Pub Date : 2024-09-09DOI: 10.3389/fonc.2024.1420666
Jaroslav Cermak
IntroductionInherited bone marrow failure (IBMF) syndromes are caused by mutations forming pathologic germline variants resulting in the production of defective hematopoietic stem cells (HSC) and in congenital failure in the production of one or more blood lineages. An acquisition of subsequent somatic mutations is determining further course of the disease. Nevertheless, a certain number of patients with IBMF may escape correct diagnosis in childhood, especially those with mild cytopenia and minimal clinical features without non-hematologic symptoms. These patients usually present in the third decade of life with unexplained cytopenia or myelodysplastic syndrome (MDS).Methods and resultsWe report 2 patients with IBMF who were correctly diagnosed between 20 and 40 years of age when they were referred with progressive MDS with adverse prognostic factors that affected their outcome.DiscussionIBMF syndromes should be excluded in all patients below 40 years of age with unexplained cytopenia. Early hematopoietic stem cell transplantation (HSCT) is the treatment of choice in these patients.
{"title":"Case report: Development of clonal hematologic disorders from inherited bone marrow failure","authors":"Jaroslav Cermak","doi":"10.3389/fonc.2024.1420666","DOIUrl":"https://doi.org/10.3389/fonc.2024.1420666","url":null,"abstract":"IntroductionInherited bone marrow failure (IBMF) syndromes are caused by mutations forming pathologic germline variants resulting in the production of defective hematopoietic stem cells (HSC) and in congenital failure in the production of one or more blood lineages. An acquisition of subsequent somatic mutations is determining further course of the disease. Nevertheless, a certain number of patients with IBMF may escape correct diagnosis in childhood, especially those with mild cytopenia and minimal clinical features without non-hematologic symptoms. These patients usually present in the third decade of life with unexplained cytopenia or myelodysplastic syndrome (MDS).Methods and resultsWe report 2 patients with IBMF who were correctly diagnosed between 20 and 40 years of age when they were referred with progressive MDS with adverse prognostic factors that affected their outcome.DiscussionIBMF syndromes should be excluded in all patients below 40 years of age with unexplained cytopenia. Early hematopoietic stem cell transplantation (HSCT) is the treatment of choice in these patients.","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.3389/fonc.2024.1399296
Yini Li, Cao Li, Tao Yang, Lingzhi Chen, Mingquan Huang, Lu Yang, Shuxian Zhou, Huaqing Liu, Jizhu Xia, Shijie Wang
ObjectivesTo develop and validate a deep learning (DL) based automatic segmentation and classification system to classify benign and malignant BI-RADS 4 lesions imaged with ABVS.MethodsFrom May to December 2020, patients with BI-RADS 4 lesions from Centre 1 and Centre 2 were retrospectively enrolled and divided into a training set (Centre 1) and an independent test set (Centre 2). All included patients underwent an ABVS examination within one week before the biopsy. A two-stage DL framework consisting of an automatic segmentation module and an automatic classification module was developed. The preprocessed ABVS images were input into the segmentation module for BI-RADS 4 lesion segmentation. The classification model was constructed to extract features and output the probability of malignancy. The diagnostic performances among different ABVS views (axial, sagittal, coronal, and multi-view) and DL architectures (Inception-v3, ResNet 50, and MobileNet) were compared.ResultsA total of 251 BI-RADS 4 lesions from 216 patients were included (178 in the training set and 73 in the independent test set). The average Dice coefficient, precision, and recall of the segmentation module in the test set were 0.817 ± 0.142, 0.903 ± 0.183, and 0.886 ± 0.187, respectively. The DL model based on multiview ABVS images and Inception-v3 achieved the best performance, with an AUC, sensitivity, specificity, PPV, and NPV of 0.949 (95% CI: 0.945-0.953), 82.14%, 95.56%, 92.00%, and 89.58%, respectively, in the test set.ConclusionsThe developed multiview DL model enables automatic segmentation and classification of BI-RADS 4 lesions in ABVS images.
{"title":"Multiview deep learning networks based on automated breast volume scanner images for identifying breast cancer in BI-RADS 4","authors":"Yini Li, Cao Li, Tao Yang, Lingzhi Chen, Mingquan Huang, Lu Yang, Shuxian Zhou, Huaqing Liu, Jizhu Xia, Shijie Wang","doi":"10.3389/fonc.2024.1399296","DOIUrl":"https://doi.org/10.3389/fonc.2024.1399296","url":null,"abstract":"ObjectivesTo develop and validate a deep learning (DL) based automatic segmentation and classification system to classify benign and malignant BI-RADS 4 lesions imaged with ABVS.MethodsFrom May to December 2020, patients with BI-RADS 4 lesions from Centre 1 and Centre 2 were retrospectively enrolled and divided into a training set (Centre 1) and an independent test set (Centre 2). All included patients underwent an ABVS examination within one week before the biopsy. A two-stage DL framework consisting of an automatic segmentation module and an automatic classification module was developed. The preprocessed ABVS images were input into the segmentation module for BI-RADS 4 lesion segmentation. The classification model was constructed to extract features and output the probability of malignancy. The diagnostic performances among different ABVS views (axial, sagittal, coronal, and multi-view) and DL architectures (Inception-v3, ResNet 50, and MobileNet) were compared.ResultsA total of 251 BI-RADS 4 lesions from 216 patients were included (178 in the training set and 73 in the independent test set). The average Dice coefficient, precision, and recall of the segmentation module in the test set were 0.817 ± 0.142, 0.903 ± 0.183, and 0.886 ± 0.187, respectively. The DL model based on multiview ABVS images and Inception-v3 achieved the best performance, with an AUC, sensitivity, specificity, PPV, and NPV of 0.949 (95% CI: 0.945-0.953), 82.14%, 95.56%, 92.00%, and 89.58%, respectively, in the test set.ConclusionsThe developed multiview DL model enables automatic segmentation and classification of BI-RADS 4 lesions in ABVS images.","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.3389/fonc.2024.1387014
Yan Lei, Shucui Wang, Jun Chen, Lanjun Liu, Linting Huang, Xiujuan Wu, Hui Xu, Yali Yang
BackgroundPrimary malignant melanoma (MM) of skin threatens health, especially in the older population, causing a significant risk of early death. The purpose of this study was to establish a diagnostic nomogram to predict the early mortality risk in older patients with primary skin MM and to determine the independent risk factors of cancer-specific early death in such patients.MethodsThe Surveillance, Epidemiology and End Results (SEER) database provided the clinical and pathological characteristics of older patients with primary skin MM from 2000 to 2019. Initially, a 7:3 random assignment was used to place the recruited patients into training and validation cohorts. Then, the independent risk variables of cancer-specific early death in those individuals were determined using univariate and multivariate logistic regression analysis. Those patients’ diagnostic nomograms were constructed using the acquired independent risk variables. Ultimately, the performance of the newly created diagnostic nomogram was verified using calibration curves, receiver operating characteristic (ROC), and decision curve analysis (DCA) curves.ResultsIn this study, 2,615 patients in total were included. Age, histology, liver metastasis, tumor stage, surgery, therapy, and radiation were found to be independent risk factors following statistical analysis, with a special emphasis on early death in older patients with primary skin MM. A diagnostic nomogram for the cancer-specific early death risk was created and validated based on these variables. High agreement was reported between the expected and actual probabilities in the calibration curves. Area under the curves (AUC) of the novel created diagnostic nomogram was greater than that of each independent risk factor, with AUCs for the training and validation cohorts being 0.966 and 0.971, respectively. The nomogram had a high value for its applicability in clinical settings, according to DCA.ConclusionIn older patients with primary skin MM, the current study created a diagnostic nomogram to predict the probability of cancer-specific early death. Because of the nomograms’ good performance, physicians will be better able to identify older patients who are at a high risk of early death and treat them individually to increase their survival benefit.
背景原发性皮肤恶性黑色素瘤（MM）威胁着人们的健康，尤其是在老年人群中，会导致很大的早期死亡风险。本研究的目的是建立一个诊断提名图来预测老年原发性皮肤 MM 患者的早期死亡风险，并确定此类患者癌症特异性早期死亡的独立风险因素。方法监测、流行病学和最终结果（SEER）数据库提供了 2000 年至 2019 年老年原发性皮肤 MM 患者的临床和病理特征。首先，采用7:3随机分配法将所招募的患者分为训练队列和验证队列。然后，利用单变量和多变量逻辑回归分析确定了这些患者癌症特异性早期死亡的独立风险变量。利用获得的独立风险变量构建这些患者的诊断提名图。最后，利用校准曲线、接收者操作特征曲线（ROC）和决策曲线分析（DCA）曲线验证了新创建的诊断提名图的性能。经统计分析发现，年龄、组织学、肝转移、肿瘤分期、手术、治疗和放疗是独立的风险因素，其中年龄较大的原发性皮肤 MM 患者的早期死亡尤为突出。根据这些变量创建并验证了癌症特异性早期死亡风险诊断提名图。据报告，校准曲线中的预期概率与实际概率高度一致。新创建的诊断提名图的曲线下面积（AUC）大于每个独立风险因素的曲线下面积，训练组和验证组的AUC分别为0.966和0.971。结论 在老年原发性皮肤 MM 患者中，本研究创建了一个诊断提名图来预测癌症特异性早期死亡的概率。由于提名图的良好表现，医生将能更好地识别有较高早期死亡风险的老年患者，并对他们进行个体化治疗，以提高他们的生存率。
{"title":"A novel tool for predicting the risk of cancer-specific early death in older patients with primary malignant melanoma of skin: a population-based analysis","authors":"Yan Lei, Shucui Wang, Jun Chen, Lanjun Liu, Linting Huang, Xiujuan Wu, Hui Xu, Yali Yang","doi":"10.3389/fonc.2024.1387014","DOIUrl":"https://doi.org/10.3389/fonc.2024.1387014","url":null,"abstract":"BackgroundPrimary malignant melanoma (MM) of skin threatens health, especially in the older population, causing a significant risk of early death. The purpose of this study was to establish a diagnostic nomogram to predict the early mortality risk in older patients with primary skin MM and to determine the independent risk factors of cancer-specific early death in such patients.MethodsThe Surveillance, Epidemiology and End Results (SEER) database provided the clinical and pathological characteristics of older patients with primary skin MM from 2000 to 2019. Initially, a 7:3 random assignment was used to place the recruited patients into training and validation cohorts. Then, the independent risk variables of cancer-specific early death in those individuals were determined using univariate and multivariate logistic regression analysis. Those patients’ diagnostic nomograms were constructed using the acquired independent risk variables. Ultimately, the performance of the newly created diagnostic nomogram was verified using calibration curves, receiver operating characteristic (ROC), and decision curve analysis (DCA) curves.ResultsIn this study, 2,615 patients in total were included. Age, histology, liver metastasis, tumor stage, surgery, therapy, and radiation were found to be independent risk factors following statistical analysis, with a special emphasis on early death in older patients with primary skin MM. A diagnostic nomogram for the cancer-specific early death risk was created and validated based on these variables. High agreement was reported between the expected and actual probabilities in the calibration curves. Area under the curves (AUC) of the novel created diagnostic nomogram was greater than that of each independent risk factor, with AUCs for the training and validation cohorts being 0.966 and 0.971, respectively. The nomogram had a high value for its applicability in clinical settings, according to DCA.ConclusionIn older patients with primary skin MM, the current study created a diagnostic nomogram to predict the probability of cancer-specific early death. Because of the nomograms’ good performance, physicians will be better able to identify older patients who are at a high risk of early death and treat them individually to increase their survival benefit.","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.3389/fonc.2024.1451650
Jinkun Xia, Chaoyu Wang, Biao Li
Tumor immune microenvironment (TIME) is a tiny structure that contains multiple immune cell components around tumor cells, which plays an important role in tumorigenesis, and is also the potential core area of activated immunotherapy. How immune cells with tumor-killing capacity in TIME are hijacked by tumor cells during the progression of tumorigenesis and transformed into subpopulations that facilitate cancer advancement is a question that needs to be urgently addressed nowadays. γδ T cells (their T cell receptors are composed of γ and δ chains), a unique T cell subpopulation distinguished from conventional αβ T cells, are involved in a variety of immune response processes through direct tumor-killing effects and/or indirectly influencing the activity of other immune cells. However, the presence of γδ T cells in the tumor microenvironment (TME) has been reported to be associated with poor prognosis in some tumors, suggesting that certain γδ T cell subsets may also have pro-tumorigenic effects. Recent studies have revealed that metabolic pathways such as activation of glycolysis, increase of lipid metabolism, enhancement of mitochondrial biosynthesis, alterations of fatty acid metabolism reshape the local TME, and immune cells trigger metabolic adaptation through metabolic reprogramming to meet their own needs and play the role of anti-tumor or immunosuppression. Combining previous studies and our bioinformatics results, we hypothesize that γδT cells compete for resources with hepatocellular carcinoma (HCC) cells by means of fatty acid metabolic regulation in the TME, which results in the weakening or loss of their ability to recognize and kill HCC cells through genetic and epigenetic alterations, thus allowing γδT cells to be hijacked by HCC cells as a subpopulation that promotes HCC progression.
肿瘤免疫微环境（TIME）是肿瘤细胞周围包含多种免疫细胞成分的微小结构，在肿瘤发生过程中发挥着重要作用，也是活化免疫疗法的潜在核心区域。TIME中具有杀伤肿瘤能力的免疫细胞如何在肿瘤发生过程中被肿瘤细胞劫持，并转化为促进癌症进展的亚群，是当前急需解决的问题。γδT细胞（其T细胞受体由γ和δ链组成）是一种独特的T细胞亚群，有别于传统的αβT细胞，通过直接杀伤肿瘤和/或间接影响其他免疫细胞的活性，参与多种免疫反应过程。然而，据报道，肿瘤微环境（TME）中γδ T 细胞的存在与某些肿瘤的不良预后有关，这表明某些γδ T 细胞亚群也可能具有促肿瘤作用。最近的研究发现，糖酵解激活、脂质代谢增加、线粒体生物合成增强、脂肪酸代谢改变等代谢途径重塑了局部TME，免疫细胞通过代谢重编程触发代谢适应，以满足自身需要，发挥抗肿瘤或免疫抑制的作用。结合以往的研究和我们的生物信息学结果，我们假设γδT细胞通过脂肪酸代谢调控在TME中与肝细胞癌（HCC）细胞争夺资源，通过遗传和表观遗传学改变导致其识别和杀伤HCC细胞的能力减弱或丧失，从而使γδT细胞被HCC细胞劫持成为促进HCC进展的亚群。
{"title":"Hepatocellular carcinoma cells induce γδ T cells through metabolic reprogramming into tumor-progressive subpopulation","authors":"Jinkun Xia, Chaoyu Wang, Biao Li","doi":"10.3389/fonc.2024.1451650","DOIUrl":"https://doi.org/10.3389/fonc.2024.1451650","url":null,"abstract":"Tumor immune microenvironment (TIME) is a tiny structure that contains multiple immune cell components around tumor cells, which plays an important role in tumorigenesis, and is also the potential core area of activated immunotherapy. How immune cells with tumor-killing capacity in TIME are hijacked by tumor cells during the progression of tumorigenesis and transformed into subpopulations that facilitate cancer advancement is a question that needs to be urgently addressed nowadays. γδ T cells (their T cell receptors are composed of γ and δ chains), a unique T cell subpopulation distinguished from conventional αβ T cells, are involved in a variety of immune response processes through direct tumor-killing effects and/or indirectly influencing the activity of other immune cells. However, the presence of γδ T cells in the tumor microenvironment (TME) has been reported to be associated with poor prognosis in some tumors, suggesting that certain γδ T cell subsets may also have pro-tumorigenic effects. Recent studies have revealed that metabolic pathways such as activation of glycolysis, increase of lipid metabolism, enhancement of mitochondrial biosynthesis, alterations of fatty acid metabolism reshape the local TME, and immune cells trigger metabolic adaptation through metabolic reprogramming to meet their own needs and play the role of anti-tumor or immunosuppression. Combining previous studies and our bioinformatics results, we hypothesize that γδT cells compete for resources with hepatocellular carcinoma (HCC) cells by means of fatty acid metabolic regulation in the TME, which results in the weakening or loss of their ability to recognize and kill HCC cells through genetic and epigenetic alterations, thus allowing γδT cells to be hijacked by HCC cells as a subpopulation that promotes HCC progression.","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.3389/fonc.2024.1368119
Sarah J. Hardcastle, Marta Leyton-Román, Chloe Maxwell-Smith, Dana Hince
BackgroundThe PPARCS trial examined the efficacy of a distance-based wearable and health coaching intervention to increase physical activity (PA) in breast and colorectal cancer (CRC) survivors living in non-metropolitan areas. This paper examines the effects of the intervention on health-related quality of life (HRQoL) at 12 weeks (T2; end of intervention) and 24 weeks (T3; follow-up).MethodsParticipants that were insufficiently physically active and had successfully completed cancer treatment were randomised to an intervention or control group. PA was assessed using an ActiGraph (GT9X) at baseline, T2, and T3. Intervention effects on HRQoL were analysed using quantile regression comparing treatment groups across time.ResultsA total of 87 were randomised to intervention and control groups. There were generally no statistically significant differences between the groups on any HRQoL item except for pain. There was an arm (F(1, 219) = 5.0. p = 0.027) and time (F(2,221) = 4.8, p = 0.009) effect, reflecting the higher pain scores in the control group when collapsed across time points (median difference 16.7, CI 1.9 to 31.4, p = 0.027). For global HRQoL, the intervention group increased by 8.3 points between T1 and T2. The overall group median when collapsed across time was 16.7 points CI 8.2 to 25.2, p <0.001) greater in the intervention group than controls.ConclusionsWhile the PPARCS intervention resulted in significant increases in PA, participants indicated a high HRQoL at baseline, leaving little room for improvement. Findings suggest that PA may improve global HRQoL and pain in breast and CRC survivors.
{"title":"Impact of the Promoting Physical Activity in Regional and Remote Cancer Survivors intervention on health-related quality of life in breast and colorectal cancer survivors","authors":"Sarah J. Hardcastle, Marta Leyton-Román, Chloe Maxwell-Smith, Dana Hince","doi":"10.3389/fonc.2024.1368119","DOIUrl":"https://doi.org/10.3389/fonc.2024.1368119","url":null,"abstract":"BackgroundThe PPARCS trial examined the efficacy of a distance-based wearable and health coaching intervention to increase physical activity (PA) in breast and colorectal cancer (CRC) survivors living in non-metropolitan areas. This paper examines the effects of the intervention on health-related quality of life (HRQoL) at 12 weeks (T2; end of intervention) and 24 weeks (T3; follow-up).MethodsParticipants that were insufficiently physically active and had successfully completed cancer treatment were randomised to an intervention or control group. PA was assessed using an ActiGraph (GT9X) at baseline, T2, and T3. Intervention effects on HRQoL were analysed using quantile regression comparing treatment groups across time.ResultsA total of 87 were randomised to intervention and control groups. There were generally no statistically significant differences between the groups on any HRQoL item except for pain. There was an arm (F(1, 219) = 5.0. p = 0.027) and time (F(2,221) = 4.8, p = 0.009) effect, reflecting the higher pain scores in the control group when collapsed across time points (median difference 16.7, CI 1.9 to 31.4, p = 0.027). For global HRQoL, the intervention group increased by 8.3 points between T1 and T2. The overall group median when collapsed across time was 16.7 points CI 8.2 to 25.2, p &lt;0.001) greater in the intervention group than controls.ConclusionsWhile the PPARCS intervention resulted in significant increases in PA, participants indicated a high HRQoL at baseline, leaving little room for improvement. Findings suggest that PA may improve global HRQoL and pain in breast and CRC survivors.","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.3389/fonc.2024.1449068
Di Yang, Yafei Miao, Changjiang Liu, Nan Zhang, Duo Zhang, Qiang Guo, Shuo Gao, Linqian Li, Jianing Wang, Si Liang, Peng Li, Xuan Bai, Ke Zhang
Lung cancer remains a leading cause of cancer-related deaths globally, with its incidence steadily rising each year, representing a significant threat to human health. Early detection, diagnosis, and timely treatment play a crucial role in improving survival rates and reducing mortality. In recent years, significant and rapid advancements in artificial intelligence (AI) technology have found successful applications in various clinical areas, especially in the diagnosis and treatment of lung cancer. AI not only improves the efficiency and accuracy of physician diagnosis but also aids in patient treatment and management. This comprehensive review presents an overview of fundamental AI-related algorithms and highlights their clinical applications in lung nodule detection, lung cancer pathology classification, gene mutation prediction, treatment strategies, and prognosis. Additionally, the rapidly advancing field of AI-based three-dimensional (3D) reconstruction in lung cancer surgical resection is discussed. Lastly, the limitations of AI and future prospects are addressed.
{"title":"Advances in artificial intelligence applications in the field of lung cancer","authors":"Di Yang, Yafei Miao, Changjiang Liu, Nan Zhang, Duo Zhang, Qiang Guo, Shuo Gao, Linqian Li, Jianing Wang, Si Liang, Peng Li, Xuan Bai, Ke Zhang","doi":"10.3389/fonc.2024.1449068","DOIUrl":"https://doi.org/10.3389/fonc.2024.1449068","url":null,"abstract":"Lung cancer remains a leading cause of cancer-related deaths globally, with its incidence steadily rising each year, representing a significant threat to human health. Early detection, diagnosis, and timely treatment play a crucial role in improving survival rates and reducing mortality. In recent years, significant and rapid advancements in artificial intelligence (AI) technology have found successful applications in various clinical areas, especially in the diagnosis and treatment of lung cancer. AI not only improves the efficiency and accuracy of physician diagnosis but also aids in patient treatment and management. This comprehensive review presents an overview of fundamental AI-related algorithms and highlights their clinical applications in lung nodule detection, lung cancer pathology classification, gene mutation prediction, treatment strategies, and prognosis. Additionally, the rapidly advancing field of AI-based three-dimensional (3D) reconstruction in lung cancer surgical resection is discussed. Lastly, the limitations of AI and future prospects are addressed.","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.3389/fonc.2024.1450326
Nurshad Ali, Silvana Debernardi, Evelyn Kurotova, Jian Tajbakhsh, Nirdesh K. Gupta, Stephen J. Pandol, Patrick Wilson, Stephen P. Pereira, Bill Greenhalf, Oleg Blyuss, Tatjana Crnogorac-Jurcevic
Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related death worldwide. Up to now, no specific screening or diagnostic tests are available for early PDAC detection. As a result, most patients are diagnosed with advanced or metastatic disease, which leads to a poor prognosis. In this study, we aimed to evaluate the diagnostic value of urinary CRP (uCRP) alone and in combination with our previously established urine biomarker panel (REG1B, LYVE1 and TFF1) for early detection of PDAC. A total of 534 urine samples from multiple centres were analysed: 93 from healthy individuals, 265 from patients with benign hepatobiliary diseases and 176 from PDAC patients. The uCRP and the urinary biomarker panel were assessed using commercial ELISA assays, while plasma CA19-9 and blood CRP (bCRP) were measured using Roche Cobas platform. Multiple logistic regression and nonparametric Kruskal–Wallis test were used for statistical analysis. An internal validation approach was applied, and the validated AUC estimators were reported to ensure accuracy. A significant difference was observed in the medians of uCRP between healthy and benign controls and PDAC sample groups (p < 0.001). uCRP levels were not dependent on gender and age, as well as cancer stage. When uCRP was combined with the urinary biomarker panel, it achieved AUCs of 0.878 (95% CI: 0.802-0.931), 0.798 (95% CI: 0.738-0.859) and 0.813 (95% CI: 0.758-0.869) in healthy vs PDAC, benign vs PDAC and healthy and benign vs PDAC sample groups, respectively. However, adding plasma CA19-9 to the urinary biomarker panel yielded a better performance, with AUCs of 0.978 (95% CI: 0.959-0.996), 0.911 (95% CI: 0.873-0.949) and 0.919 (95% CI: 0.883-0.955) in the healthy vs PDAC, benign vs PDAC and healthy and benign vs PDAC comparisons, respectively. In conclusion, we show that measuring CRP in urine is a feasible analytical method, and that uCRP could potentially be a promising biomarker in various diseases including other cancer types.
{"title":"Evaluation of urinary C-reactive protein as an early detection biomarker for pancreatic ductal adenocarcinoma","authors":"Nurshad Ali, Silvana Debernardi, Evelyn Kurotova, Jian Tajbakhsh, Nirdesh K. Gupta, Stephen J. Pandol, Patrick Wilson, Stephen P. Pereira, Bill Greenhalf, Oleg Blyuss, Tatjana Crnogorac-Jurcevic","doi":"10.3389/fonc.2024.1450326","DOIUrl":"https://doi.org/10.3389/fonc.2024.1450326","url":null,"abstract":"Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related death worldwide. Up to now, no specific screening or diagnostic tests are available for early PDAC detection. As a result, most patients are diagnosed with advanced or metastatic disease, which leads to a poor prognosis. In this study, we aimed to evaluate the diagnostic value of urinary CRP (uCRP) alone and in combination with our previously established urine biomarker panel (REG1B, LYVE1 and TFF1) for early detection of PDAC. A total of 534 urine samples from multiple centres were analysed: 93 from healthy individuals, 265 from patients with benign hepatobiliary diseases and 176 from PDAC patients. The uCRP and the urinary biomarker panel were assessed using commercial ELISA assays, while plasma CA19-9 and blood CRP (bCRP) were measured using Roche Cobas platform. Multiple logistic regression and nonparametric Kruskal–Wallis test were used for statistical analysis. An internal validation approach was applied, and the validated AUC estimators were reported to ensure accuracy. A significant difference was observed in the medians of uCRP between healthy and benign controls and PDAC sample groups (p &lt; 0.001). uCRP levels were not dependent on gender and age, as well as cancer stage. When uCRP was combined with the urinary biomarker panel, it achieved AUCs of 0.878 (95% CI: 0.802-0.931), 0.798 (95% CI: 0.738-0.859) and 0.813 (95% CI: 0.758-0.869) in healthy vs PDAC, benign vs PDAC and healthy and benign vs PDAC sample groups, respectively. However, adding plasma CA19-9 to the urinary biomarker panel yielded a better performance, with AUCs of 0.978 (95% CI: 0.959-0.996), 0.911 (95% CI: 0.873-0.949) and 0.919 (95% CI: 0.883-0.955) in the healthy vs PDAC, benign vs PDAC and healthy and benign vs PDAC comparisons, respectively. In conclusion, we show that measuring CRP in urine is a feasible analytical method, and that uCRP could potentially be a promising biomarker in various diseases including other cancer types.","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IntroductionAcquired vulvar lymphangioma (AVL), a rare disease caused by the dilation of superficial lymphatic vessels secondary to deep lymphatic vessel injury, is characterized by a wide range of morphological diversity and massive exudate. This morphological heterogeneity has often led to misdiagnosis or non-diagnosis. The management of AVL presents a therapeutic challenge due to the absence of a standardized treatment protocol.Case presentationA 53-year-old female patient, previously received surgical treatments for stage IIb cervical squamous cell carcinoma, presented with vulvar enlargement and copious amount of yellow exudate seven years post-treatment. Clinically, the patient exhibited chronic vulvar swelling, with easily-exudated nodules. The vulvar biopsy revealed lymphatic vessel dilation with lymphocyte infiltration, consistent with AVL. Due to the extensive lesions and severe exudate, staged excisions of bilateral vulvar lesions were performed at one-month intervals. Follow-up examinations of this patient for one-year post-surgery showed no evidence of recurrence.ConclusionIn this instance, AVL manifest secondary to cervical cancer surgery, as a result of damage to the deep lymphatic vessels of the vulva, with characteristic symptoms of copious amounts of exudate and vulvar lesions with diverse morphologies, which provides a cautionary note for physicians. Besides, the staged resection strategy in this case may offer insights into surgical treatment protocol for extensive AVL.
{"title":"Case report: Staged tension-reducing excision of giant acquired vulvar lymphangioma secondary to cervical cancer surgery","authors":"Ling-Juan Hu, Hao-Ming Fang, Huan-Mei Lin, Xu Kang, Ying Lin, Jing Xiao","doi":"10.3389/fonc.2024.1418829","DOIUrl":"https://doi.org/10.3389/fonc.2024.1418829","url":null,"abstract":"IntroductionAcquired vulvar lymphangioma (AVL), a rare disease caused by the dilation of superficial lymphatic vessels secondary to deep lymphatic vessel injury, is characterized by a wide range of morphological diversity and massive exudate. This morphological heterogeneity has often led to misdiagnosis or non-diagnosis. The management of AVL presents a therapeutic challenge due to the absence of a standardized treatment protocol.Case presentationA 53-year-old female patient, previously received surgical treatments for stage IIb cervical squamous cell carcinoma, presented with vulvar enlargement and copious amount of yellow exudate seven years post-treatment. Clinically, the patient exhibited chronic vulvar swelling, with easily-exudated nodules. The vulvar biopsy revealed lymphatic vessel dilation with lymphocyte infiltration, consistent with AVL. Due to the extensive lesions and severe exudate, staged excisions of bilateral vulvar lesions were performed at one-month intervals. Follow-up examinations of this patient for one-year post-surgery showed no evidence of recurrence.ConclusionIn this instance, AVL manifest secondary to cervical cancer surgery, as a result of damage to the deep lymphatic vessels of the vulva, with characteristic symptoms of copious amounts of exudate and vulvar lesions with diverse morphologies, which provides a cautionary note for physicians. Besides, the staged resection strategy in this case may offer insights into surgical treatment protocol for extensive AVL.","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The manifestation of a giant ovarian yolk sac tumor during late pregnancy is relatively rare. A yolk sac tumor is a highly malignant germ cell tumor that originates from primitive germ cells. It is characterized by yolk sac differentiation in vitro. The frequency of prenatal examinations should be appropriately increased for ovarian tumors discovered during pregnancy. Furthermore, regular follow-up ultrasound should be performed, and tumor markers should be dynamically detected. If needed, imaging examinations such as computed tomography and magnetic resonance imaging should be combined to comprehensively investigate disease progression. If the tumor diameter and tumor marker levels rapidly increase during pregnancy, the possibility of malignancy increases. Therefore, exploratory laparotomy should be immediately performed to further improve subsequent treatment modalities, early diagnosis, early treatment, and prognosis. Herein, we report the case of a 28-year-old pregnant woman whose pregnancy was terminated at 29 weeks and 5 days. She complained of lower abdominal pain for 2 days. A pelvic mass was detected for 1 week, accompanied by increased levels of tumor markers such as serum alpha-fetoprotein, cancer antigen 125, carbohydrate antigen 724, and human epididymis protein 4. Imaging revealed the presence of a pelvic mass. At 32 weeks and 3 days of pregnancy, a cesarean section was performed, with a transverse incision in the lower uterine segment. Furthermore, pelvic adhesiolysis, omentectomy, right adnexectomy, right pelvic lymph node dissection, and pelvic metastasis peritonectomy were performed. The postoperative pathological diagnosis was yolk sac tumors of the ovary (stage IIB). Postoperatively, a five-cycle chemotherapy regimen comprising bleomycin, etoposide, and cisplatin was administered. During postoperative follow-up, the patient’s general condition was noted to be good, with the newborn and pregnant women ultimately achieving good outcomes. We reviewed the relevant literature to increase clinical doctors’ understanding of ovarian malignancy during pregnancy, guide treatment selection, and facilitate early intervention for associated diseases.
{"title":"Giant ovarian yolk sac tumor during late pregnancy: a case report and literature review","authors":"Qin Wang, Jianxin Zuo, Chong Liu, Huansheng Zhou, Wenjie Wang, Yankui Wang","doi":"10.3389/fonc.2024.1437728","DOIUrl":"https://doi.org/10.3389/fonc.2024.1437728","url":null,"abstract":"The manifestation of a giant ovarian yolk sac tumor during late pregnancy is relatively rare. A yolk sac tumor is a highly malignant germ cell tumor that originates from primitive germ cells. It is characterized by yolk sac differentiation <jats:italic>in vitro</jats:italic>. The frequency of prenatal examinations should be appropriately increased for ovarian tumors discovered during pregnancy. Furthermore, regular follow-up ultrasound should be performed, and tumor markers should be dynamically detected. If needed, imaging examinations such as computed tomography and magnetic resonance imaging should be combined to comprehensively investigate disease progression. If the tumor diameter and tumor marker levels rapidly increase during pregnancy, the possibility of malignancy increases. Therefore, exploratory laparotomy should be immediately performed to further improve subsequent treatment modalities, early diagnosis, early treatment, and prognosis. Herein, we report the case of a 28-year-old pregnant woman whose pregnancy was terminated at 29 weeks and 5 days. She complained of lower abdominal pain for 2 days. A pelvic mass was detected for 1 week, accompanied by increased levels of tumor markers such as serum alpha-fetoprotein, cancer antigen 125, carbohydrate antigen 724, and human epididymis protein 4. Imaging revealed the presence of a pelvic mass. At 32 weeks and 3 days of pregnancy, a cesarean section was performed, with a transverse incision in the lower uterine segment. Furthermore, pelvic adhesiolysis, omentectomy, right adnexectomy, right pelvic lymph node dissection, and pelvic metastasis peritonectomy were performed. The postoperative pathological diagnosis was yolk sac tumors of the ovary (stage IIB). Postoperatively, a five-cycle chemotherapy regimen comprising bleomycin, etoposide, and cisplatin was administered. During postoperative follow-up, the patient’s general condition was noted to be good, with the newborn and pregnant women ultimately achieving good outcomes. We reviewed the relevant literature to increase clinical doctors’ understanding of ovarian malignancy during pregnancy, guide treatment selection, and facilitate early intervention for associated diseases.","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-06DOI: 10.3389/fonc.2024.1442127
Yaochen Lou, Feng Jiang, Yan Du, Jun Guan
ObjectiveTo establish a nomogram based on presurgical predictors of concurrent endometrial cancer (EC) for patients diagnosed with endometrial atypical hyperplasia before definitive surgery (preoperative-EAH) to improve the risk stratification and clinical application.MethodsPreoperative-EAH patients who underwent hysterectomy in a tertiary hospital from January 2020 to December 2022 were retrospectively analyzed. Independent predictors from the multivariate logistic regression model were used to establish a nomogram, and bootstrap resampling was used for internal validation.ResultsOf 370 preoperative-EAH patients, 23.4% were diagnosed with EC after definitive surgery (final-EC). Multivariate analyses found three independent predictors of final EC: human epididymis protein 4 (HE4) ≥43.50 pmol/L [odds ratio (OR) = 3.70; 95% confidence intervals (CI) = 2.06–6.67], body mass index (BMI) ≥ 28 kg/m2 (OR = 2.05; 95% CI = 1.14–3.69), and postmenopausal status, particularly at postmenopausal time ≥5 years (OR = 5.84, 95% CI = 2.51–13.55), which were used to establish a nomogram model. The bootstrap-corrected C-index of the nomogram was 0.733 (95% CI = 0.68–0.79), which was significantly higher than that of each individual factor. The calibration curve and decision curve showed good consistency and clinical net benefit of the model. At the maximum Youden index, 49.4% (43/87) of women in the high-risk group defined by nomogram had concurrent EC, versus 16.6% in the low-risk group (P< 0.001).ConclusionThe nomogram based on HE4, menopausal status, and BMI was found with an improved predictive value to stratify preoperative-EAH patients at high risk of concurrent EC for better clinical management.
{"title":"Nomogram using human epididymis protein 4 predicted concurrent endometrial cancer from endometrial atypical hyperplasia before surgery","authors":"Yaochen Lou, Feng Jiang, Yan Du, Jun Guan","doi":"10.3389/fonc.2024.1442127","DOIUrl":"https://doi.org/10.3389/fonc.2024.1442127","url":null,"abstract":"ObjectiveTo establish a nomogram based on presurgical predictors of concurrent endometrial cancer (EC) for patients diagnosed with endometrial atypical hyperplasia before definitive surgery (preoperative-EAH) to improve the risk stratification and clinical application.MethodsPreoperative-EAH patients who underwent hysterectomy in a tertiary hospital from January 2020 to December 2022 were retrospectively analyzed. Independent predictors from the multivariate logistic regression model were used to establish a nomogram, and bootstrap resampling was used for internal validation.ResultsOf 370 preoperative-EAH patients, 23.4% were diagnosed with EC after definitive surgery (final-EC). Multivariate analyses found three independent predictors of final EC: human epididymis protein 4 (HE4) ≥43.50 pmol/L [odds ratio (OR) = 3.70; 95% confidence intervals (CI) = 2.06–6.67], body mass index (BMI) ≥ 28 kg/m<jats:sup>2</jats:sup> (OR = 2.05; 95% CI = 1.14–3.69), and postmenopausal status, particularly at postmenopausal time ≥5 years (OR = 5.84, 95% CI = 2.51–13.55), which were used to establish a nomogram model. The bootstrap-corrected C-index of the nomogram was 0.733 (95% CI = 0.68–0.79), which was significantly higher than that of each individual factor. The calibration curve and decision curve showed good consistency and clinical net benefit of the model. At the maximum Youden index, 49.4% (43/87) of women in the high-risk group defined by nomogram had concurrent EC, versus 16.6% in the low-risk group (<jats:italic>P</jats:italic>&lt; 0.001).ConclusionThe nomogram based on HE4, menopausal status, and BMI was found with an improved predictive value to stratify preoperative-EAH patients at high risk of concurrent EC for better clinical management.","PeriodicalId":12482,"journal":{"name":"Frontiers in Oncology","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142224662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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