Novel Biomarker Proteins in Chronic Lymphocytic Leukemia: Impact on Diagnosis, Prognosis and Treatment

<div><p>In many cancers, cells undergo re-programming of metabolism, cell survival and anti-apoptotic defense strategies, with the proteins mediating this reprogramming representing potential biomarkers. Here, we searched for novel biomarker proteins in chronic lymphocytic leukemia (CLL) that can impact diagnosis, treatment and prognosis by comparing the protein expression profiles of peripheral blood mononuclear cells from CLL patients and healthy donors using specific antibodies, mass spectrometry and binary logistic regression analyses and other bioinformatics tools. Mass spectrometry (LC-HR-MS/MS) analysis identified 1,360 proteins whose expression levels were modified in CLL-derived lymphocytes. Some of these proteins were previously connected to different cancer types, including CLL, while four other highly expressed proteins were not previously reported to be associated with cancer, and here, for the first time, DDX46 and AK3 are linked to CLL. Down-regulation expression of two of these proteins resulted in cell growth inhibition. High DDX46 expression levels were associated with shorter survival of CLL patients and thus can serve as a prognosis marker. The proteins with modified expression include proteins involved in RNA splicing and translation and particularly mitochondrial proteins involved in apoptosis and metabolism. Thus, we focused on several metabolism- and apoptosis-modulating proteins, particularly on the voltage-dependent anion channel 1 (VDAC1), regulating both metabolism and apoptosis. Expression levels of Bcl-2, VDAC1, MAVS, AIF and SMAC/Diablo were markedly increased in CLL-derived lymphocytes. VDAC1 levels were highly correlated with the amount of CLL-cancerous CD19+/CD5+ cells and with the levels of all other apoptosis-modulating proteins tested. Binary logistic regression analysis demonstrated the ability to predict probability of disease with over 90% accuracy. Finally, based on the changes in the levels of several proteins in CLL patients, as revealed from LC-HR-MS/MS, we could distinguish between patients in a stable disease state and those who would be later transferred to anti-cancer treatments. The over-expressed proteins can thus serve as potential biomarkers for early diagnosis, prognosis, new targets for CLL therapy, and treatment guidance of CLL, forming the basis for personalized therapy.</p></div

Hierarchical clustering and functional analysis of proteins expression in PBMCs obtained from healthy controls and CLL patients.

<p>The protein expression profiles of PBMCs obtained from healthy donors and CLL patients were analyzed by LC-HR-MS/MS as described under Materials and Methods. <b>A.</b> Hierarchical clustering based on the expression pattern of all 2,441 detected proteins with at least 1 unique peptide is presented. Healthy (white) and CLL (grey) are indicated. The color scale of the standardized expression values is shown on the right. <b>B.</b> Significantly enriched pathways associated with differentially expressed proteins in CLL, with their enrichment p-value, are presented. The number of proteins related to each pathway is indicated inside the chart. <b>C</b>. Significantly enriched functional groups based on the DAVID functional analysis are presented, with their enrichment p-value. The number of proteins related to each functional group is indicated inside the chart. Small pies on the left indicate apoptosis- and metabolism-related proteins of interest.</p

List of selected proteins differentially expressed between healthy donors and CLL patients identified by LC-HR-MS/MS.

<p>List of selected proteins differentially expressed between healthy donors and CLL patients identified by LC-HR-MS/MS.</p

Over-expression of Bcl-2, VDAC, AIF, MAVS, SMAC/Diablo and PPWD1 in PBMCs from CLL patients.

<p>Immunoblot analysis of cell lysates of PBMCs derived from CLL patients (P) and healthy donors (H) probed with antibodies directed against VDAC1 [A<b>a</b>, n = 28 (P), 20 (H)], Bcl-2 [A<b>b</b>, n = 28 (P), 20 (H)], MAVS [A<b>c</b>, n = 28 (P), 19 (H)], SMAC/Diablo [A<b>d</b>, n = 21 (P), 15 (H)], AIF [Ae, n = 17 (P), 16 (H)], HK-I [A<b>f</b>, n = 28 (P), 20 (H)], BAX [A<b>g</b>, n = 6 (P), 6 (H)], PPWD1 [A<b>h</b>, n = 16(P), 10(H)] or β-actin. Representative immunoblots (<b>A</b>) and quantitative analysis (mean ± SEM) (<b>B</b>) of protein levels of healthy donors (white) and CLL patients (grey) of these and other samples are presented. For each sample, three independent immunoblots were performed. A difference between healthy and CLL groups was considered statistically significant when P < 0.001 (***) or P < 0.01 (**), as determined by the Mann-Whitney test.</p

siRNA silencing of AK3 or DDX46 expression inhibits cell growth.

<p>(<b>A</b>) Differential expression of the 4 proteins not previously connected to any cancer between healthy and CLL individuals. (<b>B-D</b>) MEC-1 cells were transfected with (50 nM) scrambled siRNA (si-Scr,), one of the 2 different siRNAs against AK3 (siAK3 1 or 2), or against DDX46 (si-DDX46 1 or 2), a combination of siAK3 1 and 2 or a combination of siDDX46 1 and 2 and, at the indicated time, were analyzed for AK3 and DDX46 mRNA levels by RT-PCR (<b>B,C</b>) or analyzed for cell growth using the SRB method (n = 3) (<b>D</b>).</p

Comparison of apoptosis-related proteins in CLL patient- and healthy donor-derived PBMCs.

<p>Scatter plots display the expression levels of VDAC1 (<b>A</b>), MAVS (<b>B</b>), Bcl-2 (<b>C</b>), SMAC/Diablo (<b>D</b>), AIF (<b>E</b>), HK-I (<b>F</b>) and Bax (<b>G</b>), for each control subject and CLL patient, as analyzed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0148500#pone.0148500.g002" target="_blank">Fig 2</a>. Statistics were calculated with GraphPad Prism software. Horizontal lines represent mean values for each group. A difference between the healthy donor and CLL patient groups was considered statistically significant when P < 0.001 (***) or P < 0.01 (**), as determined by the Mann-Whitney test.</p

The VDAC1 expression level is correlated with the level of cancerous CD19+/CD5+ cells and apoptosis-related proteins.

<p>The percentages of CD19+/CD5+ cells in PBMCs isolated from representative healthy donor (n = 9) (<b>A</b>) or CLL patient (n = 16) (<b>B</b>) were determined using monoclonal antibodies directed to CD19/CD5, by flow cytometry analysis. CD19+/CD5+ cells represent cancerous CLL B lymphocytes. PBMCs obtained from 3 CLL patients (P (were subjected to CD19-positive cell separation using a magnetic bead-based method described in Materials and Methods. VDAC1 levels in PBMCs and their CD19-positive and -negative fractions were analyzed by immunoblotting using anti-VDAC1 antibodies (<b>C</b>). Quantitative analysis (mean ± SEM) (<b>D)</b> is presented. VDAC1 (<b>E</b>, R² = 0.7) and SMAC/Diablo (F, R² = 0.66) expression levels were determined as a function of the percentage of CD19+/CD5+ cells for each healthy donor (O) and CLL patient (▲). VDAC1 levels were assayed as described in the legend to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0148500#pone.0148500.g003" target="_blank">Fig 3</a>.</p

Binary logistic regression testing for specificity, sensitivity and overall CLL predication based on the relative expression of apoptosis-related proteins.

<p>Bivariance analysis was performed based on the relative expression of apoptosis-related proteins from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0148500#pone.0148500.g003" target="_blank">Fig 3</a>, considered as independent variables. Data was analyzed in terms of the sensitivity and specificity by assessing levels of apoptotic-regulating proteins based on a cut-off value of 0.5, using binary logistic regression analysis. Probability of disease is presented for healthy donor (●) and CLL patient (O) for VDAC1 (A), SMAC/Diablo (C), Bcl-2 (E) and MAVS (G). The dependents were determined as zero for healthy donors and 100 for CLL patients. The binary logistic regression model was carried out with a 95% confidence interval. Data was also analyzed using ROC curves of VDAC1 (B), SMAC/Diablo (D), Bcl-2 (F) and MAVS (H) expression levels in PBMCs samples from CLL patients and healthy donors. The AUC of the ROC curves for classifying CLL are presented in each curve.</p

List of selected proteins differentially expressed between CLL patients in a stable disease state and those transferred to anti-cancer treatments, identified by LC-HR-MS/MS.

<p>List of selected proteins differentially expressed between CLL patients in a stable disease state and those transferred to anti-cancer treatments, identified by LC-HR-MS/MS.</p