Evidence map›Paper›PMID 33589521›Full record

Observational studyJournal for immunotherapy of cancer2021

Back to simplicity: a four-marker blood cell score to quantify prognostically relevant myeloid cells in melanoma patients.

Veronica Huber, Lorenza Di Guardo, Luca Lalli, Daniele Giardiello, Agata Cova, Paola Squarcina, Paola Frati, Anna Maria Di Giacomo, Lorenzo Pilla, Marcella Tazzari and 11 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Journal for immunotherapy of cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Review
  6. Development of a Molecular Blood-Based Immune Signature Classifier as Biomarker for Risks Assessment in Lung Cancer Screening.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2022
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
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

21 authors.

Veronica HuberUnit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy veronica.huber@istitutotumori.mi.it.ORCID 0000-0001-6304-3575
Lorenza Di GuardoDepartment of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Luca LalliUnit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Daniele GiardielloUnit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Agata CovaUnit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Paola SquarcinaUnit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Paola FratiUnit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Anna Maria Di GiacomoCenter for Immuno-Oncology, University Hospital of Siena, Siena, Italy.
Lorenzo PillaUnit of Immuno-biotherapy of Melanoma and Solid Tumors, IRCCS San Raffaele Hospital, Milan, Italy.
Marcella TazzariImmunotherapy-Cell Therapy and Biobank Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", Meldola, Italy.ORCID 0000-0002-8112-1773
Chiara CamisaschiUnit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Flavio ArientiImmunohematology and Transfusion Medicine Service (SIMT), Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Chiara CastelliUnit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Monica RodolfoUnit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Valeria BerettaUnit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Massimo Di NicolaDepartment of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Michele MaioCenter for Immuno-Oncology, University Hospital of Siena, Siena, Italy.
Michele Del VecchioDepartment of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Filippo de BraudDepartment of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Luigi MarianiUnit of Clinical Epidemiology and Trial Organization, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.
Licia RivoltiniUnit of Immunotherapy of Human Tumors, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMyeloid-derived suppressor cells (MDSC), a cornerstone of cancer-related immunosuppression, influence response to therapy and disease outcomes in melanoma patients. Nevertheless, their quantification is far from being integrated into routine clinical practice mostly because of the complex and still evolving phenotypic signatures applied to define the cell subsets. Here, we used a multistep downsizing process to verify whether a core of few markers could be sufficient to capture the prognostic potential of myeloid cells in peripheral blood mononuclear cells (PBMC) of metastatic melanoma patients.

methodsIn baseline frozen PBMC from a total of 143 stage IIIc to IV melanoma patients, we first assessed the relevant or redundant expression of myeloid and MDSC-related markers by flow cytometry (screening set, n=23 patients). Subsequently, we applied the identified panel to the development set samples (n=59 patients undergoing first/second-line therapy) to obtain prognostic variables associated with overall survival (OS) and progression-free survival (PFS) by machine learning adaptive index modeling. Finally, the identified score was confirmed in a validation set (n=61) and compared with standard clinical prognostic factors to assess its additive value in patient prognostication.

resultsThis selection process led to the identification of what we defined myeloid index score (MIS), which is composed by four cell subsets (CD14

conclusionThe MIS >0 identifies melanoma patients with a more aggressive disease, thus acting as a simple blood biomarker that can help tailoring therapeutic choices in real-life oncology.

Indexed as

Biomarkers, TumorCase-Control StudiesHumansL-Lactate DehydrogenaseLymphocyte CountMachine LearningMelanomaMyeloid-Derived Suppressor CellsNeoplasm MetastasisNeutrophilsPrognosisSurvival AnalysisBiomarkers, TumorL-Lactate Dehydrogenaseimmune evasionimmunotherapymelanomamyeloid-derived suppressor cellstumor biomarkers

Identifiers

PMID33589521
PMCPMC7887358

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.