JOURNAL CLUB - liver pancreas gall bladder

JOURNAL CLUB
2 SEPTEMBER 2024
Presenter : Dr. Sai Jyoti
Moderator: Dr. Nidhi Priya

HAEMATOLOGY
The Expression and Secretion Profile of
TRAP5 Isoforms in Gaucher Disease
Margarita M. Ivanova * , Julia Dao, Neala Loynab, Sohailla Noor, Neil Kasaci, Andrew Friedman
and Ozlem Goker-Alpan

• Cells VOLUME 13
• Published on : 20 April 2024
• Conducted in:
Lysosomal and Rare Disorders
Research and Treatment Center,
Fairfax, USA

Why I chose this article…?
• The article highlights the significance of tartrate-resistant acid phosphatase type 5
(TRAP5) isoforms in Gaucher disease.
• It improves understanding of disease’s effects on bone health and immune
activation, offering potential for better diagnostics and treatment strategies.

INTRODUCTION
• Gaucher disease (GD) is a genetic lysosomal storage disorder caused by mutations
in the glucocerebrosidase (GBA1) gene, leading to enzyme deficiency.
• Two main forms:
1. Non-neuronopathic- Type I or the chronic non neuronopathic form (M/C)
2. Neuronopathic- Type II or acute neuronopathic Gaucher disease
- is the infantile acute cerebral pattern
• A third pattern, type III, is intermediate between types I and II.

Pathogenesis of lysosomal
storage diseases.
In the example shown, a
complex substrate is normally
degraded by a series of
lysosomal enzymes (A, B, and
C) into soluble end products.
If there is a deficiency or
malfunction of one of the
enzymes (e.g., B), catabolism
is incomplete and insoluble
intermediates accumulate in
the lysosomes.
REVISION OF LYSOSOMAL STORAGE
DISEASES

1. Non-neuronopathic:
Enlarged spleen and liver
Anemia
Low platelet counts
Bone issues: pain, avascular necrosis, early-onset osteoporosis
2. Neuronopathic:
Severe neurological symptoms
Affects children particularly

Gaucher Disease
(GD) Mechanism:
Caused by
glucocerebrosidase
(GCase) enzyme
deficiency.
Leads to accumulation
of glucosylceramide
(Gb-1) and its
metabolite,
glucosylsphingosine
(Lyso-Gb-1).
Accumulation
interferes with cellular
pathways, including
autophagy-lysosomal
and mitochondrial
functions.

Gaucher Cells (GCs):
• Accumulation of Gb-1/Lyso-Gb-1 leads to formation of large,
foamy macrophages.
• These GCs are found in the liver, spleen, and bone marrow.
• GCs are involved in chronic immune activation, organ
enlargement & skeletal involvement.

Gaucher disease involving the bone marrow
Gaucher cells are plump macrophages that
characteristically have the appearance in the
cytoplasm of crumpled tissue paper due to
accumulation of glucocerebroside.
(A Wright stain B Hematoxylin and eosin)
• often enlarged (up to 100 μm in diameter)
• have one or more dark eccentrically placed
nuclei.
• PAS staining is usually intensely positive.

Gaucher cells with abundant lipid-laden granular cytoplasm.

Biomarkers in GD:
• Chitotriosidase (Chito) and CCL18: Secreted by
activated macrophages, used to monitor GD therapy and
disease activity.
• TRAP5 (Tartrate-Resistant Acid Phosphatase Type 5):
Initially a nonspecific marker of sphingolipid storage.

TRAP5 Isoforms:
TRAP5a: Monomer, expressed in
macrophages & dendritic cells, serves as a
marker for inflammatory macrophages.
TRAP5b: Heterodimer, expressed in
osteoclasts, regulates bone resorption & is a
key biomarker for bone pathology.

• Early ELISA tests were non-
specific and variable.
• New isoform-specific ELISAs
provide more accurate diagnostic
tools.
Diagnosti
c
Advances
:

Study Aim
Develop blood-based biomarkers to detect bone mineral
density (BMD) abnormalities in GD earlier than traditional
methods.
Analyze TRAP5a and TRAP5b in relation to immune
activation, bone resorption & BMD.
Correlate findings with established GD biomarkers (Lyso-Gb-
1, chito, CCL18) and assess age-related osteoporosis in GD.

MATERIALS AND METHODS
Subjects
• Under IRB-approved protocols, 39 participants (29 women, 10 men) were
recruited.
• Plasma was obtained from StemExpress (Folsom, CA, USA).
• Gaucher Disease (GD) diagnosis was confirmed through GCase activity and
GBA1 sequencing.

Treatment Status:
• 3 were treatment-naïve
• 22 were on enzyme replacement therapy (ERT)
• 13 were on substrate reduction therapy (SRT)
• 1 switched from SRT to ERT
Genotypes:
• 17 patients had homozygous p.N370S
• 12 had p.L444P
• 1 had L444P/L444P

The GD cohort, aged 18 to 68 years (mean 42 ± 15 years), was categorized by
bone mineral density (BMD) into:
• Normal BMD (NB; n = 11)
• Osteopenia (OSN; n = 14)
• Osteoporosis (OSR; n = 14)
Healthy controls had a mean age of 48 ± 11 years.

Blood Sample Collection
Venous blood was collected into EDTA K+ tubes,
then centrifuged at 800 × g for 5 minutes to separate
plasma.
The plasma was aliquoted into 1.5 mL tubes and spun at
2000 × g for 2 minutes to clear.
After centrifugation, plasma was further aliquoted and stored
at -80°C or -120°C.
The remaining blood was diluted with PBS/2% FBS &
peripheral blood mononuclear cells (PBMCs) were isolated
using SepMate™ tubes (Stemcells Technology) according to the
manufacturer’s protocol.

Freshly isolated PBMCs were resuspended in complete M2
macrophage generation media (RPMI 1640 with 10% FBS, 1%
Normocin, 2 mM glutamine, 1% Na-pyruvate, 1% Non-Essential Amino
Acids, and 50 ng/mL M-CSF).
After 6 days, M2
differentiation media
was added, and after
two more days, the
media was completely
replaced with fresh M2
differentiation media.
On day 10,
macrophages were
collected for analysis
or treated with
plasma for 48 hours.
All cultures were
maintained at 37°C
and 5% CO .
₂
Differentiation of M2 Macrophages from PBMCs

The THP-1 cell line, human monocytic cell line derived from an acute
monocytic leukemia patient and obtained from MilliporeSigma, was
maintained in RPMI-1640 medium supplemented with 10% FBS and 2 mM L-
glutamine.
• To induce differentiation into macrophages, cells were treated with 100
nM phorbol 12-myristate 13-acetate (PMA) for 72 hours.
• After the PMA stimulation -containing media was removed & THP- 1
machrophages were incubated in fresh RPMI-1640 supplemented with
10% FBS and 1% L-glutamine for an additional 24 hours.
Differentiation of Macrophages from THP-1

Following treatment, cells were washed with PBS, lysed in RNA
lysis buffer & stored at -80°C until analysis.
Macrophages from healthy controls, GD patients & THP-1 cells
were treated with various concentrations of Lyso-Gb-1 (HY-
N7745, MedChemExpress).
Cell Treatment

RNA was
extracted using
the Quick-RNA
Microprep Kit
(Zymo Research).
Real-time PCR
was performed
with the
LunaScript®
Multiplex One-
Step or Two-Step
RT-PCR Kit (New
England Biolabs).
mRNA levels of
ACP5, CCL2/MCP-1 &
GAPDH were
measured using the
StepOnePlus™ Real-
time PCR System
(ThermoFisher
Scientific) and was
normalized using
GAPDH
(Glyceraldehyde-3-
phosphate
dehydrogenase
reference gene).
Gene expression
was assessed in
triplicate and
analyzed using
the comparative
CT method
RNA Isolation and Quantitative Real-Time PCR (q-RT-PCR)

Plasma bone markers were measured using ELISA kits.
TRAP5b concentration was determined with a MicroVue™ TRAP5b
EIA kit (Quidel Corporation) and had a range of 0–16.5 U/L.
TRAP5a levels were assessed using TRAP5a kits (MyBioSource),
with an assay range of 2.5–50 ng/mL, and analytical sensitivity of 1.0
ng/mL.
CCL18 concentration was measured with a PARC/CCL18 Human
ELISA Kit (ThermoFisher Scientific) following the manufacturer’s
instructions.
Measurement of TRAP5 Isoforms and Macrophage Activation Biomarkers in
Plasma

Activity was reported as nmol/hr/mL.
Enzyme activity was measured with excitation at 450 nm and emission at 360 nm using the
Spectramax M2.
The reaction was incubated for 3 hours and stopped with Glycine-Sodium Hydroxide Buffer.
A chitotriosidase assay was conducted on dried blood spots (DBS) using 0.11 mM substrate
4-methylumbelliferyl-β-D-N,N′,N″-triacetyl-chitotrioside (4MU-C, Sigma,Millipore Sigma ) in a 0.1
M/0.2 M citrate-phosphate buffer.
Analysis of Chitotriosidase Enzymatic Activity in Dried Blood Spot Samples

STATISTICALANALYSIS
• Software: GraphPad Prism
• Two Groups: Student’s t-tests or F-tests
• Multiple Groups: One-way ANOVA followed by Kruskal–Wallis tests
• Significance Level: p < 0.05
• Correlation: Pearson or Spearman methods

RESULT
Assessment of TRAP5a and TRAP5b Plasma Levels in GD Cohorts
• TRAP5b: Elevated in GD patients, positively correlated with osteopenia,
osteoporosis & biomarkers (CCL18, Lyso-Gb-1, Chito)

TRAP5a: Elevated in 15 of 40 GD
patients; mean level was 13.1 ± 1.9
vs. 8.9 ± 0.8 in healthy controls,
with a difference of 4.5 ± 2.3
(Figure 1A).
Correlation: No significant
correlation between TRAP5a and
osteopenia/osteoporosis, unlike
TRAP5b (Figure 1B). NB- no bone complication OSN-osteopenia
OSR-Osteoporosis

• Naïve GD patients were excluded
from analysis due to small sample size
(Figure 1C).
• In Substrate reduction therapy (SRT)
Group: Significant increase in
TRAP5a levels in the “Normal
BMD” cohort compared to controls
(Figure 1C).

• TRAP5b Levels: In new GD
patients, TRAP5b levels were
remeasured and confirmed to
be elevated, correlating with
osteopenia osteoporosis
(Figure 1D,E).
• Therapy Impact: Neither
ERT nor SRT affected
TRAP5b levels (Figure 1E).

• TRAP5a and TRAP5b Correlation:
No linear correlation between
TRAP5a and TRAP5b was observed
(Figure 1G), indicating that TRAP
isoforms are regulated by distinct
factors, highlighting their unique roles
and regulatory mechanisms in GD
pathology.

Long-Term Monitoring of TRAP5a and TRAP5b in GD patients
• TRAP5a Levels: Most GD patients with normal BMD or osteopenia did not
show any significant changes in TRAP5a levels over 24 months, except for two
patients with normal BMD and two patients with osteopenia (Figure 2A,B)

• TRAP5b Levels: Normal BMD: Remained stable, with only 2 patients
showing slight elevations (Figure 2D,E).Among GD patients with osteopenia,
the TRAP5b level remained unchanged in 5 patients, increased in 1 patient,
and significantly decreased in another patient (Figure 2E).
Plasma level of TRAP5b within 24 months of monitoring. GD patients with
normal BMD (D), with osteopenia (E)

• Most GD patients with osteoporosis had
elevated TRAP5b levels, except for 2
patients who showed normal levels on
visit one but elevated levels 24 months
later (visit 5). Additionally, 1 patient
showed a normalization of the TRAP5b
level & the BMD test showed a
stabilization of the T-score over 24
months (Figure 2F)

Correlation Analysis between TRAP5a, TRAP5b & Other Inflammatory
Biomarkers in GD
• Chito (CHIT-1): Highly expressed in activated macrophages and Kupffer cells.
• CCL18: Produced by dendritic cells, monocytes, and macrophages.
• TRAP5b: Positively correlated with both Chito and CCL18 in the GD cohort.

• TRAP5a and Chito: Exhibited heterogeneity of variance, suggesting different
regulatory mechanisms of their expression in machrophages under chronic
inflammation.
• CCL18: associated with TRAP5b but not with TRAP5a
• A strong correlation was noted b/w TRAP5b and Lyso-Gb-1.

(A)Scatterplot of TRAP5a and Chito:
Spearman correlation analysis showed
significant correlation (p < 0.05).
(B)(B, C) Scatterplots of TRAP5a with
Lyso-Gb1: No significant correlation
observed.
(C)TRAP5a with CCL18 : No significant
correlation observed.
(D)(D–F) Correlation matrix and
hierarchical clustering- Significant
differences are marked in red (p <
0.05).

The Role of TRAP5b, TRAP5a, and the Bone Mineral Density Abnormalities in
GD
General Population:
• Bone Aging:
• Decreases BMD, leading to primary osteoporosis
• BMD Loss:
• Women ≥ 50: Start losing BMD, with rapid decline between 65–69 years.
• Men ≥ 60: Begin losing BMD, with rapid decline between 74–79 years

In GD Patients:
• Early Onset Osteoporosis: Significant BMD decrease occured early, even in
patients undergoing ERT or SRT.
• GD patients with osteoporosis (OSN and OSR) were generally younger than
those with osteoporosis in the general population
• No correlation b/w age and BMD was noted (Figures 3D–F and 4A,B).

(A,B) Scatterplot analysis of age and Z- or
T-score.
(C,D) Scatterplot analysis of age and
TRAP5b & TRAP5a showed no
correlation.
(E,F) TRAP5b and Z-score & TRAP5b
and T-score showed a medium
correlation.
(G,H) TRAP5a versus Z-score (G) and
T-score showed no correlation.

ACP5 mRNA Expression in Cultured GD Macrophages
• The expression of TRAP (gene abbreviation ACP5) mRNA in macrophages from
healthy control and GD patients was examined.
• MCP-1(monocyte chemoattractant protein-1) and Chit-1 mRNA levels were also
evaluated.
• M2 macrophages were differentiated from PBMCs of healthy controls and GD
patients (Table 1).
• M2 macrophages were obtained from 7 GD Patients.

Controls P1 P2 * P15 P17 P23 * P35 * P37 *
GBA
N370S/
N370S
L444P/
L444P
N370S/
N370S
N370S/
N370S
N370S/
N370S
N370S/
N370S
N370S/
Y412X
Bone pathology NB NB NB OSN OSN OSN OSR OSR
TRAP5b 1.47 ± 0.09 2.0 ± 0.3 2.7 ± 0.1 1.7 ± 0.8 4.9 ± 2.6 2.4 ± 0.2 9.2 ± 4 7.7 ± 2
TRAP5a 5.1 ± 1.1 7.3 ± 1.3 6.5 ± 1.6 5.7 ± 1.9 62.8 ± 16 5.0 ± 1.6 7.7 ± 1.8 10.1 ±
1.1
CCL2/MCP1 27.18 ± 4.9 74 ± 6.2 45.7 ± 6.4 141.5 19 ± 7.2 189 ± 28 27 ± 17 68 ± 16
GM-CSF 1.9 ± 0.3 2.0 ± 0.3 1.7 0.2 1.4 76.5 ± 5 1.8 10.3
TNF-alpha 12.2 ± 2.9 33.8 ± 6.4 28.1 25 ± 3.7 32 ± 5.7 31 ± 5.7 23 ± 17 18 ± 3.9
CCL18 71 ± 20 60.9 180 37.3 407.0 97.5 331 562.9
Lyso-Gb1 normal 2.7 15.9 1.0 49.0 5.1 39 85.6
Chito 95 ± 26 52 273 42.0 1194.0 164.0 97.8 546.0
Table 1. C/F of GD pts, including bone diseases, plasma levels of TRAP5b and TRAP5a, inflammatory
markers (monocyte chemoattractant protein 1 (MCP1), granulocyte macrophage colony-stimulating
factor (GM-CFS), tumor necrosis factor-alpha (TNF-alpha) & GD biomarkers (CCL18, Lyso-Gb-1,
Chito). NB—normal BMD, OSN—osteopenia, OSR—osteoporosis. Healthy control (n = 5). * Plasma
was used for the t/t of macrophages in vitro.

• ACP5 Levels: Significantly decreased in GD macrophages after 12 days of
differentiation, except for one cell line from a GD patient with osteoporosis (P7)
(Figure 5A).
• CCL2/MCP-1 mRNA: significantly reduced in GD macrophages (Figure 5B).
• GCase Deficiency: Likely suppresses ACP5 and CCL2/MCP-1 expression since
macrophages were cultured under the same conditions for both controls and GDs.

• Cytokine Expression: Decreased for CCL5/RANTES and CXCR4 in GD macrophages.
• Elevated serum levels of CCL5/RANTES are observed in GD patients with osteonecrosis.
• Chit-1 mRNA: Significantly elevated in GD macrophages compared to controls (Figure
5C).
• ACP5 Expression: GD plasma increased ACP5 mRNA expression in both control and GD
macrophages (Figure 5B, C).

• CCL2/MCP-1 and Chit1: Expression levels of CCL2/MCP-1 and Chit1
remained unchanged with plasma treatment (Figure 5D, E).
• Conclusion: The increase in ACP5 expression due to plasma t/t suggests that
external factors in the blood influence ACP5 regulation.

• Lyso-Gb-1 increased ACP5 expression in a concentration- and time-dependent
manner (Figure 5F).
Role of Lyso –Gb-1 levels in regulation of ACP 5 TRANSCRIPTION in
macrophages from GD Patients

• Increased ACP5 mRNA expression in a dose-dependent manner, similar to
results from GD patient-derived macrophages (Figure 5G).
• Lyso-Gb-1 also activated TRAP5 expression, consistent with previous reports .
Regulation ACP5 Expression and Lyso-Gb-1

DISCUSSION
• TRAP in GD is traditionally used as a clinical biomarker for Gaucher Disease, but its
role in GD pathology, especially regarding TRAP5a and TRAP5b, is not fully
understood.
• Historically, studies have measured total TRAP5 levels using antibody-based assays.
• Development of antibodies distinguishing TRAP5 isoforms reveals:
• TRAP5a: An inflammatory biomarker.
• TRAP5b: A bone biomarker secreted by osteoclasts

• The impact of Gb-1 and Lyso-Gb-1 on ACP5 gene expression and the differential
roles of TRAP5 isoforms in GD are areas of ongoing research.
• TRAP5a is highly expressed in alveolar macrophages, inflammatory
macrophages, and biomaterial-induced multinucleated giant cell and less
expressed in activated macrophages & dendritic cells.
• TRAP5a levels correlate with rheumatoid factors and disease severity due to
macrophage activation and inflammation.

• Upregulation of TRAP5a indicates pro-inflammatory activities in macrophages and
a higher proportion of glycolipid-enriched Gaucher cells.
• ACP5 mRNA expression in GD macrophages may be stimulated by Lyso-Gb-1 and
other factors in GD plasma, like elevated RANKL.
• Positive correlation with Chit-1, suggested involvement in pro-inflammatory
activities.
• No correlation with CCL18, indicated distinct roles in macrophage activation.

• Increased TRAP5a in GD does not correlate with TRAP5b or decreased BMD,
implying no direct link to osteoclast activity or accelerated bone resorption.
• TRAP5a is a monomer without enzymatic activity, highly expressed in alveolar
macrophages, and linked to nitric oxide (NO) production for bacterial infection
protection.
• It enhances migration in lung tissue; highly active in COPD and asthma patients,
reflecting disease activity in chronic inflammatory conditions, including RA .

• Transcription Factors like MITF (Microphthalmia Transcription Factor)NFATc1
(Nuclear Factor of Activated T-cells c1)RANKL (Receptor Activator of NF-κB
Ligand) bind to the proximal TRAP promoter to increase TRAP activity.
• RANKL indirectly promotes osteoclasts to break down the tissue in bones and,
after bone dissolution, release TRAP5b into the extracellular space .
• Thus, RANKL and components of the RANK pathway may be utilized as
markers to track the progression of bone disease in GD patients

• TRAP5b as a marker is highly sensitive and specific for detecting osteopenia
and osteoporosis.
• It is recently shown to be a predictive marker for osteoporosis in GD.
• Increased TRAP5b indicates higher bone resorption due to more osteoclasts.
• TRAP5b can be used as an indicator of bone loss, complementing other GD
biomarkers like Gb-1 and Lyso-Gb-1 for disease monitoring.

CONCLUSIONS
• TRAP5 isoforms could be targeted for adjunct therapies to address BMD
abnormalities in GD.
• TRAP5b: Positively correlates with GD-specific biomarkers (Lyso-Gb-1, CCL18,
Chito) & lower BMD Z-score, suggesting glucosylsphingosine accumulation's
role in osteoporosis development (underlying mechanisms involved in bone
pathology in GD).
• Relationship of TRAP5a and Chito indicates a shared origin of secretion, likely
from activated macrophages or Gaucher cells which may effectively assess
macrophage activation status & immune-driven inflammation in GD.

CYTOLOGY
Utility of guided FNAC and cell block
preparation from liver and gall bladder
masses: Learning experience from a tertiary
care center
Bohara, Sangita; Shukla, Prakriti; Shah, Saman1
; Chaturvedi, Rashmi; Singh, Kushal2

• Published on: 22 JAN 2024
• Journal of Cancer Research and
Therapeutics.
• Conducted in:
Hind Institute of Medical Sciences,
Barabanki, Uttar Pradesh, India

• Guided FNAC in conjunction with the cell block technique is extremely helpful in
the evaluation of mass lesions of the liver and gall bladder for cytological
diagnosis.

INTRODUCTION
• Guided FNAC allows access to most liver and gall bladder lesions.
• It improves diagnostic accuracy for lesions near complex structures and those that
are deep, small, or non-palpable.

• Recent advancements have increased FNAC's diagnostic sensitivity (67–100%)
and specificity (93–100%) for deep-seated lesions.
• Combining FNAC with cell blocks allows for multiple sections and the use of
ancillary techniques such as IHC, special stains and molecular testing.

METASTATIC COLONIC ADENOCARCINOMA

REVISION OF GALL BLADDER CYTOLOGY

The aim of this study was
to assess the effectiveness
of FNAC and cell blocks in
diagnosing liver and gall
bladder mass lesions.

• Study period - July 2020 to June 2022
• Relevant clinical details, radiology reports & tumor marker levels (if
available) were recorded for all patients before the procedure.
• CT and USG-guided FNACs were performed after obtaining informed consent.
• A brief discussion with the radiologist preceded the FNAC.

• Needles Used:
• 22-gauge needle with a 10 ml syringe for superficial masses.
• Spinal needle for deep masses.
• Technique:
• Needle inserted into the lesion, monitored on the screen.
• Material adequacy was checked in the needle hub.
• Needle was withdrawn, noting the lesion's consistency and the type of aspirate.

• 5 to 6 slides were prepared, including air-dried and wet-fixed smears (wet-fixed in
isopropyl alcohol).
• 2 slides were stained with Hematoxylin and Eosin (H&E).
• 1 slide was stained with Papanicolaou and 2 air-dried slides were stained with MGG.
• Wet-fixed slide was dipped in hematoxylin staining solution for 10 seconds.

• Slide was rinsed in tap water for rapid onsite assessment.
• It was examined under a microscope for blue-stained nuclei to confirm cytological
material adequacy.
• Tentative diagnosis was noted based on clinico-radiological and intra-procedural
findings.
• Differential diagnosis was provided in case of discrepancies.

• Remaining material was collected and preserved in 10% neutral buffered formalin
for cell block preparation.
• It was centrifuged at 1500 rpm for 5 minutes; supernatant was discarded.
• 4 drops each of pooled plasma and thrombin was added to 1 ml sediment and
mixed gently.
• A soft ball was formed and placed into a labeled cassette.
• It was processed as routine biopsies and stained with H and E.

• Cases were reported based on cellularity, cell composition, cytological atypia,
and clinico-radiological diagnosis.
Cell types were classified into:
• Atypical hepatocellular
• Atypical-glandular/squamoid/round/spindle
• Atypical-unclassified
• Atypia of undetermined significance.

• Cellular pattern, size, shape, nuclear features and cytoplasmic details were assessed.
• Additional findings like endothelial wrapping, blood vessels, hemorrhage, necrosis,
mucin and parasites were noted.
Histological grading (for malignancy) was based on nuclear atypia:
• Grade 1 (mild)
• Grade 2 (moderate)
• Grade 3 (severe).

A step-wise reporting questionnaire to reduce reporting time and enhance data reproducibility was used.

STATISTICALANALYSIS
• Statistical analysis was conducted using Microsoft Excel 2008.
• Results were expressed as numbers and percentages.

RESULT
80 image-guided FNACs from liver and gall bladder were
conducted over 2 years.
50 males and 30 females
Male-to-female ratio - 1.6:1
Mean age: 55.39 ± 13.36 years
Most common age group: 41–60 years

Liver masses were more
common (72 cases; 90%)
compared to GB masses (8
cases; 10%).
Rapid on-site evaluation
(ROSE) achieved adequate
cellularity in 62 of 65 cases
(95.38%).

Out of 72 liver masses:
57 cases (79.2%) were malignant.
6 cases (8.3%) were benign.
9 cases (12.5%) were inconclusive.
Among 57 malignant cases:
7 cases (12.2%) were atypical-hepatocellular.
43 cases (75.4%) were atypical glandular/squamoid/round/spindle cell types.
7 cases (12.2%) were atypical-unclassified.

Found 38 cases of adenocarcinomas.
11 cases (28.95%) were graded histologically:
Poorly differentiated: 7 cases (18.4%).
Moderately differentiated: 2 cases (5.3%).
Well differentiated: 2 cases (5.3%).

(a) Cytosmear
showing atypical
glandular clusters
with enlarged
round to columnar
shaped nuclei with
moderate to scant
cytoplasm (H E;
40×)
(b)Cell block of the
same case of
metastatic
adenocarcinoma
showing atypical
glandular nests
(H E; 40×)

Diagnostic cytomorphological features
included:
•Trabecular pattern.
•Polygonal cells with eosinophilic cytoplasm.
•Large vesicular nuclei with prominent
nucleoli.
•Transgressing vessels.
•Intranuclear inclusions.
•Absence of bile duct epithelium.
•Among 7 hepatocellular carcinoma
(HCC) cases:
•5 cases (71.4%) were well
differentiated.
•2 cases (28.6%) were poorly
differentiated.

(a) Cytosmear showing
paucicellularity with
scattered atypical
hepatocytes of round to
polygonal shape with
moderate to scant
cytoplasm and nuclear
atypia (H E, 40×)
(b) Cell block of the
same case of poorly
differentiated
hepatocellular
carcinoma showed
better cellularity and ill-
defined trabecular
architecture (H E; 40×)

Final categorization of
cases in liver and gall
bladder masses

All 8 gall bladder masses were categorized as atypical glandular:
•5 cases (62.5%) were moderately differentiated.
•3 cases (37.5%) were poorly differentiated.
•Cytomorphology of GB malignancy showed sheets and acini of atypical cells with
moderate-to-severe nuclear pleomorphism.
•1 MD adenocarcinoma had a mucin-rich background with intracellular mucin pushing
nuclei to the periphery.

Cell blocks prepared in 12 malignant cases:
• 9 from the liver
• 3 from the gall bladder
• 5 cases (41.67%) had diagnosis possible only on cell blocks due to better cellular yield.
• 2 cases (16.67%) had scant cellularity in cell blocks, making them non-contributory.
• 5 cases (41.67%) had cell blocks that were complementary and helpful in lesion
characterization.

• Clinico-radiological diagnosis was concordant with cytological diagnosis in 53 cases
(74.6%).
• A follow-up biopsy was available in only 7 cases (8.75%) and was done when
cytology was inconclusive.
• Of these, 6 cases (85.72) were consistent with the cytology findings.

The reporting questionnaire was helpful chiefly in terms of
• time-efficient reporting in 34 cases (42.5%)
• increasing the ease and confidence in 69 cases (86.25%)
• advantage of easy reproducibility of data in all cases (100%).

DISCUSSION
•Early diagnosis of liver and gall bladder carcinomas is crucial for therapy and
prognosis.
•Image-guided FNAC combined with cell blocking enhances diagnostic accuracy
for deep-seated lesions.

In this study
• 80 cases: 50 males, 30 females
• Male-to-female ratio of 1.6:1
• Mean age: 55 years
• Most cases - 5th and 6th decade.
• Similar to Talukder SI et al. and Nazir RT et al.

In this study
• Among the liver cases, the majority were adenocarcinomas (38 cases; 51.3%).
• Within these, 7 cases (8.8%) were graded as PD & 2 cases (3%) were graded as
WD. Additionally, 2 cases of small cell tumors was observed.
• These findings are consistent with those of Das DK et al., who studied 61
metastatic lesions and found adenocarcinomas to be the most common (70.49%),
followed by small cell anaplastic carcinomas (9.8%), and undifferentiated
carcinoma and soft tissue sarcomas (1.63% each).

In this study
• HCC was the 2nd most common diagnosis (10 cases; 13.5%), with half being
WD and the other half PD.
• This contrasts with Gatphoh ED et al., who reported a higher prevalence of HCC
compared to adenocarcinomas among liver masses.

In this study
• cell blocks were prepared for 12 cases (15%), with 9 from liver lesions and 3 from
gall bladder lesions.
• An overall improvement in diagnostic accuracy was observed when conventional
cytological smears were supplemented with cell block sections.
• Previous research supports that cell blocks enhance the effectiveness of
cytodiagnosis, particularly for malignant and suspicious cases.
In this study
• 5 cases were diagnosed exclusively from cell block sections.

• ROSE enhances diagnostic accuracy by ensuring adequate cellularity for analysis
and aiding in sample collection for various tests.
• However, it requires skilled cytopathologists and high-quality staining methods.
• Structured formats and synoptic reporting have improved diagnostic accuracy in
cytology, particularly for bile cytology and HCC.
• This indigenous reporting method streamlined the process, but further studies are
needed to evaluate its effectiveness.

LIMITATIONS
• Cell blocks were prepared for a limited number of cases.
• Structured questionnaire-based reporting format could not be compared to past
studies due to its indigenous nature.

CONCLUSION
• Guided FNAC in conjunction with the cell block technique is extremely helpful in
cytological diagnosis of liver and gall bladder mass lesions.
• ROSE is an important pre-requisite in CT and USG-guided FNAC and can be
done using hematoxylin staining to achieve adequate cellularity for reporting.

HISTOPATHOLOGY
ABCD1 as a Novel Diagnostic Marker for
Solid Pseudopapillary Neoplasm of the
Pancreas
Ying-ao Liu, BS, Yuanhao Liu, BS, Jiajuan Tu, PhD, Yihong Shi, BS, Junyi Pang, BS, Qi Huang, BS,
Xun Wang, BS, Zhixiang Lin, PhD, Yupei Zhao, MM, Wenze Wang, MD, Junya Peng, PhD, and
Wenming Wu, MD

• The American Journal of Surgical
Pathology: 5 MAY 2024 - Volume 48
Issue 5
• Conducted in:
• Department of General Surgery
and Pathology Peking Union
Medical College Hospital, Beijing,
China.

• Diagnosing solid pseudopapillary neoplasm (SPN) of the pancreas can be tricky
because it may be mistaken for pancreatic neuroendocrine tumors (NETs) with
current markers.
• ABCD1 shows promise as a highly effective and easy-to-use marker for
distinguishing SPN from NETs through IHC staining.

RECAP SOLID PSEUDOPAPILLARY NEOPLASM

INTRODUCTION
• Solid pseudopapillary neoplasm (SPN) is a rare, low-grade malignant pancreatic
tumor representing 1% to 3% of pancreatic tumors.
• Diagnosis mainly relies on distinct histomorphologic features and
immunohistochemical staining.
• SPN can be confused with pancreatic neuroendocrine tumors (NET),
pancreatoblastoma (PB) and acinar cell carcinoma (ACC) based on morphological
criteria alone.

• In over 90% of SPN cases, a point mutation in exon 3 of the CTNNB1 gene leads
to increased nuclear β-catenin accumulation.
• IHC staining typically shows nuclear positivity for β-catenin.
• However, similar β-catenin patterns can be seen in pancreatic neuroendocrine
tumors (NETs), pancreatoblastoma (PB) and acinar cell carcinoma (ACC),
complicating diagnosis.

• Variability in β-catenin expression, with some regions showing strong nuclear
staining and others not, can result in false negatives, particularly in biopsy
samples.
• Thus, a more specific and sensitive diagnostic marker is needed to enhance
accuracy in diagnosing SPN.

• The use of β-catenin as a diagnostic marker for SPN is based on the presence of
CTNNB1 mutations in over 90% of SPN cases.
• Gene expression datasets for SPNs are now readily available.
• To identify additional diagnostic markers, they analyzed mRNA expression
profiles from SPNs, adjacent normal tissues & NETs.
• The study aimed to find upregulated pathways and potential diagnostic markers
through IHC staining in a large patient cohort, including SPNs and other tumors
with similar features.

• The patient cohort for this study included a diverse range of pancreatic tumors
collected from Peking Union Medical College Hospital between 2011 and 2023.
• Clinical information of all patients – TABLE 1

TABLE
1
SPN NF-NET F-NEN
Acinar cell
carcinoma
Pancreato-
blastoma
PDAC IPMN PanIN MCA SCA
Total (n) 111 98 10 9 3 54 5 12 19 20
Sex
Female [n (%)]
89 （ 80.2
）
54 （ 55.1
）
8 （ 80 ） 4 （ 44.4 ） 1 （ 33.3 ）
20 （ 37.0
）
1 （ 20.0 ） 6 （ 50.0 ） 19 （ 100.0 ）
17 （ 85.0
）
Male [n (%)]
22 （ 19.8
）
44 （ 44.9
）
2 （ 20 ） 5 （ 55.6 ） 2 （ 66.7 ）
34 （ 63.0
）
4 （ 80.0 ） 6 （ 50.0 ） 0 （ 0.0 ）
3 （ 15.0
）
Median age 31 53 53.5 58 32 63.5 63 63.5 35 50.5
[years(range)] 12-62 18-77 23-58 38-66 29-41 42-87 57-83 48-74 24-67 29-70
Maximum tumor
volume(cm)
18x14x7 11x8x11 6x3x2.5 9.5x7.5x5 9x7.5x7.6 5x4.5x4 4.5x4x4 7x6.5x1.8 8.7x4.5x3.5
6.5x6.5x6.
5

• For the differential gene expression analysis, the researchers utilized the limma
package to identify differentially expressed genes (DEGs) between two groups.
• Limma (linear model for microarray data) , a linear model-based method,
enhanced analysis stability by incorporating shrinkage estimation and
borrowing information across genes.
• The analysis adhered to the default parameter settings specified in the limma
documentation.
Differential Gene Expression Analysis

Analysis Workflow:
1.Normalization: The raw read count data were normalized using a library size factor
and log transformation.
2.Statistical Analysis: The ImFit, eBayes, and top table functions within the limma
package were used to compute P-values for each gene.
3.Filtering: DEGs were filtered based on a false discovery rate (FDR) cutoff of 0.05.
• This approach enabled the researchers to effectively identify and validate
significant gene expression differences between the groups.

Gene Set Enrichment Analysis
• The researchers ranked all genes based on log2 fold change (log2FC) values,
which were derived from gene expression levels between different phenotypes:
SPNs VS normal, NETs VS normal & SPNs VS NETs.
• The ranked gene lists were then imported into the R package clusterProfiler
to perform gene set enrichment analysis (GSEA).

• This analysis specifically targeted the Gene Ontology (GO) biological
process gene sets, focusing on GOBP_PEROXISOME_ORGANIZATION from
the Molecular Signatures Database (MsigDB).
• The results of the analysis were visualized using the R package Enrichplot.

STAINING
Antibodies and Reagents
• Anti-catalase rabbit monoclonal antibody, Cell Signaling Technology, 12980S,
using concentration of 1:200 for immunofluorescence staining.
• BOND Ready-To-Use Primary Antibody Beta- Catenin (17C2), Leica, PA0083,
using original reagents directly for IHC staining.
• Anti-ABCD1 rabbit monoclonal antibody, Abcam, ab197013, using
concentration of 1:100 for IHC staining.

• Goat anti-mouse IgG H&L (Alexa Fluor 488), Abcam, ab150113, using
concentration of 1:500 for immunofluorescence staining.
• Goat anti-rabbit IgG H&L (HRP), Abcam, ab6721, using concentration of
1:200 for IHC staining.
• OptiView Amplification Kit, Roche, 860-099, using original reagents
directly for IHC staining.

Immunohistochemistry Staining
• IHC assays were conducted using a fully automated immunohistochemistry
stainer (Roche Ventana and Leica Bond III), with corresponding reagents,
following the manufacturer’s instructions.
• Tissue samples were fixed in 10% neutral formalin, paraffin-embedded, cut
into 4-μm thick consecutive sections & dewaxed as per standard procedures.
• Primary antibodies were appropriately diluted with a TBS diluent &
dispensed into user-fillable containers.

Immunofluorescence Staining
• Fresh tissue samples were fixed in 4% paraformaldehyde, embedded in
Optimal Cutting Temperature & sectioned into 4-μm thick frozen slices.
• The sections were incubated with 10% fetal bovine serum and 0.2% Triton X-
100 for 30 minutes to block nonspecific binding and permeabilize cells.

• Primary antibodies were applied for 2 hours, followed by 1 hour incubation
with fluorescently labeled secondary antibodies at room temperature.
• 4’,6-Diamidino-2-phenylindole (DAPI) was used for nuclear staining.
• Sections were washed 3 times with PBS, kept moist, and protected from light
during secondary antibody incubation.

Western Blotting
• Frozen SPN and normal pancreas tissues were homogenized in RIPA buffer
with 1% proteinase inhibitor.
• The lysates were incubated on ice for 1 hour, centrifuged at 14,000 rpm for 10
minutes & the supernatant was collected.
• Protein concentrations were measured using a BCA Protein Assay Kit.
• Protein samples were diluted with 5x loading buffer, separated by 10% SDS-
PAGE (Sodium dodecyl-sulfate polyacrylamide gel electrophoresis) &
transferred to nitrocellulose membranes.

• Membranes were blocked with 5% skim milk for 1 hour, incubated with primary
antibodies overnight at 4°C and then washed with Tris-Buffered Saline with
Tween.
• Secondary antibodies were applied for 1 hour at room temperature.
• Immunoblotting images were acquired with a Tanon visualizer and β-actin
was used as a loading control.

Histoscore Analysis
• Two pathologists independently evaluated all staining results using Histoscore
(Hs) & they were blinded to the clinical data.
• The Histoscore was a semiquantitative assessment comprising 2 components: the
intensity (I) of staining, which ranged from 0 (no staining) to 3 (strong), and the
percentage (P) of cytoplasmic staining.
• Hs = (1 × [% weak staining]) + (2 × [% moderate staining]) + (3 × [% strong
staining])

Quantification of Immunohistochemical Staining
of ABCD1 Expression
• IHC sections were scanned with a NanoZoomer S360.
• Five random regions from each image were analyzed using FIJI software to
assess staining intensity.
• Images were segmented into hematoxylin and DAB components, converted to 8-
bit format & analyzed for staining intensity and cell area.
• The ratio of these values was used to determine average intensity.

STATISTICALANALYSIS
• Statistical analysis - GraphPad Prism (Version 8.0).
• Continuous variables - 2-tailed Student's t test.
• Categorical variables - Fisher's exact test.
• Significance was set at P < 0.05.
• ROC analysis - MedCalc software.

Figure 1A outlines the study's
experimental design,
analyzing gene expression
data from 13 SPNs, 6 NETs &
5 normal pancreases.
Peroxisomes Are Enriched in SPNs

Figure 1B Gene Set Enrichment
Analysis (GSEA) plots for SPN and
normal pancreas
• The green line shows enrichment,
and the colored band indicates
gene correlation with
peroxisomal organization (red:
positive, blue: negative).
• GSEA showed higher expression
of peroxisome-related genes in
SPNs compared to normal
tissues.

Figure C
Immunofluorescence images of
Catalase (peroxisome marker) in
normal & SPN tissues. Catalase, an
enzyme in peroxisomes that converts
hydrogen peroxide into water and
oxygen, was used to quantify
peroxisomes.
Figure D
Immunofluorescence staining revealed
a higher number of Catalase-positive
dots in SPN tissues compared to

Figure E
Transmission electron
microscopy images showing
peroxisome morphology in
normal and SPN cells
Figure F
Elevated peroxisome levels
was noted in SPN cells.

ABCD1 Exhibits Elevated Expression in SPN
• Analysis of differentially expressed genes (DEGs) revealed 1895 upregulated
genes in SPNs compared to normal tissues (P≤0.05, Log2FC≥1).
• Among peroxisome genes, ABCD1 showed the highest expression in SPNs.
• Immunoblotting confirmed ABCD1 upregulation in SPN tissues supporting
transcriptome data.
• IHC of ABCD1 in 72 primary SPNs, 16 metastatic SPNs, and 72 normal
pancreas samples revealed strong or moderate positive staining in SPN
tissues, while normal tissues were negative or weakly positive .

Figure A and B
Volcano plots show
differentially expressed
genes (DEGs) b/w
(A)SPN tumor tissues &
normal pancreas
(B) SPN and NETs
Red dots represent
peroxisome organization
genes.

Figure C
Immunoblotting analysis of ABCD1 protein expression in SPN & normal
pancreas.

Figure D
Representative H&E and IHC staining for ABCD1 in SPN tumor and
adjacent normal tissues.

Figure E
ABCD1 IHC images with
varying histoscores (− to ++
+) in SPN and normal
pancreas.

Figure F
Histoscore distribution for
ABCD1 in 72 normal pancreas,
72 primary SPNs, and 16
metastatic SPNs.

Figure G
Fisher exact test results for histoscores, comparing different groups: P(−) for “−”
vs. others; P(−/+) for “−” and “+” vs. others; P(−/+/++) for “+++” vs. others.

ABCD1 Specifically Identifies SPN From
Morphologically Similar Pancreatic Neoplasms
by IHC
• Uniformly homogeneous round to oval cells complicated the differentiation of
SPN from NET, ACC & PB based on morphology alone.
• The study involved 111 SPN, 108 NET (98 nonfunctional, 10 functional), 9
ACC and 3 PB samples.
• The staining results were analyzed using the Hs scoring method.

Figure 3A: Representative IHC images with ABCD1 scores for NET, acinar cell
carcinoma & pancreatoblastoma (“−”, “+”, “++”).

• Over 95% of SPN samples showed strong positive staining (+++), whereas
similar staining was not observed in other pancreatic tumors, which were mostly
negative or weakly positive (Figs. 3B, C).
• ABCD1 expression was notably higher in SPNs than in NET, ACC, and PB
samples, suggesting its potential as a distinguishing marker for SPN.

Figure 3B: Percentage of ABCD1 histoscores in 111 SPN, 108 NET, 9 acinar cell carcinoma, and 3
pancreatoblastoma tissues.
Figure 3C: Fisher exact test results for histoscores

Also Distinguishes SPN From Other
Pancreatic Tumors by IHC
To investigate if ABCD1 could distinguish SPN from other pancreatic tumors, IHC
staining was conducted on
• 54 cases of pancreatic ductal adenocarcinoma (PDAC)
• 5 intraductal papillary mucinous neoplasms (IPMN)
• 12 pancreatic ductal intraepithelial neoplasias (PanIN)
• 19 pancreatic mucinous cystadenomas (MCA)
• 20 pancreatic serous cystadenomas (SCA)
The Hs scoring method was used for analysis.

• Results showed that 95.5% of SPN samples exhibited strong positive staining
for ABCD1 (+++).
• In contrast, nearly all other pancreatic tumors displayed either negative (−) or
weak positive (+) staining, except for PDAC.
• Of the 54 PDAC cases, only 3 showed moderate positive expression (++), while
the rest were either negative (−) or weakly positive (+)

Performs Well as a Positive Marker for
SPN Diagnosis
• To evaluate the diagnostic potential of ABCD1 as a marker for SPN, ROC curve
analysis was performed to determine sensitivity and specificity.

Figure 5A shows the ROC curve for ABCD1 histoscore distinguishing SPN from NET
Figure 5B displays the ROC curve for ABCD1 histoscore in differentiating SPN from all
pancreatic tumors listed (NET, ACC, PB, PDAC, SCA, MCA, IPMN, and PanIN).

• These findings underscore the potential of ABCD1 as a valuable diagnostic
marker for distinguishing SPN.

DISCUSSION
• The study compared SPNs, NETs and normal pancreatic tissues, identifying
significant upregulation of the peroxisome organization pathway in SPNs.
• Validation with catalase immunofluorescence and transmission electron
microscopy, along with IHC staining of various tumor types, showed high
ABCD1 expression in SPNs, confirming its effectiveness as a diagnostic
marker.

• While nuclear β-catenin is commonly used for SPN diagnosis, other markers like
CD10, cyclin D1 and vimentin have varied sensitivity & specificity and some
SPN cases may be negative for these markers.
• β-catenin alone also has limitations due to variable staining intensity and
overlap with other tumors, underscoring the need for new, specific markers.
• The study found increased ABCD1 expression in both primary and metastatic
SPN sites compared to normal pancreas.
• In contrast, NET, ACC, PB and most other pancreatic tumors showed negative or
weakly positive ABCD1 staining.

• High ABCD1 staining intensity was strongly indicative of SPN, particularly in
cases with partially nuclear-negative or unclear β-catenin expression.
• IHC staining of 16 metastatic SPN samples consistently revealed strong positive
results, suggesting ABCD1's utility in identifying SPN metastasis.
• Multicenter validation is needed to confirm its clinical feasibility.

• To assess ABCD1 as a supplementary marker for SPN alongside β-catenin, the study
examined ABCD1 expression in tumor cells with negative nuclear β-catenin.
• Although none of the 111 SPN cases were completely negative for nuclear β-
catenin, some had areas with negative or obscure staining where ABCD1 was
consistently positive.
• This suggests that ABCD1 could complement β-catenin, especially in biopsies
where β-catenin staining may be variable.

• Additionally, negative ABCD1 staining in some β-catenin-positive NET samples
highlights its potential to distinguish SPN from similar pancreatic tumors and
reduce false positives.
• Future research should explore the combined use of ABCD1 and β-catenin in SPN
diagnosis.

• In the cohort, 95.5% of SPN cases showed strong positive ABCD1 staining (+++),
with none exhibiting negative staining.
• Although some similar tumors also expressed ABCD1, they lacked the strong
positive pattern seen in SPN.
• This distinct staining profile makes ABCD1 suitable for future automated
quantification.

CONCLUSION
• The study underscores ABCD1's specific enrichment in SPN compared to other
pancreatic tumors, demonstrating its potential as a precise and reliable diagnostic
marker for SPN.

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