Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Precision oncology in urothelial cancer.

ABSTRACT: Genomics-driven, precision medicine has been adopted in virtually every tumour type and underlies the significant advances in cancer management to date. The paradigm shift from the indiscriminate use of chemotherapeutics, to strategies that harness our mechanistic knowledge of cancer biology has led to profound clinical benefit for patients, and will continue to mould present and future treatment approaches. In the realm of urothelial cancer, the present status of precision medicine includes a rich landscape that encompasses molecularly-matched therapy, predictive biomarkers that could help inform response to chemotherapy and immunotherapy, as well as novel strategies such as antibody drug conjugates that exploit the use of target proteins for enhanced tumour killing. Here, we present an overview on these clinically-impactful discoveries in urothelial cancer, discuss the limitations and challenges in the implementation of precision oncology, and offer our vision for its future.

SUBMITTER: Liow E

PROVIDER: S-EPMC7059486 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Precision oncology in urothelial cancer.

Liow Elizabeth E Tran Ben B

ESMO open 20200301 Suppl 1

Genomics-driven, precision medicine has been adopted in virtually every tumour type and underlies the significant advances in cancer management to date. The paradigm shift from the indiscriminate use of chemotherapeutics, to strategies that harness our mechanistic knowledge of cancer biology has led to profound clinical benefit for patients, and will continue to mould present and future treatment approaches. In the realm of urothelial cancer, the present status of precision medicine includes a r ...[more]

PMID: 32132102

Similar Datasets

Precision oncology in liver cancer.

Project description:With the widespread adoption of molecular profiling in clinical oncology practice, many physicians are faced with making therapeutic decisions based upon isolated genomic alterations. For example, epidermal growth factor receptor tyrosine kinase inhibitors (TKIs) are effective in EGFR-mutant non-small cell lung cancers (NSCLC) while anti-EGFR monoclonal antibodies are ineffective in Ras-mutant colorectal cancers. The matching of mutations with drugs aimed at their respective gene products represents the current state of "precision" oncology. Despite the great expectations of this approach, only a fraction of cancers responds to 'targeted' interventions, and many early responders will ultimately develop resistance to these agents. The underwhelming success of mutation-driven therapies across all cancer types is not due to an inability to detect genetic changes in tumors; rather a deficit in functional insight into the genomic alterations that give rise to each cancer. The Achilles heel of precision oncology thus remains the lack of a robust functional understanding of an individual cancer genome that then allows prediction of the best therapy and resultant outcome for that patient. Current practice focuses on one 'actionable' mutation at a time, while solid cancers typically possess many mutations that involve different cellular sub-populations within a tumor. No method or platform currently exists to guide the interpretation of these complex data, nor to accurately predict response to treatment. This problem is particularly germane to primary liver cancers (PLC), for which only a handful of targeted therapies have been introduced. Here, we will review strategies aimed at overcoming some of these challenges in precision oncology, using liver cancer as an example.

| S-EPMC6068329 | biostudies-literature

Applied Precision Cancer Medicine in Neuro-Oncology.

Project description:Brain tumours that are refractory to treatment have a poor prognosis and constitute a major challenge in offering effective treatment strategies. By targeting molecular alterations, precision cancer medicine may be a viable option for the treatment of brain tumours. In this retrospective analysis of our PCM platform, we describe the molecular profiling of primary brain tumours from 50 patients. Tumour samples of the patients were examined by a 161-gene next-generation sequencing panel, immunohistochemistry, and fluorescence in situ hybridization (FISH). We identified 103 molecular aberrations in 36 (72%) of the 50 patients. The predominant mutations were TP53 (14.6%), IDH1 (9.7%) and PIK3CA (6.8%). No mutations were detected in 14 (28%) of the 50 patients. IHC demonstrated frequent overexpression of EGFR and mTOR, in 38 (76%) and 35 (70%) patients, respectively. Overexpression of PDGFRa and PDGFRb were less common and detected in 16 and four patients, respectively. For 35 patients a targeted therapy was recommended. In our database, the majority of patients displayed mutations, against which targeted therapy could be offered. Based on our observations, PCM may be a feasible novel treatment approach in neuro-oncology.

| S-EPMC6934769 | biostudies-literature

Precision Oncology Targets in Biliary Tract Cancer.

Project description:Targeted therapies in biliary tract cancer (BTC) are emerging as options for patients not who do not respond to first-line treatment. Agents acting on tumor-specific oncogenes in BTC may target fibroblast growth factor receptor 2 (FGFR2), isocitrate dehydrogenase (IDH), B-raf kinase (BRAF), and human epidermal growth factor receptor 2 (HER-2). Additionally, given the heterogeneous genetic landscape of advanced BTCs, many harbor genetic aberrations that are common among solid tumors, including RET fusions, tropomyosin receptor kinase (TRK) fusions, and high tumor mutational burden (TMB). This review aims to provide updates on the evolving array of therapeutics available, and to summarize promising works on the horizon.

| S-EPMC10093316 | biostudies-literature

Precision oncology: A new era of cancer clinical trials.

Project description:Traditionally, site of disease and anatomic staging have been used to define patient populations to be studied in individual cancer clinical trials. In the past decade, however, oncology has become increasingly understood on a cellular and molecular level, with many cancer subtypes being described as a function of biomarkers or tumor genetic mutations. With these changes in the science of oncology have come changes to the way we design and perform clinical trials. Increasingly common are trials tailored to detect enhanced efficacy in a patient subpopulation, e.g. patients with a known biomarker value or whose tumors harbor a specific genetic mutation. Here, we provide an overview of traditional and newer biomarker-based trial designs, and highlight lessons learned through implementation of several ongoing and recently completed trials.

| S-EPMC5023449 | biostudies-other

"Personalized Cancer Therapy": A Publicly Available Precision Oncology Resource.

Project description:High-throughput genomic and molecular profiling of tumors is emerging as an important clinical approach. Molecular profiling is increasingly being used to guide cancer patient care, especially in advanced and incurable cancers. However, navigating the scientific literature to make evidence-based clinical decisions based on molecular profiling results is overwhelming for many oncology clinicians and researchers. The Personalized Cancer Therapy website (www.personalizedcancertherapy.org) was created to provide an online resource for clinicians and researchers to facilitate navigation of available data. Specifically, this resource can be used to help identify potential therapy options for patients harboring oncogenic genomic alterations. Herein, we describe how content on www.personalizedcancertherapy.org is generated and maintained. We end with case scenarios to illustrate the clinical utility of the website. The goal of this publicly available resource is to provide easily accessible information to a broad oncology audience, as this may help ease the information retrieval burden facing participants in the precision oncology field. Cancer Res; 77(21); e123-6. ©2017 AACR.

| S-EPMC5774617 | biostudies-other

PDX bank from urothelial cancer to guide precision medicine.

Project description:We developed preclinical PDX models, recapitulating the molecular heterogeneity of MIBCs and UTUC, which will represent an essential tool in therapy development. Pharmacological characterization of the PDXs suggested that upper urinary tract and bladder cancers (UCC/ SCC) with similar molecular characteristics could benefit from the same treatments, and showed a benefit for combined FGFR/EGFR inhibition in FGFR3-mutant PDXs, compared to FGFR inhibition alone.

2022-08-31 | GSE181962 | GEO

Translating cancer genomes and transcriptomes for precision oncology.

Project description:Understanding the molecular landscape of cancer has facilitated the development of diagnostic, prognostic, and predictive biomarkers for clinical oncology. Developments in next-generation DNA sequencing technologies have increased the speed and reduced the cost of sequencing the nucleic acids of cancer cells. This has unlocked opportunities to characterize the genomic and transcriptomic landscapes of cancer for basic science research through projects like The Cancer Genome Atlas. The cancer genome includes DNA-based alterations, such as point mutations or gene duplications. The cancer transcriptome involves RNA-based alterations, including changes in messenger RNAs. Together, the genome and transcriptome can provide a comprehensive view of an individual patient's cancer that is beginning to impact real-time clinical decision-making. The authors discuss several opportunities for translating this basic science knowledge into clinical practice, including a molecular classification of cancer, heritable risk of cancer, eligibility for targeted therapies, and the development of innovative, genomic-based clinical trials. In this review, key applications and new directions are outlined for translating the cancer genome and transcriptome into patient care in the clinic.

| S-EPMC4713245 | biostudies-literature

Evidence-Based Precision Oncology with the Cancer Targetome.

Project description:A core tenet of precision oncology is the rational choice of drugs to interact with patient-specific biological targets of interest, but it is currently difficult for researchers to obtain consistent and well-supported target information for pharmaceutical drugs. We review current drug-target interaction resources and critically assess how supporting evidence is handled. We introduce the concept of a unified Cancer Targetome to aggregate drug-target interactions in an evidence-based framework. We discuss current unmet needs and the implications for evidence-based clinical omics. The focus of this review is precision oncology but the discussion is highly relevant to targeted therapies in any area.

| S-EPMC5759325 | 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

Personal Cancer Genome Reporter: variant interpretation report for precision oncology.

Project description:Individual tumor genomes pose a major challenge for clinical interpretation due to their unique sets of acquired mutations. There is a general scarcity of tools that can (i) systematically interrogate cancer genomes in the context of diagnostic, prognostic, and therapeutic biomarkers, (ii) prioritize and highlight the most important findings and (iii) present the results in a format accessible to clinical experts. We have developed a stand-alone, open-source software package for somatic variant annotation that integrates a comprehensive set of knowledge resources related to tumor biology and therapeutic biomarkers, both at the gene and variant level. Our application generates a tiered report that will aid the interpretation of individual cancer genomes in a clinical setting.The software is implemented in Python/R, and is freely available through Docker technology. Documentation, example reports, and installation instructions are accessible via the project GitHub page: https://github.com/sigven/pcgr.sigven@ifi.uio.no.Supplementary data are available at Bioinformatics online.

| S-EPMC5946881 | biostudies-other

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