The present tool has
been developed to translate RT-qPCR data from routine clinical samples
as a new approach to objectively distinguish ALK negative ALCL from
PTCL-NOS, as described in "Identification
of a three-gene model as a powerful
diagnostic tool for the recognition of ALK negative ALCL"
by Agnelli L et al.
Abstract
Anaplastic Large Cell
Lymphomas (ALCL) are a clinically
and biologically heterogeneous disease including the ALK+ and ALK-
systemic forms. While ALK+ ALCL are molecularly characterized and can
be readily diagnosed, specific immunophenotypic or genetic features to
define ALK- ALCL are missing, and their distinction from other T-Cell
Non-Hodgkin Lymphomas (T-NHL) remains controversial. We undertook a
systematic approach to profile the expression signature of a large set
of primary T-NHL, and defined a minimum set of genes useful for the
stratification of ALK- ALCL. Application of RT-qPCR in independent data
sets from cryo-preserved and
formalin-fixed paraffin embedded (FFPE) samples validated a three-gene
model (TNFRSF8,
BATF3, TMOD1)
able to
successfully separate ALK- ALCL
from PTCL-NOS, with an overall accuracy of 95.7%. Here, we provide a
web-based platform for the application of RT-qPCR protocols from
routine clinical settings, as a new approach to objectively dissect
T-NHL and to select more appropriate therapeutic protocols.
In the next form, insert the Ct values of the
indicated
genes,
according to the RT-qPCR protocol described in the paper;
then hit
"submit" button.
Contributed by:
Luca Agnelli, Elisabetta Mereu, Elisa Pellegrino, Tania Limongi, Ivo
Kwee, Maurilio Ponzoni, Alberto Zamò, Javeed Iqbal, Pier
Paolo Piccaluga, Antonino Neri, John C Chan, Stefano Pileri, Francesco
Bertoni, Giorgio Inghirami, Roberto Piva, on behalf of the European
T-Cell Lymphoma Study Group, from: Department of Medical
Sciences, University of Milan, Italy; Department of Pathology
and Center for Experimental Research and Medical Studies (CeRMS),
University of Torino, Italy; Institute of Oncology Research (IOR),
Bellinzona, Switzerland; Dalle Molle Institute for Artificial
Intelligence (IDSIA), Manno, Switzerland; Pathology & Lymphoid
Malignancies Units, San Raffaele Scientific Institute, Milan, Italy;
Department of Pathology, University of Verona, Verona, Italy;
Department of Pathology and Microbiology, University of Nebraska
Medical Center, Omaha, NE, USA; Institute of Hematology and Medical
Oncology, S. Orsola-Malpighi Hospital, University of Bologna, Italy;
Oncology Institute of Southern Switzerland (IOSI), Bellinzona,
Switzerland; and Department of Pathology and NYU Cancer Center, New
York University School of Medicine, New York, NY, USA.
This page powered by: Luca Agnelli