ReviewMolecular oncology2022
Bioinformatics roadmap for therapy selection in cancer genomics.
Review in Molecular oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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.
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.
Who cites it
19 citing papers in PubMed, 27 citations in OpenAlex.
- Article
- Omics and artificial intelligence integration for stratifying blast crisis CML using COSMIC signatures and pan-cancer precision drug repurposing.World journal of clinical oncology · 2025Article
- Neuropharmacological effects of calycosin: a translational review of molecular mechanisms and therapeutic applications.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- Ferroptosis-Linked Six-Gene Panel Enables Machine Learning-Assisted Diagnosis and Therapeutic Guidance in Lung Adenocarcinoma.Biology · 2025Article
- Harnessing technologies to unravel gastric cancer heterogeneity.Trends in cancer · 2025Review
- Unveiling the Therapeutic Potential of Targeting RRM2 in Hepatocellular Carcinoma: An Integrated In Silico and In Vitro Study.Functional & integrative genomics · 2025Article
- Interactions Between Non-Coding RNAs and HIF-1alpha in the Context of Colorectal Cancer.Biomolecules · 2025Review
- Review
- Bioinformatics-Driven Investigations of Signature Biomarkers for Triple-Negative Breast Cancer.Bioinformatics and biology insights · 2025Article
- Advancing precision oncology with AI-powered genomic analysis.Frontiers in pharmacology · 2025Review
- Spatial transcriptomics in breast cancer reveals tumour microenvironment-driven drug responses and clonal therapeutic heterogeneity.NAR cancer · 2024Article
- From Crypts to Cancer: A Holistic Perspective on Colorectal Carcinogenesis and Therapeutic Strategies.International journal of molecular sciences · 2024Review
- Clinical bioinformatics desiderata for molecular tumor boards.Briefings in bioinformatics · 2024Review
- Unraveling the Potential of Attentive Bi-LSTM for Accurate Obesity Prognosis: Advancing Public Health towards Sustainable Cities.Bioengineering (Basel, Switzerland) · 2024Article
- Integrated machine learning-driven disulfidptosis profiling: CYFIP1 and EMILIN1 as therapeutic nodes in neuroblastoma.Journal of cancer research and clinical oncology · 2024Article
- Proteomic and transcriptomic analyses identify apo-transcobalamin-II as a biomarker of overall survival in osteosarcoma.Frontiers in oncology · 2024Article
- Integrative genomic analyses combined with molecular dynamics simulations reveal the impact of deleterious mutations of Bcl-2 gene on the apoptotic machinery and implications in carcinogenesis.Frontiers in genetics · 2024Article
- Computational Biology Helps Understand How Polyploid Giant Cancer Cells Drive Tumor Success.Genes · 2023Review
- Insight into Oncogenic Viral Pathways as Drivers of Viral Cancers: Implication for Effective Therapy.Current oncology (Toronto, Ont.) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tumour heterogeneity is one of the main characteristics of cancer and can be categorised into inter- or intratumour heterogeneity. This heterogeneity has been revealed as one of the key causes of treatment failure and relapse. Precision oncology is an emerging field that seeks to design tailored treatments for each cancer patient according to epidemiological, clinical and omics data. This discipline relies on bioinformatics tools designed to compute scores to prioritise available drugs, with the aim of helping clinicians in treatment selection. In this review, we describe the current approaches for therapy selection depending on which type of tumour heterogeneity is being targeted and the available next-generation sequencing data. We cover intertumour heterogeneity studies and individual treatment selection using genomics variants, expression data or multi-omics strategies. We also describe intratumour dissection through clonal inference and single-cell transcriptomics, in each case providing bioinformatics tools for tailored treatment selection. Finally, we discuss how these therapy selection workflows could be integrated into the clinical practice.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.