This article, centered on precision therapy, argues that traditional disease-centered clinical trials are flawed with prolonged cycles, insufficient early-phase samples, and inflexible protocols, thus proposing the concept of “clinical trial re-innovation.” It elaborates that this re-innovation, driven by biomarker technology, multi-arm multi-stage designs, and improved trial flexibility, is realized through innovative designs like basket, umbrella, and platform trials, and explores their application in multiple diseases with cases, aiming to advance precise and efficient clinical research and improve patient outcomes.
{"title":"Re-Innovation in Clinical Trial Designs Based on Precision Therapy","authors":"Shenglan Li, Jiachen Wang, Zhuang Kang, Xun Kang, Feng Chen, Wenbin Li","doi":"10.1002/cai2.70028","DOIUrl":"https://doi.org/10.1002/cai2.70028","url":null,"abstract":"<p>This article, centered on precision therapy, argues that traditional disease-centered clinical trials are flawed with prolonged cycles, insufficient early-phase samples, and inflexible protocols, thus proposing the concept of “clinical trial re-innovation.” It elaborates that this re-innovation, driven by biomarker technology, multi-arm multi-stage designs, and improved trial flexibility, is realized through innovative designs like basket, umbrella, and platform trials, and explores their application in multiple diseases with cases, aiming to advance precise and efficient clinical research and improve patient outcomes.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 5","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70028","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145146286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zar Soe Thin, Nancy Choon-Si Ng, Long Chiau Ming, Rebecca Shin-Yee Wong, Bey Hing Goh
Stem cell-based cancer therapies offer novel mechanisms for tumour targeting, immune modulation and tissue repair, with applications from haematopoietic to induced pluripotent stem cells. While showing strong therapeutic promise, their clinical translation is hindered by ethical, regulatory and economic barriers. Coordinated global action is essential to unlock their full potential in oncology.
{"title":"Stem Cell-Based Cancer Therapies: A Commentary on Therapeutic Promise, Health Impacts and Translational Barriers","authors":"Zar Soe Thin, Nancy Choon-Si Ng, Long Chiau Ming, Rebecca Shin-Yee Wong, Bey Hing Goh","doi":"10.1002/cai2.70025","DOIUrl":"https://doi.org/10.1002/cai2.70025","url":null,"abstract":"<p>Stem cell-based cancer therapies offer novel mechanisms for tumour targeting, immune modulation and tissue repair, with applications from haematopoietic to induced pluripotent stem cells. While showing strong therapeutic promise, their clinical translation is hindered by ethical, regulatory and economic barriers. Coordinated global action is essential to unlock their full potential in oncology.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 5","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70025","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145012547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Extrachromosomal circular DNA (eccDNA) is an emerging class of genetic material that exists outside of the chromosomal genome. These circular DNA molecules are gaining increasing attention as important biomarkers in various cancers because of their roles in gene amplification, genetic heterogeneity, and drug resistance. In this review, we explore in depth the impacts of eccDNAs on cancer biology, their potential to predict treatment sensitivity and resistance, and their involvement in the development of new anticancer therapies. eccDNAs can be used as biomarkers for various tumor types to help diagnose and predict prognosis.
{"title":"Extrachromosomal Circular DNA as a Cancer Biomarker: From Diagnosis to Treatment","authors":"Hexin Li, Jiahui Cai, Gang Zhao, Lihui Zou","doi":"10.1002/cai2.70026","DOIUrl":"https://doi.org/10.1002/cai2.70026","url":null,"abstract":"<p>Extrachromosomal circular DNA (eccDNA) is an emerging class of genetic material that exists outside of the chromosomal genome. These circular DNA molecules are gaining increasing attention as important biomarkers in various cancers because of their roles in gene amplification, genetic heterogeneity, and drug resistance. In this review, we explore in depth the impacts of eccDNAs on cancer biology, their potential to predict treatment sensitivity and resistance, and their involvement in the development of new anticancer therapies. eccDNAs can be used as biomarkers for various tumor types to help diagnose and predict prognosis.</p>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 5","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70026","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145012545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chronic myeloid leukemia (CML) is a clonal malignancy propelled by the BCR::ABL1 fusion gene originating from the Philadelphia chromosome. This gene activates ABL tyrosine kinase, which enhances the survival of leukemic cells. Although tyrosine kinase inhibitors (TKIs) have significantly advanced the treatment of CML, resistance to these inhibitors presents a substantial hurdle. Consequently, novel therapeutic strategies targeting resistance mechanisms independent of BCR::ABL1 are urgently needed.
Methods
This study investigated the potential impact of combining WEE1 inhibitors, particularly MK-1775, with vitamin K2 (VK2) in treating CML. To analyze differentially expressed and spliced transcripts in CML, we examined mRNA profiles from peripheral blood mononuclear cells of five patients with CML (during chronic and blast phases) and five healthy controls. The samples were analyzed using deep sequencing. Differential expression analyses were performed using RaNA-Seq and Heatmapper, the latter of which was designed for complex data set visualizations.
Results
WEE1 controls the G2/M checkpoint to prevent early mitosis, and blocking it increases the cytotoxicity of agents that damage deoxyribonucleic acid, especially in cancers lacking p53. VK2, a micronutrient, exerts anticancer effects against various malignancies. Gene expression studies have indicated that PKMYT1 expression is elevated in CML but not WEE1 cells. MK-1775 successfully halted the growth of both standard and TKI-resistant CML cell lines by triggering apoptosis via caspase 3/7 activation. VK2 reduced the viability of CML cells and increased cytotoxicity. A combined regimen of MK-1775 and VK2 markedly decreased colony growth, disrupted mitochondrial membrane potential, and increased death in CML cells, including those resistant to TKIs.
Conclusions
The results suggest that a combination of MK-1775 and VK2 represents a potentially effective treatment strategy for CML, especially in drug-resistant cases.
{"title":"Combination of WEE1 Inhibitor and Vitamin K2 Enhances Therapeutic Efficacy in Chronic Myeloid Leukemia","authors":"Seiichi Okabe, Yuya Arai, Akihiko Gotoh, Daigo Akahane","doi":"10.1002/cai2.70024","DOIUrl":"https://doi.org/10.1002/cai2.70024","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Chronic myeloid leukemia (CML) is a clonal malignancy propelled by the <i>BCR::ABL1</i> fusion gene originating from the Philadelphia chromosome. This gene activates ABL tyrosine kinase, which enhances the survival of leukemic cells. Although tyrosine kinase inhibitors (TKIs) have significantly advanced the treatment of CML, resistance to these inhibitors presents a substantial hurdle. Consequently, novel therapeutic strategies targeting resistance mechanisms independent of <i>BCR::ABL1</i> are urgently needed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study investigated the potential impact of combining WEE1 inhibitors, particularly MK-1775, with vitamin K2 (VK2) in treating CML. To analyze differentially expressed and spliced transcripts in CML, we examined mRNA profiles from peripheral blood mononuclear cells of five patients with CML (during chronic and blast phases) and five healthy controls. The samples were analyzed using deep sequencing. Differential expression analyses were performed using RaNA-Seq and Heatmapper, the latter of which was designed for complex data set visualizations.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>WEE1 controls the G2/M checkpoint to prevent early mitosis, and blocking it increases the cytotoxicity of agents that damage deoxyribonucleic acid, especially in cancers lacking p53. VK2, a micronutrient, exerts anticancer effects against various malignancies. Gene expression studies have indicated that PKMYT1 expression is elevated in CML but not WEE1 cells. MK-1775 successfully halted the growth of both standard and TKI-resistant CML cell lines by triggering apoptosis via caspase 3/7 activation. VK2 reduced the viability of CML cells and increased cytotoxicity. A combined regimen of MK-1775 and VK2 markedly decreased colony growth, disrupted mitochondrial membrane potential, and increased death in CML cells, including those resistant to TKIs.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The results suggest that a combination of MK-1775 and VK2 represents a potentially effective treatment strategy for CML, especially in drug-resistant cases.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 5","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70024","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144915029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Qingcong Kong, Yongxin Chen, Yi Sui, Siyi Chen, Xinghan Lv, Wenjie Tang, Zhidan Zhong, Xiaomeng Yu, Kuiming Jiang, Lei Zhang, Jianning Chen, Jie Qin, Yuan Guo
Background
The predictive value of different MRI sequences for axillary lymph node metastasis (ALNM) in patients with invasive breast cancer remains unclear. This study compared the performance of radiomics models based on individual and combined MRI sequences for the preoperative prediction of ALNM and evaluated the clinical application value of the optimal model.
Methods
This retrospective study included 454 patients (mean ± SD age 50.9 ± 10.7 years) diagnosed with invasive breast cancer from two centers, with 382 patients from Center 1 (training cohort) and 72 patients from Center 2 (external test cohort). Tumor segmentation and radiomics feature extraction were performed on T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) images. The least absolute shrinkage and selection operator with 10-fold cross-validation was used for feature selection and radiomics score construction. Three single-sequence models and one multi-sequence radiomics model were developed, and the optimal model was combined with conventional MRI features to create a combined MRI model. The combined model's performance was compared to radiologists' diagnoses. A nomogram was developed based on the optimal model and correlated with prognosis using the Kaplan–Meier curve and Cox proportional hazard regression. Model performance was evaluated using area under the curve (AUC); DeLong's test was used for comparison.
Results
In the external test cohort, the DCE model showed the highest performance (AUC = 0.76) but was not significantly different from T2WI (AUC = 0.72) and DWI (AUC = 0.70) (all p > 0.05). The combined radiomics model achieved an AUC of 0.82, outperforming DWI and T2WI (p < 0.05), but was not significantly different from the DCE model (p > 0.05). The combined MRI model demonstrated the highest AUC of 0.84 and notably improved radiologist diagnostic accuracy. A nomogram based on the combined MRI model was developed to assist clinical decision-making by providing individualized risk predictions. The higher-risk group based on the model's predictive probability showed a significantly worse prognosis (p < 0.001).
Conclusion
The combined radiomics model outperformed single-sequence models in predicting ALNM. The combined MRI model demonstrated the highest performance, improving diagnostic accuracy and showing potential for prognostic prediction.
{"title":"The Role of Multiparametric MRI Radiomics for Preoperative Prediction of Axillary Lymph Node Metastasis in Patients With Invasive Breast Cancer: A Comparative Study","authors":"Qingcong Kong, Yongxin Chen, Yi Sui, Siyi Chen, Xinghan Lv, Wenjie Tang, Zhidan Zhong, Xiaomeng Yu, Kuiming Jiang, Lei Zhang, Jianning Chen, Jie Qin, Yuan Guo","doi":"10.1002/cai2.70022","DOIUrl":"https://doi.org/10.1002/cai2.70022","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The predictive value of different MRI sequences for axillary lymph node metastasis (ALNM) in patients with invasive breast cancer remains unclear. This study compared the performance of radiomics models based on individual and combined MRI sequences for the preoperative prediction of ALNM and evaluated the clinical application value of the optimal model.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This retrospective study included 454 patients (mean ± SD age 50.9 ± 10.7 years) diagnosed with invasive breast cancer from two centers, with 382 patients from Center 1 (training cohort) and 72 patients from Center 2 (external test cohort). Tumor segmentation and radiomics feature extraction were performed on T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced (DCE) images. The least absolute shrinkage and selection operator with 10-fold cross-validation was used for feature selection and radiomics score construction. Three single-sequence models and one multi-sequence radiomics model were developed, and the optimal model was combined with conventional MRI features to create a combined MRI model. The combined model's performance was compared to radiologists' diagnoses. A nomogram was developed based on the optimal model and correlated with prognosis using the Kaplan–Meier curve and Cox proportional hazard regression. Model performance was evaluated using area under the curve (AUC); DeLong's test was used for comparison.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In the external test cohort, the DCE model showed the highest performance (AUC = 0.76) but was not significantly different from T2WI (AUC = 0.72) and DWI (AUC = 0.70) (all <i>p</i> > 0.05). The combined radiomics model achieved an AUC of 0.82, outperforming DWI and T2WI (<i>p</i> < 0.05), but was not significantly different from the DCE model (<i>p</i> > 0.05). The combined MRI model demonstrated the highest AUC of 0.84 and notably improved radiologist diagnostic accuracy. A nomogram based on the combined MRI model was developed to assist clinical decision-making by providing individualized risk predictions. The higher-risk group based on the model's predictive probability showed a significantly worse prognosis (<i>p</i> < 0.001).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The combined radiomics model outperformed single-sequence models in predicting ALNM. The combined MRI model demonstrated the highest performance, improving diagnostic accuracy and showing potential for prognostic prediction.</p","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144615273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiangyi Kong, Qiang Liu, Zheng Qu, Xiangyu Wang, Wenxiang Zhang, Yulu Liu, Robert Coleman, Chunqing Lin, Jing Wang
Background
Breast cancer is the most common malignancy and a leading cause of cancer-related deaths among women worldwide. Although treatment advances have improved outcomes, the 5-year survival rate for metastatic breast cancer remains low. Understanding the anatomical distribution, associated risks, and prognostic features of metastases in patients with newly diagnosed stage IV breast cancer is essential for improving clinical management. This study aims to comprehensively investigate these aspects using data from the SEER database.
Methods
This study utilized a retrospective cohort design, examining data from the Surveillance, Epidemiology, and End Results (SEER) database. The investigation considered patients diagnosed with stage IV breast cancer from SEER database. Using logistic regression, odds ratios (ORs) were calculated to determine the risk of various metastases, stratified based on sociodemographic and clinicopathological variables. Survival analyses were executed with Kaplan–Meier methodology in tandem with Cox regression analyses.
Results
Out of 356,789 breast cancer patients considered, 18,036 (5.06%) were diagnosed with de novo stage IV disease. Bone metastasis predominated with a composition ratio of 42.6%. Patients with the HR−/HER2+ subtype exhibited the highest metastasis incidence at the time of diagnosis, constituting 8.7% of the entire cohort. Male patients displayed heightened susceptibility to bone, lung, and brain metastases compared to female counterparts. Hispanic individuals exhibited the highest propensity for brain metastases. Relative to other subtypes, the HR−/HER2− patients were more inclined toward lung metastases. Those with bone metastasis had a median survival period of 27 months. Grade III patients with brain or liver metastases faced the most adverse prognoses. A comprehensive profile detailing metastasis patterns by demographics, tumor site and stage, biology, and treatment was presented.
Conclusions
This study represents the most comprehensive analysis of metastasis' anatomical distribution and prognosis in breast cancer, offering invaluable insights into metastatic tendencies and characteristics.
{"title":"Mapping the Metastatic Landscape: A Population-Based Cohort Study for Prognostic Insights Into Newly Diagnosed Stage IV Breast Cancer Cases","authors":"Xiangyi Kong, Qiang Liu, Zheng Qu, Xiangyu Wang, Wenxiang Zhang, Yulu Liu, Robert Coleman, Chunqing Lin, Jing Wang","doi":"10.1002/cai2.70017","DOIUrl":"https://doi.org/10.1002/cai2.70017","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Breast cancer is the most common malignancy and a leading cause of cancer-related deaths among women worldwide. Although treatment advances have improved outcomes, the 5-year survival rate for metastatic breast cancer remains low. Understanding the anatomical distribution, associated risks, and prognostic features of metastases in patients with newly diagnosed stage IV breast cancer is essential for improving clinical management. This study aims to comprehensively investigate these aspects using data from the SEER database.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This study utilized a retrospective cohort design, examining data from the Surveillance, Epidemiology, and End Results (SEER) database. The investigation considered patients diagnosed with stage IV breast cancer from SEER database. Using logistic regression, odds ratios (ORs) were calculated to determine the risk of various metastases, stratified based on sociodemographic and clinicopathological variables. Survival analyses were executed with Kaplan–Meier methodology in tandem with Cox regression analyses.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Out of 356,789 breast cancer patients considered, 18,036 (5.06%) were diagnosed with de novo stage IV disease. Bone metastasis predominated with a composition ratio of 42.6%. Patients with the HR−/HER2+ subtype exhibited the highest metastasis incidence at the time of diagnosis, constituting 8.7% of the entire cohort. Male patients displayed heightened susceptibility to bone, lung, and brain metastases compared to female counterparts. Hispanic individuals exhibited the highest propensity for brain metastases. Relative to other subtypes, the HR−/HER2− patients were more inclined toward lung metastases. Those with bone metastasis had a median survival period of 27 months. Grade III patients with brain or liver metastases faced the most adverse prognoses. A comprehensive profile detailing metastasis patterns by demographics, tumor site and stage, biology, and treatment was presented.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study represents the most comprehensive analysis of metastasis' anatomical distribution and prognosis in breast cancer, offering invaluable insights into metastatic tendencies and characteristics.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70017","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144598566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There is significant heterogeneity in patterns of colorectal cancer burden, which is still not well understood. This study examines global trajectories in the colorectal cancer burden, explores associated factors, and predicts future trends.
Methods
Data on the colorectal cancer burden for 204 countries and territories from 1990 to 2021 were sourced from the Global Burden of Disease Study. Growth mixture models identified subgroups of age-standardized incidence and mortality rates. Eleven modifiable risk factors and four socioeconomic determinants were analyzed across the subgroups. Trends to 2040 were predicted using a Bayesian age-period-cohort model.
Results
Three trajectories of colorectal cancer burden were observed: slowly increasing, rapidly increasing, and slowly decreasing age-standardized incidence rate, corresponding to stable, increasing, and decreasing mortality rate. Most countries showed slowly increasing incidence rates (49.0%, n = 100) and stable age-standardized mortality rates (51.0%, n = 104). Latin America and the Caribbean predominantly have a rapidly increasing trend (age-standardized incidence: 69.7%; mortality rates: 63.6%), while high-income countries largely followed decreasing trajectories (incidence: 58.3%; mortality: 75.0%). Higher sociodemographic index, universal health coverage, health expenditure, and gross domestic product per capita were linked to decreasing trends (all p < 0.05). Low consumption of whole grains and milk, and excessive red meat consumption, contributed significantly to colorectal cancer mortality. However, the impact of behavioral factors such as physical inactivity, smoking, and alcohol consumption was relatively small. Mortality attributable to high fasting blood sugar and body mass index is rising. Despite a slight global decline in mortality, disparities are projected to persist through 2040.
Conclusion
Global disparities in colorectal cancer burden highlight the need for targeted interventions, particularly focusing on dietary factors and health inequities.
{"title":"Global Trajectories of Colorectal Cancer Burden From 1990 to 2021 and Projection to 2040","authors":"Xiaolu Chen, Xuesi Dong, Yadi Zheng, Chenran Wang, Zilin Luo, Jiaxin Xie, Zeming Guo, Xiaoyue Shi, Xinyue Zhu, Yongjie Xu, Wei Cao, Fei Wang, Ni Li","doi":"10.1002/cai2.70020","DOIUrl":"https://doi.org/10.1002/cai2.70020","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>There is significant heterogeneity in patterns of colorectal cancer burden, which is still not well understood. This study examines global trajectories in the colorectal cancer burden, explores associated factors, and predicts future trends.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Data on the colorectal cancer burden for 204 countries and territories from 1990 to 2021 were sourced from the Global Burden of Disease Study. Growth mixture models identified subgroups of age-standardized incidence and mortality rates. Eleven modifiable risk factors and four socioeconomic determinants were analyzed across the subgroups. Trends to 2040 were predicted using a Bayesian age-period-cohort model.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Three trajectories of colorectal cancer burden were observed: slowly increasing, rapidly increasing, and slowly decreasing age-standardized incidence rate, corresponding to stable, increasing, and decreasing mortality rate. Most countries showed slowly increasing incidence rates (49.0%, <i>n</i> = 100) and stable age-standardized mortality rates (51.0%, <i>n</i> = 104). Latin America and the Caribbean predominantly have a rapidly increasing trend (age-standardized incidence: 69.7%; mortality rates: 63.6%), while high-income countries largely followed decreasing trajectories (incidence: 58.3%; mortality: 75.0%). Higher sociodemographic index, universal health coverage, health expenditure, and gross domestic product per capita were linked to decreasing trends (all <i>p</i> < 0.05). Low consumption of whole grains and milk, and excessive red meat consumption, contributed significantly to colorectal cancer mortality. However, the impact of behavioral factors such as physical inactivity, smoking, and alcohol consumption was relatively small. Mortality attributable to high fasting blood sugar and body mass index is rising. Despite a slight global decline in mortality, disparities are projected to persist through 2040.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Global disparities in colorectal cancer burden highlight the need for targeted interventions, particularly focusing on dietary factors and health inequities.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144582231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Glioblastoma is a highly malignant type of brain tumor that remains one of the most challenging cancers to treat because of its aggressive nature, genetic heterogeneity, and immunosuppressive tumor microenvironment. Despite advances in standard treatments, such as surgery, radiation, and chemotherapy, patient outcomes remain poor, driving the need for innovative therapeutic approaches. Cellular immune theranostics, which combines therapeutic and diagnostic capabilities, has emerged as a promising strategy to combat glioblastoma. The present review discusses recent advances in cellular immunotherapy, including the development and application of chimeric antigen receptor T cells, chimeric antigen receptor natural killer cells, and macrophage-based therapies. In addition, this review highlights the potential of oncolytic viruses and personalized tumor vaccines for improving immunotherapy outcomes. The integration of advanced diagnostic tools, such as the real-time monitoring of therapeutic responses through immunobiomarkers and imaging techniques, is emphasized as crucial for optimizing treatment strategies. However, important challenges remain, including the complexity of immune cell engineering, the difficulties of therapeutic delivery across the blood–brain barrier, and the immunosuppressive properties of the tumor microenvironment. Overcoming these challenges through innovative methodologies will be vital for improving the efficacy of cellular immune theranostics in the treatment of glioblastoma, with the ultimate goal of improving patient survival and quality of life.
{"title":"Advances in Cellular Immune Theranostic Approaches for Glioblastoma: Current Trends and Future Directions","authors":"Ying Gong, Wanying Lin, Xuechun Fang, Ruyi Zhang, Min Luo, Haoran Wu, Shuai Chu, Chuangkun Li, Yiming Peng, Zhiyan Piao, Siping Wu, Junhao Li, ZongZhong He, Haixia Li, Hongxia Wang","doi":"10.1002/cai2.70018","DOIUrl":"https://doi.org/10.1002/cai2.70018","url":null,"abstract":"<p>Glioblastoma is a highly malignant type of brain tumor that remains one of the most challenging cancers to treat because of its aggressive nature, genetic heterogeneity, and immunosuppressive tumor microenvironment. Despite advances in standard treatments, such as surgery, radiation, and chemotherapy, patient outcomes remain poor, driving the need for innovative therapeutic approaches. Cellular immune theranostics, which combines therapeutic and diagnostic capabilities, has emerged as a promising strategy to combat glioblastoma. The present review discusses recent advances in cellular immunotherapy, including the development and application of chimeric antigen receptor T cells, chimeric antigen receptor natural killer cells, and macrophage-based therapies. In addition, this review highlights the potential of oncolytic viruses and personalized tumor vaccines for improving immunotherapy outcomes. The integration of advanced diagnostic tools, such as the real-time monitoring of therapeutic responses through immunobiomarkers and imaging techniques, is emphasized as crucial for optimizing treatment strategies. However, important challenges remain, including the complexity of immune cell engineering, the difficulties of therapeutic delivery across the blood–brain barrier, and the immunosuppressive properties of the tumor microenvironment. Overcoming these challenges through innovative methodologies will be vital for improving the efficacy of cellular immune theranostics in the treatment of glioblastoma, with the ultimate goal of improving patient survival and quality of life.</p>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144551111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaomei Yao, Ashirbani Saha, Sharan Saravanan, Ashley Low, Jonathan Sussman
Background
Conducting a systematic review (SR) is a time-intensive process and represents the first phase in developing a clinical practice guideline (CPG). Completing a CPG through the Program in Evidence-Based Care (PEBC), a globally acknowledged guideline program supported by Ontario Health (Cancer Care Ontario), typically takes about 2 years. Thus, expediting an SR can significantly reduce the overall time required to complete a CPG. Our recently published review identified two artificial intelligence (AI) tools, DistillerSR and EPPI-Reviewer that reduced time in the title and abstract screening in an SR process when developing a CPG. However, the consistency and generalizability of these tools remain unclear within or across different SRs related to cancer. This study protocol aims to evaluate and compare the performance of DistillerSR and EPPI-Reviewer against human reviewers for title and abstract screening (Stage I screening) in cancer CPG development.
Methods
We will conduct a retrospective simulation study to evaluate and compare the performance of DistillerSR and EPPI-Reviewer across 10 previously published CPGs by PEBC. These CPGs include the five cancer types with the highest incidence (lung, breast, prostate, colorectal, and bladder). We will run 30 simulation trials for one CPG per AI tool. Primary outcomes are workload savings and time savings in Stage I screening. The secondary outcome is the percentage of missing articles among the final included articles. This informs the accuracy and comprehensiveness of the AI tools. Descriptive and inferential statistical analysis will be conducted to evaluate the outcomes.
Results
This is a study protocol. The data presented in the tables are illustrative examples rather than actual study results, in accordance with the journal s standard structure. All data included in the final study will be thoroughly validated.
Discussion
This will be the first study to investigate and compare the performance of DistillerSR and EPPI-Reviewer in Stage I screening of SRs in CPGs across different cancer types. These findings will inform the reliable use of AI tools in future cancer-related CPGs. The results from this retrospective study will need to be confirmed by prospective studies.
{"title":"A Study Protocol for a Comprehensive Evaluation of Two Artificial Intelligence-Based Tools in Title and Abstract Screening for the Development of Evidence-Based Cancer Guidelines","authors":"Xiaomei Yao, Ashirbani Saha, Sharan Saravanan, Ashley Low, Jonathan Sussman","doi":"10.1002/cai2.70021","DOIUrl":"https://doi.org/10.1002/cai2.70021","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Conducting a systematic review (SR) is a time-intensive process and represents the first phase in developing a clinical practice guideline (CPG). Completing a CPG through the Program in Evidence-Based Care (PEBC), a globally acknowledged guideline program supported by Ontario Health (Cancer Care Ontario), typically takes about 2 years. Thus, expediting an SR can significantly reduce the overall time required to complete a CPG. Our recently published review identified two artificial intelligence (AI) tools, DistillerSR and EPPI-Reviewer that reduced time in the title and abstract screening in an SR process when developing a CPG. However, the consistency and generalizability of these tools remain unclear within or across different SRs related to cancer. This study protocol aims to evaluate and compare the performance of DistillerSR and EPPI-Reviewer against human reviewers for title and abstract screening (Stage I screening) in cancer CPG development.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We will conduct a retrospective simulation study to evaluate and compare the performance of DistillerSR and EPPI-Reviewer across 10 previously published CPGs by PEBC. These CPGs include the five cancer types with the highest incidence (lung, breast, prostate, colorectal, and bladder). We will run 30 simulation trials for one CPG per AI tool. Primary outcomes are workload savings and time savings in Stage I screening. The secondary outcome is the percentage of missing articles among the final included articles. This informs the accuracy and comprehensiveness of the AI tools. Descriptive and inferential statistical analysis will be conducted to evaluate the outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>This is a study protocol. The data presented in the tables are illustrative examples rather than actual study results, in accordance with the journal s standard structure. All data included in the final study will be thoroughly validated.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>This will be the first study to investigate and compare the performance of DistillerSR and EPPI-Reviewer in Stage I screening of SRs in CPGs across different cancer types. These findings will inform the reliable use of AI tools in future cancer-related CPGs. The results from this retrospective study will need to be confirmed by prospective studies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144514973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Although lung cancer remains a global threat to public health, evidenced based advances in screening and prevention hold promise for reducing its impact on mortality. An ongoing challenge facing the clinical and research community are the glaring disparities in access to preventive services faced by ethnically and socioeconomically marginalized groups. In this context, novel approaches are needed to improve research methods and thus bolster our ability to improve outcomes. Artificial intelligence (AI) applications such as machine learning and natural language processing hold promise as catalysts in this process, enhancing speed, accuracy and capability. This perspective will highlight the potential of AI methods as essential tool for growth across the lung cancer diagnostic continuum from screening to diagnosis.
{"title":"Artificial Intelligence-Based Methods: The Path Forward in Achieving Equity in Lung Cancer Screening and Evaluation","authors":"Stephen J. Kuperberg, David C. Christiani","doi":"10.1002/cai2.70019","DOIUrl":"https://doi.org/10.1002/cai2.70019","url":null,"abstract":"<p>Although lung cancer remains a global threat to public health, evidenced based advances in screening and prevention hold promise for reducing its impact on mortality. An ongoing challenge facing the clinical and research community are the glaring disparities in access to preventive services faced by ethnically and socioeconomically marginalized groups. In this context, novel approaches are needed to improve research methods and thus bolster our ability to improve outcomes. Artificial intelligence (AI) applications such as machine learning and natural language processing hold promise as catalysts in this process, enhancing speed, accuracy and capability. This perspective will highlight the potential of AI methods as essential tool for growth across the lung cancer diagnostic continuum from screening to diagnosis.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144323529","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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