Translational cancer research最新文献

Background: There is no conclusive evidence on whether neoadjuvant chemotherapy (NACT) is suitable for locally advanced cervical cancer (LACC). This study aimed to evaluate the efficacy and safety of NACT combined with concurrent chemoradiotherapy (CCRT) and CCRT alone in LACC. This evaluation aims to offer valuable insights for clinical diagnosis and treatment decisions.

Methods: A thorough investigation was performed across the CNKI, Medline, Cochrane Library, PubMed, and EMBASE records to search for studies that evaluated NACT in combination with CCRT, as well as CCRT alone, for individuals suffering from LACC. Subsequently, we computed the odds ratios (ORs) along with their respective 95% confidence intervals (CIs). Additionally, we considered the incidence of adverse events in our analysis.

Results: The review encompassed 12 eligible randomized controlled trials, comprising a total of 2,609 patients (Experiment: 1,313, Control: 1,296). NACT combined with chemoradiotherapy had higher complete response rate (CRR, OR =2.06, 95% CI: 1.27-3.34) and objective response rate (ORR, OR =2.41, 95% CI: 1.20-4.87), but there was no difference in disease control rate (DCR) and 3-year survival rate. However, leucopenia was more frequent (OR =2.37, 95% CI: 1.09-5.14), and there was no difference in other adverse reactions.

Conclusions: Compared with CCRT alone, combined NACT had a higher initial effect on individuals with LACC, rather than a sustained benefit. Taxol and platinum (TP) regimen may be a better option but more attention should be paid to leucopenia. Further prospective studies with larger sample sizes are needed for the development of therapy regimens for LACC.

Background: F-box protein 28 (FBXO28) plays a role in several malignancies; however, its association with gastric cancer (GC) remains uncertain. This study aimed to investigate the effects of FBXO28 on GC by bioinformatics analysis and molecular biology.

Methods: The expression of FBXO28 in GC was discovered. The probable roles of FBXO28 in the proliferation, migration, invasion, and apoptosis of GC cells were explored. To further study the possible mechanism, western blotting was conducted to evaluate whether FBXO28 was involved in the epithelial-mesenchymal transition (EMT) and the mitogen-activated protein kinase/extracellular signal-regulated kinase (MAPK/ERK) pathway. The GSE62254 dataset and 213 clinical samples were used to explore the connection between FBXO28 and the clinicopathological features of GC.

Results: Based on bioinformatics analysis, FBXO28 messenger RNA (mRNA) was found to be highly expressed in GC. However, compared with normal tissues, GC tissues had lower levels of FBXO28 expression. The cell experiments showed that FBXO28 played an anti-tumor role in GC cells. The pathway analysis results illustrated that FBXO28 could affect the EMT and the MAPK/ERK pathway. Furthermore, there was a correlation between FBXO28 and GC's clinicopathological features, and FBXO28 serves as an independent predictor of the prognosis.

Conclusions: FBXO28 played a tumor-suppressive role in GC cells and was related to the EMT process. Patients with GC with a better prognosis expressed higher levels of FBXO28.

Background: MicroRNAs (miRNAs) have been verified to be involved in various biological processes through regulating their target genes, and some previous studies have revealed the antitumour role of microRNA-374b-5p (miR-374b-5p) in several tumours. Therefore, the purpose of this study was to explore the functions and potential mechanisms of miR-374b-5p in osteosarcoma (OS) progression.

Methods: The differentially expressed gene miR-374b-5p was discovered in the dataset GSE65071 from the Gene Expression Omnibus (GEO) database via bioinformatics analysis, and its expression levels in OS tissues and cell lines were confirmed by RNA fluorescence in situ hybridization (FISH) staining and quantitative real-time polymerase chain reaction (qRT-PCR). OS cell proliferation ability was evaluated by Cell Counting Kit-8 (CCK-8) assay and colony formation assay, cell migration and invasion abilities were assessed by Transwell assays, and apoptosis was detected by flow cytometry. The underlying mechanisms of miR-374b-5p in regulating OS progression were explored by qRT-PCR, dual-luciferase reporter assay and western blotting. In vivo experiments, a nude mice xenograft tumour model was performed to evaluate the effects of miR-374b-5p on tumour growth and gene expression changes.

Results: In this study, miR-374b-5p expression was confirmed to be significantly down-regulated in OS, and miR-374b-5p overexpression could inhibit the proliferation, migration, and invasion abilities but promote apoptosis of OS cells. Mechanism studies revealed that miR-374b-5p suppressed the AKT pathway via negatively regulating the expression of phosphoinositide-dependent protein kinase 1 (PDPK1). Notably, PDPK1 were highly expressed in OS cell lines, as verified by qRT-PCR, and PDPK1-silencing considerably restrained OS progression. Moreover, the inhibitory effects of miR-374b-5p on OS progression were partially reversed by PDPK1 overexpression both in vitro and in vivo.

Conclusions: MiR-374b-5p was lowly expressed in OS, and its upregulation inhibited the progression of OS by directly targeting PDPK1 to affect the activity of the AKT pathway.

Background: Methyltransferase-like 14 (METTL14) is recognized as a key factor in the advancement and progression of breast cancer (BC). While its involvement in this context is acknowledged, many aspects of METTL14's functions remain unclear. We aimed to explore the function and potential mechanism of METTL14 in BC.

Methods: The level of METTL14 in BC cell lines and tissues was evaluated using quantitative real-time polymerase chain reaction, immunohistochemistry, and western blotting methods. The cell counting kit-8 (CCK-8) assay, wound healing assay, and transwell chamber assay were employed to investigate the biological functions of METTL14 in BC. The relationship between immune characteristics and METTL14 was analyzed using the Tumor Immune Estimation Resource (TIMER) and Tumor-Immune System Interaction Database (TISIDB). The Tumor Immune Dysfunction and Exclusion (TIDE) algorithm was used to predict immunotherapy response of BC patients. Multiplex immunofluorescence (mIF) was used to evaluate the expression of eight candidate markers of immune cell subsets and checkpoints in BC samples. Furthermore, a Kaplan-Meier survival analysis was performed to assess the prognostic significance of METTL14 in BC.

Results: Our study revealed a significant downregulation of METTL14 in BC tissues. The reduced expression of METTL14 was found to be associated with tumor progression, unfavorable recurrence-free survival (RFS) outcomes, and advanced tumor stages. Furthermore, METTL14 expression exhibited a positive correlation with the abundance of CD8⁺ T cells, CD4⁺ T cells, macrophages, and mast cells, while a negative correlation was observed with the abundance of regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), natural killer (NK) cells, and follicular helper T cells, as determined through immune analysis. METTL14 downregulation is associated with an immunosuppressive tumor microenvironment (TME), potentially through the upregulation of certain immunosuppressive factors. Results from mIF confirmed that low METTL14 expression correlates with high programmed death-1 (PD-1) expression. The analysis using the TIDE algorithm indicated that METTL14 expression was primarily negatively associated with the response to immunotherapy.

Conclusions: METTL14 demonstrates significant predictive value regarding prognosis in BC. The METTL14 has the potential to serve as a predictive biomarker and a promising target for immunotherapy.

Background: Large cell neuroendocrine carcinoma (LCNEC) is a rare and aggressive subtype of pulmonary malignancy, for which prognostic assessment remains challenging due to limited predictive models. This study aimed to develop and validate prognostic nomograms for estimating overall survival (OS) and cancer-specific survival (CSS) in individuals diagnosed with LCNEC.

Methods: A total of 613 patients confirmed to have LCNEC between 2010 and 2015 were selected from the Surveillance, Epidemiology and End Results (SEER) database. They were further divided into a training cohort and a validation cohort. The discrimination and calibration of the nomogram were evaluated using concordance index (C-index), area under time-dependent receiver operating characteristic curve [time-dependent area under the curve (AUC)], and calibration plots. The calibration curves were constructed to assess the consistency between predicted and observed outcomes. Decision curve analysis (DCA) was performed to evaluate the clinical utility of the nomograms across different probability threshold.

Results: Six variables were selected to establish the nomogram for LCNEC. The C-index (0.732 for the validation cohort) and the time-dependent AUC (>0.7) indicated satisfactory discriminative ability of the nomogram. The calibration plots showed favorable consistency between the prediction of the nomogram and actual observations in both the training and validation cohorts. Furthermore, DCA showed that the nomogram was clinically useful to recognize patients at high risk.

Conclusions: The prognostic nomograms developed in this study incorporate key clinical and pathological variables, including sex, radiotherapy, surgery, T stage, N stage, and brain metastasis status, to provide individualized estimates of OS and CSS in individuals with LCNEC. These models offer a practical tool for risk stratification and may support more personalized treatment planning in clinical practice.

Background: Voltage-dependent anion channels (VDACs) are mitochondrial outer membrane proteins regulating metabolism, apoptosis, and immune responses, but their clinical value in hepatocellular carcinoma (HCC) remains incomplete. This study aimed to clarify whether VDAC1 and VDAC2 serve as prognostic biomarkers and potential therapeutic targets in HCC by comprehensively analyzing their expression patterns, prognostic value, regulatory mechanisms, immune associations, and functional roles through multi-omics approaches and in vitro validation.

Methods: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) database (33 cancer types) were analyzed to evaluate VDAC1 and VDAC2 expression, diagnostic performance, and prognostic significance using receiver operating characteristic (ROC), Kaplan-Meier, and Cox regression, with nomogram construction for recurrence prediction. Validation was performed using Gene Expression Omnibus (GEO) database (GSE14520) and the Human Protein Atlas. Genetic and epigenetic regulation, including mutations, copy number variations, and promoter methylation, were assessed for prognostic impact via cBioPortal, Gene Set Cancer Analysis (GSCA), and UALCAN (an interactive TCGA-based analysis portal). Immune associations, including tumor-infiltrating cells and immune evasion potential, were examined using TIMER2.0, CIBERSORTx, and Tumor Immune Dysfunction and Exclusion (TIDE). Functional relevance was tested in Hep3B and PLC cells through Small interfering RNA (siRNA)-mediated knockdown, with assays of proliferation, apoptosis, Ferroptosis, migration, and epithelial-mesenchymal transition.

Results: VDAC1 and VDAC2 were significantly upregulated in HCC and independently predicted poorer overall survival. VDAC1 had a stronger prognostic impact in advanced-stage patients, while VDAC2 retained predictive value in early-stage tumors. Both accurately distinguished tumors from normal tissues. Multi-omics analyses revealed distinct regulation: VDAC1 was driven by copy number gain and promoter hypermethylation, whereas VDAC2 was largely independent of these alterations, suggesting post-transcriptional control. High expression correlated with immunosuppressive cell infiltration and elevated immune evasion scores, with immune context modulating prognostic effects. Functional experiments confirmed that silencing either genos inhibited cell proliferation, promoted apoptosis, reduced migration, and differentially affected ferroptosis.

Conclusions: VDAC1 and VDAC2 are prognostic biomarkers and therapeutic targets in HCC, with genetic and immune interactions jointly influencing outcomes, supporting their potential for patient risk stratification and targeted or immune-based therapies.

Background: Lung cancer has a high incidence rate, and immunotherapy is only effective for a subset of patients. This study aimed to develop a signature associated with immunotherapy response to accurately predict the prognosis of non-small cell lung cancer (NSCLC) patients and assess immunotherapy efficacy. Such efforts are crucial to address the therapeutic challenges faced by patients with advanced lung cancer.

Methods: Using weighted gene co-expression network analysis (WGCNA), we identified genes correlated with immunotherapy response. These genes were subsequently integrated with the data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) to formulate prognostic signatures. A total of 101 machine learning algorithms were employed to construct these prognostic signatures. Following this, we conducted an in-depth analysis of the prognostic signatures and investigated their associations with patient prognosis, tumor microenvironment (TME), and the efficacy of chemotherapeutic agents, targeted therapies, and immunotherapy.

Results: The constructed signature demonstrated a significant disparity in prognosis between high-risk and low-risk NSCLC patient groups. The prognostic capability of this signature was rigorously validated across various clinical subgroups and TCGA cohorts, and it emerged as an independent prognostic factor through multivariable analysis. To augment the precision of prognostic predictions, we developed a nomogram. Notably, the immune checkpoint inhibitor response prediction scores (IPS) were elevated in the low-risk group, indicating a potential benefit of immunotherapy for these patients. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to determine the expression levels of key risk-associated genes in the tissue samples, leading to the identification of Acyl-CoA synthetase medium chain family member 5 (ACSM5) as a promising therapeutic target in NSCLC.

Conclusions: Our signature, which is linked to immunotherapy response, aids in predicting the prognosis and immunotherapy outcomes of NSCLC patients, thereby offering valuable insights for their clinical management.

Interleukin-12 (IL-12) is a pleiotropic pro-inflammatory cytokine with potent antitumour activity and has been extensively explored as a candidate for cancer immunotherapy. However, its clinical development has been severely limited by the substantial systemic toxicities observed following systemic administration of recombinant IL-12. Nevertheless, the capacity of IL-12 to remodel the immunosuppressive tumour microenvironment (TME) by enhancing immune effector cell activation, proliferation, and infiltration, as well as by shifting suppressive immune cells toward a proinflammatory phenotype, underscores the need to engineer safe delivery strategies that confine cytokine activity to the tumour site. Herein, this review provides a broad and updated overview of diverse strategies for targeted IL-12 delivery to tumours. Specifically, we focus on immunocytokines, adoptive T-cell therapies, and biodegradable polymeric microspheres, while also briefly touching on protein-engineering and nanotechnology-based approaches. By reviewing their modes of action and comparing their benefits and challenges, we illustrate how modern engineering approaches have the potential to overcome the historical barriers to IL-12 therapy while preserving its potent and pleiotropic antitumour functions. Although numerous IL-12-based platforms have recently emerged, an integrative framework that connects advances across diverse engineering modalities has been lacking. Finally, we consider how combination strategies incorporating multiple therapeutic components may enable the safe deployment of IL-12 while fully realising its antitumour potential.

Background: Primary breast diffuse large B-cell lymphoma (PB-DLBCL) is a rare malignancy with limited population-level prognostic data. We aimed to characterize incidence trends, estimate dynamic conditional survival (CS), and develop a prognostic model for overall survival (OS) using Surveillance, Epidemiology, and End Results (SEER) data.

Methods: We identified 792 patients with PB-DLBCL from the SEER database (2000-2021). Age-adjusted incidence rates were calculated to assess trends over time. 10-year CS probabilities were estimated to evaluate dynamic survival patterns. The cohort was randomly divided into training (n=554) and validation (n=238) sets. Best subset regression (BSR) and stepwise backward Cox regression were applied to identify the most informative prognostic variables, which were incorporated into a CS-nomogram. Model performance was assessed using calibration plots, time-dependent receiver operating characteristic curves, concordance index (C-index), and decision curve analysis (DCA).

Results: The age-adjusted incidence of PB-DLBCL remained stable over two decades, with no significant trend [annual percent change (APC) =-0.16%]. CS analysis revealed that patients who survived the first post-diagnosis year had progressively improved long-term survival probabilities (10-year CS: 49% at diagnosis vs. 57% after 1-year survival; 73% for 5-year survivors). BSR with stepwise backward Cox regression identified age, Ann Arbor stage, and chemotherapy as the optimal prognostic factors. The CS-nomogram incorporating these variables effectively stratified patients into high- and low-risk groups, demonstrating robust discrimination and calibration in both training and validation cohorts. DCA confirmed the model's clinical utility in guiding individualized patient management.

Conclusions: PB-DLBCL showed stable incidence and dynamic improvement in survival among patients who surpassed early post-diagnosis milestones. Age, stage, and chemotherapy were key prognostic determinants. The CS-nomogram provided a practical, individualized tool for dynamic survival prediction and risk stratification, supporting personalized clinical decision-making in this rare lymphoma subtype.