Clinical & Translational Oncology最新文献

Background: This study aimed to develop and validate a hybrid deep learning (DL) model that integrates convolutional neural network (CNN) and vision transformer (ViT) architectures to predict distant metastasis (DM) in patients with non-small cell lung cancer (NSCLC) using ¹⁸F-FDG PET/CT images.

Methods: A retrospective analysis was conducted on a cohort of consecutively registered patients who were newly diagnosed and untreated for NSCLC. A total of 167 patients with available PET/CT images were included in the analysis. DL features were extracted using a combination of CNN and ViT architectures, followed by feature selection, model construction, and evaluation of model performance using the receiver operating characteristic (ROC) and the area under the curve (AUC).

Results: The ViT-based DL model exhibited strong predictive capabilities in both the training and validation cohorts, achieving AUCs of 0.824 and 0.830 for CT features, and 0.602 and 0.694 for PET features, respectively. Notably, the model that integrated both PET and CT features demonstrated a notable AUC of 0.882 in the validation cohort, outperforming models that utilized either PET or CT features alone. Furthermore, this model outperformed the CNN model (ResNet 50), which achieved an AUC of 0.752 [95% CI 0.613, 0.890], p < 0.05. Decision curve analysis further supported the efficacy of the ViT-based DL model.

Conclusion: The ViT-based DL developed in this study demonstrates considerable potential in predicting DM in patients with NSCLC, potentially informing the creation of personalized treatment strategies. Future validation through prospective studies with larger cohorts is necessary.

Background: Non-small cell lung cancer (NSCLC) is prevalent and often diagnosed at advanced stages. Immune checkpoint inhibitors targeting PD-1/PD-L1 pathways have transformed treatment, yet elderly patients remain underrepresented in clinical trials.

Methods: We conducted a systematic review and meta-analysis of randomized clinical trials (RCTs) comparing PD-1/PD-L1 inhibitors with placebo and/or chemotherapy in elderly patients with NSCLC. Overall survival (OS), Event-Free Survival (EFS) and OS for large studies were evaluated. Random-effects model with 95% confidence intervals were applied.

Results: Twelve RCTs with 3078 patients were included. PD-1/PD-L1 inhibitors significantly improved OS (HR 0.76; 95% CI 0.69-0.84; p < 0.001) and EFS (HR 0.67; 95% CI 0.54-0.83; p < 0.001). Large studies showed consistent benefit.

Conclusions: PD-1/PD-L1 inhibitors significantly improve clinical outcomes in elderly NSCLC patients compared to standard treatments.

Statins are widely recognized as cholesterol-lowering agents that reduce the risk of myocardial infarction and stroke, but emerging evidence highlights their broader therapeutic potential, particularly in oncology. By inhibiting the mevalonate pathway, statins disrupt the activation of small GTP-binding proteins such as Ras and Rho, key mediators of cancer cell proliferation, migration, and survival. This disruption triggers multiple antitumoral mechanisms, including cell cycle arrest, induction of apoptosis, suppression of angiogenesis, and inhibition of metastatic progression. Preclinical studies across diverse tumor models-most notably breast cancer-demonstrate robust anticancer activity. Clinical data now echo these findings, with observations suggesting that patients on statins, particularly hydrophilic agents like rosuvastatin, may achieve improved disease- free survival and reduced recurrence rates. Importantly, statins also confer cardioprotective effects, mitigating chemotherapy-induced cardiotoxicity through their antioxidant and anti-inflammatory properties-an advantage of significant relevance in long-term survivorship. Despite this promising dual benefit, statins have not yet been integrated into standard oncology practice. Rigorous clinical trials are required to define the patient subgroups most likely to benefit, optimize combination strategies, and establish safety in the oncologic setting. If validated, statins could represent a cost-effective, widely accessible adjunct to improve cancer outcomes while preserving cardiovascular health.

Background: Uveal melanoma (UM) is a rare cancer with an estimated annual incidence of 6 incidences per million people. About half of UM patients develop distant metastases, mainly to the liver. After metastasis, prognosis is poor, with median survival under 1 year and limited treatment options. Thus, earlier diagnostic methods for UM are a critical unmet need. The aim of this study was to evaluate the accuracy (sensitivity, specificity, and combined F1 score) of deep learning algorithms in the differential diagnosis of individuals with uveal melanoma.

Methods: We searched PubMed, Scopus, and Web of Science for studies comparing UM patients to healthy individuals or those with ocular nevi using AI diagnostic tools. AI performance metrics were extracted, with clinical or expert-based assessment as the reference standard. The study adhered to PRISMA guidelines.

Results: Five studies comprising 6388 patients (2981 UM, 2563 nevi, and 844 healthy) were included. The mean age of UM patients ranged from 58 to 63.2 years; for nevi, from 58 to 66 years. Pooled sensitivity was 89.0% (95% CI 88.6-89.5%) with no heterogeneity (I² = 0.0%, p = 0.9242); individual sensitivities ranged from 82.4 to 100.0%. Pooled specificity was 84.9% (95% CI 73.7-91.9%) with significant heterogeneity (I² = 72.3%, p = 0.006), ranging from 73.7 to 95.0%. The largest cohort had a specificity of 76.0% (95% CI 75.1-76.9%).

Conclusions: While fundus imaging is widely used in outpatient care, multimodal imaging remains limited to specialized clinics. Developing software to analyze fundus images could improve early, noninvasive UM detection and offer a cost-effective diagnostic tool.

Objective: To characterize gut microbiota alterations and metabolic changes in gastric cancer (GC) patients from high-altitude regions using 16S rDNA sequencing and untargeted metabolomics.

Methods: Fecal samples from 30 GC patients and 30 healthy controls in Qinghai Province were analyzed. Microbial diversity and composition were assessed via 16S rDNA sequencing, and metabolite profiles were determined using untargeted metabolomics. Correlations between significantly altered microbial taxa and metabolites were evaluated.

Results: Microbial diversity differed significantly between groups (P < 0.001). Proteobacteria abundance was higher in GC patients (P < 0.05). At the genus level, Prevotella_9, Streptococcus, and Lactobacillus showed significant differences (P < 0.05-P < 0.001). GC patients exhibited upregulation of desulfo-biotin, glycylproline, glycine, hydroxyhexanoic acid, tyramine, methanethiol oxidase, 5-aminopentanoic acid, citrulline, betaine, and formyl glutamic acid, and downregulation of cytidine, 5'-methylthioadenosine, trehalose, melezitose, lotaustralin, adenosine, creatinine, 5-methyluridine, raffinose, and galactitol. Proteobacteria correlated positively with desulfo-biotin, glycylproline, and glycine, while Lactobacillus correlated with several upregulated metabolites including tyramine and betaine (all P < 0.05). Cytidine correlated negatively with Proteobacteria, whereas creatinine and 5-methyluridine correlated positively with Prevotella_9.

Conclusion: GC patients in high-altitude regions display distinct gut microbiota and metabolite profiles, with notable microbe-metabolite associations. These findings suggest potential biomarkers and therapeutic targets for GC in plateau populations.

Background: Cytochrome P450 oxidoreductase (POR) plays a vital role in ferroptosis within lung cancer. A potential link exists between ferroptosis-related genes and immune cell activity. This research aimed to confirm whether POR influences lung cancer by modulating immune cells.

Methods: Genetic variants of the POR gene were identified from lung tissue expression quantitative trait loci (eQTL) data using single nucleotide polymorphisms (SNPs). A genome-wide study of 40,187 Europeans found variants linked to lung cancer. Mediation analysis on 731 immunophenotypes was done to assess their mediating effect on the POR gene-lung cancer relationship.

Results: This study identified four SNPs for further investigation. Mediation analysis suggested that three immune cell traits might mediate the effect of POR on lung cancer, with CD11c on granulocyte showing a clear mediation effect (β₁₂ = - 0.01, mediation proportion = 8.18%). There was a negative correlation between CD11c on granulocyte and the POR gene (β₁ = - 0.23), as well as a positive correlation between CD11c on granulocyte and lung cancer risk (β₂ = 0.05).

Conclusions: Our analysis revealed that increased expression in the POR gene was linked to a lower genetically predicted risk of lung cancer, with a significant mediation effect by the CD11c on granulocyte.

Cancer remains a leading cause of mortality in developed countries, with advancements in targeted therapies, antibody-drug conjugates (ADCs), and immunotherapy significantly improving patient survival. However, these treatments often result in cutaneous adverse effects (AEs), impacting the skin, mucosa, hair, and nails. This expert consensus statement provides a comprehensive overview of the mechanisms behind these skin toxicities, their clinical manifestations, and the importance of rapid diagnosis and treatment. The spectrum of skin toxicities ranges from mild reactions such as xerosis and pruritus to severe, potentially life-threatening conditions such as Stevens-Johnson syndrome/toxic epidermal necrolysis (SJS/TEN). This statement underlines the need for healthcare professionals to work in multidisciplinary teams, use standardized classification systems such as the Common Terminology Criteria for AEs (CTCAE) v5.0, educate patients on preventive measures, and establish clinical management guidelines to mitigate these AEs. By understanding the pathophysiological mechanisms and implementing effective management strategies such as photoprotection, gentle hygiene, emollients, prophylactic antibiotics, or specific hair and nail care, the quality of life for cancer patients can be significantly improved, ensuring continuity of oncologic treatment and improving overall survival.

Purpose: This study investigates the immunohistochemical expression of SLC48A1 and GLUT-1 in different grades of oral squamous cell carcinoma (OSCC) and explores their potential association with the development of tumor. OSCC is a heterogeneous malignancy characterized by increased glycolysis and glucose oxidation. Heme plays a crucial role in oxidative metabolism and ATP production via mitochondrial oxidative phosphorylation. SLC48A1 (solute carrier family 48 member 1) facilitates GLUT-1 trafficking, enhancing glucose uptake and lactate production, thereby promoting cancer cell migration and invasion. However, the relationship between SLC48A1, GLUT-1, and OSCC remains poorly understood.

Materials and methods: Seventy-two formalin-fixed, paraffin-embedded OSCC tissue samples and ten normal oral mucosa (NOM) were analyzed using immunohistochemistry to assess SLC48A1 and GLUT-1 expression. Staining intensity and distribution were correlated with histopathological grades. Statistical analysis was conducted to evaluate their association with tumor behavior.

Results: GLUT-1 expression showed strong expression in cases of well-differentiated OSCC, supporting its association with tumor. SLC48A1 expression was also seen to be markedly elevated in few cases of poorly differentiated OSCC.

Conclusion: While GLUT-1 expression correlates directly with OSCC, SLC48A1 expression was not seen to be uniformly distributed across the different histological grades. Through this study, it has been proven that both markers hold diagnostic significance and the results of the present study may serve as a future milestone for exploring these markers as potential therapeutic target for disrupting cancer metabolism as well as to correlate with the progression in different grades of OSCC.

Cancer is a disease marked by widespread molecular dysregulation, including alterations in gene expression, signaling pathways, and protein function. Among the critical regulators of protein function are post-translational modifications (PTMs), which fine-tune protein stability, activity, localization, and interactions. At the same time, more and more data has shown that mutations in parts of the splicing machinery, such as SF3B1, SRSF2, U2AF1, and ZRSR2, are common causes of different types of hematologic and solid tumors. Although the transcriptome implications of these mutations have been thoroughly delineated, their subsequent impacts on PTM regulation are still predominantly unexamined. This review seeks to address this deficiency by emphasizing the nascent connections between spliceosome mutations and the alteration of PTM landscapes in cancer. We suggest that modified splicing of PTM-related enzymes and substrates could significantly transform the cancer proteome, providing novel mechanistic insights and therapeutic prospects. We also look into how splicing-driven PTM changes, especially those that affect ubiquitination pathways and other important modification systems, affect the immune landscape of tumors. This gives us new information about how tumors with splicing mutations become more fit by changing the pathways that control the immune system and tumor surveillance.