Discover. Oncology最新文献

Background: Increasing evidence suggests that resistance to 5-fluorouracil (5FU) and oxaliplatin (OXP) in colorectal cancer (CRC) is linked to poor prognosis. This study aimed to probe the effect of colony-stimulating factor 2 (CSF2) on the resistance of CRC to 5FU and OXP.

Methods: The expression of CSF2 in CRC and the impact of abnormal CSF2 expression on the prognosis of CRC patients were analyzed using bioinformatics. The half-maximal inhibitory concentrations (IC50) of 5FU and OXP on CRC cells were determined using the CCK-8 assay. Apoptosis in CRC cells was assessed through flow cytometry. mRNA and protein levels were measured using qRT-PCR and western blot, respectively. Gene Set Enrichment Analysis (GSEA) was conduced to investigate the signaling pathways regulated by CSF2 in CRC. The Notch pathway activator Jagged-1 (JAG) was employed to verify whether CSF2 influences the resistance of CRC cells to 5-FU and OXP by modulating the Notch signaling pathway.

Results: High expression of CSF2 is associated with poor prognosis in CRC patients. CSF2 is downregulated in CRC cells that resistance to 5-FU and OXP. Silencing CSF2 inhibits resistance to 5FU and OXP, reduces the survival of resistant CRC cells, and promotes apoptosis. CSF2 activates the Notch signaling pathway, which is highly expressed in CRC resistant cells; conversely, silencing CSF2 inhibits the activation of this pathway. Treatment with JAG reversed the effects of CSF2 silencing on resistance to 5FU and OXP in CRC cells.

Conclusion: The silencing of CSF2 inhibited the resistance of CRC cells to 5FU and OXP by regulating the Notch signaling pathway.

Background: Acute myeloid leukemia (AML) is associated with high rates of resistance to standard therapies, necessitating the exploration of novel treatment strategies. Venetoclax (VEN) has shown efficacy in AML, yet drug resistance remains a significant challenge. This study aims to explore the synergistic effects of combining dihydroartemisinin (DHA) with VEN to improve therapeutic outcomes in AML.

Methods: AML cell lines and primary cells from AML patients were treated with various concentrations of DHA, VEN and their combined regimen. The cytotoxic effects were evaluated using MTS assays, flow cytometry for apoptosis analysis, and cell cycle assessments. Protein levels of caspase-3, PARP, MCL-1, BCL-XL and C-MYC were analyzed to elucidate the underlying mechanisms of the observed synergy.

Results: The combination of VEN and DHA demonstrated a significant synergistic cytotoxic effect on AML cells, characterized by reduced cell proliferation, induced apoptosis, and cell cycle arrest in the G0/G1 phase. Mechanistically, the synergy was associated with increased levels of cleaved caspase-3 and PARP, along with the downregulation of anti-apoptotic proteins MCL-1 and BCL-XL. Additionally, the combined treatment led to a significant decrease in C-MYC expression. This synergistic effect was consistently observed across all primary AML patient samples analyzed.

Conclusion: The findings suggest that the combination of VEN and DHA exerts synergistic anti-leukemic effects by targeting BCL-XL, MCL-1 and C-MYC, offering a promising therapeutic strategy for AML.

Background: The DNA damage response (DDR) has a major impact on the development and progression of pancreatic ductal adenocarcinoma (PDAC). Investigating biomarkers linked to the DDR may facilitate prognostic assessment and prediction of immunological characteristics for patients with PDAC.

Methods: The single-cell RNA sequencing (scRNA-seq) dataset GSE212966 was obtained from the GEO database, whereas the bulk RNA-seq data were sourced from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Least absolute shrinkage and selection operator (LASSO) and univariate Cox regression analyses were used to select genes to construct a prognostic risk model. Finally, the correlations of the model score with drug sensitivity, immunological checkpoints, and immune infiltration were assessed.

Results: We used 16 DDR marker genes to construct a predictive model. Furthermore, we established that the model had strong performance in both the training and validation cohorts. For PDAC, the model risk score served as an independent predictor of prognosis. There were notable differences in the proportions of the immune cells in the tumor microenvironment and drug sensitivity between the high and low risk score groups. The study confirmed that the risk score model is useful for predicting the immunotherapy response. Our experiments verified that knockdown of LY6D inhibits cell proliferation, promotes apoptosis and DNA damage.

Conclusion: Our creative integration of bulk RNA sequencing and scRNA-seq data allowed us to construct a DDR-related prognostic model. Our model can be used to predict the immunological features, treatment response and prognosis of PDAC with a relatively high degree of accuracy.

Introduction: Plasmablastic lymphoma (PBL), an extremely aggressive B-cell non-Hodgkin lymphoma, is known to be associated with immunosuppression. PBL with primary peritoneal or ovarian involvement is extremely rare. Here, we report a case of PBL in an immunocompetent woman, which involved the right ovary, peritoneum, cervical lymph nodes, and bone marrow.

Case presentation: A 42 year-old immunocompetent premenopausal woman presented with abdominal dullness and distension. Imaging studies revealed the presence of ascites, ovarian mass, peritoneal seedings, and generalized lymphadenopathy. Laparoscopic biopsies of the right adnexal tumor, omental cake, and peritoneal seedings were performed. Poorly differentiated carcinoma was suggested from initial intraoperative frozen sections. The conclusive histological and immunohistochemical diagnosis was however that of PBL. Bone marrow involvement was also confirmed. The patient was treated with dose-adjusted etoposide, prednisone, vincristine, cyclophosphamide, and doxorubicin plus daratumumab and bortezomib. Haploidentical peripheral blood stem cell transplantation (halpo-PBSCT) was performed to achieve better disease control. The patient showed sustained partial response for six months.

Conclusion: The diagnosis of immunocompetent PBL with intraperitoneal spread before surgery and during intraoperative cryosections remains challenging. Intraperitoneal biopsy and delayed cytoreduction can prevent unnecessary tumor resection. However, a definitive treatment modality is yet to be established. Our patient responded to chemotherapy plus targeted therapy, followed by halpo-PBSCT, leading to a 6-month partial response. Our experience provides additional information on pretreatment evaluation and therapeutic considerations for patients with PBL.

Background: This study was aimed at examining the causes of death (CODs) in patients with advanced intrahepatic cholangiocarcinoma (ICC) undergoing chemotherapy (CT). In addition, machine learning models were incorporated to predict the treatment outcomes of patients with advanced ICC and identify the factors most closely related to prognosis.

Methods: A total of 5564 patients (CT group, 3632; non-CT group, 1932) were included in the Surveillance Epidemiology and End Results registries between 2000 and 2020. The CODs were compared between the two groups before and after the inverse probability of treatment weighting (IPTW). Furthermore, seven machine learning models were utilized as predictive tools to select variable features, aiming to assess the therapeutic effectiveness in patients with advanced ICC.

Results: After IPTW, the CT group exhibited a lower cumulative incidence of cholangiocarcinoma-related deaths (30%, 49%, and 73% vs. 59%, 66%, and 73%; P < 0.001), secondary malignant neoplasms (8.5%, 13%, and 20% vs. 19%, 22%, and 24%; P < 0.001), and other CODs (1.8%, 2.9%, and 4.4% vs. 4.1%, 4.6%, and 5.4%; P < 0.001) at 0.5-, 1-, and 3- years than the non-CT group, whereas the cumulative incidence of cardiovascular diseases (P = 0.4) was comparable between the two groups. Of the seven machine learning models, the random forest model showed the highest predictive effectiveness. This model verified that variables such as CT, radiotherapy, tumor dimensions, sex, and distant metastasis were strongly correlated with the prognosis of advanced ICC.

Conclusions: CT has improved the therapeutic efficacy of advanced ICC without significantly increasing other CODs. Furthermore, the analysis of various features using machine learning models has confirmed that the random forest model demonstrates the highest predictive performance.

Aim: Cholangiocarcinoma (CCA) is the most common malignant tumor of the bile ducts. Due to its anatomical location, growth pattern, and lack of clear diagnostic criteria, it presents diagnostic challenges. Exploring its occurrence and development to find early markers and treatment targets is of great significance.

Methods: To determine whether Mucin 3A (MUC3A) can regulate the occurrence and development of cholangiocarcinoma cells and its mechanism, we compared the expression levels of MUC3A between intrahepatic biliary epithelial cells and cholangiocarcinoma cells and constructed stable transfections of KONC (transfection negative control group) and MUC3A-KO1 and KO2 (transfection MUC3A knockout vectors) lentivirus in CCA cell lines. We investigated the effect of MUC3A on the proliferative capacity of cholangiocarcinoma cells using the CCK-8 assay and colony formation assay. The regulatory effect of MUC3A on the cell cycle of cholangiocarcinoma cells was examined using flow cytometry. The impact of MUC3A on the invasion and migration of cholangiocarcinoma cells was observed through scratch and Transwell assays. Additionally, the mechanism by which MUC3A regulates proliferation and metastasis of cholangiocarcinoma was explored using Western blot.

Results: MUC3A is highly expressed in cholangiocarcinoma. MUC3A promotes the proliferation of cholangiocarcinoma cells by regulating the cell cycle. Additionally, MUC3A enhances the invasion and migration of cholangiocarcinoma cells by regulating the epithelial-mesenchymal transition. Furthermore, MUC3A regulates the proliferation and metastasis of cholangiocarcinoma cells through the ERK signaling pathway.

Conclusions: This study demonstrates that MUC3A regulates the proliferation and metastasis of cholangiocarcinoma cells through the ERK signaling pathway.

Background: Gastric cancer is a leading cause of cancer deaths globally due to its often late diagnosis and poor survival rates. There's an urgent need for reliable non-invasive biomarkers for early detection. Claudin-9 (CLDN9), a protein implicated in epithelial-mesenchymal transition (EMT), has shown elevated expression in various cancers. This study investigates CLDN9's potential as a diagnostic marker for GC, with particular focus on mitochondrial pathway involvement.

Methods: The analysis of CLDN9 expression in gastric cancer was conducted and validated through immunohistochemistry using data from The Cancer Genome Atlas (TCGA) database. The identification of microRNAs regulating CLDN9 utilized machine learning techniques, such as LASSO regression and random forest algorithms. The diagnostic potential of hsa-miR-4496, a primary regulatory miRNA, was evaluated in plasma and saliva samples, with diagnostic accuracy assessed using ROC curve analysis.

Results: CLDN9 is significantly overexpressed in GC tissues and is associated with advanced stages and reduced survival rates. Immunohistochemical analysis confirmed the increased expression of CLDN9 protein in tumor tissues. Machine learning algorithms identified hsa-miR-4496 as the primary regulatory factor of CLDN9, with miRNA-regulated mRNA pathway analysis emphasizing that miRNA could exert its effects through the regulation of mitochondrial pathways. Pathway enrichment analysis highlighted mitochondrial processes as key regulatory pathways. Diagnostic evaluation of CLDN9 in plasma and saliva showed an AUC of 0.823, indicating strong diagnostic potential.

Conclusions: The results underscore the potential of CLDN9 and hsa-miR-4496 as promising non-invasive biomarkers for gastric cancer, with mitochondrial pathways being integral to their regulatory mechanisms. These biomarkers present potential for incorporation into clinical protocols, thereby facilitating early intervention and personalized treatment strategies for gastric cancer (GC).

Background: Glioma is the most common malignancy of the central nervous system, characterised by its high invasiveness and recurrence, which significantly limit therapeutic outcomes. Energy metabolism reprogramming, especially mitochondrial dysfunction, plays a pivotal role in tumour growth, survival, and progression. Mitochondria serve as the central hub for energy production and biosynthesis, adapting through alterations in oxidative phosphorylation, lipid metabolism, and the tricarboxylic acid cycle to meet the high metabolic demands of gliomas. Gancao Nourishing-Yin (GCNY) decoction, a traditional herbal compound, has demonstrated potential antitumour effects, particularly in modulating mitochondrial metabolic pathways and oxidative stress, which are critical for tumour cell adaptation.

Methods: Genomic data from the glioma GWAS dataset in the Finnish R11 database and eQTL data from 13 distinct brain regions were analysed using Summary-data-based Mendelian Randomization(SMR) to identify glioma-associated genes. MitoCarta3.0, a database of mitochondrial genes, was used to pinpoint mitochondrial-related genes. Differentially expressed genes (DEGs) in human microglial cells treated with GCNY were extracted from the GEO dataset GSE210945 and cross-referenced with SMR results to identify key genes. Colocalisation analysis, validation using the TCGA database, survival analysis, and functional annotations of mitochondrial energy pathways were performed to explore the mechanisms of action.

Results: Integration of SMR and MitoCarta3.0 identified 19 mitochondrial-related genes linked to gliomas, primarily involved in amino acid and fatty acid metabolism. Among these, CYB5R3 and PICK1 emerged as key genes with strong genetic links to glioma GWAS signals (PPH4 = 1). CYB5R3, upregulated in gliomas, was associated with enhanced oxidative phosphorylation, elevated reactive oxygen species (ROS) production, and poor survival outcomes (HR = 2.23, P < 0.001). PICK1, despite being downregulated, showed context-dependent roles in mitochondrial energy metabolism and tumour progression, with its high expression linked to worse prognosis (HR = 2.86, P < 0.001). PICK1 demonstrated moderate predictive capacity for one-year survival (AUC = 0.695).

Conclusion: This study highlights the critical roles of mitochondrial energy metabolism in glioma progression, identifying CYB5R3 and PICK1 as key regulators influenced by GCNY. By modulating mitochondrial pathways, including ROS production and oxidative phosphorylation activity, GCNY offers a novel multitarget strategy for glioma therapy. These findings underscore the importance of energy metabolism as a therapeutic target in gliomas and provide new insights into the potential of GCNY for integrated tumour management.

Background: Breast cancer is the most prevalent malignancy and the leading cause of cancer-related deaths among women worldwide. Several case reports have shown that some breast cancer patients subsequently develop acute myeloid leukemia (AML) within a short period. However, the causal relationship and pathogenic mechanisms between breast cancer and AML remain incompletely understood.

Methods: Mendelian randomization (MR) analyses were conducted to explore the bidirectional causal relationships between breast cancer and AML. Additionally, we applied the Bayesian Weighted Mendelian Randomization (BWMR) approach to validate the results of the MR analysis. Subsequently, we utilized RNA-seq data from various sources to explore the potential molecular signaling pathways between breast cancer and AML.

Results: Both IVW method and BWMR approach demonstrated that data from three distinct sources consistently indicated breast cancer as a risk factor for AML, with all sources showing statistically significant results (all P < 0.05, Odds Ratios [ORs] > 1). Bioinformatic analyses suggested that extracellular vesicle functions and p53 signaling pathway may mediate molecular links between breast cancer and AML. Using machine learning, we identified 8 genes with high diagnostic efficacy for predicting the occurrence of AML in breast cancer patients.

Conclusions: MR analyses indicated a causal relationship between breast cancer and AML. Additionally, transcriptome analysis offered a theoretical basis for understanding the potential mechanisms and therapeutic targets of AML in breast cancer patients.

Background: Pancreatic ductal adenocarcinoma (PDA) is a highly aggressive and fatal cancer. M1 macrophages are generally considered to have anti-tumor properties, capable of suppressing tumor growth and metastasis by secreting pro-inflammatory cytokines and enhancing the immune response.

Aims: The objective of this research was to pinpoint crucial genes associated with M1 macrophages and search for a new way to activate the M1 phenotype of macrophages in PDA.

Methods: The level of immune cell infiltration was assessed using CIBERSORT in TCGA-PAAD cohort and ICGC-PACA cohort. We performed weighted gene co-expression network analysis (WGCNA) to identify the module most correlated with M1 macrophages and we identified hub genes through protein-protein interaction (PPI) analyse. Through survival analysis, correlation analysis and single cell analysis, we obtained the relationship between hub genes and prognosis, and the relationship between key genes and immune cells, as well as its expression in various cells.

Results: PRSS1 (Cationic trypsinogen) and CTRB1 (Chymosinogen B) were hub genes of the M1 macrophage-associated WGCNA module (211genes) and are closely related to the extension of survival time, which are also verified as cell growth-related genes by DepMap database. Through single-cell sequencing analysis, we determined that the expression levels of PRSS1 and CTRB1 in the acinar cells of tumor tissues were diminished. PRSS1 and CTRB1 are considered to be the signature genes of acinar cells. The proportion of acinar cells was also correlated with the infiltration of CD8T cells and M1 cells. Immunostaining revealed elevated expression levels of PRSS1 and CTRB1 in adjacent normal tissues. Cell line experiments confirmed that macrophages polarize towards M1 by engulfing pancreatic enzyme granules, thereby inhibiting the malignant phenotype of tumor cells.

Conclusion: Our findings highlight the critical role of acinar cells in modulating the immune microenvironment of pancreatic tumors by influencing macrophage polarization. This insight may provide novel opportunities for therapeutic interventions in cancer treatment.