Evidence map›Paper›PMID 34063805›Full record

ReviewInternational journal of molecular sciences2021

Analysis and Interpretation of the Impact of Missense Variants in Cancer.

Maria Petrosino, Leonore Novak, Alessandra Pasquo, Roberta Chiaraluce, Paola Turina, Emidio Capriotti, Valerio Consalvi

Open access · goldAbstract readReview
In one paragraph

Review in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 1 pooled it
9.4field-weighted citation impact, top 2% of its field
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

50 citing papers in PubMed, 1 synthesis or guideline pooled it, 78 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Cancer-associated TRF1 mutations alter PARP1 interaction dynamics: an in silico study.Mammalian genome : official journal of the International Mammalian Genome Society · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Molecular Consequences ofInternational journal of molecular sciences · 2025
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Mass balance approximation of unfolding boosts potential-based protein stability predictions.Protein science : a publication of the Protein Society · 2025
    Article
  17. Article
  18. Article
  19. Comprehensive computational analysis of deleterious nsSNPs inMolecular biology research communications · 2025
    Article
  20. Article
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

7 authors at 3 institutions in 1 country.

Maria PetrosinoDipartimento Scienze Biochimiche "A. Rossi Fanelli", Sapienza University of Rome, 00185 Roma, Italy.ORCID 0000-0001-7875-5954
Leonore NovakDipartimento Scienze Biochimiche "A. Rossi Fanelli", Sapienza University of Rome, 00185 Roma, Italy.
Alessandra PasquoENEA CR Frascati, Diagnostics and Metrology Laboratory FSN-TECFIS-DIM, 00044 Frascati, Italy.
Roberta ChiaraluceDipartimento Scienze Biochimiche "A. Rossi Fanelli", Sapienza University of Rome, 00185 Roma, Italy.ORCID 0000-0001-7748-2237
Paola TurinaDipartimento di Farmacia e Biotecnologie (FaBiT), University of Bologna, 40126 Bologna, Italy.ORCID 0000-0001-9174-511X
Emidio CapriottiDipartimento di Farmacia e Biotecnologie (FaBiT), University of Bologna, 40126 Bologna, Italy.
Valerio ConsalviDipartimento Scienze Biochimiche "A. Rossi Fanelli", Sapienza University of Rome, 00185 Roma, Italy.
Sapienza University of Rome · ITUniversity of Bologna · ITNational Agency for New Technologies, Energy and Sustainable Economic Development · IT

Funding

Ministero Istruzione, Università e Ricerca, PRIN project, "Integrative tools for defining the molecular basis of the diseases: Computational and Experimental methods for Protein Variant Interpretation" 201744NR8S
6 · The paper itself

Abstract

Large scale genome sequencing allowed the identification of a massive number of genetic variations, whose impact on human health is still unknown. In this review we analyze, by an in silico-based strategy, the impact of missense variants on cancer-related genes, whose effect on protein stability and function was experimentally determined. We collected a set of 164 variants from 11 proteins to analyze the impact of missense mutations at structural and functional levels, and to assess the performance of state-of-the-art methods (FoldX and Meta-SNP) for predicting protein stability change and pathogenicity. The result of our analysis shows that a combination of experimental data on protein stability and in silico pathogenicity predictions allowed the identification of a subset of variants with a high probability of having a deleterious phenotypic effect, as confirmed by the significant enrichment of the subset in variants annotated in the COSMIC database as putative cancer-driving variants. Our analysis suggests that the integration of experimental and computational approaches may contribute to evaluate the risk for complex disorders and develop more effective treatment strategies.

Indexed as

Computational BiologyComputer SimulationHumansMutation, MissenseNeoplasmsProteinsProtein StabilityProteinsfree-energy changeprotein functionprotein stabilityprotein structureputative cancer driving variantsingle amino acid variant

Identifiers

PMID34063805
PMCPMC8196604
OpenAlexW3165327420

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.