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. 2023 Nov 14:14:1266265.
doi: 10.3389/fimmu.2023.1266265. eCollection 2023.

EBF1, MYO6 and CALR expression levels predict therapeutic response in diffuse large B-cell lymphomas

Alice Turdo #  1 , Miriam Gaggianesi #  2 , Caterina D'Accardo  1 , Gaetana Porcelli  1 , Sebastiano Di Bella  2 , Dario Cricchio  2 , Irene Pillitteri  1 , Rossana Porcasi  1 , Melania Lo Iacono  1 , Francesco Verona  1 , Chiara Modica  2 , Narges Roozafzay  1 , Ada Maria Florena  1 , Giorgio Stassi  2 , Salvatrice Mancuso #  1 , Matilde Todaro #  1   3
Affiliations

EBF1, MYO6 and CALR expression levels predict therapeutic response in diffuse large B-cell lymphomas

Alice Turdo et al. Front Immunol. .

Abstract

Background: Diffuse large B-cell lymphoma (DLBCL) is a hematological malignancy representing one-third of non-Hodgkin's lymphoma cases. Notwithstanding immunotherapy in combination with chemotherapy (R-CHOP) is an effective therapeutic approach for DLBCL, a subset of patients encounters treatment resistance, leading to low survival rates. Thus, there is an urgent need to identify predictive biomarkers for DLBCL including the elderly population, which represents the fastest-growing segment of the population in Western countries.

Methods: Gene expression profiles of n=414 DLBCL biopsies were retrieved from the public dataset GSE10846. Differentially expressed genes (DEGs) (fold change >1.4, p-value <0.05, n=387) have been clustered in responder and non-responder patient cohorts. An enrichment analysis has been performed on the top 30 up-regulated genes of responder and non-responder patients to identify the signatures involved in gene ontology (MSigDB). The more significantly up-regulated DEGs have been validated in our independent collection of formalin-fixed paraffin-embedded (FFPE) biopsy samples of elderly DLBCL patients, treated with R-CHOP as first-line therapy.

Results: From the analysis of two independent cohorts of DLBCL patients emerged a gene signature able to predict the response to R-CHOP therapy. In detail, expression levels of EBF1, MYO6, CALR are associated with a significant worse overall survival.

Conclusions: These results pave the way for a novel characterization of DLBCL biomarkers, aiding the stratification of responder versus non-responder patients.

Keywords: R-CHOP; biomarkers of response; diffuse large B-cell lymphoma; elderly patients; gene expression signature; therapy resistance.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Figures

Figure 1
Figure 1
Gene expression analysis of a large cohort of DLBCL patients reveal a gene signature associated to prognosis. (A) Workflow chart indicating the process to select DLBCL responder and non-responder gene signatures in the training cohort of the GSE10846 database. (B) Heatmap of differential expressed genes (DEGs) (fold change >1.4, p-value <0.05, κ=387) in responder versus non responders DLBCL patients. The LDH levels and the molecular subtype classification are shown. (C) Top ten up-regulated genes (log2) in responder (blue) and non-responder (orange) DLBCL patient cohort. (D) Enrichment analysis in gene ontology (MSigDB) in responder and non-responder DLBCL patient cohort. (E) Protein network analysis, generated with DEGs listed in Supplementary Table 1 The networks were generated through the use of QIAGEN IPA (QIAGEN Inc., https://digitalinsights.qiagen.com/IPA), in responder and non-responder DLBCL patient cohort.
Figure 2
Figure 2
EBF1 and MYO6 result highly expressed in responder DLBCL patients whilst CALR high expression characterize non responder DLBCL patients. (A) Workflow chart indicating the validation of the identified signature in our cohort of FFPE DLBCL samples. (B) Absolute mRNA levels (copies/µl) of EBF1, MYO6 and CALR in responder and non-responder DLBCL patients (n=19). Data are represented as mean  ±  SEM of three independent experiments. (C) Representative droplet digital PCR (ddPCR) scatter plots showing single, double, triple or quadruple positive droplets for EBF1, MYO6, CALR and CWF19L1 of FFPE samples of responder (pt#1) and non-responder DLBCL patient (pt#14). (D) Representative IHC analysis for EBF1, MYO6 and CALR of patients as in (C) Scale bar is 100 µm.
Figure 3
Figure 3
Expression of EBF1, MYO6 and CALR correlate with prognosis in DLBCL. (A) Kaplan Meier overall survival (OS) curves of elderly DLBCL patients (GSE10846) stratified by high or low EBF1, MYO6 and CALR expression levels. (B) Functional protein association network of EBF1, MYO6 and CALR based on STRING database.
Figure 4
Figure 4
EBF1, MYO6 and CALR characterize DLBCL as compared to normal lymphoid tissues. (A) RNA seq expression data of EBF1, MYO6 and CALR in DLBCL patients at different age, retrieved from the TCGA database and analyzed by UALCAN. (B) Kaplan Meier overall survival (OS) curves of adult DLBCL patients (<65-year-old) (GSE10846) stratified by high or low EBF1, MYO6 and CALR expression levels. N/A stands for not available.
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