Cancer Innovation最新文献

{"title":"Treatment Outcomes With Novel Targeted and Immunotherapeutic Regimens in CAYA Hodgkin Lymphoma: A Retrospective Study","authors":"Mengqing Xie,&nbsp;Meng Yuan,&nbsp;Mengwei Ren,&nbsp;Jing Tian,&nbsp;Shengyu Zhou,&nbsp;Xiaohui He,&nbsp;Yan Qin,&nbsp;Peng Liu,&nbsp;Jianliang Yang,&nbsp;Mengyuan Han,&nbsp;Fei Ma,&nbsp;Sheng Yang,&nbsp;Sidan Li","doi":"10.1002/cai2.70050","DOIUrl":"https://doi.org/10.1002/cai2.70050","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>To evaluate the efficacy and safety of novel chemotherapy regimens, including brentuximab vedotin (BV) and immune checkpoint inhibitors (ICIs), in children, adolescents, and young adults (CAYA) with Hodgkin lymphoma (HL).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A retrospective analysis was conducted on untreated Stage IIB (bulky), III, or IV HL patients (≤ 24 years) who were admitted to Cancer Hospital of the Chinese Academy of Medical Sciences and Beijing Children's Hospital, Capital Medical University, from 2017 to 2024. The cohort compared conventional regimens with BV‑based therapies (BV‑AVD ± R). Furthermore, the efficacy and safety of ICIs were evaluated in relapsed/refractory cHL patients receiving second‑line or later therapy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>In this comparison between BV and conventional regimens, 182 patients were enrolled. The median follow-up was 38 months. No significant differences were observed in objective response rate (ORR) (96.4% <i>vs</i> 95.4%, <i>p</i> = 0.927) or progression-free survival (PFS) rate (92.8% <i>vs</i> 95.3%, <i>p</i> = 0.466).However, the incidence of Grade 4 hematologic toxicity was significantly higher with conventional therapy compared to BV-AVD±R (61.2% <i>vs</i> 25.6%, <i>p</i> &lt; 0.001). The BV-AVD group alone achieved a significantly higher ORR than the BV -AVD+R group (100% vs. 93.9%, <i>p</i> = 0.047), while there was no significant difference in PFS rate. However, the BV-AVD + R group exhibited a significantly higher incidence of Grade 3–4 hematologic toxicities (78.8% vs. 20.0%, <i>p</i> = 0.023). Immune checkpoint inhibitors was well-tolerated with infrequent adverse events, and 18/19 cases (94.7%) demonstrated treatment efficacy.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>For patients with stage II Hodgkin lymphoma presenting with bulky disease, as well as those with stage III–IV disease, the BV-AVD regimen is recommended as first-line therapy, given its more favorable toxicity profile.Although ICIs represent a promising therapeutic approach, existing studies are constrained by limited sample sizes. Future research should focus on expanding patient cohorts to refine treatment strategies and ultimately improve clinical outcomes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"5 2","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70050","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147566454","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}

{"title":"East-West Convergence in Oncology: Treating Different Diseases With the Same Therapy","authors":"Fei Ma,&nbsp;Yuchen Jiao","doi":"10.1002/cai2.70051","DOIUrl":"10.1002/cai2.70051","url":null,"abstract":"&lt;p&gt;In the course of millennia, traditional Chinese medicine (TCM) has crystallized eastern medical wisdom into a pragmatic, patient-centered worldview during clinical practice. Over the past century, western medicine has increasingly drawn theory support from TCM's conceptual framework, helping to accelerate the shift from empirical medicine to precision medicine. The earliest extant TCM classic, the Huangdi Neijing (Yellow Emperor's Classic of Internal Medicine), compiled during the Spring and Autumn Period (770–476 &lt;span&gt;BCE&lt;/span&gt;) and the Warring States Period (475–221 &lt;span&gt;BCE&lt;/span&gt;), articulates a principle that still resonates today: governing the many through the One.&lt;/p&gt;&lt;p&gt;This convergence is also philosophical. Taoism traces all things to a common source—“the Tao gives birth to the One; the One generates the Two, the Two generate the Three, and from the Three arise all things.”—while Confucianism embraces “harmony without uniformity,” the search for unity within diversity. In oncology, that means looking past outward differences to the inner drivers of disease. In clinical practice, this becomes the “yi bing tong zhi” theory, that is, treating different diseases with the same therapy. While tumors arise in different organs and present different signs and symptoms in clinical practice, their underlying imbalances may be due to blood stasis or deficiency of vital qi. On that common foundation, practitioners apply shared therapeutic principles—regulating the spleen and stomach, clearing heat and resolving toxins—to restore systemic balance and halt disease progression. Academician of Chinese Academy of Engineering (CAE), Sun Yan, a leading authority of clinical oncology in China, has often recited the TCM tenet of “treating different diseases with the same therapy.” Clinical breakthroughs in modern oncology's precision targeted therapy echo this concept, bridging time and space to connect eastern and western medicine in a shared exploration of life and health.&lt;/p&gt;&lt;p&gt;With the progress of Human Genome Project and the rise of comprehensive molecular profiling, our insight into cancer has moved from the macro to the micro. Tumors historically defined by various organs can harbor the same driver alterations. HER2 (human epidermal growth factor receptor 2) overexpression is observed in both breast and gastric cancers; HER2 mutations appear in subsets of lung cancers; alterations in HER2 signaling are found in portions of colorectal and gynecologic malignancies. In essence, tumors from different systems may share a common disease etiology—the western analogue to TCM's notion of shared pathogenesis. This insight has reshaped modern therapeutic practice.&lt;/p&gt;&lt;p&gt;Trastuzumab is the first targeted drug, which transformed outcomes in HER2-positive breast cancer and subsequently prolonged survival in HER2-positive advanced gastric cancer. A new generation of HER2-targeted agents—exemplified by trastuzumab deruxtecan—leverages the precision of an antibo","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"5 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12909263/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146222558","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}

{"title":"Binary and Ternary Classification Prediction for Breast Cancer and Breast Sclerosing Adenosis With Interpretable Artificial Intelligence From Clinical and Imaging Features: A Retrospective, Diagnostic Accuracy Cohort Study","authors":"Yang Qu,&nbsp;Jie Lian,&nbsp;Tianli Liu,&nbsp;Ying Xu,&nbsp;Zhe Wang,&nbsp;Futian Weng,&nbsp;Jiahui Zhang,&nbsp;Xu Yang,&nbsp;Jing Qin,&nbsp;Ming Wang,&nbsp;Wen Xu,&nbsp;Wenbo Li,&nbsp;Lingyan Kong,&nbsp;Xinyu Ren,&nbsp;Qiang Sun,&nbsp;Bo Pan,&nbsp;Yidong Zhou,&nbsp;Yan Xu","doi":"10.1002/cai2.70049","DOIUrl":"10.1002/cai2.70049","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Sclerosing adenosis (SA) and breast cancer (BC) often exhibit overlapping clinical, imaging, and pathological characteristics, making them difficult to differentiate. SA may also coexist with BC (SA + BC), including ductal carcinoma in situ (SA-DCIS) and invasive breast cancer (SA-IBC), which complicates diagnosis even when core-needle biopsy (CNB) suggests SA. This study aimed to develop interpretable AI-based binary and ternary classification models that leverage clinical and imaging features to distinguish SA-only from SA + BC and to further differentiate among SA-only, SA-DCIS, and SA-IBC.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We retrospectively analyzed a cohort of 726 patients with SA (January 2006 to December 2021), comprising 537 SA-only and 189 SA + BC cases (90 SA-DCIS, 99 SA-IBC). Multiple machine learning algorithms—logistic regression, support vector machine, decision tree, XGBoost, and random forest—were compared using AUC, accuracy, F1-score, and C-index. Model interpretability was assessed with SHAP to elucidate feature contributions and identify key predictors. Additionally, we incorporated an independent external validation cohort consisting of 113 patients to verify the model's effectiveness.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;XGBoost consistently outperformed other algorithms in both tasks. Eight features emerged as most informative: age, ultrasound BI-RADS category, maximum and minimum ultrasound diameters, ultrasound margin characteristics, biopsy procedure, mammographic density, and microcalcifications. For binary classification (SA-only vs. SA + BC), XGBoost achieved an AUC of 0.925, accuracy of 0.883, and C-index of 0.844. For ternary classification (SA-only, SA-DCIS, SA-IBC), the model achieved an AUC of 0.888, accuracy of 0.811, and C-index of 0.813. Age, ultrasound BI-RADS, and minimum lesion diameter were consistently top predictors. We further proposed a three-tier interpretability framework (global, cohort-level; local, subgroup-level; and individual, case-level) to facilitate clinical translation.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusion&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Given the substantial risk of coexisting of SA with DCIS or IBC, and the potential for CNB to underestimate disease due to limited sampling, lesions diagnosed as SA on CNB should be evaluated with additional modalities before determining the need for surgical excision. The proposed interpretable AI model enhances discrimination between SA-only and SA with concomitant breast cancer (SA + BC), thereby supporting more in","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"5 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12901693/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146204531","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}

{"title":"AI and Big Data in Oncology: A Physician-Centered Perspective on Emerging Clinical and Research Applications","authors":"Binliang Liu,&nbsp;Qingyao Shang,&nbsp;Jun Li,&nbsp;Shuna Yao,&nbsp;Meishuo Ouyang,&nbsp;Yu Wang,&nbsp;Sheng Luo,&nbsp;Quchang Ouyang","doi":"10.1002/cai2.70047","DOIUrl":"10.1002/cai2.70047","url":null,"abstract":"<p>The convergence of artificial intelligence (AI) and big data is reshaping contemporary oncology by enabling the integration of multimodal information across imaging, pathology, genomics, and clinical records. From a physician-centered perspective, these technologies can potentially be used to improve diagnostic precision, support individualized treatment planning, enhance longitudinal patient management, and accelerate both clinical and translational research. In this review, we synthesize the core AI methodologies most relevant to oncology—machine learning, deep learning, and large language models—and examine how they interact with established and emerging oncology data platforms. We further highlight practical use cases in clinical workflows and research pipelines, emphasizing opportunities for advancing precision cancer care while also addressing challenges associated with data heterogeneity, model generalizability, privacy protection, and real-world implementation. By underscoring the synergistic value of AI and big data, this review aims to inform the development of clinically meaningful, context-adapted strategies that promote translational innovation in both global and locally resourced healthcare environments.</p>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"5 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12855167/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146109491","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}

{"title":"Global, Population and Genetic Evidence on the Relationships Between Immune-Mediated Inflammatory Disease and Cancer Risk","authors":"Xuesi Dong,&nbsp;Jiaxin Xie,&nbsp;Zilin Luo,&nbsp;Hao Hong,&nbsp;Chenran Wang,&nbsp;Yadi Zheng,&nbsp;Xiaoyue Shi,&nbsp;Zeming Guo,&nbsp;Xiaolu Chen,&nbsp;Yongjie Xu,&nbsp;Wei Cao,&nbsp;Fei Wang,&nbsp;Dong Hang,&nbsp;Sipeng Shen,&nbsp;Fengwei Tan,&nbsp;Ni Li","doi":"10.1002/cai2.70048","DOIUrl":"10.1002/cai2.70048","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Immune-mediated inflammatory disease (IMID) and cancer share underlying mechanisms. We aimed to comprehensively evaluate the associations between IMIDs and cancers from global, population and genetic perspectives.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A triangulation framework was employed to assess the association between IMIDs and cancers, using the Global Burden of Disease Study (2012–2021) to analyse six IMIDs and 33 cancers. The UK Biobank (UKBB) prospective cohort was subsequently used to validate these associations, with hazard ratios (HRs) and 95% confidence intervals (CIs) estimated by Cox proportional hazards models. Causal inference based on genetic instruments was performed in the FinnGen and UKBB to assess the potential causal effects between IMIDs and cancers.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>IMIDs were positively associated with the occurrence of cancers from a global perspective. Moreover, 170 specific IMID-cancer pairs revealed statistically significant associations. A total of 20 pairs of specific IMID-cancer associations were further confirmed in the UKBB cohort. Among these, the five most pronounced associations included atopic dermatitis with Hodgkin lymphoma (HR = 12.56, 95% CI: 1.76–89.59), with ovarian cancer (HR = 5.65, 95% CI: 1.41–22.65) and with non-Hodgkin lymphoma (HR = 5.11, 95% CI: 1.91–13.63); rheumatoid arthritis with Hodgkin lymphoma (HR = 3.85, 95% CI: 1.11–13.32); and psoriasis with Hodgkin lymphoma (HR = 3.43, 95% CI: 1.69–6.96). Additionally, a positive causal association between rheumatoid arthritis and Hodgkin lymphoma (inverse variance weighted OR = 1.31, 95% CI: 1.10–1.57) was observed.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>This study provides comprehensive evidence of the relationships between IMIDs and cancers from global, population and genetic perspectives and identifies 20 pairs of specific IMID-cancer associations, thereby contributing to advancements in cancer prevention and control.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"5 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12815612/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146021009","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}

{"title":"Potential Targets and Biomarkers of Radionuclide Therapy in Breast Cancer","authors":"Yujing Tan,&nbsp;Cheng Zeng,&nbsp;Jiani Wang,&nbsp;Fei Ma","doi":"10.1002/cai2.70043","DOIUrl":"https://doi.org/10.1002/cai2.70043","url":null,"abstract":"<p>In recent years, multidisciplinary treatment strategies have profoundly improved drug responses and survival outcomes of breast cancer (BC) patients. However, there is an urgent need for novel therapies for BC patients who are heavily treated or develop resistance to conventional treatment regimens. Radionuclide therapy (RT) and targeted radionuclide therapy (TRT) have emerged as paradigm-shifting therapeutic approaches for BC, which enable functions of both imaging and localised treatment. They utilise radionuclides that can selectively bind to biomarkers overexpressing on BC cells, allowing precise delivery and localised tumour irradiation. Moreover, several types of radionuclides possess ‘cross-fire’ effects that result in the eradication of neighbouring tumour cells lacking the biomarker expression. In the current review, we summarise the potential biomarkers for the development of RT and TRT that can be employed in the treatment of BC, including receptor markers of ER, PR and HER2, together with other markers of Trop2, PD-1, EGFR, GRPR and PSMA.</p>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"5 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70043","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146002372","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}

{"title":"Statins in Breast Cancer Therapy: Mechanistic Insights and Emerging Evidence","authors":"Rohina Alim,&nbsp;H. M. Kasuni Akalanka","doi":"10.1002/cai2.70040","DOIUrl":"10.1002/cai2.70040","url":null,"abstract":"<p>Breast cancer (BC) remains the most frequently diagnosed malignancy worldwide, with an estimated 2.3 million new cases and approximately 685,000 deaths reported in 2020. Forecasts suggest a substantial rise in global incidence, with new annual cases projected to reach 3.2 million by 2050, representing a 39% increase. Additionally, BC is expected to account for approximately 7.7% of the anticipated $25.2 trillion global economic burden associated with cancer by 2050. These trends underscore an urgent need for affordable, widely accessible and effective therapeutic strategies, particularly in low- and middle-income countries. Statins, commonly prescribed for the treatment of hypercholesterolaemia via inhibition of 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase, have garnered increasing interest for their potential anticancer properties. This review focuses on the mechanistic underpinnings and therapeutic implications of statin use, particularly simvastatin, in the context of BC. Statins exert their primary effect through inhibition of the mevalonate pathway, which is crucial for cholesterol and isoprenoid biosynthesis. Disruption of this pathway impairs the prenylation of key signalling proteins, including members of the Ras and Rho GTPase families, which are essential for cancer cell proliferation, survival and metastasis. Preclinical evidence has demonstrated that simvastatin can induce tumour cell apoptosis, arrest cell-cycle progression and inhibit oncogenic signalling pathways. These effects have been particularly pronounced in hormone receptor-negative and triple-negative breast cancer (TNBC) subtypes, which are often associated with poor prognosis and limited treatment options. Epidemiological and observational studies further support a potential association between statin use and reduced BC recurrence and mortality. Nevertheless, robust evidence from randomised controlled trials remains limited, and further investigation is required to establish causality and define optimal therapeutic regimens. Given their well-established safety profile, global accessibility and pleiotropic effects, statins, especially simvastatin, represent a promising class of repurposed drugs in the adjuvant treatment of BC. This review synthesises evidence from the past two decades, highlighting the need for continued clinical research to validate and optimise the use of statins as adjunctive agents in BC therapy.</p>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"5 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12810717/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146000354","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}

{"title":"An Anoikis Resistance Phenotype Converged to Immune Dysfunction and Resistance to Immune Checkpoint Blockades in Gastric Cancer","authors":"Xing Cai,&nbsp;Jinru Yang,&nbsp;Fangyuan Zhang,&nbsp;Fuwang Xu,&nbsp;Yuan Fang,&nbsp;Zongbi Yi","doi":"10.1002/cai2.70044","DOIUrl":"https://doi.org/10.1002/cai2.70044","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Gastric cancer (GC) continues to pose a significant global health challenge due to its high rates of incidence and mortality, with the majority of cases identified at advanced stages. Immunotherapy, particularly immune checkpoint blockades (ICBs), has demonstrated considerable therapeutic potential; however, many patients do not exhibit a favorable response. As a result, constructing a predictive model to assess ICBs' responsiveness is essential for enhancing treatment outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Using consensus clustering based on anoikis-related gene expression, GC patients were stratified into two subclusters. Differences in tumor immune microenvironment, ICB resistance, genomic alterations, methylation profiles, and transcriptional networks were analyzed. A machine learning-based strategy was employed to develop a consensus anoikis-related gene signature (ARGS). Potential therapeutic targets were identified through single-cell RNA sequencing (scRNA-seq), and validation was conducted using multiplex immunofluorescence and immunohistochemistry in an in-house cohort (n = 28), including 14 ICB responders and 14 nonresponders.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The anoikis-resistant cluster (Cluster A) was associated with poorer survival, immunosuppressive infiltration, lower tumor mutation burden, and ICB resistance. ScRNA-seq revealed high fibroblast and endothelial infiltration, with GLI3⁺ cancer-associated fibroblasts suggesting Hedgehog pathway involvement. The ARGS model effectively stratified patients, with elevated scores associated with immunotherapy resistance, enhanced AR characteristics, and poorer clinical outcomes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The ARGS model offers a valuable tool for predicting prognosis and ICB response in GC, and may guide more precise and personalized immunotherapeutic strategies.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"5 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2026-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cai2.70044","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145987193","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}

{"title":"Artificial Intelligence-Enabled Electrocardiogram for the Detection and Management of Cancer Therapy-Related Cardiotoxicity","authors":"Wenhua Song,&nbsp;Runze Gao,&nbsp;Tong Liu","doi":"10.1002/cai2.70042","DOIUrl":"10.1002/cai2.70042","url":null,"abstract":"&lt;p&gt;Cancer remains a predominant cause of morbidity and mortality in contemporary society globally. Whilst therapeutic advancements such as chemotherapy, radiotherapy, immunotherapy, have substantially improved survival outcomes in cancer patients, these interventions are frequently associated with cardiotoxic effects [&lt;span&gt;1-3&lt;/span&gt;]. Notably, the incidence of cardiotoxicity among cancer patients exhibits substantial heterogeneity across studies, with documented rates between 3.8% and 37.5% [&lt;span&gt;4&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;Guidelines from learned cardiology societies recommend the use of baseline electrocardiograms (ECGs) for all patients prior to the initiation of cancer therapy [&lt;span&gt;1&lt;/span&gt;]. Thus, ECG data should be readily available as part of the routinely collected health data. Artificial intelligence (AI) can integrate multimodal data (e.g., imaging, pathology, and clinical records) together with ECG analysis to optimize diagnostic accuracy and treatment personalization [&lt;span&gt;5&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;Feng et al. recently published a review article in &lt;i&gt;Cancer Innovation&lt;/i&gt; on the use of AI for breast cancer management. The authors highlighted the significance of constructing patient-oriented AI algorithms in management of breast cancer patients [&lt;span&gt;6&lt;/span&gt;]. AI has been extensively employed across all facets of breast cancer management, including diagnosis, risk prediction, treatment response evaluation, and prognosis assessment. As the most widely accessible and standardized cardiac diagnostic tool, the integration of AI with ECG interpretation has the potential to transform cardiovascular care for cancer patients. Here, we evaluate the evidence for AI-enabled ECG analysis in cancer therapy-related cardiotoxicity (CTRC) detection and its emerging role in risk stratification for high-risk oncology patients, also analyze the implications for clinical decision-making in cardio-oncology.&lt;/p&gt;&lt;p&gt;The integration of large-scale ECGs with comprehensive data fields from clinical databases has enabled the development of AI models with high sensitivity to detect diverse cardiovascular pathologies [&lt;span&gt;7-9&lt;/span&gt;]. Unlike conventional ECG interpretation that requires the manual interpretation by cardiologists, AI-based algorithms demonstrate distinct advantages including operator independence, rapid processing capability, and integrated diagnostic-prognostic functionality [&lt;span&gt;10&lt;/span&gt;]. AI primarily encompasses two dominant approaches in contemporary healthcare applications, including machine learning and deep learning (DL). Notably, convolutional neural networks (CNN)—a specialized DL architecture—have become particularly transformative in medical image analysis due to their exceptional capability to deal with spatial hierarchies in imaging data [&lt;span&gt;11&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;Numerous studies have indeed demonstrated the effectiveness and potential clinical practicality of AI-ECG in evaluating various cardiac conditions, which showed promising accuracy of","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12745162/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145866562","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}

{"title":"The Role of DNA Methyltransferases in Urinary System Diseases","authors":"Wei Dong,&nbsp;Shengbin Pei,&nbsp;Dacheng Zhu,&nbsp;Cheng Zeng,&nbsp;Yue Qiu,&nbsp;Yuxin Wu,&nbsp;Xinlu Jia,&nbsp;Siqi Zhang,&nbsp;Chao Li,&nbsp;Wenjuan Zhang,&nbsp;Wenbing Zhang,&nbsp;Zhihua Chen","doi":"10.1002/cai2.70034","DOIUrl":"10.1002/cai2.70034","url":null,"abstract":"<p>DNA methylation is a crucial epigenetic regulatory mechanism that can modify chromatin structure, DNA conformation, DNA stability, and the interactions between DNA and proteins, thereby controlling gene expression. It has been shown to play a significant role in pathological processes such as fibrosis and tumorigenesis. DNA methyltransferases (DNMTs) are key players in this process. This study aims to investigate the role of DNMTs in the development of urinary system diseases, such as renal fibrosis and prostate cancer, revealing how they regulate gene expression by modulating DNA methylation levels, thereby significantly promoting the progression of these diseases. Additionally, this review explores their potential clinical applications as therapeutic targets, which may offer new research directions for understanding the pathogenesis and treatment of urinary system diseases in the future.</p>","PeriodicalId":100212,"journal":{"name":"Cancer Innovation","volume":"4 6","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12720420/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145822577","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}