Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Computational quantification and characterization of independently evolving cellular subpopulations within tumors is critical to inhibit anti-cancer therapy resistance

20 Oct 2022

Abstract excerpt

BACKGROUND: Drug resistance continues to be a major limiting factor across diverse anti-cancer therapies. Contributing to the complexity of this challenge is cancer plasticity, in which one cancer subtype switches to another in response to treatment, for example, triple-negative breast cancer (TNBC) to Her2-positive breast cancer. For optimal treatment outcomes, accurate tumor diagnosis and subsequent therapeutic...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cancer Cells and Metastasis
Share to Cancer Immunotherapy and Biomarkers
Share to Single-cell and spatial transcriptomics

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 36266692
DOI: 10.1186/s13073-022-01121-y

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Computational quantification and characterization of independently evolving cellular subpopulations within tumors is critical to inhibit anti-cancer therapy resistancePMID 36266692Read ↗

A Multimodal Framework to Uncover Drug-Responsive Subpopulations in Triple-Negative Breast CancerSemantic proximity Read ↗

Single-cell decoding of drug induced transcriptomic reprogramming in triple negative breast cancersSemantic proximity Read ↗

Deciphering intratumoral heterogeneity using integrated clonal tracking and single-cell transcriptome analysesSemantic proximity Read ↗

Single cell lineage tracing reveals clonal dynamics of anti-EGFR therapy resistance in triple negative breast cancerSemantic proximity Read ↗

Novel computational method for predicting polytherapy switching strategies to overcome tumor heterogeneity and evolutionSemantic proximity Read ↗

Integrating multimodal data sets into a mathematical framework to describe and predict therapeutic resistance in cancerSemantic proximity Read ↗

Spatial Agent-Based Modeling and Interpretable Machine Learning Predict Combination Therapy Response in HER2-Heterogeneous Breast CancerSemantic proximity Read ↗

Chemotherapy reshapes cellular clonal landscape via persister programs in breast cancer xenograftsSemantic proximity Read ↗

Single-cell profiling guided combinatorial immunotherapy for fast-evolving CDK4/6 inhibitor resistant HER2-positive breast cancerSemantic proximity Read ↗

Phenotypic deconvolution in heterogeneous cancer cell populations using drug screening dataSemantic proximity Read ↗

Dissection of triple-negative breast cancer microenvironment and identification of potential therapeutic drugs using single-cell RNA sequencing analysisSemantic proximity Read ↗

Deciphering intratumoral heterogeneity using integrated clonal tracking and single-cell transcriptome analysesSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.