Genomic Guided Therapy: Show Me the Data!

June 12, 2015

I was recently asked to speak to an audience of nonmedical adult participants enrolled in a leadership program in St. Petersburg, Florida. Many of the attendees were lawyers, bankers, and other professionals, who were generally foreign to the world of genetic cancer research. I was specifically asked to discuss how Moffitt Cancer Center is working to fight cancer through personalized medicine.

I was recently asked to speak to an audience of nonmedical adult participants enrolled in a leadership program in St. Petersburg, Florida. Many of the attendees were lawyers, bankers, and other professionals, who were generally foreign to the world of genetic cancer research. I was specifically asked to discuss how Moffitt Cancer Center is working to fight cancer through personalized medicine. 

Some of the questions I was asked following my presentation centered on the simple question: “Does this novel treatment paradigm actual work?" This is a very valid question and though I am a strong believer in the value of genetic tumor profiling, discussions at this meeting helped me to take a step back and assess the big picture and data supporting what I admit to believing is beneficial for patients with cancer.

The fact is that the novel nature of using tumor genetics to guide therapy and the rigor of the data we desire to support this treatment method results in less data currently published than we would like.

Ideally, we would have large prospective clinical trials that enrolled a population of patients with diverse cancers that demonstrated an overall survival advantage to selecting treatment based on tumor genetic findings. Even better would be economic data to support the method was cost effective and improved quality of life. The good news is those basket trials are enrolling and data should be forth coming. The bad news is it may be a while in coming and feasibility of enrolling on some of these kinds of trials has resulted in early closures and less than optimal outcome data (though still valuable data for future study designs).

Perhaps the first trial to support the use of molecular profiling of patients’ tumors to guide treatment was from Daniel D. Von Hoff, MD, FACP, and his team which was published in the Journal of Clinical Oncology in November 2010.1

This pilot trial of 86 heterogeneous cancer patients with advanced disease had molecular profiling of their tumors and treatment guided by the findings. To capture treatment benefit while appreciating the limitation of the heterogeneous patient population, each patient served as his or her own control, and the primary outcome was the progression-free survival (PFS) ratio (PFS on molecular directed therapy compared with PFS on the prior therapy not directed by molecular profiling). Clinical benefit was declared if this ratio was at least 1.3. A molecular target was identified in the tumor tissue of 98% of the 86 patients, and 66 of these patients received treatment directed by the molecular results. Of these 66 patients, 27% had a PFS ratio of > 1.3 (P < .007). Limitations of the study included the limited sequencing assessment and treatment options that were FDA-approved drugs only; not novel therapies in clinical trials.

The positive results of this study are encouraging, especially considering it was published in 2010, but it also needs to be replicated in larger sample sizes and reflect the sequencing platforms and current treatment landscape. Additionally, the novel endpoint of PFS ratio should be further interrogated in terms of meaningful clinical value. 

More recent data using more traditional endpoints describes experiences at MD Anderson and the University of California, San Diego.2, 3

In 1,144 patients treated at MD Anderson Cancer Center, 40.2% had one or more genetic alteration. In the 175 patients with only one genetic alteration, therapy directed by this alteration resulted in a higher overall response rate compared with the 116 patients who did not receive genetically matched therapy (27% compared with 5%, respectively, P < .0001). Additionally, patients who received genetically matched therapy had longer time-to-treatment failure (5.2 months vs 2.2 months, P < .0001) and longer median overall survival (13.4 months vs 9.0 months, P = .017). 

Finally, when looking at patients as their own controls, similar to the Von Hoff trial, genetically matched therapy was associated with a time-to-treatment failure of 5.2 months compared with each patient’s prior therapy of 3.1 months.2 In 34 patients treated at the University of California, San Diego, 11 patients had subsequent treatment directed by genetic tumor profiling and three of these patients achieved a partial response.Limitations of both of these trials included the heterogeneous population with varying types of cancer, prior therapies, and other characteristics that may impact response and survival to therapy.

Is this data convincing enough for my nonmedical conference attendees? Perhaps it’s enough to keep them following the story, but maybe not enough to totally buy in yet. Part of the excitement I have for using tumor molecular therapy to target a treatment-based decision is getting to be a part of its initial integration into care and the firm belief in the potential benefits it holds. However, it is important to consider the questions that will be asked and the need to build in methods of collecting efficacy data along with other important endpoints including patient quality of life, preferences in terms of how treatment decisions are made, and cost effectiveness data.

Passion can persuade, but solid data from quality science is essential to support the future of precision medicine initiatives like molecularly targeted therapy. It is my hope that the initiatives being reported as abstracts at national meetings today will yield the supportive data for which we are searching in the near future.

 

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