Oncologists Turn To Genomics For Improved Answers

Each year, more than 1.8 million people in the United States are diagnosed with cancer. Despite new therapies coming to market and advances in personalized medicine, over half a million patients die annually from cancer in the United States alone. Four types – breast, pancreas, colon and rectum, and lung and bronchus – result in the most deaths each year: 42,680 (breast); 51,980 (pancreas); 52,900 (colon and rectum); and 124,730 (lung and bronchus). Besides heart disease, cancer delivers the most deaths in the United States annually. For those under 65, cancer spikes to the leading cause of death. 

Genomic profiling advancements have paved the way for identifying the different types of cancers, such as connecting BRCA1 or BRCA2 to breast cancer, the KRAS biomarker for colorectal cancer, CA-125 with ovarian cancer, and PCA3 for prostate cancer. In particular, bioinformatics and next-generation sequencing (NGS) technologies can speed up previous timelines to identify mutations of clinical significance and provide faster treatment options for patients.

Genomics supports treatment selection efficacy

Such genomic technologies not only help to identify cancers, but also offer opportunities for assessing the potential efficacy of different treatment options. By analyzing the genomic profile of a particular patient, doctors can see which medications might offer the most support, and which could cause more harm. For example, if a non-small cell lung cancer patient has cancer that manifests from epidermal growth factor receptor (EGFR) gene mutations, an EGFR inhibitor treatment could offer a viable solution. Genomic testing could both flag that biomarker as well as assess if the EGFR inhibitor has potential to treat the given gene change causing the cancer. 

Further, understanding a patient’s genomic profile can support the doctor in selecting medications that have less of a chance of adverse drug reactions for the given patient. In addition, such pharmacogenomic information allows physicians to tailor the dose of a medication to how fast the patient may metabolize a medication. The benefits to patients abound: minimized side effects, less trial and error to find effective medications, potentially fewer doctor appointments as a result of getting the right medication earlier on, savings of not paying for multiple medications before finding one that works. All this potentially translates to shortened timelines to remission. 

Answers hidden by data

The genomic analysis tools available frequently come with an abundance of data. In particular, the results include lengthy secondary reports. In oncology, reports usually deliver NGS data as raw or secondary data that requires specialized interpretation, increasing dependency on bioinformaticians, and ultimately delaying actionable results for patients as a result. Furthermore, many oncology workflows often remain fragmented, requiring separate tools and training for different necessary components: variant calling, annotation, and pharmacogenomic interpretation to guide targeted therapies.

A high need exists for integrated genomics platforms that do not just include a thorough secondary report but also a tertiary analysis with embedded pharmacogenomics insights and guidelines for therapy.  Such tertiary analysis empowers real-time integrated decision support for precision medicine, so patients can receive answers about viable treatments from amongst their genomics data. 

Select an effective genomic profiling technology

Genomic technologies on the market come with different value propositions, so oncology researchers, labs, and genetic testing companies should carefully consider the unique features of each in conjunction with their own needs and budgets when selecting which tool to implement. First, the efficacy of the technology and the comprehensiveness of the genomic profiling available vary by tool. As well, some platforms unify NGS secondary/tertiary analysis and pharmacogenomics interpretation into a single environment. Such options can allow oncology teams to move from raw data to treatment-guiding insights quicker, as well as reduce operational costs by eliminating the need for multiple licenses.

Further, certain tools require many steps and bioinformatic domain specific expertise to use. However, others do not rely on either: for example, select technologies offer cloud-based workflows – some with as few as three steps – where a user only uploads the data and then downloads the tertiary analysis produced and recommendations. Such options can especially support oncology researchers, molecular pathology labs, and genetic testing companies that do not have larger bioinformatics teams already on staff. Mitigating the need for employing additional technical experts can support companies in further minimizing cost. 

Ultimately, sourcing effective genomics technology can empower oncology teams to reduce turnaround times for biomarker-driven therapy decisions, streamline reporting for tumor boards, and improve the outcomes for their patients.

Photo: iLexx, Getty Images

This post appears through the MedCity Influencers program. Anyone can publish their perspective on business and innovation in healthcare on MedCity News through MedCity Influencers. Click here to find out how.