Background. Diffuse large B cell lymphoma (DLBCL) is a life-threatening malignant tumor characterized by heterogeneous clinical, phenotypic, and molecular manifestations. Given the association between immunity and tumors, identifying a suitable immune biomarker could improve DLBCL diagnosis. Methods. We systematically searched for DLBCL gene expression microarray datasets from the GEO database. Immune-related genes (IRGs) were obtained from the ImmPort database, and 318 transcription factor (TF) targets in cancer were retrieved from the Cistrome Cancer database. An immune-related classifier for DLBCL prognosis was constructed using Cox regression and LASSO analysis. To assess differences in overall survival between the low- and high-risk groups, we analyzed the tumor microenvironment (TME) and immune infiltration in DLBCL using the ESTIMATE and CIBERSORT algorithms. WGCNA was applied to study the molecular mechanisms explaining the clinical significance of our immune-related classifier and TFs. Results. Eighteen IRGs were selected to construct the classifier. The multi-IRG classifier showed powerful predictive ability. Patients with a high-risk score had poor survival. Based on the AUC for three- and five-year survival, the classifier exhibited better predictive power than clinical data. Discrepancies in overall survival between the low- and high-risk score groups might be explained by differences in immune infiltration, TME, and transcriptional regulation. Conclusions. Our study describes a novel prognostic IRG classifier with strong predictive power in DLBCL. Our findings provide valuable guidance for further analysis of DLBCL pathogenesis and clinical treatment.
Background: Acute myeloid leukemia (AML) is a devastating malignancy with great heterogeneity, novel prognostic biomarkers and therapy targets are needed to improve the precise management of AML patients. Increasing evidence has shown the role of RPL34, a ribosomal protein, in tumorigenesis and progression. However, the detailed expression status and clinical significance of RPL34 in AML are largely unknown. Methods: The expression level of RPL34 was detected in bone marrow samples from both AML patients and AML cell lines. Then using recombinant shRNA-lentiviral vector, we analyzed the impact of RPL34 knockdown on cell proliferation, apoptosis and cell cycle distribution. Lastly, by analyzing public gene expression datasets (GSE12417 and GSE2191), we determined the prognostic role of RPL34 in AML. Results: The mRNA level of RPL34 was significantly elevated in AML bone marrow samples and cell lines. Patients with high level of RPL34 had inferior survival outcomes than their counterparts, and upregulation of RPL34 may mediate chemoresistance in AML. Through knockdown of RPL34 in HL-60 cell line, we found cell proliferation was inhibited, cell apoptosis was triggered, and cell cycle was arrested in S phase. Conclusions: The present study demonstrated that downregulation of RPL34 could inhibit cell proliferation, promote cell apoptosis, and induce cell cycle arrest in AML cell line HL-60. Also, its expression and clinical significance in AML patients was confirmed. All these findings suggest that RPL34 may be a potential novel therapy target in AML.
Ferroptosis is a unique way of regulating cell death (RCD), which is quite different from other programmed cell deaths such as autophagy. It presents iron overload, accumulation of reactive oxygen species (ROS), and lipid peroxidation. A ferroptotic cell usually has an intact cell structure as well as shrinking mitochondria with decreased or vanishing cristae, concentrated membrane density, and ruptured outer membrane. Recently, increasing investigations have discovered that tumor cells have a much greater iron demand than the normal ones, making them more sensitive to ferroptosis. In other words, ferroptosis may inhibit the progress of the tumor, which can be used in the therapy of tumor patients, especially for those with chemotherapy resistance. Therefore, ferroptosis has become one hot spot in the field of tumor research in recent years. Colorectal cancer (CRC) is one common type of gastrointestinal malignancy. The incidence of CRC appears to have an upward trend year by year since the enhancement of living standards. Although surgery and chemoradiotherapy have largely improved the prognosis of patients with CRC, some patients still appear to have severe adverse reactions and drug resistance. Moreover, much research has verified that ferroptosis has a necessary association with the occurrence and progression of gastrointestinal tumors. In this review, we provide a comprehensive evaluation of the main mechanisms of iron metabolism, lipid metabolism, and amino acid metabolism involved in the occurrence of ferroptosis, as well as the research progress of ferroptosis in CRC.
As the most common subtype of non-Hodgkin's lymphoma, diffuse large B-cell lymphoma (DLBCL) is characterized by a huge degree of clinical and prognostic heterogeneity. Currently, there is an urgent need for highly specific and sensitive biomarkers to predict the therapeutic response of DLBCL and assess which patients can benefit from systemic chemotherapy to help develop more precise therapeutic regimens for DLBCL. Systems biology (holistic study of diseases) is more comprehensive in quantifying and identifying biomarkers, helps addressing major biological problems, and possesses high accuracy and sensitivity. In this article, we provide an overview of research advances in DLBCL prognostic biomarkers made using the multi-omics approach of genomics, transcriptomics, epigenetics, proteomics, metabonomics, radiomics, and the currently developing single-cell technologies.
This article is aimed at exploring the relationship between the phosphatase 2A catalytic subunit Cα (PP2Acα, encoded by PPP2CA) and methyltransferase-like 3 (METTL3) in the malignant progression of gastric cancer (GC). Through analyzing the bioinformatics database and clinical tissue immunohistochemistry results, we found that abnormal PP2Acα and METTL3 levels were closely related to the malignant progression of GC. To explore the internal connection between PP2Acα and METTL3 in the progression of GC, we carried out cellular and molecular experiments and finally proved that PP2Acα inhibition can upregulate METTL3 levels by activating ATM activity, thereby promoting the malignant progression of GC.
Background: Colorectal cancer (CRC) is one gastrointestinal malignancy, accounting for 10% of cancer diagnoses and cancer-related deaths worldwide each year. Therefore, it is urgent to identify genes involved in CRC predicting the prognosis.Methods: CRC’s data were acquired from the Gene Expression Omnibus (GEO) database (GSE39582 and GSE41258 datasets) and The Cancer Genome Atlas (TCGA) database. The differentially expressed necroptosis-related genes (DENRGs) were sorted out between tumor and normal tissues. Univariate Cox regression analysis and least absolute shrinkage and selectionator operator (LASSO) analysis were applied to selected DENRGs concerning patients’ overall survival and to construct a prognostic biomarker. The effectiveness of this biomarker was assessed by the Kaplan–Meier curve and the receiver operating characteristic (ROC) analysis. The GSE39582 dataset was utilized as external validation for the prognostic signature. Moreover, using univariate and multivariate Cox regression analyses, independent prognostic factors were identified to construct a prognostic nomogram. Next, signaling pathways regulated by the signature were explored through the gene set enrichment analysis (GSEA). The single sample gene set enrichment analysis (ssGSEA) algorithm and tumor immune dysfunction and exclusion (TIDE) were used to explore immune correlation in the two groups, high-risk and low-risk ones. Finally, prognostic genes’ expression was examined in the GSE41258 dataset.Results: In total, 27 DENRGs were filtered, and a necroptosis-related prognostic signature based on 6 DENRGs was constructed, which may better understand the overall survival (OS) of CRC. The Kaplan–Meier curve manifested the effectiveness of the prognostic signature, and the ROC curve showed the same result. In addition, univariate and multivariate Cox regression analyses revealed that age, pathology T, and risk score were independent prognostic factors, and a nomogram was established. Furthermore, the prognostic signature was most significantly associated with the apoptosis pathway. Meanwhile, 24 immune cells represented significant differences between two groups, like the activated B cell. Furthermore, 32 immune checkpoints, TIDE scores, PD-L1 scores, and T-cell exclusion scores were significantly different between the two groups. Finally, a 6-gene prognostic signature represented different expression levels between tumor and normal samples significantly in the GSE41258 dataset.Conclusion: Our study established a signature including 6 genes and a prognostic nomogram that could significantly assess the prognosis of patients with CRC.
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