Evidence map›Paper›PMID 38848164›Full record

ReviewThe oncologist2024

Understanding variants of unknown significance: the computational frontier.

Xi Fu, Raul Rabadan

Abstract readReview
In one paragraph

Review in The oncologist, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Xi FuColumbia University Irving Medical Center, New York, NY, USA.ORCID 0000-0001-9835-5018
Raul RabadanColumbia University Irving Medical Center, New York, NY, USA.ORCID 0000-0001-7946-9255

Funding

The Role of CTIP in Lymphocyte Development and LymphomagenesisP01CA174653 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GAUTIER, JEAN · 2014 to 2024
$17.6M
Towards a quantitative understanding of tumor evolutionR35CA253126 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Raul Rabadan · 2021 to 2026
$5.6M
Single-cell characterization of tumor and microenvironment co-evolution in Peripheral T-cell LymphomasU01CA243073 · NCI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI PALOMERO, TERESA, RABADAN, RAUL · 2019 to 2023
$3.0M
NCI NIH HHS P01 CA174653NCI NIH HHS R35 CA253126NCI NIH HHS U01 CA243073NIH HHS R35 CA253126
6 · The paper itself

Abstract

The rapid advancement of sequencing technologies has led to the identification of numerous mutations in cancer genomes, many of which are variants of unknown significance (VUS). Computational models are increasingly being used to predict the functional impact of these mutations, in both coding and noncoding regions. Integration of these models with emerging genomic datasets will refine our understanding of mutation effects and guide clinical decision making. Future advancements in modeling protein interactions and transcriptional regulation will further enhance our ability to interpret VUS. Periodic incorporation of these developments into VUS reclassification practice has the potential to significantly improve personalized cancer care.

Indexed as

NeoplasmsComputational BiologyGenetic VariationGenomicsHumansMutationcancer genomicscomputational biologymachine learningsomatic variants

Identifiers

PMID38848164
PMCPMC11299926

What OpenQuestion holds

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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.