Cancer Bioinformatics: Data Analysis for Oncology Research
Since cancer is a leading cause of death worldwide, accounting for almost 10 million deaths in 2020* alone, it is unsurprising that it is a research focus for so many. With the number of cancer cases increasing each year and expected to reach 27.5 million by 2040**, we understand that cancer bioinformatics have never been more crucial.
Oncology Bioinformatics – Revealing The Insights In Your Cancer Research Data
Bioinformatics analyses pinpoint the actionable information in study data, providing quick results so your cancer research can continue at pace. As a result, bioinformatics approaches are widely used in oncology-related drug development, in both the preclinical and clinical stages. Oncology bioinformatics providers like Fios Genomics can help with:
- Target and lead identification and validation
- Identifying biomarkers for measurement of drug efficacy and mechanism of action
- Predicting biomarkers for stratification/classification of patient response to drug
- SNP genotype analysis and DNA sequence analysis for the detection of novel SNPs implicated in disease or response to drugs
What’s more, a good bioinformatics provider understands that each project is different. There is no ‘one-size-fits-all’ solution: our team tailors the analysis approach for each project. Above all, our goal is to use bioinformatics analyses to answer your research question and advance your vital cancer research efforts.
Fios Genomics Cancer Bioinformatics Experience
For the past several years over 30% of our bioinformatics analyses for clients have focused on an area of cancer research. As a result, we are continually honing our expertise and refining our oncology bioinformatics offering. Our work in this area is featured extensively in client papers, some of which are detailed below.
- ctDNA guiding adjuvant immunotherapy in urothelial carcinoma
- Development of a gene expression–based prognostic signature for IDH wild-type glioblastoma
- Tumor Fusion Burden as a Hallmark of Immune Infiltration in Prostate Cancer
If you would like to see more of the publications Fios have been featured in, please visit our oncology publications page.
With a 95% repeated business rate, we are pleased to report that clients trust us time and again to meet their bioinformatics needs for oncology projects. Whether a client requires the mining of public data sets, experimental design guidance, or data analysis, they can count on our speed and expertise.
The Fios Difference
At Fios Genomics we do not simply provide you with more data. Instead, we pride ourselves on interpreting that data for you to reveal the significant biological insights it holds. Furthermore, each of our analysis reports is fully interactive, allowing you to fully explore the data. In fact, the lead analyst for your project will talk through the report with you. This ensures that you fully understand the results and provides an opportunity to ask questions.
We could list several more benefits of working with us. However, the best people to tell you what it is like working with us are our clients:
If you have an oncology project you would like to discuss, contact us today. However, if you would like to learn more about our cancer bioinformatics solutions you can visit our oncology services page.
Author: Breige McBride, Content and Social Media Manager, Fios Genomics
Reviewed by Fios Genomics Bioinformatics Experts to ensure accuracy
Further Reading
Webinar: Tumour Fusion Burden and the Immune Landscape of Prostate Cancer
What is Bioinformatics? Overview and Examples
References
- (*) World Health Organisation, https://www.who.int/news-room/fact-sheets/detail/cancer, Accessed June 2021
- (**) Cancer Research UK, https://www.cancerresearchuk.org/health-professional/cancer-statistics/worldwide-cancer, Accessed June 2021
Access a Sample of our Data Analysis Reports
Fill in the form below to access the data analysis report our team created. The study we helped with aimed to investigate the response to PD-L1 blockade therapies in patients with metastatic urothelial cancers, and has been published in Nature (Mariathasan et al. Nature 2018).The report presents a portion of the published analysis above concerning overall survival and response to treatment. We highlight the ability of high-throughput approaches to define biomarkers which accurately predict both treatment response to anti-PD-L1 therapy and overall survival in patients with metastatic urothelial cancer.
