Pub Date : 2025-12-01DOI: 10.1016/j.mcp.2025.102057
Xin Chen, Weiqing Chen
Background
Diffuse large B cell lymphoma (DLBCL) is a heterogeneous malignancy with an unidentified molecular etiology. This study aims to investigate the role of DEAD-box helicase 10 (DDX10), a novel carcinogenic gene, in DLBCL.
Methods
The expression of DDX10 in DLBCL was analyzed by the GEPIA2 bioinformatics tool. DDX10 and fibrillarin (FBL) expressions in DLBCL patients’ cancer tissues and cell lines were measured via quantitative real-time reverse transcription polymerase chain reaction. RNA immunoprecipitation assay was used to confirm FBL-DDX10 interaction. The effects of DDX10/FBL overexpression and knockdown on cell viability, invasion, and Wnt/β-catenin pathway proteins were evaluated in DLBCL cell lines.
Results
DDX10 and FBL exhibited elevated expression levels in patients with DLBCL, particularly in those with stage III or IV DLBCL. DDX10 can bind to FBL in DLBCL cells. Silencing of DDX10 or FBL suppressed viability, proliferation and invasion, and downregulated the expressions of β-catenin, cyclin D1, and c-Myc proteins in DLBCL cells. The regulatory impact of DDX10 or FBL silencing on DLBCL cells was counteracted by the overexpression of FBL or DDX10.
Conclusion
DDX10 contributes to the proliferation and invasion of DLBCL cells via positively regulating FBL, highlighting the DDX10–FBL axis as a potential therapeutic target. This work provides new insights into DLBCL pathogenesis and underscores the biomedical relevance of targeting DDX10–FBL.
{"title":"Reveal the regulatory role of DDX10 in diffuse large B-cell lymphoma: binding with FBL to promote cell proliferation and invasion","authors":"Xin Chen, Weiqing Chen","doi":"10.1016/j.mcp.2025.102057","DOIUrl":"10.1016/j.mcp.2025.102057","url":null,"abstract":"<div><h3>Background</h3><div>Diffuse large B cell lymphoma (DLBCL) is a heterogeneous malignancy with an unidentified molecular etiology. This study aims to investigate the role of DEAD-box helicase 10 (DDX10), a novel carcinogenic gene, in DLBCL.</div></div><div><h3>Methods</h3><div>The expression of DDX10 in DLBCL was analyzed by the GEPIA2 bioinformatics tool. DDX10 and fibrillarin (FBL) expressions in DLBCL patients’ cancer tissues and cell lines were measured via quantitative real-time reverse transcription polymerase chain reaction. RNA immunoprecipitation assay was used to confirm FBL-DDX10 interaction. The effects of DDX10/FBL overexpression and knockdown on cell viability, invasion, and Wnt/β-catenin pathway proteins were evaluated in DLBCL cell lines.</div></div><div><h3>Results</h3><div>DDX10 and FBL exhibited elevated expression levels in patients with DLBCL, particularly in those with stage III or IV DLBCL. DDX10 can bind to FBL in DLBCL cells. Silencing of DDX10 or FBL suppressed viability, proliferation and invasion, and downregulated the expressions of β-catenin, cyclin D1, and c-Myc proteins in DLBCL cells. The regulatory impact of DDX10 or FBL silencing on DLBCL cells was counteracted by the overexpression of FBL or DDX10.</div></div><div><h3>Conclusion</h3><div>DDX10 contributes to the proliferation and invasion of DLBCL cells via positively regulating FBL, highlighting the DDX10–FBL axis as a potential therapeutic target. This work provides new insights into DLBCL pathogenesis and underscores the biomedical relevance of targeting DDX10–FBL.</div></div>","PeriodicalId":49799,"journal":{"name":"Molecular and Cellular Probes","volume":"85 ","pages":"Article 102057"},"PeriodicalIF":3.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145665704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-17DOI: 10.1016/j.mcp.2025.102056
Qian Wei , Ze Li , Honglei Feng , Jingya Zhang , Lijuan Wei
Introduction
Pancreatic cancer (PC) remains one of the most lethal malignancies worldwide, creating a critical need for reliable prognostic biomarkers, particularly those reflecting tumor microenvironment dynamics.
Methods
We investigated the combined prognostic value of a composite inflammatory prognostic model for PC progression. A retrospective cohort analysis of 171 patients with PC was conducted using receiver operating characteristic (ROC) curve analysis, along with univariate and multivariate Cox regression analyses. Survival curves were plotted using the Kaplan-Meier method. A clinical prognostic nomogram was constructed based on independent prognostic factors.
Results
ROC curve analysis demonstrated that C-reactive protein-to-lymphocyte ratio (CLR) had the highest predictive accuracy for 3-year survival. Survival analysis revealed that TNM stage, CA19-9, CEA, neutrophil count, CRP level, the neutrophil-to-lymphocyte ratio (NLR), and CLR were significantly associated with overall survival. Multivariate Cox regression analysis confirmed that advanced lymphatic metastasis, advanced TNM stage, elevated CA19-9, elevated CEA, elevated neutrophil count, elevated NLR, and elevated CLR were independent prognostic factors. The prognostic nomogram incorporating these variables exhibited robust discriminative capacity and well-calibrated predictions of survival. Using the inflammatory prognostic model, patients in the high-risk group had a significantly shorter median overall survival than those in the low-risk group, with strong predictive accuracy for 1-year and 3-year survival. Validation in a subgroup of patients with pancreatic ductal adenocarcinoma further supported the clinical utility of the model, showing superior 3-year predictive performance and a pronounced survival disparity between the risk groups.
Conclusions
A combination of inflammatory and clinical markers can effectively predict the prognosis of pancreatic cancer. The constructed composite inflammatory prognostic model demonstrated high clinical practical value and provided a reliable tool for individualized prognostic risk assessment.
{"title":"Prognostic value of composite inflammatory prognostic model in pancreatic cancer","authors":"Qian Wei , Ze Li , Honglei Feng , Jingya Zhang , Lijuan Wei","doi":"10.1016/j.mcp.2025.102056","DOIUrl":"10.1016/j.mcp.2025.102056","url":null,"abstract":"<div><h3>Introduction</h3><div>Pancreatic cancer (PC) remains one of the most lethal malignancies worldwide, creating a critical need for reliable prognostic biomarkers, particularly those reflecting tumor microenvironment dynamics.</div></div><div><h3>Methods</h3><div>We investigated the combined prognostic value of a composite inflammatory prognostic model for PC progression. A retrospective cohort analysis of 171 patients with PC was conducted using receiver operating characteristic (ROC) curve analysis, along with univariate and multivariate Cox regression analyses. Survival curves were plotted using the Kaplan-Meier method. A clinical prognostic nomogram was constructed based on independent prognostic factors.</div></div><div><h3>Results</h3><div>ROC curve analysis demonstrated that C-reactive protein-to-lymphocyte ratio (CLR) had the highest predictive accuracy for 3-year survival. Survival analysis revealed that TNM stage, CA19-9, CEA, neutrophil count, CRP level, the neutrophil-to-lymphocyte ratio (NLR), and CLR were significantly associated with overall survival. Multivariate Cox regression analysis confirmed that advanced lymphatic metastasis, advanced TNM stage, elevated CA19-9, elevated CEA, elevated neutrophil count, elevated NLR, and elevated CLR were independent prognostic factors. The prognostic nomogram incorporating these variables exhibited robust discriminative capacity and well-calibrated predictions of survival. Using the inflammatory prognostic model, patients in the high-risk group had a significantly shorter median overall survival than those in the low-risk group, with strong predictive accuracy for 1-year and 3-year survival. Validation in a subgroup of patients with pancreatic ductal adenocarcinoma further supported the clinical utility of the model, showing superior 3-year predictive performance and a pronounced survival disparity between the risk groups.</div></div><div><h3>Conclusions</h3><div>A combination of inflammatory and clinical markers can effectively predict the prognosis of pancreatic cancer. The constructed composite inflammatory prognostic model demonstrated high clinical practical value and provided a reliable tool for individualized prognostic risk assessment.</div></div>","PeriodicalId":49799,"journal":{"name":"Molecular and Cellular Probes","volume":"84 ","pages":"Article 102056"},"PeriodicalIF":3.0,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145557565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-04DOI: 10.1016/j.mcp.2025.102055
Adrian Rombach , Maximilian Geissler , Liu Xiao , Lina-Elisabeth Qasem , Lena Stange , Vincent Prinz , Daniel Jussen , Somaya Landolsi , Konstantinos D. Kokkaliaris , Hind Medyouf , Lisa Sevenich , Pia Zeiner , Yvonne Reiss , Pinar Cakmak , Moritz Armbrust , Katharina J. Weber , Karl Heinz Plate , Stefan Offermanns , Thomas Broggini , Marcus Czabanka
Human tissue samples are a crucial resource for cancer research, offering key insights into physiological and pathological processes while enabling comprehensive characterization of molecular signatures across cancer subtypes. Recent advances in genetic analysis techniques lead to a substantiall expansion of specific molecular pathways knowledge. The application of these technologies to fresh tissue samples from patients undergoing surgical resection for metastatic disease represents a promising approach to gain a deeper understanding of the biology of brain metastasis. Brain metastases remain particularly challenging due to their poor prognosis and the complex mechanisms underlying central nervous system invasion. This study sought to identify preoperative factors influencing the research utility of fresh brain metastasis tissue samples. A pipeline was established to transfer fresh, surplus tissue from surgical resections to research laboratories with histological quality assessment. Of the fifty-five fresh specimens collected, thirty-eight (69 %) were classified as suitable for further research applications. Statistical analysis revealed that only two factors significantly affected sample quality. First, the extent of MRI-derived necrosis was significantly higher in unsuitable samples (mean 18.0 %) than in suitable samples (mean 8.3 %) (p = 0.0273). Second, prior treatment with target-specific therapeutics (TST) was associated with a lower proportion of suitable samples (47 %) compared to no prior TST (79 %) (p = 0.018). Logistic regression confirmed these variables as significant predictors, with MRI-derived necrosis (odds ratio 1.049) and target-specific therapy exposure (odds ratio 4.486) independently increasing the likelihood of obtaining suboptimal samples. Other parameters, including age, gender, metastasis volume, localization, primary cancer site, and other therapeutic interventions, showed no significant impact on sample quality. Based on these findings, the collection pipeline was modified to include evaluation by board-certified neuropathologists before samples are used for research purposes, improving the efficiency of translational research utilizing brain metastasis tissue.
{"title":"Impact of preoperative clinical patient parameters on surgically obtained brain metastasis samples for translational research","authors":"Adrian Rombach , Maximilian Geissler , Liu Xiao , Lina-Elisabeth Qasem , Lena Stange , Vincent Prinz , Daniel Jussen , Somaya Landolsi , Konstantinos D. Kokkaliaris , Hind Medyouf , Lisa Sevenich , Pia Zeiner , Yvonne Reiss , Pinar Cakmak , Moritz Armbrust , Katharina J. Weber , Karl Heinz Plate , Stefan Offermanns , Thomas Broggini , Marcus Czabanka","doi":"10.1016/j.mcp.2025.102055","DOIUrl":"10.1016/j.mcp.2025.102055","url":null,"abstract":"<div><div>Human tissue samples are a crucial resource for cancer research, offering key insights into physiological and pathological processes while enabling comprehensive characterization of molecular signatures across cancer subtypes. Recent advances in genetic analysis techniques lead to a substantiall expansion of specific molecular pathways knowledge. The application of these technologies to fresh tissue samples from patients undergoing surgical resection for metastatic disease represents a promising approach to gain a deeper understanding of the biology of brain metastasis. Brain metastases remain particularly challenging due to their poor prognosis and the complex mechanisms underlying central nervous system invasion. This study sought to identify preoperative factors influencing the research utility of fresh brain metastasis tissue samples. A pipeline was established to transfer fresh, surplus tissue from surgical resections to research laboratories with histological quality assessment. Of the fifty-five fresh specimens collected, thirty-eight (69 %) were classified as suitable for further research applications. Statistical analysis revealed that only two factors significantly affected sample quality. First, the extent of MRI-derived necrosis was significantly higher in unsuitable samples (mean 18.0 %) than in suitable samples (mean 8.3 %) (p = 0.0273). Second, prior treatment with target-specific therapeutics (TST) was associated with a lower proportion of suitable samples (47 %) compared to no prior TST (79 %) (p = 0.018). Logistic regression confirmed these variables as significant predictors, with MRI-derived necrosis (odds ratio 1.049) and target-specific therapy exposure (odds ratio 4.486) independently increasing the likelihood of obtaining suboptimal samples. Other parameters, including age, gender, metastasis volume, localization, primary cancer site, and other therapeutic interventions, showed no significant impact on sample quality. Based on these findings, the collection pipeline was modified to include evaluation by board-certified neuropathologists before samples are used for research purposes, improving the efficiency of translational research utilizing brain metastasis tissue.</div></div>","PeriodicalId":49799,"journal":{"name":"Molecular and Cellular Probes","volume":"84 ","pages":"Article 102055"},"PeriodicalIF":3.0,"publicationDate":"2025-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145460548","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-01DOI: 10.1016/j.mcp.2025.102054
Su Qin , Jing Zhang , Meifang Cao , Tao Jiang , Baohong Jiang
This study aims to explore the lymphangiogenesis (LG)-related diagnostic markers of abdominal aortic aneurysm (AAA) through bioinformatics, as well as the alteration of the regional lymphatic system during the progression of AAA and the influence of lymphatic drainage obstruction on AAA progression. 2957 differentially expressed genes (DEGs) were identified between the AAA patient group and the healthy donor group in Gene Expression Omnibus microarray datasets. Subsequently, the DEGs and the LG gene were intersected, and 93 genes were obtained. Weighted gene co-expression network analysis (WGCNA) was performed to obtain module genes. Module genes intersected with the above 93 genes, and 26 genes were obtained. Five hub genes (HSPA5, RAB10, RAB1A, RAF1, SMAD4) identified by machine learning may serve as diagnostic candidates for AAA patients through nomogram and ROC evaluation. Gene set enrichment analysis (GSEA) and immune infiltration analysis were performed further to understand the function of these candidate genes and explore the effect of immunity in AAA, respectively. By establishing an AAA animal model, it was found that the iliac lymph nodes around the abdominal aorta were significantly enlarged, and the number and lumen size of lymphatic vessels in the vessel wall were both significantly increased during the progression of AAA. Additionally, AAA was significantly promoted by ligating lymphatic vessels, which caused lymphatic drainage obstruction around the abdominal aorta. Our findings have the potential to enhance knowledge about the development and diagnosis of AAA.
本研究旨在通过生物信息学的方法探讨腹主动脉瘤(AAA)的淋巴管生成(LG)相关诊断指标,以及AAA进展过程中局部淋巴系统的改变及淋巴引流阻塞对AAA进展的影响。在基因表达集成芯片(Gene Expression Omnibus microarray)数据集中,鉴定出AAA患者组与健康供者组之间存在2957个差异表达基因。随后,将DEGs与LG基因进行交叉,得到93个基因。采用加权基因共表达网络分析(WGCNA)获得模块基因。模块基因与上述93个基因相交,得到26个基因。通过机器学习识别的5个中心基因(HSPA5、RAB10、RAB1A、RAF1、SMAD4)可通过nomogram和ROC评价作为AAA患者的候选诊断基因。进一步进行基因集富集分析(GSEA)和免疫浸润分析,分别了解这些候选基因的功能,探讨免疫在AAA中的作用。通过建立AAA动物模型发现,在AAA的进展过程中,腹主动脉周围的髂淋巴结明显增大,血管壁淋巴管数量和管腔大小均明显增加,结扎淋巴管可明显促进AAA,造成腹主动脉周围淋巴管引流阻塞。我们的发现有可能提高对AAA的发展和诊断的认识。
{"title":"Identification of lymphangiogenesis-related diagnostic model for predicting abdominal aortic aneurysm onset and progression and validation of lymphopoiesis in abdominal aortic aneurysm","authors":"Su Qin , Jing Zhang , Meifang Cao , Tao Jiang , Baohong Jiang","doi":"10.1016/j.mcp.2025.102054","DOIUrl":"10.1016/j.mcp.2025.102054","url":null,"abstract":"<div><div>This study aims to explore the lymphangiogenesis (LG)-related diagnostic markers of abdominal aortic aneurysm (AAA) through bioinformatics, as well as the alteration of the regional lymphatic system during the progression of AAA and the influence of lymphatic drainage obstruction on AAA progression. 2957 differentially expressed genes (DEGs) were identified between the AAA patient group and the healthy donor group in Gene Expression Omnibus microarray datasets. Subsequently, the DEGs and the LG gene were intersected, and 93 genes were obtained. Weighted gene co-expression network analysis (WGCNA) was performed to obtain module genes. Module genes intersected with the above 93 genes, and 26 genes were obtained. Five hub genes (HSPA5, RAB10, RAB1A, RAF1, SMAD4) identified by machine learning may serve as diagnostic candidates for AAA patients through nomogram and ROC evaluation. Gene set enrichment analysis (GSEA) and immune infiltration analysis were performed further to understand the function of these candidate genes and explore the effect of immunity in AAA, respectively. By establishing an AAA animal model, it was found that the iliac lymph nodes around the abdominal aorta were significantly enlarged, and the number and lumen size of lymphatic vessels in the vessel wall were both significantly increased during the progression of AAA. Additionally, AAA was significantly promoted by ligating lymphatic vessels, which caused lymphatic drainage obstruction around the abdominal aorta. Our findings have the potential to enhance knowledge about the development and diagnosis of AAA.</div></div>","PeriodicalId":49799,"journal":{"name":"Molecular and Cellular Probes","volume":"85 ","pages":"Article 102054"},"PeriodicalIF":3.0,"publicationDate":"2025-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145439965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-01DOI: 10.1016/j.mcp.2025.102053
Mohammad Javad Bazyari , Ali Ahmadizad Firouzjaei , Seyed Mahdi Ahmadi , Mohsen Khorashadizadeh , Seyed Hamid Aghaee-Bakhtiari
Metastasis is a major challenge in colorectal cancer (CRC) treatment. The incidence of regional and distant stages has increased during the past decade and the 5-year survival of metastatic CRC patients is 20 %. Although there is a necessity to develop systematic treatment, the cost and time of novel drug discovery hinder this progress. Drug repositioning simplifies this process by accelerating regulatory processes in drug discovery. Here we used a systems biology approach to find key player genes in the metastasis. First, we found differentially expressed genes in metastatic tissue compared to primary tumors. Then, we constructed and analyzed the protein-protein interaction (PPI) network to find hub genes and subjected them to query in the DrugBank database. We found plasminogen (PLG) is the hub gene in the constructed PPI network and tranexamic acid (TXA) is its known inhibitor with clinically approved antifibrinolytic activity. Pathway enrichment analysis showed that PLG is involved in matrix remodeling, Platelet activation, and cell energy production through insulin-growth factor uptake in colorectal cancer cells which are important processes during metastasis. We further explored the CPTAC-COAD proteomics data and found that the PLG level is significantly higher in stage IV compared to stage I. Interestingly, we found that PLG is correlated with mutation rate. We then investigated the effect of TXA on SW480 cells' mobility and migration by scratch assay and transwell migration assay. Both assays indicated that TXA can significantly inhibit the cells’ migratory potential.
{"title":"Exploiting network-based drug repositioning to target metastasis in colorectal cancer: In-Silico prediction and in-vitro evidence","authors":"Mohammad Javad Bazyari , Ali Ahmadizad Firouzjaei , Seyed Mahdi Ahmadi , Mohsen Khorashadizadeh , Seyed Hamid Aghaee-Bakhtiari","doi":"10.1016/j.mcp.2025.102053","DOIUrl":"10.1016/j.mcp.2025.102053","url":null,"abstract":"<div><div>Metastasis is a major challenge in colorectal cancer (CRC) treatment. The incidence of regional and distant stages has increased during the past decade and the 5-year survival of metastatic CRC patients is 20 %. Although there is a necessity to develop systematic treatment, the cost and time of novel drug discovery hinder this progress. Drug repositioning simplifies this process by accelerating regulatory processes in drug discovery. Here we used a systems biology approach to find key player genes in the metastasis. First, we found differentially expressed genes in metastatic tissue compared to primary tumors. Then, we constructed and analyzed the protein-protein interaction (PPI) network to find hub genes and subjected them to query in the DrugBank database. We found plasminogen (PLG) is the hub gene in the constructed PPI network and tranexamic acid (TXA) is its known inhibitor with clinically approved antifibrinolytic activity. Pathway enrichment analysis showed that PLG is involved in matrix remodeling, Platelet activation, and cell energy production through insulin-growth factor uptake in colorectal cancer cells which are important processes during metastasis. We further explored the CPTAC-COAD proteomics data and found that the PLG level is significantly higher in stage IV compared to stage I. Interestingly, we found that PLG is correlated with mutation rate. We then investigated the effect of TXA on SW480 cells' mobility and migration by scratch assay and transwell migration assay. Both assays indicated that TXA can significantly inhibit the cells’ migratory potential.</div></div>","PeriodicalId":49799,"journal":{"name":"Molecular and Cellular Probes","volume":"84 ","pages":"Article 102053"},"PeriodicalIF":3.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145226254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-26DOI: 10.1016/j.mcp.2025.102052
Bashdar Mahmud Hussen , Snur Rasool Abdullah , Hazha Jamal Hidayat , Mark C. Glassy , Arash Safarzadeh , Alireza Komaki , Majid Samsami , Mohammad Taheri
Drug resistance remains a significant challenge in cancer therapy, often resulting in treatment failure, tumor progression, and metastasis. The underlying resistance mechanisms—including genetic mutations, epigenetic alterations, and modifications in drug efflux pathways—are complex and not yet fully understood. This review explores the application of CRISPR-Cas gene editing technology in understanding and overcoming drug resistance in cancer. It focuses on how CRISPR can identify and target resistance-associated genes to restore drug sensitivity. CRISPR-based approaches enable precise genetic modifications that offer new insights into the molecular basis of drug resistance. The technology has shown promise in dissecting resistance mechanisms and developing targeted therapeutic strategies. Nevertheless, key limitations such as inefficient delivery systems, off-target effects, and limited specificity hinder clinical translation. Current efforts focus on improving guide RNA design, creating more effective delivery vectors, and integrating CRISPR with existing treatments. CRISPR-Cas technology holds significant potential to address drug resistance in cancer by enabling targeted genetic interventions. Continued advancements are required to enhance its safety, specificity, and delivery, paving the way for its integration into future clinical applications.
{"title":"CRISPR/Cas as a tool to overcome drug resistance in cancer: From challenge to opportunity","authors":"Bashdar Mahmud Hussen , Snur Rasool Abdullah , Hazha Jamal Hidayat , Mark C. Glassy , Arash Safarzadeh , Alireza Komaki , Majid Samsami , Mohammad Taheri","doi":"10.1016/j.mcp.2025.102052","DOIUrl":"10.1016/j.mcp.2025.102052","url":null,"abstract":"<div><div>Drug resistance remains a significant challenge in cancer therapy, often resulting in treatment failure, tumor progression, and metastasis. The underlying resistance mechanisms—including genetic mutations, epigenetic alterations, and modifications in drug efflux pathways—are complex and not yet fully understood. This review explores the application of CRISPR-Cas gene editing technology in understanding and overcoming drug resistance in cancer. It focuses on how CRISPR can identify and target resistance-associated genes to restore drug sensitivity. CRISPR-based approaches enable precise genetic modifications that offer new insights into the molecular basis of drug resistance. The technology has shown promise in dissecting resistance mechanisms and developing targeted therapeutic strategies. Nevertheless, key limitations such as inefficient delivery systems, off-target effects, and limited specificity hinder clinical translation. Current efforts focus on improving guide RNA design, creating more effective delivery vectors, and integrating CRISPR with existing treatments. CRISPR-Cas technology holds significant potential to address drug resistance in cancer by enabling targeted genetic interventions. Continued advancements are required to enhance its safety, specificity, and delivery, paving the way for its integration into future clinical applications.</div></div>","PeriodicalId":49799,"journal":{"name":"Molecular and Cellular Probes","volume":"84 ","pages":"Article 102052"},"PeriodicalIF":3.0,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145187370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-19DOI: 10.1016/j.mcp.2025.102051
Asma Vafadar , Negar Nayerain Jazi , Melika Eghtesadi , Sajad Ehtiati , Ahmad Movahedpour , Amir Savardashtaki
Ovarian cancer (OC) is one of the most aggressive gynecologic malignancies, largely due to its asymptomatic progression and frequent diagnosis at an advanced stage. Early detection is essential for improving patient survival rates. Exosomes, small extracellular vesicles secreted by cells, are actively involved in OC progression and have been recognized as potential biomarkers for early diagnosis. Over the past decade, advancements in exosome research have emphasized the need for detection methods that are not only sensitive and reliable but also practical for clinical use. However, conventional approaches often face challenges such as limited sensitivity and complex sample preparation. Biosensors have emerged as a promising alternative, offering benefits such as non-invasiveness and improved analytical performance. This review examines recent developments in electrochemical, optical, and electrical biosensors for detecting OC-related exosomes, discussing their sensitivity, specificity, and potential applications in clinical settings.
{"title":"Exosome biosensors for detection of ovarian cancer","authors":"Asma Vafadar , Negar Nayerain Jazi , Melika Eghtesadi , Sajad Ehtiati , Ahmad Movahedpour , Amir Savardashtaki","doi":"10.1016/j.mcp.2025.102051","DOIUrl":"10.1016/j.mcp.2025.102051","url":null,"abstract":"<div><div>Ovarian cancer (OC) is one of the most aggressive gynecologic malignancies, largely due to its asymptomatic progression and frequent diagnosis at an advanced stage. Early detection is essential for improving patient survival rates. Exosomes, small extracellular vesicles secreted by cells, are actively involved in OC progression and have been recognized as potential biomarkers for early diagnosis. Over the past decade, advancements in exosome research have emphasized the need for detection methods that are not only sensitive and reliable but also practical for clinical use. However, conventional approaches often face challenges such as limited sensitivity and complex sample preparation. Biosensors have emerged as a promising alternative, offering benefits such as non-invasiveness and improved analytical performance. This review examines recent developments in electrochemical, optical, and electrical biosensors for detecting OC-related exosomes, discussing their sensitivity, specificity, and potential applications in clinical settings.</div></div>","PeriodicalId":49799,"journal":{"name":"Molecular and Cellular Probes","volume":"84 ","pages":"Article 102051"},"PeriodicalIF":3.0,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145114922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-09-03DOI: 10.1016/j.mcp.2025.102049
Zeyu Li , Chunfeng Zhang , Kuo Ma , Guangye Han , Weihang Song , Minghao Yue , Shuaiqi Chen
Background
Interleukin-1 receptor-like 1 (IL1RL1, also known as ST2) plays a critical role in immune regulation. Pan-cancer analysis has revealed that IL1RL1 is closely associated with cellular immune functions; however, its role in clear cell renal cell carcinoma (ccRCC) and the tumor microenvironment (TME) remains poorly defined.
Methods
We analyzed IL1RL1 expression patterns using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) were employed to investigate the cellular localization and biological functions of IL1RL1 in ccRCC. In addition, IL1RL1 knockout experiments were conducted to explore its potential role in antigen presentation.
Results
Compared to adjacent normal tissues, IL1RL1 expression was significantly downregulated in renal cancer tissues. Higher IL1RL1 expression correlated with improved patient prognosis, suggesting its potential as an independent prognostic biomarker. IL1RL1 was predominantly expressed in mast cells, with higher levels observed in adjacent normal tissues than in tumor tissues, implying a regulatory role in tumor immunity. Subset analysis revealed that IL1RL1-high mast cells were enriched in immune-inflammatory functions, including leukocyte activation, chemokine production, and antigen presentation. Cell–cell communication analysis further demonstrated that IL1RL1+ mast cells may enhance CD8+ cytotoxic T cell activation via the MHC-I signaling pathway. Spatial transcriptomics and multiplex immunohistochemistry (mIHC) confirmed the spatial co-localization of IL1RL1+ mast cells and T cells within the TME. Furthermore, IL1RL1 knockout led to a reduction in HLA-A expression, providing functional evidence for its involvement in antigen presentation.
Conclusion
Our findings highlight the immune-regulatory role of IL1RL1+ mast cells in ccRCC. IL1RL1 may contribute to anti-tumor immunity through the modulation of antigen presentation and CD8+ T cell activation, offering new insights into its potential as a prognostic biomarker and therapeutic target in renal cancer.
{"title":"Spatial and functional characterization of IL1RL1+ mast cells reveals immune regulatory roles in renal cancer","authors":"Zeyu Li , Chunfeng Zhang , Kuo Ma , Guangye Han , Weihang Song , Minghao Yue , Shuaiqi Chen","doi":"10.1016/j.mcp.2025.102049","DOIUrl":"10.1016/j.mcp.2025.102049","url":null,"abstract":"<div><h3>Background</h3><div>Interleukin-1 receptor-like 1 (IL1RL1, also known as ST2) plays a critical role in immune regulation. Pan-cancer analysis has revealed that IL1RL1 is closely associated with cellular immune functions; however, its role in clear cell renal cell carcinoma (ccRCC) and the tumor microenvironment (TME) remains poorly defined.</div></div><div><h3>Methods</h3><div>We analyzed IL1RL1 expression patterns using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) were employed to investigate the cellular localization and biological functions of IL1RL1 in ccRCC. In addition, IL1RL1 knockout experiments were conducted to explore its potential role in antigen presentation.</div></div><div><h3>Results</h3><div>Compared to adjacent normal tissues, IL1RL1 expression was significantly downregulated in renal cancer tissues. Higher IL1RL1 expression correlated with improved patient prognosis, suggesting its potential as an independent prognostic biomarker. IL1RL1 was predominantly expressed in mast cells, with higher levels observed in adjacent normal tissues than in tumor tissues, implying a regulatory role in tumor immunity. Subset analysis revealed that IL1RL1-high mast cells were enriched in immune-inflammatory functions, including leukocyte activation, chemokine production, and antigen presentation. Cell–cell communication analysis further demonstrated that IL1RL1<sup>+</sup> mast cells may enhance CD8<sup>+</sup> cytotoxic T cell activation via the MHC-I signaling pathway. Spatial transcriptomics and multiplex immunohistochemistry (mIHC) confirmed the spatial co-localization of IL1RL1<sup>+</sup> mast cells and T cells within the TME. Furthermore, IL1RL1 knockout led to a reduction in HLA-A expression, providing functional evidence for its involvement in antigen presentation.</div></div><div><h3>Conclusion</h3><div>Our findings highlight the immune-regulatory role of IL1RL1<sup>+</sup> mast cells in ccRCC. IL1RL1 may contribute to anti-tumor immunity through the modulation of antigen presentation and CD8<sup>+</sup> T cell activation, offering new insights into its potential as a prognostic biomarker and therapeutic target in renal cancer.</div></div>","PeriodicalId":49799,"journal":{"name":"Molecular and Cellular Probes","volume":"84 ","pages":"Article 102049"},"PeriodicalIF":3.0,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145006730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-30DOI: 10.1016/j.mcp.2025.102048
Amir Hossein Aghayan , Ali Arab , Shadi Haddadi , Amir Atashi
Background
Chronic lymphocytic leukemia (CLL) comprises around 25–30 % of leukemia cases in the West. Emerging evidence underscores the role of non-coding RNAs (ncRNAs) like miRNAs, lncRNAs, and CircRNAs in CLL pathogenesis and regulation. The unique properties of ncRNAs have given the potential as non-invasive diagnostic biomarkers for CLL.
Methods
PubMed, Web of Science, Scopus, ProQuest, and Embase databases were searched (from inception up to January 2024) for studies addressing the correlation of ncRNA expression levels with diagnosis of CLL. The QUADAS-2 tool was employed to evaluate the risk of bias in the included studies. The GRADE approach evaluated the certainty of the evidence for diagnostic test accuracy.
Results
A total of 14 studies including 934 CLL patients were analyzed. Evaluations focused on miRNAs and CircRNAs due to sufficient primary data. For miRNAs, pooled sensitivity: 0.84, specificity: 0.98, positive likelihood ratio (PLR): 42.19, negative likelihood ratio (NLR): 0.16, diagnostic odds ratio (DOR): 260.14; area under the curve (AUC): 0.96. For CircRNAs, pooled sensitivity: 0.69, specificity: 0.77, PLR: 3.01, NLR: 0.40, DOR: 7.51, AUC: 0.80. GRADE assessments indicated very low certainty of evidence for miRNAs and low certainty for CircRNAs.
Conclusion
Both miRNAs and CircRNAs appear to hold promise as non-invasive diagnostic biomarkers in CLL, with miRNAs demonstrating higher diagnostic performance. However, based on the GRADE assessments, the certainty of evidence may undermine the reliability of the pooled estimates. Future studies with rigorous design, larger sample sizes, and standardized protocols are essential to strengthen the certainty of evidence.
背景:慢性淋巴细胞白血病(CLL)约占西方白血病病例的25-30%。新出现的证据强调了非编码rna (ncRNAs)如miRNAs、lncRNAs和CircRNAs在CLL发病机制和调控中的作用。ncrna的独特特性赋予了其作为CLL非侵入性诊断生物标志物的潜力。方法:检索PubMed, Web of Science, Scopus, ProQuest和Embase数据库(从成立到2024年1月),寻找ncRNA表达水平与CLL诊断相关性的研究。采用QUADAS-2工具评估纳入研究的偏倚风险。GRADE方法评估诊断测试准确性证据的确定性。结果:共纳入14项研究,共纳入934例CLL患者。由于有足够的原始数据,评估主要集中在mirna和circrna上。对于miRNAs,合并敏感性:0.84,特异性:0.98,阳性似然比(PLR): 42.19,阴性似然比(NLR): 0.16,诊断优势比(DOR): 260.14;曲线下面积(AUC): 0.96。对于CircRNAs,总敏感性为0.69,特异性为0.77,PLR为3.01,NLR为0.40,DOR为7.51,AUC为0.80。GRADE评估表明,mirna和circrna的证据确定性非常低。结论:mirna和circrna似乎都有望成为CLL的非侵入性诊断生物标志物,其中mirna表现出更高的诊断性能。然而,基于GRADE评估,证据的确定性可能会破坏汇总估计的可靠性。严格设计、更大样本量和标准化方案的未来研究对于加强证据的确定性至关重要。
{"title":"Non-coding RNAs in chronic lymphocytic leukemia: A systematic review and meta-analysis to decode the diagnostic potential","authors":"Amir Hossein Aghayan , Ali Arab , Shadi Haddadi , Amir Atashi","doi":"10.1016/j.mcp.2025.102048","DOIUrl":"10.1016/j.mcp.2025.102048","url":null,"abstract":"<div><h3>Background</h3><div>Chronic lymphocytic leukemia (CLL) comprises around 25–30 % of leukemia cases in the West. Emerging evidence underscores the role of non-coding RNAs (ncRNAs) like miRNAs, lncRNAs, and CircRNAs in CLL pathogenesis and regulation. The unique properties of ncRNAs have given the potential as non-invasive diagnostic biomarkers for CLL.</div></div><div><h3>Methods</h3><div>PubMed, Web of Science, Scopus, ProQuest, and Embase databases were searched (from inception up to January 2024) for studies addressing the correlation of ncRNA expression levels with diagnosis of CLL. The QUADAS-2 tool was employed to evaluate the risk of bias in the included studies. The GRADE approach evaluated the certainty of the evidence for diagnostic test accuracy.</div></div><div><h3>Results</h3><div>A total of 14 studies including 934 CLL patients were analyzed. Evaluations focused on miRNAs and CircRNAs due to sufficient primary data. For miRNAs, pooled sensitivity: 0.84, specificity: 0.98, positive likelihood ratio (PLR): 42.19, negative likelihood ratio (NLR): 0.16, diagnostic odds ratio (DOR): 260.14; area under the curve (AUC): 0.96. For CircRNAs, pooled sensitivity: 0.69, specificity: 0.77, PLR: 3.01, NLR: 0.40, DOR: 7.51, AUC: 0.80. GRADE assessments indicated very low certainty of evidence for miRNAs and low certainty for CircRNAs.</div></div><div><h3>Conclusion</h3><div>Both miRNAs and CircRNAs appear to hold promise as non-invasive diagnostic biomarkers in CLL, with miRNAs demonstrating higher diagnostic performance. However, based on the GRADE assessments, the certainty of evidence may undermine the reliability of the pooled estimates. Future studies with rigorous design, larger sample sizes, and standardized protocols are essential to strengthen the certainty of evidence.</div></div>","PeriodicalId":49799,"journal":{"name":"Molecular and Cellular Probes","volume":"84 ","pages":"Article 102048"},"PeriodicalIF":3.0,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144976163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}