Cancer Investigation最新文献

Chronic Inflammation and Cancer: Key Pathways and Targeted Therapies.

IF 1.8 4区医学

Cancer Investigation Pub Date : 2024-12-08 DOI: 10.1080/07357907.2024.2437614

Gauri Kapoor, Swati Prakash, Vishakha Jaiswal, Ashok K Singh

引用次数: 0

Prediction of Brain Cancer Occurrence and Risk Assessment of Brain Hemorrhage Using Hybrid Deep Learning Technique.

IF 1.8 4区医学

Cancer Investigation Pub Date : 2024-12-04 DOI: 10.1080/07357907.2024.2431829

Rajeshwar Prasad, Amit Kumar Saxena, Suman Laha

{"title":"Prediction of Brain Cancer Occurrence and Risk Assessment of Brain Hemorrhage Using Hybrid Deep Learning Technique.","authors":"Rajeshwar Prasad, Amit Kumar Saxena, Suman Laha","doi":"10.1080/07357907.2024.2431829","DOIUrl":"https://doi.org/10.1080/07357907.2024.2431829","url":null,"abstract":"The prediction of brain cancer occurrence and risk assessment of brain hemorrhage using a hybrid deep learning (DL) technique is a critical area of research in medical imaging analysis. One prominent challenge in this field is the accurate identification and classification of brain tumors and hemorrhages, which can significantly impact patient prognosis and treatment planning. The objectives of the study address the prediction of brain cancer occurrence and the assessment of risk levels associated with both brain cancers due to brain hemorrhage. A diverse dataset of brain MRI and CT scan images. Utilize Unsymmetrical Trimmed Median Filter with Optics Clustering for noise removal while preserving edges and details. The Chan-Vese segmentation process for refined segmentation. Brain cancer detection using Multi-Head Self-Attention Dilated Convolution Neural Network (MH-SA-DCNN) with Efficient Net Model. Brain cancer detection using MH-SA-DCNN with Efficient Net Model. This trains the algorithm to predict cancerous regions in brain images. Further, implement a Graph-Based Deep Neural Network Model (G-DNN) to capture spatial relationships and risk factors from brain images. Cox regression model to estimate cancer risk over time and fine-tune and optimize the model's parameters and features using the Osprey optimization algorithm (OPA).","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"1-23"},"PeriodicalIF":1.8,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142766467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Viral Hepatitis in Western Patients with Advanced Intrahepatic Cholangiocarcinoma: Retrospective Assessment of Prevalence, Prognostic and Predictive Significance. 西方晚期肝内胆管癌患者中的病毒性肝炎：对患病率、预后和预测意义的回顾性评估。

IF 1.8 4区医学

Cancer Investigation Pub Date : 2024-11-27 DOI: 10.1080/07357907.2024.2432013

Roberto Filippi, Giovanni Brandi, Andrea Casadei-Gardini, Francesco Leone, Nicola Silvestris, Maria Antonietta Satolli, Francesca Salani, Elisa Sperti, Stefania Eufemia Lutrino, Giuseppe Aprile, Daniele Santini, Mario Scartozzi, Luca Faloppi, Andrea Palloni, Marzia Deserti, Simona Tavolari, Margherita Rimini, Oronzo Brunetti, Rosella Spadi, Depetris Ilaria, Massimo Di Maio

{"title":"Viral Hepatitis in Western Patients with Advanced Intrahepatic Cholangiocarcinoma: Retrospective Assessment of Prevalence, Prognostic and Predictive Significance.","authors":"Roberto Filippi, Giovanni Brandi, Andrea Casadei-Gardini, Francesco Leone, Nicola Silvestris, Maria Antonietta Satolli, Francesca Salani, Elisa Sperti, Stefania Eufemia Lutrino, Giuseppe Aprile, Daniele Santini, Mario Scartozzi, Luca Faloppi, Andrea Palloni, Marzia Deserti, Simona Tavolari, Margherita Rimini, Oronzo Brunetti, Rosella Spadi, Depetris Ilaria, Massimo Di Maio","doi":"10.1080/07357907.2024.2432013","DOIUrl":"https://doi.org/10.1080/07357907.2024.2432013","url":null,"abstract":"Despite a biologically established causative role of viral hepatitis (VH), i.e. HBV and HCV infections, on intrahepatic cholangiocarcinoma (ICC), only few large Western cohorts exploring the association between VH and ICC development are available. The prognostic significance of VH in ICC is debated, and no data are available regarding a predictive role for standard first-line CT (CT1), consisting of gemcitabine +/- platinoids. VH-positivity definition is often clinically incomplete and inconsistent among studies. Five different VH conditions, based on laboratory and anamnestic data, were investigated in a multicentric retrospective cohort of advanced ICC cases. Depending on the specific VH condition considered, 139-194 of 472 ICC cases could be categorized according to the presence of the mentioned VH conditions. VH prevalence ranged from 9.3 to 25.3%. No VH condition showed an impact on survival, although a non-significant worse outcome was observed for some HBV-related conditions. HCV-related conditions were associated to lower pre-CT1 biomarkers of inflammation, markedly higher disease control, and numerically longer time-to-progression with CT1. No benefit on time-to-progression was demonstrated for the addition of platinoids to gemcitabine in VH-positive patients (HR 0.77, CI95% 0.41-1.45), at least in HBV-related cases. These findings are clinically relevant and deserve further investigation.","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"1-11"},"PeriodicalIF":1.8,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142726239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LDHB Mediates Histone Lactylation to Activate PD-L1 and Promote Ovarian Cancer Immune Escape. LDHB 介导组蛋白乳化，激活 PD-L1 并促进卵巢癌免疫逃逸。

IF 1.8 4区医学

Cancer Investigation Pub Date : 2024-11-25 DOI: 10.1080/07357907.2024.2430283

Xuemei Hu, Zhenqiang Huang, Lingyun Li

{"title":"LDHB Mediates Histone Lactylation to Activate PD-L1 and Promote Ovarian Cancer Immune Escape.","authors":"Xuemei Hu, Zhenqiang Huang, Lingyun Li","doi":"10.1080/07357907.2024.2430283","DOIUrl":"https://doi.org/10.1080/07357907.2024.2430283","url":null,"abstract":"Background: To investigate the effects of LDHB on lactylation of programmed cell death 1 ligand (PD-L1) and immune evasion of ovarian cancer.Methods: Ovarian cancer cells were transfected with LDHB siRNA and cultured with primed T cells. Cell proliferation and viability were measured by cell counting kit 8 (CCK-8) and colony formation assay. The production of immune factors was detected by enzyme-linked immunosorbent assay (ELISA). The histone lactylation and activity of PD-L1 promoter were measured by chromatin immunoprecipitation (ChIP)-qPCR assay and luciferase reporter gene assay, respectively.Results: Knockdown of LDHB notably inhibited the growth, glucose uptake, lactate production, and ATP production of ovarian cancer cells. Knockdown of LDHB enhanced the killing effects of T cells, led to increased production of immune activation factors IL-2, TNF-α, and IFN-γ, as well as elevated the levels of granzyme B and perforin. Mechanical study identified that LDHB regulated the H3K18 lactylation (H3K18la) modification on PD-L1 promoter region to promote its expression. Overexpression of PD-L1 abolished the immune activation effects that induced by siLDHB.Conclusion: The LDHB modulated lactate production and the histone lactylation on PD-L1 promoter, which ultimately regulated its expression and participated in the immune evasion of ovarian cancer cells.","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"1-10"},"PeriodicalIF":1.8,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142715479","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Transforming Skin Cancer Diagnosis: A Deep Learning Approach with the Ham10000 Dataset. 改变皮肤癌诊断：利用 Ham10000 数据集的深度学习方法。

IF 1.8 4区医学

Cancer Investigation Pub Date : 2024-11-01 Epub Date: 2024-11-10 DOI: 10.1080/07357907.2024.2422602

Priyeshkumar A T, Shyamala G, Vasanth T, Ponniyin Selvan V

{"title":"Transforming Skin Cancer Diagnosis: A Deep Learning Approach with the Ham10000 Dataset.","authors":"Priyeshkumar A T, Shyamala G, Vasanth T, Ponniyin Selvan V","doi":"10.1080/07357907.2024.2422602","DOIUrl":"10.1080/07357907.2024.2422602","url":null,"abstract":"Skin cancer (SC) is one of the three most common cancers worldwide. Melanoma has the deadliest potential to spread to other parts of the body among all SCs. For SC treatments to be effective, early detection is essential. The high degree of similarity between tumor and non-tumors makes SC diagnosis difficult even for experienced doctors. To address this issue, authors have developed a novel Deep Learning (DL) system capable of automatically classifying skin lesions into seven groups: actinic keratosis (AKIEC), melanoma (MEL), benign keratosis (BKL), melanocytic Nevi (NV), basal cell carcinoma (BCC), dermatofibroma (DF), and vascular (VASC) skin lesions. Authors introduced the Multi-Grained Enhanced Deep Cascaded Forest (Mg-EDCF) as a novel DL model. In this model, first, researchers utilized subsampled multigrained scanning (Mg-sc) to acquire micro features. Second, authors employed two types of Random Forest (RF) to create input features. Finally, the Enhanced Deep Cascaded Forest (EDCF) was utilized for classification. The HAM10000 dataset was used for implementing, training, and evaluating the proposed and Transfer Learning (TL) models such as ResNet, AlexNet, and VGG16. During the validation and training stages, the performance of the four networks was evaluated by comparing their accuracy and loss. The proposed method outperformed the competing models with an average accuracy score of 98.19%. Our proposed methodology was validated against existing state-of-the-art algorithms from recent publications, resulting in consistently greater accuracies than those of the classifiers.","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"801-814"},"PeriodicalIF":1.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142614264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) Spectroscopy Analysis of Saliva as a Diagnostic Specimen for Rapid Classification of Oral Squamous Cell Carcinoma Using Chemometrics Methods. 使用化学计量学方法对作为诊断样本的唾液进行衰减全反射-傅立叶变换红外光谱分析，以快速对口腔鳞状细胞癌进行分类。

IF 1.8 4区医学

Cancer Investigation Pub Date : 2024-11-01 Epub Date: 2024-10-01 DOI: 10.1080/07357907.2024.2403086

Mohammad Mahdi Khanmohammadi Khorrami, Nozhan Azimi, Maryam Koopaie, Mahsa Mohammadi, Soheila Manifar, Mohammadreza Khanmohammadi Khorrami

{"title":"Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) Spectroscopy Analysis of Saliva as a Diagnostic Specimen for Rapid Classification of Oral Squamous Cell Carcinoma Using Chemometrics Methods.","authors":"Mohammad Mahdi Khanmohammadi Khorrami, Nozhan Azimi, Maryam Koopaie, Mahsa Mohammadi, Soheila Manifar, Mohammadreza Khanmohammadi Khorrami","doi":"10.1080/07357907.2024.2403086","DOIUrl":"10.1080/07357907.2024.2403086","url":null,"abstract":"Background & aim: Recent advancements in analytical techniques have highlighted the potential of Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectroscopy as a quick, cost-effective, non-invasive, and efficient tool for cancer diagnosis. This study aims to evaluate the effectiveness of ATR-FTIR spectroscopy in combination with supervised machine learning classification models for diagnosing OSCC using saliva samples.Methods & materials: Eighty unstimulated whole saliva samples from OSCC patients and healthy controls were collected. The ATR-FTIR spectroscopy was performed and spectral data were used to classify healthy and OSCC groups. The data were analyzed using machine learning classification methods such as Partial Least Squares-Discriminant Analysis (PLS-DA) and Support Vector Machine Classification (SVM-C). The classification performance of the models was evaluated by computing sensitivity, specificity, precision, and accuracy.Results: The samples were classified into two classes based on their spectral data. The obtained results demonstrate a high level of accuracy in the prediction sets of the PLS-DA and SVM-C models, with accuracy values of 0.960 and 0.962, respectively. The OSCC group sensitivity values for both PLS-DA and SVM-C models was 1.00, respectively.Conclusion: The study indicates that ATR-FTIR spectroscopy, combined with chemometrics, is a potential method for the non-invasive diagnosis of OSCC using saliva samples. This method achieved high accuracy and the findings of this study suggest that ATR-FTIR spectroscopy could be further developed for clinical applications in OSCC diagnosis.","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"815-826"},"PeriodicalIF":1.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142361174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Construction and Validation of a Novel T/NK-Cell Prognostic Signature for Pancreatic Cancer Based on Single-Cell RNA Sequencing. 基于单细胞 RNA 测序的新型胰腺癌 T/NK 细胞预后特征的构建与验证

IF 1.8 4区医学

Cancer Investigation Pub Date : 2024-11-01 Epub Date: 2024-11-10 DOI: 10.1080/07357907.2024.2424328

Yu Wang, Cong Zhang, Jianlu Zhang, Haoran Huang, Junchao Guo

{"title":"Construction and Validation of a Novel T/NK-Cell Prognostic Signature for Pancreatic Cancer Based on Single-Cell RNA Sequencing.","authors":"Yu Wang, Cong Zhang, Jianlu Zhang, Haoran Huang, Junchao Guo","doi":"10.1080/07357907.2024.2424328","DOIUrl":"10.1080/07357907.2024.2424328","url":null,"abstract":"Background: Evidence with regards to the distinction between primary and metastatic tumors in pancreatic cancer and driving factors for metastases remains limited.Methods: Single-cell RNA sequencing (scRNA-seq) was conducted on metastatic pancreatic cancer. Bioinformatics analysis on relevant sequencing data was used to construct a risk model to predict patient prognosis. Furthermore, immune infiltration and metabolic differences were assessed. The biological function of key differential genes was evaluated.Results: Paired primary and metastatic tumor tissues from 3 pancreatic cancer patients were collected and conducted scRNA-seq. Subsequently, the T/NK cell subgroup was the most different cell type between primary tumors and liver metastases and was selected for further analysis. Eventually, 6 specifically expressed genes of T/NK cells (B2M, ZFP36L2, ANXA1, ARL4C, TSPYL2, FYN) were used constructing the prognostic model. The stability of this model was validated by an external cohort. Meanwhile, different immune infiltration abundances occurred between high and low risk groups stratified by the model. The high-risk group had a stronger metabolic capability.Conclusions: A novel prognostic T/NK-cell signature for pancreatic cancer was constructed based on scRNA-seq data and externally validated. The involved key genes may play a role in multiple metabolic pathways of metastasis and affect the tumor immune microenvironment.","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"876-892"},"PeriodicalIF":1.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142613738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification of Immune-Related Gene Pair Signature to Predict Prognosis of Diffuse Large B-Cell Lymphoma Based on Bioinformatics Analyses. 基于生物信息学分析鉴定用于预测弥漫大 B 细胞淋巴瘤预后的免疫相关基因对签名

IF 1.8 4区医学

Cancer Investigation Pub Date : 2024-11-01 Epub Date: 2024-09-23 DOI: 10.1080/07357907.2024.2405184

Zeinab Davoodi-Moghaddam, Farideh Jafari-Raddani, Davood Bashash

引用次数: 0

Once-a-Week Ablative Radiotherapy as Replacement of Prolonged Fractionation in Frail Patients: Feasibility and Toxicity Results. 用每周一次的烧蚀放疗替代对体弱患者的长期分次放疗：可行性和毒性结果

IF 1.8 4区医学

Cancer Investigation Pub Date : 2024-11-01 Epub Date: 2024-11-06 DOI: 10.1080/07357907.2024.2425729

Liliana Belgioia, Camilla Satragno, Gladys Blandino, Alessandra Fozza, Flavio Giannelli, Michela Marcenaro, Giulia Vidano, Federica Picichè, Francesco Lanfranchi, Alberto Tagliafico, Gianmario Sambuceti, Matteo Bauckneht, Giorgia Timon

{"title":"Once-a-Week Ablative Radiotherapy as Replacement of Prolonged Fractionation in Frail Patients: Feasibility and Toxicity Results.","authors":"Liliana Belgioia, Camilla Satragno, Gladys Blandino, Alessandra Fozza, Flavio Giannelli, Michela Marcenaro, Giulia Vidano, Federica Picichè, Francesco Lanfranchi, Alberto Tagliafico, Gianmario Sambuceti, Matteo Bauckneht, Giorgia Timon","doi":"10.1080/07357907.2024.2425729","DOIUrl":"10.1080/07357907.2024.2425729","url":null,"abstract":"Introduction: The aim of this work was to explore the use of an original once-weekly radiotherapy fractionation in elderly or frail patients with recurrence or metastasis from different solid malignancies.Material and methods: A retrospective analysis was conducted on 29 patients treated from 2011 to 2019 with a once-weekly radiotherapy schedule. Patients received a median dose of 27.5 Gy, with weekly fractions of 4-5 Gy over 7-10 weeks. The treatment aimed at both palliative and cytoreductive objectives. Primary endpoints were feasibility and compliance, secondary outcome was acute toxicity.Results: All patients completed the planned radiotherapy without interruptions. Acute toxicity was mild, with only one patient developing grade 3 toxicity (bowel perforation). Three months post-treatment, 74% of patients experienced symptom relief and tumor response. One-year local control rates were 26.7%, and treatment was generally well-tolerated.Conclusion: This once-weekly hypofractionated radiotherapy regimen demonstrated feasibility, good tolerance, and promising tumor response in frail and elderly patients. Although limited by a small sample size, the approach offers a practical alternative for patients unable to undergo conventional daily radiotherapy. Further studies on larger cohorts are required to validate these findings.","PeriodicalId":9463,"journal":{"name":"Cancer Investigation","volume":" ","pages":"893-898"},"PeriodicalIF":1.8,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142581668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Glucose Metabolism and Glucose Transporters in Head and Neck Squamous Cell Carcinoma. 头颈部鳞状细胞癌中的葡萄糖代谢和葡萄糖转运体

IF 1.8 4区医学

Cancer Investigation Pub Date : 2024-11-01 Epub Date: 2024-09-26 DOI: 10.1080/07357907.2024.2407424

Yanyan Ye, Zaizai Cao

引用次数: 0