142855562","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}
引用次数: 0
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