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Related Concept Videos

Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

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Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
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Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
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Cancer-Critical Genes I: Proto-oncogenes01:33

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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
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Cancer-Critical Genes II: Tumor Suppressor Genes01:05

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Adaptive Mechanisms in Cancer Cells02:53

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Cancer cells accumulate genetic changes at an abnormally rapid rate due to the defects in the DNA repair mechanisms. From an evolutionary perspective, such genetic instability is advantageous for cancer development. Mutant cell lines accumulate a series of beneficial mutations that contribute to their progression into cancer.
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Cancer02:18

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Cancers arise due to mutations in genes involved in the regulation of cell division, which leads to unrestricted cell proliferation. Modern science and medicine have made great strides in the understanding and treatment of cancer, including eradicating cancer in some patients. However, there is still no cure for cancer. This is largely due to the fact that cancer is a large group of many diseases.
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Updated: Mar 1, 2026

Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
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Concurrent driver mutations induce distinct tumour morphologies on radiological imaging.

Diana Ivonne Rodríguez Sánchez1, Thera Vanneste2, Julian Middelkoop2

  • 1GROW Research Institute for Oncology and Reproduction, Maastricht University, Maastricht, The Netherlands; Department of Radiology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.

European Journal of Radiology
|February 27, 2026
PubMed
Summary
This summary is machine-generated.

Cancer co-mutations create unique imaging phenotypes distinct from single mutations, revealing complex tumor biology. Radiogenomics must explicitly model these co-mutation contexts for accurate non-invasive cancer stratification.

Keywords:
Artificial IntelligenceCo-mutationsComputed TomographyEGFRKRASPrecision OncologyRadiogenomicsRadiomicsTP53Tumour Morphology

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Area of Science:

  • Radiogenomics
  • Cancer Genomics
  • Medical Imaging

Background:

  • Most radiogenomic studies analyze single driver mutations in isolation.
  • Co-occurring driver alterations are common in cancer and can interact functionally.
  • It remains unknown if concurrent mutations create distinct imaging phenotypes or simply average single-mutation effects.

Purpose of the Study:

  • To investigate whether co-occurring driver mutations in cancer patients result in distinct imaging phenotypes compared to single mutations.
  • To determine if concurrent mutations produce additive or emergent effects on imaging characteristics.
  • To explore the utility of radiomics in identifying genotype-specific phenotypes in a multi-cancer cohort.

Main Methods:

  • Retrospective analysis of 1235 patients with 8633 segmented lesions from contrast-enhanced CT scans and matched genomic profiling.
  • Comparison of imaging phenotypes across patient groups: no driver mutations, TP53 + other, TP53-only, EGFR-only, KRAS-only, and specific co-mutations (TP53 + EGFR, TP53 + KRAS).
  • Quantification of phenotypic separation using centroid distance and cross-group inter-patient distance, with lesion-level dimensionality reduction and parental-axis geometry analysis to test for emergence beyond additivity.

Main Results:

  • Single-mutant cohorts (EGFR-only vs. KRAS-only, TP53-only vs. EGFR-only) exhibited distinct phenotypes.
  • Co-mutated tumors demonstrated separation from single-mutant parent groups in both patient-level and lesion-level analyses.
  • Co-mutated lesions were morphologically closer to TP53-only cohorts than to EGFR-only or KRAS-only cohorts.
  • Emergence beyond additivity was statistically supported for TP53 + EGFR co-mutations and trended for TP53 + KRAS.

Conclusions:

  • CT radiomics can identify genotype-specific phenotypes across various cancers.
  • Co-mutations generate distinct morphological characteristics detectable via imaging.
  • Explicit modeling of co-mutation context is crucial for advancing radiogenomics and enabling non-invasive molecular stratification of cancer.