An alpha-enolase-related signature predicts prognosis risk and therapeutic response in diffuse large B-cell lymphoma
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ABSTRACT:
ORGANISM(S): Homo Sapiens
SUBMITTER: 
Haina Wang
PROVIDER: PXD061736 | iProX | Wed Mar 12 00:00:00 GMT 2025
REPOSITORIES: iProX
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Project description:Kinesin family member 2A (KIF2A), a conserved motor protein, plays a critical role in the pathogenesis and prognosis of several malignant tumors. The aim of the present study was to investigate KIF2A expression in diffuse large B cell lymphoma (DLBCL), evaluate the association between KIF2A expression and the clinical parameters of the disease, and determine its prognostic value. KIF2A expression was evaluated in 134 DLBCL and 57 reactive hyperplasia samples using immunohistochemistry on a tissue microarray. The correlations between KIF2A expression with clinical parameters and prognosis were estimated using univariate and multivariate analyses. The expression of KIF2A was significantly higher in DLBCL tissue samples compared with those from subjects with reactive hyperplasia (P=0.002). Furthermore, increased expression of KIF2A protein in DLBCL was related to Ann Arbor stage (P=0.027) and international prognostic index (IPI) score (P=0.01). The survival analysis showed that KIF2A expression (P=0.016), serum LDH level (P=0.049), and IPI score (P<0.001) were independent prognostic markers for DLBCL. Our findings also confirmed that downregulating KIF2A expression decreased tumor cell viability, accompanied by downregulation of pAKT levels. Taken together, these data provide the first evidence that increased KIF2A expression predicts poor prognosis in patients with DLBCL, and a rationale for treatment of DLBCL by targeting KIF2A.
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Project description:Diffuse large B cell lymphoma (DLBCL) exhibits a tightly complexity immune landscape. In this study, we intended to identify different immune phenotype and to examine the immune related mRNA signature for clinical characteristic, therapeutic responsiveness as well as risk stratification and survival prediction in DLBCL. We identified two immune infiltration subtypes of DLBCL patients based on 28 immune cell types. GSEA analysis uncovered the concordant classification of two robust significant subtypes of DLBCL. Considering the convenient application of the immune infiltration subtypes for prognostic prediction, we developed a risk score based on the differentially expressed genes between the Immunity-H and Immunity-L groups. By a least absolute shrinkage and selection operator (LASSO)-Cox regression model, a sixteen-gene risk signature, comprising ANTXR1, CD3D, TIMP1, FPR3, NID2, CTLA4, LPAR6, GPR183, LYZ, PTGDS, ITK, FBN1, FRMD6, PLAU, MICAL2, C1S, was established. The comprehensive results showed that the high-risk group was correlated with lower immune infiltration, more aggressive phenotypes, lower overall survival and more sensitive to lenalidomide. In contrast, a low-risk group score was associated with higher immune infiltration, less aggressive phenotypes, better overall survival and more likely to benefit from PD-1/PD-L1 inhibitors. Finally, a nomogram comprised of the risk score and IPI score was verified to more accurately predict the overall survival of DLBCL than traditional clinical prediction models. Altogether, our data demonstrate the heterogeneity of immune patterns within DLBCL and deepen our molecular understanding of this tumor entity.
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Project description:Diffuse large B-cell lymphoma (DLBCL) is a disease with heterogeneous outcome. Stromal signatures have been correlated to survival in DLBCL. Their use, however, is hampered by the lack of assays for formalin-fixed paraffin-embedded material (FFPE). We constructed a lymphoma-associated macrophage interaction signature (LAMIS) interrogating features of the microenvironment using a NanoString assay applicable to FFPE. The clinical impact of the signature could be validated in a cohort of 466 patients enrolled in prospective clinical trials of the German High-Grade Non-Hodgkin Lymphoma Study Group (DSHNHL). Patients with high expression of the signature (LAMIShigh) had shorter EFS, PFS, and OS. Multivariate analyses revealed independence from IPI factors in EFS (HR 1.7, 95% CI 1.2–2.4, p-value = 0.001), PFS (HR 1.8, 95% CI 1.2–2.5, p-value = 0.001) and OS (HR 1.8, 95% CI 1.3–2.7, p-value = 0.001). Multivariate analyses adjusted for the IPI factors showed the signature to be independent from COO, MYC rearrangements and double expresser status (DE). LAMIShigh and simultaneous DE status characterized a patient subgroup with dismal prognosis and early relapse. Our data underline the importance of the microenvironment in prognosis. Combined analysis of stromal features, the IPI and DE may provide a new rationale for targeted therapy.
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Project description:BackgroundDiffuse large B-cell lymphoma (DLBCL) is the most common type of lymphoma which possess highly aggressive and heterogeneous. Despite advances in understanding heterogeneity and development of novel targeted agents, the prognosis of DLBCL patients remains unsatisfied. Lipids are crucial components of biological membranes and signal transduction while accumulating evidence has supported the vital roles of abnormal lipid metabolism in tumorigenesis. Furthermore, some related pathways could serve as prognostic biomarkers and potential therapeutic targets. However, the clinical significance of abnormal lipid metabolism reprogramming in DLBCL has not been investigated. In the current study, we developed a prognostic risk model for DLBCL based on the abnormal expressed lipid metabolism genes and moreover based on our risk model we classified patients with DLBCL into novel subtypes and identified potential drugs for DLBCL patients with certain lipid metabolism profiles.MethodsWe utilized univariate Cox regression analysis to identify the prognosis-related lipid metabolism genes, and then performed LASSO Cox regression to identify prognostic related lipid metabolism related genes. Multivariate cox regression was used to establish the prognostic model. Patients were divided in to high and low risk groups based on the median risk score. Immune cell infiltration and GSEA were used to identify the pathways between high and low risk groups. Oncopredict algorithm was utilized to identify potential drug for high-risk patients. In vitro cell apoptosis and viability analysis were employed to verify the specific tumor inhibition effects of AZD5153.ResultsNineteen survival related lipid metabolism genes TMEM176B, LAYN, RAB6B, MMP9, ATAD3B, SLC2A11, CD3E, SLIT2, SLC2A13, SLC43A3, CD6, SIRPG, NEK6, LCP2, CTTN, CXCL2, SNX22, BCL6 and FABP4 were identified and subjected to build the prognostic model which was further verified in four external microarray cohorts and one RNA seq cohorts. Tumor immune microenvironment analysis and GSEA results showed that the activation of MYC targets genes rather than immunosuppression contribute to the poor survival outcome of patients in the high-risk group. AZD5153, a novel bivalent BET bromodomain inhibitor which could inhibit the transcription of MYC and E2F exhibited specific antitumor function for cells with high-risk score.ConclusionsOur results provide the first lipid metabolism-based gene signature for predicting the survival of patients with DLBCL. Furthermore, by determining novel subtypes with our lipid metabolism prognostic model we illustrated that drugs that compromising MYC target genes rather than immune checkpoint inhibitors may be beneficial to DLBCL patients with certain lipid metabolism profiles.
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Project description:Primary gastrointestinal diffuse large B-cell lymphoma (PGI-DLBCL) is a highly heterogeneous type of non-Hodgkin lymphoma. A number of studies have demonstrated that microRNA-130a (miR-130a) serves a role in the tumorigenesis and prognosis of numerous human tumors. However, to the best of our knowledge, the prognostic significance of miR-130a in PGI-DLBCL remains unknown. The present study explored the association between miR-130a and the clinical outcomes of PGI-DLBCL. Relative miR-130a expression was assessed by reverse transcription-quantitative PCR. Immunohistochemistry was used to detect expression levels of BCL-2, c-MYC, neprilysin, B-cell lymphoma 6 protein, PWWP domain-containing DNA repair factor 3A and proliferation marker protein Ki-67. A receiver operating characteristic curve was constructed to analyze the specificity and sensitivity of microRNA levels in the diagnosis of PGI-DLBCL. Survival curves were constructed using the Kaplan-Meier method. In the present study, miR-130a expression was notably higher in patients with PGI-DLBCL compared with in the controls (P<0.0001). miR-130a overexpression was closely associated with a high International Prognostic Index score (3–5) and drug resistance (P=0.017 and P=0.044, respectively). No significant difference in other clinical features was observed. Patients with increased expression levels of miR-130a had lower overall survival [hazard ratio (HR), 2.998; 95% CI, 1.347-6.673; P=0.007] and progression-free survival (HR, 3.325; 95% CI, 1.488-7.429; P=0.003) compared with patients who had lower expression levels of miR-130a. Furthermore, multivariate Cox regression analysis suggested that miR-130a was a negative prognostic parameter in PGI-DLBCL. Therefore, upregulation of miR-130a could become a potential prognostic marker for PGI-DLBCL. Additionally, further study of these results may have important guiding significance for the prognosis of patients with PGI-DLBCL in the clinical setting.
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Project description:Diffuse large B-cell lymphoma (DLBCL), the most common subtype of non-Hodgkin's lymphoma, is clinically heterogeneous: 40% of patients respond well to current therapy and have prolonged survival, whereas the remainder succumb to the disease. We proposed that this variability in natural history reflects unrecognized molecular heterogeneity in the tumors. Using DNA microarrays, we have conducted a systematic characterization of gene expression in B-cell malignancies. Here we show that there is diversity in gene expression among the tumors of DLBCL patients, apparently reflecting the variation in tumor proliferation rate, host response and differentiation state of the tumor. We identified two molecularly distinct forms of DLBCL which had gene expression patterns indicative of different stages of B-cell differentiation. One type expressed genes characteristic of germinal center B cells ('germinal center B-like DLBCL'); the second type expressed genes normally induced during in vitro activation of peripheral blood B cells ('activated B-like DLBCL'). Patients with germinal center B-like DLBCL had a significantly better overall survival than those with activated B-like DLBCL. The molecular classification of tumors on the basis of gene expression can thus identify previously undetected and clinically significant subtypes of cancer. This study is described more fully in Alizadeh AA et al.(2000) Nature 403:503-11
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