Cancers最新文献

{"title":"Occurrence of Malignancies Other than Breast and Ovarian Cancer in Female Carriers of a <i>BRCA1/2</i> Germline Pathogenic Variant.","authors":"Annechien Stuursma, Bert van der Vegt, Lieke P V Berger, Maaike B C Ten Hoor, Jan C Oosterwijk, Marian J E Mourits, Geertruida H de Bock","doi":"10.3390/cancers17101687","DOIUrl":"10.3390/cancers17101687","url":null,"abstract":"<p><strong>Introduction: </strong>Previous studies have suggested an additional increased risk for types of malignancies other than breast and ovarian cancer for female <i>BRCA1/2</i> GPV carriers, but risk estimates vary widely. The aim of this study was to investigate if female <i>BRCA1/2</i> GPV carriers have an increased risk of malignancies other than breast and tubal/ovarian cancer at an early age.</p><p><strong>Methods: </strong>Prospectively collected data from female <i>BRCA1/2</i> GPV carriers in our hospital-based data/biobank were linked to the PALGA Dutch Pathology Database. Incidences of malignancies occurring before 60 years of age were compared to crude rates/100.000 person-years in the Netherlands, stratified by age and calendar time. Standardized incidence ratios (SIRs) were calculated with 95% confidence intervals (95%CIs).</p><p><strong>Results: </strong>In 1347 women, 82 malignancies other than breast and tubal/ovarian cancer were detected in patients under 60 years of age in 37,068 person-years. An increased risk of cancer in general (SIR:2.25, 95%CI:1.78-2.80, <i>p</i> < 0.001), head and neck cancer (SIR:3.17, 95%CI:1.03-7.39, <i>p</i> < 0.05), gastrointestinal cancer (SIR:1.96, 95%CI:1.14-3.13, <i>p</i> < 0.05), and female genital cancer (SIR:2.48, 95%CI:1.61-3.65, <i>p</i> < 0.001) was found.</p><p><strong>Conclusions: </strong>If confirmed in larger, prospective studies that include the role of bias and previous cancer treatment, awareness of the possible increased risks of head and neck, gastrointestinal, and female genital cancer may be used to tailor clinical guidelines for female <i>BRCA1/2</i> GPV carriers.</p>","PeriodicalId":9681,"journal":{"name":"Cancers","volume":"17 10","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109804/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interleukin-6 Is a Crucial Factor in Shaping the Inflammatory Tumor Microenvironment in Ovarian Cancer and Determining Its Hot or Cold Nature with Diagnostic and Prognostic Utilities.","authors":"Hina Amer, Katie L Flanagan, Nirmala C Kampan, Catherine Itsiopoulos, Clare L Scott, Apriliana E R Kartikasari, Magdalena Plebanski","doi":"10.3390/cancers17101691","DOIUrl":"10.3390/cancers17101691","url":null,"abstract":"<p><p>Ovarian cancer (OC) remains the leading cause of cancer-related deaths among women, often diagnosed at advanced stages due to the lack of effective early diagnostic procedures. To reduce the high mortality rates in OC, reliable biomarkers are urgently needed, especially to detect OC at its earliest stage, predict specific drug responses, and monitor patients. The cytokine interleukin-6 (IL6) is associated with low survival rates, treatment resistance, and recurrence. In this review, we summarize the role of IL6 in inflammation and how IL6 contributes to ovarian tumorigenesis within the tumor microenvironment, influencing whether the tumor is subsequently classified as \"hot\" or \"cold\". We further dissect the molecular and cellular mechanisms through which IL6 production and downstream signaling are regulated, to enhance our understanding of its involvement in OC development, as well as OC resistance to treatment. We highlight the potential of IL6 to be used as a reliable diagnostic biomarker to help detect OC at its earliest stage, and as a part of predictive and prognostic signatures to improve OC management. We further discuss ways to leverage artificial intelligence and machine learning to integrate IL6 into diverse biomarker-based strategies.</p>","PeriodicalId":9681,"journal":{"name":"Cancers","volume":"17 10","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109964/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144155999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergistic Effects of Cryotherapy and Radiotherapy in Glioblastoma Treatment: Evidence from a Murine Model.","authors":"Hélène Cebula, Chrystelle Po, Carole Mura, Benoit Lhermitte, Roberto Luigi Cazzato, Marion Rame, Clara Le Fèvre, Julien Todeschi, Charles-Henry Mallereau, Afshin Gangi, Georges Noël, Michel de Mathelin, François Proust, Hélène Burckel","doi":"10.3390/cancers17101692","DOIUrl":"10.3390/cancers17101692","url":null,"abstract":"<p><strong>Background/objectives: </strong>Cryotherapy involves the insertion of cryoprobes into tumors to induce cell destruction through exposure to extremely low temperatures over several minutes. This localized treatment modality may enhance the efficacy of established therapies, such as radiotherapy, particularly for glioblastomas. Our study aimed to provide proof-of-concept for the efficacy of combining cryotherapy and radiotherapy in the treatment of subcutaneous murine brain tumors (GL-261) in immunocompetent C57BL/6 mice.</p><p><strong>Methods: </strong>Tumor growth, survival and response were evaluated using MRI and histological analysis.</p><p><strong>Results: </strong>Partial cryotherapy alone showed no therapeutic efficacy. However, combining cryotherapy with radiotherapy significantly potentiated treatment outcomes. A statistically significant survival benefit was observed in the combined therapy group compared to control, cryotherapy and radiotherapy groups. Notably, 40% of mice receiving the combined treatment exhibited complete responses, with no detectable tumor cells on MRI or histological analysis. Furthermore, MRI-based monitoring revealed that the Apparent Diffusion Coefficient (ADC) map could predict complete response 14 days post-treatment, unlike caliper-based measurements.</p><p><strong>Conclusions: </strong>These findings suggest that cryotherapy may enhance radiotherapy efficacy, resulting in complete tumor regression in 4 out of 10 cases. ADC distribution may serve as a predictive marker for therapeutic response. However, given the limitations of the model, further studies in orthotopic models are needed to validate these findings and assess their clinical relevance.</p>","PeriodicalId":9681,"journal":{"name":"Cancers","volume":"17 10","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110222/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Validation and Post-Implementation Performance Monitoring of a Neural Network-Assisted Approach for Detecting Chronic Lymphocytic Leukemia Minimal Residual Disease by Flow Cytometry.","authors":"Jansen N Seheult, Gregory E Otteson, Matthew J Weybright, Michael M Timm, Wenchao Han, Dragan Jevremovic, Pedro Horna, Horatiu Olteanu, Min Shi","doi":"10.3390/cancers17101688","DOIUrl":"10.3390/cancers17101688","url":null,"abstract":"<p><p><b>Background</b>: Flow cytometric detection of minimal residual disease (MRD) in chronic lymphocytic leukemia (CLL) is complex, time-consuming, and subject to inter-operator variability. Deep neural networks (DNNs) offer potential for standardization and efficiency improvement, but require rigorous validation and monitoring for safe clinical implementation. <b>Methods</b>: We evaluated a DNN-assisted human-in-the-loop approach for CLL MRD detection. Initial validation included method comparison against manual analysis (n = 240), precision studies, and analytical sensitivity verification. Post-implementation monitoring comprised four components: daily electronic quality control, input data drift detection, error analysis, and attribute acceptance sampling. Laboratory efficiency was assessed through a timing study of 161 cases analyzed by five technologists. <b>Results</b>: Method comparison demonstrated 97.5% concordance with manual analysis for qualitative classification (sensitivity 100%, specificity 95%) and excellent correlation for quantitative assessment (r = 0.99, Deming slope = 0.99). Precision studies confirmed high repeatability and within-laboratory precision across multiple operators. Analytical sensitivity was verified at 0.002% MRD. Post-implementation monitoring identified 2.97% of cases (26/874) with input data drift, primarily high-burden CLL and non-CLL neoplasms. Error analysis showed the DNN alone achieved 97% sensitivity compared to human-in-the-loop-reviewed results, with 13 missed cases (1.5%) showing atypical immunophenotypes. Attribute acceptance sampling confirmed 98.8% of reported negative cases were true negatives. The DNN-assisted workflow reduced average analysis time by 60.3% compared to manual analysis (4.2 ± 2.3 vs. 10.5 ± 5.8 min). <b>Conclusions</b>: The implementation of a DNN-assisted approach for CLL MRD detection in a clinical laboratory provides diagnostic performance equivalent to expert manual analysis while substantially reducing analysis time. Comprehensive performance monitoring ensures ongoing safety and effectiveness in routine clinical practice. This approach provides a model for responsible AI integration in clinical laboratories, balancing automation benefits with expert oversight.</p>","PeriodicalId":9681,"journal":{"name":"Cancers","volume":"17 10","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110696/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Innate Immunity and Platelets: Unveiling Their Role in Chronic Pancreatitis and Pancreatic Cancer.","authors":"Juliane Blümke, Moritz Schameitat, Atul Verma, Celina Limbecker, Elise Arlt, Sonja M Kessler, Heike Kielstein, Sebastian Krug, Ivonne Bazwinsky-Wutschke, Monika Haemmerle","doi":"10.3390/cancers17101689","DOIUrl":"10.3390/cancers17101689","url":null,"abstract":"<p><p>Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal forms of cancer, characterized by a highly desmoplastic tumor microenvironment. One main risk factor is chronic pancreatitis (CP). Progression of CP to PDAC is greatly influenced by persistent inflammation promoting genomic instability, acinar-ductal metaplasia, and pancreatic intraepithelial neoplasia (PanIN) formation. Components of the extracellular matrix, including immune cells, can modulate this progression phase. This includes cells of the innate immune system, such as natural killer (NK) cells, macrophages, dendritic cells, mast cells, neutrophils, and myeloid-derived suppressor cells (MDSCs), either promoting or inhibiting tumor growth. On one hand, innate immune cells can trigger inflammatory responses that support tumor progression by releasing cytokines and growth factors, fostering tumor cell proliferation, invasion, and metastasis. On the other hand, they can also activate immune surveillance mechanisms, which can limit tumor development. For example, NK cells are cytotoxic innate lymphoid cells that are able to kill tumor cells, and active dendritic cells are crucial for a functioning anti-tumor immune response. In contrast, mast cells and MDSCs rather support a pro-tumorigenic tumor microenvironment that is additionally sustained by platelets. Once thought to play a role in hemostasis only, platelets are now recognized as key players in inflammation and cancer progression. By releasing cytokines, growth factors, and pro-angiogenic mediators, platelets help shape an immunosuppressive microenvironment that promotes fibrotic remodeling, tumor initiation, progression, metastasis, and immune evasion. Neutrophils and macrophages exist in different functional subtypes that can both act pro- and anti-tumorigenic. Understanding the complex interactions between innate immune cells, platelets, and early precursor lesions, as well as PDAC cells, is crucial for developing new therapeutic approaches that can harness the immune and potentially also the coagulation system to target and eliminate tumors, offering hope for improved patient outcomes.</p>","PeriodicalId":9681,"journal":{"name":"Cancers","volume":"17 10","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110028/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144155881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Breath Insights: Advancing Lung Cancer Early-Stage Detection Through AI Algorithms in Non-Invasive VOC Profiling Trials.","authors":"Bernardo S Raimundo, Pedro M Leitão, Manuel Vinhas, Maria V Pires, Laura B Quintas, Catarina Carvalheiro, Rita Barata, Joana Ip, Ricardo Coelho, Sofia Granadeiro, Tânia S Simões, João Gonçalves, Renato Baião, Carla Rocha, Sandra Alves, Paulo Fidalgo, Alípio Araújo, Cláudia Matos, Susana Simões, Paula Alves, Patrícia Garrido, Marcos Pantarotto, Luís Carreiro, Rogério Matos, Cristina Bárbara, Jorge Cruz, Nuno Gil, Fernando Luis-Ferreira, Pedro D Vaz","doi":"10.3390/cancers17101685","DOIUrl":"10.3390/cancers17101685","url":null,"abstract":"<p><p><i>Background:</i> Lung cancer (LC) is the leading cause of cancer-related deaths worldwide. Effective screening strategies for early diagnosis that could improve disease prognosis are lacking. Non-invasive breath analysis of volatile organic compounds (VOC) is a potential method for earlier LC detection. This study explores the association of VOC profiles with artificial intelligence (AI) to achieve a sensitive, specific, and fast method for LC detection. <i>Patients and methods:</i> Exhaled breath air samples were collected from 123 healthy individuals and 73 LC patients at two clinical sites. The enrolled patients had LC diagnosed with different stages. Breath samples were collected before undergoing any treatment, including surgery, and analyzed using gas chromatography coupled to ion-mobility spectrometry (GC-IMS). AI methods classified the overall chromatographic profiles. <i>Results:</i> GC-IMS is highly sensitive, yielding detailed chromatographic profiles. AI methods ranked the sets of exhaled breath profiles across both groups through training and validation steps, while qualitative information was deliberately not taking part nor influencing the results. The K-nearest neighbor (KNN) algorithm classified the groups with an accuracy of 90% (sensitivity = 87%, specificity = 92%). Narrowing the LC group to those only in early-stage IA, the accuracy was 90% (sensitivity = 90%, specificity = 93%). <i>Conclusions:</i> Evaluation of the global exhaled breath profiles using AI algorithms enabled LC detection and demonstrated that qualitative information may not be required, thus easing the frustration that many studies have experienced so far. The results show that this approach coupled with screening protocols may improve earlier detection of LC and hence its prognosis.</p>","PeriodicalId":9681,"journal":{"name":"Cancers","volume":"17 10","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110429/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revealing New Patterns in Colorectal Cancer Screening with a Focus on a Younger Patient Population.","authors":"Lynette Sequeira, Dhananjay Vaidya, Jianqiao Ma, Aarav Bansal, Shanshan Huang, Ashish Nimgaonkar, Ekta Gupta","doi":"10.3390/cancers17101686","DOIUrl":"10.3390/cancers17101686","url":null,"abstract":"<p><p>Colorectal cancer (CRC) continues to impart a significant mortality burden in the United States, with a growing number of cases affecting younger individuals. In this study, we set out to characterize predictors of missed colorectal cancer screening in a general and age-stratified population. <b>Methods</b>: We analyzed a patient population of over 85,000 patients who presented to a large outpatient network in the Baltimore, Maryland area and were due for CRC screening. We analyzed different characteristics, including race, occupation, relationship status, tobacco smoking status, and body mass index, of patients up to date and overdue on their CRC screening. The majority (over 99%) of our patient population was insured. We performed this analysis on the patient population as a whole and as an age-stratified patient population. <b>Results</b>: In our overall patient population, all of the aforementioned characteristics were significantly different between patients up to date and those overdue on CRC screening. Races with the highest up-to-date CRC screening proportion were Pacific Islanders, East Asian, and White patients, while Asian Indian patients had the lowest up-to-date percentage. Non-employed patients (including patients with disabilities and students), single patients, and current or past tobacco smokers were all found to have significantly lower percentages of up-to-date patients as compared to other groups within these categories. BMI was significantly lower in up-to-date patients. In our age-stratified analysis, younger patients had a significantly lower percentage of up-to-date patients. Notably, younger patients had a significantly higher proportion of patients electing for noninvasive screening modalities. <b>Conclusions</b>: These disparities in CRC screening warrant targeted interventions to minimize future risk of heightened mortality in certain patient populations.</p>","PeriodicalId":9681,"journal":{"name":"Cancers","volume":"17 10","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110369/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Developing Cancer Quality of Care Indicators to Quantify the Impact of a Global Destabilization of the Care System (COLLAT-COVID).","authors":"Nathalie Piazzon, Julie Haesebaert, Philippe Michel, Anne Sophie Belmont, Vahan Kepenekian, Gery Lamblin, Charlotte Costentin, Julien Péron","doi":"10.3390/cancers17101680","DOIUrl":"10.3390/cancers17101680","url":null,"abstract":"<p><strong>Background/objectives: </strong>The COVID-19 pandemic led to significant disruptions in healthcare systems, particularly impacting cancer care through delays in diagnoses and treatments. Quality indicators (QIs) are essential tools for monitoring healthcare performance, yet existing QIs may not be suited for crises. This study aimed to develop a set of hospital-based QIs tailored to assess the impact of care reorganization during health crises across four cancer types: breast cancer, hepatocellular carcinoma, gynecological cancers (excluding ovarian cancer), and peritoneal carcinomatosis.</p><p><strong>Methods: </strong>A multidisciplinary steering committee (SC) conducted a five-stage process, including a literature review, indicator selection, content validation via the RAND/UCLA method, final validation by the SC, and a pilot feasibility study. QIs were assessed based on clinical relevance, reproducibility, sensitivity to change, and feasibility. Expert panels evaluated and validated the indicators in two rounds of voting.</p><p><strong>Results: </strong>Among 150 initially identified QIs, 49 were validated: 12 for breast cancer, 11 for hepatocellular carcinoma, 8 for gynecological cancers, and 18 for peritoneal carcinomatosis. Most (92%) were process indicators, covering diagnosis, treatment, and care delays. Two common indicators were identified across all four cancers: multidisciplinary team meeting discussions and psychological support consultations.</p><p><strong>Conclusions: </strong>This study demonstrates the feasibility of developing crisis-responsive QIs to monitor cancer care during health system disruptions. Future work will focus on their real-time implementation, validation in international settings, and integration into healthcare policies to enhance crisis preparedness.</p>","PeriodicalId":9681,"journal":{"name":"Cancers","volume":"17 10","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High <i>KYNU</i> Expression Is Associated with Poor Prognosis, <i>KEAP1</i>/<i>STK11</i> Mutations, and Immunosuppressive Metabolism in Patient-Derived but Not Murine Lung Adenocarcinomas.","authors":"Ling Cai, Thomas J Rogers, Reza Mousavi Jafarabad, Hieu Vu, Chendong Yang, Nicole Novaresi, Ana Galán-Cobo, Luc Girard, Edwin J Ostrin, Johannes F Fahrmann, Jiyeon Kim, John V Heymach, Kathryn A O'Donnell, Guanghua Xiao, Yang Xie, Ralph J DeBerardinis, John D Minna","doi":"10.3390/cancers17101681","DOIUrl":"10.3390/cancers17101681","url":null,"abstract":"<p><p><b>Background/Objectives:</b> We aimed to discover genes with bimodal expression linked to patient outcomes, to reveal underlying oncogenotypes and identify new therapeutic insights in lung adenocarcinoma (LUAD). <b>Methods:</b> We performed meta-analysis to screen LUAD datasets for prognostic genes with bimodal expression patterns. Kynureninase (KYNU), a key enzyme in tryptophan catabolism, emerged as a top candidate. We then examined its relationship with LUAD mutations, metabolic alterations, immune microenvironment states, and expression patterns in human and mouse models using bulk and single-cell transcriptomics, metabolomics, and preclinical model datasets. Pan-cancer prognostic associations were also assessed. <b>Results:</b> Model-based clustering of <i>KYNU</i> expression outperformed median-based dichotomization in prognostic accuracy. <i>KYNU</i> was elevated in tumors with <i>KEAP1</i> and <i>STK11</i> co-mutations but remained a strong independent prognostic marker. Metabolomic analysis showed that <i>KYNU</i>-high tumors had increased anthranilic acid, a catalytic product, while maintaining stable kynurenine levels, suggesting a compensatory mechanism sustaining immunosuppressive signaling. Single-cell and bulk data showed <i>KYNU</i> expression was cancer cell-intrinsic in immune-cold tumors and myeloid-derived in immune-infiltrated tumors. In murine LUAD models, <i>Kynu</i> expression was predominantly immune-derived and uncoupled from Nrf2/Lkb1 signaling, indicating poor model fidelity. <i>KYNU</i>'s prognostic associations extended across cancer types, with poor outcomes in pancreatic and kidney cancers but favorable outcomes in melanoma, underscoring the need for lineage-specific considerations in therapy development. <b>Conclusions:</b><i>KYNU</i> is a robust prognostic biomarker and potential immunometabolic target in LUAD, especially in <i>STK11</i> and <i>KEAP1</i> co-mutated tumors. Its cancer cell-intrinsic expression and immunosuppressive metabolic phenotype offer translational potential, though species-specific expression patterns pose challenges for preclinical modeling.</p>","PeriodicalId":9681,"journal":{"name":"Cancers","volume":"17 10","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109616/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Steroid Profiling and Machine Learning Reveal Androgens as Candidate Biomarkers for Endometrial Cancer Diagnosis: A Case-Control Study.","authors":"Marija Gjorgoska, Angela E Taylor, Špela Smrkolj, Tea Lanišnik Rižner","doi":"10.3390/cancers17101679","DOIUrl":"10.3390/cancers17101679","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the diagnostic and prognostic potential of preoperative serum steroid levels in endometrial cancer (EC) alone and in combination with clinical parameters and biomarkers CA-125 and HE4.</p><p><strong>Methods: </strong>This single-center observational study included 62 patients with EC and 70 controls with benign uterine conditions who underwent surgery between June 2012 and February 2020. Preoperative serum levels of classic androgens, 11-oxyandrogens, glucocorticoids and mineralocorticoids were measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Machine learning was used to assess their diagnostic and prognostic value alone and combined with clinical parameters and tumor biomarkers.</p><p><strong>Results: </strong>Patients with EC had significantly higher serum levels of classic androgens (androstenedione, testosterone), 11-oxyandrogens (11β-hydroxy-androstenedione, 11β-hydroxy-testosterone) and glucocorticoids (17α-hydroxy-progesterone, 11-deoxycortisol) compared to controls. While individual steroids had limited diagnostic value, a multivariate model including classic androgens, CA-125, HE4, BMI and parity achieved an AUC 0.87, 79.1% sensitivity and 74.7% specificity in distinguishing EC from benign uterine condition. This model outperformed our previously published model based on CA-125, HE4 and BMI (AUC: 0.81, <i>p</i> < 0.0001). Prognostically, HE4 was the strongest marker for lymphovascular space invasion (LVSI) (AUC: 0.79) and deep myometrial invasion (MI) (AUC: 0.71). Among steroids, androstenedione was the most predictive of LVSI (AUC: 0.67), while 11β-hydroxy-testosterone was the strongest predictor of deep MI (AUC: 0.64).</p><p><strong>Conclusions: </strong>Patients with EC exhibit distinct steroid hormone profiles. While steroids alone offer modest diagnostic and prognostic value, integrating them into multivariate models improves diagnostic accuracy.</p>","PeriodicalId":9681,"journal":{"name":"Cancers","volume":"17 10","pages":""},"PeriodicalIF":4.5,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110686/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}