Journal of Cancer最新文献

Breast cancer (BC) is the most frequently diagnosed and the leading cause of cancer-related deaths among women worldwide. It is crucial to develop a cost-effective BC genetic panel for detection and diagnosis. In this study, tissue samples from 52 BC patients and peripheral blood samples from 18 healthy volunteers were collected in western China, followed by gDNA extraction. H&E and IHC analysis were employed to detect the expression of invasive BC tissues. We analyzed data using public databases such as COSMIC/ClinVar/HGMD along with our own previously published data and queried commercial BC panels to select high-risk genes. Using Illumina DesignStudio, gene panel primers consisting of 13 genes were designed with 696 primer pairs. The specificity of all primers was validated through common PCR assays. Once the gene panel was completed, multiple polymerase chain reactions (MPCR) were performed using the designed panel primers. The resulting MPCR products were purified to enrich them as library templates. Subsequently, after passing quality tests for library integrity assessment, Next-generation sequencing (NGS) was conducted. Through bioinformatics analysis of the NGS data, 4,571 variants were identified in the annotation files from 52 samples, classified into different types. Among these variants, 358 (approximately 7.8%) were newly discovered and distributed across 11 genes in 52 patients without in the ExAC database. The KMT2C gene exhibited the highest frequency of variants, presenting in 83.0% of 52 patient samples. Variants in BRCA2 (71%), BRCA1 (48%), PALB2 (40%), PIK3CA (23%), and RNF40 (21%) genes were found in over 20% of patients. Additionally, variants were observed in the AKT1 (12%), ERBB2 (10%), ESR1 (8%), TWIST1 (8%), and PIK3R1 (4%) genes. Further analysis using PolyPhen-2, SIFT, CADD, and Mutation Taster tools analysis showed that out of these new variants, 49 (49/358) had potential pathogenic effects on protein functions and structure across 52 patients. Consequently, a high-risk gene panel has been preliminarily established for early detection/diagnosis that will contribute to earlier prevention and treatment strategies for individuals with BC, particularly those residing in developing or underdeveloped countries. The identification of novel pathogenic variants within our cohort not only expands knowledge regarding genetic diagnosis applications for BC patients but also facilitates genetic counseling services for affected individuals and their families.

Purpose: This study aims to compare the efficacy of two treatment strategies for gastric cancer with clinical evidence of pancreatic head or duodenal involvement: gastrectomy combined with pancreaticoduodenectomy (GPD) and neoadjuvant chemotherapy followed by surgery (NCS). Methods: A retrospective analysis of patient data from January 2012 to January 2022 was conducted to evaluate the outcomes of these two treatment strategies. Results: The study included 284 patients, comprising 78 in the GPD group and 206 in the NCS group. In the NCS group, 119 patients required extended pancreaticoduodenectomy, a significantly smaller proportion compared to the GPD group (p < 0.001). The NCS group successfully avoided unnecessary extended pancreaticoduodenectomy. In contrast, 15 patients in the GPD group underwent surgery despite postoperative pathological confirmation of no pancreatic head or duodenal involvement (p < 0.001). The incidence of Clavien-Dindo grade ≥ IIIb complications was significantly greater in the GPD group than in the NCS group (10.3% vs. 3.3%, p = 0.034). Overall survival was significantly longer in the NCS group, with a median of 25 months compared to 20 months in the GPD group (p = 0.0005). Multivariate Cox regression analysis revealed that tumor diameter ≥7 cm and N3 stage were independent adverse prognostic factors. Conclusion: Neoadjuvant chemotherapy is recommended for patients with gastric cancer presenting clinical evidence of pancreatic head or duodenal involvement. This approach reduces unnecessary extended surgeries, lowers complication rates, and improves overall survival.

Breast cancer remains the leading cause of cancer-related mortality among women globally. A significant challenge in lowering breast cancer death rates is multidrug resistance. This resistance arises through various mechanisms, such as heightened drug efflux, improved DNA repair, escape from senescence, epigenetic modifications, tumor heterogeneity, alterations in the tumor microenvironment (TME), and the epithelial-to-mesenchymal transition (EMT). These factors collectively make overcoming drug resistance particularly difficult. Therefore, in this study, we analyzed data from The Cancer Genome Atlas (TCGA) and identified a novel gene, galectin-8, which plays a critical regulatory role in breast cancer progression. Gene Set Enrichment Analysis (GSEA) further revealed that galectin-8 is involved in modulating drug resistance in breast cancer. To validate this finding, we conducted a mass assay comparing drug-resistant triple-negative breast cancer (TNBC) cell lines with control groups. Our results demonstrated a significant increase in galectin-8 expression in the drug-resistant cells, with statistically significant differences observed. In addition, we found that reducing galectin-8 expression in drug-resistant cell lines not only reinstated the effectiveness of anticancer drugs but also suppressed tumor cell proliferation and migration. Therefore, our findings highlight the significant prognostic and therapeutic potential of galectin-8, emphasizing the importance of future research to explore targeted therapeutic strategies in breast cancer.

Background: Basement membrane is a special component of extracellular matrix of epithelial and endothelial tissues, which can maintain their normal morphologies and functions. It can also participate in tumor progression and affect tumor treatment. However, the roles of basement membrane-related genes (BMGs) in acute myeloid leukemia (AML) remain unknown. Material and methods: We downloaded the data of AML and normal samples from TCGA, GTEx, and GEO. Then, we performed bioinformatics analysis to identify differential BMGs. We calculated the risk score of the training cohort and divided it into two risk groups. In addition, we also introduced external cohorts, serving as validation cohorts, to estimate the accuracy of risk score. A nomogram was established based on the risk score and clinicopathological characteristics to predict the prognosis. Based on BMGs, AML patients of TCGA were clustered into 2 subtypes. To investigate the biological features and the association between immune cells and TME, we utilized GSVA to assess pathway enrichment and ssGSEA to quantify the levels of immune cell infiltration across samples. Results: We obtained 3 differential BMGs between AML and normal samples. The training cohort was divided into high- and low-risk groups based on the risk score. The Kaplan-Meier survival analysis indicated that the two groups had significant differences. The nomogram could be used to predict the survival outcomes of AML patients. Based on the clustering result, we found significant differences between the two gene clusters. Sankey's diagram suggested that cluster B was associated with the high-risk group and poor prognosis. GSVA analysis showed that cluster B was also related to the upregulation of intercellular and intracellular signal transduction pathways. In TME, resting mast cells, follicular helper T cells, and plasma cells decreased while monocytes increased in the high-risk group. In addition, the high-risk group was more sensitive to BTK and AKT inhibitors. Conclusion: Our study indicated that the nomogram model of BMGs could predict the prognosis of AML patients. Meanwhile, BMGs were correlated with immune TME in AML. A correct and comprehensive assessment of the mechanisms of BMGs in individuals will help guide more effective treatment.

Metastasis is the leading cause of cancer-related deaths and poses a treatment challenge. Although studies have shown the importance of epithelial-mesenchymal transition (EMT) and metabolic reprogramming during cancer metastasis, the link between EMT and metabolic reprogramming, as well as the underlying molecular mechanisms by which both mediate cancer cell invasion and metastasis have not been elucidated. Here, we observed that interactions between platelets and cancer cells promote the secretion of TGF-β, thereby initiating EMT, promoting the invasion, and altering the metastatic and metabolic potential of colon cancer cells. TGF-β activates the AKT signaling pathway to enhance HK1 and HK2 expression in cancer cells, leading to increased glucose consumption, ATP production, and precise modulation of cell cycle distribution. In an energy-deficient model induced by oxidative phosphorylation (OXPHOS) inhibition with oligomycin A, TGF-β-induced highly metastatic HCT116 (H-HCT116) cells adapt by upregulating HK expression and glycolytic metabolism, while concurrently decreasing cell proliferation to conserve energy for survival. Mechanistically, H-HCT116 cells regulate cell division rates by downregulating CDK2, CDK4, and Cyclin D1 protein expression and upregulating p21 expression. Furthermore, H-HCT116 cells display enhanced motility, which is linked to increased mitochondrial metabolic activity. These findings indicated that cancer cells-platelets interaction secreted TGF-β activates cancer metastasis potential by inducing metabolic reprogramming and bioenergetic adaptation. The present study provides new insights into the adaptive strategies of highly metastatic cancer cells under adverse conditions and indicates that targeting glycolysis and metabolic reprogramming could serve as a viable approach to prevent cancer metastasis.

Background: Early-onset kidney cancer (EOKC) is often associated with genetic factors and a high risk of metastasis. However, there is a lack of accurate prediction models for the prognosis of EOKC. The aim of this study is to establish an effective nomogram for predicting and evaluating the prognosis of patients with EOKC. Methods: The patients with EOKC were selected from the latest SEER database during 2004-2015. Patients between 2004 and 2014 were randomly divided into a training cohort and a validation cohort at a ratio of 7:3, and patients in 2015 were used for temporal external validation. Additionally, we included patients from First Hospital of Shanxi Medical University between 2013 and 2021 for spatial external validation. The performance of the nomogram was assessed using the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Patients were stratified based on the nomogram, and Kaplan-Meier (KM) curves were plotted to compare the survival probability of patients. Results: In the temporal and spatial external validation cohort, the C-index of the nomogram for OS was 0.872 and 0.875, respectively, and the C-index of the nomogram for CSS were 0.872 and 0.851, respectively. In the temporal external validation cohort, the 1-year, 3-year and 5-year AUC of the nomogram for OS were 0.906, 0.899 and 0.876, respectively. In addition, the AUC showed that the nomogram had also high predictive ability for CSS. The calibration curves and DCA also indicated that the nomogram had a strong clinical utility. The KM curve revealed that patients in the low-risk group had a better prognosis than those in the high-risk group. Conclusion: Our study developed a novel high-performance nomogram for assessing the prognosis of patients with EOKC, and it has great potential for clinicians to assess patient prognosis and formulate effective intervention and follow-up strategies.

Matrix stiffness is a critical determinant of tumorigenesis and cancer progression. Transient receptor potential vanilloid 4 (TRPV4), a mechanosensitive calcium channel, regulates angiogenesis and stromal stiffness in various tumors. However, it is unclear whether matrix stiffness regulates the invasiveness of nasopharyngeal carcinoma (NPC) cells through TRPV4. In this study, we found that increased matrix stiffness of NPC tissues correlated with advanced tumor stages. Furthermore, simulation of high matrix stiffness in vitro upregulated TRPV4, and increased the migration, invasion, and epithelial mesenchymal transition (EMT) of NPC cells. Knockdown or pharmacological inhibition of TRPV4 significantly suppressed the calcium influx in NPC cells, and inhibited their invasiveness and EMT under high-stiffness conditions. Mechanistically, TRPV4 modulated the invasiveness of NPC cells in response to matrix stiffness via the NOX4/IL-8 axis. Notably, TRPV4 and IL-8 levels were significantly increased in the high-stiffness NPC tissues, and showed a positive correlation. Taken together, matrix stiffness promotes the malignant progression of NPC cells through the activation of the TRPV4/NOX4/IL-8 axis, which could be explored further as a potential target for NPC therapy.

In recent years, aurora kinase C (AURKC) has emerged as a potential therapeutic target for cancer, having been found to induce proliferation in a variety of cancers. However, at present, its precise mechanism remains unclear. In this study, the specific role of AURKC in renal clear cell carcinoma and its mechanism was investigated. The protein expression levels of AURKC were evaluated in clear cell carcinoma and adjacent normal tissues, followed by prognostic analysis. Subsequently, cell models with knocked-down and overexpressed AURKC were constructed for in vitro cell experiments, and tumor-bearing mouse models were constructed to confirm the specific role of AURKC in vivo. AURKC was found to be highly expressed in ccRCC, which was associated with poor prognosis. In the in vitro experiments, the expression levels of CyclinD1 and proliferating cell nuclear antigen (PCNA) proteins were downregulated after AURKC knockdown, and the cell proliferation ability was found to decrease significantly. After AURKC overexpression, the levels of ERp57 protein expression increased significantly, also significantly enhancing the cell proliferation ability. In addition, AURKC was found to interact with ERp57 and exhibited a colocalization relationship. In the in vivo experiments, AURKC downregulation significantly inhibited the expression of ERp57 protein and blocked the growth of tumor tissue in tumor-bearing mice. These results suggest that the abnormal expression of AURKC in ccRCC enhances the expression of ERp57 protein, thereby promoting the proliferation of clear cell renal cell carcinoma. Thus, AURKC shows potential as a target for the treatment of ccRCC.

Background: This study aimed to investigate glycogen metabolism in gastric cancer (GC) and develop a glycogen-based riskScore model for predicting GC prognosis. Methods: Patients' expression profiles for 33 tumor types were retrieved from TCGA. Four GC bulk and one single-cell sequencing datasets were obtained from GEO database. This study also enrolled a bladder urothelial carcinoma immunotherapeutic IMvigor210 cohort. The ssGSEA method was conducted to assess glycogen biosynthesis and degradation level. Consensus clustering analysis was conducted to identify different clusters. A glycogen riskScore signature was developed to evaluate prognostic value across different cohorts. Besides, in vitro experiments were conducted to further evaluate the role of glycogen metabolism related genes in GC. Results: Both glycogen biosynthesis and degradation were significantly associated with worse overall survival and were also related with malignant phenotype in GC at both bulk and single-cell levels. Differential outcomes and immune functions were verified in the three identified clusters. The constructed glycogen riskScore model accurately classified GC patients with different outcomes, genomic and immune landscape, and performed well in predicting prognosis through external validation, immunotherapy and pan-cancer cohorts. Furthermore, the riskScore could predict response to chemotherapy and immunotherapy. Functional analyses revealed the signature's connection to pro-tumor and immunosuppression related pathways across pan-cancer. Additionally, glycogen metabolism related genes were found to regulate the malignant phenotypes of GC cells. Conclusion: This study revealed important roles of glycogen metabolism in promoting progression of GC and presented a glycogen riskScore model as a novel tool for predicting prognosis and treatment response.

Background: Ovarian cancer (OC) is a common malignant tumor of the female reproductive organs. The novel serine/threonine kinase NEK6 is highly expressed in various cancers and affects the prognosis of patients. However, the role of NEK6 in OC is still unclear. Methods: In this study, the expression profiles of NEK6 in OC and its roles in the development of OC were investigated. The expression profiles of NEK6 across cancers and OC were explored using bioinformatics analysis, and its expression in OC patients was detected by immunohistochemical (IHC) staining. The correlation between its expression and clinicopathological factors was also analyzed. Furthermore, the NEK6 levels in the tumor tissues of OC patients were detected via RT‒qPCR and Western blotting. Biological functions, including cell growth, migration, invasion and apoptosis, were analyzed using MTT, Transwell and flow cytometry assays, respectively. Results: Bioinformatics analysis revealed that NEK6 was highly expressed in most human cancers, including OC. IHC revealed 67.27% moderate or strong NEK6 staining in tumor tissues, 32.73% (36/110) weak staining, and negative or weak NEK6 staining in normal ovarian tissues, and its high expression was correlated with clinicopathological factors, including histological grade (P=0.008) and metastasis (P=0.006). The Kaplan‒Meier survival curve revealed that OC patients with high expression of NEK6 had poorer overall survival rates (P=0.025). NEK6 was overexpressed in OC tissues and SK-OV-3 and A2780 cells, and when NEK6 was knocked down with siRNAs, cell growth, migration and invasion were inhibited, whereas cell apoptosis was significantly promoted. Conclusion: NEK6 is highly expressed in OC; its overexpression indicates poor prognosis; and NEK6 knockdown leads to inhibited growth, migration and invasion while promoting the apoptosis of OC cells. These findings indicate that NEK6 is a potential oncogene and a poor prognostic factor in OC, suggesting that NEK6 can serve as a new therapeutic candidate for OC and that NEK6 inhibition may be an effective strategy for OC treatment.