Translational cancer research最新文献

{"title":"Engineering an arginine-nitric oxide circuit in <i>Escherichia coli</i> Nissle 1917 to remodel the tumor microenvironment for enhanced immunotherapy: a review.","authors":"Sujuan Li, Yuanhang Zhang, Pengfei Sun","doi":"10.21037/tcr-2026-1254","DOIUrl":"https://doi.org/10.21037/tcr-2026-1254","url":null,"abstract":"<p><p>Cancer immunotherapy, particularly immune checkpoint blockade (ICB), faces a major obstacle: the immunosuppressive tumor microenvironment (TME), characterized by abnormal vasculature, T cell exhaustion, and infiltration of suppressive immune cells including tumor-associated macrophages (TAMs), myeloid-derived suppressor cells (MDSCs), and regulatory T cells (Tregs). Nitric oxide (NO), a critical gasotransmitter, exhibits concentration-dependent dual roles in tumor biology. However, conventional NO delivery methods are limited by poor targeting specificity and systemic toxicity. Engineered <i>Escherichia coli</i> Nissle 1917 (EcN), with its century-long safety record, facultative anaerobic nature enabling tumor-selective colonization, and well-characterized genetic background, has emerged as a promising living therapeutic platform. This review systematically examines EcN engineered with a synthetic arginine-NO circuit (EcN-NO), in which deletion of argR eliminates feedback inhibition, while plasmid-encoded argAᶠᵐʳ, argG, argH, and <i>Bacillus subtilis</i> NO synthase (BsNOS) drive constitutive, sustained NO production after intratumoral colonization. We first provide a comparative analysis positioning EcN-NO within the historical landscape of engineered bacterial cancer therapy, including seminal work by Danino <i>et al.</i> (EcN tumor detection, 2015), Din <i>et al.</i> [synchronized lysis circuit (SLC), 2016], Chowdhury <i>et al.</i> (CD47 nanobody-mediated systemic antitumor immunity, 2019), and the framework of Gurbatri, Arpaia, and Danino [2022]. We then present a focused evidence-based analysis of EcN-NO's multidimensional mechanisms: tumor vascular normalization, dendritic cell (DC) recruitment and activation, reprogramming of immunosuppressive myeloid cells (TAM repolarization and MDSC reduction), direct cytotoxicity, and induction of immunogenic cell death (ICD). The review further details how this TME remodeling synergizes with αPD-L1 checkpoint blockade to expand functional CD8⁺ T cells, reverse T cell exhaustion, and establish long-term immunological memory across colorectal and breast cancer models. Finally, we outline unresolved translational questions regarding biosafety and biocontainment, optimal dosing and administration routes, good manufacturing practice (GMP) manufacturing, predictive biomarkers for patient stratification, and rational combination regimens. This review aims to provide a comprehensive theoretical foundation for overcoming immunotherapy resistance through engineered bacterial NO delivery.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"15 9","pages":"718"},"PeriodicalIF":2.1,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13657832/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184441","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":"Efficacy and safety of antibody-drug conjugates in advanced small cell lung cancer: a systematic review and single-arm meta-analysis of prospective clinical trials.","authors":"Peipei Zhang, Weixing Zhao, Jiayun Ma, Yuan Li, Huiyuan Peng, Jun Jiang","doi":"10.21037/tcr-2026-1433","DOIUrl":"https://doi.org/10.21037/tcr-2026-1433","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Antibody-drug conjugates (ADCs) are being evaluated in advanced small cell lung cancer (SCLC), but the available trials include different targets, constructs, doses, and treatment settings. We aimed to determine the overall range of reported activity and safety while clarifying whether the evidence supports a clinically uniform ADC class effect.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;PubMed/MEDLINE, Embase, Web of Science, the Cochrane Central Register of Controlled Trials (CENTRAL), clinical-trial registries, and major oncology conference proceedings were searched from inception through July 31, 2026. Eligibility was restricted to reports with sufficient methodological and outcome information available in English; study country, recruitment region, investigator nationality, and participant ethnicity were not exclusion criteria. Prospective phase I-III studies of ADC monotherapy in adults with advanced, extensive-stage, relapsed, or refractory SCLC were eligible; no comparator was required, and only the ADC arm of comparative trials contributed to the single-arm synthesis. Outcomes were objective response rate (ORR), disease control rate (DCR), duration of response (DOR), progression-free survival (PFS), overall survival (OS), and clinically important safety events. Randomized trials were assessed using the Cochrane risk-of-bias tool and non-comparative studies using the Methodological Index for Non-Randomized Studies (MINORS). Random-effects models were used, with subgroup and sensitivity analyses.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Eighteen prospective studies comprising 20 analytic cohorts and 2,246 patients were included: 12 phase I/Ib/I-II studies, three phase II studies, and three phase III studies. The pooled ORR was 34.38% [95% confidence interval (CI): 24.96-44.43%; I&lt;sup&gt;2&lt;/sup&gt;=95.3%], and the pooled DCR was 77.50% (95% CI: 67.98-85.81%; I&lt;sup&gt;2&lt;/sup&gt;=94.7%). The pooled median DOR, PFS, and OS were 4.99 months (95% CI: 4.24-5.86; I&lt;sup&gt;2&lt;/sup&gt;=77.2%), 4.36 months (95% CI: 3.87-4.92; I&lt;sup&gt;2&lt;/sup&gt;=84.8%), and 7.48 months (95% CI: 6.15-9.10; I&lt;sup&gt;2&lt;/sup&gt;=92.6%), respectively. Subgroup analyses by intervention and target indicated substantial clinical and statistical heterogeneity. Safety was summarized by individual agent, dose, and source population because adverse-event definitions and denominators were not sufficiently comparable; the predominant hematologic, gastrointestinal, pulmonary, and neurologic signals varied among products. Cochrane risk-of-bias judgments were predominantly low risk, with selected domains rated unclear or high risk. MINORS scores ranged from 11 to 15 of 16, with recurrent limitations in consecutive enrollment, blinded endpoint assessment, follow-up reporting, and prospective sample-size calculation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;ADC-based therapy shows antitumor activity in advanced SCLC, but substantial clinical and pharmacological heterogeneity limits the interpretation of poole","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"15 9","pages":"685"},"PeriodicalIF":2.1,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13657816/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184499","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":"Magnetic resonance imaging-based radiomics for predicting P53-mutated hepatocellular carcinoma: intratumoral and peritumoral analysis.","authors":"Jingfei Weng, Dinghua Yao, Qihu Zeng, Yuqing He, Chun Yang, Bin Yang","doi":"10.21037/tcr-2026-1579","DOIUrl":"https://doi.org/10.21037/tcr-2026-1579","url":null,"abstract":"<p><strong>Background: </strong>Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide, and TP53 mutation acts as a trunk mutation driving tumor progression. However, TP53 mutation status can currently be determined only by invasive liver biopsy. This study applies multiregional radiomics features from magnetic resonance imaging (MRI) to predict P53-mutated HCC and offers a non-invasive tool for identifying this invasive subtype.</p><p><strong>Methods: </strong>In this retrospective study, data from 320 patients who underwent preoperative MRI were analyzed and divided into a training cohort (TC; n=224) and a validation cohort (VC; n=96). Clinical risk factors were identified using stepwise regression to construct predictive models. We evaluated three machine learningclassifiers across six MRI sequences, and the least absolute shrinkage and selection operator method was applied to select the best IntraPeri fusion model from four regions (whole tumor, IntraPeri_9mm, IntraPeri_11mm, and IntraPeri_13mm) to establish a radiomics model. The predictive nomogram for P53-mutated HCC integrated these clinical predictors with discriminative radiomics features, and its performance was assessed using receiver operating characteristic analysis, calibration, and decision curves.</p><p><strong>Results: </strong>Among 320 patients (259 men and 61 women; mean age, 58.25±11.51 years), 183 had P53-mutated HCC and 137 had non-P53-mutated HCC. The largest tumor diameter (LTD), Edmondson-Steiner grade, and rim arterial phase hyperenhancement were identified as independent predictors of P53-mutated HCC. The ExtraTrees classifier based on radiomics features from the optimal MRI sequence [T1-weighted imaging-arterial phase (T1WI-AP)] within the IntraPeri_11mm region achieved strong predictive accuracy [area under the curve (AUC)_TC =0.805; AUC_VC =0.660]. Predictive nomogram integrating clinical and radiomics features demonstrated excellent performance in both the TC [AUC =0.815; 95% confidence interval (CI): 0.758-0.872] and VC (AUC =0.802; 95% CI: 0.713-0.890). Decision curve analysis further confirmed its clinical utility.</p><p><strong>Conclusions: </strong>Nomogram combining clinical model with IntraPeri_11mm radiomics may serve as effective predictors of preoperative P53 mutation status in HCC.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"15 9","pages":"709"},"PeriodicalIF":2.1,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13657831/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149183781","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":"A narrative review of barrier-matched engineering of macrophages for solid tumor immunotherapy: design logic, translational barriers and clinical outlook.","authors":"Jian Wu, Jiabao Dong, Yi Shen, Haoyun Yu, Miyang Xu, Jiangfeng Zhang, Wei Wei, Xiongfeng Li","doi":"10.21037/tcr-2026-1686","DOIUrl":"https://doi.org/10.21037/tcr-2026-1686","url":null,"abstract":"<p><strong>Background and objective: </strong>Macrophages are being investigated as adoptive cell therapies for solid tumors because they can migrate into tissues, phagocytose tumor cells, present antigen, secrete cytokines, and interact with stromal and other myeloid cells. However, their plasticity is also a liability. Once transferred into solid tumors, macrophages are exposed to hypoxia, metabolic stress, suppressive cytokines, and tumor-derived signals that may reduce phagocytosis, dampen inflammatory activation, and redirect them toward tumor-associated macrophage (TAM)-like, tumor-supportive phenotypes. This review examines engineered macrophage therapy through a barrier-matched framework.</p><p><strong>Methods: </strong>PubMed, Web of Science, Scopus, and ClinicalTrials.gov were initially searched from database inception to 24 December 2024, with a supplementary search update conducted through 21 July 2026. Search terms covered engineered macrophages, chimeric antigen receptor macrophages (CAR-M), solid tumors, the tumor microenvironment, phagocytosis checkpoints, macrophage backpacks, nanoparticle macrophages, and stem-cell-derived macrophages. Peer-reviewed original studies, clinical trial reports, high-quality reviews, and registered trials directly relevant to macrophage- or myeloid-cell-based cancer immunotherapy were selected. No formal risk-of-bias assessment or meta-analysis was performed.</p><p><strong>Key content and findings: </strong>Solid tumors impose five interacting barrier layers on macrophage therapy: physical barriers, metabolic barriers, immunosuppressive barriers, anti-phagocytic barriers, and phenotypic-plasticity barriers. These include restricted infiltration through dense extracellular matrix and abnormal vasculature, hypoxia, lactate accumulation, extracellular adenosine (eAdo)-A2A receptor (A2AR) signaling, suppressive tumor microenvironmental cues, do-not-eat-me checkpoints such as CD47-SIRPα, and TAM-like reprogramming after transfer. Engineering strategies have therefore shifted from simple cell transfer toward barrier-matched design. Some approaches add tumor-directed recognition, as in CAR-M or ligand-modified macrophages. Others aim to preserve inflammatory or phagocytic activity, deliver local payloads, attenuate inhibitory signaling, define scalable cell sources, or improve release and safety testing. The evidence base remains uneven. CAR-M has entered early clinical testing, whereas many nanoparticle-armed, backpack-based, stimulus-responsive, and genome-edited systems remain largely preclinical.</p><p><strong>Conclusions: </strong>Engineered macrophage therapy should be guided by the dominant barrier layer in a given solid tumor setting rather than by the number of modifications added to the cell product. Future development requires clearer links between engineering modules, barrier-adapted translational readouts, manufacturing feasibility, persistence, safety, and rational trial design.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"15 9","pages":"719"},"PeriodicalIF":2.1,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13657824/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184312","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":"A clinicopathological and hematological biomarker-based nomogram for overall survival in early-onset colorectal cancer: development, external validation, and translational implications.","authors":"Mingming Su, Changhe Xia, Zhihan Li, Bo Gao, Juan Zhang, Guanglin Wang, Guangquan An, Xiaoling Duan, Jitao Hu, Jiaxu Han, Chenhui Li","doi":"10.21037/tcr-2026-1568","DOIUrl":"https://doi.org/10.21037/tcr-2026-1568","url":null,"abstract":"<p><strong>Background: </strong>Early-onset colorectal cancer (EOCRC) is increasing globally, yet prognostic tools specifically tailored to younger patients remain limited. Molecular markers such as mismatch repair (MMR) status, although biologically important, are not routinely available in many clinical settings, creating a translational gap between laboratory advances and bedside practice. This study aimed to develop and externally validate a practical nomogram for predicting overall survival (OS) in EOCRC using widely accessible clinicopathological variables and routine hematological biomarkers, thereby bridging routine laboratory data to individualized risk stratification.</p><p><strong>Methods: </strong>This retrospective study included 410 EOCRC patients who underwent radical surgery (training cohort n=246, internal validation n=164). An independent external cohort (n=91) from a second tertiary center was used for validation. Candidate predictors included T/N stage, presenting symptoms, tumor markers [carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9)], and the systemic immune-inflammation index (SII)-a composite biomarker reflecting the balance between tumor-promoting inflammation and antitumor immunity. A nomogram was constructed using the least absolute shrinkage and selection operator (LASSO) and multivariable Cox regression. Model performance was assessed by discrimination [time-dependent area under the curve (AUC)], calibration, decision curve analysis (DCA), risk stratification, and head-to-head comparison with an anatomical-stage model and a clinicopathological model without inflammatory biomarkers.</p><p><strong>Results: </strong>Six predictors were retained in the final nomogram: T stage, N stage, changes in bowel habits, CEA, CA19-9, and SII. For 3-year OS, the AUC was 0.897 (training), 0.837 (internal validation), and 0.861 (external validation); for 5-year OS, the corresponding AUCs were 0.904, 0.873, and 0.868. The nomogram significantly outperformed the anatomical-stage model in all cohorts (all P<0.001) and provided incremental value over the clinicopathological model in both validation cohorts. Calibration curves showed good agreement between predicted and observed survival probabilities. DCA confirmed clinical net benefit across a range of threshold probabilities. The nomogram successfully stratified patients into high- and low-risk groups (log-rank P<0.001 in all three cohorts).</p><p><strong>Conclusions: </strong>This externally validated nomogram translates routinely available clinicopathological and hematological data into individualized OS predictions for EOCRC. By integrating inflammatory biomarkers such as SII, the model provides a translatable tool that may support risk-stratified surveillance and management, particularly in clinical settings where routine hematological and clinicopathological assessments are available but comprehensive molecular profiling is not.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"15 9","pages":"697"},"PeriodicalIF":2.1,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13657838/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184316","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":"Development and internal validation of machine learning models for predicting lymph node metastasis in cutaneous head and neck melanoma.","authors":"Bingyu Cheng, Jianqun Yu, Qiang Ji","doi":"10.21037/tcr-2026-1283","DOIUrl":"https://doi.org/10.21037/tcr-2026-1283","url":null,"abstract":"<p><strong>Background: </strong>Cutaneous head and neck melanoma (CHNM) carry substantial metastatic potential, yet reliable individualized prediction of lymph node metastasis (LNM) remains challenging for clinical practice. This study developed machine learning models to predict LNM risk in patients with CHNM using routine clinicopathological data, and compared model predictive performance to support clinical nodal risk stratification for sentinel lymph node biopsy decision-making.</p><p><strong>Methods: </strong>We enrolled 1,451 patients with CHNM. Among them, 242 (16.7%) had LNM, and 1,209 (83.3%) did not. We used one-hot encoding for categorical variables and Z-score standardization for continuous variables, respectively. The Boruta algorithm was used to select key factors. Seven machine learning models were built, with hyperparameters optimized by 5-fold cross-validation. We tested model performance using sensitivity, specificity, area under the curve (AUC), calibration curves, and decision curve analysis (DCA) eta. Finally, SHapley Additive exPlanations (SHAP) analysis was adopted to explain model results.</p><p><strong>Results: </strong>According to the Boruta algorithm, age, histological type, ulceration, mitotic rate and Breslow thickness were selected as independent predictive factors. Nodular melanoma (Histologic_X8721) emerged as a novel independent predictor, which has been rarely reported in CHNM. The extreme gradient boosting (XGBoost) showed good AUC of 0.748 [95% confidence interval (CI): 0.692-0.804], balanced performance (accuracy 0.686, sensitivity 0.658, specificity 0.691), and better clinical practicability in high-threshold DCA. KNN achieved the highest sensitivity (0.671), alongside a balanced accuracy of 0.687 and an AUC of 0.734 (95% CI: 0.672-0.795), with good calibration and net benefit in most situations. Although the MLP obtained the highest AUC value (0.755, 95% CI: 0.698-0.811), the model showed sub-optimal outcomes on calibration and decision-curve-analysis plots.</p><p><strong>Conclusions: </strong>These interpretable machine learning models may serve as an auxiliary reference for assessing LNM risk at initial diagnosis, supporting nodal metastasis risk stratification and clinical judgment of sentinel lymph node biopsy in CHNM patients.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"15 9","pages":"688"},"PeriodicalIF":2.1,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13657843/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184419","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":"LncRNA FGD5-AS1 promotes M2 polarization of tumor-associated macrophages to facilitate the malignant phenotype of non-small cell lung cancer cells.","authors":"Jing Wang, Hangui Wang, Zheng Song, Lijie Yang, Ning Wang","doi":"10.21037/tcr-2026-1646","DOIUrl":"https://doi.org/10.21037/tcr-2026-1646","url":null,"abstract":"<p><strong>Background: </strong>Tumor-associated macrophages (TAMs) take up a high proportion among immune cells in the tumor microenvironment (TME), and their M2- polarized phenotype has been implicated in promoting non-small cell lung cancer (NSCLC) development. Long non-coding RNA FGD5-AS1 (FGD5-AS1) is up-regulated within multiple tumor types, which has been shown to modulate both TAMs polarization and metabolic reprogramming. However, its exact mechanisms in NSCLC are largely unclear. This study aims to investigate whether FGD5-AS1 regulates M2 polarization of TAMs and thereby influences the malignant progression of NSCLC, as well as to explore the underlying molecular mechanisms.</p><p><strong>Methods: </strong>Human monocytic leukemia THP-1 cells were induced to differentiate into M0 macrophages <i>in vitro</i> and subsequently co-cultured with NSCLC cell lines (A549 and NCI-H1299) to mimic the TME and generate TAMs. The impacts of FGD5-AS1 silencing on M2 polarization of TAMs were assessed using flow cytometry and quantitative real-time polymerase chain reaction (qRT-PCR). To investigate the molecular mechanism underlying FGD5-AS1-mediated regulation of M2 polarization, Wnt5a was overexpressed via lentiviral transduction in FGD5-AS1-silenced M0 macrophages, followed by evaluation of Wnt5a expression and M2 polarization status using flow cytometry, qRT-PCR, and Western blot analysis. Finally, FGD5-AS1-silenced M0 macrophages were subjected to co-culture using A549 as well as NCI-H1299 cells, and functional consequences of FGD5-AS1- regulated M2-polarized TAMs on NSCLC cell growth, invasion, migration, alongside epithelial-mesenchymal transition (EMT) were evaluated using Cell Counting Kit-8 (CCK-8), scratch, Transwell, and Western blotting assays.</p><p><strong>Results: </strong>FGD5-AS1 showed remarkable up-regulation inside M2-polarized TAMs. FGD5-AS1 knockdown inhibited the M2 polarization of TAMs, as evidenced by down-regulated M2 macrophage marker levels including CD206, interleukin (IL)-10, transforming growth factor-beta (TGF-β), and CCL22, along with decreased Wnt5a protein levels. Mechanistically, overexpression of Wnt5a reversed the inhibitory effects of FGD5-AS1 silencing on M2 polarization, indicating that Wnt5a acts downstream of FGD5-AS1 in this regulatory axis. Notably, silencing FGD5-AS1 in M0 macrophages attenuated the proliferation, migration, invasion, and EMT of A549 and NCI-H1299 cells in the co-culture system, suggesting a functional role of FGD5-AS1-modulated TAMs in promoting malignant phenotypes of NSCLC cells.</p><p><strong>Conclusions: </strong>FGD5-AS1 may promote M2 polarization of TAMs through upregulation of Wnt5a, thereby contributing to the enhancement of malignant phenotypes in NSCLC cancer cells.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"15 9","pages":"693"},"PeriodicalIF":2.1,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13657827/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184426","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":"Prognostic value of neutrophil-to-lymphocyte ratio in nasopharyngeal carcinoma: a systematic review and meta-analysis of 30 cohorts through June 30, 2026.","authors":"Yunliang Lu, Biaoyou Chen, Jingfeng Ye, Xinyi Hu, Tingting Jiang, Zhe Zhang, Tingting Huang","doi":"10.21037/tcr-2026-1021","DOIUrl":"https://doi.org/10.21037/tcr-2026-1021","url":null,"abstract":"<p><strong>Background: </strong>Previous meta-analyses have linked an elevated pretreatment neutrophil-to-lymphocyte ratio (NLR) to poor outcomes in nasopharyngeal carcinoma (NPC), but they included few recent cohorts and often combined adjusted and unadjusted estimates. We updated the evidence base and evaluated the consistency and certainty of the associations between pretreatment NLR and survival outcomes.</p><p><strong>Methods: </strong>We systematically searched PubMed, Web of Science, Embase, the Cochrane Library, China National Knowledge Infrastructure (CNKI), and Wanfang Data from inception through June 30, 2026. Eligible reports were cohort studies of pathologically confirmed NPC that compared high versus low pretreatment NLR and reported multivariable-adjusted hazard ratios (HRs) for overall survival (OS), progression-free survival (PFS), distant metastasis-free survival (DMFS), or locoregional recurrence-free survival (LRFS). Two reviewers independently selected studies, extracted data, and assessed risk of bias using the Newcastle-Ottawa Scale (NOS). Random-effects models, prespecified subgroup analyses, leave-one-out analyses, assessment of small-study effects, and Grading of Recommendations Assessment, Development and Evaluation (GRADE) certainty assessment were used.</p><p><strong>Results: </strong>Thirty cohorts comprising 11,671 patients were included; NOS scores ranged from 7 to 9. Elevated pretreatment NLR was associated with inferior OS [27 cohorts; HR: 2.16, 95% confidence interval (CI): 1.76-2.66] and PFS (18 cohorts; HR: 1.70, 95% CI: 1.45-2.00). Furthermore, high NLR correlated with compromised DMFS (6 cohorts; HR: 1.61, 95% CI: 1.33-1.93) and LRFS (2 cohorts; HR: 4.82, 95% CI: 1.51-15.31). Heterogeneity was substantial for OS (I²=84%) and moderate for PFS (I²=57%). Egger's tests indicated funnel-plot asymmetry for OS (P<0.001), but not PFS (P=0.26). GRADE certainty was very low for OS and PFS and low for DMFS and LRFS.</p><p><strong>Conclusions: </strong>Elevated pretreatment NLR was associated with poorer survival outcomes in NPC. However, substantial heterogeneity, evidence of small-study effects for OS, and low to very low certainty of evidence preclude routine clinical implementation. Prospective validation using standardized sampling and cutoff methods is needed.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"15 9","pages":"710"},"PeriodicalIF":2.1,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13657807/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184444","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":"Global research trends in oncolytic virotherapy for sarcomas of bone and soft tissue (2000-2024): a bibliometric and visualization study.","authors":"Guangjian Bai, Jian Cui, Zhitao Han, Xingdan Pan, Pan Gao, Baoquan Xin, Qingwei Geng, Tielong Liu","doi":"10.21037/tcr-2026-1435","DOIUrl":"https://doi.org/10.21037/tcr-2026-1435","url":null,"abstract":"<p><strong>Background: </strong>Oncolytic viruses (OVs) represent a class of naturally occurring or genetically engineered viruses that selectively infect and lyse tumor cells while sparing normal tissues. Sarcomas of bone and soft tissue are malignant neoplasms originating from mesenchymal tissues, encompassing a wide spectrum of pathological subtypes. Current standard treatments primarily involve surgical resection, radiotherapy, and neoadjuvant chemotherapy, with oncolytic virotherapy emerging as a promising therapeutic approach in this field.</p><p><strong>Methods: </strong>The Web of Science Core Collection was comprehensively searched for literature on oncolytic virotherapy for bone and soft tissue sarcomas. After filtering, a total of 192 articles published between January 1, 2000, and December 31, 2024, were included in the final analysis. A bibliometric analysis was performed for the evaluation of multiple dimensions, including international collaboration, country and institutional contributions, publishing journals, authorship, keyword co-occurrence, reference patterns, citation counts, research topics, and publication chronology.</p><p><strong>Results: </strong>The most cited article was authored by E. Galanis <i>et al.</i>, published in <i>Gene Therapy</i> in 2005, and received 166 citations. This study investigated the intratumoral injection of ONYX-015 combined with the MAP (mitomycin C + adriamycin + cisplatin) chemotherapy regimen in sarcoma patients. The journal <i>Viruses</i> was featured most frequently among the included publications (n=9), while the Ohio State University was the most productive institution (n=16). The United States contributed the largest number of articles (n=100).</p><p><strong>Conclusions: </strong>The current study analyzed 192 publications concerning oncolytic virotherapy for bone and soft tissue sarcomas over the past 25 years. This information identifies recent research frontiers and hot directions, which would provide a reference for scholars studying oncolytic virotherapy for sarcomas of bone and soft tissue.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"15 9","pages":"677"},"PeriodicalIF":2.1,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13657805/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184481","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":"Radiomics-based machine learning models decipher heterogeneity of anoikis-related molecular subtypes for prognostic stratification in head and neck squamous cell carcinoma.","authors":"Linyong Wu, Dayou Wei, Wubiao Chen, Songhua Li, Zhendong Lu, Youwen Fu, Wenci Liu","doi":"10.21037/tcr-2026-1628","DOIUrl":"https://doi.org/10.21037/tcr-2026-1628","url":null,"abstract":"<p><strong>Background: </strong>Head and neck squamous cell carcinoma (HNSC) exhibits high molecular heterogeneity and frequent metastasis, which is strongly linked to anoikis dysregulation. This study aimed to investigate whether radiomics could offer a novel perspective for assessing the heterogeneity and risk stratification of HNSC associated with anoikis-related genes (ANRGs).</p><p><strong>Methods: </strong>A total of 118 HNSC patients with paired gene expression and imaging data were included. Radiomics features were extracted from computed tomography (CT) images using PyRadiomics. By employing consensus clustering methods, the heterogeneity of ANRGs-related HNSC was identified into different subtypes, and multi-machine learning model combinations were constructed based on radiomics features to predict the molecular subtypes. An ANRGs-related radiomics prognostic model was constructed to assess the association between subtypes and clinical outcomes.</p><p><strong>Results: </strong>Three subtypes were identified via consensus clustering of 31 prognostic ANRG expression profiles: C1, C2, and C3. Compared to other subtypes, C1 exhibited significantly worse overall survival and distinct immune infiltration levels. Of the multi-combination machine learning models, 71% demonstrated robust generalization in predicting C1 [areas under the curve (AUC) >0.75). The least absolute shrinkage and selection operator-random forest combined model achieved optimal performance, with an AUC of 0.86. The ANRGs-associated radiomics prognostic model showed significant prognostic value and was closely linked to pathways involving enhanced tumor invasiveness and immunosuppressive microenvironment.</p><p><strong>Conclusions: </strong>This study demonstrated that radiomics enables stratified prediction of ANRGs-associated HNSC heterogeneity while providing molecular annotation and prognostic evaluation for ANRGs-related radiomics features, highlighting its translational value in precision oncology.</p>","PeriodicalId":23216,"journal":{"name":"Translational cancer research","volume":"15 9","pages":"711"},"PeriodicalIF":2.1,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13657819/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184493","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}