Cancer Biotherapy and Radiopharmaceuticals最新文献

Colorectal cancer (CRC) remains a significant factor contributing to the morbidity and mortality rates linked with cancer throughout the world, especially in its stages of progression. Increasingly attractive therapeutic options include immune modulation combined with preoperative chemotherapy and radiation therapy (CRT). Recent studies have revealed that the protein serine peptidase inhibitor Kazal type 4 (SPINK4), which is abundantly expressed in gastrointestinal tract tissues, plays a role in immune evasion and treatment resistance in cancers. This meta-analysis aims to assess the relationship between SPINK4 expression levels and the therapeutic effectiveness of radiolabeled immune modulators in patients with advanced CRC who are undergoing preoperative chemotherapy and radiation treatment. The degree of SPINK4 expression and a lower objective response to radiolabeled immune modulators showed a statistically significant link. Conversely, patients with low SPINK4 expression have more favorable treatment responses and ongoing clinical improvement following CRT. High SpINK4 expression can act as a negative prognostic biomarker for radiolabeled immune control in advanced CRC.

Background: Chemotherapy sensitivity in renal carcinoma may be influenced by renal ischemia-reperfusion injury (RIRI). This study elucidates the underlying mechanism by investigating the regulatory role of MYDGF. Methods: The public dataset was downloaded, and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were used to analyze functional and pathway enrichment of genes in the most significant modules. MitoTracker Green and MitoSOX were used to assess mitochondrial activity and superoxide production in oxygen-glucose deprivation/reoxygenation (OGD/R)-treated renal proximal tubular epithelial cells (RPTECs), with or without MYDGF treatment. Reactive oxygen species production and apoptosis were further analyzed through flow cytometry. A mouse model of RIRI was established and treated with MYDGF, followed by kidney evaluation after 24 h. Histological damage was assessed using hematoxylin-eosin and Masson staining in both RIRI mice and IR-induced patients with AKI. Immunohistochemistry and quantitative real-time polymerase chain reaction were performed to evaluate MYDGF, BCL2, and BAX expression levels in renal tissues. Results: A total of 557 differentially expressed genes were identified. GO and KEGG analyses revealed significant enrichment in oxidative phosphorylation and apoptosis pathways, both of which are relevant to chemosensitivity. MYDGF treatment significantly inhibited apoptosis, enhanced mitochondrial function, and reduced superoxide production in OGD/R-treated RPTECs. In vivo, MYDGF reduced tubular apoptosis and protected against kidney injury, as shown by TUNEL and Masson staining. Notably, MYDGF increased BCL2 and decreased BAX expression both in vitro and in vivo, suggesting an antiapoptotic shift. These changes may contribute not only to protection from RIRI but also to increased susceptibility of damaged renal cells to chemotherapy-induced apoptosis by maintaining mitochondrial integrity. Conclusions: Regulation of apoptotic signaling by MYDGF attenuates ischemia-reperfusion injury and improves chemotherapy outcomes in advanced renal carcinoma.

Objective: This study explored the role of monocarboxylate transporter 1 (MCT1) in nasopharyngeal carcinoma (NPC) metastasis and its regulation via DNA methyltransferase 3B (DNMT3B)-mediated methylation, to identify therapeutic targets for NPC. Methods: MCT1/DNMT3B expression was analyzed in NPC (n = 30) and normal tissues (n = 30) using quantitative polymerase chain reaction (qPCR) and immunohistochemistry. DNMT3B overexpression plasmids were transfected into NPC cells to assess MCT1 expression and promoter methylation via bisulfite sequencing PCR. Luciferase and chromatin immunoprecipitation (ChIP) assays identified DNMT3B-MCT1 promoter interactions. Migration/invasion assays and Western blot evaluated functional impacts of MCT1 silencing on metastasis-related pathways. Bioinformatic validation utilized GEO datasets. Results: MCT1 mRNA/protein levels were significantly elevated in NPC versus normal tissues (***p < 0.001), whereas DNMT3B was downregulated. DNMT3B overexpression reduced MCT1 expression (*p < 0.05) and increased MCT1 promoter methylation (**p < 0.01). Luciferase assays revealed that DNMT3B suppressed wild-type MCT1 promoter activity, dependent on an 80 bp CpG island (**p < 0.01). ChIP confirmed DNMT3B enrichment at hypermethylated MCT1 promoter regions (**p < 0.01). MCT1 silencing inhibited NPC cell migration/invasion (*p < 0.05) and downregulated p-AKT, p-mTOR, and p-NFκB (*p < 0.05). High MCT1 correlated with Epstein-Barr virus (EBV)-associated EBNA1BP2 (**p < 0.01), but not PD-L1 markers. DNMT3B inversely correlated with MCT1 (*p < 0.05) and was upregulated in advanced-stage NPC (Stage III + IV vs. I + II, ***p < 0.001), indicating stage-specific epigenetic dysregulation. Conclusion: MCT1 promotes NPC metastasis via NF-κB and PI3K/AKT/mTOR pathways, regulated by DNMT3B-driven promoter methylation. The MCT1-DNMT3B axis, linked to EBV-associated metabolic reprogramming, represents a prognostic biomarker and therapeutic target for advanced NPC.

Objective: This study elucidated the role of the forkhead box E1 (FOXE1)-laminin γ2 (LAMC2) signaling axis in promoting brain metastasis (BM) of lung cancer and evaluated its potential as a therapeutic target to enhance the efficacy of preoperative chemoradiotherapy (CRT). Methods: Bioinformatics analysis of the GSE126548 dataset revealed a significant association between elevated FOXE1 expression and BM in lung cancer patients. Functional in vitro assays-including real-time polymerase chain reaction, Western blotting, migration, invasion, and endothelial permeability assays-were conducted in lung cancer cells and human umbilical vein endothelial cells exposed to tumor-conditioned media. In addition, in vivo xenograft and BM mouse models were established to assess the impact of FOXE1 on tumor growth, metastatic potential, and treatment responsiveness. Results: FOXE1 knockdown significantly inhibited lung cancer cell proliferation, migration, invasion, and epithelial-mesenchymal transition. Mechanistically, LAMC2 was identified as a downstream effector of FOXE1, with rescue experiments confirming that the FOXE1-LAMC2 axis plays a central role in driving tumor progression and brain metastatic potential. Notably, FOXE1 silencing enhanced sensitivity to CRT in preclinical models. Conclusions: FOXE1 promotes lung cancer progression and BM by upregulating LAMC2. Targeting the FOXE1-LAMC2 pathway may improve the efficacy of preoperative CRT and offers a promising strategy for therapeutic intervention in lung cancer patients at high risk of BM.

Background: Lung combined large-cell neuroendocrine carcinoma (CoLCNEC) refers to lung regions exhibiting both the features of large-cell neuroendocrine carcinoma (LCNEC) and the defined components of nonsmall cell lung cancer (NSCLC), with a relatively high mitotic rate. Diagnosing and predicting the prognosis of CoLCNEC are challenging. This study explored spatial transcriptomic expression patterns and identified crucial genes. Methods: We utilized a sample from a CoLCNEC patient containing three distinct components, namely, LCNEC, adenocarcinoma, and squamous cell carcinoma, with the former being predominant. Spatial transcriptomics (ST) technology, which employs the 10× Genomics Visium formalin-fixed paraffin-embedded ST kit, was applied along with high-throughput sequencing to obtain gene expression information and spatial locations for each spot. Subsequent analysis included differentially gene expression and functional enrichment. Finally, immunohistochemistry was employed to validate the marker protein structural maintenance of chromosomes 1A (SMC1A). Then, SMC1A was overexpressed and silenced in NCI-H661 and LTEP-a-2 cells, and the migration and invasion ability of the cells were detected by scratch assay and Transwell, respectively. The role of SMC1A in cancer cell cycle was detected by Real-time Reverse Transcription-PCR(RT-qPCR), Western blot, and flow cytometry, the apoptosis was detected by flow cytometry. Results: The results revealed that tumor tissue regions had higher unique molecular identifiers and gene counts than nontumor regions did. Unsupervised clustering identified four clusters, revealing the uniform distribution of unique transcripts, which were mapped onto slices to display apparent spatial separation. Differentially gene expression analysis revealed genes highly expressed in cancer cells. Further analysis of different regions revealed distinct cellular subgroups enriched through differentially gene expression analysis in various pathways, such as the cell cycle and DNA replication. Finally, SMC1A was chosen as a candidate gene, and immunohistochemistry confirmed its elevated expression in tumor regions. In addition, compared with oe-NC, oe-SMC1A can significantly promote the migration, invasion and G1/S phase transition of lung cancer cells, and promote the inhibition of apoptosis of cancer cells, while sh-SMC1A is completely opposite. Conclusions: In the tumor region of CoLCNEC, SMC1A is significantly upregulated. Moreover, silencing SMC1A effectively inhibits lung cancer cell invasion, migration, and G1/S phase transition, while promoting apoptosis. These findings indicate that SMC1A has the potential to be a new therapeutic target for CoLCNEC treatment.

Background: Accurate and noninvasive breast cancer grading and therapy monitoring remain critical challenges in oncology. Traditional methods often rely on invasive histopathological assessments or imaging-only techniques, which may not fully capture the molecular and morphological intricacies of tumor response. Method: This article presents a novel, noninvasive framework for breast cancer analysis and therapy monitoring that combines two parallel mechanisms: (1) a dual-stream convolutional neural network (CNN) processing high-intensity ultrasound images, and (2) a biomarker-aware CNN stream utilizing patient-specific breast cancer biomarkers, including carbohydrate antigen 15-3, carcinoembryonic antigen, and human epidermal growth factor receptor 2 levels. The imaging stream extracts spatial and morphological features, while the biomarker stream encodes quantitative molecular indicators, enabling a multimodal understanding of tumor characteristics. The outputs from both streams are fused to predict the cancer grade (G1-G3) with high reliability. Results: Experimental evaluation on a cohort of pre- and postchemotherapy patients demonstrated the effectiveness of the proposed approach, achieving an overall grading accuracy of 97.8%, with an area under the curve of 0.981 for malignancy classification. The model also enables quantitative post-therapy analysis, revealing an average tumor response improvement of 41.3% across the test set, as measured by predicted regression in grade and changes in biomarker-imaging correlation. Conclusions: This dual-parallel artificial intelligence strategy offers a promising noninvasive alternative to traditional histopathological and imaging-alone methods, supporting real-time cancer monitoring and personalized treatment evaluation. The integration of high-resolution imaging with biomolecular data significantly enhances diagnostic depth, paving the way for intelligent, patient-specific breast cancer management.

Background: This study investigated the expression characteristics of WD repeat domain 35 (WDR35) in lung adenocarcinoma (LUAD) and its association with chemotherapy sensitivity and prognosis. Methods: Differentially expressed genes were analyzed in combination with Random Forest and Support Vector Machine algorithms to identify key genes associated with chemotherapy sensitivity. The expression differences of the core gene at both transcriptomic and proteomic levels were then experimentally validated using real-world LUAD samples. Drug sensitivity analysis was conducted using the Genomics of Drug Sensitivity in Cancer database to evaluate the correlation between the core gene and the IC₅₀ values of various chemotherapeutic agents. Gene Set Enrichment Analysis (GSEA) was used to explore the potential mechanisms involved. Finally, Kaplan-Meier survival analysis and stratified analysis by tumor stage and lymph node status were performed to assess the prognostic value of the core gene. Results: WDR35 as a core gene associated with chemotherapy sensitivity and highly expressed in normal lung tissue compared with tumor tissue, which was further validated at both the qPCR and proteomic levels. Clinical correlation analysis indicated that WDR35 expression is significantly associated with tumor size, lymph node metastasis, and tumor stage. Further analysis revealed that patients with high WDR35 expression were more likely to achieve partial or complete response to initial chemotherapy. Drug sensitivity prediction analysis demonstrated that high WDR35 expression was significantly correlated with increased sensitivity to various anticancer drugs. GSEA pathway enrichment analysis suggested that WDR35 may enhance chemotherapy sensitivity by regulating stress response and metabolic pathways. Survival analysis indicated that high WDR35 expression was associated with better overall survival and disease-specific survival. Conclusions: Our study reveals that WDR35 is closely associated with chemotherapy sensitivity and prognosis in lung adenocarcinoma.

Background: Understanding T cell exhaustion (TEX)-related molecular characteristics can provide novel insights into treatment response prediction. This study developed a TEX-based prognostic model to predict survival outcomes and therapy responses in kidney renal clear cell carcinoma (KIRC) patients. Methods: The authors analyzed 518 KIRC patients from The cancer genome atlas (TCGA), identifying TEX-related genes via gene set variation analysis and weighted correlation network analysis. Survival random forest and Least Absolute Shrinkage and Selection Operator-Cox analyses selected eight key genes to construct a TEX risk model. Functional analyses explored TEX-related pathways and immune infiltration. The IMvigor210 dataset assessed immunotherapy response, whereas the Genomics of Drug Sensitivity in Cancer (GDSC) database predicted chemotherapy sensitivity. Single-cell RNA sequencing and quantitative real-time polymerase chain reaction validated a key TEX gene. Results: The TEX risk model demonstrated strong prognostic performance, effectively stratifying KIRC patients into high-risk (HR) and low-risk (LR) groups with significant differences in overall survival. Gene set enrichment analysis results revealed that TEX-related pathways were enriched in tumor proliferation, migration, and immune regulation. Immune cell infiltration analysis indicated that the TEX HR group exhibited distinct immune microenvironment characteristics, including increased expression of specific immune checkpoints. The model effectively predicted clinical responses to immunotherapy, with patients in the TEX HR group showing poorer immunotherapy efficacy. In addition, drug sensitivity analysis based on the GDSC database suggested that TEX features could influence chemotherapy response, highlighting potential therapeutic vulnerabilities. Experimental validation confirmed the expression pattern of a key TEX gene in KIRC samples. Conclusion: Their TEX risk model could effectively predict patient outcomes and responses to immunotherapy and chemotherapy, supporting its potential clinical utility in personalized treatment strategies.

Nonsmall cell lung cancer (NSCLC), which constitutes 85%-90% of lung cancer (LC) cases, is among the most frequently diagnosed malignancies. Peroxisome proliferator-activated receptor γ coactivator 1 α (PPARGC1A, also known as PGC-1α) has emerged as a major modulator of mitochondrial formation and energy expenditure, and serves critical functions in a range of malignancies. Nevertheless, its clinicopathological significance and biological function in the development of NSCLC remain obscure. This investigation revealed that PGC-1α expression exhibited elevated levels in LC. Moreover, enhanced PGC-1α expression augmented the oncogenic potential of NSCLC cells, whereas the downregulation of PGC-1α inhibited the proliferative and migrative capability and suppressed tumor growth in vivo. Mechanistically, PGC-1α interacted with forkhead box protein M1 (FOXM1), a commonly known transcription factor, and enhanced its transcriptional activation of downstream target mucin-1 (MUC1). The ectopic expression of MUC1 could reverse the inhibitory impact of PGC-1α depletion on the proliferation of NSCLC cells. Overall, the data suggested that targeting PGC-1α suppresses NSCLC progression through the FOXM1/MUC1 pathway and potentially offers a novel therapeutic approach for NSCLC treatment.

Lung cancer continues to be a primary contributor to cancer-related deaths globally, and multidrug resistance (MDR) poses a significant obstacle in its management. Traditional Chinese medicines (TCMs), recognized for their comprehensive therapeutic strategies and low incidence of adverse effects, have garnered attention due to their capacity to mitigate MDR in cancer cells. Nevertheless, deciphering the precise mechanisms through which TCMs reverse MDR in lung cancer presents a substantial scientific challenge. The objective of this review is to examine prevalent manifestations of MDR in lung cancer and underscore recent advancements in understanding how TCMs might surmount this form of resistance. The review begins by investigating the unique characteristics of TCMs and their pivotal function in reversing MDR in lung cancer. Subsequently, it explores various forms of MDR in lung cancer, such as aberrant expression of cell membrane transport proteins, dysregulation of intracellular enzyme systems, disrupted apoptosis, and heightened cellular repair mechanisms, emphasizing their detrimental impact on lung cancer treatment outcomes. Central to this review is a thorough analysis of the intricate mechanisms by which TCMs counteract MDR, along with an assessment of their efficacy in lung cancer therapy. Based on this analysis, the review offers insights into potential future research directions for utilizing TCMs to overcome MDR. This review seeks to provide a thorough examination of the role of TCMs in reversing MDR in lung cancer and to stimulate additional research into their clinical applications.