Evidence map›Paper›PMID 41413116›Full record

ArticleScientific reports2025

Single cell RNAseq signatures refined with combiroc enhance identification of NK cells in blood and solid tissues.

Ivan Ferrari, Saveria Mazzara, Andrea Gobbini, Noemi Di Marzo, Mariacristina Crosti, Sergio Abrignani, Renata Grifantini, Mauro Bombaci, Riccardo L Rossi

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Ivan FerrariIstituto Nazionale Genetica Molecolare "Romeo ed Enrica Invernizzi", Milan, Italy.
Saveria MazzaraDepartment of Computing Sciences, Bocconi Institute for Data Science and Analytics (BIDSA), Bocconi University, Milan, Italy.
Andrea GobbiniIstituto Nazionale Genetica Molecolare "Romeo ed Enrica Invernizzi", Milan, Italy.
Noemi Di MarzoCheckmAb Srl, Milan, Italy.
Mariacristina CrostiIstituto Nazionale Genetica Molecolare "Romeo ed Enrica Invernizzi", Milan, Italy.
Sergio AbrignaniIstituto Nazionale Genetica Molecolare "Romeo ed Enrica Invernizzi", Milan, Italy.
Renata GrifantiniIstituto Nazionale Genetica Molecolare "Romeo ed Enrica Invernizzi", Milan, Italy.
Mauro BombaciIstituto Nazionale Genetica Molecolare "Romeo ed Enrica Invernizzi", Milan, Italy. maurobombaci@gmail.com.
Riccardo L RossiIstituto Nazionale Genetica Molecolare "Romeo ed Enrica Invernizzi", Milan, Italy. riccardo.rossi@ifom.eu.

Funding

European Research Council 772970 to F. BuffaFondazione Romeo ed Enrica Invernizzi Institutional grantHORIZON EUROPE European Research Council 101191725NextGenerationEU PE00000007Regione Lombardia COiMMUNITY (ID 1842163)Regione Lombardia MAINSTREAM (ID 1835032)
6 · The paper itself

Abstract

Cytotoxic CD8 T lymphocytes (CTLs) and natural killer (NK) cells share the common objective of controlling infections and detecting and removing tumor cells, albeit through distinct target recognition mechanisms. Although CTLs belong to the adaptive immune system and NK cells are innate lymphoid cells, they frequently exhibit considerable overlap in their molecular phenotypes. This overlap, as with many others in cell biology, poses challenges for distinguishing cells in the context of single cell transcriptomics. Building on a previous ROC-driven combinatorial approach, we developed a new computational framework for single-cell RNA-seq with the combiroc R package, and in this study we showed that it can identify non-canonical marker combinations for NK cells in Peripheral Blood Mononuclear Cell datasets. These combinatorial markers were in line with the Human Protein Atlas and we validated them through cytometry staining and functional assays. Markers selected with combiroc exhibit exceptional discriminatory power for identifying NK cells, both in blood and solid tumoral tissues. Besides this finding, we showed that our approach vastly optimizes standard differential expression signatures: it reduces dimensionality while improving interpretability and transferability to diagnostic applications, offering a practical solution for refining immune cell identities in complex transcriptomic datasets.

Indexed as

Killer Cells, NaturalRNA-SeqSingle-Cell AnalysisGene Expression ProfilingHumansSingle-Cell Gene Expression AnalysisSoftwareTranscriptomeBiomarkersCombinatoricsGene signaturesPhenotype overlapR packagescRNA-seq

Identifiers

PMID41413116
PMCPMC12769544

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