Browse
Submit Data
Databases
API
Help

Dataset Information

52 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Applying Precision Oncology Principles in Radiation Oncology.

ABSTRACT: Radiation therapy is a critical component in the curative management of many solid tumor types, and advances in radiation delivery techniques during the past decade have led to improved disease control and quality of life for patients. During the same period, remarkable advances have also been made in understanding the genomic landscape of tumors; however, treatment decisions in radiation oncology continue to depend primarily on clinical and histopathologic characteristics rather than on the genetic features of the tumor or the patient. With the development of novel genomic techniques and their increasing use in clinical practice, radiation oncology is uniquely positioned to leverage these advances to identify novel biomarkers that could inform radiation dose, field, and the use of concurrent systemic agents. Here, we summarize efforts to use genomic techniques to guide radiation decisions, and we highlight some of the current opportunities and challenges that exist in attempting to apply precision oncology principles in radiation oncology.

SUBMITTER: Kamran SC

PROVIDER: S-EPMC7446508 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Applying Precision Oncology Principles in Radiation Oncology.

Kamran Sophia C SC Mouw Kent W KW

JCO precision oncology 20180514

Radiation therapy is a critical component in the curative management of many solid tumor types, and advances in radiation delivery techniques during the past decade have led to improved disease control and quality of life for patients. During the same period, remarkable advances have also been made in understanding the genomic landscape of tumors; however, treatment decisions in radiation oncology continue to depend primarily on clinical and histopathologic characteristics rather than on the gen ...[more]

PMID: 32914000

Similar Datasets

Implementing the FAIR Data Principles in precision oncology: review of supporting initiatives.

Project description:Compelling research has recently shown that cancer is so heterogeneous that single research centres cannot produce enough data to fit prognostic and predictive models of sufficient accuracy. Data sharing in precision oncology is therefore of utmost importance. The Findable, Accessible, Interoperable and Reusable (FAIR) Data Principles have been developed to define good practices in data sharing. Motivated by the ambition of applying the FAIR Data Principles to our own clinical precision oncology implementations and research, we have performed a systematic literature review of potentially relevant initiatives. For clinical data, we suggest using the Genomic Data Commons model as a reference as it provides a field-tested and well-documented solution. Regarding classification of diagnosis, morphology and topography and drugs, we chose to follow the World Health Organization standards, i.e. ICD10, ICD-O-3 and Anatomical Therapeutic Chemical classifications, respectively. For the bioinformatics pipeline, the Genome Analysis ToolKit Best Practices using Docker containers offer a coherent solution and have therefore been selected. Regarding the naming of variants, we follow the Human Genome Variation Society's standard. For the IT infrastructure, we have built a centralized solution to participate in data sharing through federated solutions such as the Beacon Networks.

| S-EPMC7299292 | biostudies-literature

Bioinformatics for precision medicine in oncology: principles and application to the SHIVA clinical trial.

Project description:Precision medicine (PM) requires the delivery of individually adapted medical care based on the genetic characteristics of each patient and his/her tumor. The last decade witnessed the development of high-throughput technologies such as microarrays and next-generation sequencing which paved the way to PM in the field of oncology. While the cost of these technologies decreases, we are facing an exponential increase in the amount of data produced. Our ability to use this information in daily practice relies strongly on the availability of an efficient bioinformatics system that assists in the translation of knowledge from the bench towards molecular targeting and diagnosis. Clinical trials and routine diagnoses constitute different approaches, both requiring a strong bioinformatics environment capable of (i) warranting the integration and the traceability of data, (ii) ensuring the correct processing and analyses of genomic data, and (iii) applying well-defined and reproducible procedures for workflow management and decision-making. To address the issues, a seamless information system was developed at Institut Curie which facilitates the data integration and tracks in real-time the processing of individual samples. Moreover, computational pipelines were developed to identify reliably genomic alterations and mutations from the molecular profiles of each patient. After a rigorous quality control, a meaningful report is delivered to the clinicians and biologists for the therapeutic decision. The complete bioinformatics environment and the key points of its implementation are presented in the context of the SHIVA clinical trial, a multicentric randomized phase II trial comparing targeted therapy based on tumor molecular profiling versus conventional therapy in patients with refractory cancer. The numerous challenges faced in practice during the setting up and the conduct of this trial are discussed as an illustration of PM application.

| S-EPMC4039073 | biostudies-literature

Translation of Precision Medicine Research Into Biomarker-Informed Care in Radiation Oncology.

Project description:The reach of personalized medicine in radiation oncology has expanded greatly over the past few decades as technical precision has improved the delivery of radiation to each patient's unique anatomy. Yet, the consideration of biological heterogeneity between patients has largely not been translated to clinical care. There are innumerable promising advancements in the discovery and validation of biomarkers, which could be used to alter radiation therapy directly or indirectly. Directly, biomarker-informed care may alter treatment dose or identify patients who would benefit most from radiation therapy and who could safely avoid more aggressive care. Indirectly, a variety of biomarkers could assist with choosing the best radiosensitizing chemotherapies. The translation of these advancements into clinical practice will bring radiation oncology even further into the era of precision medicine, treating patients according to their unique anatomical and biological differences.

| S-EPMC8667861 | biostudies-literature

The OncoLoop Network-based Precision Oncology Framework

Project description:We introduce OncoLoop, a highly-generalizable, precision medicine framework to triangulate between available mouse models, human tumors, and large-scale drug perturbational assays with in vivo validation to predict personalized treatment

2022-10-31 | GSE186566 | GEO

Precision medicine in pediatric oncology.

Project description:Outcome in treatment of childhood cancers has improved dramatically since the 1970s. This success was largely achieved by the implementation of cooperative clinical research trial groups that standardized and developed treatment of childhood cancer. Nevertheless, outcome in certain types of malignancies is still unfavorable. Intensification of conventional chemotherapy and radiotherapy improved outcome only marginally at the cost of acute and long-term side effects. Hence, it is necessary to develop targeted therapy strategies.Here, we review the developments and perspectives in precision medicine in pediatric oncology with a special focus on targeted drug therapies like kinase inhibitors and inducers of apoptosis, the impact of cancer genome sequencing and immunotherapy.

| S-EPMC6119176 | biostudies-other

Epigenetics and Precision Oncology.

Project description:Epigenetic alterations such as DNA methylation defects and aberrant covalent histone modifications occur within all cancers and are selected for throughout the natural history of tumor formation, with changes being detectable in early onset, progression, and ultimately recurrence and metastasis. The ascertainment and use of these marks to identify at-risk patient populations, refine diagnostic criteria, and provide prognostic and predictive factors to guide treatment decisions are of growing clinical relevance. Furthermore, the targetable nature of epigenetic modifications provides a unique opportunity to alter treatment paradigms and provide new therapeutic options for patients whose malignancies possess these aberrant epigenetic modifications, paving the way for new and personalized medicine. DNA methylation has proven to be of significant clinical utility for its stability and relative ease of testing. The intent of this review is to elaborate upon well-supported examples of epigenetic precision medicine and how the field is moving forward, primarily in the context of aberrant DNA methylation.

| S-EPMC5708865 | biostudies-literature

Precision Detection Technology: Equipping Precision Oncology with Wings.

Project description:In recent years, precision medical detection techniques experienced a rapid transformation from low-throughput to high-throughput genomic sequencing, from multicell promiscuous detection to single-cell precision sequencing. The emergence of liquid biopsy technology has compensated for the many limitations of tissue biopsy, leading to a tremendous transformation in precision detection. Precision detection techniques contribute to monitoring disease development more closely, evaluating therapeutic effects more scientifically, and developing new targets and new drugs. In the future, the role of precision detection and the joint detection in epigenetics, rare gene detection, individualized targeted therapy, and multigene targeted drug combination therapy should be extensively explored. This article reviews the changes in precision medical detection technology in the era of precision medicine, as well as the development, clinical application, and future challenges of liquid biopsy.

| S-EPMC7368234 | biostudies-literature

Microscaled Proteogenomic Methods for Precision Oncology

Project description:Shankha Satpathy, Eric J. Jaehnig, et al., <a href="https://www.nature.com/articles/s41467-020-14381-2" target="_blank">Nature Communications volume 11, Article number: 532 (2020)</a>Cancer proteogenomics promises new insights into cancer biology and treatment efficacy by integrating genomics, transcriptomics and protein profiling including modifications by mass spectrometry (MS). A critical limitation is sample input requirements that exceed many sources of clinically important material. Here we report a proteogenomics approach for core biopsies using tissue-sparing specimen processing and microscaled proteomics. As a demonstration, we analyze core needle biopsies from ERBB2 positive breast cancers before and 48-72 h after initiating neoadjuvant trastuzumab-based chemotherapy. We show greater suppression of ERBB2 protein and both ERBB2 and mTOR target phosphosite levels in cases associated with pathological complete response, and identify potential causes of treatment resistance including the absence of ERBB2 amplification, insufficient ERBB2 activity for therapeutic sensitivity despite ERBB2 amplification, and candidate resistance mechanisms including androgen receptor signaling, mucin overexpression and an inactive immune microenvironment. The clinical utility and discovery potential of proteogenomics at biopsy-scale warrants further investigation. Genomic Data for samples in the Microscaled Proteogenomic Methods Publication are available from the NIH Database of Genotypes and Phenotypes (dbGaP), Study Accession: phs001907.v1.p1, <a href="https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001907.v1.p1" target="_blank">here</a> <ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/study-summary/S051">https://cptac-data-portal.georgetown.edu/study-summary/S051</a> on 06/02/21</li></ul>

2021-06-02 | MSV000087566 | MassIVE

Towards Optimization of Precision Oncology in Metastatic Uterine Tumors

Project description:Precision oncology and its diagnostic tools are essential for developing personalized cancer treatments. The purpose of this study was to integrate data on the digital patterns of reticulin fiber scaffolding and the immune cell infiltrate, transcriptomic and epigenetic profiles in aggressive uterine adenocarcinoma (uADC), uterine leiomyosarcoma (uLMS) and their respective lung metastases (LM-uADC and LM-uLMS), with the aim of obtaining key tumor microenvironment (TME) biomarkers that can help improve metastatic prediction and shed light on potential therapeutic targets.

2022-12-16 | GSE216313 | GEO

Synthetic lethality-mediated precision oncology via the tumor transcriptome

Project description:Precision oncology has made significant advances in the last few years, mainly by targeting actionable mutations in cancer driver genes. However, the proportion of patients whose tumors can be targeted therapeutically remains limited. Recent studies have begun to explore the benefit of analyzing tumor transcriptomics data to guide patient treatment, raising the need for new approaches for systematically accomplishing that. Here we show that computationally derived genetic interactions can successfully predict patient response.

2021-02-11 | GSE166449 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data