Targeting Cancer

Lung Cancer Molecular Disease Model Published in PLoS ONE

Jeff Shrager — Wed, 22 Feb 2012 19:07:38 +0000

A team including leading lung cancer researchers, and CollabRx scientists, has just published a novel Lung Cancer Molecular Disease Model in PLoS ONE, a leading peer-reviewed open source journal. (click here to read the published paper online). This is the model that underlies the CollabRx Lung Cancer Targeted Therapy Finder App.

Targeted Therapies Improve Prognosis for Lung Cancer Patients

Ben Kaplan — Thu, 16 Feb 2012 23:49:38 +0000

February, 2012 — CollabRx’s Lung Cancer Targeted Therapy Finder and Dr. Ravi Salga, chief editor and advisor for the Lung Cancer Targeted Therapy Finder, are featured in an article published by the University of Chicago School of Medicine as part of their Comprehensive Cancer Center’s lung cancer program.

OncLive: Targeted Therapies Yield Most Promising Results: A New Era in Melanoma Treatment Has Begun

Ben Kaplan — Thu, 09 Feb 2012 21:33:09 +0000

Melanoma is one of the most frequent cancers; more than 2 million Americans are treated for skin cancer annually. Although in its earlier stages, it can be easily cured by removal of the skin lesion, “once melanoma metastasizes to distant sites, it is highly resistant to therapy”, said Lynn M. Schuchter, MD, professor of Medicine, University of Pennsylvania School of Medicine, Philadelphia. Melanoma caused an estimated 8700 deaths in 2010. Indeed, chemotherapy for advanced melanoma has yielded poor 5-year survivals for patients with metastatic disease — 16% of those with metastatic melanoma survive 5 years post-diagnosis. Dacarbazine has long been the only drug approved by the FDA for treating metastatic melanoma, and it is often ineffective. In other words, the prognosis for patients whose melanoma has spread is generally poor, and very few therapies existed before 2011 that could make more than a marginal difference. Only recently have investigational products emerged that, alone or in combination, seem to yield positive responses in some patients.

Systems Cancer Medicine: Towards Realization of Predictive, Preventive, Personalized, and Participatory (P4) Medicine.

Ben Kaplan — Thu, 15 Dec 2011 21:38:40 +0000

J Intern Med. 2011 Dec 5. doi: 10.1111/j.1365-2796.2011.02498.x. [Epub ahead of print]
Tian Q, Price ND, Hood L.
Institute for Systems Biology

Excerpts from the abstract: A grand challenge impeding optimal treatment outcomes for cancer patients arises from the complex nature of the disease. Systems biology enables a comprehensive approach to medicine. [T]he mounting influx of global quantitative data from both wellness and diseases is shaping up a transformational paradigm we termed predictive, preventive, personalized, and participatory (P4) medicine. P4 medicine will have a profound impact on society – transforming the healthcare system, turning around the ever escalating costs of healthcare, digitizing the practice of medicine and creating enormous economic opportunities for those organizations and nations that embrace this revolution.

PMID: 22142401

Genetic Sequencing Could Help Match Patients with Biomarker-Driven Cancer Trials, Treatments

Ben Kaplan — Thu, 01 Dec 2011 21:29:15 +0000

ANN ARBOR, Mich. - As cancer researchers continue to identify genetic mutations driving different cancer subtypes, they are also creating a catalog of possible targets for new treatments. The University of Michigan Comprehensive Cancer Center and Michigan Center for Translational Pathology (MCTP) recently completed a pilot study aimed at solving the practical challenges involved in quickly and systematically sequencing genetic material from patients with advanced or treatment-resistant cancer in order to match them with existing clinical trials based on the biomarkers identified.

“We’re talking about more than just examining a few genes where mutations are known to occur, or even about a hundred genes,” says co-lead investigator Dan Robinson, Ph.D., a post-doctoral fellow at MCTP. “We’re talking about the ability to sequence more than 20,000 genes and look not just for individual genetic mutations, but at combinations of mutations.”

The exploratory study, known as the Michigan Oncology Sequencing Project (MI-ONCOSEQ), found that identifying a patient’s “mutational landscape” provides a promising approach for identifying which trials may best help a patient, the researchers say. Their findings were published today in Science Translational Medicine.