Journal of Cancer最新文献

Breast cancer, including triple-negative breast cancer (TNBC), is the most commonly diagnosed cancer in women, with subtypes differing in treatment options and prognoses. In particular, TNBC, characterized by the absence of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) expression, is the most aggressive subtype, with limited treatment options, high metastatic rates, and poor survival outcomes. In recent years, epigenetic studies have emerged as a promising tool for analyzing gene expression and alterations in TNBC, providing potential insights into the development of novel therapeutic strategies. Epigenetic mechanisms, such as DNA methylation, histone modifications, and non-coding RNA (ncRNA)-mediated gene silencing, play a crucial role in the development and progression of TNBC. Research into these mechanisms holds significant promise for the development of personalized therapeutic approaches, potentially improving outcomes for TNBC patients. This review provides a comprehensive overview of recent advances in research on epigenetic alterations in TNBC, with an emphasis on potential clinical applications aimed at improving survival and quality of life in TNBC patients.

The C-X-C chemokine receptor type 4 (CXCR4) is a G protein-coupled transmembrane receptor that contributes to tumor growth and angiogenesis. While prior studies have primarily focused on CXCR4 expression in cancer cells and its role in metastasis, a few have examined its involvement in tumor-associated vasculature. In this study, we reported for the first time that CXCR4 expression within the tumor vasculature is significantly associated with higher pathological grades of human oral squamous cell carcinoma (OSCC) (p<0.03). A previous study reported that inhibiting CXCR4 with AMD3100 induces tumor cell death and enhances the efficacy of the chemotherapeutic agent cisplatin. These findings suggest that CXCR4 is an important target for cancer treatment. However, the tumor vascular system is known to be heterogeneous within the tumor microenvironment (TME), which may influence the treatment outcomes. Therefore, this study aimed to explore the effect of CXCR4 antagonism on various blood vessels present within the oral squamous cell carcinoma (OSCC) tumor stroma. Although the efficiency of AMD3100 was not significant in MOC cancer cells, necrosis was induced in the TME when applied to a poorly differentiated OSCC model, highlighting the role of the TME. Notably, CXCR4 is found to be highly overlapped with CD105⁺ angiogenic tumor vessels among various vascular markers. Treatment with AMD3100 leads to a marked reduction in the CD105⁺ vessels and impairs the maturation of tumor micro-vessels, explaining the cause of observed necrosis. Thus, CXCR4 serves as a promising biomarker in OSCC, and its inhibition with AMD3100 offers the therapeutic potential, particularly in cases with advanced pathological grades.

Melanoma, a highly aggressive form of skin cancer, presents considerable challenges in early detection and accurate diagnosis, particularly across its diverse subtypes such as acral lentiginous melanoma (ALM), melanoma in situ (MIS), nodular melanoma (NM), and superficial spreading melanoma (SSM). This study assesses the epidemiology, clinical characteristics, and screening techniques related to various melanoma subtypes, emphasizing their distinct features and risk factors. Moreover, the use of machine learning (ML) methodologies to categorize melanoma subtypes and the thorough examination of advancements in AI-based melanoma diagnosis, primarily emphasizing convolutional neural networks (CNN) and transfer learning approaches. Evaluate the efficacy of several deep learning models in classifying melanoma subtypes while addressing significant obstacles, including class imbalance and model generalization. Furthermore, it contemplates the integration of multimodal data, including genetic information and patient demographics, to enhance diagnostic accuracy. This comprehensive review assesses the epidemiology, clinical characteristics, and machine learning techniques utilized for the classification and detection of different melanoma subtypes, emphasizing recent advancements in AI-driven methods and their clinical significance.

Background: As the most disastrous tumor microenvironment of pancreatic cancer, nutrient deprivation determined various cancer cell biology, especially the cell death resistance. Our objective is to elucidate the role of nutrient deprivation in ferroptosis resistance of pancreatic cancer cells and to explore potential therapeutic strategies to overcome it. Methods: To replicate the nutrient-deprived tumor microenvironment, pancreatic cancer cell lines (PANC1 and Patu8988T) were cultured in Dulbecco's Modified Eagle Medium (DMEM) supplemented with 2% fetal bovine serum (FBS). Ferroptosis was assessed by Cell Counting Kit-8 (CCK8), Malondialdehyde (MDA) assay, and C11 BODIPY staining. The signaling activity was assessed via western blot and quantitative reverse transcription polymerase chain reaction (qRT-PCR), respectively. Results: Ferroptosis inducers promoted pancreatic cancer cell death could be significantly reversed under nutrient deprivation condition. Nutrient deprivation upregulated the expression of SREBP1 and SCD1, leading to increased intracellular levels of monounsaturated fatty acids (MUFAs). Genetic knockdown of SREBP1 or SCD1, as well as treatment with rapamycin (an mTOR inhibitor), reversed the nutrient deprivation induced increase in mature SREBP1 and SCD1 expression and restored lipid peroxidation both in vitro and in vivo. The synergistic application of sorafenib and rapamycin yielded a profoundly efficacious therapeutic outcome in vivo. Conclusion: Our findings demonstrate that nutrient-deprived pancreatic cancer cells adaptively enhance MUFA biosynthesis through the SREBP1-SCD1 axis, conferring resistance to ferroptosis. This resistance can be effectively overcome by combination therapy with sorafenib and rapamycin, offering a promising strategy to target the ferroptosis vulnerability shaped by the pancreatic tumor microenvironment.

Background Disulfidptosis, a newly recognized form of cell death activated by disulfide bond stress, differs from apoptosis, ferroptosis, cuproptosis, and pyroptosis. Understanding its role in prostate cancer is essential for developing tailored therapeutic approaches for managing this condition. Here, we establish the first disulfidptosis-based molecular subtyping framework for prostate cancer (PCa) and identify CCNB2 as a novel regulator of disulfidptosis, revealing its dual role in apoptosis activation and immune microenvironment remodeling. Methods We used consensus clustering to classify disulfidptosis into different subtypes and to study the unique characteristics linked to each one. We also developed a Dis score to measure the severity of each patient's subtype. We compared immune infiltration, pathway enrichment, and survival differences among the subtypes and revealed that the level of the score is significantly associated with the prognosis of PCa.Subsequently, we used Cytoscape software to further filter out hub genes and investigated how these genes influence the progression of PCa and their potential mechanisms through in vitro and in vivo experiments. Results We identified three molecular subtypes associated with disulfidptosis (Cluster A, B, C) and three gene subtypes (GeneCluster A, B, C). Each subtype exhibited a distinct prognosis, level of immune cell infiltration, and biological pathway activation. Notably, Cluster B and GeneCluster B, characterized by elevated disulfidptosis gene expression, were correlated with favorable prognosis. Additionally, we discovered that patients with higher scores exhibited lower tumor mutational burden (TMB) and improved prognosis. Finally, our experimental results confirmed that downregulation of CCNB2 expression promoted disulfidptosis in prostate cancer cells, thereby inhibiting their migration and proliferation capacities. Conclusion This study demonstrates that disulfidptosis can be utilized to stratify risk in patients with PCa. Furthermore, the CCNB2 gene emerges as a potential therapeutic target for prostate cancer by regulating disulfidptosis, thereby influencing the biological behaviors of PCa cells, including their proliferation and migration.

Background: Prostate cancer (PCa), a prevalent malignant neoplasm in men, has its biochemical recurrence-free survival (BCRFS) serving as a critical determinant for patient prognosis. PARP inhibitors have demonstrated potential therapeutic value in the management of PCa. Nevertheless, the precise influence exerted by their associated genes on BCRFS remains elusive. Methods: We selected the differentially expressed genes after treatment with olaparib and defined them as PARP inhibitor-related genes (PIRGs). Consensus clustering was employed to evaluate the relationships among different PIRGs clusters, prognosis, and the immune microenvironment. Univariate COX regression analysis was used to screen the prognosis-related PIRGs, which were then incorporated into multiple machine learning frameworks. The random forest algorithm with the highest C-index was chosen to construct a BCRFS prediction model. A prognostic nomogram was developed based on the risk score and clinical information, and the predictive performance of the model was assessed. Results: In C4 - 2B and LNCaP cell lines, 230 and 58 genes were differentially expressed, respectively. Consensus clustering results showed distinct survival prognoses and immune - infiltrated microenvironments among different groups. The random forest model had a high average C - index in both the training and validation sets. The prognostic model constructed in this study demonstrated a higher C-index compared to the prognostic models from previous studies. High - risk group patients had a poor immunotherapy response. A nomogram based on risk scores and clinical information accurately predicted PCa patients' BCRFS. Cell experiments revealed that KANK3 was downregulated in PCa and upregulated by olaparib treatment. KANK3 overexpression in PCa cell lines inhibited cell proliferation, migration, and invasion, suggesting its oncogenic role in PCa. Conclusion: Our study has described the correlations between PARP inhibitor-related genes and the immune landscape, recurrence after radical prostatectomy, as well as clinical characteristics. The risk score can improve the existing risk stratification system.

Background: It has been reported that the proteome in blood was an important source for biomarker and therapeutic target discovery. However, up to now, few proteomes have been identified with the risk of hematologic malignancies. Methods: Genome-wide association studies (GWASs) including 3,083 plasma proteins are based on data from 54,219 people in the UK Biobank Pharma Proteomics Project (UKB-PPP) and 35,559 individuals from Iceland (deCODE). Genetic correlations with 33 hematologic malignancies were derived from the FinnGen cohort and the UK Biobank Data. Further studies, including Bayesian colocalization, protein-protein interaction assessment, pathway enrichment analysis, and drug target evaluation, were performed to enhance knowledge and identify prospective therapeutic targets for 33 hematologic cancers. Results: Our study indicated that 86 potential plasma proteins may have a substantial causal association with the incidence of 33 hematological tumors, such as BCL2, NFKB1, PARP1, and TNFRSF14. There are 18 proteins with strong evidence of genetic co-localization and 9 proteins with moderate support from colocalization analysis. Out of the 86 proteins, 51 have druggable targets, and 26 were identified as targets for current or prospective pharmaceuticals. Conclusion: Our research revealed numerous significant proteins linked to the likelihood of hematologic malignancies. It may elucidate protein-mediated processes of hematological tumors and provide prospective treatment options for individuals with these conditions.

Background: Although blinatumomab, a bispecific T-cell engager, has exhibited promising clinical outcomes in the treatment of B-precursor acute lymphoblastic leukemia (B-ALL) and B cell non-Hodgkin's lymphoma (B-NHL), it still has some limitations due to CD19-negative relapse and an immunosuppressive phenotype. Epigenetic modulators have the potential to influence the tumor microenvironment (TME) and immune cycle in various ways. Combining multiple drugs is a trend in tumor treatment. Methods: In this article, we generated a novel tri‑specific antibody, called CiTE (CD3-BAFF-R-PD-L1), which is composed of a CD3 binding Fab frame, a BAFF-R binding scFv, and an additional scFv derived from PD‑L1. The cytotoxicity of T cells induced by CiTE (CD3-BAFF-R-PD-L1) was detected in combination with Chidamide. Results: The purified CiTE (CD3-BAFF-R-PD-L1) exhibited high binding capability for CD3-positive cells, BAFF-R-positive cells, and PD-L1-positive cells. Consequently, specific lysis towards BAFF-R-positive cell lines were induced by CiTE (CD3-BAFF-R-PD-L1) in the presence of T cells. We also confirmed that Chidamide could enhance T-cell mediated lysis by upregulating antigen strength on tumor cells and altering the TME by increasing the expression of T cell-attracting chemokines and costimulatory molecules. Conclusions: The novel tri-specific antibody combined with Chidamide holds promise as a safe and effective drug for the treatment of B-cell malignancies, due to its integration of three sections targeting different molecules into one compound.

P53 is a crucial tumor suppressor gene that plays an essential role in maintaining genomic stability, regulating cell cycle progression, and inducing apoptosis. In hematologic malignancies, P53 mutations are frequently associated with poor prognosis, treatment resistance, and immune evasion. Recent research has highlighted the impact of P53 dysfunction on tumor immune escape mechanisms, including impaired antigen presentation, altered cytokine signaling, and recruitment of immunosuppressive cells. This review integrates recent findings on P53 mutations in hematologic malignancies, focusing on their role in immune evasion and potential therapeutic strategies aimed at restoring P53 function or targeting associated pathways. Understanding these mechanisms may provide new insights into the development of effective immunotherapeutic approaches for hematologic cancers.

Background: Gastric cancer (GC) is one of the most common malignant tumors and a leading cause of cancer-related death worldwide. Although advances in surgical techniques and novel treatment techniques such as immunotherapy have improved the prognosis of many tumors, the effectiveness of treatment for advanced GC patients is still limited. Methods: Immunohistochemistry (IHC) staining analysis was conducted to compare the expression of ALDOA and ENO1 in GC tissues and adjacent normal tissues, complemented by bioinformatics analysis using GEPIA, LinkedOmics, and TIMER databases to explore their association with glycolysis and immune cell infiltration. A survival prediction nomogram was constructed based on Cox proportional hazard model data to evaluate prognostic significance. Results: In this study, through IHC staining analysis, it was observed that the expression levels of ALDOA and ENO1 in GC tissues were significantly higher than those in adjacent normal tissues. Moreover, the aberrant expression of ALDOA/ENO1 was associated with a poor prognosis in GC patients. Bioinformatics analysis revealed a positive correlation between ALDOA and ENO1 expression, both intricately associated with glycolysis pathway activation. A survival prediction nomogram, constructed based on the univariate analysis of data from the Cox proportional hazard model, demonstrated that the expression of ALDOA and ENO1 significantly impacts the prognosis of GC patients. Conclusions: ALDOA/ENO1 may play a crucial role in GC, which may potentially offer new perspectives and directions for the development of targeted therapies specifically designed for GC patients.