ArticleScientific reports2018
Pathway-based dissection of the genomic heterogeneity of cancer hallmarks' acquisition with SLAPenrich.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 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
20 citing papers in PubMed, 36 citations in OpenAlex.
- On the potential origin of the zygote-like cancer stem cell with a focus on fusion for cell rescue.Frontiers in cell and developmental biology · 2026Article
- Path2Omics Enhances Transcriptomic and Methylation Prediction Accuracy from Tumor Histopathology.Cancer research · 2025Article
- Temporal trends in evidence supporting novel drug target discovery.Nature communications · 2025Article
- scMalignantFinder distinguishes malignant cells in single-cell and spatial transcriptomics by leveraging cancer signatures.Communications biology · 2025Article
- Charting the transcriptomic landscape of primary and metastatic cancers in relation to their origin and target normal tissues.Science advances · 2024Article
- A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics.Nature cancer · 2024Article
- Unraveling druggable cancer-driving proteins and targeted drugs using artificial intelligence and multi-omics analyses.Scientific reports · 2024Article
- Prediction of DNA methylation-based tumor types from histopathology in central nervous system tumors with deep learning.Nature medicine · 2024Article
- A heuristic algorithm solving the mutual-exclusivity-sorting problem.Bioinformatics (Oxford, England) · 2023Article
- Gastric Cancer Pre-Stage Detection and Early Diagnosis of Gastritis Using Serum Protein Signatures.Molecules (Basel, Switzerland) · 2022Article
- Genomic analyses of the metastasis-derived prostate cancer cell lines LNCaP, VCaP, and PC3-AR.The Prostate · 2022Article
- A human-based multi-gene signature enables quantitative drug repurposing for metabolic disease.eLife · 2022Article
- The somatic molecular evolution of cancer: Mutation, selection, and epistasis.Progress in biophysics and molecular biology · 2021Article
- An efficient and effective method to identify significantly perturbed subnetworks in cancer.Nature computational science · 2021Article
- Article
- Using mechanistic models for the clinical interpretation of complex genomic variation.Scientific reports · 2019Article
- Article
- Open Targets Platform: new developments and updates two years on.Nucleic acids research · 2019Article
- Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis.Annals of oncology : official journal of the European Society for Medical Oncology · 2018Article
- Widespread Post-transcriptional Attenuation of Genomic Copy-Number Variation in Cancer.Cell systems · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
Abstract
Cancer hallmarks are evolutionary traits required by a tumour to develop. While extensively characterised, the way these traits are achieved through the accumulation of somatic mutations in key biological pathways is not fully understood. To shed light on this subject, we characterised the landscape of pathway alterations associated with somatic mutations observed in 4,415 patients across ten cancer types, using 374 orthogonal pathway gene-sets mapped onto canonical cancer hallmarks. Towards this end, we developed SLAPenrich: a computational method based on population-level statistics, freely available as an open source R package. Assembling the identified pathway alterations into sets of hallmark signatures allowed us to connect somatic mutations to clinically interpretable cancer mechanisms. Further, we explored the heterogeneity of these signatures, in terms of ratio of altered pathways associated with each individual hallmark, assuming that this is reflective of the extent of selective advantage provided to the cancer type under consideration. Our analysis revealed the predominance of certain hallmarks in specific cancer types, thus suggesting different evolutionary trajectories across cancer lineages. Finally, although many pathway alteration enrichments are guided by somatic mutations in frequently altered high-confidence cancer genes, excluding these driver mutations preserves the hallmark heterogeneity signatures, thus the detected hallmarks' predominance across cancer types. As a consequence, we propose the hallmark signatures as a ground truth to characterise tails of infrequent genomic alterations and identify potential novel cancer driver genes and networks.
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.