Evidence map›Paper›PMID 39540258›Full record

ArticleHematological oncology2024

CAT rs1001179 Single Nucleotide Polymorphism Identifies an Aggressive Clinical Behavior in Chronic Lymphocytic Leukemia.

Marilisa Galasso, Vittoria Salaorni, Riccardo Moia, Valentina Mozzo, Ester Lovato, Chiara Cosentino, Omar Perbellini, Simona Gambino, Ornella Lovato, Maria Elena Carazzolo and 8 more

Abstract read
In one paragraph

Article in Hematological oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Marilisa GalassoDepartment of Engineering for Innovation Medicine, Section of Biomedicine, University of Verona, Verona, Italy.ORCID https://orcid.org/0000-0003-3028-1205
Vittoria SalaorniDepartment of Diagnostics and Public Health, University of Verona, Verona, Italy.
Riccardo MoiaDepartment of Translational Medicine, Division of Hematology, University of Piemonte Orientale, Novara, Italy.ORCID https://orcid.org/0000-0001-7393-1138
Valentina MozzoVeneto Institute of Oncology IOV - IRCCS, Padova, Italy.
Ester LovatoDepartment of Engineering for Innovation Medicine, Section of Biomedicine, University of Verona, Verona, Italy.
Chiara CosentinoDepartment of Translational Medicine, Division of Hematology, University of Piemonte Orientale, Novara, Italy.
Omar PerbelliniUOC di Ematologia - Azienda ULSS 8 Berica, Vicenza, Italy.
Simona GambinoDepartment of Engineering for Innovation Medicine, Section of Biomedicine, University of Verona, Verona, Italy.
Ornella LovatoLaboratory of Medical Research, University of Verona, Verona, Italy.
Maria Elena CarazzoloDepartment of Medicine, University of Verona, Verona, Italy.
Isacco FerrariniDepartment of Engineering for Innovation Medicine, Section of Biomedicine, University of Verona, Verona, Italy.ORCID https://orcid.org/0000-0001-9867-8335
Francesca M QuagliaHematology Unit, Azienda Ospedaliera Universitaria Integrata Verona, Verona, Italy.
Massimo DonadelliDepartment of Neurosciences, Biomedicine and Movement Sciences, Section of Biochemistry, University of Verona, Verona, Italy.
Maria G RomanelliDepartment of Neurosciences, Biomedicine and Movement Sciences, Section Biology and Genetics, University of Verona, Verona, Italy.
Carlo ViscoDepartment of Engineering for Innovation Medicine, Section of Biomedicine, University of Verona, Verona, Italy.
Mauro KramperaDepartment of Engineering for Innovation Medicine, Section of Biomedicine, University of Verona, Verona, Italy.
Gianluca GaidanoDepartment of Translational Medicine, Division of Hematology, University of Piemonte Orientale, Novara, Italy.
Maria T ScupoliDepartment of Engineering for Innovation Medicine, Section of Biomedicine, University of Verona, Verona, Italy.

Funding

Associazione Italiana per la Ricerca sul Cancro Foundation Milan-5 x 1000 21198European Union PNRR PNC-E3-2022-23683266MUR
6 · The paper itself

Abstract

Chronic lymphocytic leukemia (CLL) is characterized by an extremely variable clinical course. Although several parameters have been shown to be associated with clinical outcomes in patients with CLL, there remains substantial intragroup clinical heterogeneity in otherwise molecularly and staging homogeneous CLL subgroups. We have recently shown that high catalase (CAT) expression identifies patients with an aggressive clinical course and that higher CAT expression is associated with the presence of the rs1001179 single nucleotide polymorphism (SNP) T allele in the CAT promoter. Herein, we genotyped CLL patients for CAT rs1001179 SNP in an exploratory study (n = 235) and in a sequential independent validation study (n = 531). Time-to-event modeling analyses for time-to-first-treatment (TTFT) from the two patients' cohorts showed that TT genotype was associated with a shorter TTFT, independently of other currently used prognostic parameters in CLL. Moreover, the TT genotype identifies CLL patients with a faster clinical progression even within subgroups of patients with low-risk biological and clinical hallmarks. In conclusion, our data show that the TT genotype identifies CLL patients with a shorter TTFT, pointing to this SNP as a possible prognostic factor, which can improve patients' risk stratification leading to better patient management and personalized therapeutic choices.

Indexed as

CatalaseLeukemia, Lymphocytic, Chronic, B-CellPolymorphism, Single NucleotideAdultAgedAged, 80 and overFemaleGenotypeHumansMaleMiddle AgedPrognosisCatalaseCAT protein, humancatalasechronic lymphocytic leukemiasingle nucleotide polymorphism

Identifiers

PMID39540258
PMCPMC11590045

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.