Discover. Oncology最新文献

{"title":"Multi-omic discovery of SCG5 as a shared driver and prognostic biomarker in head-neck and non-small cell lung cancers.","authors":"Fenghui Zhao, Haining Wang, Tao Qin, Yize Wang, Huiyuan Yang, Honghai Wang, Mi Zhou","doi":"10.1007/s12672-026-05356-8","DOIUrl":"10.1007/s12672-026-05356-8","url":null,"abstract":"<p><strong>Background: </strong>Patients with head and neck squamous cell carcinoma (HNSC) face a high risk of developing non-small cell lung cancer (NSCLC). However, the shared molecular drivers linking these two malignancies remain poorly defined.</p><p><strong>Methods: </strong>We integrated TCGA and GEO datasets to identify shared differentially expressed genes (DEGs) between HNSC and NSCLC, subsequently evaluating their prognostic value, immune infiltration patterns (ssGSEA), and enriched pathways. Clinical validation of SCG5 protein expression was comprehensively performed using tissue microarrays (TMA) via immunohistochemistry. in vitro assays, including siRNA-mediated knockdown, CCK-8, colony formation, and Western blotting, were conducted in both HNSC (SCC-25) and NSCLC (A549) cell lines to ascertain its oncogenic functions and underlying molecular mechanisms.</p><p><strong>Results: </strong>SCG5 was identified as a consistently upregulated, independent predictor of poor survival in both cancers. IHC confirmed SCG5 protein overexpression, correlating with lymph node metastasis and advanced clinical stages. GSEA revealed that SCG5-associated genes were significantly enriched in focal adhesion and the PI3K/AKT signaling pathway in both HNSC and NSCLC. SCG5 expression correlated positively with tumor-infiltrating macrophages (P < 0.001) and with PDCD1LG2, HAVCR2 and SIGLEC15 (P < 0.05). SCG5 knockdown significantly suppressed cell proliferation and colony formation in both SCC-25 and A549 cells, concurrently attenuating PI3K and AKT phosphorylation.</p><p><strong>Conclusion: </strong>SCG5 is a novel shared oncogenic driver and prognostic biomarker for HNSC and NSCLC. Downregulation of SCG5 suppresses the growth of HNSC and NSCLC cells, potentially through modulating the PI3K/AKT signaling pathway, thereby presenting a potential therapeutic target for both malignancies.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"17 1","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13388605/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148535611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Researching the role of ubiquitination and macrophage activation-related genes in hepatocellular carcinoma through a systematic study based on gene expression profiling.","authors":"Chunsheng Zhang, Jianyang Peng, Zhicheng Weng, Weida Wu, Yuanzhen Lin","doi":"10.1007/s12672-026-05571-3","DOIUrl":"https://doi.org/10.1007/s12672-026-05571-3","url":null,"abstract":"<p><p>Hepatocellular carcinoma (HCC) remains a formidable global health challenge, particularly in developing nations, due to its asymptomatic nature in early stages and consequent late diagnosis. This study aims to identify novel biomarkers and therapeutic targets by focusing on Ubiquitin and Macrophage Activation-Related Genes (UMARGs), which play a crucial role in modulating the tumor microenvironment. Utilizing a comprehensive bioinformatics framework, we integrated transcriptomic data from TCGA and GEO databases with gene signatures from GeneCards. Our methodology included differential gene expression analysis, Cox regression modeling, and protein interaction networking to identify key prognostic determinants and their heterogeneity across HCC molecular subtypes. The analysis revealed two distinct HCC subtypes, Cluster A and Cluster B, each with unique gene expression profiles. Immune microenvironment heterogeneity was highlighted through CIBERSORT deconvolution, showing diverse distributions across 12 cellular subsets, notably activated T cells and macrophages.Survival analysis showed that high expression of HPX was associated with better Overall survival, while high expression of MMP9 was associated with worse Overall survival, and these trends were validated in an external GEO cohort. HPX and MMP9 may serve as candidate prognostic biomarkers for Hepatocellular carcinoma, but their Biological function and clinical application value still require further experimental investigation. Despite limitations, including the lack of experimental validation and reliance on retrospective data, this study provides valuable insights into gene expression dynamics and immune characteristics associated with HCC. These findings lay the groundwork for precision oncology paradigms, facilitating the translational trajectory of these targets to optimize clinical prognosis. Future research should focus on experimental validation and the development of targeted therapies based on these molecular insights. This study underscores the potential of UMARGs in advancing HCC treatment strategies and improving patient outcomes.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148548098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of adjuvant chemotherapy on survival in stage IIA colon cancer with partial bowel obstruction after propensity score matching.","authors":"In Jun Yang, Dong Ha Kim, Kyung-Ha Lee, Ji Yeon Kim","doi":"10.1007/s12672-026-05580-2","DOIUrl":"https://doi.org/10.1007/s12672-026-05580-2","url":null,"abstract":"<p><strong>Introduction: </strong>Obstruction in stage II colon cancer is a high-risk factor, but its definition remains unclear. The survival benefit of adjuvant chemotherapy (AC) in patients with partial obstruction has not been fully established. This study aimed to evaluate the oncologic implications of partial obstruction in stage IIA colon cancer and to examine whether AC was associated with improved survival.</p><p><strong>Patients and methods: </strong>We retrospectively analyzed 214 patients with stage IIA colon cancer who underwent radical resection between January 2012 and December 2020. Partial obstruction was defined using endoscopic passability, adequacy of bowel preparation, and radiological bowel dilatation. Patients were grouped into surgery only (SO) (n = 108) and surgery plus AC (SC, n = 106). To reduce treatment-selection bias, 1:1 propensity score matching was performed, resulting in 53 matched pairs. Primary endpoints were overall survival (OS) and disease-free survival (DFS), estimated using Kaplan-Meier analyses and Cox proportional hazards models.</p><p><strong>Results: </strong>Before matching, the SC group was younger and had higher rates of lymphatic, venous, and perineural invasion. In the matched cohort, 3-year disease-free survival was 92.1% in the SC group versus 81.4% in the SO group (log-rank p = 0.048), whereas 3-year OS was 98.1% versus 89.6%, respectively (p = 0.059). In multivariable Cox analysis of the matched cohort, adjuvant chemotherapy was not independently associated with improved OS (HR, 0.459; 95% CI 0.142-1.480; p = 0.193) or disease-free survival (HR, 0.492; 95% CI 0.206-1.174; p = 0.110). Most patients received capecitabine (72.6%), with a completion rate of 74.5%. A total of 10 grade 3-4 adverse events were recorded.</p><p><strong>Conclusions: </strong>AC was associated with more favorable Kaplan-Meier survival patterns in the matched cohort, particularly for disease-free survival, but an independent survival advantage was not confirmed after multivariable adjustment. These findings support cautious, individualized decision-making and prospective validation using a reproducible definition of partial bowel obstruction.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148535600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Therapeutic implications of peroxisome proliferator-activated receptors in non-small cell lung cancer.","authors":"Li Nie, Xinliang Zou, Huaxi Liu, Yan Peng, Jingyao Li, Tao Jing, Haidong Wang, Donglin Wang","doi":"10.1007/s12672-026-05599-5","DOIUrl":"https://doi.org/10.1007/s12672-026-05599-5","url":null,"abstract":"<p><p>Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 80-85% of cases. Despite therapeutic advances, drug resistance and suboptimal outcomes persist, underscoring the need for novel molecular targets. Peroxisome proliferator-activated receptors (PPARα, PPARβ/δ, PPARγ) are ligand-activated transcription factors that regulate lipid metabolism and inflammation. Their expression is dysregulated in NSCLC, but functional studies have yielded conflicting results: all three isoforms can exert either tumor-suppressive or tumor-promoting effects depending on cellular context, metabolic state, and genetic background. This context-dependent duality has created uncertainty in the field, even as the intersection of metabolism and anti-tumor immunity becomes increasingly recognized as a driver of NSCLC progression. PPARs sit at this intersection, integrating metabolic, inflammatory, and immune signals, which has renewed interest in their therapeutic potential. Clinically available PPAR agonists (e.g., fibrates, thiazolidinediones) are being investigated in exploratory combinations with immune checkpoint or targeted therapies, though their success may depend on biomarker-guided patient selection. This review critically discusses the isoform-specific functions and molecular mechanisms of PPARs in NSCLC, summarizes preclinical and clinical advances in PPAR-targeted strategies for prevention and treatment, and highlights key translational gaps. We aim to provide a conceptual framework for developing precision therapies that account for the context-dependent nature of PPAR signaling.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148535538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An evidence informed framework for artificial intelligence in rare breast cancers using small cohort validation synthetic data practices and clinical governance.","authors":"Bandar Saad Alshreef","doi":"10.1007/s12672-026-05573-1","DOIUrl":"10.1007/s12672-026-05573-1","url":null,"abstract":"<p><p>Rare breast cancers represent a clinically important but underrepresented group of malignancies. In this Perspective, rare breast cancers are considered within the broader rare cancer definition of an annual incidence below 6 cases per 100,000 persons, while also recognizing breast-specific rarity based on uncommon histology, molecular hallmarks, clinical presentation or sex-specific occurrence. These conditions are characterized by limited case numbers, biological heterogeneity, reduced clinical trial inclusion and fragmented evidence. These constraints challenge artificial intelligence (AI) development because many systems depend on large, balanced and externally validated datasets. AI may support diagnosis, histopathology, molecular interpretation, prognostic stratification and precision oncology decision support, but its use in rare breast cancers requires evidence standards adapted to small cohorts. This Perspective proposes an evidence-informed clinical governance framework organized around five domains: intended clinical use, small-cohort validation, synthetic data governance, human oversight and lifecycle monitoring. Its distinctive contribution is to translate general AI reporting and governance principles into rare breast cancer-specific safeguards, including objective data-quality checks, leakage prevention, uncertainty-aware validation, synthetic data plausibility scoring, pan-rare model reporting, patient involvement and post-deployment surveillance. Synthetic data may support development and simulation, but should not replace validation on real clinical cases. By linking small-cohort methodology with clinical oversight, regulatory alignment and lifecycle monitoring, the framework offers a practical roadmap for safe AI-enabled rare breast cancer precision oncology.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13400513/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148497236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integration of network toxicology, machine learning and single-cell sequencing identifies candidate molecular links between air pollutants and hepatocellular carcinoma.","authors":"Lin Yang, Xin Qing, Jiaxing Wang","doi":"10.1007/s12672-026-05569-x","DOIUrl":"https://doi.org/10.1007/s12672-026-05569-x","url":null,"abstract":"<p><strong>Background: </strong>Epidemiological studies link long-term air pollution to an increased risk of hepatocellular carcinoma (HCC), but the underlying toxicological targets remain poorly understood. We used an integrative computational framework to identify and prioritize candidate molecular mediators potentially linking pollutant-associated gene signatures with hepatocarcinogenesis.</p><p><strong>Methods: </strong>We retrieved pollutant-responsive genes associated with seven toxicants from the Comparative Toxicogenomics Database and intersected them with HCC-associated genes. We used protein-protein interaction (PPI) network analysis to identify hub nodes. An optimized machine learning pipeline (glmBoost and Ridge regression) was trained on GSE36376 and validated in three independent cohorts. We mapped gene program activity within the tumor microenvironment using single-cell RNA sequencing (scRNA-seq) and modeled perturbations with scTenifoldKnk. Finally, we assessed structural compatibility between pollutants and protein targets.</p><p><strong>Results: </strong>We identified 240 genes at the intersection of pollutant and HCC sets. Enrichment analysis highlighted innate immune signaling and chronic inflammation, specifically the IL-17, TNF, and NF-κB pathways. Hub nodes included IL6, TNF, MMP9, and AKT1. The machine learning model prioritized five candidate transcriptomic markers: FOS (AUC = 0.944), PARP1 (AUC = 0.929), MMP9 (AUC = 0.813), CCL5 (AUC = 0.747), and JUN (AUC = 0.733), all validated across cohorts. scRNA-seq module scoring showed the highest activity in T cells, monocytes, and macrophages. However, these data lack individual-level pollutant exposure documentation. In silico MMP9 knockout perturbed genes involved in angiogenesis and the extracellular matrix. Molecular docking suggested preliminary structural compatibility between toluene and MMP9 (-5.2 kcal/mol).</p><p><strong>Conclusion: </strong>This analysis outlines a potential \"pollutant-immune/inflammation-HCC\" framework and identifies five transcriptomic signatures for further validation. These findings support a hypothesis that air pollutant-associated molecular programs may be linked to HCC pathobiology and warrant experimental validation.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148497232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated multi-omics and SHAP analysis reveal the core mechanisms of metabolic reprogramming in lung adenocarcinoma.","authors":"Yuqing Huang, Chaojie Wang, Zhihao Zhang, Yandan Shi, Peng Lei","doi":"10.1007/s12672-026-05588-8","DOIUrl":"10.1007/s12672-026-05588-8","url":null,"abstract":"<p><p>Metabolic reprogramming is a pivotal hallmark of the malignant progression of lung adenocarcinoma (LUAD), yet its core regulatory genes and underlying molecular mechanisms remain largely elusive. In this study, we systematically deciphered the core regulatory network of LUAD metabolic reprogramming by integrating multi-omics analysis with the SHAP (SHapley Additive exPlanations) algorithm. Initially, LUAD transcriptomic and clinical data were acquired from the TCGA and GEO databases. Combined with 703 metabolic reprogramming-related genes retrieved from the Genecards database, 40 differentially expressed genes were identified via differential analysis, and key genes significantly impacting patient survival were subsequently isolated through prognostic analysis. Utilizing SHAP analysis to quantify the specific prognostic contributions of these genes, GPI, PFKP, and LDHB were recognized as the core regulatory genes. Single-cell sequencing analysis revealed that these three genes are highly expressed in the epithelial cells of LUAD tumor tissues and are closely associated with immune cell infiltration. In vitro cellular functional assays confirmed that silencing GPI, PFKP, or LDHB significantly restrained the proliferation and invasion capabilities of A549 cells, whilst regulating glucose metabolism and lactate production. Virtual knockout experiments further unraveled the downstream signaling pathway networks orchestrated by these three genes. Through combined multi-omics and SHAP analysis, this study elucidates, for the first time, the central roles of GPI, PFKP, and LDHB in the metabolic reprogramming of LUAD, providing a novel theoretical foundation for the development of diagnostic biomarkers and targeted therapeutics.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148497222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-omics and network toxicology prioritize ADAMTS13 as a candidate gene computationally linked to TDCPP targets in hepatocellular carcinoma.","authors":"Xin Liu, Dacai Gong, Tiantian Gou, Peng Chen","doi":"10.1007/s12672-026-05610-z","DOIUrl":"https://doi.org/10.1007/s12672-026-05610-z","url":null,"abstract":"<p><strong>Background: </strong>Tris(1,3-dichloro-2-propyl) phosphate (TDCPP), a widely used organophosphate flame retardant, has been increasingly recognized as a potential environmental risk factor for human cancers. However, its potential association with hepatocellular carcinoma (HCC) and the underlying molecular mechanisms remain largely unclear.</p><p><strong>Methods: </strong>An integrative network toxicology and multi-omics approach was employed to explore the potential computational link between TDCPP‑related targets and HCC transcriptomic changes. TDCPP-associated targets were collected from public databases and intersected with differentially expressed genes from The Cancer Genome Atlas (TCGA). Weighted gene co-expression network analysis (WGCNA) and machine learning algorithms were applied to identify candidate genes. Functional enrichment, immune infiltration, single-cell RNA sequencing, and molecular docking analyses were subsequently performed.</p><p><strong>Results: </strong>A total of six candidate genes were identified, among which ADAMTS13 exhibited strong discriminative performance in the predictive models. Functional analyses suggested that these genes may be involved in pathways related to extracellular matrix organization, immune regulation, and tumor microenvironment remodeling. Immune infiltration and single-cell analyses indicated a potential association between ADAMTS13 expression and tumor microenvironment characteristics. Molecular docking analysis further suggested a potential interaction between TDCPP and ADAMTS13 at the structural level.</p><p><strong>Conclusions: </strong>These findings suggest a computational association between TDCPP-related targets and HCC transcriptomic changes, with ADAMTS13 emerging as a computationally prioritized candidate gene for further experimental investigation. This study provides a hypothesis-generating framework for understanding possible molecular links between environmental contaminants and hepatocarcinogenesis, but does not establish causality or confirm actual TDCPP exposure in the analyzed patient cohorts.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148497217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prospective evaluation of UroCAD combined with ultrasonography for detecting bladder urothelial carcinoma in patients with hematuria.","authors":"Yunze Xiao, Xinghao Wang, Hankai Chen, Ke Liang, Xiaogang Zhang, Xiao Guo, Chenye Tang, Yuntao Wu","doi":"10.1007/s12672-026-05594-w","DOIUrl":"10.1007/s12672-026-05594-w","url":null,"abstract":"<p><strong>Background: </strong>Hematuria is a common clinical presentation of bladder cancer (BC). Accurate non-invasive diagnostic tools are needed to complement or reduce the reliance on cystoscopy. In this study, we investigated the diagnostic performance of urinary exfoliated-cell chromosomal copy-number aberration detection (UroCAD), a novel assay utilizing low-coverage whole-genome sequencing (LC-WGS) to detect chromosomal instability (CIN) in exfoliated urothelial cells. The evaluation included the use of UroCAD alone and in combination with ultrasonography.</p><p><strong>Methods: </strong>A consecutive series of 153 patients with hematuria was prospectively enrolled. Urine samples were subjected to genome-wide copy-number variation (CNV) profiling using UroCAD. The diagnostic performance of UroCAD and ultrasonography, individually and in combination, was assessed using histopathology as the reference standard. Statistical analyses included receiver operating characteristic (ROC) curves, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy.</p><p><strong>Results: </strong>Of the 153 enrolled patients, 151 (113 with pathologically confirmed BC and 38 with benign lesions) were included in the final analysis. UroCAD alone showed a specificity of 78.9% and a PPV of 90.1%, with an area under the ROC curve (AUC) of 0.84 (95% confidence interval [CI]: 0.77-0.91). Ultrasonography alone exhibited higher sensitivity than UroCAD (67.0% vs. 64.6%), but lower specificity (59.5%). The \"CIN OR ultrasound\" rule achieved the highest sensitivity (85.7%) and overall accuracy (75.8%), with an NPV of 51.5%. The \"CIN AND ultrasound\" rule yielded the highest specificity (91.9%) and PPV (94.4%). The CNV burden was strongly associated with tumor stage, with higher-stage tumors showing more frequent and pronounced genomic instability.</p><p><strong>Conclusions: </strong>UroCAD has potential as a non-invasive assay for BC detection. Combined with ultrasonography, it offers a dual-strategy approach: a high-sensitivity strategy (\"CIN OR ultrasound\") that may help identify patients warranting further evaluation, although its low NPV precludes safe exclusion of malignancy; and a high-specificity strategy (\"CIN AND ultrasound\") for confirmatory purposes. This synergistic strategy may aid in the risk stratification of patients with hematuria, although further prospective studies are required to validate its clinical utility. Trial registration ISRCTN Registry ISRCTN50547972 (http//www.isrctn.com/ISRCTN50547972). Registration date 27 April 2026.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148497300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Translational gaps and clinical readiness of artificial intelligence and multimodal imaging in breast cancer diagnostics.","authors":"Anas Shahin, Mohamad Faisal ALibrahim, Mohammad Ehsan Kawas, Reham Elawi","doi":"10.1007/s12672-026-05608-7","DOIUrl":"https://doi.org/10.1007/s12672-026-05608-7","url":null,"abstract":"<p><strong>Background: </strong>A persistent translational gap separates the high research-benchmark performance of artificial intelligence (AI) and advanced imaging in breast cancer from demonstrated real-world clinical utility. Most systems reporting accuracy above 95% on curated datasets have not been externally validated across diverse populations and imaging platforms.</p><p><strong>Purpose: </strong>We critically examine AI-driven diagnostics and advanced imaging modalities for breast cancer, focusing on the barriers-generalization failure, algorithmic bias, reproducibility, and workflow integration-that determine clinical readiness rather than on benchmark capability alone.</p><p><strong>Methods: </strong>We conducted a structured review of peer-reviewed literature (January 2015-March 2025) across PubMed, Scopus, IEEE Xplore, and Web of Science, combining breast cancer terms with AI, deep learning, vision transformers, digital breast tomosynthesis (DBT), contrast-enhanced mammography (CEM), MRI, and liquid biopsy. Study selection followed an explicit, PRISMA-style screening workflow; 127 of 312 identified records met predefined eligibility and quality criteria.</p><p><strong>Results: </strong>Reported benchmark performance is consistently optimistic relative to clinical performance: deep learning exceeds 95% accuracy and vision transformers report near-perfect classification on CBIS-DDSM, yet a reproducible 5-15% degradation follows deployment owing to distribution shift, scanner and vendor heterogeneity, and population differences. Among validated technologies, DBT raises cancer detection by 27% while lowering false positives; CEM increases sensitivity from 71.5% to 92.7% in dense breasts; and the Mirai risk model (AUC 0.76-0.81) outperforms traditional clinical tools. Liquid biopsy offers high-specificity molecular profiling but inadequate sensitivity (33%) for population screening. Critically, technical maturity is decoupled from validation depth and equity readiness-the dimensions that actually gate adoption.</p><p><strong>Conclusion: </strong>Realizing the potential of AI-augmented, risk-stratified screening requires multicenter prospective and multi-vendor external validation, fairness-aware design with subgroup reporting, transparent reproducibility, and adaptive regulation of continuously learning systems. We propose an operationally defined translational readiness framework that scores each technology along six dimensions, locating it on the continuum from research capability to equitable clinical deployment.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":" ","pages":""},"PeriodicalIF":2.8,"publicationDate":"2026-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148497254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}