Discover. Oncology最新文献

{"title":"The network map of mucin 1 mediated signaling in cancer progression and immune modulation.","authors":"Akhina Palollathil, Shobha Dagamajalu, Mukhtar Ahmed, Manavalan Vijayakumar, Thottethodi Subrahmanya Keshava Prasad, Rajesh Raju","doi":"10.1007/s12672-025-03030-z","DOIUrl":"https://doi.org/10.1007/s12672-025-03030-z","url":null,"abstract":"<p><p>Mucin 1 (MUC1) is a type-I transmembrane glycoprotein, ranked as the second most promising cancer antigen for therapeutic development by the National Cancer Institute. Recently, MUC1 has gained significant attention as a therapeutic target in cancer immunotherapy. Thus, understanding MUC1-regulated signaling is essential for advancing therapeutic strategies. Since existing pathway repositories lack a comprehensive MUC1 signaling map, we constructed one by manually annotating experimentally validated signaling events from 115 articles following NetPath annotation criteria. Considering the topology of annotated molecules, a pathway map was developed using the PathVisio software. This pathway map is a valuable resource cataloguing 209 molecules and 690 signaling events, of which 395 events are unique. The catalogued reactions include 118 enzyme catalysis events, 133 molecular associations, 132 gene regulation events, 216 protein expressions, 49 activation/inhibition and 42 protein translocation events. MUC1 signaling pathway showed significant cross-talk with Wnt/β-catenin, NF-κB, PI3K-AKT, and MAPK signaling. The aberrant expression of MUC1 is associated with proliferation, metastasis, angiogenesis and invasion in various cancers, such as breast, lung, pancreatic, colon, oral, prostate, ovarian, and gastric cancers. Moreover, it also regulates the proliferation and function of immune cells, including myeloid-derived suppressor cells, tumour-associated macrophages, dendritic cells, CD4 + T-cells and CD8 + T-cells. This pathway map may serve as a valuable reference for understanding MUC1-driven oncogenic and immunomodulatory mechanisms, providing insights for developing novel therapeutic strategies for cancer treatment.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1404"},"PeriodicalIF":2.8,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144706700","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":"Shared blood gene signature in lung adenocarcinoma and microbial lung infections: a bioinformatic analysis and in silico validation.","authors":"Milad Sheervalilou, Mostafa Ghanei, Masoud Arabfard","doi":"10.1007/s12672-025-03272-x","DOIUrl":"https://doi.org/10.1007/s12672-025-03272-x","url":null,"abstract":"<p><strong>Background: </strong>Microbial lung infections may promote development of lung cancer through overlapping molecular mechanisms. This analysis aimed to identify a co-regulated peripheral blood gene signature in lung adenocarcinoma (LUAD) and microbial lung infections.</p><p><strong>Methods: </strong>A total of 403 peripheral blood transcriptomic profiles from five GEO test datasets-two LUAD (GSE39345, GSE103527) and three infection-related (GSE40012, GSE65682, GSE103119)-were analyzed using the limma package. Differentially expressed genes (DEGs) were defined by|log₂FC| >1 and p < 0.05. Two additional GEO datasets (GSE42826 and GSE42830), comprising 30 blood samples (16 LUAD, 14 lung infection), served as validation sets. Shared DEGs were subjected to KEGG and GO enrichment analyses. Protein-protein interaction (PPI) networks were constructed in Cytoscape, and the top 10 hub genes were identified. Expression data of hub genes were compared between validation LUAD and lung infection samples using the Mann-Whitney U test, followed by linear regression and Pearson correlation to confirm co-regulation. Immune cell infiltration was assessed using xCell deconvolution algorithm.</p><p><strong>Results: </strong>Ninety-three significant DEGs were shared between LUAD and infection datasets, including 40 upregulated and 53 downregulated genes. Eight hub genes showed consistent differential expression in both LUAD and lung infection: BCL6, CD163, S100A12 (upregulated); and FLT3LG, RPL13, RPL14, RPL22, RPS4X (downregulated), of which BCL6, S100A12, FLT3LG, RPL13, RPL14, RPL22 and RPS4X were significantly co-regulated (R² >0.8, p < 0.001) and correlated (p < 0.05). Immune profiling revealed that upregulated genes were associated with immunosuppressive cells such as Tregs and M2 macrophages, while downregulated genes were positively correlated with antitumor immune cell infiltration including CD8⁺ T cells and M1 macrophages. Consistent immune, stroma and microenvironment scores were observed between LUAD and lung infection.</p><p><strong>Conclusion: </strong>This analysis identified a blood-based 7-gene signature shared between LUAD and microbial lung infections, associated with immunosuppressive microenvironment features, suggesting a potential link between infection-driven inflammation and tumor-promoting immune modulation.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1403"},"PeriodicalIF":2.8,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144706690","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":"Integrating molecular docking and network pharmacology to reveal the molecular mechanisms of Anemarrhena asphodeloides in the treatment of non-small cell lung cancer.","authors":"Xianshun Xie, Yiling Jiang, Sumei Liu, Changjun Xie","doi":"10.1007/s12672-025-03178-8","DOIUrl":"https://doi.org/10.1007/s12672-025-03178-8","url":null,"abstract":"<p><p>Non-small cell lung cancer (NSCLC) is a major cause of global mortality. This study investigated Anemarrhena asphodeloides' potential mechanisms in treating NSCLC through network pharmacology and molecular docking, offering a theoretical basis for future experimental and clinical applications of traditional Chinese medicine in lung cancer therapy. Active compounds of Anemarrhena asphodeloides and their relevant targets were identified by network pharmacology methods. Key targets influenced by Anemarrhena asphodeloides in NSCLC were analyzed using the String 11.0 database to construct a PPI network. The binding abilities of these active ingredients to core targets were validated using molecular docking and dynamics simulations. The results of the network pharmacology analysis were validated by in vitro experiments. A total of 15 active compounds from Anemarrhena asphodeloides were identified, corresponding to 432 targets. Molecular docking and dynamics simulations confirmed that kaempferol, asperglaucide, and coumaroyltyramine exhibited strong binding interactions with key proteins such as AKT1, SRC, and HSP90AA1. Additionally, in vitro experiments confirmed that the active compounds of Anemarrhena asphodeloides reduced the expression of AKT1, SRC, and HSP90AA1, thereby inhibiting the malignant characteristics of human NSCLC cells. In conclusion, this study explored the pharmacological mechanisms of Anemarrhena asphodeloides in NSCLC, offering references for further research and supporting its clinical application in NSCLC treatment.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1399"},"PeriodicalIF":2.8,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144697775","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":"Application of Mendelian randomization and bioinformatic analysis to construct a prognostic model for thyroid cancer and perform pan-cancer analysis.","authors":"Zhenrun Zhan, Zhiyan Weng, Ke Zheng, Jiebin Lin, Sunjie Yan, Ximei Shen","doi":"10.1007/s12672-025-03222-7","DOIUrl":"https://doi.org/10.1007/s12672-025-03222-7","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to identify causal effects and potential molecular mechanisms of genes associated with THCA development.</p><p><strong>Methods: </strong>Bioinformatic analyses were performed to identify differentially expressed genes (DEGs) associated with THCA. Subsequently, Mendelian randomization (MR) analysis was conducted using large-scale eQTL data and THCA GWAS summary statistics to screen for candidate genes. The intersection of DEGs and MR-derived candidate genes was used to determine DEGs with potential causal associations with thyroid carcinogenesis. Functional enrichment analysis, pathway analysis, and immune cell infiltration profiling were performed. External datasets were used for validation. Additionally, prognostic modeling and pan-cancer analyses of the candidate genes were conducted.</p><p><strong>Results: </strong>IVW-based MR analysis revealed that elevated expression levels of ALOX15B [OR = 1.647, 95% CI (1.120-2.420), P < 0.05], TIAM1 [OR = 1.270, 95% CI (1.001-1.611), P < 0.05], and TMC6 [OR = 1.250, 95% CI (1.021-1.530), P < 0.05] were associated with an increased risk of THCA. Conversely, elevated expression of JUN [OR = 0.795, 95% CI (0.653-0.967), P < 0.05], PAPSS2 [OR = 0.779, 95% CI (0.608-1.000), P < 0.05], and RAP1GAP [OR = 0.895, 95% CI (0.810-0.989), P < 0.05] was associated with a reduced risk. Gene set enrichment analysis (GSEA) indicated that risk genes were enriched in proliferation- and metastasis-related pathways, such as extracellular matrix (ECM)-receptor interaction and cell adhesion molecules (CAMs). Findings from the training set were further validated experimentally and via external datasets. Additionally, candidate risk genes demonstrated associations with the development and progression of multiple tumor types.</p><p><strong>Conclusion: </strong>This study identified ALOX15B, TIAM1, and TMC6 as potential risk genes and JUN, PAPSS2, and RAP1GAP as protective genes in THCA. These genes may serve as promising biomarkers and therapeutic targets for THCA, offering novel insights into precision oncology.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1402"},"PeriodicalIF":2.8,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144697771","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":"Identification of key targets and exploration of therapeutic molecular mechanisms of natural compound tangeretin in osteosarcoma.","authors":"Ruoping Yanzhang, Zhaojie Yang, Xiangping Li, Yin Yu, Ruifang Shen, Huijun Zhang, Ying Wu, Junyan Teng","doi":"10.1007/s12672-025-03221-8","DOIUrl":"https://doi.org/10.1007/s12672-025-03221-8","url":null,"abstract":"<p><strong>Introduction: </strong>Osteosarcoma (OS) is an invasive and lethal malignancy showing a low 5 year survival rate, underscoring the need for identifying new therapeutic targets and their inhibitors to enhance prevention and treatment strategies.</p><p><strong>Methods: </strong>In this study, in vitro experiments including CCK-8 assay, anchorage-independent growth assays, and plate cloning assays were used to detect the anti-proliferation ability of natural compound tangeretin towards OS cells. An integrated approach was performed including WGCNA and network pharmacology to identify the key genes of tangeretin for the treatment of OS. Multigene diagnostic model, reverse transcription quantitative polymerase chain reaction (RT-qPCR) analysis along with molecular docking analysis were further conducted to validate the reliability of the targets obtained by bioinformatics methods. Single-cell and gene enrichment analyses were chosen to explore the mechanism of tangeretin in OS.</p><p><strong>Results: </strong>Hub genes identified by the bioinformatics strategy included ABCC1, AKR1C3, BACE1, and CA12. RT-qPCR validation and molecular docking analysis confirmed that ABCC1 and BACE1 were the most likely potential targets. A multigene diagnostic model for OS demonstrated moderate accuracy of the hub genes. Single-cell sequencing results indicated that these two hub targets were closely related to OS and provided more potential mechanisms for targeting OS.</p><p><strong>Conclusion: </strong>Our research highlights the therapeutic potential of the natural compound tangeretin and its antineoplastic mechanisms in OS. It offers new insights into the molecular mechanisms of tangeretin, paving the way for the development of effective OS treatments.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1401"},"PeriodicalIF":2.8,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144697773","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 network toxicology and bioinformatics reveal PFAS-driven prognostic biomarkers and molecular mechanisms in breast cancer: insights from transcriptome analysis and molecular docking.","authors":"Yingqiang Fu, Yiyang Liu, Ziqi Sui","doi":"10.1007/s12672-025-03084-z","DOIUrl":"https://doi.org/10.1007/s12672-025-03084-z","url":null,"abstract":"<p><strong>Background: </strong>Per- and polyfluoroalkyl substances (PFAS), pervasive environmental contaminants, are increasingly linked to breast cancer, yet their molecular mechanisms remain unclear. This study integrates network toxicology and bioinformatics to elucidate PFAS-associated pathways and prognostic biomarkers in breast cancer.</p><p><strong>Methods: </strong>Using the TCGA-BRCA dataset, we identified differentially expressed genes (DEGs) between normal and breast cancer tissues. We cross-referenced these genes with PFAS-related genes from the Comparative Toxicogenomics Database (CTD) to identify common targets. Enrichment analysis, network construction, and survival analysis were performed to elucidate the biological mechanisms and prognostic value. The CIBERSORT algorithm assessed immune cell infiltration, and molecular docking evaluated interactions between PFAS compounds and key genes.</p><p><strong>Results: </strong>We identified 141 common DEGs, significantly enriched in pathways related to cytokine activity, growth factor activity, and chemokine receptor binding. A PFAS-toxicity target-breast cancer network illustrated potential mechanistic pathways. Six key prognostic genes (MRPL13, LEF1, ATP7B, IFNG, SFRP1, DNMT3B) were identified, forming a risk model that stratified patients with significant differences in survival. Higher risk scores were associated with advanced stages, specific histological types, and hormone receptor statuses. Immune cell infiltration analysis revealed distinct profiles between high and low-risk groups, with high-risk patients exhibiting elevated activated T cells and macrophages. Molecular docking showed strong interactions between PFAS compounds (PFOS and PFDE) and DNMT3B, suggesting potential gene function disruptions.</p><p><strong>Conclusion: </strong>PFAS exposure is linked to altered gene expression, immune cell infiltration, and potential disruptions in key genes, contributing to breast cancer development and progression. These findings provide insights into potential therapeutic targets and underline the importance of addressing environmental factors in breast cancer management.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1400"},"PeriodicalIF":2.8,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144697774","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":"A 23-gene multi-omics signature predicts prognosis and treatment response in non-small cell lung cancer.","authors":"Yinxu Zhang, Siwang Wang, Xiaoyang Chen, Guangyu Zhang, Yuxi Wang, Xiaomei Liu","doi":"10.1007/s12672-025-03243-2","DOIUrl":"https://doi.org/10.1007/s12672-025-03243-2","url":null,"abstract":"","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1391"},"PeriodicalIF":2.8,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144689475","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":"Identification of cell adhesion related signature for molecular subtyping and prognostic prediction in acute myeloid leukemia.","authors":"Caifang Zhao, Xiang Weng, Wei He","doi":"10.1007/s12672-025-03208-5","DOIUrl":"https://doi.org/10.1007/s12672-025-03208-5","url":null,"abstract":"<p><strong>Background: </strong>Acute Myeloid Leukemia (AML) is a heterogeneous hematologic malignancy, characterized by complex molecular features that significantly impact prognosis and therapeutic responses. Despite considerable progress, effective risk stratification and predictive biomarkers for personalized therapies remain inadequate. The involvement of cell adhesion-related genes in the progression of AML has yet to be fully explored.</p><p><strong>Methods: </strong>AML patients were grouped into distinct molecular subtypes based on the expression patterns of cell adhesion-related genes. Enrichment analyses were subsequently performed to identify associated biological pathways. Differentially expressed genes were identified, and through Lasso regression and multivariate Cox regression, eight prognostically significant genes were selected. These genes were then used to construct a prognostic model, which was validated using external datasets. Furthermore, analyses of immune cell infiltration and drug sensitivity were conducted to evaluate the practical applicability of the model.</p><p><strong>Results: </strong>Two AML molecular subtypes were identified, each linked to distinct biological pathways. A prognostic model comprising 8 genes was developed, showing strong predictive power for overall survival and significant correlations with immune cell infiltration patterns. Drug sensitivity analyses identified potential therapeutic targets and candidate drugs, offering new directions for AML treatment.</p><p><strong>Conclusion: </strong>This study reveals novel AML subtypes driven by cell adhesion-related genes, providing insights into genetic heterogeneity, immune landscape, and therapeutic vulnerabilities. The developed prognostic model and identified therapeutic candidates offer valuable tools for prognosis prediction and personalized treatment strategies in AML.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1397"},"PeriodicalIF":2.8,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144697772","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":"Application of ultrasound in liver cancer from 2014 to 2024: bibliometric analysis and global trends.","authors":"Yaping Zhu, Yanyan Lu, Xinju Chen","doi":"10.1007/s12672-025-03177-9","DOIUrl":"https://doi.org/10.1007/s12672-025-03177-9","url":null,"abstract":"<p><strong>Background: </strong>Liver cancer remains one of the most prevalent and lethal malignancies worldwide, highlighting the need for effective diagnostic and monitoring strategies. Ultrasound plays a vital role in the early diagnosis, monitoring, and treatment of liver cancer. However, no bibliometric analysis has been conducted in this field before. This study aims to provide a comprehensive overview of the knowledge structure and research hotspots related to the application of ultrasound in liver cancer via bibliometric methodologies.</p><p><strong>Methods: </strong>A search was performed in the Web of Science Core Collection database for English literature studies on the application of ultrasound in liver cancer from 2014 to 2024. Bibliometric analysis tools including VOSviewer, CiteSpace, and R Studio, were utilized to analyze global trends and research hotspots in this field.</p><p><strong>Results: </strong>A total of 2501 eligible publications, including 2048 articles and 453 reviews, were analyzed. In the past decade, both the annual output of publications and the citation rates have rapidly increased. The majority of published articles on this topic were originated in China (n = 832, 33.27%), followed by the United States (n = 586, 23.43%), and Italy (n = 222, 8.88%). Researchers from the United States have demonstrated high productivity, prominence, and influence in this area of research. Additionally, Sun Yat-sen University published the most papers (n = 64), whereas the University of Michigan had the highest average citation value (value = 60.28) related to research on the application of ultrasound in liver cancer. Notably, Singal, Amit G from the USA was the author with both the highest number of published articles and the highest average citation value.</p><p><strong>Conclusion: </strong>In recent years, rapid advancements in ultrasound research for liver cancer have been reported. Increasing evidence has illustrated the crucial role of ultrasound in the early diagnosis and monitoring of liver cancer.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1395"},"PeriodicalIF":2.8,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144689478","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":"Mucinous carcinoma of the breast: epidemiological, clinical, and prognostic characteristics; a single-center experience.","authors":"Omar Hamdy, Mosab Shetiwy, Mahmoud M Saber, Basma A Eldawody, Shorouq A Kassab, Mariam H Nabih, Mostafa Abdelhakiem, Mona Zaki, Shaimaa M Yussif, Saleh Saleh, Khaled Abdelwahab","doi":"10.1007/s12672-025-03146-2","DOIUrl":"https://doi.org/10.1007/s12672-025-03146-2","url":null,"abstract":"<p><strong>Introduction: </strong>Mucinous (colloid) carcinoma (MC) of the breast typically affects postmenopausal and elderly women, with a more favorable prognosis compared to invasive breast carcinoma of no special type (IBC-NST). It is characterized by the presence of extracellular mucin and better outcomes. In our work, we presented a fifteen-year yield of a tertiary cancer center for MC.</p><p><strong>Methods: </strong>In this retrospective study, the data of the patients with MC from January 2009 to August 2023 were retrieved by searching the prospectively registered electronic database of the Oncology Center, Mansoura University. The patients' epidemiological, clinical, pathological, therapeutic, and oncological data were analyzed.</p><p><strong>Results: </strong>A total of 152 patients with the pathology of MC of the breast were included. The mean age of patients was 55.38 ± 13.82 years. Imaging revealed a unifocal lesion in 93 patients (61.2%). The mean mass size by imaging was 37.25 ± 20.21 mm. Positive lymph nodes (LNs) were detected by imaging in 71 (46.7%) patients. Pathological variants were either pure MC (42.1%) or mixed mucinous ductal carcinoma (57.9%). Luminal A was the most common subtype. Neoadjuvant therapy (NAT) was received by 34.8% of the patients. Mastectomy was done for 103 patients (68.2%). Axillary lymph node dissection was done for 122 patients (80.3%), and sentinel lymph node biopsy (SLNB) was done for 30 patients (19.7%). Adjuvant chemotherapy and radiotherapy were received by 65.1% and 60.8% of patients, respectively, while adjuvant hormonal therapy was received by 84.5%. The mean disease-free survival (DFS) was 43 ± 34.02 months, while the mean overall survival (OAS) was 44.5 ± 33.46 months. Seventeen patients (11.2%) were reported dead during the follow-up period.</p><p><strong>Conclusion: </strong>MC of the breast is a unique type of breast cancer. It may mimic benign lesions on imaging. The primary treatment for MC is mostly surgery, followed by adjuvant radiotherapy and systemic therapy. Comparing MC to IBC-NST, the former had a better prognosis and fewer lymphatic metastases, especially with pure MC, which shows a better prognosis.</p>","PeriodicalId":11148,"journal":{"name":"Discover. Oncology","volume":"16 1","pages":"1396"},"PeriodicalIF":2.8,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144697776","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}