Precision or Targeted Oncology deals with a way to target specific pathways or even proteins that are activated in tumors to prevent, stop or minimize he impact tumor growth and metastasis has on the patient’s condition.
Since the tumor growth and proliferation is guided by sub-cellular processes and regulated through a variety of molecular mechanisms, it is important to learn to extract these signals from the DNA, RNA and proteins. A typical way to do this is by studying Next Generation Sequencing (NGS) data from a biopsy sample taken from a patient. In recent years, these samples are also taken and separated into individual cells using singe-cell sequencing techniques to understand the above mentioned processes at a single cell level.
Once the data is generated, short reads from the DNA or RNA of that sample are used to either detect DNA variations (SNPs, CNV, etc.) or levels of RNA expression. In a variety of cancers, this information can be sufficient to understand a variety of things. For example, we know that tumor growth can be associated with a lack of controlled death (apoptosis) mechanisms that should start getting activated as soon as DNA damage occurs. Or we can spot changes to cell differentiation because tumors do not behave like real tissue around them, but rather act like immature, undifferentiated cells. To get such information from raw data, it is important to have serious bioinformatics skills!
Extracting such information from short DNA or RNA reads, or short sequences, is a challenge. It typically involves quite a number of steps that all have to be tuned to the specific type of data and references relevant to the project. For example,e when we study DNA variation, we take into consideration a reference genome but also have to understand the difference between germline and somatic mutations in a given sample. For RNA, a variety of conclusions can be made just by changing the reference information at the mapping stage – we can map our reads to the reference genome or limiting mapping to just to the expressed genes (the transcriptome). We can also look for gene expression or for alternative splicing events, etc. For each one of these steps, it is important to have training in bioinformatics.
The more precise we can be in understanding these sub cellular mechanisms of action, the better we can target the intervention and spot other risks for the patient. Often times, however, this is not possible to study on the patient themselves. That’s why researchers use cell lines or animal models to study and understand these molecular mechanisms. When we have sufficient data and can make reliable conclusions, we might get a set of biomarkers that can help us distinguish patients and diagnose them better. This type of information can also lead to the understanding of treatment efficacy and selection of an appropriate treatment strategy. A link between the data and the interpretation is the analysis. Analyzing data using bioinformatics methods can be learned by biologists and clinicians.
Analyzing data using bioinformatics methods can be learned by biologists and clinicians.
To learn more about bioinformatics for precision oncology please visit: https://edu.t-bio.info/bioinformatics-training-precision-oncology/
Key points from reference publications:
The goal of precision oncology has begun to be realized through multiplex molecular testing including NGS.
Oncologists should be familiar with technical aspects of NGS to facilitate selecting the most appropriate and cost-effective testing platform.
Considerations for molecular testing include which tissue type to utilize, timing of profiling in the disease course, extent of panel to order, and degree of clinical annotation reported.
Actionable biomarkers of non–small cell lung cancer make this disease a paradigm for precision oncology at diagnosis of advanced disease, during therapy, and at time of progression.
Interpretation of molecular data to facilitate best practice remains a challenge; clinical trial participation and sharing of linked molecular/clinical data sets are strongly encouraged.