We are Changing the Way

The advances in science and technology have eliminated the fear of plague, but today another plague haunts mankind – cancer, which is becoming the number one killer in America. Fifty-five thousand researchers are employed in the pharmaceutical industry. Thirty-two Nobel Laureates have been awarded Nobel Prizes on cancer research. Millions of dollars have been spent, and yet this disease has not been eradicated. Why have we not succeeded? One of the reasons is reductionism. The development of a highly effective treatment regimen is hampered by the reductionist view of researchers who are trying to delineate the ideal molecular pathways to target for cancer treatment, and by a lack of tools to identify those patients who are most likely to benefit from any given therapy.

We are approaching a new era in cancer research as we now have the tools to mount a systematic assault on the hallmarks of cancer, both in terms of understanding the underlying interconnected pathogenic processes and devising high-impact therapies to treat cancer. The goal of our translational research is to explore new approaches for identifying cancer drug targets and provide practical considerations for the application of cancer therapies.

The Institute of Integrative BioOncology (I2B) is dedicated to advancing translational cancer research by bringing forward innovative and targeted therapeutic concepts into the clinical trial setting. The systems approach to complex biological problems has rapidly gained ground during the first decade of this century. Through a deep commitment to science, I2B is dedicated to defining the complex circuits of cancer cells at the systems level and to translating this knowledge into the development of novel anti-cancer cocktails that target all the hallmarks of cancer and lead to greater cure rates than those achieved with the fragmented and generic approaches currently is use.

One primary goal of our translational program is to foster development of the next generation of cancer treatment cocktails by bringing together a critical mass of physicians and researchers in a collaborative effort to devise state-of-the-art clinical studies.

At I2B, we perform innovative cutting-edge basic, clinical, and translational research. At I2B, this research is being translated from bench-side to bedside and then back to the bench. Disease-oriented research conducted at the cellular, molecular, and organ levels is being applied in the clinical setting and returned to the lab for refinement. Regular communications with extramural researchers worldwide bring together the best minds to present fresh, inventive approaches to tackle cancer in a rich collaborative environment.

Using Systems Biology Tools and Concepts in Cancer Cure

Understanding cancer and other such complex human disorders requires a systems biology approach. Systems biology, or integrative biology, in which high-throughput experimental and computational studies that address the complexities of host-disease-drug interactions are conducted, holds significant promise in the development and optimization of cancer combination therapies, including personalized therapies and the identification of biomarkers for monitoring the success of these strategies.

Systems medicine is a subset of systems biology related to human therapeutics. It is increasingly clear that the development of effective cancer treatments will have to consider the holistic approach from a systems or integrative biology perspective, rather than focusing exclusively on specific genes or proteins. It should take pathways and networks of pathways into account.

The increasing application of high-throughput technologies in oncology, such as DNA and protein microarrays and Next Gen deep sequencing, has fundamentally altered the methods used to analyze the molecular basis of cancer even in the clinical setting. These new technologies offer prospects of achieving personalized cancer treatment by finding the right drug for the right patient, as well as a drug-set or combinatorial cocktail for most common cancers.

The practice of modern oncology faces the challenge of matching the right therapeutics with the right patient, balancing relative benefit with risk to achieve the most successful outcome. The treatment guidelines proposed by the National Comprehensive Cancer Network (NCCN) based on current clinical trials used to serve as a “gold standard” for the administration and selection of therapy for cancer patients can be imprecise. Multiple potential regimens with roughly equivalent efficacies and side-effect profiles are often indicated for a patient population; yet, little guidance is provided on to the appropriate method for selection or prioritization of available choices. This is an especially relevant issue in many cancer treatment scenarios, given that there are often multiple regimens approved for use but without a clear superiority for any one agent or regimen. Although there is likely to be overlap in the sensitivities to the chemotherapeutic agents, it is also likely that there are distinct groups of patients predicted to be sensitive to a given agent. Systems medicine offer strategies to achieve truly personalized cancer treatment. In particular, the ability to develop gene expression signatures will likely allow us to guide the use of currently-available cancer drugs, develop new targeted therapeutics, and provide an opportunity to better match the most effective drug or drugs with the molecular characteristics of the individual patient.

The major limitation of chemotherapies and some targeted agents is our current inability to guide their use by identifying the fraction of cancer patients who will benefit from a given regimen based on their specific tumor biology. As an example, 70–80% of patients receiving cytotoxic therapy for lung cancer obtain little-to-no clinical benefit from their treatment. However, even in the so-called “negative” phase II clinical trials, complete remissions are some times seen in 1-3% of lung cancer patients. In this sense, these cytotoxic agents do have specificity to some extent, not necessarily for a biologic target but rather for a particular class of tumors. Therefore, there is an opportunity to improve cancer care by implementing methods that improve a physician’s ability to choose the appropriate therapy for each cancer patient. Gene expression patterns can help define specific tumor classes in a way that correlates directly with chemotherapeutic options.

Predictors of chemotherapy response provide an opportunity to guide the selection of a specific drug that is optimal for an individual patient. A number of studies over the past several years have sought to develop methods to predict who would respond to various chemotherapeutic drugs. Such prediction usually involves the analysis of tumor samples collected prior to treatment to identify gene expression profiles that can then be associated with the response.

An alternative strategy has made use of drug sensitivity data from patient cancer cells. However, so far in phase III patient cohorts treated with chemotherapy, the in vitro drug sensitivity assays have been unable to accurately predict the response of the patients to these drugs.

To better direct the use of chemotherapeutic agents in individual patients, we at I2B are taking a novel approach by incorporating the analysis of oncogenic pathways and in vitro drug sensitivity assays on cancer stem cells isolated from patient biopsy or blood samples. This combined analysis offers an opportunity to identify potentially new therapeutic options that target the most drug resistant tumor or cancer stem cells in a pathway-specific manner. One major value of this approach is the capacity to rationally design combinations of therapies using multiple drugs that target multiple pathways on the basis of genomic information that describes the status of the activity of specific pathways in cancer stem cells.

System Medicine for High-order Combinatorial Cocktails in Cancer Cure

 

Past clinical experience in cancer treatment indicates that combinations of drugs that act on different cellular targets sometimes demonstrate superiority over single agent-based treatments. Yet, these combined treatments are mostly based on empirical trials and lack, in many instances, a biological rationale. The older, empirical drug combinations are frequently no more effective and/or more toxic than monotherapy, thereby compromising the quality of life for little clinical benefit. Next generation cancer treatment must be based on drug combinations that target various pathways, illustrated by Dr. Weinberg as “hallmarks of cancer”, and cellular entities such as cancer stem and multi-drug resistant cells that sustain the survival of cancer cells after treatment. With this knowledge, we are developing efficient algorithms for the combination of drugs that target a set of proteins critical for sustaining cancer stem cells using high-throughput screening of combinatorial cocktails.