We thank the Lymphoid Malignancies Unit, Elisa ten Hacken, Lydia Scarf&#242;,&#160;Massimo Alessio, Antonio Conti, Angela Bachi, and Angela Cattaneo.
This project was supported by: Associazione Italiana per la Ricerca sul Cancro AIRC (Investigator Grant and Special Program Molecular Clinical Oncology &#8211; 5 per mille #9965)
C.S. and B.A designed the study, performed the experiments, analyzed the data and wrote the manuscript. M.T.S.B., U.R., F.B. P.R. assisted in writing the manuscript. P.G. and F.C.C. designed the study provided patients&#8217; samples and clinical data.

NOTE: All tissue samples were obtained with approval of the institutional review board of San Raffaele Hospital (Milan, Italy).
1. Human Tissue Samples and Cell Purification (Figure 1)
NOTE: Leukemic lymphocytes were obtained from the Peripheral Blood (PB) of CLL patients, diagnosed according to Mulligan et al. 9
1.1) Leukemic Cell Separation from PB
<ol>
	<li>Collect PB in vacutainer blood collection tubes with Sodium Heparin.</li>
	<li>Transfer blood into a 15 ml tube and add human B-cell enrichment cocktail at 50 &#956;L/mL of whole blood. Mix well and incubate 20 min at room temperature.</li>
	<li>Dilute sample with an equal volume of PBS + 2% FBS, mix gently and carefully overlay blood over the Ficoll, making sure not to break the interface. Use at least 1 part of Ficoll to 2 parts of the diluted sample (i.e. 4 ml Ficoll + 10 ml blood in a 15 ml tube).</li>
	<li>Centrifuge at 400 x g, at room temperature (20 &#176;C) for 20 min with no brake. Mononuclear cells will be at the interface.</li>
	<li>Carefully aspirate the interface to recover the cells and place into a new tube. Wash cells once with PBS and centrifuge at 300 x g, 4 &#176;C in the dark&#160;for 5 min. The pellet will be at the bottom.</li>
	<li>Discard the supernatant. Resuspend the pellet in the remaining supernatant by flicking the tube back and forth with fingers. Dilute the pellet with 10 ml complete RPMI medium (RPMI 1640 supplemented with 10% Fetal Calf Serum and 15 mg/ml gentamicin) and count cells using the Trypan Blue exclusion method.</li>
</ol>
1.2) Purity Evaluation
NOTE: Purity of all preparations needs to be always above 99%.
<ol>
	<li>Incubate 100 &#956;l&#160;of purified cell suspension with the following antibodies (commercially available; see Table of Materials): CD3FITC (5 &#181;l/test), CD14PE (5 &#181;l/test), CD19ECD (6 &#181;l/test), CD16-CD56PC5 (2 &#181;l/test), CD5PC7 (4 &#181;l/test), for 20 min at 4 &#176;C in a FACS tube.</li>
	<li>Wash the sample with 4 ml of PBS (centrifuge for 5 min at 300 x g) and check the purity by flow cytometry.Check in the plot the % of CLL cells (&#62; 99%) which co-express CD19 and CD5 on their surface as shown in Figure 1(6). Ensure that the preparations are virtually devoid of NK, T lymphocytes and monocytes by checking the % of CD3, CD14 and CD16-56 in the plot, which should be near zero.</li>
</ol>
1.3) Samples Storage
<ol>
	<li>For proteomic studies, collect 25 x 106 cells in a 1.5 ml tube, centrifuge cells at 300 x g for 10 min, discard the supernatant and lyophilize pellets for 4 hr. Keep at -80 &#176;C until use.</li>
	<li>For validation assays, resuspend cells in complete RPMI (quantity depends on the further assay that is chosen) and proceed with Step 4.</li>
</ol>
2. Two-dimensional Electrophoresis (2-DE) (Figure 2)
2.1) Isoelectrofocusing (IEF)
<ol>
	<li>Solubilize CLL cells pellets with a final volume of 380 &#956;l 2-DE buffer (344 &#956;l of a RBthio solution (9 M Urea, 10 mM Tris, 4% CHAPS), 30 &#956;l of 65mM DTT, 6 &#956;l of 2% IPG buffer ampholine pH 4-7).</li>
	<li>Apply protein samples (1 mg) to 18 IPG strips (pH 4-7) and perform IEF following standard protocol as described by Conti et al. 10</li>
	<li>Equilibrate strips in 2 ml of Equilibration Buffer (EB: 50 mM pH 8.8 Tris-HCl buffer containing 6 M urea, 30% glycerol, 2% SDS), supplemented with 2% of fresh DTT, for 15 minutes at RT. Discard EB+DTT and add 2 ml of EB supplemented with 2.5% Iodoacetamide. Incubate for 15 min at RT on a rocking platform.</li>
</ol>
2.2) SDS-PAGE
<ol>
	<li>Dry the strips on a paper without touching the gel to remove the excess of EB. Load each strip on top of a 9-16% gradient SDS-PAGE gel. Add a small volume of SDS-Electrophoresis Buffer (Tris 25 mM, Glycine 192 mM, SDS 0,1% w/v) on top of the gel to facilitate loading of the strip.</li>
	<li>Seal the gel by adding ~5 ml of agar solution (0.8%) to prevent floating of the strip, then assemble the electrophoretic unit and fill with SDS-Electrophoresis buffer. Perform the run at 60 mA/gel for 4 hr at 4 &#176;C.</li>
	<li>Remove the gel from the electrophoretic unit and place it in the proper staining box.</li>
</ol>
2.3) Silver Stain for Preparative Gel
<table border="0" cellpadding="0" cellspacing="0" fo:keep-together.within-page="always">
	<tbody>
		<tr>
			<td>FIXER</td>
			<td>50% Methanol 12% Acetic Acid 
			0,05% Formalin</td>
			<td>2 hr (or overnight)*</td>
		</tr>
		<tr>
			<td>WASH BUFFER</td>
			<td>&#160;35% Ehanol</td>
			<td>20 min (repeat the step three times)</td>
		</tr>
		<tr>
			<td>SENSITIZING</td>
			<td>&#160;0,02% Sodium Thiosulfate</td>
			<td>2 min</td>
		</tr>
		<tr>
			<td>WASH</td>
			<td>&#160;H2O</td>
			<td>5 min (repeat the step three times)&#160;</td>
		</tr>
		<tr>
			<td>SILVER NITRATE</td>
			<td>&#160;0,2% Silver Nitrate 0,076% Formalin</td>
			<td>20 min</td>
		</tr>
		<tr>
			<td>WASH</td>
			<td>&#160;H2O</td>
			<td>1 min (repeat the step twice)&#160;</td>
		</tr>
		<tr>
			<td>DEVELOPER</td>
			<td>6% Sodium Carbonate 0,0004% Sodium Thiosulfate 
			&#160;0,05% formalin</td>
			<td>Until the staining is sufficient</td>
		</tr>
		<tr>
			<td>STOP</td>
			<td>50% Methanol</td>
			<td>30 min</td>
		</tr>
		<tr>
			<td></td>
			<td>* 2 hr is the minimum time required for protein fixation&#160;</td>
			<td></td>
		</tr>
	</tbody>
</table>
Table 1.
NOTE: Protein spots can be visualized by staining gels with MS compatible silver stain11. All the solutions needed for silver staining are listed in Table 1.
<ol>
	<li>Prepare about 200 ml of each solution/gel and proceed as indicated in Table 1. Carefully add each solution to the staining box containing the gel. Perform all incubations on a rocking platform.</li>
	<li>After the staining, remove the Stop Solution and leave the gel in a solution of 1% Acetic Acid until acquisition.</li>
</ol>
2.4) Gel Acquisition and Analysis
<ol>
	<li>Acquire images at high resolution using a densitometer within 3 days from the staining.</li>
	<li>Analyze 2-D protein patterns by using software for 2-DE gels. 
	NOTE: The software allows a fast and reliable image comparison.
	<ol>
		<li>Create a project by choosing &#8220;create a new project&#8221; from the contextual menu. Create a folder and import the gels by choosing &#8220;import gel images&#8221; with .tif, .png. or .gel extension.</li>
		<li>Once the gels are imported and added to the workspace, perform an automated spot detection by selecting the gels for spot detection and choosing &#8220;edit &#62; spot&#62; detect&#8221; in the menu.</li>
		<li>Next, perform a background subtraction by selecting from the menu &#8220;subtract background&#8221;. Note: After that it is possible to compare multiple gels and to detect differences or similarities by quantitative and/or qualitative analysis.</li>
	</ol>
	</li>
</ol>
3. Protein Identification by MALDI-TOF MS analysis (Figure 3)
3.1) Protein Digestion
<ol>
	<li>Rinse the gel with water and excise spots of interest from gels either by manual (cutting with a clean scalpel) or by automated excision.</li>
	<li>Wash gel particles with water (100-150 &#956;l), spin down (30 sec at 400 x g) and remove the liquid.</li>
	<li>Add an equal volume (depending on the gel volume) of CH3CN to the gel pieces and wait for 10-15 min until the gel pieces shrink. Dry the gel particles in a vacuum centrifuge.</li>
	<li>Add 75-100 &#181;l of 10 mM Dithioerythritol diluted in 50 mM NH4HCO3 and incubate for 30 min at 56 &#176;C (Reduction Step). Shrink again the gel pieces with CH3CN as described in Step 3.1.3.</li>
	<li>Proceed with alkylation by adding 75-100 &#181;l of a solution 55 mM Iodoacetamide diluted in 50 mM NH4HCO3 and incubate for 20 min at room temperature in the dark.</li>
	<li>Shrink the gel pieces once more with CH3CN using enough volume to cover the gel pieces as described in Step 3.1.3. Dry in a vacuum centrifuge.</li>
	<li>Rehydrate the particles in a buffer containing 25 mM NH4HCO3, 5 mM CaCl2,and 12,5 ng/&#956;l of trypsin at 4 &#176;C for 20 min. Use enough volume of buffer to cover the gel pieces. Remove the un-absorbed supernatant from the gel pieces and add 25 mM NH4HCO3, 5 mM CaCl2 without trypsin to cover the gel.</li>
	<li>Leave samples at 37 &#176;C at least 3 hr (the minimum time required for peptide digestion) to overnight.</li>
</ol>
3.2) Mass Spectrometry Analysis (Dried droplet technique)
<ol>
	<li>Spot 1 &#956;l aliquot of each sample onto a stainless steel MALDI plate and mix with 1 &#181;l of &#945;-cyano-4-hydroxycinnamic acid as matrix, prepared in 50% CH3CN and 0.1% TFA.</li>
	<li>Obtain mass spectra on a MALDI&#8211;TOF mass spectrometer. Accumulate about 200 spectra per spot, adjusting laser intensity to prevent signal saturation or to increase the signal. Process spectra via Data Explorer software as described below:
	<ol>
		<li>Import the .dat file and perform the baseline correction by choosing &#8220;process &#62; baseline correction&#8221;. Calibrate masses using the trypsin autolysis products and matrix peaks by choosing &#8220;process &#62; mass calibration &#62; manual calibration; select peaks close to m/z 855.1 and 2163.1 by left dragging and select the corresponding reference masses, then click &#8220;plot&#8221; and &#8220;apply calibration&#8221; in the manual calibration window.</li>
		<li>Adjust the threshold for peak detection (&#8220;peak &#62;peak detection&#8221;), duplicate the active trace (&#8220;display &#62;duplicate active trace&#8221;), select the new trace and perform the deisotoping (&#8220;peak &#62;deisotoping&#8221;). Using the macro &#8220;getpeaklist&#8221;, generate a list of masses to be used for the identification. If required, manually remove noise signals picked as peaks to clean the list and get a better identification.</li>
	</ol>
	</li>
	<li>Identify proteins by searching a comprehensive non-redundant protein database using ProFound and Mascot as search engines12.
	<ol>
		<li>Use the following parameters in all searches: one missed cleavage per peptide, methionine oxidation as variable modification, cysteine carbamidomethylation as fixed modification and an initial mass tolerance of 50 ppm.</li>
	</ol>
	</li>
</ol>
4. Cytoskeletal Activity Assays (Figure 4)
NOTE: Resuspend cells purified in Step 1 in complete RPMI (106 cells/200 &#956;l).
4.1) Migration Assay. This test allows quantification of the migratory capacity of the analyzed cells (lymphocytes ). Use a transwell chamber of 6.5 mm diameter and 5.0 &#956;m pore size and perform the assay in triplicate. Optimize pore size and migration time (Step 4.1.3) in the case of different cell types.
<ol>
	<li>Prepare the lower chamber by adding 600 &#956;l of complete RPMI with or without the specific stimuli (i.e. SDF-1) to measure the induced and the spontaneous migration respectively.</li>
	<li>Put the upper chamber on it and let the system equilibrate for 30 minutes at 37 &#176;C in the incubator.</li>
	<li>Seed 106 cells/200 &#956;l in the upper chamber (total cell number) and incubate the plate for 4 hr at 37 &#176;C in the incubator.</li>
	<li>Remove the upper chamber, collect the media in the lower chamber and wash the lower chamber once with 1 ml PBS. Collect the PBS in the tube.</li>
	<li>Centrifuge 5 minutes at 300 x g, discard the supernatant and resuspend in 500 &#956;l PBS.</li>
	<li>By flow cytometry, count the number of migrated cells after 1 min of acquisition. In case of an isolated cell population it is not necessary to add any surface antibody. Check the number of cells in a bi-dimensional dot plot considering the side scatters of the cells and the number of events visualized in 1 min, which is the number to use for calculation.</li>
	<li>Calculate the Migration Index (MI) as: 
	<img alt="Equation 1" fo:content-width="3.5in" src="/files/ftp_upload/51942/51942eq1.jpg" /></li>
</ol>
4.2) Adhesion assay. This assay allows measuring the adhesion capacity of the cells. Perform the assay in triplicate.
<ol>
	<li>Pre-coat 96-wells plate (flat-bottom) with 50 &#956;l/well of either 2% BSA-PBS (as background) or 1 &#956;g ICAM-1 diluted in PBS, overnight at 4 &#176;C.</li>
	<li>Wash the plate twice with PBS and block non-specific sites by adding 2% BSA-PBS (100 &#956;l/well) for 1 hr at 37 &#176;C.</li>
	<li>In the meantime resuspend cells at 5 x 106/ml in complete RPMI, label them with 1 mM CMFDA-green cell tracker and incubate 30 min at 37 &#176;C.</li>
	<li>Add 1 x 106 cells/well to the pre-coated wells after discarding the blocking solution (Step 4.2.2) and incubate 1 hr at 37 &#176;C.</li>
	<li>Quantify adhesion by using an ELISA reader (Excitation filter: 485 nM, Emission filter: 535 nM). Perform a first measurement on the total input (INPUT).</li>
	<li>Wash the plate gently with 2% BSA-PBS (200 &#956;l/well) 4 times (x). Perform a reading of the plate after each washing step (Adhesionx).</li>
	<li>After background subtraction for each measurement, calculate specific adhesion (ADHESION): 
	<img alt="Equation 1" fo:content-width="2in" src="/files/ftp_upload/51942/51942eq2.jpg" /></li>
</ol>
4.3) Polymerization assay. This is a colorimetric assay that quantifies F-actin polymerization. Perform the assay in triplicate.
<ol>
	<li>Resuspend 1x10^6 cells in 100 &#956;l of pre-warmed complete RPMI and add the specific stimulus (i.e. &#945;-IgM 20 &#956;g/ml ) for 10 min.</li>
	<li>Stop the reaction with 400&#160;&#956;l of 4% paraformaldehyde and fix cells for 10 min at RT.</li>
	<li>Wash 3 times with PBS (centrifuge at 300 x g for 5 min, 4 &#176;C).</li>
	<li>Discard the supernatant and permeabilize cells with PBS-saponine 0.2% (200&#160;&#956;l) on ice for 2 min.</li>
	<li>Wash 3 times with PBS-saponine 0.1% (centrifuge at 100 x g for 5 min, 4 &#176;C), discard the supernatant and resuspend in 100&#160;&#956;l&#160;PBS-saponine 0.1%.</li>
	<li>Stain with Phalloidin-Alexafluor 488 (3&#160;&#956;g/ml) for 30 min at room temperature in the dark.</li>
	<li>Wash 3 times with PBS-0.1% saponine. Discard the supernatant and resuspend in 300&#160;&#956;l PBS.</li>
	<li>Quantify the amount of F-actin by flow cytometry, calculating the Mean Florescence Intensity (MFI) of the Phalloidin. Analyze the generated data in a single dimension plot in order to produce a histogram based on the fluorescent intensity, the MFI value is shown in the graph report.</li>
	<li>Measure F-actin polymerization (&#8710; F-actin) as: 
	<img alt="Equation 1" fo:content-width="2in" src="/files/ftp_upload/51942/51942eq3.jpg" /></li>
</ol>

<ol><li>Caligaris-Cappio, F., Ghia, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Novel+insights+in+chronic+lymphocytic+leukemia%3A+are+we+getting+closer+to+understanding+the+pathogenesis+of+the+disease%5BTitle%5D)+AND+%22J+Clin+Oncol%22%5BJournal%5D)">Novel insights in chronic lymphocytic leukemia: are we getting closer to understanding the pathogenesis of the disease.</a> J Clin Oncol. 26, 4497-4503 (2008).</li>
<li>Rawstron, A. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Monoclonal+B-cell+lymphocytosis+and+chronic+lymphocytic+leukemia%5BTitle%5D)+AND+%22N+Engl+J+Med%22%5BJournal%5D)">Monoclonal B-cell lymphocytosis and chronic lymphocytic leukemia.</a> N Engl J Med. 359, 575-583 (2008).</li>
<li>Dagklis, A., Fazi, C., Scarfo, L., Apollonio, B., Ghia, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Monoclonal+B+lymphocytosis+in+the+general+population%5BTitle%5D)+AND+%22Leuk+Lymphoma%22%5BJournal%5D)">Monoclonal B lymphocytosis in the general population.</a> Leuk Lymphoma. 50, 490-492 (2009).</li>
<li>Fazi, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((General+population+low-count+CLL-like+MBL+persists+over+time+without+clinical+progression%2C+although+carrying+the+same+cytogenetic+abnormalities+of+CLL%5BTitle%5D)+AND+%22Blood%22%5BJournal%5D)">General population low-count CLL-like MBL persists over time without clinical progression, although carrying the same cytogenetic abnormalities of CLL.</a> Blood. 118, 6618-6625 (2011).</li>
<li>Caligaris-Cappio, F., Bertilaccio, M. T., Scielzo, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((How+the+microenvironment+wires+the+natural+history+of+chronic+lymphocytic+leukemia%5BTitle%5D)+AND+%22Seminars+in+cancer+biology%22%5BJournal%5D)">How the microenvironment wires the natural history of chronic lymphocytic leukemia.</a> Seminars in cancer biology. , (2013).</li>
<li>Damle, R. N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Ig+V+gene+mutation+status+and+CD38+expression+as+novel+prognostic+indicators+in+chronic+lymphocytic+leukemia%5BTitle%5D)+AND+%22Blood%22%5BJournal%5D)">Ig V gene mutation status and CD38 expression as novel prognostic indicators in chronic lymphocytic leukemia.</a> Blood. 94, 1840-1847 (1999).</li>
<li>Lanham, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Differential+signaling+via+surface+IgM+is+associated+with+VH+gene+mutational+status+and+CD38+expression+in+chronic+lymphocytic+leukemia%5BTitle%5D)+AND+%22Blood%22%5BJournal%5D)">Differential signaling via surface IgM is associated with VH gene mutational status and CD38 expression in chronic lymphocytic leukemia.</a> Blood. 101, 1087-1093 (2003).</li>
<li>Wiestner, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((ZAP-70+expression+identifies+a+chronic+lymphocytic+leukemia+subtype+with+unmutated+immunoglobulin+genes%2C+inferior+clinical+outcome%2C+and+distinct+gene+expression+profile%5BTitle%5D)+AND+%22Blood%22%5BJournal%5D)">ZAP-70 expression identifies a chronic lymphocytic leukemia subtype with unmutated immunoglobulin genes, inferior clinical outcome, and distinct gene expression profile.</a> Blood. 101, 4944-4951 (2003).</li>
<li>Mulligan, C. S., Thomas, M. E., Mulligan, S. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Lymphocytes%2C+B+lymphocytes%2C+and+clonal+CLL+cells%3A+observations+on+the+impact+of+the+new+diagnostic+criteria+in+the+2008+Guidelines+for+Chronic+Lymphocytic+Leukemia+%28CLL%29%5BTitle%5D)+AND+%22Blood%22%5BJournal%5D)">Lymphocytes, B lymphocytes, and clonal CLL cells: observations on the impact of the new diagnostic criteria in the 2008 Guidelines for Chronic Lymphocytic Leukemia (CLL).</a> Blood. 113, 6496-6497 (2009).</li>
<li>Conti, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Proteome+study+of+human+cerebrospinal+fluid+following+traumatic+brain+injury+indicates+fibrin%28ogen%29+degradation+products+as+trauma-associated+markers%5BTitle%5D)+AND+%22J+Neurotrauma%22%5BJournal%5D)">Proteome study of human cerebrospinal fluid following traumatic brain injury indicates fibrin(ogen) degradation products as trauma-associated markers.</a> J Neurotrauma. 21, 854-863 (2004).</li>
<li>Mortz, E., Krogh, T. N., Vorum, H., Gorg, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Improved+silver+staining+protocols+for+high+sensitivity+protein+identification+using+matrix-assisted+laser+desorption%2Fionization-time+of+flight+analysis%5BTitle%5D)+AND+%22Proteomics%22%5BJournal%5D)">Improved silver staining protocols for high sensitivity protein identification using matrix-assisted laser desorption/ionization-time of flight analysis.</a> Proteomics. 1, 1359-1363 (2001).</li>
<li>Zhang, W., Chait, B. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((ProFound%3A+an+expert+system+for+protein+identification+using+mass+spectrometric+peptide+mapping+information%5BTitle%5D)+AND+%22Anal+Chem%22%5BJournal%5D)">ProFound: an expert system for protein identification using mass spectrometric peptide mapping information.</a> Anal Chem. 72, 2482-2489 (2000).</li>
<li>Scielzo, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((HS1+protein+is+differentially+expressed+in+chronic+lymphocytic+leukemia+patient+subsets+with+good+or+poor+prognoses%5BTitle%5D)+AND+%22J+Clin+Invest%22%5BJournal%5D)">HS1 protein is differentially expressed in chronic lymphocytic leukemia patient subsets with good or poor prognoses.</a> J Clin Invest. 115, 1644-1650 (2005).</li>
<li>Muzio, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((HS1+complexes+with+cytoskeleton+adapters+in+normal+and+malignant+chronic+lymphocytic+leukemia+B+cells%5BTitle%5D)+AND+%22Leukemia%22%5BJournal%5D)">HS1 complexes with cytoskeleton adapters in normal and malignant chronic lymphocytic leukemia B cells.</a> Leukemia. 21 (9), 2067-2070 (2007).</li>
<li>Scielzo, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((HS1+has+a+central+role+in+the+trafficking+and+homing+of+leukemic+B+cells%5BTitle%5D)+AND+%22Blood%22%5BJournal%5D)">HS1 has a central role in the trafficking and homing of leukemic B cells.</a> Blood. 116, 3537-3546 (2010).</li>
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</ol>

The authors have nothing to disclose.

The aim of this manuscript is to describe an optimized protocol for the identification of molecules involved in the pathogenesis of CLL, even if this approach can be extended to other diseases and/or other sample types16-18. By comparing the proteomic profiles of 2 subsets of CLL patients, good vs bad prognosis19, we demonstrated that they differ in the phosphorylation status of HS1 and that its activation affects the migration and adhesion capacity of leukemic cells.
<p class="jove_con...

Chronic Lymphocytic Leukemia (CLL), the most common adult leukemia in the Western countries, derives from the accumulation of monoclonal neoplastic CD5+ B lymphocytes and is clinically very heterogeneous. It may be present as a pre-leukemic form, defined as monoclonal B-cell lymphocytosis (MBL) 1,2,3. In other cases the disease can appear either with an indolent clinical course, that can remain stable for years before needing treatment, or as a progressive chemorefractory disease with dismal prognosis despite therapy. Finally, it may progress into a frequently lethal high grade lymphoma (Richter&#8217;s Syndrome-RS) 2,3,4. Patients are usually classified in two main subsets: good and bad prognosis, based on a set of prognostic factors that provides complementary information on predictors of disease outcome and survival. Clinical heterogeneity likely reflects biological heterogeneity. A number of genetic, microenvironmental and cellular factors have been shown to concur to disease pathogenesis though no unifying mechanisms have been found 5. In detail, several studies have demonstrated that differences in the clinical course of the disease can be partially explained by the presence (or the absence) of some biological markers that have a prognostic value 6,7,8. These data demonstrated that a better understanding of the disease biology could provide additional hints for the clinical management of the pathology, by the identification of both prognostic markers and therapeutic targets.
The goal of the present paper is to show how a combination of different proteomic techniques can be used for the identification of proteins involved in CLL onset and progression. Our approach demonstrates that it is possible to join together basic proteomic and clinical data5.
In the present workflow, primary leukemic cells from selected patients (good vs bad prognosis) are isolated and cell lysates are then used to obtain proteomic maps. 2DE allows the characterization of the proteomic profile of a cell population, including post-translational modifications, thus giving indirect information on the biological activity of each protein. Whole cell lysates are resolved by a first dimension run based on the isoelectric point, followed by a second dimension run on a polyacrylamide gel that resolves proteins based on their molecular weight. Comparative analysis of proteomic maps allows the identification of differentially expressed proteins (both in terms of abundance and post-translational modifications) as spots on the gel that can be cut and analyzed by Mass Spectrometry. The role of each candidate can be then exploited by different assays.
This approach, restricted to CLL in the current manuscript, can be easily expanded to other diseases/samples, thus providing information about the proteomic/biological differences between two groups (i.e. pathologic vs normal, stimulated vs unstimulated, wild-type vs knockdown).

<table><tbody><tr><td>Acetonitril</td><td>MERCK</td><td>61830025001730&amp;nbsp;</td><td></td></tr><tr><td>Ammonium Bicarbonate</td><td>SIGMA</td><td>A6141-500G</td><td></td></tr><tr><td>1,4-Dithioerythritol</td><td>SIGMA</td><td>D9680-5G</td><td></td></tr><tr><td>Iodoacetamide</td><td>SIGMA</td><td>I6125-25G</td><td></td></tr><tr><td>Calcium chloride dihydrate</td><td>SIGMA</td><td>223506-25G</td><td></td></tr><tr><td>Trypsin, Sequencing Grade</td><td>ROCHE</td><td>11418475001</td><td></td></tr><tr><td>&amp;alpha;-cyano-4-hydroxycinnamic acid</td><td>SIGMA</td><td>C2020-10G</td><td></td></tr><tr><td>Trifluoroacetic acid</td><td>SIGMA</td><td>T6580</td><td></td></tr><tr><td>ZipTip&lt;sub&gt;&amp;micro;-C18&lt;/sub&gt;</td><td>MILLIPORE</td><td>ZTC18M096</td><td></td></tr><tr><td>RosetteSep Human B Cell Enrichment Cocktail</td><td>STEMCELL</td><td>15064</td><td></td></tr><tr><td>PBS</td><td>EUROCLONE</td><td>ECB4004L</td><td></td></tr><tr><td>FBS</td><td>DOMINIQUE DUTSCHER</td><td>S1810</td><td></td></tr><tr><td>Lymphoprep</td><td>SENTINEL DIAGNOSTICS</td><td>1114547</td><td></td></tr><tr><td>Trypan Blue</td><td>SIGMA</td><td>T8154</td><td></td></tr><tr><td>CD19</td><td>BECKMAN COULTER</td><td>082A07770</td><td>ECD</td></tr><tr><td>CD5</td><td>BECKMAN COULTER</td><td>082A07754</td><td>PC5</td></tr><tr><td>CD3</td><td>BECKMAN COULTER</td><td>082A07746</td><td>FITC</td></tr><tr><td>CD14</td><td>BD</td><td>345785</td><td>PE</td></tr><tr><td>CD16</td><td>BECKMAN COULTER</td><td>082A07767</td><td>PC5</td></tr><tr><td>CD56</td><td>BECKMAN COULTER</td><td>082A07789</td><td>PC5</td></tr><tr><td>Ettan IPGphor 3 Isoelectric Focusing Unit</td><td>GE-Healthcare</td><td>11-0033-64&amp;nbsp;</td><td></td></tr><tr><td>Urea</td><td>SIGMA</td><td>U6504</td><td></td></tr><tr><td>Tris-Hcl Buffer</td><td>BIO-RAD</td><td>161-0799</td><td></td></tr><tr><td>CHAPS</td><td>SIGMA</td><td>C2020-10G</td><td></td></tr><tr><td>DTT</td><td>SIGMA</td><td>D9163-5G</td><td></td></tr><tr><td>IPGstrips</td><td>GE-Healthcare</td><td>17-1233-01&amp;nbsp;</td><td>Linear pH 4-7 18cm</td></tr><tr><td>IPGbuffer</td><td>GE-Healthcare</td><td>17-6000-86</td><td>pH 4-7</td></tr><tr><td>Glycerol</td><td>SIGMA</td><td>G6279</td><td></td></tr><tr><td>PROTEAN II XL Cell</td><td>BIO-RAD</td><td>165-3188</td><td></td></tr><tr><td>SDS</td><td>INVITROGEN</td><td>NP0001</td><td></td></tr><tr><td>Acrilamide</td><td>BIO-RAD</td><td>161-0156</td><td></td></tr><tr><td>Agarosio</td><td>INVITROGEN</td><td>16500</td><td></td></tr><tr><td>Methanol</td><td>SIGMA</td><td>32213</td><td></td></tr><tr><td>Acetic Acid</td><td>VWR</td><td>631000</td><td></td></tr><tr><td>Formalin</td><td>BIO-OPTICAL</td><td>05-K01009</td><td></td></tr><tr><td>Ethanol</td><td>VWR</td><td>9832500</td><td></td></tr><tr><td>Sodium Thiosulfate</td><td>FLUKA</td><td>72049</td><td></td></tr><tr><td>Silver Nitrate</td><td>FLUKA</td><td>85228</td><td></td></tr><tr><td>Molecular Dynamics Personal SI Laser Densitometer</td><td>Amersham Biosciences</td><td></td><td></td></tr><tr><td>ImageMaster 2D Platinum 5.0</td><td>Amersham Biosciences</td><td></td><td></td></tr><tr><td>Sodium Carbonate</td><td>MERCK</td><td>A0250292</td><td></td></tr><tr><td>MALDI-TOF Voyager-DE STR</td><td>Applied Biosystems</td><td></td><td></td></tr><tr><td>Data Explorer software (version 3.2)&amp;nbsp;</td><td>Applied Biosystems</td><td></td><td></td></tr><tr><td>transwell chambre 6.6 mm diameter</td><td>CORNING</td><td>3421</td><td></td></tr><tr><td>RPMI</td><td>EUROCLONE</td><td>ECB2000L</td><td>WITH L-GLUTAMINE</td></tr><tr><td>Gentamicin</td><td>SIGMA</td><td>G1397</td><td></td></tr><tr><td>SDF-1</td><td>PREPROTECH</td><td>300-28A</td><td></td></tr><tr><td>Flat-bottom 96-well plate</td><td>BECTON DICKINSON</td><td>353072</td><td></td></tr><tr><td>BSA</td><td>SANTA CRUZ</td><td>9048-46-8</td><td></td></tr><tr><td>ICAM-1</td><td>R&amp;amp;D Systems</td><td>720-IC</td><td></td></tr><tr><td>CMFDA</td><td>Life Thechnology</td><td>C7025</td><td>Green</td></tr><tr><td>IgM</td><td>SOUTHERNBIOTECH</td><td>2020-02</td><td></td></tr><tr><td>Paraformaldehyde</td><td>SIGMA</td><td>P6148</td><td></td></tr><tr><td>Saponine</td><td>SIGMA</td><td>S-7900</td><td></td></tr><tr><td>Phalloidin&amp;nbsp;</td><td>Life Thechnology</td><td>A12379</td><td>Alexa fluor 488</td></tr></tbody></table>

from a 2de-gel spot to protein function: lesson learned from hs1 in chronic lymphocytic leukemia

The identification of molecules involved in tumor initiation and progression is fundamental for understanding disease&#8217;s biology and, as a consequence, for the clinical management of patients. In the present work we will describe an optimized proteomic approach for the identification of molecules involved in the progression of Chronic Lymphocytic Leukemia (CLL). In detail, leukemic cell lysates are resolved by 2-dimensional Electrophoresis (2DE) and visualized as &#8220;spots&#8221; on the 2DE gels. Comparative analysis of proteomic maps allows the identification of differentially expressed proteins (in terms of abundance and post-translational modifications) that are picked, isolated and identified by Mass Spectrometry (MS). The biological function of the identified candidates can be tested by different assays (i.e. migration, adhesion and F-actin polymerization), that we have optimized for primary leukemic cells.

We isolated primary leukemic B cells form PB of CLL patients and we analyzed proteomic maps. Samples (n = 104) were grouped in two main subsets based on the clinical features of each patient (bad prognosis vs good prognosis) and comparative analysis of 2DE gels was performed.
The analysis allowed identification of spots differentially expressed between the two subsets (in term of presence/absence or shift on the gel, implying changes in post-translational modifications; n &#8776; 16)....

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From a 2DE-Gel Spot to Protein Function: Lesson Learned From HS1 in Chronic Lymphocytic Leukemia

Here we describe a protocol that couples two proteomic techniques, namely 2-dimensional Electrophoresis (2DE) and Mass Spectrometry (MS), to identify differentially expressed/post-translational modified proteins among two or more groups of primary samples. This approach, together with functional experiments, allows the identification and characterization of prognostic markers/therapeutic targets.

The identification of molecules involved in tumor initiation and progression is fundamental for understanding disease&#8217;s biology and, as a ...

from-2de-gel-spot-to-protein-function-lesson-learned-from-hs1-chronic

Research

JoVE Journal

Medicine

13.7K Views.  IRCCS, San Raffaele Scientific Institute.  Hier beschrijven we een protocol dat paren twee proteomics technieken, namelijk de 2-dimensionale elektroforese (2DE) en massaspectrometrie (MS), te identificeren differentieel tot expressie / post-translationeel gemodificeerde eiwitten tussen twee of meer groepen van primaire monsters. Deze aanpak, in combinatie met functionele experimenten, maakt de identificatie en karakterisering van prognostische markers / therapeutische doelen. 

Video: From a 2DE-Gel Spot to Protein Function: Lesson Learned From HS1 in Chronic Lymphocytic Leukemia

Flow-sorting and Exome Sequencing of the Reed-Sternberg Cells of Classical Hodgkin Lymphoma

The Hodgkin Reed-Sternberg cells of classical Hodgkin lymphoma are sparsely distributed within a background of inflammatory lymphocytes and typically comprise less than 1% of the tumor mass. Material derived from bulk tumor contains tumor content at a concentration insufficient for characterization. Therefore, fluorescence activated cell sorting using eight antibodies, as well as side- and forward-scatter, is described here as a method of rapidly separating and concentrating with high purity thousands of HRS cells from the tumor for subsequent study. At the same time, because standard protocols for exome sequencing typically require 100-1,000 ng of input DNA, which is often too high, even with flow sorting, we also provide an optimized, low-input library construction protocol capable of producing high-quality data from as little as 10 ng of input DNA. This combination is capable of producing next-generation libraries suitable for hybridization capture of whole-exome baits or more focused targeted panels, as desired. Exome sequencing of the HRS cells, when compared against healthy intratumor T or B cells, can identify somatic alterations, including mutations, insertions and deletions, and copy number alterations. These findings elucidate the molecular biology of HRS cells and may reveal avenues for targeted drug treatments.

Here, we describe a combined flow cytometric cell sorting and low-input, next-generation library construction protocol designed to produce high-quality, whole-exome data from the Hodgkin Reed-Sternberg (HRS) cells of classical Hodgkin lymphoma (CHL).

The Hodgkin Reed-Sternberg cells of classical Hodgkin lymphoma are sparsely distributed within a background of inflammatory lymphocytes and typically ...

Genetics

Flow Cytometry to Estimate Leukemia Stem Cells in Primary Acute Myeloid Leukemia and in Patient-derived-xenografts, at Diagnosis and Follow Up

Acute myeloid leukemia (AML) is a heterogeneous, and if not treated, fatal disease. It is the most common cause of leukemia-associated mortality in adults. Initially, AML is a disease of hematopoietic stem cells (HSC) characterized by arrest of differentiation, subsequent accumulation of leukemia blast cells, and reduced production of functional hematopoietic elements. Heterogeneity extends to the presence of leukemia stem cells (LSC), with this dynamic cell compartment evolving to overcome various selection pressures imposed upon during leukemia progression and treatment. To further define the LSC population, the addition of CD90 and CD45RA allows the discrimination of normal HSCs and multipotent progenitors within the CD34+CD38- cell compartment. Here, we outline a protocol to detect simultaneous expression of several putative LSC markers (CD34, CD38, CD45RA, CD90) on primary blast cells of human AML by multiparametric flow cytometry. Furthermore, we show how to quantify three progenitor populations and a putative LSC population with increasing degree of maturation. We confirmed the presence of these populations in corresponding patient-derived-xenografts. This method of detection and quantification of putative LSC may be used for clinical follow-up of chemotherapy response (i.e., minimal residual disease), as residual LSC may cause AML relapse.

We outline a protocol to detect simultaneous expression of leukemia stem cell markers on primary acute myeloid leukemia cells by flow cytometry. We show how to quantify three progenitor populations and a putative LSC population with increasing degree of maturation. We confirmed the presence of these populations in corresponding patient-derived-xenografts.

Acute myeloid leukemia (AML) is a heterogeneous, and if not treated, fatal disease. It is the most common cause of leukemia-associated mortality in ...

Cancer Research

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Biomarker detection is one of the more important biomedical questions for high-throughput &#39;omics&#39; researchers, and almost all existing biomarker detection algorithms generate one biomarker subset with the optimized performance measurement for a given dataset. However, a recent study demonstrated the existence of multiple biomarker subsets with similarly effective or even identical classification performances. This protocol presents a simple and straightforward methodology for detecting biomarker subsets with binary classification performances, better than a user-defined cutoff. The protocol consists of data preparation and loading, baseline information summarization, parameter tuning, biomarker screening, result visualization and interpretation, biomarker gene annotations, and result and visualization exportation at publication quality. The proposed biomarker screening strategy is intuitive and demonstrates a general rule for developing biomarker detection algorithms. A user-friendly graphical user interface (GUI) was developed using the programming language Python, allowing biomedical researchers to have direct access to their results. The source code and manual of kSolutionVis can be downloaded from http://www.healthinformaticslab.org/supp/resources.php.

Existing algorithms generate one solution for a biomarker detection dataset. This protocol demonstrates the existence of multiple similarly effective solutions and presents a user-friendly software to help biomedical researchers investigate their datasets for the proposed challenge. Computer scientists may also provide this feature in their biomarker detection algorithms.

Biomarker detection is one of the more important biomedical questions for high-throughput &#39;omics&#39; researchers, and almost all existing biomarker ...

Immunoglobulin Gene Sequence Analysis In Chronic Lymphocytic Leukemia: From Patient Material To Sequence Interpretation

During B cell maturation, the complex process of immunoglobulin (IG) gene V(D)J recombination coupled with somatic hypermutation (SHM) gives rise to a unique DNA sequence within each individual B cell. Since B cell malignancies result from the clonal expansion of a single cell, IG genes represent a unique molecular signature common to all the malignant cells within an individual patient; thus, IG gene rearrangements can be used as clonal markers. In addition to serving as an important clonal identifier, the IG gene sequence can act as a &#39;molecular timeline&#39; since it is associated with specific developmental stages and hence reflects the history of the B cell involved in the neoplastic transformation. Moreover, for certain malignancies, in particular chronic lymphocytic leukemia (CLL), the IG gene sequence holds prognostic and potentially predictive capabilities. That said, extrapolating meaningful conclusions from IG gene sequence analysis would be impossible if robust methods and tools were not available to aid in their analysis. This article, drawing on the vast experience of the European Research Initiative on CLL (ERIC), details the technical aspects and essential requirements necessary to ensure reliable and reproducible IG gene sequence analysis in CLL, a test that is now recommended for all CLL patients prior to treatment. More specifically, the various analytical stages are described ranging from the identification of the clonotypic IG gene rearrangement and the determination of the nucleotide sequence to the accurate clinical interpretation of the IG gene sequence data.

Herein, we present a protocol that details the technical aspects and essential requirements to ensure robust IG gene sequence analysis in patients with chronic lymphocytic leukemia (CLL), based on the accumulated experience of the European Research initiative on CLL (ERIC).

During B cell maturation, the complex process of immunoglobulin (IG) gene V(D)J recombination coupled with somatic hypermutation (SHM) gives rise to a ...

A Chromatin Immunoprecipitation Assay to Identify Novel NFAT2 Target Genes in Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is characterized by the expansion of malignant B cell clones and represents the most common leukemia in western countries. The majority of CLL patients show an indolent course of the disease as well as an anergic phenotype of their leukemia cells, referring to a B cell receptor unresponsive to external stimulation. We have recently shown that the transcription factor NFAT2 is a crucial regulator of anergy in CLL. A major challenge in the analysis of the role of a transcription factor in different diseases is the identification of its specific target genes. This is of&#160;great significance for the elucidation of pathogenetic mechanisms and potential therapeutic interventions. Chromatin immunoprecipitation (ChIP) is a classic technique to demonstrate protein-DNA interactions and can, therefore, be used to identify direct target genes of transcription factors in mammalian cells. Here, ChIP was used to identify LCK as a direct target gene of NFAT2 in human CLL cells. DNA and associated proteins are crosslinked using formaldehyde and subsequently sheared by sonication into DNA fragments of approximately 200-500 base pairs (bp). Cross-linked DNA fragments associated with NFAT2 are then selectively immunoprecipitated from cell debris using an &#945;NFAT2 antibody. After purification, associated DNA fragments are detected via quantitative real-time PCR (qRT-PCR). DNA sequences with evident enrichment represent regions of the genome which are targeted by NFAT2 in vivo. Appropriate shearing of the DNA and the selection of the required antibody are particularly crucial for the successful application of this method. This protocol is ideal for the demonstration of direct interactions of NFAT2 with target genes. Its major limitation is the difficulty to employ ChIP in large-scale assays analyzing the target genes of multiple transcription factors in intact organisms.

Chronic lymphocytic leukemia (CLL) is the most common leukemia in the western world. NFAT transcription factors are important regulators of development and activation in numerous cell types. Here, we present a protocol for the use of chromatin immunoprecipitation (ChIP) in human CLL cells to identify novel target genes of NFAT2.

Chronic lymphocytic leukemia (CLL) is characterized by the expansion of malignant B cell clones and represents the most common leukemia in western ...

HPLC-based Assay to Monitor Extracellular Nucleotide/Nucleoside Metabolism in Human Chronic Lymphocytic Leukemia Cells

This method describes a sensitive, specific, reliable and reproducible reverse phase high-performance liquid chromatography (RP-HPLC) assay developed and validated for the quantification of extracellular purine nucleotides and nucleosides produced by purified chronic lymphocytic leukemia (CLL) cells under different culture conditions. The chromatographic separation of adenosine 5&#39;-monophosphate (AMP), adenosine (ADO) and inosine (INO) is performed at RT on a silica-based, reversed-phase column that is used for polar compound retention. The method includes a binary mobile phase, which consists of 7 mM ammonium acetate and acetonitrile with a flow rate of 1.00 ml/min. The eluates are monitored using a Photodiode Array UV detector set at 260 nm. A standard calibration curve is generated to calculate the equation for the analytical quantification of each purine compound. System control, data acquisition and analysis are then performed. Applying this protocol, AMP, INO and ADO elute at 7, 11 and 11.9 min, respectively, and the total run time for each sample is 20 min. This protocol may be applied to different cell types and cell lines (both suspension and adherent), using culture media as matrix. The advantages are easy and fast sample preparation and the requirement of a small amount of supernatant for analysis. Furthermore, the use of a serum-free medium allows skipping the protein precipitation step with acetonitrile that impacts the final concentration of purine compounds. One of the limitations of the method is the requirement of the equilibration column run before each single sample run, making the total run time of the experiment longer and preventing high throughput screening applications.

The protocol described here represents an easy and reproducible method that employs reverse phase high-performance liquid chromatography (RP-HPLC) to measure purine metabolism on chronic lymphocytic leukemia (CLL) cells cultured under different conditions.

This method describes a sensitive, specific, reliable and reproducible reverse phase high-performance liquid chromatography (RP-HPLC) assay developed and ...

Chemistry

Subcellular Fractionation of Primary Chronic Lymphocytic Leukemia Cells to Monitor Nuclear/Cytoplasmic Protein Trafficking

Nuclear export of macromolecules is often deregulated in cancer cells. Tumor suppressor proteins, such as p53, can be rendered inactive due to aberrant cellular localization disrupting their mechanism of action. The survival of chronic lymphocytic leukaemia (CLL) cells, among other cancer cells, is assisted by the deregulation of nuclear to cytoplasmic shuttling, at least in part through deregulation of the transport receptor XPO1 and the constitutive activation of PI3K-mediated signaling pathways. It is essential to understand the role of individual proteins in the context of their intracellular location to gain a deeper understanding of the role of such proteins in the pathobiology of the disease. Furthermore, identifying processes that underlie cell stimulation and the mechanism of action of specific pharmacological inhibitors, in the context of subcellular protein trafficking, will provide a more comprehensive understanding of the mechanism of action. The protocol described here enables the optimization and subsequent efficient generation of nuclear and cytoplasmic fractions from primary chronic lymphocytic leukemia cells. These fractions can be used to determine changes in protein trafficking between the nuclear and cytoplasmic fractions upon cell stimulation and drug treatment. The data can be quantified and presented in parallel with immunofluorescent images, thus providing robust and quantifiable data.

This protocol enables the optimization and subsequent efficient generation of nuclear and cytoplasmic fractions from primary chronic lymphocytic leukemia cells. These samples are used to determine protein localization as well as changes in protein trafficking that take place between the nuclear and cytoplasmic compartments upon cell stimulation and drug treatment.

Nuclear export of macromolecules is often deregulated in cancer cells. Tumor suppressor proteins, such as p53, can be rendered inactive due to aberrant ...

Neutrophil Isolation and Analysis to Determine their Role in Lymphoma Cell Sensitivity to Therapeutic Agents

Neutrophils are the most abundant (40% to 75%) type of white blood cells and among the first inflammatory cells to migrate towards the site of inflammation. They are key players in the innate immune system and play major roles in cancer biology. Neutrophils have been proposed as key mediators of malignant transformation, tumor progression, angiogenesis and in the modulation of the antitumor immunity; through their release of soluble factors or their interaction with tumor cells. To characterize the specific functions of neutrophils, a fast and reliable method is coveted for in vitro isolation of neutrophils from human blood. Here, a density gradient separation method is demonstrated to isolate neutrophils as well as mononuclear cells from the blood. The procedure consists of layering the density gradient solution such as Ficoll carefully above the diluted blood obtained from patients diagnosed with chronic lymphocytic leukemia (CLL), followed by centrifugation, isolation of mononuclear layer, separation of neutrophils from RBCsby dextran then lysis of residual erythrocytes. This method has been shown to isolate neutrophils &#8805; 90 % pure. To mimic the tumor microenvironment, 3-dimensional (3D) experiments were performed using basement membrane matrix such as Matrigel. Given the short half-life of neutrophils in vitro, 3D experiments with fresh human neutrophils cannot be performed. For this reason promyelocytic HL60 cells are differentiated along the granulocytic pathway using the differentiation inducers dimethyl sulfoxide (DMSO) and retinoic acid (RA). The aim of our experiments is to study the role of neutrophils on the sensitivity of lymphoma cells to anti-lymphoma agents. However these methods can be generalized to study the interactions of neutrophils or neutrophil-like cells with a large range of cell types in different situations.

Neutrophils are the most abundant type of white blood cells. The isolation of neutrophils from human blood by density gradient separation method and the differentiation of human promyelocytic (HL60) cells along the granulocytic pathway are described here; to test their role on sensitivity of lymphoma cells to anti-lymphoma agents.

Neutrophils are the most abundant (40% to 75%) type of white blood cells and among the first inflammatory cells to migrate towards the site of ...

Immunology and Infection

Traction Force Microscopy to Study B Lymphocyte Activation

Traction force microscopy (TFM) enables the measurement of forces produced by a cell on a substrate. This technique infers traction force measurements from an experimentally observed displacement field produced by a cell pulling on an elastic substrate. Here, we adapted TFM to investigate the spatial and temporal structure of the force field exerted by B cells when activated by antigen engagement of the B cell receptor. Gel rigidity, bead density, and protein functionalization must be optimized for the study of relatively small cells (~ 6 &#181;m) that interact with, and respond specifically to ligands for cell surface receptors.

Here we present a protocol used to perform traction force microscopy experiments on B cells. We describe the preparation of soft polyacrylamide gels and their functionalization, as well as data acquisition at the microscope and a summary of data analysis.

Traction force microscopy (TFM) enables the measurement of forces produced by a cell on a substrate. This technique infers traction force measurements ...

Bioengineering

In Vitro Differentiation Model of Human Normal Memory B Cells to Long-lived Plasma Cells

Plasma cells (PCs) secrete large amounts of antibodies and develop from B cells that have been activated. PCs are rare cells located in the bone marrow or mucosa and ensure humoral immunity. Due to their low frequency and location, the study of PCs is difficult in human. We reported a B to PC in vitro differentiation model using selected combinations of cytokines and activation molecules that allow to reproduce the sequential cell differentiation occurring in vivo. In this in vitro model, memory B cells (MBCs) will differentiate into pre-plasmablasts (prePBs), plasmablasts (PBs), early PCs and finally, into long-lived PCs, with a phenotype close to their counterparts in healthy individuals.&#160;We also built an open access bioinformatics tools to analyze the most prominent information from GEP data related to PC differentiation. These resources can be used to study human B to PC differentiation and in the current study, we investigated the gene expression regulation of epigenetic factors during human B to PC differentiation.

Using multi-step culture systems, we report an in vitro B cell to plasma cell differentiation model.

Plasma cells (PCs) secrete large amounts of antibodies and develop from B cells that have been activated. PCs are rare cells located in the bone marrow or ...

From a 2DE-Gel Spot to Protein Function: Lesson Learned From HS1 in Chronic Lymphocytic Leukemia

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