ReviewHigh-throughput2018
From Single Level Analysis to Multi-Omics Integrative Approaches: A Powerful Strategy towards the Precision Oncology.
Review in High-throughput, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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
34 citing papers in PubMed.
- Beyond chemotherapy: The rise of nucleic acid nanoformulations in personalized lung cancer therapy.Cancer pathogenesis and therapy · 2026Review
- Multidimensional, integrative profiling identifies BCL2L1 methylation as a predictor of MCL1 dependency in pediatric malignancies.JCI insight · 2025Article
- Development of a novel circulating miRNA panel for early detection of esophageal cancer.American journal of translational research · 2025Article
- LNA-i-miR-221 activity in colorectal cancer: A reverse translational investigation.Molecular therapy. Nucleic acids · 2024Article
- Machine learning pipeline to analyze clinical and proteomics data: experiences on a prostate cancer case.BMC medical informatics and decision making · 2024Article
- Scaling approaches for the prediction of human clearance of LNA-i-mir-221: A retrospective validation.Current research in pharmacology and drug discovery · 2024Article
- Classification of Long Non-Coding RNAs s Between Early and Late Stage of Liver Cancers From Non-coding RNA Profiles Using Machine-Learning Approach.Bioinformatics and biology insights · 2024Article
- Effectiveness of Treatments That Alter Metabolomics in Cancer Patients-A Systematic Review.Cancers · 2023Review
- Druggability of Targets for Diagnostic Radiopharmaceuticals.ACS pharmacology & translational science · 2023Review
- Lynch Syndrome Biopathology and Treatment: The Potential Role of microRNAs in Clinical Practice.Cancers · 2023Review
- Analysis of age-dependent gene-expression in human tissues for studying diabetes comorbidities.Scientific reports · 2023Article
- SARS-CoV-2 protein structure and sequence mutations: Evolutionary analysis and effects on virus variants.PloS one · 2023Article
- Exploiting DNA Ligase III addiction of multiple myeloma by flavonoid Rhamnetin.Journal of translational medicine · 2022Article
- Design and Implementation of a New Local Alignment Algorithm for Multilayer Networks.Entropy (Basel, Switzerland) · 2022Article
- The identification and validation of EphA7 hypermethylation, a novel biomarker, in cervical cancer.BMC cancer · 2022Article
- miR-221/222 as biomarkers and targets for therapeutic intervention on cancer and other diseases: A systematic review.Molecular therapy. Nucleic acids · 2022Review
- Using dual-network-analyser for communities detecting in dual networks.BMC bioinformatics · 2022Article
- Article
- miR-22 Modulates Lenalidomide Activity by Counteracting MYC Addiction in Multiple Myeloma.Cancers · 2021Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Integration of multi-omics data from different molecular levels with clinical data, as well as epidemiologic risk factors, represents an accurate and promising methodology to understand the complexity of biological systems of human diseases, including cancer. By the extensive use of novel technologic platforms, a large number of multidimensional data can be derived from analysis of health and disease systems. Comprehensive analysis of multi-omics data in an integrated framework, which includes cumulative effects in the context of biological pathways, is therefore eagerly awaited. This strategy could allow the identification of pathway-addiction of cancer cells that may be amenable to therapeutic intervention. However, translation into clinical settings requires an optimized integration of omics data with clinical vision to fully exploit precision cancer medicine. We will discuss the available technical approach and more recent developments in the specific field.
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.