Evidence map›Paper›PMID 42794980›Full record

ReviewCancers2026

The Evolution of Fitness Landscapes: From Visualizing Evolution to Controlling It.

Meaghan Elizabeth Parks, Peng Chen, Jinling Wu, Jacob G Scott

Abstract readReview
In one paragraph

Review in Cancers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Meaghan Elizabeth ParksGenomic Sciences and Systems Biology, Cleveland Clinic Research, Cleveland, OH 44106, USA.ORCID 0000-0002-6488-7056
Peng ChenGenomic Sciences and Systems Biology, Cleveland Clinic Research, Cleveland, OH 44106, USA.ORCID 0009-0005-4820-914X
Jinling WuGenomic Sciences and Systems Biology, Cleveland Clinic Research, Cleveland, OH 44106, USA.ORCID 0009-0009-1553-0921
Jacob G ScottGenomic Sciences and Systems Biology, Cleveland Clinic Research, Cleveland, OH 44106, USA.ORCID 0000-0003-2971-7673

Funding

Exploiting Ecology and Evolution to Prevent Therapy Resistance in EGFR-Driven Lung CancerR37CA244613 · NCI · CLEVELAND CLINIC LERNER COM-CWRU · PI Jacob Gardinier Scott · 2020 to 2026
$4.0M
Tumor-barcoding coupled with high-throughput sequencing for quantitative radiogenomics of the abscopal response in NSCLCR01CA271540 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Phuoc T. Tran · 2023 to 2026
$2.3M
NCI NIH HHS R01 CA271540NCI NIH HHS R01CA271540NCI NIH HHS R37 CA244613NIH HHS 5R37CA244613-02
6 · The paper itself

Abstract

Fitness landscapes have long served as a conceptual tool in evolutionary biology. In recent years, however, they have shifted from being viewed primarily as theoretical constructs to being used to interpret experimental data and, increasingly, to guide evolutionary outcomes in biomedical systems. In this review, we trace that progression across major landscape formalisms, including Fisher's geometric model, Wright's adaptive landscape, fitness seascapes, and empirical fitness landscapes. We aim to highlight the strengths of each model and its potential for use in cancer research. Rather than treating these frameworks as isolated models, we show how they collectively reflect the field's maturation: from describing adaptation in idealized settings to quantifying epistasis and evolutionary accessibility, to interpreting experimental genotype-fitness data, and finally to motivating strategies for steering evolution in contexts such as treatment resistance in cancer. We argue that the central promise of the fitness landscape framework now lies not only in explaining evolutionary dynamics, but also in enabling predictive interventions and overcoming cancer evolution.

Indexed as

evolutionary controlFisher’s geometric modelfitness landscape

Identifiers

PMID42794980
PMCPMC13604621

What OpenQuestion holds

Textmetadata
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.