Immunohistochemical Algorithms and Gene Expression Profiling in Primary Cutaneous B-cell Lymphoma

doi:10.21203/rs.3.rs-72812/v1

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Research article

Immunohistochemical Algorithms and Gene Expression Profiling in Primary Cutaneous B-cell Lymphoma

https://doi.org/10.21203/rs.3.rs-72812/v1

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posted 18 Sep, 2020

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Objective: to assess whether immunohistochemical (IHC) algorithms used to classify the cell of origin (COO) of nodal Diffuse Large B-cell lymphoma (nDLBCL) in Germinal Center type (GCB) and non-GCB subtypes may be applied to Primary Cutaneous B-cell lymphoma (PCBCL) too, and which of these algorithms performs better on PCBCL.

Design: retrospective case control study.

Setting: Pathology Department of the University Hospital “San Giovanni di Dio e Ruggi d’Aragona” Salerno, Italy.

Participants : fourteen PCBCL, including Primary Cutaneous follicle centre lymphoma (PCFCL) and primary cutaneous diffuse large B-cell lymphoma, Leg type (PCDLBCL-LT) and 14 nDLBCL were evaluated for 7-year period (January 2011 to December 2017). Primary cutaneous marginal zone cell lymphoma (PCMZL) cases were not included in the present study.

Intervention: evaluation of immunohistochemical CD10, BCL6, MUM1/IRF4, BCL2, MYC and Ki-67 expression and classification according to three different algorithms. Gene expression profiling (GEP) was performed on the same series using Lymph2Cx assay (Nanostring). The data obtained were compared and analysed.

Results: all the IHC algorithms showed 13 GCB and 15 non-GCB. GEP showed 12 GCB, 12 activated B cell–type and 4 unclassified.

Conclusions: the PCBCL were classifiable as GCB and non-GCB like the nDLBCL as IHC algorithms were concordant to GEP and produced the same results.

Cancer Biology

Oncology

Primary cutaneous B-cell lymphoma

nodal diffuse large B-cell lymphoma

Cell of Origin

Gene expression profiling

What is already known on this topic:

Primary cutaneous lymphomas (PCBCL) are classified in PCMZL, PCFCL and PCDLBCL-LT. A sub-classification of these entities, like that of nDLBCL, based on the identification of Cell-of -Origin (COO) would be useful for diagnostic and prognostic purposes but no consistent data are available.

What this study adds:

Data obtained in our series support the reliability of both GEP and IHC algorithms in the prognostic and predictive evaluation of PCBCL with accuracy comparable to that reported for nDLCBL

Primary cutaneous B-cell lymphoma (PCBCL) is a heterogeneous group of lymphoproliferative disorders, which accounts for 20–25% of all primary cutaneous lymphomas [1]. The World Health Organization (WHO) and the European Organization for Research and Treatment of Cancer (EORTC) classify PCBCL in three main histotypes: 1) primary cutaneous marginal zone B-cell lymphoma (PCMZL); 2) primary cutaneous follicle centre cell lymphoma (PCFCL); 3) primary cutaneous diffuse, large, B-cell lymphoma, leg type (PCDLBCL-LT) [1–3]. Whereas the PCMZL and PCFCL are indolent diseases (with disease-related 10-year survival greater than 90%), diffuse PCFCL and PCDLBCL-LT show an aggressive behaviour with a disease-related 5-year survival of approximately 50%. Despite the difficulties, it is useful to discriminate diffuse PCFCL from PCDLBCL-LT because the latter has a significantly shorter survival, lower response to therapy and requires multiagent chemotherapy and anti-CD20 monoclonal antibodies [4]. Considering nodal diffuse large B-cell lymphoma (nDLBCL) as their possible counterpart, they have been exhaustively investigated by gene expression profiling (GEP) and by immunohistochemistry (IHC) applying different antibodies and algorithms [5–7]. The classification of PCBCL in GCB and non-GCB might have relevant prognostic and predictive implications [8, 9]. Nonetheless, the reproducibility of GEP and IHC classification of PCBCL has not been definitively assessed [4, 8–10]. Moreover, the available studies on this subject have led to conflicting results [5]. In these studies, the discrimination between PCDLBCL-LT and other PCBCL, particularly PCFCL with diffuse growth pattern and predominance of centroblasts is often investigated [5]. For this purpose, the application of immunohistochemistry (IHC) algorithms used to subclassify nDLBCL in GCB and non-GCB might be useful but has not been validated on PCBCL. For instance, the expression of B-Cell lymphoma-2 (BCL2) antigen and multiple myeloma-1/Interferon regulatory factor-4 (MUM1/IRF4) are common in PCDLBCL-LT, but BCL2 is weakly or not expressed in PCFCL [11], even if about 10–20% of PCFCL are BCL2 positive [12]. In fact, as in the case of cutaneous pseudolymphoma, BCL2 overexpression seems to be associated with chromosomal amplification of BCL2 rather than with the t(14,18)(q32,q21) translocation, which determines BCL2-IGH rearrangement and is common in nDLBCL GCB [12].

The aim of the present study is to assess whether the IHC algorithms utilized to classify the cell of origin (COO) of the nDLBCL may be also applied on PCBCL, and which of these algorithms performs better on PCBCL. For this purpose, a series of diffuse PCFCL and PCDLBCL-LT has been investigated by IHC and their phenotypes have been compared to an additional series of corresponding nDLBCL. The data obtained have been classified using different algorithms and validated by GEP, which is the gold standard for this classification.

Study group

Fourteen PCBCL, including PCFCL and PCDLBCL-LT, collected over a 7-year period (January 2011 to December 2017) at the Pathology Department of the University of Salerno (Italy), were retrieved and evaluated together with 14 nDLBCL used as controls. PCMZL cases were not included in the present study.

Patients

Cutaneous and lymph nodal biopsies were available for all the samples. All the corresponding patients had received a diagnosis of PCBCL on longstanding single or multiple cutaneous lesions from different sites (Tab. 1).

Table 1

Clinical, histologic, phenotypic and gene expression profiling of 14 PCBCL.
Patients	1c	2c		3c	4c		5c	6c	7c
Sex	M	M		M	F		F	M	M
Age	65	54		76	54		56	80	49
Site	Trunk	Eyelid		Arm	Leg		Leg	Arm	Trunk
Size, mm	44	18		23	15		25	10	12
Relapse	Yes (LN cervical)	Yes (Local)		Yes (Local)	Yes (Local)		No	No	No
Diagnosis	PCDLBCL-LT	PCFCL		PCFCL	PCDLBCL-LT		PCDLBCL-LT	PCFCL	PCFCL
Reactive T-cells	Yes	Yes		Yes	Yes		No	No	Yes
Growth pattern	Diffuse	Follicular		Diffuse	Diffuse		Diffuse	Follicular	Follicular
Dendritic meshwork	No	Yes		Yes	No		No	No	No
Skin ulceration	No	No		No	No		Yes	No	No
Necrosis	No	No		Yes	Yes		Yes	Yes	No
Nuclear debris	No	No		Yes	Yes		Yes	Yes	No
“Starry sky” pattern	No	No		No	No		No	No	No
Ki67 positivity (%)	80%	20%		80%	60%		90%	60%	60%
CD2	-	-		-	-		-	-	-
CD4	-	-		-	-		-	-	-
CD5	-	-		-	-		-	-	-
CD8	-	-		-	-		-	-	-
CD3	+	+		+	+		-	-	+
CD20	+	+		+	+		+	+	+
CD79A	+	+		+	+		+	+	+
PAX5	-	-		-	-		-	-	-
Alk	-	-		-	-		-	-	-
CyclinD1	-	-		-	-		-	-	-
Cytokeratin	-	-		-	-		-	-	-
MYC	-	-		-	-		-	-	-
CD30	-	-		-	-		-	-	-
CD68	-	-		-	-		-	-	-
CD138	-	-		-	-		-	-	-
Bcl2	+	+		-	+		+	+	+
Bcl6	+	+		+	-		-	+	+
CD10	-	+		+	-		-	+	+
Mum1/IRF4	+	-		-	+		+	-	-
Hans’ algorithm	Non-GCB	GCB		GCB	Non-GCB		Non-GCB	GCB	GCB
Colomo’s algorithm	Non-GCB	GCB		GCB	Non-GCB		Non-GCB	GCB	GCB
Muris’ algorithm	Non-GCB	GCB		GCB	Non-GCB		Non-GCB	GCB	GCB
t(14;18)-PCR	No	No		No	No		No	No	No
GEP	ABC	GCB		GCB	Unclassified		ABC	GCB	GCB

Patients	8c		9c	10c		11c	12c	13c	14c
Sex	F		M	F		M	F	F	F
Age	80		76	45		58	73	40	67
Site	Arm		Leg	Head		Trunk	Trunk	Trunk	Arm
Size, mm	30		23	14		28	16	9	21
Relapse	Yes (local)		No	No		Yes (local)	No	No	No
Diagnosis	PCFCL		PCDLBCL-LT	PCFCL		PCFCL	PCFCL	PCFCL	PCFCL
Reactive T-cells	No		No	Yes		No	No	Yes	No
Growth pattern	Diffuse		Diffuse	Mixed		Diffuse	Mixed	Follicular	Mixed
Dendritic meshwork	No		No	Yes		Yes	No	No	No
Skin ulceration	No		No	No		No	No	No	No
Necrosis	Yes		No	No		Yes	No	No	No
Nuclear debris	Yes		No	No		Yes	No	No	No
“Starry sky” pattern	No		No	No		No	No	No	No
Ki67 positivity (%)	87%		75%	30%		78%	82%	65%	80%
CD2	-	-		-	-		-	-	-
CD4	-	-		-	-		-	-	-
CD5	-	-		-	-		-	-	-
CD8	-	-		-	-		-	-	-
CD3	-	-		+	-		-	+	-
CD20	+		+	+		+	+	+	+
CD79A	+		+	+		+	+	+	+
PAX5	-	-		-	-		-	-	-
Alk	-	-		-	-		-	-	-
CyclinD1	-	-		-	-		-	-	-
Cytokeratin	-	-		-	-		-	-	-
MYC	-		-	-		-	-	-	-
CD30	-	-		-	-		-	-	-
CD68	-	-		-	-		-	-	-
CD138	-	-		-	-		-	-	-
Bcl2	+		+	-		+	+	-	-
Bcl6	-		-	+		+	+	+	+
CD10	-		-	+		-	-	+	+
Mum1/IRF4	+		+	-		+	+	-	-
Hans’ algorithm	Non-GCB		Non-GCB	GCB		Non-GCB	Non-GCB	GCB	GCB
Colomo’s algorithm	Non-GCB		Non-GCB	GCB		Non-GCB	Non-GCB	GCB	GCB
Muris’ algorithm	Non-GCB		Non-GCB	GCB		Non-GCB	Non-GCB	GCB	GCB
t(14;18)-PCR	No		No	No		No	No	No	No
GEP	ABC		ABC	GCB		ABC	ABC	GCB	GCB
LN: lymph node; PCBCL: primary cutaneous large, B-cell lymphoma; PCFCL: primary cutaneous follicle centre lymphoma; PCDLBCL-LT: primary cutaneous diffuse, large, B-cell lymphoma, leg type; ABC: Activated-B-Cell; GCB: Germinal Center-B-Cell; IHC: immunohistochemistry; GEP: Gene Expression Profiling.

The pathological history in all the patients was negative for previous lymphoma.

After the histological diagnosis clinical staging was assessed in each of them by flow cytometry of peripheral blood, immunoglobulin gene rearrangements in lesional skin or in peripheral blood, complete and differential blood cell count, routine serum biochemistry analysis with lactate dehydrogenase (LDH), serum protein electrophoresis, liver function tests, computed tomography-fluorodeoxyglucose-positron emission tomography (CT-FDG-PET) scan and bone marrow biopsy. The staging and therapy were assessed according to the European Society for Medical Oncology (ESMO) recommendations for primary cutaneous lymphoma [13]. All the patients, after specific therapies, underwent strict clinical follow-up.

Immunohistochemistry

Immunohistochemistry (IHC) was performed on 4-µm serial sections of formalin-fixed, paraffin-embedded (FFPE) tissue from each sample using CD20, CD79A, PAX5, CD10, BCL6, MUM1/IRF4, BCL2, CD3, CD68, CD5, CD2, CD4, CD8, CD138, CD30, ALK, CyclinD1, MYC, Cytokeratin and Ki-67.

The sections were stained using the BenchMark XT autostainer (Ventana Medical Systems Inc, Tucson, Arizona) with standard protocols [14-16]. The following pre-diluted monoclonal antibodies were used in all cases: CD20 (1:100; clone L26; cat. N. 760-2531; Ventana); CD79a (1:100; clone SP18; cat. N. 790-4432; Ventana); PAX5 (1:100; clone SP34; cat. N. 790-4420; Ventana); CD10 (1:25; clone SP67; cat. N. 790-4506, Ventana), BCL6 (1:200; clone GI191/A8; cat. N. 760-4241, Cell Marque Corporation – Sigma Aldrich, Rocklin, California); Mum1/IRF4 (1:100; clone MRQ-43; cat. N. 760-4529; Cell Marque Corporation); BCL2 (1:100; clone 124; cat. N. 790-4464; Ventana); CD3 (1:100; clone 2GV6; cat. N. 790-4341; Ventana); CD68 (1:100; clone KP-1; cat. N. 790-2931; Ventana); CD5 (1:100; clone SP19; cat. N. 790-4451; Ventana); CD2 (1:100; clone MRQ-11; cat. N. 760-4377; Ventana); CD4 (1:100; clone SP35; cat. N. 790-4423; Ventana); CD8 (1:100; clone SP57; cat. N. 790-4460; Ventana); CD138 (1:100; clone B-A38; cat. N. 760-4248; Ventana); CD30 (1:100; clone Ber-H2; cat. N. 790-2926; Ventana); ALK (1:100; clone D5F3; cat. N. 790-4794; Ventana); CyclinD1 (1:100; clone SP4-R; cat. N. 790-4508; Ventana); MYC (1:100; clone Y69; cat. N. 790-4628; Ventana); Cytokeratin (1:100; clone AE1/AE3/PCK26; cat. N. 760-2595; Ventana) and Ki-67 (1:100; clone 30-9; cat. N. 790-4286; Ventana). The slides were then washed and incubated with multimer-labeled anti-mouse or rabbit IgG (cat. N. 760-2680, Ventana). Staining was then performed using the iVIEW 3,3’-diaminobenzidine detection kit (Ventana) according to the manufacturer’s instructions. Samples were then counterstained with Hematoxylin. Placenta and lymphoma sections, utilized as negative and positive controls, were run simultaneously.

IHC results were independently blindly interpreted by two pathologists (I.C. and P.Z.) to assess intrapersonal and interpersonal reproducibility.

IHC evaluation was performed through the nuclear (PAX5, BCL6, MUM1/IRF4, MYC, CyclinD1) and cytoplasmic membrane (CD10, BCL2, CD5, CD20, CD79a, CD3, CD4, CD8, CD2, CD30, ALK, Cytokeratin) positivity. For this purpose, 10 high-power fields were evaluated for each case and the proportion of cells with positive signals, rather than signal intensity, was quantified and assessed as positive or negative [1,2]. CD20, CD79a, PAX5, CD10, BCL6, MUM1/IRF4, CD3, CD68, CD5, CD2, CD4, CD8, CD138, CD30, ALK, CyclinD1 and Cytokeratin staining were considered positive when 30% or more of the cells showed antigen expression [1,2,17-19]. BCL2 staining was considered positive when expressed in over 50% of tumor cells [1,2,17-19]. MYC staining was considered positive when expressed in over 40% of tumor cells [1,2,17-19] A Ki-67 rate >50% of nuclei was considered a ‘‘high proliferation’’ rate [1,2]. Small or indeterminate cells were not considered in cell counting.

Immunoreactivity was evaluated without any knowledge of the patient’s survival or other clinical data. IHC results were merged with the histological features of PCBCL and nDLBCL.

Immunohistochemical classification

Hans’, Colomo’s and Muris’ algorithms, used for nDLBCL groups (GCB and non-GCB), were applied in order to assign the cell of origin (COO) to PCBCL [12,15-17]. In particular, PCBCL and nDLBCL were considered GCB when expressing CD10-/BCL6+/MUM1- or CD10+/BCL6±/MUM1- profiles by using the Hans’ algorithm [17], or MUM1-/CD10±/BCL6+ or MUM1-/CD10+/BCL6± profiles with the Colomo’s algorithm [18] or BCL2+/CD10±/MUM1- or BCL2-/CD10±/MUM1- with Muris’ algorithm [19]. PCBCL and nDLBCL were considered non-GCB when expressing the CD10-/BCL6±/MUM1+ profiles at Hans’ algorithm, or MUM1+/CD10-/BCL6± profiles at Colomo’s algorithm or BCL2+/CD10±/MUM1+ profiles at Muris’ algorithm.

Gene Expression Profiling

To assign the PCBCL to the GCB or activated B cell (ABC) groups, samples were analyzed with the Lymphoma/Leukemia Molecular Profiling Lymph2Cx assay, a digital gene expression (NanoString)–based test for COO assignment in FFPE tissue (FFPET).

Ten-micrometer scrolls of FFPET were cut with a surface area of ≥8 mm² of each case tested by GEP. RNA was extracted using the Qiagen RNeasy FFPET kit (cat. N. 73504, Qiagen, Inc., Valencia, CA, USA), following the manufacturer’s instruction, after treatment with Qiagen Deparaffinization Solution (cat. N. 19093, Qiagen) and digital GEP was performed on 200 ng RNA using NanoString technology (Seattle, WA) with 23-Gene Signature for COO Classification Lymph2Cx (Nanostring Technologies, Seattle, WA, USA). GEP was performed on Affymetrix U133 plus 2.0 microarrays at Polo Tecnologico Pharmadiagen Srl
Laboratory (Pordenone, Italy). The data algorithm nCounter-based Lymph2Cx Assay Misclassification Rate was 2%. GEP analysed cases were blindly classified according to the COO assignment [6,7].

Gene expression profiling analysis

The 14 PCBCL and 14 nDLBCL samples were analysed using the RUO version of the GEP NanoString Lymphoma Subtyping Test (LST) algorithm to determine the COO molecular subtype of each sample. The LST algorithm measures the geometric mean of 5 housekeeping genes (HK geomean) to ensure RNA quality based on a pre-defined clinical quality control (QC) threshold of 128. An HK geomean value below 64 is deemed to be insufficient in terms of RNA quality to provide a subtyping result (subtype listed as N/A). A value between 64 and 128 is borderline quality since it meets previously published thresholds for RNA quality within clinical research studies [5,6], but does not meet the clinical QC threshold of 128 for individual patients. Samples that met the QC threshold were marked as “pass” (tab. 3).

Table 3

Sample stratification by IHC algorithms and GEP
Samples (N.)	IHC Analysis				GEP
Samples (N.)	IHC Profiles	Hans	Colomo	Muris	GEP
1c	BCL2+/CD10-/BCL6+/MUM1+	non-GCB	non-GCB	non-GCB	ABC
2c	BCL2+/CD10+/BCL6+/MUM1-	GCB	GCB	GCB	GCB
3c	BCL2-/CD10+/BCL6+/MUM1-	GCB	GCB	GCB	GCB
4c	BCL2+/CD10-/BCL6-/MUM1+	non-GCB	non-GCB	non-GCB	Unclassified
5c	BCL2+/CD10-/BCL6-/MUM1+	non-GCB	non-GCB	non-GCB	ABC
6c	BCL2+/CD10+/BCL6+/MUM1-	GCB	GCB	GCB	GCB
7c	BCL2+/CD10+/BCL6+/MUM1-	GCB	GCB	GCB	GCB
8c	BCL2+/CD10-/BCL6-/MUM1+	non-GCB	non-GCB	non-GCB	ABC
9c	BCL2+/CD10-/BCL6-/MUM1+	non-GCB	non-GCB	non-GCB	ABC
10c	BCL2-/CD10+/BCL6+/MUM1-	GCB	GCB	GCB	GCB
11c	BCL2+/CD10-/BCL6+/MUM1+	non-GCB	non-GCB	non-GCB	ABC
12c	BCL2+/CD10-/BCL6+/MUM1+	non-GCB	non-GCB	non-GCB	ABC
13c	BCL2-/CD10+/BCL6+/MUM1-	GCB	GCB	GCB	GCB
14c	BCL2-/CD10+/BCL6+/MUM1-	GCB	GCB	GCB	GCB
1n	BCL2+/CD10-/BCL6-/MUM1+	non-GCB	non-GCB	non-GCB	ABC
2n	BCL2+/CD10+/BCL6-/MUM1-	GCB	GCB	GCB	GCB
3n	BCL2+/CD10-/BCL6+/MUM1+	non-GCB	non-GCB	non-GCB	Unclassified
4n	BCL2+/CD10-/BCL6+/MUM1+	non-GCB	non-GCB	non-GCB	Unclassified
5n	BCL2+/CD10+/BCL6+/MUM1-	GCB	GCB	GCB	GCB
6n	BCL2+/CD10-/BCL6+/MUM1+	non-GCB	non-GCB	non-GCB	ABC
7n	BCL2+/CD10-/BCL6+/MUM1+	non-GCB	non-GCB	non-GCB	ABC
8n	BCL2+/CD10-/BCL6-/MUM1+	non-GCB	non-GCB	non-GCB	ABC
9n	BCL2-/CD10+/BCL6+/MUM1-	GCB	GCB	GCB	GCB
10n	BCL2-/CD10+/BCL6+/MUM1-	GCB	GCB	GCB	GCB
11n	BCL2+/CD10+/BCL6+/MUM1-	GCB	GCB	GCB	GCB
12n	BCL2+/CD10-/BCL6+/MUM1+	non-GCB	non-GCB	non-GCB	ABC
13n	BCL2-/CD10+/BCL6+/MUM1-	GCB	GCB	GCB	Unclassified
14n	BCL2+/CD10-/BCL6+/MUM1+	non-GCB	non-GCB	non-GCB	ABC
1c to 14c: primary cutaneous large, B-cell lymphoma cases; 1n to 14n: nodal DLBCL cases; ABC: Activated-B-Cell; GCB: Germinal Center-B-Cell; ABC: Activated-B-Cell; GCB: Germinal Center-B-Cell; IHC: immunohistochemistry; GEP: Gene Expression Profiling.

Each sample meeting the QC threshold is reported as one of the three molecular subtypes GCB, or ABC or Unclassified within the equivocal zone. Subtypes are determined using a Linear Predictor Score (LPS), which is computed by summing the products of 15 weighted gene coefficients and the gene expression measurements and applying pre-defined thresholds [6,7]. Subtypes were ABC when LPS was higher or equal to 2433.5 (≥ 2433.5); GCB when LPS was lower or equal to 1907.8 (≤ 1907.8) and unclassified when LPS value was in equivocal zone (tab. 3).

t(14,18)(q32;q21) Polymerase Chain Reaction

To evaluate the t(14,18)(q32;q21) causing the BCL2-IGH rearrangements, genomic DNA was extracted by 8 sections (5–10 μm thick) using the Qiagen QIAamp DNA FFPE Tissue Kit (Qiagen, cat. n. 56404), following the manufacturer’s instructions, after treatment with Qiagen Deparaffinization Solution (Qiagen, cat. n. 19093). The kit combines the selective binding properties of a silica-based membrane by allowing the genomic DNA purification from FFPET sections without overnight incubation. Once paraffin was dissolved in xylene, samples were lysed under denaturing conditions with proteinase K and incubated at 90°C to reverse formalin cross-linking. The DNA was bound to the membrane and contaminants flowed through by centrifugation at 8000 rpm; DNA was then washed to remove the residual contaminants by centrifugation at 8000 rpm and then eluted from the membrane in 20-100 μl of Buffer ATE by centrifugation at 13200 rpm. In less than 30 minutes, the pure and concentrated DNA was ready for use in amplification reactions or for storage at –20°C.

The PCR analysis of t(14,18)(q32;q21) was carried out to evaluate BCL2-IGH rearrangement, according to Rambaldi A. et al. [20]. Briefly, the first round of amplification was in 50 μl of final volume of 1X GoTaq(R) Green Master Mix (2X; Promega, Madison, WI, USA, cat. n. M7123) using 100 ng of DNA with primers MBR for major breakpoint region, or mcr for minor cluster region and JH consensus region.

Samples were amplified on Veriti® Thermocycler (Applied Biosystems, Carlsbad, California, USA) with an initial denaturation at 95°C for 7 minutes, followed by either 27 cycles of denaturation for MBR or 30 cycles for the mcr. Each cycle was performed with 1 minute of denaturation at 94°C and 1 minute of annealing at 55°C for the MBR and 55°C for mcr amplifications and 1 minute of extension at 72°C. A nested PCR reaction was performed using 5 μl of 1:10 dilution of the first-round amplification product using oligonucleotide primers internal to the original primers, such as MBR nested, mcr nested and JH nested of which nucleotide sequences were described by Rambaldi A. et al. [20]. PCR reactions were performed according the following PCR temperature profile: denaturation for 7 minutes at 94°C, 30 cycles (1 minute at 94°C, 1 minute at 58°C and 1 minute at 72°C for each cycle) and final extension at 72°C for 10 minutes. A 25 μl aliquot of PCR product was verified on a 2% agarose gel containing ethidium bromide in Tris-borate electrophoresis buffer and visualized under UV light. Specifically, positive and negative PCR controls were processed, and samples were run in duplicate to ensure PCR reproducibility.

Data comparison

IHC data were compared to the GEP data to validate results and to one or more IHC algorithms to be used as GEP surrogate. Concordance percentage was calculated to determine the reproducibility between the GEP and IHC in PCBCL and nDLBCL. To evaluate the influence of biological, histological, immunohistochemical, or molecular data on the distribution of cases with GEP and IHC, ANOVA analysis was carried out with a significance of 5% and with two tails for independent data. Statistical analysis was performed using Graphpad Prism 8.0®. Different clinical and histological features were evaluated in discordant cases as possible cause of disagreement.

Clinical data

The 14 PCBCL sites of onset were the trunk (5 cases, 36%), arms (4 cases, 29%), legs (3 cases, 21%), eyelid (1 case, 7%) and head (1 case, 7%). nDLBCL were from cervical (5 cases, 36%), inguinal (4 cases, 29%), submandibular (3 cases, 21%) and para-aortic (2 cases, 14%) lymph nodes. The median size of PCBCL was 19,5 mm (range: 9–44 mm). The median diameter of nDLBCL was 18 mm (range, 8–60 mm). The male: female ratio of PCBCL was 7:7 with median age of 61,5 years (range: 40–80 years); the male: female ratio of nDLBCL was 6:8 with a median age of 64,5 years (range: 43–77 years). The 4 PCDLBCL-LT (29% of the PCBCL cases) concerned 2 females and 2 males, with median age of 60,5 years (range: 54–76 years). Lesions were on the legs (2 females and 1 male) and the trunk (1 male) with a median size of 25 mm (range: 15–44 mm). The 10 PCFCL (71% of the PCBCL cases) were 5 males and 5 females with median age of 62,5 years (range: 40–80 years). Lesions were on the trunk (4 cases), the arms (4 case), the head (1 case) and the eyelid (1 case) with a median size of 17 mm (range: 9–30 mm). Patients follow-up revealed relapse in 2 PCDLBCL-LT (lymph node and local, respectively) and 4 PCFCL (local).

The flow cytometry of peripheral blood, immunoglobulin gene rearrangements in lesional skin or in peripheral blood, complete and differential blood cell count, routine serum biochemistry analysis with LDH, serum protein electrophoresis, liver function tests were negative and CT-FDG-PET scan and bone marrow biopsy did not show systemic diffusion of corresponding PCBCL. As far the staging is concerned, all cases were T3-N0-M0-B0 according to ESMO recommendations [13]. All the patients underwent specific therapies, namely PCFCL with solitary or localized skin lesion received radiotherapy at the dose of 24-30 Gy, PCFCL with multifocal lesions received rituximab and/or steroids, the PCDLBCL-LT received rituximab, cyclophosphamide, deoxyrubicin, vincristine, prednisone (R-CHOP).

All the PCBCL patients were alive at the moment of the study except one (case n. 1c) who died due to disease progression and eventually central nervous system involvement. All the above-reported data are summarized in Tables 1 and 2.

Histological features and classification

Four PCBCL (29%) showed monomorphic, diffuse infiltration of the dermis by large, roundish or irregular, nucleolated cells (monotonous proliferation of centrobasts and immunoblasts), with numerous mitoses. The cells did not show epidermotropism and small lymphocytes were scant or absent (Fig. 1A and Tab. 1); these cases were diagnosed as PCDLBCL-LT. Among these cases, 2 PCDLBCL-LT (14% of PCBCL) showed reactive T cells, whereas in the remaining 2 cases T lymphocytes were few or absent (Tab. 1). Only one (25%) PCDLBCL-LT case showed skin ulceration and 2 (14% of PCBCL) cases showed necrosis and nuclear debris (Tab. 1).

Ten cases (71%) showed follicular, or follicular and diffuse (mixed), or diffuse infiltrate in the dermis of small to large centrocytes with a variable number of centroblasts; these cases were diagnosed as PCFCL (Fig. 2A and Tab. 1). 4 (29% of PCBCL) cases showed follicular growth pattern, 3 (21% of PCBCL) cases diffuse growth pattern and 3 (21% of PCBCL) mixed growth pattern (Fig. 2A and Tab. 1). Five of these cases (36% of PCBCL) showed reactive T cells and 4 (29%) cases showed a dendritic meshwork. Four PCFCL (29 % of PCBCL) showed small areas of necrosis with nuclear debris (Tab. 1).

The 14 lymph nodes used as control, had all been diagnosed as nDLBCL with diffuse growth pattern (Figs. 3A and 4A and Tab. 2).

Table 2

Clinical, histologic, phenotypic and gene expression profiling of 14 nDLBCL.
Patients	1n	2n	3n	4n	5n	6n	7n
Sex	F	F	F	M	F	M	M
Age	74	77	64	73	77	72	53
Site	Para-aortic lumbar	Cervical	Para-aortic lumbar	Inguinal	Cervical	Inguinal	Cervical
Size, mm	15	33	17	60	20	11	15
Relapse	No	No	No	No	No	No	No
Diagnosis	DLBCL	DLBCL	DLBCL	DLBCL	DLBCL	DLBCL	DLBCL
Reactive T-cells	Yes	No	Yes	Yes	Yes	Yes	No
Growth pattern	Diffuse	Diffuse	Diffuse	Diffuse	Diffuse	Diffuse	Diffuse
Necrosis	No	Yes	No	Yes	No	No	No
Nuclear debris	No	Yes	No	Yes	No	No	No
“Starry sky” pattern	No	No	No	Yes	No	No	No
Ki67 % positivity	95%	90%	70%	90%	90%	90%	90%
MYC	-	-	-	-	-	-	-
CD20	-	+	+	-	+	+	+
CD79A	+	+	+	+	+	+	+
PAX5	+	-	-	+	+	+	+
CD138	-	-	-	-	-	-	-
CD30	-	-	-	-	-	-	-
CyclinD1	-	-	-	-	-	-	-
CD5	-	-	-	-	-	-	-
CD43	-	-	-	-	-	-	-
Bcl2	+	+	+	+	+	+	+
Bcl6	-	-	+	+	-	+	+
CD10	-	+	-	-	+	-	-
Mum1/IRF4	+	-	+	+	-	+	+
Hans’ algorithm	Non-GCB	GCB	Non-GCB	Non-GCB	GCB	Non-GCB	Non-GCB
Colomo’s algorithm	Non-GCB	GCB	Non-GCB	Non-GCB	GCB	Non-GCB	Non-GCB
Muris’ algorithm	Non-GCB	GCB	Non-GCB	Non-GCB	GCB	Non-GCB	Non-GCB
t(14;18)-PCR	No	Yes	No	Yes	No	No	No
GEP	ABC	GCB	Unclassified	Unclassified	GCB	ABC	ABC

Patients	8n	9n	10n	11n	12n	13n	14n
Sex	F	F	F	F	M	M	M
Age	58	43	48	72	65	59	52
Site	Submandibular	Inguinal	Cervical	Submandibular	Submandibular	Inguinal	Cervical
Size, mm	26	9	21	40	10	8	18
Relapse	No	No	No	No	No	No	No
Diagnosis	DLBCL	DLBCL	DLBCL	DLBCL	DLBCL	DLBCL	DLBCL
Reactive T-cells	No	No	No	No	No	No	Yes
Growth pattern	Diffuse	Diffuse	Diffuse	Diffuse	Diffuse	Diffuse	Diffuse
Necrosis	No	No	No	No	No	Yes	No
Nuclear debris	No	No	No	No	No	Yes	No
“Starry sky” pattern	No	No	No	No	No	Yes	No
Ki67 % positivity	95%	90%	45%	90%	75%	80%	30%
MYC	-	-	-	-	-	-	-
CD20	+	+	+	+	+	+	+
CD79A	+	+	-	+	+	+	+
PAX5	+	+	+	+	+	-	+
CD138	-	-	-	-	-	-	-
CD30	-	-	-	-	-	-	-
Cyclin1	-	-	-	-	-	-	-
CD5	-	-	-	-	-	-	-
CD5	-	-	-	-	-	-	-
Bcl2	+	-	-	+	+	-	+
Bcl6	-	+	+	+	+	+	+
CD10	-	+	+	+	-	+	-
Mum1/IRF4	+	-	-	-	+	-	+
Hans’ algorithm	Non-GCB	GCB	GCB	GCB	Non-GCB	GCB	Non-GCB
Colomo’s algorithm	Non-GCB	GCB	GCB	GCB	Non-GCB	GCB	Non-GCB
Muris’ algorithm	Non-GCB	GCB	GCB	GCB	Non-GCB	GCB	Non-GCB
t(14;18)-PCR	No	Yes	Yes	Yes	No	Yes	No
GEP	ABC	GCB	GCB	GCB	ABC	Unclassified	ABC
nDLBCL: nodal Diffuse, large, B-cell Lymphoma; ABC: Activated-B-Cell; GCB: Germinal Center-B-Cell; IHC: immunohistochemistry; GEP: Gene Expression Profiling.

Six of these (43%) showed reactive T cells intermingled in the tumour, being absent in the remaining 8 (57%) cases (Tab. 2). Necrosis and nuclear debris were observed in 3 out of 14 (21%) nDLBCL and 2 (14%) cases showed also “starry sky” pattern (Tab. 2).

Clinical and histological data of the 14 PCBCL and 14 nDLBCL are summarized in Tables 1 and 2.

Immunohistochemistry

The immunohistochemical evaluation showed the following results: CD20 positivity was observed in all 14 PCBCL cases and in 12 nDLBCL (86%) being negative in cases 1n and 4n (Tabs. 1 and 2). In all 28 PCBCL and nDLBCL cases CD79A positivity was observed, whereas PAX5 was expressed only by 11 nDLCBL cases, being absent in 2n,3n,13n and in the all 14 PCBCL cases.

CD10 positivity was observed in 13 out of 28 (46%) cases, namely in 7 out of 14 (50%) PCFCL and in 6 out of 14 (43%) nDLBCL (Tabs. 1 and 2, Figs. 2B and 3B). BCL6 positivity was showed in 20 out of 28 (71%) cases: 9 PCFCL (64% of PCBCL), 1 PCDLBCL-LT (7% of PCBCL) and 10 nDLBCL (Tabs. 1 and 2, Figs. 2C, 3C and 4C). MUM1/IRF4 positivity was observed in 15 out of 28 (54%) cases (50% PCBCL and 57% nDLBCL), namely: 4 PCDLBCL-LT (29% of PCBCL), 3 PCFCL (21% of PCBCL) and 8 nDLBCL (Tabs. 1 and 2, Figs 1D and 4D). BCL2 positivity was observed in 21 out of 28 (75%) cases (71% PCBCL and 79% nDLBCL): 4 PCDLBCL-LT (29% of PCBCL), 6 PCFCL (43% of PCBCL) and 11 nDLBCL (Tabs. 1 and 2, Fig. 1E). CD3 positive reactive lymphocytes were observed in 13 out of 28 (46%) cases (50% PCBCL and 43% nDLBCL), namely: 2 PCDLBCL-LT (14% of PCBCL), 5 PCFCL (36% of PCBCL) and 6 nDLBCL (Tabs. 1 and 2). CD2, CD4, CD5, CD8, CD30, CD68, CD138, ALK, MYC, CyclinD1 and Cytokeratin were unexpressed in the neoplastic cells of the all 28 PCBCL and nDLBCL but not in the internal controls (Tabs. 1 and 2).

Ki-67 showed a median value of 76,5% (range: 20-90%) for PCBCL and 80% (range, 30-95%) for nDLBCL (Tabs. 1 and 2). In particular, the Ki-67% median value was 77,5% (range, 60-90%) in PCDLBLC-LT and 71,5% (range, 20-87%) in PCFCL cases. According to the Ki67 rate, 12 PCBCL (86%) and 12 nDLBCL (86%) were defined to have “high proliferative rate” (>50%) namely 4 PCDLBCL-LT and 8 PCFCL (Tabs. 1 and 2). The remaining 2 PCFCL and 2 nDLBCL were classified as “low proliferative rate” (<50%).

“Cell of Origin” classification by Immunohistochemical Algorithms

The IHC COO classification in both series was performed according to Hans’, Colomo’s and Muris’ algorithms [15,17-19] using CD10, BCL6, MUM1 and BCL2 IHC stains. Applying Hans’ algorithm, 13 out of 28 (46%) samples were classified as GCB [7 out of 14 (50%) PCBCL and 6 out of 14 (43%) nDLBCL] by showing CD10+/BCL6+/MUM1- (6 PCFCL and 4 nDLBCL) and CD10+/BCL6-/MUM1- (2 nDLBCL) profiles; 15 out of 28 (54%) samples were classified as non-GCB [7 out of 14 (50%) PCBCL and 8 out of 14 (57%) nDLBCL] by showing the CD10-/BCL6+/MUM1+ (1 PCDLBCL-LT, 2 PCFCL and 6 nDLBCL) and CD10-/BCL6-/MUM1+ (3 PCDLBCL-LT and 2 nDLBCL) profiles (Tabs. 1, 2 and 3). Applying Colomo’s algorithm, 13 out of 28 (46%) samples were classified as GCB [7 out of 14 (50%) PCBCL and 6 out of 14 (43%) nDLBCL] by showing MUM1-/CD10+/BCL6+ (7 PCFCL and 4 nDLBCL) or MUM1-/CD10+/BCL6- (2 nDLBCL) profiles; 15 out of 28 (54%) samples were classified as non-GCB [7 out of 14 (50%) PCBCL and 8 out of 14 (57%) nDLBCL] by showing the MUM1+/CD10-/BCL6- (3 PCDLBCL-LT, 1 PCFCL and 2 nDLBCL) profile or showing the MUM1+/CD10-/BCL6+ (1 PCDLBLC-LT, 2 PCFCL and 6 nDLBCL) (Tabs. 1, 2 and 3). Applying Muris’ algorithm, 13 out of 28 (46%) samples were classified as GCB [7 out of 14 (50%) PCBCL and 6 out 14 (43%) nDLBCL] by showing BCL2+/CD10+/MUM1- (3 PCFCL and 3 nDLBCL) or BCL2-/CD10+/MUM1- (4 PCFCL and 3 nDLBCL) profiles; 15 out of 28 (54%) samples were classified as non-GCB [7 out of 14 (50%) PCBCL and 8 out 14 (57%) nDLBCL] by showing the BCL2+/CD10-/MUM1+ (4 PCDLBCL-LT, 3 PCFCL and 8 nDLBCL) profile (Tabs. 1, 2 and 3).

Comparing the three algorithms, 13 out of 28 (46%) samples were GCB (7 PCFCL and 6 nDLBCL), 14 out of 28 (50%) were non-GCB (4 PCDLBCL-LT, 3 PCFCL and 8 nDLBCL). No samples showed discordant results when IHC algorithms were compared to each other (Tabs. 1, 2 and 3). The only case (PCDLBCL-LT, case 5c) with skin ulceration was non-GCB (Tabs. 1, 2 and 3).

“Cell of Origin” classification by Gene Expression Profiling

At GEP, all the 28 samples met the QC threshold of 128 and subtypes reported as GCB, ABC or unclassified were provided. The subtype distribution was 12 GCB (43%), 12 ABC (43%) and 4 unclassified (14%) (Tabs. 1, 2, 3 and 4). QC status of each sample and subtype output for all the samples that passed RNA quality are summarized in Table 4.

Table 4

Cell of origin subtype and QC results by GEP.
Sample ID	LPS	Subtype	HK Geomean	QC
1 c	3140	ABC	938	Pass
2 c	157	GCB	1198	Pass
3 c	19	GCB	1126	Pass
4 c	2130	Unclassified	850	Pass
5 c	2648	ABC	1154	Pass
6 c	314	GCB	2153	Pass
7 c	784	GCB	930	Pass
8 c	2478	ABC	3487	Pass
9 c	3143	ABC	1322	Pass
10 c	1906	GCB	899	Pass
11 c	3254	ABC	2092	Pass
12 c	2578	ABC	1509	Pass
13 c	45	GCB	3216	Pass
14 c	189	GCB	986	Pass
1 n	2924	ABC	1491	Pass
2 n	547	GCB	802	Pass
3 n	2070	Unclassified	8425	Pass
4 n	2016	Unclassified	823	Pass
5 n	944	GCB	863	Pass
6 n	2418	ABC	1047	Pass
7 n	3340	ABC	1047	Pass
8 n	2864	ABC	863	Pass
9 n	243	GCB	897	Pass
10 n	1452	GCB	1146	Pass
11 n	1402	GCB	1407	Pass
12 n	2507	ABC	2013	Pass
13 n	2238	Unclassified	1054	Pass
14 n	3009	ABC	3048	Pass
GEP: gene expression profiling; LPS: Linear Predictor Score; HK geomean: housekeeping genes; QC: quality control; ABC: Activated-B-Cell; GCB: Germinal Center-B-Cell; 1c to 14c: primary cutaneous large, B-cell lymphoma cases; 1n to 14n: nodal DLBCL cases. HK geomean was the geometric mean of 5 housekeeping genes; LPS were computed by summing the products of 15 weighted gene coefficients and the gene expression measurements and applying pre-defined thresholds; ABC is sample with LPS ≥ 2433.5; GCB is sample with LPS ≤ 1907.8; Unclassified is sample with an equivocal zone; Pass: sample met the pre-defined clinical QC threshold of 128.

In particular, GCB were represented by 7 out of 14 (50%) PCBCL (7 PCFCL) and 5 out of 14 nDLBCL (36%); ABC cases were 6 out of 14 (43%) PCBCL (3 PCDBLCL-LT and 3 PCFCL) and 6 out of 14 nDLBCL (43%); unclassified cases were 1 PCDLBCL-LT and 3 nDLBCL (Tabs. 1, 2, 3 and 4 and Figs. 5 and 6). Among ABC, only one PCDLBCL-LT showed skin ulceration (case 5c); among unclassified only 2 nDLBCL (cases 4n and 13n) showed starry sky pattern (tabs. 1, 2, 3 and 4).

PCR evaluation of t(14,18)(q32;q21)

On agarose gel electrophoresis, the BCL2-IGH expected bands were showed by all positive controls and by 6 nDLBCL (43%) (Tab. 2). The reproducible sensitivity level was 10^-5 for MBR and 10^-4 for mcr [20]. Comparing PCR data with IHC, 3 nDLBCL (cases 2n, 4n, 11n) resulted BCL2 positive in both procedures (Tab. 2). The remaining 3 cases showed only PCR positivity (Tab. 2), whereas 8 cases (1n, 3n, 5n, 6n, 7n, 8n, 12n and 14n) showed only IHC BCL2 positivity. With reference to IHC algorithms and GEP, t(14;18) was detected in 5 GCB and 1 non-GCB as defined by IHC’ algorithms; and in 4 GCB and 2 unclassified as defined by GEP (Tab. 2).

Data comparison

The concordance percentage between IHC algorithms and GEP was calculated. Among PCBCL, concordance was 93% with IHC algorithms and GEP, with identical results in 10 PCFCL (7 GCB and 3 ABC), 3 PCDLBCL-LT (ABC) (Tabs. 1, 2 and 3). Concordance between GEP ABC and IHC non-GCB was 43%, whereas concordance between GEP GCB and IHC GCB was 50%. Moreover, the three IHC algorithms showed a 100% concordance with each other (Tabs. 1, 2 and 3). Among nDLBCL, concordance was 79% with IHC algorithms and GEP, results being identical in 11 nDLBCL (5 GCB and 6 ABC) (Tabs. 1, 2 and 3). Concordance between GEP ABC and IHC non-GCB PCBCL was of 43%, whereas concordance between GEP GCB and IHC GCB was 79%.

ANOVA analysis showed that the different distribution of the PCBCL (p=0,9795) and nDLBCL (p=0,9951) cases among GEP and IHC cases was not influenced by biological, histological, immunological and molecular data. No statistically significant differences were found when ANOVA was carried out for distribution PCBCL in GEP (p=0,7114) and IHC (p=0,8911) groups; similarly when we compared GEP GCB vs IHC GEP (p>0,9999) and GEP ABC vs IHC non-GCB (p=0,4808). Regarding nDLBCL no statistically significant differences were found when ANOVA was carried out only on GEP (p=0,9538) and IHC (p=0,3096) groups and when we compared GEP GCB vs IHC GEP (p=0,5191) and GEP ABC vs IHC non-GCB (p=0,2127).

The 4 out of 28 IHC vs GEP discordant cases were: 1 PCDLBCL-LT (case 4c) that resulted non-GCB at IHC algorithms and unclassified at GEP (Tabs. 1, 2 and 3); 2 nDLBCL (cases 3n and 4n) were non-GCB at IHC and unclassified at GEP, while the other case (13n) was GCB at IHC algorithms and unclassified at GEP (Tabs. 1, 2 and 3). Among discordant cases, 4c PCDLBCL-LT case was a 54-year-old female with a 15 mm lesion on the leg and local relapse, with reactive T cells, diffuse growth pattern, necrosis and nuclear debris, Ki-67 of 60% and IHC BCL2 positivity (Tab. 1). The 2 nDLBCL (cases 3n and 4n) that were non-GCB at IHC algorithms and unclassified at GEP were a female and a male aged 64 and 73 respectively, with 17 mm and 60 mm lesions on para-aortic lumbar and inguinal nodules, with reactive T cells (Tab. 2). The female nDLBCL (case 3n) showed diffuse growth pattern, Ki-67 of 70% and IHC BCL2 positivity, while the male nDLBCL (case 4n) showed diffuse growth pattern, nuclear and necrotic debris and starry sky pattern, Ki-67 of 90%, IHC BCL2 and t(14;18) positivity (Tab. 2). The 13n nDLBCL case GCB at IHC algorithms and unclassified at GEP was a male aged 59 with a 8 mm lesion on inguinal nodules, diffuse growth pattern, nuclear and necrotic debris and starry sky pattern, Ki-67 of 80% and t(14;18) positivity (Tab. 2).

PCBCL are a rare and heterogeneous sub-group of primary cutaneous lymphoma; the latest WHO classification of lymphoid tumours has classified PCBCL in PCMZL, PCFCL and PCDLBCL-LT [1–3]. PCMZL is a defined entity with specific prognosis and therapeutic indications. The distinction between PCFCL and PCDLBCL-LT may be less defined whereas prognosis and treatment may be different [13]. Therefore, an accurate sub-classification of these entities, like that of nDLBCL, might be useful. nDLBCL is the largest and most heterogeneous group of non-Hodgkin lymphomas (NHLs); they may arise de novo or from a pre-existing differentiated NHL. Evidence shows that their prognosis and response to therapies are influenced by the corresponding COO; namely, GCB has a better response to therapy and longer disease-free survival than ABC and unclassified cases.

Numerous studies have investigated the COO classification of nDLBCL and its clinical relevance either by IHC or GEP, but little corresponding data on PCBCL are available so far [8, 9, 12, 21–35]. This is probably due to the heterogeneity of PCBCL, their relatively recent classification and their low incidence when compared to nDLBCL. Despite that, a COO sub-classification of PCFCL and PCDLBCL-LT would be desirable for prognostic and predictive evaluations as PCFCL are generally treated with radiotherapy only where PCDLBCL-LT require chemotherapy. A large and comprehensive study on GEP of PCBCL has been performed by Hoefnagel et al. [8]. In this study differences in GEP of PCFCL and PCDLBCL-LT have been detected and considered to be the cutaneous counterpart of nDLBCL GCB and ABC types, respectively. For this purpose, Hoefnagel et al. [8] investigated the whole genome of PCBCL and concluded that the different expression of few genes determines the distinction of PCBCL in 2 subtypes. This distinction was validated by quantitative PCR of seven genes and by the MUM1/IRF4 expression only by IHC. In our study we analysed 14 PCBCL and 14 nDLBCL cases by GEP, focusing on a small number of genes (23 Lymphoma/Leukaemia-related and 5 housekeeping genes) of the Lymph2Cx assay of Nanostring Technologies (Seattle, WA, USA) GEP, that are involved in cell cycle apoptosis, B-cell differentiation, B-cell receptor signalling, antigen presentation, chromatin regulation/DNA methylation [6, 7]. IHC and GEP data of two parallel series of PCBCL and nDLBCL were compared to validate IHC data and to analyse the performance of three IHC algorithms frequently used in clinical practice. As previously reported, most PCFCL were CD10+ (70%, 7 out of 10) and BCL6+ (90%, 9 out of 10), but only 6 out of 10 (60%) showed BCL2 positivity. Only 3 PCFCL were MUM1/IRF4+ (80%, 4 out 5) while the all 4 PCDLBCL-LT were MUM1/IRF4+ (100%) and BCL2+ (100%). Therefore, BCL2 expression seems to differentiate PCDLBCL-LT from PCFCL with diffuse growth pattern and predominance of centroblasts, since BCL2 was strongly expressed in PCDLBCL-LT, as already observed elsewhere [39–41]. Moreover, the molecular analysis of t(14;18) confirmed that the BCL2-IGH translocation was negative in PCBCL [23, 42]. Therefore, according to the literature, BCL2 over-expression in PCBCL seems to be associated with BCL2 amplification rather than with a translocation; conversely BCL2 over-expression is rare in PCFCL lacking either amplification or translocation [39]. As for BCL2 expression, in nDLBCL 11 cases (78%) showed BCL2 over-expression at IHC and 6 cases (43%) the t(14;18), with 3 cases showing translocation and over-expression.

The comparison between GEP and IHC data in PCBCL showed concordance in 93% (13 out of 14 cases) with IHC algorithms (Table 3). IHC profiles and GEP were concordant in nDLBCL cohorts at 79% (11 out of 14 cases) with IHC algorithms (Table 3). The percentage of nDLBCL is similar to data provided elsewhere [5, 6, 9, 15, 17–19, 21, 26, 30, 34].

In addition to the GEP, some studies have been conducted to identify PCBCL genetic differences by using whole genome sequencing or comparative genomic hybridization array analysis [29]. Different alterations were found including gains such as 18/18q; 7/7p; 3/3q; 1p; 12/12q; 13/13q or loss such as 6q of different chromosomes. Oncogene gains (SAS/CDK4, MYCL1, MYC, FGFR2, BCL2, CSE1L, PDGFB) or losses (AKT1, IGFR1, JUNB, FGR, ESR, ABL1, TOP2A, ERBB2, CCNE1, BCR) were also detected as demonstrated by Mao et al. by comparative genomic hybridization and microarray-based genomic analysis [29]. Multiple genomic mutations in the NF-kB and B-cell signalling pathways have been characterized in PCDLBCL-LT [26], similarly to MYD88 somatic mutation in PCDLBCL-LT [31]. MicroRNA studies on PCBCL have demonstrated the overexpression of microRNA 17–92 cluster and its paralogs miR-106a-363 in PCDLBCL-LT, that have a causative role in lymphomagenesis, when compared to PCFCL [22]. Conversely miR-9-5p, miR-31-5p, miR-129-2-3p and miR214-3p are overexpressed in PCFCL when compared to PCDLBCL-LT [28]. Nonetheless the same authors assess that microRNAs — reported as overexpressed in the ABC type when compared to the GCB type — in nDLBCL are not differentially expressed between PCFCL and PCDLBCL-LT [28]. Another study has highlighted different profiling of genes of apoptosis and cytotoxic immune response being the first enhanced in PCDLBCL-LT and the second in PCFCL [41]. PCDLBCL-LT and PCFCL may be differentiated for specific chromosomal abnormalities too [24]. According to their study, performed by array-based comparative genomic hybridization, amplification of 2p16.1 and deletion of 14q32.33 chromosomes frequently occur in PCFCL [24]. Conversely amplification of 18q21.31-q21.33 including the BCL-2 and MALT1 genes and deletions of 9p21.3 were specific of PCDLBCL-LT [24]. All these studies produced significant information on PCBCL but do not have clinical implications in terms of prognostic and predictive evaluation.

With reference to the IHC differentiation of the PCFCL and PCDLBCL-LT, Hallerman et al. [25] observed that BCL2, OCT2 and MUM1 positivity was associated with poor prognosis and BCL6 positivity with a better prognosis, whereas the differentiation between PCBCL and PCDLBCL-LT was less straightforward. Similar data were reported by Sundram U et al. [33]: analysing 14 PCBCL, they noted that the patients were divided into two groups: one with BCL6 positivity, MUM1 negativity and overall survival of 176 months; the second with BCL6 negativity, MUM1 positivity and shortest overall survival (26 months). Another study showed that PCFCL and PCDLBCL-LT have a germinal centre B-cell differentiation stage signature when applying gene profiling on 17 PCBCL [9].

Consequently, most PCFCL were GCB when applying the three IHC algorithms, while most PCFCL with diffuse growth pattern and all the PCDLBCL-LT were ABC by GEP. Therefore, PCFCL with the follicular growth pattern might be equivalent to the nDLBCL GCB type and the PCFCL with diffuse growth pattern and PCDLBCL-LT might be referable to the nDLBCL ABC type.

Data obtained in our series support the reliability of IHC algorithms in the prognostic and predictive evaluation of PCBCL with accuracy comparable to that reported for nDLCBL. With reference to the different applied algorithms, Hans’ and Muris’ algorithms seem to be the most suitable for PCBCL.

In conclusion, our study confirms that GEP classification of PCBCL reproduces the classification of nDLBCL. A good correlation has been assessed between the GEP classification and the IHC expression of CD10, MUM1/IRF4, BCL6, BCL2 and MYC. These data may be utilized for the prognostic evaluation of PCBCL, but further validation on larger series is required.

Contributor and guarantor information:

P.Z, I.C., A.P, S.P., M.T., C.S., A. I. and A.L.P. conceived and designed the study. A.L.P., P.C, C.P, A.C. and P.Z. equally contributed in writing the text of the article. P.C, A.C, and C.B. collected patient clinical and histological data. P.C and A.C provided photographic material and performed statistical analysis. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.

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the Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to i) publish, reproduce, distribute, display and store the Contribution, ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, iii) create any other derivative work(s) based on the Contribution, iv) to exploit all subsidiary rights in the Contribution, v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, vi) licence any third party to do any or all of the above.

Patient consent:

written informed consent to perform this study was obtained from all the participants.

Competing interests declaration:

all authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for the submitted work; no financial

relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

Research involving Human Participants and/or Animals:

The study was approved by the IRCCS Pascale Ethical Committee on the basis of the Institute’s ethical regulations for research on human tissues. The study was performed in accordance with the ethical standards as laid down in the 1964 Declaration of Helsinki and its later amendments.

Transparency statement:

the lead author (the manuscript's guarantor), P.Z. affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as originally planned (and, if relevant, registered) have been explained.

Funding:

This work received funding from the Italian Ministry for Education, University and Research (MIUR – Ministero dell’Istruzione, Università e Ricerca), “Fondo per gli Investimenti della Ricerca di Base (FIRB)”.

Patients and public involvement:

Patients and public have been not involved in no one of the various phases of this research.

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Immunohistochemical Algorithms and Gene Expression Profiling in Primary Cutaneous B-cell Lymphoma

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Abstract

Figures

Summary Box

What is already known on this topic:

What this study adds:

Introduction

Methods

Study group

Patients

Immunohistochemistry

Immunohistochemical classification

Gene Expression Profiling

Gene expression profiling analysis

t(14,18)(q32;q21) Polymerase Chain Reaction

Data comparison

Results

Clinical data

Histological features and classification

Immunohistochemistry

“Cell of Origin” classification by Immunohistochemical Algorithms

“Cell of Origin” classification by Gene Expression Profiling

PCR evaluation of t(14,18)(q32;q21)

Data comparison

Discussion

Declarations

Contributor and guarantor information:

Copyright/license for publication:

Patient consent:

Competing interests declaration:

Research involving Human Participants and/or Animals:

Transparency statement:

Funding:

Patients and public involvement:

References

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