Virtual Tumor Model Allows Precision Treatment of Glioblastomas

Dr. Chirag Patil, MD American Board Certified Neurosurgeon, Brain & Spine Tumor Program Lead Investigator, Precision Medicine Initiative Against Brain Cancer Program Director, Neurosurgical Residence training program Director, Center for Neurosurgical Outcomes Research – Cedars-Sinai Medical Center, Los Angeles, California

Dr. Chirag Patil

MedicalResearch.com Interview with:
Dr. Chirag Patil, MD

American Board Certified Neurosurgeon
Brain & Spine Tumor Program
Lead Investigator, Precision Medicine Initiative Against Brain Cancer
Program Director, Neurosurgical Residence training program
Director, Center for Neurosurgical Outcomes Research Cedars-Sinai Medical Center, Los Angeles, California

MedicalResearch.com Editor’s note: Dr. Patil’s research is focused on developing a method of personalized cancer treatment through the harnessing of genome wide mutational analysis of a specific patient’s cancer.

MedicalResearch.com: Would you tell us a little about yourself and your research interests?

Dr. Patil: I am a Stanford-trained, Board Certified Neurosurgeon and cancer researcher at Cedars-Sinai Medical Center in Los Angeles, California. I primarily focus on the care of patients with malignant brain tumors, particularly glioblastomas. I received my undergraduate degree from Cornell, followed by a medical degree from the University of California, San Francisco (UCSF), where I was a Regent’s scholar. I completed a residency in neurosurgery and a fellowship in stereotactic radiology at Stanford University. I also have a master’s degree in epidemiology with a focus on clinical trial design and mathematical modeling from Stanford.

MedicalResearch.com: Can you tell us about some of your research interests?

Dr. Patil: I am keenly interested in and focused on developing precision science-powered novel brain tumor therapies, immuno-therapies, and patient-centered “big data” outcomes research. I lead the recently-funded Cedars-Sinai Precision Medicine Initiative Against Brain Cancer, which utilizes tumor genomics to build a mathematical computer model, i.e., a virtual cancer cell of each patient’s unique tumor. The White House and several other stakeholders have taken keep interest in this research initiative as an example of a leading precision medicine program.

The Cedars-Sinai program uses precision science to build a mathematical virtual brain tumorfor testing.

The Cedars-Sinai program uses precision science to build a mathematical virtual brain tumor for testing.

MedicalResearch.com: What is the background for the Precision Medicine Initiative Against Brain Cancer?

Dr. Patil: Glioblastomas are very aggressive cancers for which no cure has been developed. My patients usually die from their disease within a brief 15 months.

Until now, molecular diagnostic modeling of tumors has focused on finding one critical mutation that can be attacked with a targeted drug. However, it takes 300-500 mutations to make a cell cancerous. Cancer cells are adept at evolving quickly, much like bacteria, to allow a portion of the tumor to survive and thrive even if current treatments kill portions of the tumor.

My idea, that was brought to fruition with a collaboration with Cell Works, Inc., was to find a way to model all the mutations of a particular glioblastoma simultaneously, with the goal of using data from real tumors to find targets that can be effectively attacked.

Our precision science strategy has only been possible through an intense collaboration between academia and industry. We have brought together individuals with diverse expertise in cancer biology, software engineering, mathematics and pharmacology to holistically model most of the known cancer cell-signaling pathways.

MedicalResearch.com: Can you tell us more about how the process works? How long does it take? What does it cost?

Dr. Patil: The first step is to obtain tumor tissue from the patient and then to grow cells from that tumor in the laboratory. This is the most time-consuming part of the procedure.

We then make a ‘virtual tumor’ by using tumor genomics to build a mathematical model of most of the known cancer cell-signaling pathways.

Using this model we are able to simulate response predictions to the real patient’s tumor cells that have been growing in our laboratory in order to optimize treatment for each individual patient. Instead of a one-mutation, one-drug approach, we can model almost 200 drugs in combination to find the most effective therapy for that patient.

MedicalResearch: How many tumors are you currently evaluating?

Dr. Patil: We are currently evaluating our first five tumor samples. Over the next six months, we will have data on 25 additional brain tumor samples. These lab experiments will be followed by randomized clinical trial, comparing my Precision Medicine treatment algorithm to a current standard treatment regimen.

MedicalResearch.com: How long does the process take? What does it cost?

Dr. Patil: The process takes about eight weeks, although we think we can soon bring that down to about six weeks. It currently costs about $75,000 per patient, which is why we need the investment and assistance from industry as well as grants. However, this cost too should be reduced through economies of scale because after the in-Silico computer model is optimized and validated with these initial experiments, there would no longer be a need for growing the actual tumor.

MedicalResearch.com: What other uses do you foresee for this technique?

Dr. Patil: First, the technology will be applicable to other tumors besides brain cancer/glioblastomas. Other groups are working on related processes for lung and liver cancer as well as multiple myeloma.

In addition, the process should allow for the more rapid development of new therapies as ‘virtual’ targets are identified that could be attacked with the confidence that they will precisely affect a particular tumor pathway.

MedicalResearch.com: Thank you, Dr. Patil. We look forward to learning more about this exciting step forward in precision medicine as your work progresses. You can follow Dr. Patil and his precision science approach to treating brain tumors by visiting www.BrainTumorExpert.com.

References: (8 of 86 PUBMED citations for Dr. Chirag Patil)

  1. Surgery for spinal stenosis: long-term reoperation rates, health care cost, and impact of instrumentation.

Lad SP, Babu R, Ugiliweneza B, Patil CG, Boakye M.

Spine (Phila Pa 1976). 2014 May 20;39(12):978-87. doi: 10.1097/BRS.0000000000000314

2. Interspinous device versus laminectomy for lumbar spinal stenosis: a comparative effectiveness study.

Patil CG, Sarmiento JM, Ugiliweneza B, Mukherjee D, Nuño M, Liu JC, Walia S, Lad SP, Boakye M.

Spine J. 2014 Aug 1;14(8):1484-92. doi: 10.1016/j.spinee.2013.08.053.
Epub 2013 Oct 4.PMID:24291409

  1. Complications, reoperation rates, and health-care cost following surgical treatment of lumbar spondylolisthesis.

Lad SP, Babu R, Baker AA, Ugiliweneza B, Kong M, Bagley CA, Gottfried ON, Isaacs RE, Patil CG, Boakye M.

J Bone Joint Surg Am. 2013 Nov 6;95(21):e162. doi: 10.2106/JBJS.L.00730.

4. Racial disparities in outcomes of spinal surgery for lumbar stenosis.

Lad SP, Bagley JH, Kenney KT, Ugiliweneza B, Kong M, Bagley CA, Gottfried ON, Isaacs RE, Patil CG, Boakye M.

Spine (Phila Pa 1976). 2013 May 15;38(11):927-35. doi: 10.1097/BRS.0b013e31828165f9. PMID: 23232216

5. Disparities in the outcomes of lumbar spinal stenosis surgery based on insurance status. Lad SP, Huang KT, Bagley JH, Hazzard MA, Babu R, Owens TR, Ugiliweneza B, Patil CG, Boakye M.

Spine (Phila Pa 1976). 2013 Jun 1;38(13):1119-27. doi: 10.1097/BRS.0b013e318287f04e.PMID: 23354106

  1. Morbidity, mortality, and health care costs for patients undergoing spine surgery following the ACGME resident duty-hour reform

Babu R, Thomas S, Hazzard MA, Lokhnygina YV, Friedman AH, Gottfried ON, Isaacs RE, Boakye M, Patil CG, Bagley CA, Haglund MM, Lad SP.

J Neurosurg Spine. 2014 Oct;21(4):502-15. doi: 10.3171/2014.5.SPINE13283. Epub 2014 Jul 4.PMID: 24995600

  1. Multiple resections and survival of recurrent glioblastoma patients in the temozolomide era.

Ortega A, Sarmiento JM, Ly D, Nuño M, Mukherjee D, Black KL, Patil CG.
J Clin Neurosci. 2016 Feb;24:105-11. doi: 10.1016/j.jocn.2015.05.047. Epub 2015 Dec 5.|PMID: 26671314

  1. The Efficacy of Ketogenic Diet and Associated Hypoglycemia as an Adjuvant Therapy for High-Grade Gliomas: A Review of the Literature.

Varshneya K, Carico C, Ortega A, Patil CG.
Cureus. 2015 Feb 27;7(2):e251. doi: 10.7759/cureus.251. eCollection 2015 Feb. Review.
PMID: 26180675

 

Dr. Chirag Patil, MD (2016). Virtual Tumor Model Allows Precision Treatment of Glioblastomas