Large-Scale Proteomic Analysis of Follicular Lymphoma Reveals Extensive Remodeling of Cell Adhesion Pathway and Identifies Hub Proteins Related to the Lymphomagenesis

Characterization of Human B Cell Hematological Malignancies Using Protein-Based Approaches

The maturation of B cells is a complex, multi-step process. During B cell differentiation, errors can occur, leading to the emergence of aberrant versions of B cells that, finally, constitute a malignant tumor. These B cell malignancies are classified into three main groups: leukemias, myelomas, and lymphomas, the latter being the most heterogeneous type. Since their discovery, multiple biological studies have been performed to characterize these diseases, aiming to define their specific features and determine potential biomarkers for diagnosis, stratification, and prognosis. The rise of advanced -omics approaches has significantly contributed to this end. Notably, proteomics strategies appear as promising tools to comprehensively profile the final molecular effector of these cells. In this narrative review, we first introduce the main B cell malignancies together with the most relevant proteomics approaches. Then, we describe the core studies conducted in the field and their main findings and, finally, we evaluate the advantages and drawbacks of flow cytometry, mass cytometry, and mass spectrometry for the profiling of human B cell disorders.

Proteomics identifies apoptotic markers as predictors of histological transformation in patients with follicular lymphoma

Follicular lymphoma (FL) is an indolent lymphoma with a generally favorable prognosis. However, histological transformation (HT) to a more aggressive disease leads to markedly inferior outcomes. This study aims to identify biological differences predictive of HT at the time of initial FL diagnosis. We show differential protein expression between diagnostic lymphoma samples from patients with subsequent HT (subsequently-transforming FL [st-FL]; n = 20) and patients without HT (nontransforming FL [nt-FL]; n = 34) by label-free quantification nano liquid chromatography-tandem mass spectrometry analysis. Protein profiles identified patients with high risk of HT. This was accompanied by disturbances in cellular pathways influencing apoptosis, the cytoskeleton, cell cycle, and immune processes. Comparisons between diagnostic st-FL samples and paired transformed FL (n = 20) samples demonstrated differential protein profiles and disrupted cellular pathways, indicating striking biological differences from the time of diagnosis up to HT. Immunohistochemical analysis of apoptotic proteins, CASP3, MCL1, BAX, BCL-xL, and BCL-rambo, confirmed higher expression levels in st-FL than in nt-FL samples (P < .001, P = .015, P = .003, P = .025, and P = .057, respectively). Moreover, all 5 markers were associated with shorter transformation-free survival (TFS; P < .001, P = .002, P < .001, P = .069, and P = .010, respectively). Notably, combining the expression of these proteins in a risk score revealed increasingly inferior TFS with an increasing number of positive markers. In conclusion, proteomics identified altered protein expression profiles (particularly apoptotic proteins) at the time of FL diagnosis, which predicted later transformation.

MALAT1 expression is associated with aggressive behavior in indolent B-cell neoplasms

MALAT1 long non-coding RNA has oncogenic roles but has been poorly studied in indolent B-cell neoplasms. Here, MALAT1 expression was analyzed using RNA-seq, microarrays or qRT-PCR in primary samples from clinico-biological subtypes of chronic lymphocytic leukemia (CLL, n = 266), paired Richter transformation (RT, n = 6) and follicular lymphoma (FL, n = 61). In peripheral blood (PB) CLL samples, high MALAT1 expression was associated with a significantly shorter time to treatment independently from other known prognostic factors. Coding genes expressed in association with MALAT1 in CLL were predominantly related to oncogenic pathways stimulated in the lymph node (LN) microenvironment. In RT paired samples, MALAT1 levels were lower, concordant with their acquired increased independency of external signals. Moreover, MALAT1 levels in paired PB/LN CLLs were similar, suggesting that the prognostic value of MALAT1 expression in PB is mirroring expression differences already present in LN. Similarly, high MALAT1 expression in FL predicted for a shorter progression-free survival, in association with expression pathways promoting FL pathogenesis. In summary, MALAT1 expression is related to pathophysiology and more aggressive clinical behavior of indolent B-cell neoplasms. Particularly in CLL, its levels could be a surrogate marker of the microenvironment stimulation and may contribute to refine the clinical management of these patients.

Identification of potential dilated cardiomyopathy-related targets by meta-analysis and co-expression analysis of human RNA-sequencing datasets

AIMS

Dilated cardiomyopathy (DCM) remains among the most refractory heart diseases because of its complicated pathogenesis, and the key molecules that cause it remain unclear.

MAIN METHODS

To elucidate the molecules and upstream pathways critical for DCM pathogenesis, we performed meta-analysis and co-expression analysis of RNA-sequencing (RNA-seq) datasets from publicly available databases. We analyzed three RNA-seq datasets containing comparisons of RNA expression in left ventricles between healthy controls and DCM patients. We extracted differentially expressed genes (DEGs) and clarified upstream regulators of cardiovascular disease-related DEGs by Ingenuity Pathway Analysis (IPA). Weighted Gene Co-expression Network Analysis (WGCNA) and Protein-Protein Interaction (PPI) analysis were also used to identify the hub gene candidates strongly associated with DCM.

KEY FINDINGS

In total, 406 samples (184 healthy, 222 DCM) were used in this study. Overall, 391 DEGs [absolute fold change (FC) ≥ 1.5; P < 0.01], including 221 upregulated and 170 downregulated ones in DCM, were extracted. Seven common hub genes (LUM, COL1A2, CXCL10, FMOD, COL3A1, ADAMTS4, MRC1) were finally screened. IPA showed several upstream transcriptional regulators, including activating (NFKBIA, TP73, CALR, NFKB1, KLF4) and inhibiting (CEBPA, PPARGC1A) ones. We further validated increased expression of several common hub genes in the transverse aortic constriction-induced heart failure model.

SIGNIFICANCE

In conclusion, meta-analysis and WGCNA using RNA-seq databases of DCM patients identified seven hub genes and seven upstream transcriptional regulators.

Proteomic-Based Analysis of Hypoxia- and Physioxia-Responsive Proteins and Pathways in Diffuse Large B-Cell Lymphoma

Hypoxia is a common feature in most tumors, including hematological malignancies. There is a lack of studies on hypoxia- and physioxia-induced global proteome changes in lymphoma. Here, we sought to explore how the proteome of diffuse large B-cell lymphoma (DLBCL) changes when cells are exposed to acute hypoxic stress (1% of O₂) and physioxia (5% of O₂) for a long-time. A total of 8239 proteins were identified by LC–MS/MS, of which 718, 513, and 486 had significant changes, in abundance, in the Ri-1, U2904, and U2932 cell lines, respectively. We observed that changes in B-NHL proteome profiles induced by hypoxia and physioxia were quantitatively similar in each cell line; however, differentially abundant proteins (DAPs) were specific to a certain cell line. A significant downregulation of several ribosome proteins indicated a translational inhibition of new ribosome protein synthesis in hypoxia, what was confirmed in a pathway enrichment analysis. In addition, downregulated proteins highlighted the altered cell cycle, metabolism, and interferon signaling. As expected, the enrichment of upregulated proteins revealed terms related to metabolism, HIF1 signaling, and response to oxidative stress. In accordance to our results, physioxia induced weaker changes in the protein abundance when compared to those induced by hypoxia. Our data provide new evidence for understanding mechanisms by which DLBCL cells respond to a variable oxygen level. Furthermore, this study reveals multiple hypoxia-responsive proteins showing an altered abundance in hypoxic and physioxic DLBCL. It remains to be investigated whether changes in the proteomes of DLBCL under normoxia and physioxia have functional consequences on lymphoma development and progression.