Journal of Cancer最新文献

Glioblastomas represent the most prevalent primary brain tumors in adults. Due to their highly malignant biological behavior, they are classified as grade 4 according to the World Health Organization (WHO) classification of brain tumors. Despite the progress in understanding the molecular pathogenesis of these tumors, no curative therapy has been developed for patients with glioblastoma. In this study, an integrated comparative analysis of cyclin-dependent kinase inhibitor (CDKN) 2A/B chromosomal deletion was performed on 45 glioblastomas, representing the most frequent molecular subtypes of glioblastomas, receptor tyrosine kinase (RTK) I (n=13), RTK II (n=15), and the mesenchymal subtype (MES) (n=17). The analysis of copy number variation (CNV) profiles was conducted on CDKN2A/B losses. Subsequent statistical analysis was then applied to correlate the collected data with molecular glioblastoma epigenotypes. Loss of CDKN2A/B was found 44% (20/45) of all glioblastomas, thereby, in 46% (6/13) of RTK I, 67% (10/15) RTK II, and 24% (4/17) of MES. Statistical analysis showed that loss of CDKN2A/B is significant (p < 0.01) in RTK II compared with MES. Even though CDKN2A/B does not per se function as a molecular target, there is great potential for enhancing treatment outcomes through the restoration of the tumor-suppressing capabilities of CDKN2A/B. This strategy can be employed in therapeutic interventions and is a promising avenue for research. This efficacy of this approach demonstrates high potential, as evidenced by its efficacy in other tumors, including melanoma.

Cancer stem cells (CSCs) play pivotal roles in tumor relapse, metastasis, and therapy resistance. Interleukin 17 receptor A (IL-17RA) is a key mediator in colorectal cancer (CRC) pathogenesis and progression. Our recent study demonstrated that reduced IL-17RA expression correlates with favorable prognosis in CRC patients and suppresses tumor growth in murine models. This study aimed to investigate the role of IL-17RA in promoting cancer stem-like properties and its impact on colorectal cancer prognosis and chemoresistance. Expression levels of IL-17RA and CSC markers in CRC cells were evaluated using quantitative real-time polymerase chain reaction and Western blotting. Kaplan-Meier analysis of 68 CRC patients revealed that high IL-17RA expression is associated with poor clinical outcomes. To investigate IL-17RA's functional role, CRC cells with stable IL-17RA overexpression were analyzed for changes in CSC marker expression, sphere formation, and 5-fluorouracil (5-FU) resistance. IL-17RA overexpression significantly increased CSC marker expression, including cluster of differentiation 133 (CD133), leucine-rich repeat-containing G protein-coupled receptor 5 (LGR5), sex determining region Y-box 2 (SOX2), and enhanced tumor sphere formation and 5-FU resistance in SW620 cells. Specific inhibitors of IL-17RA signaling, such as the STAT3 inhibitor Stattic, reduced the expression of CD133, LGR5, ALDHA1, SOX2 and c-MYC, as well as tumor sphere formation in SW620 cells. These findings elucidate a novel IL-17RA-STAT3 axis that regulates CSC properties in CRC and highlight IL-17RA as a promising prognostic biomarker and therapeutic target for CRC treatment.

Introduction: Appropriate patient selection is essential for optimising outcomes in individuals with peritoneal metastasis (PM) undergoing treatment with Pressurized Intraperitoneal Aerosol Chemotherapy (PIPAC). This study investigated the prognostic value of pretreatment inflammatory biomarkers and explored their ability to predict the possibility of completion of three or more PIPAC treatments. Method: This observational study analysed prospectively collected data from patients with PM of gastrointestinal or ovarian origin enrolled in the PIPAC OPC-1 or OPC-2 studies between March 2015 and January 2022. Six biomarkers were examined: Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio, Systemic Immune-Inflammation Index (SII), C-reactive protein, modified Glasgow Prognostic Score, and Prognostic Nutritional Index. Biomarkers were obtained pretreatment, and treated as continuous variables. Survival was assessed using Kaplan-Meier and Cox regression analyses, adjusting for covariates available prior to the first PIPAC. ROC analysis was used to evaluate the predictive performance. A p-value less than 0.05 was considered statistically significant. Results: The cohort consisted of 130 patients, with a median overall survival (OS) of 8.7 months. Sixty percent of the patients received three or more PIPAC treatments. Elevated levels of all six biomarkers were significantly associated with reduced OS. In the multivariate analysis, five biomarkers remained independently associated with survival. NLR and SII demonstrated moderate discriminatory power (AUC > 0.70) for predicting the completion of three or more treatments. Conclusion: Pretreatment inflammatory biomarkers are objective, readily accessible and clinically applicable tools that may support the selection of appropriate candidates for PIPAC. The findings of this study encourage the integration of biomarker assessments into future PIPAC research protocols.

Rhabdomyosarcoma (RMS) is a rare disease that arises from skeletal muscle mainly affects children and adolescents. Patients with RMS have diverse symptoms and prognosis based on tumor sizes, tumor anatomical locations, histological subtypes of the tumors and genetic testing of paired-box-forkhead box O1 (PAX-FOXO1) fusion gene. The 4 subtypes of RMS include embryonal RMS (eRMS), alveolar RMS (aRMS), spindle cell/sclerosing RMS (scRMS) and pleomorphic RMS (pRMS). Treatment for RMS patients remains challenging due to its heterogeneous nature. Thus, a combinatory approach is likely to warrant better management of RMS. Given that PAX-FOXO1 fusion gene is the most common biomarker for RMS, though this fusion gene only accounts for 16-20% of RMS patients. Targeted therapy that tailors treatment plans to the individual patient may provide additional benefits for RMS patients. This review describes the frequent genetic mutations observed in RMS patients and drug development based on these mutations shall provide direction to develop targeted therapy leading to effective personalized treatment for RMS patients.

Gastrointestinal tumors are among the most common tumors worldwide and are currently the leading cause of cancer-related deaths. Gastrointestinal tumors affect the digestive system and include esophageal, liver, gastric, colorectal, and pancreatic cancers. Aerobic glycolysis is a widespread phenomenon among gastrointestinal tumor cells, which poses a major hazard to human health and life. Increasing evidence suggests that aerobic glycolysis can induce and promote the development of gastrointestinal tumors by rapidly providing large amounts of energy and altering the tumor microenvironment. Among them, glucose transporter proteins and key enzymes involved in glycolysis are expressed at higher levels during aerobic glycolysis, and the corresponding signaling pathways and transcription regulatory factors are activated, playing an important role in the occurrence and development of tumors. Additionally, evidence has indicated that aerobic glycolysis plays an essential role in inhibiting the development of immune cells, modifying the population of immune cells present in the surrounding tumor, and promoting the polarization of immune cells. Moreover, drugs and compounds that target essential enzymes and transcription factors associated with glycolysis are known to exhibit anticancer properties.

Exostosin glycosyltransferase 1 (EXT1) and exostosin glycosyltransferase 2 (EXT2) catalyze heparan sulfate chain elongation and are increasingly implicated in cancer biology, but their roles in gliomas remain incompletely defined. Here, we performed an integrative multi-omics analysis to dissect the transcriptional, epigenetic, and microenvironmental landscape of EXT1 and EXT2 across gliomas. Bulk transcriptomic data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) revealed that both EXT1 and EXT2 are upregulated in high-grade gliomas and associate with adverse survival, with EXT1 showing the strongest and most consistent prognostic impact. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) indicated that EXT1-high tumors are enriched for DNA damage and replication stress programs, cell cycle progression, inflammatory response, and stromal activation pathways, whereas EXT2 expression is preferentially linked to extracellular matrix remodeling, cytoskeletal organization and angiogenesis-related signaling. Single-cell RNA sequencing and Immune deconvolution using Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) showed that EXT1 correlates with increased stromal and immune scores, and reduced cytotoxic T cell signatures, consistent with an immunosuppressive tumor microenvironment. EXT2 expression is enriched in gliomas with pronounced vascular and mesenchymal features, supporting a complementary role in invasive growth and tissue remodeling. Immunohistochemistry on a glioma tissue microarray validated the upregulation of EXT1 protein in high-grade tumors. The study findings identified EXT1 as a central glycosylation-linked regulator of replication stress tolerance and immune remodeling in gliomas, and suggest that EXT2 contributes to extracellular matrix and cytoskeletal reprogramming. The exostosin axis represents a promising source of prognostic biomarkers and potential therapeutic targets in glioma.

Cuproptosis, a newly identified form of cell death, influences the development, progression, and prognosis of prostate cancer (PCa). Identifying key genes associated with cuproptosis and developing robust predictive models through machine learning approaches are crucial for personalized PCa treatment. In our study, multiple machine learning methods and their combinations were employed for the construction of diagnostic and prognostic models for PCa, which were then validated in multiple external independent cohorts. The model key gene, PROK1, was selected for further analysis, and its expression was compared in clinical samples and cell lines. Additionally, the anticancer effect of PROK1 was explored through regulating the expression of PROK1. Most cuproptosis-related genes (CRGs) showed differential expression between PCa and normal prostate tissues. The two clusters derived from the Consensus Clustering method, based on cuproptosis gene expression characteristics, exhibit distinct clinical features and immune microenvironment infiltration patterns. Models constructed based on machine learning methods showed promising diagnostic capabilities for PCa and were associated with the prediction of biochemical recurrence-free survival and disease-free survival of patients. Inhibiting PROK1 expression promoted PCa cell proliferation and invasion, while its overexpression had the opposite effect. Furthermore, pathway exploration revealed that PROK1 inhibits tumor growth by mediating apoptosis under copper ion stress. Its association with cuproptosis warrants further investigation to elucidate the precise mechanism.

Cancer cell dormancy is associated with tumor recurrence and metastasis. Chemotherapy usually induces dormancy as external pressure on the tumor. Dormant cells have considerable resistance to antitumor drugs, although they are not harmful to the host if they do not wake up. Chemotherapy induces a dormant phenotype through remodeling of the tumor microenvironment and alteration of intracellular signaling networks. Multiple adaptive mechanisms that confer drug resistance have been identified in these dormant cells, including the unfolded protein response to endoplasmic reticulum stress, metabolic reprogramming favoring oxidative phosphorylation to avoid damage from oxidative stress, and autophagy to realize the circular utilization of energy. However, dormancy is reversible. The conversion between dormancy and awakening of the tumor during chemotherapy and the recovery period after treatment is modulated by several factors, including the dose and cycle of treatment, and individual differences among patients. The direct elimination of cancer cells or permanent dormancy by chemotherapy predicts favorable outcomes. According to this theory, understanding the mechanisms of cancer dormancy and awakening under chemotherapy and improving prognosis using suitable treatment strategies requires further investigation. This review analyzed studies on cancer cell dormancy and response to chemotherapy to identify potential novel interests for future studies and probable strategies to optimize chemotherapy in clinical trials.

Metabolic reprogramming is an important feature in non-small cell lung cancer (NSCLC) that can result in therapeutic resistance. Exploring dysregulated lipid metabolism in NSCLC will accelerate the development of potential lipid biomarkers to target and control the malignant progression of NSCLC. In this study, RNA next-generation sequencing of 25 paired NSCLC specimens and adjacent normal tissues was used to find that carboxylesterase 3 (CES3) was upregulated in NSCLC. Knockdown of CES3 significantly inhibited NSCLC cell proliferation and invasion. Additionally, CES3 inhibition promoted lipid accumulation in NSCLC cells. Furthermore, we found transcription factor AP-2α (TFAP2A) could regulate CES3 levels in NSCLC. TFAP2A was found upregulated in NSCLC and correlated with poorer outcome. Inhibiting TFAP2A resulted in suppressed cell proliferation as well as invasion while increasing the lipid accumulation in NSCLC. CES3 overexpression could reverse the impact of TFAP2A inhibition on NSCLC progression. In summary, TFAP2A dysregulation resulted in CES3 overexpression and the following NSCLC tumorigenesis. Targeting the TFAP2A/CES3 axis may represent a promising therapeutic strategy for NSCLC in the future.

Background: Alpha-fetoprotein (AFP), Des-gamma carboxy-prothrombin (DCP), lectin-bound AFP (AFP-L3) and Golgi protein-73 (GP73) have been used or proposed as surveillance tests for hepatocellular carcinoma (HCC). The aims of this study were to determine the performance of AFP, DCP, AFP-L3, GP73 and their combination in the diagnosis and prognosis of HCC. Methods: A total of 578 patients were enrolled, including 303 HCC patients, 104 patients with liver cirrhosis, 101 patients with chronic hepatitis and 70 healthy volunteers. The serum levels of AFP, DCP, AFP-L3 and GP73 were quantified before treatment, 7 days and 30 days after treatment. Results: AFP had the best area under the curve (AUC = 0.850), followed by DCP (0.775) and AFP-L3 (0.763), for the prediction of HCC, whereas GP73 had low diagnostic value (0.549). The combination of AFP, DCP and AFP-L3 significantly improved diagnostic performance (AUC = 0.895). The level of AFP 30 days after treatment had the best predictive value for HCC recurrence (AUC = 0.779). Higher recurrence rates were associated with an increasing number of elevated tumor markers measured both before and 30 days after treatment. Furthermore, patients whose marker status remained positive 30 days after treatment had a higher recurrence rate than patients whose marker status changed to negative. Conclusions: AFP was more effective than DCP and AFP-L3 for the diagnosis and prognosis of HCC, and the combination of AFP, AFP-L3 and DCP enhanced the diagnostic performance. The dynamic changes in biomarker positive status after treatment and the number of positive biomarkers play important roles in predicting HCC recurrence.