análisis automático. estudio inicial (lst) y clasificación

Análisis automático. Estudio inicial (LST) de los

síndromes linfoproliferativos crónicos T y NK

Teoría

Julia Almeida MD PhDCentro de Investigación del Cáncer, Universidad de Salamanca / IBSAL & CIBERONC

Análisis automático. Estudio inicial (LST) de los síndromes linfoproliferativos crónicos T y NK

Análisis automático. Estudio inicial (LST) de los síndromes linfoproliferativos crónicos T y NK

Chronic lymphoproliferative disorders

Large and heterogeneous group of disorders characterized by

proliferation and accumulation of morphologic and

immunophenotypic mature lymphocytes in diverse locations

Classification is initially based on lymphoid lineage

assessment

B-cell

CD19+

CD20+

Igs+

T- & NK- cells

CD3+

CD7+

CD4+/CD8+

CD3-

CD7+

CD56+

CD16+

Consequently, build upon morphologic, pathologic, immunophenotypic, genetic,

epidemiologic and clinical features (WHO2017 Classification)

Courtesy of Juan Flores MD PhD

Chronic lymphoproliferative disorders: WHO2017 classificationCLL/small lymphocytic lymphoma

B-cell prolymphocytic leukaemia

Splenic marginal zone lymphoma

Hairy cell leukaemia

Splenic B-cell lymphoma/leukaemia, unclassifiable

Lymphoplasmacytic lymphoma

IgM MGUS

Heavy chain diseases

Plasma cell neoplasms

Extranodal marginal zone lymphoma of MALT tissues

Nodal marginal zone lymphoma

Follicular lymphoma

Paediatric-type follicular lymphoma

Large B-cell lymphoma with IRF4 rearrangement

Primary cutaneous follicle centre lymphoma

Mantle cell lymphoma

Diffuse large B-cell lymphoma (DLBCL), NOS

T-cell/histiocyte-rich large B-cell lymphoma

Primary diffuse large B-cell lymphoma of the CNS

Primary cutaneous diffuse large B-cell lymphoma, leg type

EBV-positive diffuse large B-cell lymphoma, NOS

EBV-positive mucocutaneous ulcer

DLBCL associated with chronic inflammation

Lymphomatoid granulomatosis

Primary mediastinal (thymic) large B-cell lymphoma

Intravascular large B-cell lymphoma

ALK-positive large B-cell lymphoma

Plasmablastic lymphoma

Primary effusion lymphoma

HHV8-associated lymphoproliferative disorders

Burkitt lymphoma

Burkitt-like lymphoma with 11q aberration

High-grade B-cell lymphoma

B-cell lymphoma, unclassifiable,

with features intermediate between DLBCL and classic Hodgkin lymphoma

T-cell prolymphocytic leukaemia

T-cell large granular lymphocytic leukaemia

Chronic lymphoproliferative disorder of NK cells

Aggressive NK-cell leukaemia

EBV-positive T-cell and NK-cell LPDs of childhood

Systemic EBV+ T-cell lymphoma of childhood

Chronic active EBV infection of T- and NK-cell type, systemic form

Hydroa vacciniforme-like lymphoproliferative disorder

Severe mosquito bite allergy

Adult T-cell leukaemia/lymphoma

Extranodal NK/T-cell lymphoma, nasal type

Intestinal T-cell lymphoma

Enteropathy-associated T-cell lymphoma

Monomorphic epitheliotropic intestinal T-cell lymphoma

Intestinal T-cell lymphoma, NOS

Indolent T-cell lymphoproliferative disorder of the GIT

Hepatosplenic T-cell lymphoma

Subcutaneous panniculitis-like T-cell lymphoma

Mycosis fungoides

Sézary syndrome

Primary cutaneous CD30-positive T-cell LPDs

Lymphomatoid papulosis

Primary cutaneous anaplastic large cell lymphoma

Primary cutaneous peripheral T-cell lymphomas, rare subtypes

Primary cutaneous gamma delta T-cell lymphoma

Primary cutaneous CD8-positive aggressive epidermotropic cytotoxic T-cell lymphoma

Primary cutaneous acral CD8-positive T-cell lymphoma

Primary cutaneous CD4+ small/medium T-cell LPD

Peripheral T-cell lymphoma, NOS

Angioimmunoblastic T-cell lymphoma and other nodal lymphomas of T follicular

helper (TFH) cell originAngioimmunoblastic T-cell lymphoma

Follicular T-cell lymphoma

Nodal peripheral T-cell lymphoma with TFH phenotype

Anaplastic large cell lymphoma, ALK-positive

Anaplastic large cell lymphoma, ALK-negative

Breast implant-associated anaplastic large cell lymphoma

Matu

re B

-cell n

eopla

sms

Matu

re T

-and N

K-c

ell n

eopla

sms


Chronic lymphoproliferative disorders: WHO2017 classificationCLL/small lymphocytic lymphoma

B-cell prolymphocytic leukaemia

Splenic marginal zone lymphoma

Hairy cell leukaemia

Splenic B-cell lymphoma/leukaemia, unclassifiable

Lymphoplasmacytic lymphoma

IgM MGUS

Heavy chain diseases

Plasma cell neoplasms

Extranodal marginal zone lymphoma of MALT tissues

Nodal marginal zone lymphoma

Follicular lymphoma

Paediatric-type follicular lymphoma

Large B-cell lymphoma with IRF4 rearrangement

Primary cutaneous follicle centre lymphoma

Mantle cell lymphoma

Diffuse large B-cell lymphoma (DLBCL), NOS

T-cell/histiocyte-rich large B-cell lymphoma

Primary diffuse large B-cell lymphoma of the CNS

Primary cutaneous diffuse large B-cell lymphoma, leg type

EBV-positive diffuse large B-cell lymphoma, NOS

EBV-positive mucocutaneous ulcer

DLBCL associated with chronic inflammation

Lymphomatoid granulomatosis

Primary mediastinal (thymic) large B-cell lymphoma

Intravascular large B-cell lymphoma

ALK-positive large B-cell lymphoma

Plasmablastic lymphoma

Primary effusion lymphoma

HHV8-associated lymphoproliferative disorders

Burkitt lymphoma

Burkitt-like lymphoma with 11q aberration

High-grade B-cell lymphoma

B-cell lymphoma, unclassifiable,

with features intermediate between DLBCL and classic Hodgkin lymphoma

T-cell prolymphocytic leukaemia

T-cell large granular lymphocytic leukaemia

Chronic lymphoproliferative disorder of NK cells

Aggressive NK-cell leukaemia

EBV-positive T-cell and NK-cell LPDs of childhood*

Systemic EBV+ T-cell lymphoma of childhood

Chronic active EBV infection of T- and NK-cell type, systemic form

Hydroa vacciniforme-like lymphoproliferative disorder

Severe mosquito bite allergy

Adult T-cell leukaemia/lymphoma

Extranodal NK/T-cell lymphoma, nasal type

Intestinal T-cell lymphoma

Enteropathy-associated T-cell lymphoma

Monomorphic epitheliotropic intestinal T-cell lymphoma*

Intestinal T-cell lymphoma, NOS

Indolent T-cell lymphoproliferative disorder of the GIT*

Hepatosplenic T-cell lymphoma

Subcutaneous panniculitis-like T-cell lymphoma

Mycosis fungoides

Sézary syndrome

Primary cutaneous CD30-positive T-cell LPDs

Lymphomatoid papulosis

Primary cutaneous anaplastic large cell lymphoma

Primary cutaneous peripheral T-cell lymphomas, rare subtypes

Primary cutaneous gamma delta T-cell lymphoma

Primary cutaneous CD8-positive aggressive epidermotropic cytotoxic T-cell lymphoma

Primary cutaneous acral CD8-positive T-cell lymphoma*

Primary cutaneous CD4+ small/medium T-cell LPD*

Peripheral T-cell lymphoma, NOS

Angioimmunoblastic T-cell lymphoma and other nodal lymphomas of T follicular

helper (TFH) cell originAngioimmunoblastic T-cell lymphoma

Follicular T-cell lymphoma*

Nodal peripheral T-cell lymphoma with TFH phenotype*

Anaplastic large cell lymphoma, ALK-positive

Anaplastic large cell lymphoma, ALK-negative*

Breast implant-associated anaplastic large cell lymphoma*

Matu

re B

-cell n

eopla

sms

Matu

re T

-and N

K-c

ell n

eopla

sms

Provisional entities are shown in Italics

* Changes from the 2008 classification

CD8 - FITC

CD

4 -

PEC

y5

WHO DISEASE ENTITIES

ImmunophenotypeClinical features

Morphology Genetics & molecular

How can multiparametric

flow cytometry (FCM)

help for the study of

of T- and NK-cell CLPD

in the clinical setting?

Sequential FCM strategy to diagnose and characterize T/NK-CLPD

Leukemia 2012; 26, 1908–1975 (van Dongen et al on behalf of EuroFlow)

Clinical questions

1st step: LYMPHOCYTE SCREENING TUBE



FCM in T/NK-cell CLPD

1. Diagnostic screening

- Normal reactive/regenerating clonal

2. Classification

- Definition of biologic and clinical entities

- Risk group definition

- Prognostic stratification

3. Assessment of response to treatment

Increased T cell population

Normal / residual

T cells

Clinical questions


2nd step: T-CLPD CLASSIFICATION



FCM in T/NK-cell CLPD

1. Diagnostic screening

- Normal reactive/regenerating clonal

2. Classification

- Definition of biologic and clinical entities

- Risk group definition

- Prognostic stratification

3. Assessment of response to treatment

Normal / residual T cells

T-PLL

EuroFlow Lymphoid Screening Tube (LST)

PacB PacO FITC PEPerCp

Cy5.5PE Cy7 APC

APC

H7

LSTCD4

CD20CD45

CD8

sIgl

CD56

sIgkCD5

CD19

TCRgdCD3 CD38

• Identification of targeted cell populations: mature B-, T- & NK-cells

• Subsetting into major subpopulations

• Detection of abnormal cell populations requiring further evaluation

• Altered (distribution or absolute cell) concentration

• Aberrant immunophenotypic pattern

• B-cell clonality


AIMS

Rapid immunophenotypic screening of T/NK lymphocytosis

Normal PB

CD4/CD8 ratio = 2.5

CD20 + CD4 - PacBCD20 + CD4 - PacB CD5 - PerCP-Cy5.5

CD

3 -

APC

CD

8 +

anti

-sIg

l-

FIT

C

CD

8 +

anti

-sIg

l-

FIT

C

Only mature lymphoid

cells are shown



Normal PB

T-CLPD PB

CD4/CD8 ratio = 2.5


CD

3 -

APC

CD

8 +

anti

-sIg

l-

FIT

C

CD

8 +

anti

-sIg

l-

FIT

C


CD

3 -

APC

CD

8 +

anti

-sIg

l-

FIT

C

CD

8 +

anti

-sIg

l-

FIT

C


cells are shown



Normal PB

T-CLPD PB

CD4/CD8 ratio = 2.5


CD

3 -

APC

CD

8 +

anti

-sIg

l-

FIT

C

CD

8 +

anti

-sIg

l-

FIT

C


CD

3 -

APC

CD

8 +

anti

-sIg

l-

FIT

C

CD

8 +

anti

-sIg

l-

FIT

C


cells are shown


CD4/CD8 ratio = 22


Normal PB

CD4/CD8 ratio = 2.5


CD

3 -

APC

CD

8 +

anti

-sIg

l-

FIT

C

CD

8 +

anti

-sIg

l-

FIT

C


T-CLPD PB


CD

3 -

APC

CD

8 +

anti

-sIg

l-

FIT

C

CD

8 +

anti

-sIg

l-

FIT

C


Normal PB

CD4/CD8 ratio = 2.5


CD

3 -

APC

CD

8 +

anti

-sIg

l-

FIT

C

CD

8 +

anti

-sIg

l-

FIT

C


T-CLPD PB


CD

3 -

APC

CD

8 +

anti

-sIg

l-

FIT

C

CD

8 +

anti

-sIg

l-

FIT

CCD4/CD8 ratio = 0.32


PacB PacO FITC PEPerCp

Cy5.5PE Cy7 APC

APC

H7

LSTCD4

CD20CD45

CD8

sIgl

CD56

sIgkCD5

CD19

TCRgdCD3 CD38

• Identification of targeted cell populations: mature B-, T- & NK-cells

• Subsetting into major subpopulations

• Detection of abnormal cell populations requiring further evaluation

• Altered (distribution or absolute cell) concentration

• Aberrant immunophenotypic pattern (≥94% of T-CLPD and NK-CLPD)

• B-cell clonality


AIMS

EuroFlow strategy in CLPD

LST validation

B-cells CD8hi T-cells NK-cellsCD4+ T-

cells

Principal component analysis

Principal component 1

Pri

ncip

al com

ponent

2

Lymphoid cells abnormality N

Immunophenotypic profile (n=227) 227/233 (97.4%)

Altered numbers /distribution (n=172) 172/233 (73.8%)

Total (n=233) 233/233 (100%)

Conventional vs reference data base interpretation

Courtesy of Juan Flores MD PhD Leukemia 2012; 26, 1908–1975 (van Dongen et al on behalf of EuroFlow)

EuroFlow strategy in CLPD

LST validation

B-cells CD8hi T-cells NK-cellsCD4+ T-

cells

Principal component 1

Pri

ncip

al com

ponent

2

Lymphoid cells abnormality N

Immunophenotypic profile (n=227) 227/233 (97.4%)

Altered numbers /distribution (n=172) 172/233 (73.8%)

Total (n=233) 233/233 (100%)

Conventional vs reference data base interpretation


Principal component analysis


Rationale for using automation for the analysis of the EuroFlow LST

Classical expert-based manual gating strategies for interpreting flow cytometry data

depend on individual expertise ( = subjectivity)

Manual analysis strategies used by (individual) experts based on each

individual cell population via bivariate dot plots are hardly reproducible

Need for simpler, less laborious, less time-consuming,

more reproducible gating strategies

Rationale for using automation for the analysis of the EuroFlow LST

Classical expert-based manual gating strategies for interpreting flow cytometry data

depend on individual expertise ( = subjectivity)

Manual analysis strategies used by (individual) experts based on each

individual cell population via bivariate dot plots are hardly reproducible

Need for simpler, less laborious, less time-consuming,

more reproducible gating strategies

For this purpose, the EuroFlow consortium has designed, constructed and

validated an automated gating and identification (AGI) strategy, based on:

i) Clustering techniques to define groups of events in a sample

ii) A data base comparison step, to (objectively) classify each individual group of events in

a sample against pre-defined cell populations in a data base (matched for sample type,

antibody panel, age and/or disease condition)

EuroFlow LST PB data base construction

Key steps:

Flores-Montero J et al. J Immunol Methods. 2019 Dec;475:112662

1. Selection / Staining and acquisition of normal-

reactive samples

2. Inspection of technical quality

3. Check for biological and/or technical outliers

4. Analysis and identification of all cell populations in

the sample

5. Samples incorporation to the data base

6. Prospective validation

EuroFlow LST PB data base construction

Key steps:

LST sample selected (n=119)

QC check for technical and

biologic variables (n=73)

Samples included in

the data base (n=46)



reactive samples




the sample



EuroFlow LST data base construction

Key steps: Gating strategy for normal PB populations



reactive samples




the sample




Key steps:



reactive samples




the sample




Key steps: Tumor cell populations

Normal (residual) cell populations

% c

ells

manu

al ana

lysis

% cells AGI

% cells AGIFlores-Montero J et al. J Immunol Methods. 2019 Dec;475:112662


reactive samples




the sample



% c

ells

manu

al ana

lysis

EuroFlow LST AGI data base

LST data base(s) requirements:

• Mature aberrant lymphocytes can

infiltrate various tissues

• Peripheral blood

• Bone marrow

• Lymph node

• Other fluids

• Wide range of patients’ age:

• Normal <-> reactive <-> clonal

• Boarder variability in:

• Lymphoid cell (sub) populations presence

and distribution


EuroFlow automated analysis LST data bases

Automated analysis LST in PB sample

File selection


Data base selection

Automated gaiting & identification (AGI) process

Clustering

Classification

Output

Evaluation of CHKs

Reporting


AGI output

12%


After evaluation of CHKs


Report

EuroFlow Automated analysis in CLPD (LST)

Concluding remarks

Automated analysis is a robust and accurate tool to

support cytometrists in the diagnosis and classification of

CLPD which contributes to the systematic, more

standardized and fast analysis and reporting

Clinical questions


2nd step: ASSESSMENT OF CLONALITY



Clonality assessment for T-CLPD

Langerak et al, Blood 2001; Van Dongen et al, Leukemia 2003; Langerak et al, Leukemia 2012

TCRVβ repertoire by FCM

Expensive

Labor-intense

Difficult to interpret

Limited sensitivity

Restricted diversity of TCRγ

Complex

Lack of clone quantification or Immunophenotypic characterization

High levels of background noise amplification

(requiring sorting of the suspicious clonal cell population)

Not available in many laboratories

Molecular clonality by PCR

Aberrant TCD8+ cells

100% Vb13.2+

Normal TCD8+ cells

Limitations / disadvantages

Limitations / disadvantages

Not available in many laboratories

T-cell receptor β chain constant region (TRBC1) reagent

Tunnacliffe et al, Proc. Natl. Acad. Sci. 1985; Shi et al, Cytom. Part B 2020; Horna et al, Int. J. Mol. Sci. 2021

Anti-TRBC1:

• Against one of two mutually exclusive TRBC genes

• Randomly selected during TCR gene rearrangement

Flow cytometry TRBC1 marker (clone JOVI-1):A. Normal and virus-specific (“reactive”) Tαβ-cells: polytypic TRBC1 expression

B. Monoclonal Tαβ-CLPD: monotypic TRBC1 expression

CD4+ Tαβ-cells

37-51%

CD8+ Tαβ-cells

36-52%

Clonal

Tαβ-cells

TRBC1-

Clonal

Tαβ-cells

TRBC1+

Clonal

Tαβ-cells

TRBC1lo

A B

FCM-based clonality assay for T-CLPD

OBJECTIVES

1.- To optimize a flow cytometric method for routine use of anti-

TRBC1 to assess T-cell clonality

2.- To validate it in a large series of normal and pathological

samples

• TRBC1-expression of normal Tαβ-cells and Tαβ-cell subsets

(ranges for normality)

• Evaluation of specificity and sensitivity for detection of clonal

Tαβ-cells present at minimal disease levels

0 20 40 60 80 100

CD3 - 10’ - TRBC1

CD3 + TRBC1

TRBC1 - 10’ - CD3

Without CD3TRBC1 only

TRBC1 10’

and then CD3

CD3 + TRBC1

CD3 10’ and

then TRBC1

0 20 40 60 80 100

CD3 - 10’ - TRBC1

CD3 + TRBC1

TRBC1 - 10’ - CD3

Without CD3

% TRBC1+

0 10 20 30 40

CD3 10’ and then TRBC1

CD3 + TRBC1

TRBC1 10’ and then CD3

TRBC1 only

0 10 20 30 40

CD3 10’ and then TRBC1

CD3 + TRBC1

TRBC1 10’ and then CD3

TRBC1 only

TRBC1 Stain Index

*

*

* p≤0.05 vs TRBC1 only

# p≤0.05 vs CD3 10’ and then TRBC1

#

#

TRBC1 only

TRBC1 10’

and then CD3

CD3 + TRBC1

CD3 10’ and

then TRBC1

Optimization of the approach

% TRBC1+ of Tαβ cells TRBC1 Stain Index on Tαβ cells

TRBC1 labeling significantly improved in the presence of CD3; the best resolution to identify

TRBC1+ cells was achieved by adding CD3 either simultaneously or after TRBC1

○ TRBC1 in BV421

X CD3-APC (SK7)

X CD3-APC (REA613)

X CD3-APC (UCHT1)

∆ TRBC1 in FITC

X CD3-PECy7 (SK7)

X CD3-PEVio770

(REA613)

X Any CD3 reagent

Sta

inin

g c

ondit

ions

Sta

inin

g c

ondit

ions

Optimization and validation of the TRBC1-FCM approach for detecting

clonal Tαβ-cells (n=211 normal, reactive and pathological samples)

Muñoz-García N et al, Cancers (Basel). 2021;13:4379, on behalf of EuroFlow

Optimization and validation of the TRBC1-FCM approach for detecting clonal Tαβ-cells

(n=211 normal, reactive and pathological samples)

Muñoz-García N et al, Cancers (Basel). 2021;13:4379

Ranges for Polyclonal (Normal and Reactive) Tαβ-Cells and Major Tαβ-Cell Populations

Tαβ-cell

subset

% TRBC1+ cells* TRBC1+/TRBC1- ratio Probability (%) of Finding A Clonal

Tαβ Expansion When

TRBC1+/TRBC1− Ratio is Outside the

Range Mean ± 3 SD

(ρ-Value)

Mean ± 1 SD Range

(Mean ± 3 SD) Mean ± 1 SD

Range

(Mean ± 3 SD)

Tαβ cells 40 ± 6.7 20–60 0.66 ± 0.071 0.25–1.4

99.73%

(<0.001)

Tαβ CD4+ 43 ± 6.3 24–62 0.75 ± 0.067 0.31–1.6

Tαβ CD8+ 35 ± 8.8 8.3–61 0.53 ± 0.096 0.091–1.6

Tαβ DP 36 ± 12 1.6–71 0.57 ± 0.13 0.016–2.5

Tαβ DN 29 ± 10 0-61 0.41 ± 0.12 0–1.5

Bimodal distribution of TRBC1 for every TCRVβ subset of polyclonal Tαβ-cellsMore mature stages of Tαβ-cells were outside the normal

range of TRBC1+/TRBC1- ratio observed for total Tαβ-cells

Optimization and validation of the TRBC1-FCM approach for detecting clonal Tαβ-cells

(n=211 normal, reactive and pathological samples)

Muñoz-García N et al, Cancers (Basel). 2021;13:4379

TRBC1-FCM Assay vs. TCRVβ-FCM and/or Molecular

Techniques for Assessment of Tαβ-Cell Clonality

Sensitivity of TRBC1-FCM assay for Detection

of Clonal Tαβ-Cells

Serial dilutional experiments

(of PB pathological Tαβ cells in normal blood cells)

Sensitivity level for detecting clonal Tαβ cells

(identified among cells displaying an aberrant/suspicious

phenotype) was of at least 10-4 in 7/8 T-CLPD cases tested

112/117 (96%) concordance

Clonality status by other

techniques

TRBC1 expression pattern

P-valuePolytypic

(n=23)

Monotypic

(n=94)

Poly/oligoclonal

(n=24)21/24 (87%) 3/24 (13%)

<0.0001Monoclonal

(n=93)2/93 (2%) 91/93 (98%)

REMARKS AND CONCLUSIONS

• The optimal TRBC1 staining is achieved when CD3 antibody is added (not

before TRBC1)

• High specificity: 96% with TRBJ gene rearrangement / with other

conventional clonality techniques

• Sensitivity level of at least 10-4 can be reached in combination with

aberrant phenotype (which improves when combined with TCRVβ)

The TRBC1 approach in is a useful, simple and fast FCM assay for Tαβ-cell

clonality assessment in patients with suspicious T-CLPD

When used in combination with aberrant phenotypes, the approach has

high specificity and sensitivity

TRBC1-FCM approach for detecting clonal Tαβ-cells

Next future

• Implementation of anti-TRBC1 in screening, diagnostic and MRD panels

for the study of T-CLPD

• To built appropiate reference databases for automated análisis (i.e. LST

including both B-cell and T-cell clonality markers)

Immunophenotypic identification of Sézary cells in blood:

additional value of a T-cell clonality marker (TRBC1)

#OPO-2100462

CD4 CD7 CD26CD7

CD

3

CD

26

CD3

CD

279 (

PD

-1)

Sézary cells

Normal

(residual)

CD4+ T cells

CD8+ T cells

CD

2

CD

28

Sézary cells

Normal (residual)

CD4+ T cells

CD8+ T cells

TCR-Cb1TCR-Cb1 (TRBC1)

CD

279 (

PD

-1)

Participants: Neus Villamor (UB, Barcelona, Spain), Paula Fernández (KSA, Aarau, Switzerland), Matthias Ritgen(University of Schleswig-Holstein, Kiel, Germany),

Anton W Langerak (Erasmus MC, RT, The Netherlands)

Classification and monitoring of T/NK-CLPD (WP L&L-10)WP Leaders: Julia Almeida (USAL, Spain) and Margarida Lima (CHP Porto, Portugal)

EuroFlow Leaders: Jacques van Dongen and Alberto Orfao

análisis automático. estudio inicial (lst) y clasificación

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