{"title":"Recent Breakthroughs in Exosome-Based Drug Delivery: A Comprehensive Review for Cancer Therapy.","authors":"Dhwani Shah, Shweta Gandhi, Shreeraj Shah, Kaushika Patel","doi":"10.1089/cbr.2025.0050","DOIUrl":"https://doi.org/10.1089/cbr.2025.0050","url":null,"abstract":"<p><p>Recently, exosomes, or \"natural nanoparticles,\" have been considered as potential drug delivery methods. Due to exosome carriers' natural properties, exosome-mediated drug delivery systems (DDSs) are efficient cancer treatments. Exosomes, small membrane vesicles from many cell types, can transfer phytoconstituents, proteins, nucleic acids, and small molecule medicines across biological boundaries. Recent DDS advances have improved this potential using plant-derived exosomes (PDEs), which are biocompatible and low toxic. PDEs have anticancer effects, especially in the context of conventional treatment resistance, untargeted toxicity, and response variability. This review fills a gap by discussing the latest findings and offering new perspectives on exosome drug delivery in cancer. The study summarizes isolation and loading approaches such as ultracentrifugation and immunological isolation and the characterization parameters for the formulation of exosomes. The exosome-based DDSs are discussed in depth, along with the emphasis on PDEs. The article highlights emerging trends and challenges, including molecular targets and ongoing clinical trials, during the past decade that are critically relevant to the current scenario. Nanotechnology and personalized medicine could improve and lower the cost of exosome-mediated cancer treatment. While the preclinical data have been encouraging, clinical applications of exosome-based therapies are continuing to evolve in its early stages, and some of the problems include scalability, purification, and regulatory compliance.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144287163","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}
Lei Dou, Jianhui Jiang, Hongbing Yao, Bo Zhang, Xueyao Wang
{"title":"Exploring <i>SLC25A42</i> as a Radiogenomic Marker from the Perioperative Stage to Chemotherapy in Hepatitis-Related Hepatocellular Carcinoma.","authors":"Lei Dou, Jianhui Jiang, Hongbing Yao, Bo Zhang, Xueyao Wang","doi":"10.1089/cbr.2025.0094","DOIUrl":"https://doi.org/10.1089/cbr.2025.0094","url":null,"abstract":"<p><p><b><i>Background:</i></b> The molecular mechanisms driving hepatocellular carcinoma (HCC) and predict the chemotherapy sensitive remain unclear; therefore, identification of these key biomarkers is essential for early diagnosis and treatment of HCC. <b><i>Method:</i></b> We collected and processed Computed Tomography (CT) and clinical data from 116 patients with autoimmune hepatitis (AIH) and HCC who came to our hospital's Liver Cancer Center. We then identified and extracted important characteristic features of significant patient images and correlated them with mitochondria-related genes using machine learning techniques such as multihead attention networks, lasso regression, principal component analysis (PCA), and support vector machines (SVM). These genes were integrated into radiomics signature models to explore their role in disease progression. We further correlated these results with clinical variables to screen for driver genes and evaluate the predict ability of chemotherapy sensitive of key genes in liver cancer (LC) patients. Finally, qPCR was used to validate the expression of this gene in patient samples. <b><i>Results:</i></b> Our study utilized attention networks to identify disease regions in medical images with 97% accuracy and an AUC of 94%. We extracted 942 imaging features, identifying five key features through lasso regression that accurately differentiate AIH from HCC. Transcriptome analysis revealed 132 upregulated and 101 downregulated genes in AIH, with 45 significant genes identified by XGBOOST. In HCC analysis, PCA and random forest highlighted 11 key features. Among mitochondrial genes, <i>SLC25A42</i> correlated positively with normal tissue imaging features but negatively with cancerous tissues and was identified as a driver gene. Low expression of <i>SLC25A42</i> was associated with chemotherapy sensitive in HCC patients. <b><i>Conclusions:</i></b> In conclusion, machine learning modeling combined with genomic profiling provides a promising approach to identify the driver gene <i>SLC25A42</i> in LC, which may help improve diagnostic accuracy and chemotherapy sensitivity for this disease.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144200902","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}
{"title":"Skin Cancer Detection Using Deep Learning Approaches.","authors":"Shafiul Haque, Faraz Ahmad, Vineeta Singh, Darin Mansor Mathkor, Ashjan Babegi","doi":"10.1089/cbr.2024.0161","DOIUrl":"10.1089/cbr.2024.0161","url":null,"abstract":"<p><p><i><b>Aim:</b></i> This review examined multiple deep learning (DL) methods, including artificial neural networks (ANNs), convolutional neural networks (CNNs), k-nearest neighbors (KNNs), as well as generative adversarial networks (GANs), relying on their abilities to differentially extract key features for the identification and classification of skin lesions. <i><b>Background:</b></i> Skin cancer is among the most prevalent cancer types in humans and is associated with tremendous socioeconomic and psychological burdens for patients and caregivers alike. Incidences of skin cancers have progressively increased during the last decades. Early diagnoses of skin cancers may aid in the implementation of more effective treatment and therapeutic regimens. Indeed, several recent studies have focused on early detection strategies for skin cancer. Among the lesion features that can aid the recognition and characterization of skin cancers are symmetry, color, size, and shape. <i><b>Results:</b></i> Our assessment indicates that CNNs delivered maximum accuracy in visual lesion recognition, yet GANs have surfaced as a strong tool for training augmentation through simulated image creation. However, there were significant limitations associated with existing datasets, such as provision of insufficient skin tone variability, demanding computational needs, and unequal lesion representations, which may hamper efficiency, inclusivity, and generalizability of DL models. Researchers must combine diverse high-resolution datasets within a structural framework to develop efficient computational models with unsupervised learning methods to enhance noninvasive and precise skin cancer detection. <i><b>Conclusion:</b></i> The breakthroughs in image-based computational skin cancer detection may be crucial in reducing the requirement of invasive diagnostic tests and expanding the scope of skin cancer screening toward broad demographics, thereby aiding early cancer detection in a time- and cost-efficient manner.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":"301-312"},"PeriodicalIF":2.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143733344","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}
Ningyu Wang, Xiangping Mei, Yang Cao, Lingfang Wang, Haoting Xie, Jingru Jia, Yong Xiao, Jun Han, Ai Huang, Hong Ma
{"title":"Nab-Paclitaxel Promotes Radiosensitization by Inducing DNA Damage and Inhibiting Macrophage M2 Polarization in Cholangiocarcinoma.","authors":"Ningyu Wang, Xiangping Mei, Yang Cao, Lingfang Wang, Haoting Xie, Jingru Jia, Yong Xiao, Jun Han, Ai Huang, Hong Ma","doi":"10.1089/cbr.2024.0246","DOIUrl":"10.1089/cbr.2024.0246","url":null,"abstract":"<p><p><b><i>Background:</i></b> Nab-paclitaxel effectively inhibits tumor proliferation and modulates macrophage polarization to improve the tumor microenvironment. However, its potential to achieve radiosensitization in cholangiocarcinoma remains to be elucidated. <b><i>Materials and Methods:</i></b> The proliferation inhibition and radiosensitizing effects of nab-paclitaxel were assessed using cell counting kit-8 and colony formation assays in NOZ and TFK1 cell lines. Cell apoptosis, cell cycle progression, DNA damage, and macrophage polarization status were analyzed via flow cytometry immunofluorescence, enzyme-linked immunosorbent assay, and qRT-PCR. A tumor-bearing mouse model was established to validate radiosensitization <i>in vivo</i>. Potentially related genes and proteins involved in nab-paclitaxel-induced radiosensitization were identified through RNA transcriptome sequencing and Western blotting. <b><i>Results:</i></b> Nab-paclitaxel exhibited significant radiosensitizing effects on cholangiocarcinoma cells. Combined with radiotherapy, nab-paclitaxel increased DNA damage, promoted apoptosis, and effectively inhibited M2 polarization of macrophages <i>in vivo</i> and <i>in vitro</i>. The radiosensitizing effect is involved in the activation of the AMP-dependent protein kinase (AMPK) signaling pathway. Nab-paclitaxel significantly upregulated phosphorylated AMPKα, apoptotic proteins as zinc finger matrin-type 3, and nuclear factor kappa-B levels following radiation exposure. <b><i>Conclusions:</i></b> Our study confirmed the radiosensitizing effect of nab-paclitaxel on cholangiocarcinoma cells through a dual effect of antitumor proliferation and inhibition of M2 macrophage polarization, and the underlying mechanism involved activation of the AMPK signaling pathway.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":"352-363"},"PeriodicalIF":2.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143506210","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}
{"title":"An LNM-Associated Gene Signature for Prognostic Prediction and Immune Profiling in Head and Neck Squamous Cell Carcinoma.","authors":"Zhenzhen Wang, Zhenhua Wu, Lixin Cheng, Qi Huang, Jian Zhang, Yuan Ren, Juntao Huang, Yi Shen","doi":"10.1089/cbr.2024.0147","DOIUrl":"10.1089/cbr.2024.0147","url":null,"abstract":"<p><p>Lymph node metastasis (LNM) plays a critical role in the prognosis of head and neck squamous cell carcinoma (HNSCC). To enhance prognostic predictions and investigate the molecular interplay between LNM and HNSCC, we developed an LNM-associated gene signature. Data was sourced from The Cancer Genome Atlas (TCGA), encompassing RNA-sequencing and clinical profiles. We stratified patients based on LNM status and identified differentially expressed genes (DEGs) between lymph node-negative (N0) and lymph node-positive (N1-3) groups. A prognostic model was then constructed while employing Least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses. Patients were randomly allocated into training (70%) and internal validation (30%) cohorts, with an additional external dataset used for validation. The predictive model's performance was assessed through receiver operating characteristic curves and survival analyses. We identified 79 LNM-related prognostic DEGs that formed the basis of our LNM-related risk score (LNMRS). This score stratified patients into low- and high-risk categories, with those having lower LNMRS exhibiting improved survival outcomes, increased immune cell infiltration, and enhanced responses to immunotherapy (PD-1/CTLA4 inhibitors) and chemotherapy. In contrast, patients with high LNMRS showed poorer prognosis and reduced immune responsiveness. Our LNM-related model provides insights into the molecular mechanisms linking LNM and HNSCC and offers a promising tool for personalized treatment strategies. This approach underscores the potential of integrating LNM status with gene expression profiles to refine prognosis and optimize therapeutic interventions in HNSCC.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":"339-351"},"PeriodicalIF":2.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143607277","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}
Gündüzalp Buğrahan Babacan, Filiz Özülker, Oğuzhan Şahin, Osman Güven, Osman Kanatsız, Göksel Alçın, Tamer Özülker
{"title":"Is There Novel <sup>18</sup>F-FDG Biodistribution in the Digital PET/CT Era? A Real-World Data Analysis.","authors":"Gündüzalp Buğrahan Babacan, Filiz Özülker, Oğuzhan Şahin, Osman Güven, Osman Kanatsız, Göksel Alçın, Tamer Özülker","doi":"10.1089/cbr.2024.0226","DOIUrl":"10.1089/cbr.2024.0226","url":null,"abstract":"<p><p><b><i>Background:</i></b> This retrospective multicenter study investigated the biodistribution of fluorodeoxyglucose (<sup>18</sup>F-FDG) in the positron emission tomography (PET)/computed tomography (CT) in digital PET/CT (dPET) compared to analog PET/CT (aPET), focusing differences in physiological uptake in reference and small structures across various scanner models. <b><i>Materials and Methods:</i></b> One hundred thirty patients with similar preimaging conditions underwent both dPET and aPET imaging within 6 months. Visual evaluations and paired comparative analyses of semiquantitative parameters were performed for small and reference structures. <b><i>Results:</i></b> <sup>18</sup>F-FDG uptake was higher in both reference and small structures for dPET compared to three different aPET scanners. The Siemens mCT20-4R (mCT20) demonstrated comparable results to dPET. Notably, mCT20 had higher standardized uptake value (SUV<sub>max</sub>) for the conus medullaris (CM) (3.20 vs. 2.76). CM was most highly visible with dPET on visual evaluation by physicians. <b><i>Conclusions:</i></b> Digital PET/CT provides higher SUV values in both small and reference structures. This leads to improved visualization of <sup>18</sup>F-FDG physiological biodistribution. Given the growing adoption of dPET technology, these advancements should be carefully considered in image interpretation and clinical research.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":"313-322"},"PeriodicalIF":2.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143048842","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}
Yinghui Zhi, Wenshan Zhang, Zhenyu Wu, Yan Chen, Liang Feng, Jing He, Feng Wang, Huan Liu
{"title":"miR-223-3p Targets <i>KIF4A</i> and Promotes the Oxidative Stress-Mediated Apoptosis of Breast Cancer Cells.","authors":"Yinghui Zhi, Wenshan Zhang, Zhenyu Wu, Yan Chen, Liang Feng, Jing He, Feng Wang, Huan Liu","doi":"10.1089/cbr.2024.0102","DOIUrl":"10.1089/cbr.2024.0102","url":null,"abstract":"<p><p><b><i>Background:</i></b> The abnormal expression of kinase family member 4A (<i>KIF4A</i>) is linked to breast cancer progression, with numerous miRNAs exhibiting abnormal expression. Thus, there is an urgent need to investigate the mechanisms of action of miRNAs and their target genes for the diagnosis and treatment of breast cancer. <b><i>Materials and Methods:</i></b> A bioinformatics analysis was conducted to screen for <i>KIF4A</i>, a key gene involved in oxidative stress in breast cancer cells. Using CCK8, EdU, cell healing, and Transwell assays, the knockdown of <i>KIF4A</i> was found to effectively inhibit the proliferation, migration, and invasion of breast cancer cells. Dual-luciferase assay and Western blotting confirmed that miR-223-3p targets and regulates <i>KIF4A</i> expression. The impact of miR-223-3p and <i>KIF4A</i> on oxidative stress in breast cancer cells was assessed through reactive oxygen species (ROS), superoxide dismutase (SOD), and malondialdehyde (MDA) measurements. Flow cytometry was used to evaluate tumor cell apoptosis. <b><i>Results:</i></b> Our results suggest that <i>KIF4A</i> is a downstream target of miR-223-3p. miR-223-3p inhibits the proliferation and invasion of breast cancer cells by directly targeting and downregulating <i>KIF4A</i>. Importantly, we found that miR-223-3p and <i>KIF4A</i> play important roles in regulating oxidative stress and apoptosis in breast cancer cells. Specifically, miR-223-3p promoted apoptosis by inhibiting the expression of <i>KIF4A</i>, increasing the accumulation level of ROS and MDA, and inhibiting the activity of SOD while <i>KIF4A</i> was overexpressed.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":"323-338"},"PeriodicalIF":2.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143366846","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}
{"title":"Diagnostic Value of <sup>99m</sup>Tc-Ubiquicidin Scintigraphy in Differentiating Bacterial from Nonbacterial Pneumonia.","authors":"Sepideh Khoshbakht, Saba Zare, Mahdi Khatuni, Mohammadali Ghodsirad, Mohadeseh Bayat, Fateme Sadat Mirabootalebi, Elahe Pirayesh, Mahasti Amoui, Ghazal Norouzi","doi":"10.1089/cbr.2024.0202","DOIUrl":"10.1089/cbr.2024.0202","url":null,"abstract":"<p><p><b><i>Purpose:</i></b> Differentiating purely viral from bacterial etiologies continues to be a challenging yet key step in the management of community-acquired pneumonia (CAP), further highlighted since the COVID-19 pandemic. This study aims to evaluate the utility of <sup>99m</sup>Tc-ubiquicidin (UBI) in the differentiation of bacterial from nonbacterial pneumonia. <b><i>Methods:</i></b> A total of 30 patients with CAP were allocated into groups A, bacterial (<i>n</i> = 15), and B, viral pneumonia (<i>n</i> = 15). All patients underwent <sup>99m</sup>Tc-UBI scan with planar and single-photon emission computed tomography (SPECT) images of thorax acquired at 30 and 180 min postinjection. Target-to-background (T/B) ratios were calculated with values >1.4 interpreted as positive for bacterial infection. Correlation was made with computed tomography (CT) scan and polymerase chain reaction (PCR) results. <b><i>Results:</i></b> UBI scan was positive in 43.3% (<i>n</i> = 13) of patients, with sensitivity, specificity, and accuracy of 86.7%, 100%, and 93.3%, respectively, and close correlation with chest CT scan and PCR results (<i>p</i>-value = 0.000). Planar images were generally not helpful. Receiver operating characteristic curve analysis indicated similar diagnostic performance for 30-min and 3-h SPECT images by implementing T/B thresholds of 1.2 and 1.33, respectively. <b><i>Conclusions:</i></b> <sup>99m</sup>Tc-UBI SPECT is a promising modality for differentiating purely viral from bacterial or superimposed bacterial pneumonia and provides reliable evidence either to mandate or withhold administration of antibiotics in patients with CAP.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":"293-300"},"PeriodicalIF":2.4,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143558885","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}
{"title":"Causal Associations of 33 Health Examination Indicators and Colorectal Cancer in European and East Asian Populations: A Mendelian Randomization Analysis.","authors":"Qi Shi, Tingting Zhu, Mingzhou Chen, Yao Wang, Minguang Zhang, Xiaoling Yin, Fenggang Hou","doi":"10.1089/cbr.2025.0065","DOIUrl":"https://doi.org/10.1089/cbr.2025.0065","url":null,"abstract":"<p><p><b><i>Background:</i></b> Colorectal cancer (CRC) is a significant cause of cancer-related mortality worldwide. While many health examination indicators might be associated with CRC, their causal relationships remain unclear. The authors analyzed their causal relationship in European and East Asian populations. <b><i>Methods:</i></b> The authors collected the genome-wide association data for 33 clinical indicators and CRC in European and East Asian populations from the IEU OpenGWAS project and Riken's Japanese Genetic Association Database. These indicators include 13 hematological indicators, 7 liver function indicators, 2 kidney function indicators, 5 lipid metabolism indicators, 2 glucose metabolism indicators, 1 electrolyte indicator, and 3 comorbidity indicators. The authors performed univariate (UV) and multivariate (MV) Mendelian randomization (MR) analyses on the European and East Asian populations and followed a meta-analysis. <b><i>Results:</i></b> UVMR analysis identified 11 indicators (white blood cell count [WBC], mean corpuscular hemoglobin [MCH], mean corpuscular hemoglobin concentration, mean corpuscular volume [MCV], platelet count [Plt], C-reactive protein [CRP], total protein [TP], aspartate aminotransferase [AST], total cholesterol [TC], low-density lipoprotein cholesterol, and apolipoprotein B) with significant causal relationships (<i>p</i> < 0.05). Notably, AST, TC, glycated hemoglobin, and serum creatinine showed inverted causal relationships in different populations. After MV adjustment for TC and TP, MCH (odds ratio [OR]<sub>EU</sub> = 1.0012, 1.0000 to 1.0024; OR<sub>meta</sub> = 1.0012, 1.0001 to 1.0024), Plt (OR<sub>EU</sub> = 0.9986, 0.9974 to 0.9998; OR<sub>meta</sub> = 0.9986, 0.9974 to 0.9998), and CRP (OR<sub>EU</sub> = 0.9981, 0.9965 to 0.9998; OR<sub>meta</sub> = 0.9981, 0.9965 to 0.9998) were independent influencing indicators in European and Eurasian populations, whereas WBC (OR<sub>EAS</sub> = 0.8316, 0.7005 to 0.9871), MCH (OR<sub>EAS</sub> = 1.2430, 1.1132 to 1.3879), and MCV (OR<sub>EAS</sub> = 1.0012, 1.0001 to 1.0024) were independent influencing indicators in the East Asian population. <b><i>Conclusion:</i></b> The causal relationship between MCH, TP, and Plt and CRC has been discovered for the first time. Furthermore, TC and CRP were also independent influencing indicators. These findings offer beneficial referential value for the enhancement of preliminary screening protocols for CRC.</p>","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144152864","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}
{"title":"<i>Response to Letter:</i> \"Skin Cancer Detection Using Deep Learning Approaches\" by Haque et al.","authors":"Ilaria Proietti, Luca Filippi","doi":"10.1089/cbr.2025.0122","DOIUrl":"https://doi.org/10.1089/cbr.2025.0122","url":null,"abstract":"","PeriodicalId":55277,"journal":{"name":"Cancer Biotherapy and Radiopharmaceuticals","volume":" ","pages":""},"PeriodicalIF":2.4,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144034089","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}