Technology in Cancer Research & Treatment最新文献

{"title":"Comparison of Machine Learning and Logic Regression Algorithms for Predicting Lymph Node Metastasis in Patients with Gastric Cancer: A two-Center Study.","authors":"Tong Lu, Yu Fang, Haonan Liu, Chong Chen, Taotao Li, Miao Lu, Daqing Song","doi":"10.1177/15330338231222331","DOIUrl":"10.1177/15330338231222331","url":null,"abstract":"<p><strong>Objectives: </strong>This two-center study aimed to establish a model for predicting the risk of lymph node metastasis in gastric cancer patients using machine learning (ML) and logistic regression (LR) algorithms, and to evaluate its predictive performance in clinical practice.</p><p><strong>Methods: </strong>Data of a total of 369 patients who underwent radical gastrectomy in the Department of General Surgery of Affiliated Hospital of Xuzhou Medical University (Xuzhou, China) from March 2016 to November 2019 were collected and retrospectively analyzed as the training group. In addition, data of 123 patients who underwent radical gastrectomy in the Department of General Surgery of Jining First People's Hospital (Jining, China) were collected and analyzed as the verification group. Besides, 7 ML and logistic models were developed, including decision tree, random forest, support vector machine (SVM), gradient boosting machine (GBM), naive Bayes, neural network, and LR, in order to evaluate the occurrence of lymph node metastasis in patients with gastric cancer. The ML model was established following 10 cross-validation iterations within the training dataset, and subsequently, each model was assessed using the test dataset. The model's performance was evaluated by comparing the area under the receiver operating characteristic curve of each model.</p><p><strong>Results: </strong>Compared with the traditional logistic model, among the 7 ML algorithms, except for SVM, the other models exhibited higher accuracy and reliability, and the influences of various risk factors on the model were more intuitive.</p><p><strong>Conclusion: </strong>For the prediction of lymph node metastasis in gastric cancer patients, the ML algorithm outperformed traditional LR, and the GBM algorithm exhibited the most robust predictive capability.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10775719/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139404496","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":"Detection of Muscularis propria Invasion in Urothelial Carcinoma Using Artificial Intelligence.","authors":"Ibrahim Fahoum, Rabab Naamneh, Keren Silberberg, Rami Hagege, Dov Hershkovitz","doi":"10.1177/15330338241257479","DOIUrl":"10.1177/15330338241257479","url":null,"abstract":"<p><p><b>Background & Objective:</b> Assessment of muscularis propria invasion is a crucial step in the management of urothelial carcinoma since it necessitates aggressive treatment. The diagnosis of muscle invasion is a challenging process for pathologists. Artificial intelligence is developing rapidly and being implemented in various fields of pathology. The purpose of this study was to develop an algorithm for the detection of muscularis propria invasion in urothelial carcinoma. <b>Methods:</b> The Training cohort consisted of 925 images from 50 specimens of urothelial carcinoma. Ninety-seven images from 10 new specimens were used as a validation cohort. Clinical validation used 127 whole specimens with a total of 617 slides. The algorithm determined areas where tumor and muscularis propria events were in nearest proximity, and presented these areas to the pathologist. <b>Results:</b> Analytical evaluation showed a sensitivity of 72% for muscularis propria and 65% for tumor, and a specificity of 46% and 77% for muscularis propria and tumor detection, respectively. The incorporation of the spatial proximity factor between muscularis propria and tumor in the clinical validation significantly improved the detection of muscularis propria invasion, as the algorithm managed to identify all except for one case with muscle invasive bladder cancer in the clinical validation cohort. The case missed by the algorithm was nested urothelial carcinoma, a rare subtype with unusual morphologic features. The pathologist managed to identify muscle invasion based on the images provided by the algorithm in a short time, with an average of approximately 5 s. <b>Conclusion:</b> The algorithm we developed may greatly aid in accurate identification of muscularis propria invasion by imitating the thought process of the pathologist.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11135091/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141156827","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":"Assessing the Impact of Charged Particle Radiation Therapy for Head and Neck Adenoid Cystic Carcinoma: A Systematic Review and Meta-Analysis.","authors":"Mingyu Tan, Yanliang Chen, Tianqi Du, Qian Wang, Xun Wu, Qiuning Zhang, Hongtao Luo, Zhiqiang Liu, Shilong Sun, Kehu Yang, Jinhui Tian, Xiaohu Wang","doi":"10.1177/15330338241246653","DOIUrl":"10.1177/15330338241246653","url":null,"abstract":"<p><p><b>Purpose:</b> Head and neck adenoid cystic carcinoma (HNACC) is a radioresistant tumor. Particle therapy, primarily proton beam therapy and carbon-ion radiation, is a potential radiotherapy treatment for radioresistant malignancies. This study aims to conduct a meta-analysis to evaluate the impact of charged particle radiation therapy on HNACC. <b>Methods:</b> A comprehensive search was conducted in Pubmed, Cochrane Library, Web of Science, Embase, and Medline until December 31, 2022. The primary endpoints were overall survival (OS), local control (LC), and progression-free survival (PFS), while secondary outcomes included treatment-related toxicity. Version 17.0 of STATA was used for all analyses. <b>Results:</b> A total of 14 studies, involving 1297 patients, were included in the analysis. The pooled 5-year OS and PFS rates for primary HNACC were 78% (95% confidence interval [CI] = 66-91%) and 62% (95% CI = 47-77%), respectively. For all patients included, the pooled 2-year and 5-year OS, LC, and PFS rates were as follows: 86.1% (95% CI = 95-100%) and 77% (95% CI = 73-82%), 92% (95% CI = 84-100%) and 73% (95% CI = 61-85%), and 76% (95% CI = 68-84%) and 55% (95% CI = 48-62%), respectively. The rates of grade 3 and above acute toxicity were 22% (95% CI = 13-32%), while late toxicity rates were 8% (95% CI = 3-13%). <b>Conclusions:</b> Particle therapy has the potential to improve treatment outcomes and raise the quality of life for HNACC patients. However, further research and optimization are needed due to the limited availability and cost considerations associated with this treatment modality.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11113043/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141076982","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":"Stereotactic Body Radiotherapy Reirradiation Is Safe in Patients With Lung Cancer With In-Field Enlarged Tumor Recurrence.","authors":"Tanju Berber, Berna Akkuş Yıldırım, Özge Kandemir Gürsel","doi":"10.1177/15330338231208616","DOIUrl":"10.1177/15330338231208616","url":null,"abstract":"<p><p><b>Introduction:</b> Recurrence after stage III lung cancer treatment usually appears with a poor prognosis, and salvage therapy for these patients is challenging, with limited data for reirradiation. <b>Materials and Methods:</b> Fifteen patients with recurrent stage III lung cancer treated with stereotactic body radiotherapy (SABR) between October 2013 and December 2017 were retrospectively evaluated for local control as a first endpoint; overall survival, disease-free survival, and treatment-related toxicity were secondary endpoints. <b>Results:</b> The median age was 68 (IQR: 50-71) years, and the median tumor size was 3.3 cm (IQR: 3.0-4.5). The radiation field was all within the previous radiation (previous 80%-90% isodose line), and the median dose was 66 Gy/(2 Gy × 33 <i>standard fractionation</i>)<i>.</i> For SABR, the median biologically effective dose at an α/β ratio of 10 (BED₁₀) was 60.0 Gy (IQR: 39.38-85.0) and given in 3 to 5 fractions. Three patients experienced grade 3 or 4 toxicity but none experienced grade 5. The median follow-up period was 14 (IQR: 10-23) months. The local control rate was found as 86.7% in the first year, 80% in the second year, and 80% in the third year. The median disease-free survival was 8 (IQR: 6-20) months and the median overall survival was 14 (IQR: 10-23) months. The rate of overall survival was 66.6% for the first year and 33.3% for the second and third years. The disease-free survival rate was 46.6% for the first year and 40% for the second and third years. Nine patients who received doses of BED₁₀ ≥ 50 Gy developed no local recurrence (<i>P</i>  =  .044). <b>Discussion:</b> In local local-regional recurrence of lung cancer, radiosurgery as reirradiation can be used at doses of BED₁₀ ≥ 50 Gy and above to provide local control for radical or palliative purposes. SABR is an important and relatively safe treatment option in such recurrences.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11168055/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141301655","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":"Large Foundation Model for Cancer Segmentation.","authors":"Zeyu Ren, Yudong Zhang, Shuihua Wang","doi":"10.1177/15330338241266205","DOIUrl":"10.1177/15330338241266205","url":null,"abstract":"<p><p>Recently, large language models such as ChatGPT have made huge strides in understanding and generating human-like text and have demonstrated considerable success in natural language processing. These foundation models also perform well in computer vision. However, there is a growing need to use these technologies for specific medical tasks, especially for identifying cancer in images. This paper looks at how these foundation models, such as the segment anything model, could be used for cancer segmentation, discussing the potential benefits and challenges of applying large foundation models to help with cancer diagnoses.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11273567/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141761031","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":"Analysis of Expression Pattern and Prognostic Value of the Heparanase in Breast Cancer Through CD274/CTLA-4 Immune Checkpoint Proteins.","authors":"Weijia Kong, Ganlin Zhang, Yue Wang, Jiahui Zhang, Tongjing Ding, Dong Chen, Yuancan Pan, Runxi Yi, Xiaohui Yin, Xiaomin Wang","doi":"10.1177/15330338241281285","DOIUrl":"10.1177/15330338241281285","url":null,"abstract":"<p><p><b>Objectives:</b> Heparanase (HPSE), an endoglycosidase that cleaves heparan sulfate, regulates various biological processes related to tumor progression. We explore the prognostic value of HPSE and its relationship with immunotherapy response in patients with breast cancer, to improve the effectiveness of immunotherapy and increase the survival outcomes. <b>Methods:</b> In the study, we explored the prognostic value of HPSE through the The Cancer Genome Atlas (TCGA) database. By using the single-sample gene set enrichment analysis <b>(</b>ssGSEA) method, we measured the infiltration levels of 24 immune cell types in the tumor microenvironment. Cancer Therapeutics Response Portal (CTRP) and PRISM datasets provide the area under the dose-response curve (AUC) to measure drug sensitivity. Using nomograms, we predicted overall survival ability. In vivo studies, we investigated the relationship between HPSE and immune checkpoint proteins and pro-inflammatory cytokines by immunohistochemistry of Triple-Negative Breast Cancer tumors in mice. <b>Results:</b> Our model demonstrated that the integrating of HPSE with the clinical stage effectively predicts patients' survival time, highlighting high HPSE expression as a prognostic risk factor for breast cancer. Then the Receiver Operating Characteristic (ROC) curve [AUC of 1 year = 0.747, AUC of 3 years = 0.731] and Decision Curve Analysis (DCA) curve illustrated the satisfactory discriminative capacity of our model, emphasizing its valuable clinical applicability. Immune-related results showed that HPSE correlates strongly with immune infiltrating cells, immune-related genes, and the anti-cancer immunity cycle. In vivo studies have demonstrated that HPSE in breast cancer is associated with increased expression of immune checkpoint proteins CD274 and cytotoxic T lymphocyte-associated protein 4 (CTLA-4) and is positively correlated with the pro-inflammatory cytokine TNF-α. Meanwhile, we analyzed the 11 types of drugs that are sensitive to the HPSE gene. <b>Conclusion:</b> Our results show that HPSE can serve as an effective biomarker to predict the prognosis of breast cancer patients and reflect the impact of immunotherapy.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11388313/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142154979","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":"Rad51 and Systemic Inflammatory Indicators as Novel Prognostic Markers in Esophageal Squamous Cell Carcinoma.","authors":"Ning Wu, Yang Song, Yongjun Zhu, Liewen Pang, Zhiming Chen, Xiaofeng Chen","doi":"10.1177/15330338231216333","DOIUrl":"10.1177/15330338231216333","url":null,"abstract":"<p><strong>Background: </strong>RAD51 is a central protein involved in homologous recombination, which has been linked to cancer development and progression. systemic inflammatory indicator markers such as neutrophil-to-lymphocyte ratio and lymphocyte-to-monocyte ratio have also been implicated in cancer. However, the relationship between Rad51 and these inflammatory markers in esophageal cancer patients undergoing esophagectomy is not yet understood.</p><p><strong>Methods: </strong>We retrospectively observed 320 esophageal cancer patients who underwent esophagectomy. We collected clinical characteristics, postoperative complications, and survival analysis data and analyzed the relationship between Rad51 expression, inflammatory markers, and prognosis.</p><p><strong>Results: </strong>We found significant linear relationships among the inflammatory markers. There were also close relationships between Rad51 expression and neutrophil-to-lymphocyte ratio or C-reactive protein. Patients with low lymphocyte percentage were more likely to have low Rad51 expression (<i>P</i> = .026), high C-reactive protein (<i>P</i> = .007), and high neutrophil-to-lymphocyte ratio (<i>P</i> = .006). Low lymphocyte-to-monocyte ratio was associated with poor overall survival and was an independent prognostic factor (HR = 2.214; 95% confidence interval: 1.044-4.695, <i>P</i> = .038). In patients without lymph node metastases, low albumin (HR= 0.131; 95% confidence interval: 0.025-0.687, <i>P</i> = .016), high neutrophil-to-lymphocyte ratio (HR = 0.002; 95% confidence interval: 0.000-0.221, <i>P</i> = .009), and high Rad51 expression (HR = 14.394; 95% confidence interval: 2.217-97.402, <i>P</i> = .006) were associated with poor overall survival.</p><p><strong>Conclusions: </strong>Our study found a close correlation between elevated Rad51 expression and inflammatory markers. High Rad51 expression, high neutrophil-to-lymphocyte ratio, and low lymphocyte-to-monocyte ratio are associated with lower survival rates. The combined assessment of Rad51 and inflammatory markers can be useful for preoperative assessment and prognostic evaluation in esophageal squamous cell carcinoma patients.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10807337/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139521831","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":"Deep Learning-Based Prediction of Radiation Therapy Dose Distributions in Nasopharyngeal Carcinomas: A Preliminary Study Incorporating Multiple Features Including Images, Structures, and Dosimetry.","authors":"Yixuan Wang, Zun Piao, Huikuan Gu, Meining Chen, Dandan Zhang, Jinhan Zhu","doi":"10.1177/15330338241256594","DOIUrl":"10.1177/15330338241256594","url":null,"abstract":"<p><p><b>Purpose:</b> Intensity-modulated radiotherapy (IMRT) is currently the most important treatment method for nasopharyngeal carcinoma (NPC). This study aimed to enhance prediction accuracy by incorporating dose information into a deep convolutional neural network (CNN) using a multichannel input method. <b>Methods:</b> A target conformal plan (TCP) was created based on the maximum planning target volume (PTV). Input data included TCP dose distribution, images, target structures, and organ-at-risk (OAR) information. The role of target conformal plan dose (TCPD) was assessed by comparing the TCPD-CNN (with dose information) and NonTCPD-CNN models (without dose information) using statistical analyses with the ranked Wilcoxon test (<i>P</i> < .05 considered significant). <b>Results:</b> The TCPD-CNN model showed no statistical differences in predicted target indices, except for PTV60, where differences in the D98% indicator were < 0.5%. For OARs, there were no significant differences in predicted results, except for some small-volume or closely located OARs. On comparing TCPD-CNN and NonTCPD-CNN models, TCPD-CNN's dose-volume histograms closely resembled clinical plans with higher similarity index. Mean dose differences for target structures (predicted TCPD-CNN and NonTCPD-CNN results) were within 3% of the maximum prescription dose for both models. TCPD-CNN and NonTCPD-CNN outcomes were 67.9% and 54.2%, respectively. 3D gamma pass rates of the target structures and the entire body were higher in TCPD-CNN than in the NonTCPD-CNN models (<i>P</i> < .05). Additional evaluation on previously unseen volumetric modulated arc therapy plans revealed that average 3D gamma pass rates of the target structures were larger than 90%. <b>Conclusions:</b> This study presents a novel framework for dose distribution prediction using deep learning and multichannel input, specifically incorporating TCPD information, enhancing prediction accuracy for IMRT in NPC treatment.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11190807/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141161625","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":"Identification of Breast Cancer Subtypes Based on Endoplasmic Reticulum Stress-Related Genes and Analysis of Prognosis and Immune Microenvironment in Breast Cancer Patients.","authors":"Chen Yi, Jun Yang, Ting Zhang, Liu Qin, Dongjuan Chen","doi":"10.1177/15330338241241484","DOIUrl":"10.1177/15330338241241484","url":null,"abstract":"<p><p><b>Introduction:</b> Endoplasmic reticulum stress (ERS) was a response to the accumulation of unfolded proteins and plays a crucial role in the development of tumors, including processes such as tumor cell invasion, metastasis, and immune evasion. However, the specific regulatory mechanisms of ERS in breast cancer (BC) remain unclear. <b>Methods:</b> In this study, we analyzed RNA sequencing data from The Cancer Genome Atlas (TCGA) for breast cancer and identified 8 core genes associated with ERS: ELOVL2, IFNG, MAP2K6, MZB1, PCSK6, PCSK9, IGF2BP1, and POP1. We evaluated their individual expression, independent diagnostic, and prognostic values in breast cancer patients. A multifactorial Cox analysis established a risk prognostic model, validated with an external dataset. Additionally, we conducted a comprehensive assessment of immune infiltration and drug sensitivity for these genes. <b>Results:</b> The results indicate that these eight core genes play a crucial role in regulating the immune microenvironment of breast cancer (BRCA) patients. Meanwhile, an independent diagnostic model based on the expression of these eight genes shows limited independent diagnostic value, and its independent prognostic value is unsatisfactory, with the time ROC AUC values generally below 0.5. According to the results of logistic regression neural networks and risk prognosis models, when these eight genes interact synergistically, they can serve as excellent biomarkers for the diagnosis and prognosis of breast cancer patients. Furthermore, the research findings have been confirmed through qPCR experiments and validation. <b>Conclusion:</b> In conclusion, we explored the mechanisms of ERS in BRCA patients and identified 8 outstanding biomolecular diagnostic markers and prognostic indicators. The research results were double-validated using the GEO database and qPCR.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11085026/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140899284","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":"Involvement of S100A6/S100A11 in T-Cell Immune Regulatory in HCC Revealed by Single Cell RNA-seq.","authors":"Rui Zhou, Bo Pei, Xinzhi Li, Xianlin Zhang","doi":"10.1177/15330338241252610","DOIUrl":"10.1177/15330338241252610","url":null,"abstract":"<p><p><b>Background</b>: Immunotherapy plays a significant role in the treatment of hepatocellular carcinoma (HCC). Members of the S100 protein family (S100s) have been widely implicated in the pathogenesis and progression of tumors. However, the exact mechanism by which S100s contribute to tumor immunity remains unclear. <b>Methods:</b> To explore the role of S100s in HCC immune cells, we collected and comparatively analyzed single-cell RNA sequencing (scRNA-seq) data of HCC and hepatitis B virus-associated HCC. By mapping cell classification and searching for S100s binding targets and downstream targets. <b>Results:</b> S100A6/S100A11 was differentially expressed in tumor T cells and involved in the nuclear factor (NF) κB pathway. Further investigation of the TCGA dataset revealed that patients with low S100A6/S100A11 expression had a better prognosis. Temporal cell trajectory analysis showed that the activation of the NF-κB pathway is at a critical stage and has an important impact on the tumor microenvironment. <b>Conclusion:</b> Our study revealed that S100A6/S100A11 could be involved in regulating the differentiation and cellular activity of T-cell subpopulations in HCC, and its low expression was positively correlated with prognosis. It may provide a new direction for immunotherapy of HCC and a theoretical basis for future clinical applications.</p>","PeriodicalId":22203,"journal":{"name":"Technology in Cancer Research & Treatment","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11104034/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141065614","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}