Warwick Immune Escape in B Cell Lymphoma Sampling and Data Collection Process

HI, I want help with my methodology to make some add and change in two parts that I already writ it ( sample and data collection and protocol of the lab work ) in this project. ( I already writ my impact and introduction) I will send one of the article to let you understand the criteria of how I want the the protocol look like.

My supervisor dose not want the protocol like toking about the producer, he want to writ about the principle. also, in the sample collection and data, I just used normal healthy human sample, I did not use any sample from B CELL LYMPHOMA patient, that’s why I want to make change on this part.

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Article
Leukocyte Ig-Like receptor B1 restrains
dendritic cell function through increased
expression of the NF-kB regulator
ABIN1/TNIP1
Rahul C. Khanolkar,*,1 Michail Kalogeropoulos,* Alistair Lawrie,* Ali Roghanian,†,‡,§
Mark A. Vickers,* and Neil T. Young*
*Division of Applied Medicine, Institute of Medical Sciences, University of Aberdeen, Aberdeen, United Kingdom; †David H. Koch
Institute for Integrative Cancer Research and ‡Department of Biology, Massachusetts Institute of Technology, Cambridge,
Massachusetts, USA; and §Antibody and Vaccine Group, Cancer Sciences Unit, Faculty of Medicine, University of Southampton,
Southampton General Hospital, Southampton, United Kingdom
RECEIVED SEPTEMBER 15, 2015; REVISED APRIL 4, 2016; ACCEPTED APRIL 6, 2016. DOI: 10.1189/jlb.1A0915-420RRR
ABSTRACT
Introduction
Inhibitory receptors of the human leukocyte
immunoglobulin-like receptor family are constitutively
expressed on all myeloid cell types and regulate their
functional activity. We demonstrate that ligation of the
human leukocyte antigen class I-specific receptor
LILRB1, during the differentiation of monocytes to dendritic cells in vitro, results in increased expression of the
nuclear factor kB inhibitor protein ABIN1 (also known as
TNIP1). Similarly increased expression of ABIN1/TNIP1
was observed in the “immunosuppressive” monocyte
populations of patients with non–Hodgkin lymphoma ex
vivo. Reducing expression of ABIN1/TNIP1 using small
interfering ribonucleic acid allows dendritic cells and
immunosuppressive monocytes to respond to stimulation by allowing nuclear factor kB translocation to the
nucleus (P , 0.001), increasing cell surface expression
of antigen presentation and costimulatory molecules
(P , 0.01), increasing phagocytic capacity (P , 0.001),
secreting proinflammatory cytokines (P , 0.01), and an
increasing ability to stimulate T cell responses (P ,
0.05). Our study, therefore, identifies an important
functional role for ABIN1/TNIP1 in mediating the effects
of LILRB1 ligation-induced inhibitory effects on immune
responses. Our findings suggest that inhibiting the
LILRB1-ABIN1/TNIP1 pathway in antigen-presenting
cells could be a therapeutic approach to stimulate
antitumor immune responses. Conversely, stimulation
of the pathway may also ameliorate autoimmune diseases in which TNIP1 is a susceptibility gene.
J. Leukoc. Biol. 100: 737–746; 2016.
DCs have a central role in the initiation, regulation, and
maintenance of immune responses. Recognition of “danger”
signals by a variety of pattern-recognition receptors expressed by
DCs initiates a program of cellular maturation, creating potent
antigen-presenting cells, which are capable of stimulating
antigen-speciﬁc, naı̈ve T lymphocytes and establishing adaptive,
antigen-speciﬁc immune responses. Conversely, immature DCs
are thought to be involved in the prevention of inappropriate
immune responses against “self” antigens by secreting immunosuppressive cytokines and interacting with regulatory T cell
populations [1]. The regulation of DC maturation is controlled
by several levels of molecular control to ensure that DCs respond
appropriately and that immune homeostasis is maintained [2].
Most myeloid lineage cells, including DCs, constitutively
express transmembrane cell surface receptors of the LILR gene
family. The LILR genes comprise part of the leukocyte receptor
cluster on human chromosome band 19q13.4 and include
isoforms with either inhibitory or activating functions, dependent
on their possession of ITIM motifs within their cytoplasmic tail
[3]. ITIM motifs recruit phosphatase enzymes, such as src
homology region 2 domain-containing phosphatase 1 (SHP1),
which diminish the intracellular-signaling phosphorylation
events initiated by the activating stimuli.
We have previously demonstrated that the HLA class I–speciﬁc
inhibitory receptor LILRB1 is involved in maintaining human
monocyte–derived DCs in a quiescent state, regulating the
capacity of DCs to increase levels of cell-surface antigen
presentation and costimulatory molecules, controlling the
secretion of cytokines, conferring resistance to FAS-mediated
apoptosis and inﬂuencing T cell reactivity by interacting with a
population of CD4+ CD25+ CD1272 regulatory T cells [4]. Other
reports have described similar functions for additional members
Abbreviations: ABIN1 = A20-binding inhibitor of NF-kB, DC = dendritic cell,
LAT = linker for activation of T cells, LILR = leukocyte Ig-like receptors,
MDSC = myeloid-derived suppressor cell, NHL = non–Hodgkin lymphoma,
siRNA = small interfering ribonucleic acid, SNP = single-nucleotide polymorphisms, TNIP1 = tumor necrosis factor a-induced protein 3 interacting protein 1
The online version of this paper, found at www.jleukbio.org, includes
supplemental information.
1. Correspondence: Institute of Medical Sciences, University of Aberdeen,
Aberdeen AB25 2ZD, United Kingdom. E-mail: rahul47@live.com
0741-5400/16/0100-737 © Society for Leukocyte Biology
Volume 100, October 2016
Journal of Leukocyte Biology 737
of the LILR family [5–8], suggesting an important role for this
family of receptors in establishing activation thresholds and
regulating myeloid lineage induction of immune responses. The
murine homolog of inhibitory LILR, Pirb, has also been shown to
control the survival and function of MDSCs [9], a label applied to
a diverse range of immature myeloid-lineage cells with regulatory
properties [10], often associated with reduced immune responsiveness to tumor transformation. Mice transgenic for both
LILRB1 and its ligand HLA-G have an expanded population of
MDSCs [11], which can prolong skin allograft survival.
In an effort to delineate the molecular mechanisms underlying
the quiescent nature of monocyte-derived DCs by the ligation of
LILRB1, we have performed genome-wide mRNA expression
analysis on human monocyte derived DCs cultured with LILRB1speciﬁc mAb or isotype control. mRNA expression studies on
human monocyte–derived DCs cultured with LILRB1-speciﬁc
mAbs (henceforth, referred to as LILRB1 DC) revealed the upregulation of mRNA that encodes NF-kB–inhibiting proteins—
ABIN1 (also known as TNIP1) and ABIN3 (also known as TNIP3)
(unpublished data). Here, we describe our analysis of the
ABIN1/TNIP1 protein (A20-binding inhibitor of NF-kB/TNFa–induced protein 3 interacting protein 1) [12] after ligation of
LILRB1 during DC differentiation and show that altering the
expression level of ABIN1/TNIP1 by siRNA-mediated knockdown of gene expression has a signiﬁcant inﬂuence on the
monocyte-derived DC phenotype and function in vitro. We also
examine the expression and function of ABIN1/TNIP1 in
“immunosuppressive” monocytes [13] from ex vivo analysis of
patients with NHL. Our results suggest that LILRB1 is a
potential target to manipulate ABIN1/TNIP1 protein levels
and modulate DC responsiveness in lymphomas and immunemediated diseases.
MATERIALS AND METHODS
Isolation of monocytes from peripheral blood and
nodal biopsies
Healthy donors were identiﬁed at the Institute of Medical Sciences
(Aberdeen, United Kingdom). Patients with suspected follicular lymphoma,
mantle cell lymphoma, or nodular lymphocyte-predominant Hodgkin
lymphoma undergoing a lymph node biopsy were identiﬁed through the
Haematology Outpatient Clinic, Aberdeen Royal Inﬁrmary (Aberdeen,
United Kingdom), and samples were obtained after full informed consent was
given (North of Scotland Ethics Committee, Integrated Research Application
System, project 9412). Peripheral blood obtained from the healthy controls, as
well as lymph node biopsies obtained from patients, were subjected to
negative selection using Depletion MyOne SA Dynabeads (Thermo Fisher
Scientiﬁc, Waltham, MA, USA) to obtain a single-cell suspension of
monocytes.
Differentiation of monocytes into DCs
Monocytes isolated from peripheral blood of healthy donors were differentiated into DCs for a period of 7 d using a 50 ng/ml concentration of
recombinant human IL-4 and GM-CSF (PeproTech, Inc, Rocky Hill, NJ, USA).
Half of the medium was replaced every 2 d with fresh cytokines, and on day 6,
1 ng/ml of bacterial LPS (Sigma-Aldrich, St. Louis, MO, USA) was added for
24 h where required. Ligation of the LILRB1 receptor was mediated by the
addition of puriﬁed anti-LILRB1 (clone 292305, R&D Systems, Minneapolis,
MN, USA; or clone HPF1, eBioscience, San Diego, CA, USA) at a ﬁnal
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Journal of Leukocyte Biology
Volume 100, October 2016
concentration of 5 mg/ml in the presence of 1 mg/ml Protein G (SigmaAldrich). Mouse IgG1k (MOPC21; Sigma-Aldrich) was used as an isotype
control at the same concentration as previously described [4].
siRNA-mediated knockdown of ABIN1/TNIP1 expression
The cells of interest were seeded into 6-well plates at 2 3 105 cells/well in 2 ml
of antibiotic-free RPMI 1640 medium supplemented with 10% heatinactivated human AB serum for 24 h to ensure conﬂuence. For each
transfection, 60 pM ABIN1 siRNA (Santa Cruz Biotechnology, Inc., Santa
Cruz, CA, USA) was used along with 100 ml siRNA transfection medium (Santa
Cruz Biotechnology) and 100 ml siRNA transfection reagent (Santa Cruz
Biotechnology). The cells were then incubated at 37°C, 5% CO2 for an
additional 5 h; following which, the medium in each well containing the
siRNA-treated cells was changed to RPMI 1640 supplemented with 10% heatinactivated human AB serum and 50 U/ml of penicillin-streptomycin and was
incubated for an additional 24 h at 37°C, 5% CO2.
Flow cytometry
The following antibodies were used for ﬂow cytometry: anti-CD3-PE (clone
SK7), anti-CD4-AF700 (clone RPA-T4), anti-CD8-PE-Cy5 (clone RPA-T8), antiCD80-FITC (clone L307), anti-CD86-APC (clone 2331 FUN-1), anti-HLA-DRPE-Cy5 (clone TU36), anti-HLA-ABC-PE (clone G46-2.6), anti-pERK1/2-PE
(clone 25/MEK1), anti-pLAT-AF488 (clone 158-1169), anti-IFN-g-AF700
(clone B27), anti-IL-12p70–PE (clone 20C2) (all BD Biosciences, Franklin
Lakes, NJ, USA); anti-IL-10–PE-Cy7 (clone JES3-9D7; BioLegend, San Diego,
CA, USA); anti-IFN-a-PE (clone 1-D1K; Mabtech, Cincinnati, OH, USA). AntiTNIP1 (ABIN1) antibody (clone 5C4, Abcam, Cambridge, MA, USA) was used
in conjunction with goat anti-mouse IgG (heavy and light chain)-PE
(Beckman Coulter, Brea, CA, USA). Monocytes, DCs, or PBMCs were washed
and incubated at room temperature for 30 min with the above antibodies. The
cells were then ﬁxed with 4% paraformaldehyde, washed and analyzed on a
BD LSR II ﬂow cytometer (BD Biosciences) using FlowJo software (Tree Star,
Ashland, OR, USA). DCs and monocytes were identiﬁed using forward and
side light scatter characteristics. A minimum of 10,000 events were acquired
on all samples.
To assess the macropinocytic capacity of different DC populations, the cells
were incubated with FITC-conjugated dextran molecules at a concentration of
50 mg/ml for 24 h before ﬁxation and ﬂow cytometric analysis.
To quantify cytokine production, DCs, monocytes or PBMCs were treated
with 1 mg/ml monensin (BD Biosciences), ﬁxed with 4% paraformaldehyde,
and permeabilized with methanol before staining for ﬂow cytometry. PBMCs
were stained with T cell-speciﬁc markers to analyze cytokine production from
T cell that were stimulated with different DC populations.
To assess T cell proliferation when stimulated by different DC populations,
CFSE (Thermo Fisher Scientiﬁc)-stained PBMCs were incubated with DCs at a
ratio of 10:1 at 37°C for 5 d; following which, the cells were stained with T cellspeciﬁc markers, ﬁxed, washed, and analyzed on a BD LSR II ﬂow cytometer
using FlowJo software. A minimum of 100,000 events were acquired on all
samples.
Fluorescence and light microscopy
To assess the expression levels of NF-kB p65 in the nucleus of different DC
populations, DCs were seeded into poly-L-lysine–treated wells of a 48 well plate
and left to adhere at 37°C for 2 h. The cells were then ﬁxed with 4%
formaldehyde, permeabilized with Triton X-100, and blocked with 1% BSA in
PBS containing 0.05% Tween 20, all at room temperature. The cells were
stained with an anti–NF-kB p65 antibody (Abcam) for 1 h at room
temperature; after which, they were washed and incubated with a goat antimouse heavy and light chain secondary antibody conjugated to FITC (Abcam)
for 2 h at room temperature. The nucleus of the cells was stained with Hoechst
stain (ImmunoChemistry Technologies, Bloomington, MN, USA) for 5 min.
The cells were then washed with PBS and analyzed on a Zeiss Axio Observer
Z1 inverted microscope (Carl Zeiss Microscopy, Thornwood, NY, USA).
Nuclear expression of NF-kB p65 was analyzed using the ImageJ software (U.S.
www.jleukbio.org
Khanolkar et al. LILRB1 control of dendritic cell function
National Institutes of Health, Bethesda, MD, USA) that quantiﬁed the
ﬂuorescence emitted by ﬂuorochrome-conjugated antibodies speciﬁc to the
NF-kB subunit p65. A maximum of 50 cells were analyzed per treatment per
donor, set up in triplicates.
To assess the phagocytic population of different DC populations, cells were
incubated with 6 mm polystyrene beads at a ratio of 1:3 for 3 h. The cells were
washed with PBS, ﬁxed with 4% formaldehyde, and analyzed on an EVOS 3l
transmitted light microscope (Thermo Fisher Scientiﬁc).
Statistical analysis
Differences in ABIN1 protein expression, NF-kB/p65 translocation,
phagocytic/macropinocytic capacity, cytokine production, expression of
antigen presentation, TLRs, and costimulatory molecules in DC populations,
and phosphorylation of intracellular molecules, and proliferation of T cells
was analyzed using 1-way ANOVA test, followed by the Bonferroni multiple
comparison test. Differences in ABIN1 expression, expression of antigen
presentation and costimulatory molecules, and cytokine production between
monocytes obtained from healthy donors and those obtained from patients
with NHL were analyzed using unpaired t tests. Differences in cytokine
production and expression of antigen presentation and costimulatory
molecules in control monocytes and monocytes obtained from patients with
NHL after treatment with ABIN1 siRNA were analyzed using paired t tests.
RESULTS
Increased expression levels of ABIN1/TNIP1 protein
in monocyte-derived DCs after LILRB1 ligation
mRNA expression studies and intracellular ﬂow cytometry in
monocyte-derived DCs, in which LILRB1 had been ligated
throughout in vitro differentiation, demonstrated enhanced
expression of ABIN1/TNIP1 on an mRNA level (data not shown)
and protein level (Fig. 1A and C) when compared with DCs
cultured with the isotype control antibody. ABIN1/TNIP1
protein levels were signiﬁcantly increased after exposure to the
TLR4 ligand bacterial lipopolysaccharide (P , 0.001) (Fig. 1A
and C). Signiﬁcant differences (P , 0.05) were also noted after
transfection of LILRB1 DCs with siRNA speciﬁc for ABIN1/
TNIP1, where a reduction in protein expression was observed
Figure 1. LILRB1 ligation during in vitro DC differentiation results in higher levels of ABIN1/TNIP1 protein levels. (A and C) Higher ABIN1/
TNIP1 protein levels are evident in LILRB1 DCs and can be signiﬁcantly increased (P , 0.01) after LPS exposure. (B and C) ABIN1/TNIP1 levels
can be signiﬁcantly reduced in LILRB1 DCs using siRNA. (D) LILRB1 DCs display signiﬁcantly elevated levels of CD14 when compared with
control DCs. In all experiments (n = 4 individual donors), bars depict means 6 SEM. CI, conﬁdence interval; Geo-MFI, geometric mean
ﬂuorescence intensity; Gep-MFI, granulin-epithelin precursor mean ﬂuorescence intensity; neg, negative. *P , 0.05 (95% CI), **P , 0.01
(99% CI), ***P , 0.001 (99.9% CI).
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Volume 100, October 2016
Journal of Leukocyte Biology 739
(Fig. 1B and C). LILRB1 DCs expressed signiﬁcantly elevated
levels of CD14 when compared with the isotype control DCs
(Fig. 1D).
ABIN1/TNIP1 inﬂuences NF-kB nuclear
translocation and macropinocytic/phagocytic
functions of LILRB1 DCs
In accordance with ABIN1/TNIP1’s known cellular function, NFkB translocated to the nucleus less efﬁciently in LILRB1 DCs
than it did in isotype control DCs (P , 0.001), but translocation
signiﬁcantly (P , 0.001) increased after siRNA-mediated reduction in ABIN1/TNIP1 expression levels (Fig. 2A).
DCs are characterized by their antigen sampling abilities and
their capacity to secrete cytokines rapidly after recognition of
pathogens or damage-associated molecular patterns. After incubation with FITC-labeled dextran as a surrogate for a ﬂuid
phase antigen, LILRB1 DCs dramatically increased their uptake
capacity after the reduction in ABIN1/TNIP1 levels, as measured
by ﬂow cytometry (P , 0.001; Fig. 2B, upper panel), whereas
phagocytic uptake of 6 mM polystyrene beads, measured by
light microscopy, also signiﬁcantly increased (P , 0.05, Fig.
2B, lower panel).
ABIN1/TNIP1 inﬂuences expression levels of
antigen-presentation molecules and cytokine
secretion in LILRB1 DCs
Flow cytometric analysis of cell surface levels of important ligands
in DC antigen presentation and T cell costimulation demonstrated signiﬁcant increases in amounts of HLA- ABC (P , 0.001)
and HLA-DR (P , 0.05) when ABIN1/TNIP1 levels were
reduced by siRNA-mediated knockdown. This ﬁnding was
particularly strong for HLA-ABC because LILRB1 DCs did not
increase expression after exposure to LPS, unlike isotype control
DCs, but HLA-ABC levels almost quadrupled after reduction in
ABIN1/TNIP1 levels, even in immature LILRB1 DCs (Fig. 3A,
lower panel). Although CD80 and CD86 levels also increased,
this relationship did not reach statistical signiﬁcance (Fig. 3A,
upper panel).
Likewise, siRNA-mediated knockdown of ABIN1/TNIP1 expression signiﬁcantly increased LILRB1 DC production of IL12p70 (P , 0.001) after stimulation with the TLR4 ligand LPS
(Fig. 3B, upper panel). Signiﬁcant increases were also observed
in LILRB1 DC’s capacity to produce IL-10 (P , 0.05) and IFN-a
(P , 0.05) (Fig. 3B, upper and lower panels) following ABIN1/
TNIP1 knockdown.
ABIN1/TNIP1 inﬂuences the capacity of
LILRB1-ligated DCs to activate allogeneic
T lymphocytes
The prime function of DCs is to stimulate speciﬁc T lymphocytes
to initiate an adaptive, antigen-speciﬁc immune response. We
investigated the role that ABIN1/TNIP1 has in regulating the
function of LILRB1 DCs by coculturing the isotype control or
LILRB1 DCs with allogeneic CD4+ and CD8+ T lymphocytes after
siRNA-mediated reduction in ABIN1/TNIP1 expression.
T lymphocyte responses were assessed by ﬂow cytometric analysis
of phosphorylation of key T cell signaling molecules ERK1/2 and
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Journal of Leukocyte Biology
Volume 100, October 2016
Figure 2. Reducing ABIN1/TNIP1 expression signiﬁcantly increases
NF-kB nuclear translocation and the macropinocytic and phagocytic
capacity of LILRB1 DC. Fluorescence microscopy was used to determine
nuclear expression levels of NF-kB/p65, as described in the Materials and
Methods section. (A) Nuclear expression of NF-kB/p65 was signiﬁcantly
lower in LILRB1 DCs than it was in isotype control DCs (P , 0.001)
and was signiﬁcantly restored on siRNA knockdown of ABIN1/TNIP1
(P , 0.001) in semimature LILRB1 DCs. Following ABIN1/TNIP1
knockdown, LILRB1 DCs increased their capacity for macropinocytic/
phagocytic uptake of ﬂuorescently labeled dextran (B, upper panel)
(P , 0.001), as determined by ﬂow cytometry and 6 mm polystyrene beads
(B, lower panel) (P , 0.05), as determined by light microscopy. In all
experiments (n = 6 individual donors), bars depict means 6 SEM. CI,
conﬁdence interval; Geo-MFI, geometric mean ﬂuorescence intensity; neg,
negative; ns, not signiﬁcant. *P , 0.05 (95% CI), **P , 0.01 (99% CI),
***P , 0.001 (99.9% CI). Representative examples of images used to
obtain data depicted in (A) are provided in Supplemental Fig. 1.
www.jleukbio.org
Khanolkar et al. LILRB1 control of dendritic cell function
Figure 3. Reducing ABIN1/TNIP1 expression in LILRB1 DCs increases expression of cell-surface antigen presentation and costimulatory
molecules, with increased expression of proinﬂammatory cytokines. CD80 (ns) and CD86 (ns) (A, upper panel) and HLA-ABC (P , 0.001)
and HLA-DR (P , 0.05) (A, lower panel) were increased in LILRB1 DCs following siRNA-mediated knockdown of ABIN1/TNIP1 expression.
Production of proinﬂammatory cytokines IL-12 p70 (B, upper panel) (P , 0.001) and IFN-a (B, lower panel) (P , 0.05) were also increased
in LILRB1 DCs following treatment with ABIN1 siRNA. In all experiments (n = 6 individual donors), bars depict means 6 SEM. Geo-MFI,
geometric mean ﬂuorescence intensity; neg, negative; ns, not signiﬁcant. *P , 0.05 (95% CI), ** P , 0.01 (99% CI), *** P , 0.001 (99.9%
CI). Representative examples of the combined data are provided in Supplemental Fig. 2.
signiﬁcant changes were observed with respect to T cells capacity
to produce IFN-g when treated with the different DC populations
(Fig. 4C).
LAT using phosphospeciﬁc antibodies. T cell proliferation was
also measured by the loss of CFSE ﬂuorescence from proliferating T cells after 5 d of culture.
We observed no signiﬁcant differences in level of phosphorylation of ERK1/2 (pERK1/2) in both responding CD4 (Fig. 4A,
left panel) and CD8 T lymphocytes (Fig. 4B, left panel) when
stimulated by control or wild-type LILRB1-ligated DCs. However,
a signiﬁcant (P , 0.05) increase in pERK1/2 was seen in both
T cell subsets (Fig. 4A and B, left panel) when stimulated by
LILRB1 DCs carrying the ABIN1/TNIP1 expression knockdown.
A similar result was observed for the phosphorylation of LAT
residue 171 after ABIN1/TNIP1 expression knockdown in
LILRB1 DCs (Fig. 4A and B, middle panel). Analysis of
phosphorylation of LAT residue 226 did not show any speciﬁc
differences (data not shown).
LILRB1 ligated DCs were poor stimulators of allogeneic T cell
proliferation in mixed lymphocyte cultures in comparison to
isotype control DCs, and this was reversed by a reduction in
ABIN1/TNIP1 levels. LILRB1 DCs after ABIN1/TNIP1 expression knockdown stimulated a signiﬁcant increase in the proliferation of CD4+ T cells (Fig. 4A, right panel). No statistically
signiﬁcant changes were observed with respect to CD8+ T cell
proliferation (Fig. 4B, right panel). Furthermore, no statistically
Several studies have reported the presence of an immunosuppressive monocyte population in patients with NHL. Patients with
NHL presenting with increased percentages of these suppressive
monocytes usually display a more progressive disease. We
examined expression levels of ABIN1/TNIP1 in monocytes
obtained from patients with NHL (follicular, mantle cell, or
nodular lymphocyte predominant Hodgkin lymphoma) (n = 12).
Intracellular levels of ABIN1/TNIP1 were signiﬁcantly higher
(P , 0.01) in monocytes obtained from patient samples than
they were from peripheral population of monocytes of healthy
donors and increased after stimulation with TLR4 agonists
(Fig. 5A, left panel). ABIN1/TNIP1 levels were signiﬁcantly
reduced in monocytes obtained from patients with NHL after
siRNA treatment (Fig. 5A, right panel). Patient-derived monocytes expressed lower cell surface levels of CD80 (P , 0.01),
CD86 (not signiﬁcant, [ns]), and HLA-DR (P , 0.001) than did
those of healthy controls (Fig. 5B). Similarly, monocytes from
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Volume 100, October 2016
ABIN1/TNIP1 is expressed at high levels in monocytes
isolated from lymph nodes involved by NHL
Journal of Leukocyte Biology 741
Figure 4. Reducing ABIN1/TNIP1 expression restores the ability of LILRB1 DCs to stimulate allogeneic CD4+ and CD8+ T lymphocytes. No
statistically signiﬁcant difference were observed in the phosphorylation of ERK1/2 in CD4+ (A) and CD8+ (B) T cells when control or LILRB1 DCs
were used as stimulators. Following ABIN1/TNIP1 knockdown in LILRB1 DCs, immature LILRB1 DCs stimulated signiﬁcantly elevated
phosphorylation of ERK1/2 (P , 0.05) in allogeneic T cells (A and B, left panel), whereas the semimature LILRB1 DC population stimulated
signiﬁcantly elevated phosphorylation of LAT171 (P , 0.05) in allogeneic T cells (A and B, middle panel). Knockdown of ABIN1/TNIP1 resulted
in a signiﬁcantly increased capacity of both immature (P , 0.01) and semimature (P , 0.05) LILRB1 DCs to stimulate CD4+ T cell proliferation
(A, right panel). Results for CD8+ T cell proliferation were not signiﬁcant (B, right panel). (C) Reducing ABIN1/TNIP1 levels in LILRB1 DCs had
no statistically signiﬁcant effect in stimulating production of IFN-g in CD3+ T cells. In all experiments, statistical comparisons were made between
unstimulated T cells and T cells stimulated with different monocyte-derived DC populations. In all experiments (n = 6 individual donors), bars
depict means 6 SEM. Geo-MFI, geometric mean ﬂuorescence intensity; CI, conﬁdence interval; neg, negative; ns, not signiﬁcant. *P , 0.05
(95% CI), **P , 0.01 (99% CI). Representative examples of the combined data are provided in Supplemental Fig. 3.
patients produced signiﬁcantly less IL-12p70 (P , 0.01) and IFN-a
(P , 0.05) (Fig. 5C). Signiﬁcant differences were not observed in
IL-10 production of monocytes between those of patients with
NHL and those from healthy controls (Fig. 5C).
ABIN1/TNIP1 regulates the phenotype and function of
monocytes from patients with NHL
Monocytes obtained from healthy controls after LPS stimulation
signiﬁcantly increased their expression of CD80 (P , 0.01),
CD86 (P , 0.05), HLA-DR (P , 0.05), IL-12p70 (P , 0.05), and
IFN-a (P , 0.05) (Fig. 6A and B). Monocytes obtained from
patients with NHL after LPS stimulation did not signiﬁcantly
increase expression of CD80, CD86, HLA-DR, IL-12p70, or IFN-a
possibly because of elevated levels of ABIN1/TNIP1. siRNA742
Journal of Leukocyte Biology
Volume 100, October 2016
mediated reduction in ABIN1/TNIP1 expression levels and LPS
stimulation produced statistically signiﬁcant increases in expression levels of CD80 (P , 0.05), CD86 (P , 0.01), and HLADR (P , 0.05) in the monocytes isolated from patients with
NHL (Fig. 6A). Additionally, signiﬁcant increases (P , 0.05) in
production of IL-12p70 and IFN-a were observed in monocytes
of patients with NHL, after stimulation with LPS, and reduction
in ABIN1/TNIP1 levels. No signiﬁcant changes were observed
for IL-10 (Fig. 6B).
DISCUSSION
The plasticity of DCs, with respect to its evolving phenotype or
function as an initiator of immune responses or an inducer of
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Khanolkar et al. LILRB1 control of dendritic cell function
Figure 5. Monocytes from patients with lymphoma express higher levels of intracellular ABIN1/TNIP1 ex vivo, poorly express cell-surface antigen
presentation and costimulatory molecules, and produce limited amounts of proinﬂammatory cytokines. (A, left panel) Monocytes obtained from
patients with NHL expressed ABIN1/TNIP1 at signiﬁcantly (P , 0.01) higher levels than did monocytes obtained from healthy controls. (A, right
panel) ABIN1/TNIP1 levels in patient monocytes could be signiﬁcantly reduced following treatment with ABIN1 siRNA. Patient monocytes had
lower cell-surface levels of CD80 (P , 0.01), CD86 (ns), and HLA-DR (P , 0.001) (B) and produced signiﬁcantly less IFN-a (P , 0.05) and IL12p70 (P , 0.01) (C). Results for IL-10 were not signiﬁcant. (B and C) Black bars indicate samples were stimulated with 1 ng/ml LPS, whereas
white bars are unstimulated samples. In all experiments (n = 12 individual donors), bars depict means 6 SEM. Geo-MFI, geometric mean
ﬂuorescence intensity; CI, conﬁdence interval; HC, healthy control; neg, negative; ns, not signiﬁcant. *P , 0.05, **P , 0.01 at 95% CI,
***P , 0.001 at 99.9% CI. Representative examples of the combined data are provided in Supplemental Fig. 4.
tolerance, has made it an attractive cellular target for immunotherapy in cancer and autoimmunity. A key component of DC
activation and maturation, after pattern recognition, is activation
of the transcription factor NF-kB, which is released from a
complex, regulated control system in the cytoplasm and relocates
to the nucleus, where it initiates the expression of hundreds of
genes encoding proinﬂammatory proteins. Inhibition of canonical NF-kB signaling has been shown to reduce the functionality
of both CD34+ myeloid DCs and monocyte-derived DCs by
regulating the survival, differentiation, and maturation of both
DC populations [2, 14, 15].
We have demonstrated higher expression levels of the NF-kB
regulator ABIN1/TNIP1 in DCs in which the HLA class I–speciﬁc
inhibitory receptor LILRB1 has been ligated during in vitro
differentiation from PBMCs. We have conﬁrmed previous
ﬁndings that LILRB1 DCs retain surface expression of CD14 after
their in vitro differentiation from monocytes [4]. In this study, we
showed that modulating the expression levels of the ABIN1/
TNIP1 protein reversed the functional effects of LILRB1 ligation,
allowing the monocyte-derived DCs to partially up-regulate cell
surface expression of antigen-presenting and costimulatory
molecules, to produce cytokines, and to stimulate T cell
activation in response to challenge with LPS. The reduction of
ABIN1/TNIP1 in LILRB1-ligated, monocyte-derived DCs leave
the resultant DC population with a phenotype that bares
resemblance to the “semimature” DC population that is
extensively reviewed in the following study [16]. Our results
suggest ABIN1/TNIP1 is a potential regulator of monocytederived DC activation, and the increased ABIN1/TNIP1 expression after self-HLA recognition by LILRB1 is a mechanism
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Volume 100, October 2016
Journal of Leukocyte Biology 743
Figure 6. Reducing expression of ABIN1/TNIP1 in monocytes from patients with lymphoma restores cell-surface expression of CD80 and HLA-DR
and signiﬁcantly increases expression of IL-12p70 and IFN-a. (A) Lowering ABIN1/TNIP1 expression resulted in signiﬁcantly increased expression
of CD80 (P , 0.05), CD86 (P , 0.01), and HLA-DR (P , 0.05) in the monocytes of patients with lymphoma after stimulation with LPS. (B) After
ABIN1/TNIP1 knockdown and LPS stimulation, the monocytes of patients with NHL produced signiﬁcantly greater amounts of IL-12p70 (P , 0.05)
and IFN-a (P , 0.05), whereas results for IL-10 were not signiﬁcant. Black bars indicate samples were stimulated with 1 ng/ml LPS, whereas white
bars are unstimulated samples. In all experiments (n = 12 individual donors), bars depict means 6 SEM. Geo-MFI, geometric mean ﬂuorescence
intensity; CI, conﬁdence interval; HC, healthy control; neg, negative; ns, not signiﬁcant. *P , 0.05, **P , 0.01, ***P , 0.001 at 95% CI.
Representative examples of the combined data are provided in Supplemental Fig. 4.
establishing a threshold for NF-kB translocation and DC
maturation in response to triggering of pattern recognition
receptors. The increased production of IFN-a we detected is
consistent with a report of ABIN1/TNIP1 involvement in
regulating cellular antiviral responses [17].
ABIN1/TNIP1 functions in cooperation with the ubiquitinsensing regulatory protein TNFAIP3 (TNF-a–induced protein 3),
also known as A20, to regulate the ubiquitination of the NF-kB
inhibitory protein Ik B kinase-g [18], thus controlling its
proteasomal degradation. ABIN1/TNIP1 also functions to prevent TNF-a–induced apoptosis [12]. Genetic knockout of
ABIN1/TNIP1 is lethal in embryonic mice, but hemizygous litter
mates [19] or mice with an introduced, nonfunctioning mutation
of the polyubiquitin-binding domain [20] are highly susceptible
to the development of autoimmune conditions [21]. In addition,
many genetic studies of autoimmune conditions in human
populations have identiﬁed SNPs in TNIP1 and TNFAIP3 genes as
susceptibility factors for the development of systemic lupus
erythematosus [22, 23], psoriasis [24, 25], systemic sclerosis [26,
27], and myasthenia gravis [28]. One hypothesis suggests that
these SNPs inﬂuence expression levels of the TNIP1 gene, as was
shown for lower ABIN1/TNIP1 protein levels in a limited cohort
of systemic sclerosis patients [26], thus potentially lowering
immune activation thresholds. This hypothesis is consistent with
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Journal of Leukocyte Biology
Volume 100, October 2016
our ﬁndings that lowering ABIN1/TNIP1 protein levels in
monocyte-derived DCs allows them to achieve a “semimature”
state and to activate T cell responses.
Previously, we demonstrated that LILRB1 ligation during
differentiation of DCs in vitro resulted in a phenotype in which
the cells remain CD14+ and express low levels of HLA-DR, which
is not up-regulated on LPS exposure [4]. This cellular phenotype
resembles that of a population of “immunosuppressive monocytes” detected in patients with a variety of hematologic [13, 29]
or other malignancies [30–32]. These immunosuppressive
monocytes are sometimes referred to as MDSC, and their
numbers correlate with a poorer prognosis in several studies [32,
33], with their poor stimulatory capacity for T cell activation
often attributed to contribute to this effect. When comparing the
monocytes obtained from biopsies of patients with NHL to
circulating monocytes from healthy controls, we observed that
patient monocytes had lower surface expression of antigen
presentation and costimulatory molecules. Patient monocytes
also expressed intracellular levels of ABIN1/TNIP1 protein
approximately twice that of monocytes obtained from healthy
donors. Reducing ABIN1/TNIP1 expression levels, followed by
LPS stimulation, allowed these patient cells to increase expression of relevant cell surface molecules, secrete cytokines, and
potentially activate T cell responses.
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Khanolkar et al. LILRB1 control of dendritic cell function
LILRB1 is expressed by .99% of monocytes, and it is plausible
that HLA class I–mediated inhibition of monocyte differentiation
is the cause of the increased ABIN1/TNIP1 levels in the
immunosuppressive monocyte population, as suggested by previous studies of murine MDSC [9, 11]. Although tumor cells
often down-regulate speciﬁc HLA antigen expression to escape
recognition by class I–restricted cytotoxic T lymphocytes [34],
LILRB1 recognizes all HLA-A, HLA-B, and HLA-C antigens and
is unlikely to be affected overall by speciﬁc HLA antigen loss. In
addition, many tumors express the nonclassic HLA-G protein
[35], an efﬁcient ligand for LILRB1 [36].
Further investigation of the regulatory mechanism we have
identiﬁed is warranted in view of the novel functions of ABIN1/
TNIP1 [37] in control of cellular functions. However, our
ﬁndings in this study suggest the LILRB1–ABIN1/TNIP1 pathway
is a potential target for manipulation of immune activity, perhaps
by blocking LILRB1 interactions with HLA class I in lymphoma
and other malignancies to reduce ABIN1/TNIP1 levels, which
may allow maturation and differentiation of immunosuppressive
monocytes into functional antitumor antigen-presenting cells.
Alternatively, the use of antibody or recombinant protein
therapies [38] to ligate LILRB1 should increase ABIN1/TNIP1
levels and activation thresholds in autoimmune disease and
organ transplantation.
AUTHORSHIP
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
R.C.K, M.K, A.R, and N.T.Y performed experiments and
collected and analyzed data; R.C.K and N.T.Y planned the
experiments; A.L and M.A.V contributed patient samples; and
R.C.K and N.T.Y wrote the manuscript, with valuable contributions from A.L and M.A.V.
16.
17.
18.
ACKNOWLEDGMENTS
This study was funded by the Biotechnology and Biological
Sciences Research Council (Wiltshire, United Kingdom), Tenovus
Scotland, and the University of Aberdeen. We thank all of the
members of the laboratory (Immunity, Infection and Inﬂammation, University of Aberdeen) for their support and the ﬂow
cytometry (Raif Yucel) and microscopy (Kevin Mackenzie)
facilities at the University of Aberdeen for their technical support.
DISCLOSURES
19.
20.
21.
22.
The authors declare no conﬂicts of interests.
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KEY WORDS:
LILRB1 immunosuppression lymphoma DC maturation
inhibitory receptor
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1
Impact statement
In recent years, the country and the global healthcare system have witnessed a
progressive development of cancer cases. Cancer is one of the increasing health threats affecting
a majority of the country`s population. It is estimated that 50% of the population will be
diagnosed with cancer in their lifetime (Cancer Research UK, 2019). This trend is associated
with the increasing incidents of exposure to various challenges that would trigger cancer
development. A majority of the population has been diagnosed with lymphatic cancer trends.
This trend is associated with undermining the immune system responsible for handling the issues
affecting the health of individuals (Newman, 2018). This system is responsible for the
development of defensive mechanisms which would prevent illnesses.
The system operates through the cells referred to as lymphocytes. In recent years, there
has been a rise in the overall need for screening and monitoring the population to determine
disease development and progression (McKee et al., 2021). The continued analysis of the health
development trends has triggered a demand for better insights into the prevalence of cancer and
the causative factors. One of the common issues that have been witnessed historically is the
continued progression of cancer. Immune surveillance trends have revealed that the ability of the
human body to fight cancer cells is affected by various factors like the changes occurring in the
underlying cellular structures and potential mutation (Beatty & Gladney, 2015).
Cancerous cells are attributed to increased growth which affects the capacity of the
human body to fight them. The recent research has focused on determining the rationale for the
current prevalence and increased cancer growth. Immune evasion is a common trend that has
2
been witnessed and recorded in various settings depending on the cancer involved (Muenst et al.,
2016). It is essential to appreciate this trend’s challenges to the underlying populations
considering the diagnosis and treatment processes. The treatment outcomes of the underlying
conditions have been undermined by the prevailing challenges in diagnosis and identification.
Immune evasion is a trend that has affected cancer diagnosis through the mechanisms that the
proposed study will examine. The trends in determining the progression of certain cancer types
like lymphoma cells (Carosella et al., 2021).
This study aims to determine the evasion and hiding mechanisms that cancerous cells in
the human body systems utilise to reduce the detection trends and effectiveness. The primary
benefits that the proposed study will provide are related to the development of a reliable
diagnosis and treatment intervention which will be informed by strategic identification and
determination of cancerous cells. This project will provide insights into the primary mechanisms
that have been used and observed in cancerous cells within the lymphatic system. It is expected
that the research will determine the evasion mechanisms through the abnormalities that occur
within the cellular level, informing hiding from conventional detection mechanisms. Since the
study will determine the mechanisms and effects on the diagnosis processes, recommendations
will be provided to support future treatment procedures in cases where hiding has been recorded.
3
Introduction
In the healthcare systems, the primary goal for the underlying stakeholders, including the
government and providers, is to promote community wellness. Diseases have been reported over
the years where diverse effects have occurred, ranging from permanent disabilities to death.
Cancer is one of the leading causes of death in many jurisdictions and countries, including the
United Kingdom (Cancer Research UK, 2019). The country estimates that at least 50% of the
population will be diagnosed with cancer. This trend is increasing with the current factors that
have been associated with the prevalence of different types of cancers. One of the common types
of cancers reported within the country is lymphatic cancer.
Lymphoma cancer affects the lymphatic system, which is responsible for establishing
reliable mechanisms for fighting diseases and illnesses (Padera et al., 2016). The system
comprises critical organs, including the lymph node, thymus gland, spleen and bone marrow.
These organs form a complex system whose interactions create a cohesive mechanism for
fighting diseases. According to Cancer Research UK (2019), It is reported that the people
diagnosed with non-Hodgkin lymphoma have a 70% survival rate compared to the healthy
population in a span of five years. It follows that detecting the defensive mechanisms that the
cancerous cells exhibit at an early stage is essential for developing effective diagnosis and
treatment interventions. It is essential mentioning that in the United Kingdom, the rate of diffuse
large B cell lymphoma has been increasing annually (Sehn & Salles, 2021). The recent trends
show that the country has at least 5500 people who have been diagnosed with this condition, this
type of cancer is among the leading causes of death compared to the rest (Cancer Research UK,
2019).
4
One of the factors that will inform the development of the different elements which
define the defensive mechanisms used in immune evasion. It is worth understanding the
condition by focusing on the causes, manifestations and effects on the human body, considering
health outcomes. Non-Hodgkin lymphoma is a collection of blood-related cancers which affect
the human body. This cancer arises from the white blood cells and is associated with adverse
effects ranging from reduced immunity to pain in different body parts like the chest (Schwock &
Geddie, 2012).
Over the past decades, continued research has been executed to determine the causes,
occurrence, prevalence and diagnosis of Non-Hodgkin lymphoma. However, recent studies show
that the exact cause of this trend is unknown (Chihara et al., 2015). Associated factors have been
reported, and their significance examined to determine their relationship with the occurrence of
the condition. One of the factors that have been associated with the occurrence of the condition is
a mutation in the DNA elements responsible for the white blood cell parts. The mutation
occurring within the lymphocytes has been associated with an increased risk in the occurrence of
abnormalities which in the process have triggered the occurrence of Non-Hodgkin lymphoma
(Vaque et al., 2014). DNA is an essential part of the human body and cells because it is
responsible for providing the foundational frameworks that inform cellular operations. A
mutation in the cellular DNA affects the normal growth, which may lead to abnormal
multiplication, which leads to Non-Hodgkin lymphoma (Scoville, 2019). The uncontrolled
multiplication of the lymphatic cells has created a health challenge, including tumours. These
tumours may lead to uncontrolled pain depending on the affected areas. It is essential to mention
that lymphocytes affected by the DNA mutation may manifest in various areas, primarily in the
5
lymphatic areas. For example, people diagnosed with this condition may report abnormal
lymphocyte growth in either one of multiple lymph nodes, including the groin, armpit and neck.
Past research shows that the condition can spread to other parts of the body, including the
lungs, central nervous system, stomach and but not limited to the liver and spleen (Shankland et
al., 2012). It is worth mentioning that Non-Hodgkin lymphoma initiates its growth within the
organ setting instead of the lymph nodes. This condition is associated with adverse effects
depending on the developmental stage. For example, the common symptoms associated with
Non-Hodgkin lymphoma include painless swelling in the lymph nodes, which may appear on the
groin, neck, or the armpit. The rationale for the occurrence of swelling in these areas is that
lymph nodes are essential organs which contain white blood cells, which are necessary for
fighting diseases and illness prevention (Rosales, 2020).
Some of the other common symptoms that people diagnosed with Non-Hodgkin
lymphoma may report include sweating at night, weight gain, fever, breathlessness and but not
limited to itchy skin. On the same note, people diagnosed with this condition may record swollen
lymph glands, which may occur in the neck region, including the tonsils and skin rashes. These
symptoms are common in many patients diagnosed with the condition (Watal et al., 2018). It is
worth mentioning that only a few people who have been diagnosed with the condition may report
cellular abnormalities in their bone marrow. However, the prevailing symptoms may lead to
chronic tiredness, risk of infections due to the weaknesses of immunity and excessive bleeding
when an open wound is incurred. It is recommended that the affected parties should seek medical
interventions when they report the symptoms above (Cancer Research UK, 2019). Similarly, it is
recommended to seek medical interventions when a patient reports recurrent swollen and
sometimes painless glands for over one and half months.
6
Form another dimension, Non-Hodgkin lymphoma presents in various ways, as
mentioned above. Practitioners work towards detecting the condition within the earlier stages,
enabling them to develop effective treatment options and reduce adverse effects from a health
dimension. The manifestation of the condition can be explored through the various stages which
inform the diagnosis process (Gknation, 2015). At stage 1, the disease affects one lymph node,
including the neck, groin or armpit. Also, at this stage, the severity of the condition concerning
its spread is limited. At stage 2, the disease spreads to other lymph nodes. In stage 3, the disease
spreads to the lymph nodes on the upper and lower body sections. The last stage is where the
disease spreads throughout the lymphatic system and attacks the bone marrow. The medical
experts classify patients depending on the severity and manifestation of the symptoms (Rosolen
et al., 2015). In stage A, doctors refer to patients diagnosed with Non-Hodgkin lymphoma but
have no additional symptoms. In stage B, the doctors classify the patients who have additional
symptoms, including unexplained weight gain and fever.
One challenge that has affected the diagnosis and treatment of patients diagnosed with
Non-Hodgkin lymphoma is the immune escape and evasion mechanism that the associated cells
exhibit. This trend is responsible for the uncontrolled growth of cancerous cells (Banerjee &
Vallurupalli, 2022). This growth has caused various challenges, as seen in the symptoms and
consequences linked with Non-Hodgkin lymphoma. The mechanisms which the cells use in
evading detection have caused additional challenges to the healthcare setting due to the
widespread of the disease without detection. It is worth mentioning that cancerous cells are
known for masquerading as normal cells to avoid detection and ensure maximum adaptation
within the human body. Such trends have enabled cancerous cells to avoid detection (Carosella
et al., 2021).
7
One of the factors enabled the development of escape mechanisms in cellular mutation. A
mutation is defined through the occurrence of abnormalities which may be reported within the
human body. While numerous interventions like immunotherapy have been developed to reduce
the risks of evasion, such incidents continue to occur where increased Non-Hodgkin lymphoma
cases have been reported (Zappasodi et al., 2015).
Much of the research into the subject was completed in the 20th century. The increased
awareness about mutation in the cellular structure has triggered more research into the spread of
cancer in the human body. In the mid-20th century, it was reported that the continued growth of
cancerous cells. Throughout the studies, it was determined that the core approaches that
accelerated immune escape in the B cells lymphoma is:
1. The loss of antigenicity
2. Loss of immunogenicity
3. Triggering immunosuppressive microenvironments around the tumours (Bates et al.,
2018).
These factors are essential breakthroughs in the healthcare setting because they create a
reliable framework for understanding how cancerous cells spread from one part or system to
another. In the case of non-Hodgkin lymphoma, the discovery offers insights into determining
the best approaches to promote early detection, diagnosis, and determination to facilitate the
treatment processes (Bates et al., 2018). On the same note, it is worth appreciating the current
developments because they provide a foundation through which the problem is understood.
Immune escape mechanisms are essential discoveries in the scientific fields because they provide
a foundation for understanding how the cells masquerade the normal cellular systems and avoid
detection by the conventional diagnosis tools and mechanisms.
8
It is worth understanding that the invisibility nature of the tumour cells may be informed
by internal behaviour, which may external factious and internal regulation mechanisms may
influencers; it is essential to appreciate that the internal mechanisms that involve downregulating
the MHC play a critical role in adapting to the systemic attributes, hence avoiding detection
(Zhang et al., 2021). On the other hand, the co-stimulation of CD86 and 80 molecules and the
adhesive attributes of CD54 molecules play a critical role in supporting evasion (Nukada et al.,
2011).
The down-regulation of the CD58 molecules creates a framework that allows the
molecules to evade the natural killer cells, which are responsible for the prevention of illnesses
by destroying foreign antigens. These cells are activated by the loss of MHC-1, which is
essential in designing a defensive mechanism (Ma et al., 2016). It is essential to mention that the
tumours and cancerous cells are visible to the immune system. However, a positive reception is
inhibited by resistance to the apoptosis signals. This approach reduces the effectiveness of the
immune system response towards invasive and foreign cells, which creates a conducive growth
environment for the development of larger tumours. While the immune system recognises the
tumour cells, its effects are inhibited by the internal resistance to the apoptosis signals, which
develops due to the continued interactions with the arising exposure (Nicholson, 2016).
The tumour cells, in their resistance, implement and adopt diverse mechanisms. These
mechanisms bare the loss of FAS and hyperexpression of the molecules associated with the resist
apoptosis molecules (Sordo-Bahamonde et al., 2020). Throughout the overall interactions within
the human body, the resistance creates an internal defence system which undermines the
effectiveness of the actions performed by the natural killer cells. On the other hand, it is essential
to appreciate the inhibition action of the inhibitory ligands, which are primarily exhibited by the
9
lymphoma cells. These cells send a signal to the macrophage based on the interaction between
the cells and the ligand SIRPa (Pham et al., 2018).
On the other hand, the present cells FAS-L initiate a procedure to attack and kill the
immune system cells. This approach has enabled the tumour cells to reduce the mechanisms of
action that the immune system presents throughout the detection and intervention processes
(Strasser et al., 2009). The capacity to achieve this goal is based on the internal attributes that
define some lymphoma molecules. Some of these molecules can support antigen presentation,
which enables the overall binding of the inhibitory receptors. This approach supports the
activation of T cells which are then inhibited and blocked through the CTLA-4 (Asrir et al.,
2022).
This action is achieved through immunosuppressive mechanisms, which reduce the
effectiveness of the T and NK cells which play a critical role in the immune response processes.
The resulting interaction between the tumour cells and their microenvironments creates a
sustained platform that undermines the immune system’s effectiveness, leading the cells to
inhibit the action of the immune system, which creates an independent and undisrupted growth
microenvironment for the development of the tumour cells (Ribatti, 2021). This interaction
allows the cancerous cells to spread throughout the respective systems, manifesting in stage A or
B of the disease.
Overall, the loss of antigenicity is one of the approaches that the tumour cells initiate and
support in achieving immune evasion and escape (Bates et al., 2018). The tumour cells in this
context reduce the capacity to trigger the response of the immune system through the T cells.
This approach reduces the immune system’s effectiveness in developing a reliable framework for
fighting the antigens (Gonzalez et al., 2018). T cells are informed by the desire to fight
10
infections. However, a reduced capacity to elicit a positive immune reaction to tumour cells
where the immune system perceives them as normal agents in the body increases the chances of
growth and spread to the other body parts (Dhatchinamoorthy et al., 2021).
This research is significant because it gathers information about one of the sensitive areas
in medical research concerning the rationale for the reduced detection and diagnosis of
lymphoma. This study presents a strategic platform which will inform future research and the
clinical interventions in cancer diagnosis and treatment (Sehn & Salles, 2021). It is essential to
explore additional factors that have undermined their effectiveness in disease detection and
treatment with the current diagnosis process.
The proposed study aims to examine the different mechanisms that have informed the
capacity to evade the immune system by the B cells lymphoma. This study will consider some of
the core issues surrounding the current trends in immune escape of the associate cells. The
primary focus will be to execute a statistical analysis of the three initially defined mechanisms
that inform the immune escape processes and actions. The proposed analysis will provide a highlevel overview of the forces influencing the successful prevalence of the disease by evading
detection during diagnosis (Zhang et al., 2021).
The proposed study aims to gather statistical and clinical information about the different
mechanisms that B cell lymphoma utilises in achieving immune escape. This goal will be
achieved through exploring the past literature and carrying out a statistical examination of the
presenting laboratory data. The results will be graphically presented. Overall, the study aims to
examine the immune escape mechanisms of the B cell lymphoma using the in-vitro laboratory
exercise in the associated patients (Khanolkar et al. 2016). The primary focus will be on the
expression mechanisms that the CD 8, 14, 19 and 25 markers exhibit in addition to the LILRB1
11
in determining the factors aiding in the immune escape mechanisms and success (Bates et al.,
2018).
This study hypothesises that the presentation of the LILRB1 in the infected patients has a
higher probability of causing the tumour immune system to escape (Bates et al., 2018).
Throughout the study, the research will determine the potential relationship between LILRB1
and the manipulation of the expression of the associated cells, including TNIP1, which in the
process leads to immune escape (Carosella et al., 2021). The study’s outcomes will promote
understanding of the occurrence of lymphoma and the factors undermining the effectiveness of
the currently adopted diagnosis mechanisms. The study will provide a high-level overview of the
immune system escape process focusing on the three mechanisms which B cell lymphoma
exhibit and utilise. Since the study will involve primary analysis of blood samples, it will provide
a detailed outcome concerning the presentation of B cell lymphoma throughout the human body
outlining the role of LILRB1 in supporting and accelerating immune escape. It is expected that
the study will provide essential insights into the immune escape mechanisms understanding the
causative factors and their role in facilitating the growth of tumours in lymphoma patients.
12
Methods
In every research, it is essential to establish a reliable methodology to facilitate data
collection. The selected data collection process should align with the presenting research goals
and objectives. In the previous section, the proposal introduced the current research in cancer
treatment processes. One of the findings outlined is that cancer treatment remains challenging
due to the arising effects that certain molecules and cells exhibit, making it hard to detect.
Immune escape is a common challenge that affects the cancer diagnosis processes (Cancer
Research UK, 2019). In this context, cells exhibit various attributes that are mainly acquired that
enable them to escape the detection and diagnosis processes. Such attributes have undermined
the early detection of cancer (Bates et al., 2018). Early detection is the desired attribute because
it enables researchers and medical experts to develop effective measures to prevent further
spread to other body parts. In the proposed research, an experimental analysis of the behavioural
trends of the obtained cancer cells will be observed within the laboratory setting to establish the
best outcomes that best align with the current literature on immune escape mechanisms.
The proposed study will occur within the laboratory setting because it provides a reliable
environment away from external factors that may affect the effectiveness of the assessment
process. The laboratory environment secludes the external factors that may undermine the
integrity of the process and outcomes. This project will be designed in an experimental model.
The experiment will collect blood samples from healthy donors. The samples will be collected
and cultured within the laboratory setting, where flow cytometry will be employed in the
assessment processes. Throughout the analysis, records will be made based on the behavioural
trends that the cells exhibit under the treatments implemented. The data collected will be
analysed using statistical mechanisms to generate conclusive outcomes. The outcomes will
13
promote understanding B cell lymphoma behaviour and immune escape (Beatty & Gladney,
2015). It is projected that the outcomes will supplement the current practices within the medical
fields, where more information will be documented about cancer cell preventive mechanisms
that make it hard to detect and diagnose patients. The following section outlines some of the core
materials that will be used throughout the laboratory experiment.
Materials required
The proposed study will utilise multiple resources to facilitate the analysis processes. The
rationale for the selection of these resources is informed by the idea that they best align with the
presenting research requirements. The core resources will include anti-LILRBI functional grade,
anti-TNIP1, protein G, RBC lysis buffer and fix and perm. On the other hand, the research will
rely on RMMI 1640 medium and anti CD8 and CD14. Similarly, the research will utilise normal
mouse serum and IgG1 kappa FITC and PE. These resources will be strategically labelled to
facilitate easy recognition in the laboratory setting. The primary role of these resources and
materials is to facilitate the analysis of the collected samples in the laboratory. The samples will
be analysed within a controlled environment where an experimental and control group will be set
up. The setting will provide a reliable environment where information about the changes in each
sample will be documented.
Sampling and data collection process
In the research, the primary foundation for ensuring maximum returns and outcomes will
be based on the capacity to collect samples from the ideal participants. The research process will
start by identifying potential candidates who will provide blood samples. This step is vital
because it will ensure that only the ideal participants are identified and enrolled. Convenience
14
sampling will be utilised after identifying the target population. This population aligns with the
research goals and the impact statement, where the primary goal is to learn immune escape
mechanisms. The selected populations will be identified and enrolled through convenience
sampling. This approach will allow the researcher to enrol a section of the patients who have
been diagnosed with B cell lymphoma to ensure that only the selected participants meet the
desired attributes. The selected participants will be grouped into two categories. These categories
define the participants based on their attributes from a health dimension. The experimental group
will comprise patients who had been diagnosed with B cell lymphoma. It is essential to mention
that the patients will be based on either past or current cancer diagnoses. This population will be
conveniently randomised and enrolled into the experimental group. The second group will
comprise the parties who will be enrolled on the control category. The control group will
comprise healthy people who will be conveniently randomised.
During the initial enrolment, the researcher will design and submit consent forms. Obtaining
consent will be based on first educating the target participants about the research, the
expectations and the roles during the data collection processes. On the same note, the participants
will be sensitised about the research process and their responsibilities concerning the data
collection process. The second step will involve collecting blood samples from the participants.
Blood samples will be obtained within a duration of 6 weeks, where the participants will provide
three samples each week. It is essential to mention that the blood samples will be collected from
the experimental and control groups to facilitate the research process through comparison. The
proposed study will collect 5 samples from the target participants, where they will be stored
according to the prevailing laboratory procedures to protect them from contamination.
15
The proposed protocol
This research will be collected through the laboratory set-up, where the primary focus
will be to ensure maximum alignment with the primary goals. The research will be achieved
through a series of stages defined in a strategic protocol. The first stage is to place 100 µl of the
whole blood in to 6 Eppendorf tubes and then add 2 µl of the anti-LILRBI antibody and protein
G (concentration of 5 µg/ml in the presence of 1 µg/ml) to each tube. The samples will be
incubated at 37°C for allotted time (0, 4hr, and 24hr), where isotype control within the flow
cytometry will be applied. On the other hand, 100 µl of the red cell lysis buffer will be achieved
following the incubation in RT for 10 min where the samples will be combined. In the next step,
the research will add 1 ml of PBS wash and then using the centrifuge at 300g for 3 min, after that
re-suspending of cell pellet in 50 µl Permeabilisation Buffer (B) and 2 µl anti-TNIP1 antibody
should take place. Where IgGk will be placed as a control. This step will facilitate the control
framework for the experiment to ensure that the standard procedures are followed, and that the
analysis achieves the intended goals. The resulting samples will be stored at RT for 10 min, after
that added 1 ml of PBS wash then centrifuge it. On the same note, the researcher will then add 2
µl of goat anti-mouse IgG-PE, where the resulting sample will be placed in the dark at RT for 20
min. The next step will allow the researcher to add 1 ml PBS wash and centrifuge, followed by
the addition of 10 µl Normal Mouse Serum, where the mixture will be placed in the dark at RT
for 20 min. On the same note, add 2 µl Lineage-specific CD marker antibody-FITC onto the
initial mixture will be placed in the dark at RT for 20 min. The following step will be to apply
the centrifuge after the addition of 1 ml PBS wash.
The next step will be completed following the suspension of the cells in the resulting samples.
The cells will be added to the fixation buffer (A), where the resulting components will be mixed
16
to obtain a uniform solution. The resulting samples will be placed in the dark at 4°C, where the
last stage will be to observe the cellular behaviour on the flow cytometer. These stages will
ensure that the resulting samples best align with the proposed research goals and expectations.
Flow cytometry
This research will use 16 the BD Accuri™ C6 Plus Flow Cytometer technology in the
analysis of the resulting samples. This device will allow the researcher to observe and analyse
the chemical attributes associated with the selected samples (Vembadi et al., 2019). This device
will be used as a tool for analysing and counting the cells in the peripheral samples. One of the
motivations for using this tool is that it provides a high-level overview of the underlying samples
exhibit cellular behaviour. On the same note, the device will make it easy to determine the
behavioural trends in the cells observed within the selected samples (Adan et al., 2016). The
observation will be influenced and supported by the laser technology that uses fluorescent
lighting mechanisms to analyse the cells. One of the benefits that the tool offers is that it creates
a high-level framework for understanding the cellular attributes in the selected samples. The setup will ensure that essential details about the blood samples are documented concerning cell
count. It is essential to place the set-up in an ideal laboratory environment. The optimum
variables the researcher must guarantee in the set-up are temperature and humidity. For example,
this set-up will be established in an environment with acquiring at least 10,000 events on all
samples. The output from the tool will be used for statistical analysis processes where graphs and
supporting information will be produced.
17
Data analysis
As mentioned above, the proposed study will gather evidence about the topic in six
weeks. During this duration, statistical data will be collected from the experimental design
described above. The results will be used as an input for further analysis. This analysis will allow
the researcher to observe some of the core aspects that the cells present and their role in immune
escape. The results obtained from the flow cytometer will be subjected to a statistical analysis
where the researcher will utilise the 1-way ANOVA test. This test will provide a reliable
platform for determining the potential links and differences between the CD markets and the
TNIP1 and LILRB1 (Khanolkar et al., 2016). The primary goal of this analysis is to compare and
report on the similarities and differences observed in the control and experimental groups
concerning cellular behaviour. The results will be analysed to determine their alignment with the
initially defined mechanisms that cell utilises in immune escape.
Schedule
This project will be collected in strategic stages. At each stage, specific tasks will be
completed. The project will start with the selection of a topic and gathering the available
literature. This stage will provide insights into the current evidence collected and presented about
the topic outlining gaps and opportunities. Also, the literature analysis will reveal the need for
the study based on the existing gaps. The second step will be creating a plan for investigating the
topic focusing on setting the respective variables. On the same note, the research will examine
and determine the ethical standards that must be upheld during data collection and participants’
selection. This stage will define the consent form creation, sample collection and the
18
experimental analysis in the laboratory. The other stage will be performing further analysis using
the preferred statistical mechanism. Similarly, this step will allow the researcher to document the
findings where they will be discussed to facilitate effective reporting. Overall, during this
timeframe, the various activities surrounding the project will be completed.
Ethical Compliance
In this project, all methods were approved as a medium risk by the Coventry University Ethical
Approval process.
Contingency planning
One issue that may influence the successful completion of the project is the occurrence of
risks. Risks may arise in various areas, including the sample collection processes. One of the
core risks that may occur affecting successful project completion is the prevalence of COVID19. This risk has affected the normal operations executed within the normal learning processes.
The contingency plan against this risk is that the project will utilise a systematic review of the
past literature. This alternative will provide a viable option to promote awareness about the best
ways to respond to the presented topic. On the same note, the researcher will identify a
significant sample where sufficient blood samples will be taken to ensure project success. Such a
motivational intervention will encourage strategic data collection and the project`s success in
responding to the initial research aims.
19
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