CD5 expression correlates with inferior survival and enhances the negative effect of p53 overexpression in diffuse large B‐cell lymphoma

Zhao, Peiqi; Li, Lanfang; Zhou, Shunhua; Qiu, Lihua; Zheng, Qian; Liu, Xianming; Meng, Bin; Zhang, Huilai

doi:10.1002/hon.2657

Cited by 19 publications

(15 citation statements)

References 39 publications

(72 reference statements)

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“…For c‐MYC IHC, the UltraView™ Universal DAB Detection Kit (Ventana Medical Systems Inc., Tucson, AZ, USA) was used to increase the staining intensity. The cut‐off for c‐MYC positivity was more than 40% of tumour cells showing immunoreactivity, whereas thresholds for BCL2, p53, CD5, and CD23 were more than 50%, in accordance with previously established cut‐offs [ 31 , 33 , 37 , 38 ]. For Ki67, results were rendered semi‐quantitatively on a scale from 1 to 4+, according to the percentage of positive cells (1+ [1–25%], 2+ [26–50%], 3+ [51–75%], and 4+ [76–100%]) [ 18 ].…”

Section: Methodssupporting

confidence: 86%

“…Moreover, some studies showed that p53 overexpression enhances c‐MYC‐related adverse effects in DLBCL, identifying a high risk of relapse subgroup of patients co‐expressing c‐MYC and p53 [ 34 , 36 ]. Other IHC biomarkers can also be used, such as CD5 and CD23, which are positive in 5–10% of DLBCL [ 37 , 38 ] but their significance still remains controversial. On one hand, CD23 is expressed on naïve B cells and follicular dendritic cells and its overexpression has been associated with unfavourable outcomes in DLBCL [ 38 , 39 ].…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, CD5 is expressed on normal T cells but as it is also positive in other lymphoid malignancies (chronic lymphocytic leukaemia and Mantle cell lymphoma), further analyses (Cyclin D1 and SOX11) are needed to exclude these differential diagnoses. De novo CD5‐positive DLBCL seems to be associated with adverse clinical and biological features [ 40 ] and with poorer OS and progression‐free survival (PFS) after chemotherapy compared to CD5‐negative DLBCL [ 37 , 41 ].…”

Section: Introductionmentioning

confidence: 99%

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c‐MYC and p53 expression highlight starry‐sky pattern as a favourable prognostic feature in R‐CHOP‐treated diffuse large B‐cell lymphoma

Bouroumeau

Bussot

Bonnefoix

et al. 2021

The Journal of Pathology CR

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Diffuse large B‐cell lymphoma (DLBCL) is a clinically heterogeneous entity, in which the first‐line treatment currently consists of an immuno‐chemotherapy regimen (R‐CHOP). However, around 30% of patients will not respond or will relapse. Overexpression of c‐MYC or p53 is frequently found in DLBCL, but an association with prognosis remains controversial, as for other biomarkers previously linked with DLBCL aggressivity (CD5, CD23, or BCL2). The aim of this study was to explore the expression of these biomarkers and their correlation with outcome, clinical, or pathological features in a DLBCL cohort. Immunohistochemical (c‐MYC, p53, BCL2, CD5, and CD23), morphological (‘starry‐sky’ pattern [SSP]), targeted gene panel sequencing by next‐generation sequencing (NGS), and fluorescence in situ hybridisation analyses were performed on tissue microarray blocks for a retrospective cohort of 94 R‐CHOP‐treated de novo DLBCL. In univariate analyses, p53 overexpression (p53high) was associated with unfavourable outcome (p = 0.04) and with c‐MYC overexpression (p = 0.01), whereas c‐MYC overexpression was linked with an SSP (p = 0.004), but only tended towards an inferior prognosis (p = 0.06). Presence of a starry‐sky morphology was found to be correlated with better survival in p53high DLBCL (p = 0.03) and/or c‐MYC‐positive DLBCL (p = 0.002). Furthermore, NGS data revealed that these three variables were associated with somatic mutations (PIM1, TNFRSF14, FOXO1, and B2M) involved in B‐cell proliferation, survival, metabolism, and immune signalling. Taken together, these results show that the SSP pattern seems to be a protective factor in high‐risk DLBCL subgroups and highlight cell death as a built‐in failsafe mechanism to control tumour growth.

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Section: Methodssupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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c‐MYC and p53 expression highlight starry‐sky pattern as a favourable prognostic feature in R‐CHOP‐treated diffuse large B‐cell lymphoma

Bouroumeau

Bussot

Bonnefoix

et al. 2021

The Journal of Pathology CR

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“…Therefore, poor prognosis was presented in cancer survivors with high expression of CA5R1 (46)(47)(48)(49). CD5 was identified as a prognostic factor in large B-cell lymphoma with increased expression correlated to inferior survival (50). However, the expression of CD86, CA5R1, and CD5 seemed to be downregulated in the high-risk group, which could be due to the uniqueness of TME in the brain.…”

Section: Discussionmentioning

confidence: 99%

A Prognostic Microenvironment-Related Immune Signature via ESTIMATE (PROMISE Model) Predicts Overall Survival of Patients With Glioma

Qiu

Cheng

et al. 2020

Front. Oncol.

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ObjectiveIn the development of immunotherapies in gliomas, the tumor microenvironment (TME) needs to be investigated. We aimed to construct a prognostic microenvironment-related immune signature via ESTIMATE (PROMISE model) for glioma.MethodsStromal score (SS) and immune score (IS) were calculated via ESTIMATE for each glioma sample in the cancer genome atlas (TCGA), and differentially expressed genes (DEGs) were identified between high-score and low-score groups. Prognostic DEGs were selected via univariate Cox regression analysis. Using the lower-grcade glioma (LGG) data set in TCGA, we performed LASSO regression based on the prognostic DEGs and constructed a PROMISE model for glioma. The model was validated with survival analysis and the receiver operating characteristic (ROC) in TCGA glioma data sets (LGG, glioblastoma multiforme [GBM] and LGG+GBM) and Chinese glioma genome atlas (CGGA). A nomogram was developed to predict individual survival chances. Further, we explored the underlying mechanisms using gene set enrichment analysis (GSEA) and Cibersort analysis of tumor-infiltrating immune cells between risk groups as defined by the PROMISE model.ResultsWe obtained 220 upregulated DEGs and 42 downregulated DEGs in both high-IS and high-SS groups. The Cox regression highlighted 155 prognostic DEGs, out of which we selected 4 genes (CD86, ANXA1, C5AR1, and CD5) to construct a PROMISE model. The model stratifies glioma patients in TCGA as well as in CGGA with distinct survival outcome (P<0.05, Hazard ratio [HR]>1) and acceptable predictive accuracy (AUCs>0.6). With the nomogram, an individualized survival chance could be predicted intuitively with specific age, tumor grade, Isocitrate dehydrogenase (IDH) status, and the PROMISE risk score. ROC showed significant discrimination with the area under curves (AUCs) of 0.917 and 0.817 in TCGA and CGGA, respectively. GSEA between risk groups in both data sets were significantly enriched in multiple immune-related pathways. The Cibersort analysis highlighted four immune cells, i.e., CD 8 T cells, neutrophils, follicular helper T (Tfh) cells, and Natural killer (NK) cells.ConclusionsThe PROMISE model can further stratify both LGG and GBM patients with distinct survival outcomes.These findings may help further our understanding of TME in gliomas and shed light on immunotherapies.

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“…Currently, various markers are defined through immunophenotyping, such as CD5, CD30, BCL2, MYC, and TP53 ( Pierce and Mehta, 2017 ; Zhao et al, 2019 ). CD5 promotes downstream B-cell receptor signaling, is associated with ABC subtype and more aggressive clinical traits.…”

Section: Introductionmentioning

confidence: 99%

Whole Transcriptome Data Analysis Reveals Prognostic Signature Genes for Overall Survival Prediction in Diffuse Large B Cell Lymphoma

et al. 2021

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BackgroundWith the improvement of clinical treatment outcomes in diffuse large B cell lymphoma (DLBCL), the high rate of relapse in DLBCL patients is still an established barrier, as the therapeutic strategy selection based on potential targets remains unsatisfactory. Therefore, there is an urgent need in further exploration of prognostic biomarkers so as to improve the prognosis of DLBCL.MethodsThe univariable and multivariable Cox regression models were employed to screen out gene signatures for DLBCL overall survival (OS) prediction. The differential expression analysis was used to identify representative genes in high-risk and low-risk groups, respectively, where student t test and fold change were implemented. The functional difference between the high-risk and low-risk groups was identified by the gene set enrichment analysis.ResultsWe conducted a systematic data analysis to screen the candidate genes significantly associated with OS of DLBCL in three NCBI Gene Expression Omnibus (GEO) datasets. To construct a prognostic model, five genes (CEBPA, CYP27A1, LST1, MREG, and TARP) were then screened and tested using the multivariable Cox model and the stepwise regression method. Kaplan–Meier curve confirmed the good predictive performance of this five-gene Cox model. Thereafter, the prognostic model and the expression levels of the five genes were validated by means of an independent dataset. High expression levels of these five genes were significantly associated with favorable prognosis in DLBCL, both in training and validation datasets. Additionally, further analysis revealed the independent value and superiority of this prognostic model in risk prediction. Functional enrichment analysis revealed some vital pathways responsible for unfavorable outcome and potential therapeutic targets in DLBCL.ConclusionWe developed a five-gene Cox model for the clinical outcome prediction of DLBCL patients. Meanwhile, potential drug selection using this model can help clinicians to improve the clinical practice for the benefit of patients.

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CD5 expression correlates with inferior survival and enhances the negative effect of p53 overexpression in diffuse large B‐cell lymphoma

Cited by 19 publications

References 39 publications

c‐MYC and p53 expression highlight starry‐sky pattern as a favourable prognostic feature in R‐CHOP‐treated diffuse large B‐cell lymphoma

c‐MYC and p53 expression highlight starry‐sky pattern as a favourable prognostic feature in R‐CHOP‐treated diffuse large B‐cell lymphoma

A Prognostic Microenvironment-Related Immune Signature via ESTIMATE (PROMISE Model) Predicts Overall Survival of Patients With Glioma

Whole Transcriptome Data Analysis Reveals Prognostic Signature Genes for Overall Survival Prediction in Diffuse Large B Cell Lymphoma

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