Journal of Cancer最新文献

Aquaporins (AQPs) are a subgroup of small transmembrane transporters that are distributed in various types of tissues, including the lung, kidney, heart and central nervous system. It is evident that respiratory diseases represent a significant global health concern, with a considerable number of deaths occurring worldwide. Recent researches have demonstrated that AQPs play a pivotal role in respiratory diseases, including chronic obstructive pulmonary disease (COPD), asthma, acute respiratory distress syndrome (ARDS), and particularly non-small cell lung cancer (NSCLC). In the context of NSCLC, the overexpression of AQP1, AQP3, AQP4, and AQP5 has been demonstrated to facilitate tumor angiogenesis, as well as the proliferation, migration, and invasiveness of tumor cells. This review concisely explores the role of AQP family on respiratory diseases, to assess their clinical and translational significance for understanding molecular pathogenesis. However, the potential translation of AQPs biomarkers into clinical applications is promising and the understanding of the precise mechanisms influencing respiratory diseases is still ongoing. Addressing the challenges and outlining the future perspectives in AQPs development is essential for clinical progress in a concise manner.

Purpose: Preoperative assessment of axillary lymph node (ALN) status is essential for breast cancer treatment planning. This study prospectively analyzed risk factors for ALN metastasis by comparing high-resolution computed tomography (HRCT) imaging with pathology and developed a nomogram to aid in diagnosis. Methods: From April 2023 to May 2024, breast cancer patients confirmed by pathology participated in the study. All had chest HRCT before surgery, and ALN samples were anatomically matched to HRCT imaging and pathology. The least absolute shrinkage and selection operator (LASSO) regression helped refine metastasis features, and a nomogram was constructed using the final selected features determined by multivariate logistic regression. The nomogram's performance was evaluated with concordance index (C-index), calibration plot, and decision curve analysis, with internal validation through bootstrapping. Results: A total of 302 ALN from 98 patients were included in this study. The predictors included in the nomogram encompassed the mean CT value, short diameter, border, and shape of ALN, as well as the Ki-67 status and histological grade of the primary tumor. The model exhibited satisfactory discrimination, with a C-index of 0.869 (95% CI: 0.826-0.912) and an AUC of 0.862 (95% CI, 0.815-0.909). The calibration curve demonstrated a high degree of concordance between the predicted and actual probabilities. The decision curve analysis demonstrated that the nomogram was clinically useful when the threshold for intervention was set at the metastasis possibility range of 1% to 86%. Conclusion: The nomogram combined with preoperative pathology and HRCT imaging have the potential to improve the evaluation of ALN status.

Background: N7-methylguanosine (m7G) methyltransferases and microRNAs (miRNAs) are closely associated with tumor progression. However, the role of m7G methyltransferase-related miRNAs as prognostic markers in oral squamous cell carcinoma (OSCC) has not been studied. This study aimed to explore the m7G methyltransferase-related miRNAs in OSCC, establish a prognostic model based on m7G methyltransferase-related miRNAs, investigate their correlation with immune cell infiltration, and assess their potential prognostic value. Methods: Transcriptional and clinical data of patients with OSCC were obtained from The Cancer Genome Atlas (TCGA) database. TargetScan and miRWalk were used to predict m7G methyltransferase-related miRNAs. Subsequently, differentially expressed m7G methyltransferase-related miRNAs in TCGA-OSCC were selected. Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were used to build an m7G methyltransferase-related miRNA risk prognostic model for TCGA-OSCC. Patients were stratified into high- and low-risk groups. The predictive and diagnostic accuracies of the risk prognostic model were further validated using Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curve analysis, independent prognosis analysis, and nomogram plots. Finally, quantitative real-time polymerase chain reaction (qPCR) was used to validate the expression levels of m7G methyltransferase-related miRNAs in postoperative cancer and adjacent normal tissues from 60 patients with OSCC. Results: Through Cox and LASSO regression analysis, six candidate miRNAs (hsa-miR-338-3p, hsa-miR-1251-3p, hsa-miR-3129-5p, hsa-miR-4633-3p, hsa-miR-216a-3p, and hsa-miR-6503-3p) most relevant to the prognosis of patients with OSCC were identified to construct an m7G methyltransferase-related miRNA risk prognostic model. In this model, the overall survival (OS) of the high-risk group was significantly shorter than that of the low-risk group (P < 0.001). The model effectively predicted prognosis and served as an independent prognostic indicator for patients with OSCC. Compared with the low-risk group, the high-risk group exhibited a significantly increased capacity for immune cell infiltration (P < 0.05), while the activation and initiation abilities of immune cells were decreased. Finally, six m7G methyltransferase-related miRNAs were validated in OSCC tissue samples. Conclusion: The risk prognostic model based on six m7G methyltransferase-related miRNAs can predict the OS rate of patients with OSCC and has the potential to guide individualized treatment. This prognostic model is closely associated with immune cell infiltration in patients with OSCC.

Background: To elucidate the mechanisms by which Jolkinolide B (JB), derived from Euphorbia fischeriana, suppresses gastric cancer (GC) development, given its known potent antitumor effects and the lack of detailed understanding of its impact and molecular processes in GC. Methods: The study utilized both cellular and animal models to investigate the effects of JB on GC. The GC cell lines AGS and MKN45 were used to assess JB's impact on cell growth, proliferation, migration, and invasion. Molecular techniques, including molecular docking and dynamics simulations, were employed to explore the binding interactions between JB and caspase-8. The inhibitor Z-IETD-FMK was used to examine the role of caspase-8 in JB-mediated PANoptosis. Xenograft tumor transplantation experiments were conducted to evaluate JB's effect on tumor growth and biotoxicity in vivo. Results: JB markedly inhibited the growth, proliferation, migration, and invasion of the AGS and MKN45 GC cell lines. It induced PANoptosis in GC cells by activating caspase-8, leading to increased expression of cleaved caspase-3/7 (apoptosis), GSDMD-N (pyroptosis), and p-RIPK1 and p-MLKL (necroptosis). Molecular docking and dynamics simulations revealed that JB binds effectively to caspase-8 with a binding free energy (ΔTotal) of -34.41 kcal/mol, suggesting specific binding-induced caspase-8 activation. The inhibition of caspase-8 by Z-IETD-FMK prevented JB-mediated PANoptosis. Additionally, JB significantly reduced tumor growth in xenograft models without causing biotoxicity. Conclusion: JB is a promising bioactive agent that inhibits gastric cancer growth through the activation of the PANoptosis pathway. This study highlights JB's potential as an effective therapeutic option for GC, underlining the importance of its binding interaction with caspase-8 and subsequent activation of apoptotic, pyroptotic, and necroptotic pathways.

Background: The preoperative identification of neoadjuvant chemotherapy (NAC) treatment responsiveness in breast cancer (BC) patients is advantageous for tailoring treatment regimens. There is a relative scarcity in the current research exploring NAC treatment responsive biomarkers using bulk sequencing data obtained from fine-needle aspiration (FNA). Materials and Methods: Limma was employed for the selection of differentially expressed genes. Additionally, WGCNA, machine learning, and Genetic Perturbation Similarity Analysis (GPSA) were utilized to identify key genes associated with NAC treatment response. ConsensusClusterPlus was employed for unsupervised clustering. Rt-qPCR and WB were conducted to assess gene expression and protein levels in clinical tissues and cell lines. The Seahorse XF96 Extracellular Flux Analyzer was utilized to evaluate Extracellular Acidification Rate (ECAR) and Oxygen Consumption Rate (OCR). The "pRRophetic" package was used for drug sensitivity prediction, while CB-Dock2 was applied for molecular docking and optimal pose presentation. Spatial transcriptomic analysis was based on the CROST database. Results: Eleven biomarkers were identified associated with NAC treatment response in BC patients, with FOXA1 identified as a pivotal hub gene among them. The expression levels of FOXA1 showed a significant positive correlation with genomic stability and a marked negative correlation with the homologous recombination deficiency (HRD) score. Downregulation of the FOXA1 gene resulted in reduced glycolysis in MCF-7 cells.Additionally, FOXA1 were found to serve as a biomarker for both NAC and PARP inhibitor treatment sensitivity in BC patients. Spatial transcriptomic analysis indicates significantly elevated infiltration of T follicular helper (T-FH) cells and mast cells surrounding tumors exhibiting high FOXA1 expression. Conclusion: In summary, our study involved the analysis of diverse sequencing datasets derived from various FNA samples to identify biomarkers sensitive to NAC, thereby offering novel insights into resources for future personalized clinical treatment strategies.

Purpose: This study aims to evaluate the prognostic significance of preoperative serum cystatin C (Cys-C) in patients with renal cell carcinoma (RCC). Methods: We analyzed clinicopathological data and follow-up information of 624 RCC patients who underwent partial or radical nephrectomy at our institution. The optimal cutoff value of Cys-C was determined using X-tile software. Survival outcomes, including overall survival (OS) and cancer-specific survival (CSS), were evaluated using the Kaplan-Meier method and log-rank test. To avoid overfitting and collinearity, we used LASSO-based multivariable Cox regression analysis to identify independent predictors of OS and CSS. The predictive accuracy of the established model, including preoperative serum Cys-C, was evaluated using the time-dependent receiver operating characteristic (ROC) curves and the area under the curve (AUC). Results: The median follow-up period was 40 months. The optimal cutoff value of preoperative serum Cys-C levels was 0.95 mg/L. Compared with the low Cys-C group, patients in the high Cys-C group had significantly shorter OS and CSS. Multivariable Cox regression analysis indicated that elevated preoperative serum Cys-C level was an independent adverse predictor for RCC patients post-nephrectomy. After adjusting for all covariates, high preoperative serum Cys-C level was associated with worse OS (hazard ratio [HR]: 2.254; 95% confidence interval [CI]: 1.144, 4.439; P = 0.019) and CSS (HR: 3.621; 95% CI: 1.386, 9.456; P = 0.009). Time-dependent ROC analysis demonstrated that our model, including preoperative serum Cys-C, performed well in predicting accuracy of survival. Conclusions: Preoperative serum Cys-C level is an effective prognostic indicator for OS and CSS in RCC patients undergoing nephrectomy.

Background: The importance of fibroblasts in cancer progression is becoming more acknowledged, particularly the significance of their immune-related genes. However, the precise roles these genes play in fibroblasts throughout tumor development remains unclear. Exploring how these genes function in advancing kidney renal clear cell carcinoma (KIRC) could provide answers to these uncertainties. Material and method: The Cancer Genome Atlas (TCGA) database served as the source of data for KIRC patients. We distinguished fibroblast immune-related genes (FIGs), which are used to construct risk score. Further analysis conducted including enrichment analysis, assessment of tumor mutation burden (TMB), evaluation of tumor microenvironment (TME), analysis of immune cell infiltration, and drug sensitivity prediction. Result: The risk score using 6 FIGs effectively predicts the outcomes for KIRC patients. Nomogram which is based on the risk score and clinical data, demonstrated superior predictive performance compared to the version without the risk score. Enrichment analysis identified that coagulation pathway predominates in high-risk group, the protein secretion pathway is prevalent in low-risk patients' cohort. The adverse prognosis in high-risk patient cohort could be linked to an elevated TMB. TME analysis showed that high-risk group's tumor tissues contain more immune and stromal cells. Furthermore, the amount of regulatory T cells increases with the risk score. Low-risk group response better to immunotherapy. Finally, RT-qPCR confirmed the differential expression of FIGs in KIRC patients. Conclusion: This risk score and nomogram are valuable tools assessing KIRC patients' prognosis. Poorer prognosis in high-risk categories may have relationship with activation of coagulation pathway and a higher TMB.

Background: Triple-negative breast cancer (TNBC) is a poor prognostic subtype of breast cancer due to limited treatment. Macrophage plays a critical role in tumor growth and survival. Our study intends to explore the heterogeneity of macrophage in TNBC and establish a macrophage-related prognostic model for TNBC prognostic stratification. Materials and Methods: Seurat package was conducted to analyze the single-cell RNA expression profilers. The cell types were identified by the markers derived from public research and online database. The cell-cell interactions were calculated by the CellChat package. Monocle package was used to visualize the cell trajectory of macrophages. The prognostic model was constructed by six macrophage-related genes after a series of selections. The expression of six genes were validated in normal and TNBC tissues. And several potential agents for high-risk TNBC patients were analyzed by Connectivity Map analysis. Results: Nine cell types were identified, and the macrophages were highly enriched in TNBC samples. five distinct subgroups of macrophage were identified. Notably, SPP1+ tumor-associated macrophages exhibited a poor prognosis. The prognostic model was constructed by HSPA6, LPL, IDO1, ALDH2, TK1, and QPCT with good predictive accuracy at 3-, 5- years overall survival for TNBC patients in both training and external test cohorts. Finally, several drugs were identified for the high-risk TNBC patients decided by model. Conclusion: Our study provides a valuable source for clarifying macrophage heterogeneity in TNBC, and a promising tool for prognostic risk stratification of TNBC.

Objective: This study aimed to assess the diagnostic value of target scanning combined with three-dimensional reconstruction in early-stage lung adenocarcinoma. Methods: A retrospective analysis was conducted on 2017 patients with pathologically confirmed early-stage lung adenocarcinoma who underwent thoracoscopic lobectomy at the First Affiliated Hospital of Anhui Medical University from September 2018 to May 2023. These patients were initially diagnosed using conventional spiral CT scanning, and the study explored the application of target scanning combined with three-dimensional reconstruction in the diagnosis of early-stage lung adenocarcinoma. Results: the pulmonary nodules were classified into three groups according to the pathological classification: Pre-Invasive lesion (PI), Microinvasive adenocarcinoma (MIA), and Invasive adenocarcinoma (IA), there were significant differences in the mean diameter of pulmonary nodules, the mean diameter of solid components, the proportion of solid components, pleural indentation, lobulation, spinous process, spiculation, and vascular convergence among the three groups. There were no significant differences between conventional spiral CT scanning and target scanning combined with three-dimensional reconstruction in terms of the number of cases with pure ground-glass nodules, mixed density nodules, pure solid nodules, the detection rate of vacuole signs, the CT value of the solid component and ground-glass component, and the maximum nodule diameter (P>0.05). However, target scanning combined with three-dimensional reconstruction detected a higher number of cases with lobulation signs, spinous process signs, pleural depression signs, burr signs, vessel convergence signs, and larger maximum diameters of the solid component compared to conventional spiral CT scanning (P<0.05). Conclusions: Target scanning combined with three-dimensional reconstruction provides more reliable imaging evidence for the diagnosis of early-stage lung adenocarcinoma, particularly in identifying specific signs and characterizing solid components.

Species-specific long non-coding RNAs (lncRNAs) possess numerous unknown functions. We have recently reported that short interfering RNAs (siRNAs) designed to target mouse-specific lncRNAs caused cell death exclusively in human cancer cells, sparing normal human cells and mouse cancer cells. However, it is uncertain whether other non-human species-specific lncRNAs could also be applied as sequential targets for designing anti-tumor therapeutic siRNAs. In this research, we showed that siRNAs targeting rat or zebrafish-specific lncRNAs could exert similar cytotoxic effects against human colorectal cancer (CRC) cells while leaving normal human cells unaffected. Mechanistic investigations revealed that these siRNAs prompted apoptosis or pyroptosis in human CRC cells by triggering an IRF3-independent immune response against exogenous dsRNAs, based on the expression of protein gasdermin E (GSDME). Our study demonstrates that utilizing siRNAs to target non-human species-specific lncRNAs can trigger cell death in human CRC cells, indicating that non-human species-specific lncRNAs could serve as a promising reservoir for target libraries when designing anti-tumor siRNAs.