Evidence map›Paper›PMID 42711452›Full record

ReviewNature reviews. Cancer2026

A single-cell lens into the co-evolution of genotypes and phenotypes in cancer.

Franco Izzo, Tamara Prieto, Catherine Potenski, Dan A Landau

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Cancer, 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.

Franco IzzoIcahn School of Medicine at Mount Sinai, Department of Oncological Sciences, New York, NY, USA.
Tamara PrietoDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.ORCID http://orcid.org/0000-0002-1181-9156
Catherine PotenskiDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
Dan A LandauDivision of Hematology and Medical Oncology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA. dlandau@nygenome.org.ORCID http://orcid.org/0000-0003-2346-9541

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic heterogeneity and clonal outgrowths are observed even in otherwise healthy human tissues, shaping the genetic composition of cell populations in non-malignant disease and during physiological ageing. This clonal mosaicism likely provides the pre-cancerous seeds for malignant transformation. Once a tumour arises, clonal evolution poses a major challenge to achieving cure, as clonal diversification provides an expanded number of substrates upon which therapy can act as a selective pressure, leading to the selection of resistant clones that ultimately fuel disease recurrence. Understanding somatic clonal evolution requires not only mapping genetic diversity but also defining the resulting phenotypes that provide a fitness advantage to mutated clones. This Review discusses multimodal single-cell technologies that enable the measurement of genotypes and additional molecular features from the same cell. These technologies unveil mutant-specific phenotypic traits, often show cell-state specificity in genotype-phenotype effects and can define therapeutic vulnerabilities for precision elimination of disease-propagating mutant cells. Furthermore, the combination of phylogenetic reconstruction with phenotypic measurements allows for the temporal mapping of clonal evolution and phenotypic plasticity. These breakthroughs have created a unique opportunity to define, directly in primary human samples, the mechanisms underlying clonal expansion in both healthy and malignant tissues.

Identifiers

PMID42711452

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.