Evidence map›Paper›PMID 33396205›Full record

ArticleCells2020

Pan-Cancer Molecular Patterns and Biological Implications Associated with a Tumor-Specific Molecular Signature.

Darío Rocha, Iris A García, Aldana González Montoro, Andrea Llera, Laura Prato, María R Girotti, Gastón Soria, Elmer A Fernández

Abstract read
In one paragraph

Article in Cells, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. NF-YAl drives EMT in ClaudinCell death & disease · 2023
    Article
  3. Article
  4. Article
  5. Multi-Omics Model Applied to Cancer Genetics.International journal of molecular sciences · 2021
    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

8 authors.

Darío RochaFacultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba X5000HUA, Argentina.
Iris A GarcíaCentro de Investigación y Desarrollo en Inmunología y Enfermedades Infecciosas, Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad Católica de Córdoba, Córdoba X5016DHK, Argentina.
Aldana González MontoroFacultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba X5000HUA, Argentina.
Andrea LleraLaboratorio de Terapia Molecular y Celular-Genocan, Fundación Instituto Leloir, Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires C1405BWE, Argentina.ORCID 0000-0002-0089-0061
Laura PratoInstituto Académico Pedagógico de Ciencias Básicas y Aplicadas, Universidad Nacional de Villa María, Villa María, Córdoba X5900, Argentina.
María R GirottiLaboratorio de Inmuno Oncología Traslacional, Instituto de Biología y Medicina Experimental, Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires C1428ADN, Argentina.
Gastón SoriaDepartamento de Bioquímica Clínica, Facultad de Ciencias Químicas, Universidad Nacional de Córdoba, Córdoba X5000HUA, Argentina.ORCID 0000-0003-2177-5094
Elmer A FernándezFacultad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba X5000HUA, Argentina.ORCID 0000-0002-4711-8634

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studying tissue-independent components of cancer and defining pan-cancer subtypes could be addressed using tissue-specific molecular signatures if classification errors are controlled. Since PAM50 is a well-known, United States Food and Drug Administration (FDA)-approved and commercially available breast cancer signature, we applied it with uncertainty assessment to classify tumor samples from over 33 cancer types, discarded unassigned samples, and studied the emerging tumor-agnostic molecular patterns. The percentage of unassigned samples ranged between 55.5% and 86.9% in non-breast tissues, and gene set analysis suggested that the remaining samples could be grouped into two classes (named C1 and C2) regardless of the tissue. The C2 class was more dedifferentiated, more proliferative, with higher centrosome amplification, and potentially more TP53 and RB1 mutations. We identified 28 gene sets and 95 genes mainly associated with cell-cycle progression, cell-cycle checkpoints, and DNA damage that were consistently exacerbated in the C2 class. In some cancer types, the C1/C2 classification was associated with survival and drug sensitivity, and modulated the prognostic meaning of the immune infiltrate. Our results suggest that PAM50 could be repurposed for a pan-cancer context when paired with uncertainty assessment, resulting in two classes with molecular, biological, and clinical implications.

Indexed as

AlgorithmsBiomarkers, TumorBreast NeoplasmsCell Cycle CheckpointsCell DifferentiationCell Line, TumorCell ProliferationCentrosomeCohort StudiesDatabases, GeneticDNA DamageEmbryonic Stem CellsErb-b2 Receptor Tyrosine KinasesGene Expression ProfilingGene Expression Regulation, NeoplasticHumansBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesMembrane ProteinsRB1 protein, humanRetinoblastoma Binding ProteinsTmem43 protein, mouseTP53 protein, humanTumor Suppressor Protein p53Ubiquitin-Protein Ligasescell-cyclegene expressionPAM50tumor-agnostic classificationuncertainty assessment

Identifiers

PMID33396205
PMCPMC7823585

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Registered trials

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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.