Meditations of an oncology geek

Archive for August, 2013

How Big Data Could Mitigate Cancer Drug Side-Effects

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22 August 2013

As an oncologist, when I sit with patients to discuss starting a new chemotherapy regimen, their first questions are often ‘How will it make me feel?’ and ‘How did patients like me feel with this treatment?’ Regrettably, this information is generally missing from U.S. drug labels and from published reports of clinical trials — the two information sources most commonly available to people trying to understand the clinical effects of cancer drugs.

-Ethan Basch

It’s no secret that the side effects of cancer drugs collectively suck. The dawn of genomics-driven therapies with fewer molecular targets means fewer side effects as well… in theory. And in theory, there is no difference between theory and practice. Even the newest, most directed therapies carry adverse side effects.

About a week ago I attended a clinical trials panel discussion at the UCSD Medical School featuring Robert Abraham of Pfizer Oncology and Elizabeth Barrett-Connor, professor of epidemiology at UCSD. Dr. Barrett-Connor expressed her frustration at both the relatively modest increases in lifespan of advanced cancer patients with most new targeted therapies (many among the order of magnitude of months) and the staggering cost, some around $10,000 per month.

However, Dr. Barrett-Connor was most upset by the extreme side effects of cancer therapeutics, and was adamant about actually weighing the benefit of lifespan against the cost and benefit to the patient. The FDA is most concerned with progression-free survival (PFS) and overall survival (OS) of cancer patients when comparing the efficacy of new drugs in clinical trials. Side effects are considered in the prevalence of (very) adverse side effects, and in subtracting PFS from OS there is some discerning quality of life, but this is quite certainly not enough.

Could there be more metrics used for quality of life? Could these be incorporated into the FDA’s guidelines for approval? Would this cause a shift in how drugs are made?

Ethan Basch produced a fantastic perspective article in the New England Journal of Medicine (1) available for free.

Basch also discussed the daily use of smart devices to prompt patients for temporally and structurally consistent quick surveys of their well being during trials, and ways to incorporate this data into easily accessible, more transparent forms.

Perhaps this could be taken a step further and incorporated into data (even if supplemental) for published clinical trials? Perhaps this might make oncologists more likely to prescribe drug A vs. drug B if drug A’s side effects were more available? Would this give the company producing drug A an upper hand in their market?

Personalized medicine aims to match patients with the best possible therapies based on factors unique to the patient like their endogenous genes and genes of diseased tissue. “Best possible” thus far has been severely biased toward PFS and OS. We must do a better job including side effects into these equations, and with a slightly different approach this can be a reality. As I touched upon last month, the technology exists to make big data based clinical trials.

Regardless of success or failure, the results from cancer clinical trials would be published (…) for future analysis to find trends not otherwise comprehensible without such a macro view. Items investigated could include:

1) What genetic profiles predict response to therapy or non-response??
2) Are there unforeseen similarities between cancer types??
3) Do mechanisms of resistance correlate between types of cancer and types of drugs?
4) Do these insights correlate with other defined risk factors??
5) Questions or correlations that have yet to be considered(!)

To that list I should add:

How do patient genetic profiles correlate with side effects to new drugs?

This information could be used to better tailor specific therapeutic regimens, and could allow oncologists more informed therapeutic recommendations for their patients.

The big data approach also allows accumulated data to become more valuable over time, as the sheer magnitude allows for macro view of trends and correlations not normally visible with smaller sample sizes. Data to discern adverse effects from drugs could go from sample sizes of dozens to tens of thousands. It also allows for meta-analyses for queries not yet considered as well. For example, it could identify a rare genetic group that has no side effects to drug A, and allow for prescription of more cycles of therapy, or fewer additional drugs.


1. Basch E. Toward patient-centered drug development in oncology. The New England journal of medicine. 2013 Aug 1;369(5):397-400. PubMed PMID: 23822654. Epub 2013/07/05. eng.

Written by Ryon

August 21st, 2013 at 5:06 pm

Posted in Science Blog

The first anti-metastatic drug for young women?

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15 August 2013

Mini-Review Research Commentary

The first drug that specifically targets the spread of breast cancer metastasis might be on the horizon. I’m particularly excited about this, because:

1) It’s a therapy for young mothers affected by pregnancy-associated breast cancer.
2) The drug(s) are already FDA approved, inexpensive, and have well-tolerated side effects.

Breast cancer affects an average of 1 in 100 women age 60+ in the U.S. every year, and through a confluence of awareness campaigns and morbid prominence it has found its way deep into the public psyche. With an aging population, we expect to see an increase in incidence in the coming years. Though advanced genomic techniques we know that breast cancer has at least several distinct genetic subtypes (1) that have been exploited by a new generation of targeted therapies. There have been great advances in controlling or even curing the disease in some patients, and the American Cancer Society has been reporting a decline in deaths from breast cancer for years now (2).

Although breast cancer affects mostly older women (3) there is a sinister twist for those that develop the disease younger. Or rather, those diagnosed within five years of their last pregnancy. Those that have young children in tow.

Pregnancy-associated breast cancer (PABC) has an unusually high incidence metastases to the liver, lungs, bones, and brain, making therapy very difficult. At two sites in Colorado between 1984 and 2001, Callihan and colleagues combined data from 619 women diagnosed with breast cancer under the age of 45 in a retrospective cohort study, and found that those diagnosed within 5 years of their last pregnancy had a three-fold higher risk of developing metastases (31.1%), and roughly a 60% chance of survival after 5 years, opposed to a nearly 100% 5-year survival for nulliparous women (4). Image adopted from Callihan et al. 2013

The epidemiological data indicates that an event associated with pregnancy, but independent of growth-promoting gestational hormones, promotes the elevated PABC metastasis: PABC does not correlate with tumor size, stage, nodal status, estrogen receptor status, or HER2 expression (5). In an elegant review article in Nature Medicine, Schedin proposed a mechanism by which spatial reorganization of breast tissue during involution (natural tissue re-organization program of the breast after a period of lactation) allows access of premalignant cells to mesenchymal cellular compartments in the breast that might not otherwise have access to, also hypothesizing that this might tip the delicate scale of anti- and pro- inflammatory signals toward the latter, promoting the release of proto-tumorigenic cells from their endothelial compartments (3).

In a series of elegant experiments, Schedin’s group spent years investigating this phenomenon and found that ductal carcinoma in situ (DCIS, usually considered a low-grade tumor) actually can be driven to seed the lungs postpartum by mammary involution (6). Lyons and colleagues found that remodeling of extracellular matrix proteins post-lactation was mediated by the COX-2 signaling pathway, and that the enhanced cancer spread to the lungs could be mitigated by NSAID’s, including celecoxib (Celebrex) and ibuprofen (Advil).

So, could ibuprofen or celecoxib be an effective anti-metastatic drug for women with DCIS postpartum? A clinical trial (NCT01881048) is currently underway to test this at the University of Colorado Denver, and the results should be available soon!

This could be a boon to young mothers fighting breast cancer. Visceral emotional tug aside, this is an interesting innovation, because this approach to therapy targets a process specific to breast cancer metastasis. All other advanced breast cancer therapies that have arrived in the clinic in the last decade target all breast cancer cells, not the most deadly subset: the seeds that will form the weeds of metastases. If the results from this clinical trial come through and the NSAID’s are validated, it opens the door for these to be used synergistically in conjunction with existing drugs, because they target different mechanisms and because we already have extensive knowledge of NSAID cross-reactions with other drugs.


1. Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 2012 Jun 21;486(7403):346-52. PubMed PMID: 22522925. Pubmed Central PMCID: PMC3440846. Epub 2012/04/24. eng.
2. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA: a cancer journal for clinicians. 2013 Jan;63(1):11-30. PubMed PMID: 23335087. Epub 2013/01/22. eng.
3. Schedin P. Pregnancy-associated breast cancer and metastasis. Nature reviews Cancer. 2006 Apr;6(4):281-91. PubMed PMID: 16557280. Epub 2006/03/25. eng.
4. Callihan EB, Gao D, Jindal S, Lyons TR, Manthey E, Edgerton S, et al. Postpartum diagnosis demonstrates a high risk for metastasis and merits an expanded definition of pregnancy-associated breast cancer. Breast cancer research and treatment. 2013 Apr;138(2):549-59. PubMed PMID: 23430224. Pubmed Central PMCID: PMC3608871. Epub 2013/02/23. eng.
5. Daling JR, Malone KE, Doody DR, Anderson BO, Porter PL. The relation of reproductive factors to mortality from breast cancer. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology. 2002 Mar;11(3):235-41. PubMed PMID: 11895871. Epub 2002/03/16. eng.
6. Lyons TR, O’Brien J, Borges VF, Conklin MW, Keely PJ, Eliceiri KW, et al. Postpartum mammary gland involution drives progression of ductal carcinoma in situ through collagen and COX-2. Nature medicine. 2011 Sep;17(9):1109-15. PubMed PMID: 21822285. Epub 2011/08/09. eng.

Written by Ryon

August 15th, 2013 at 9:05 pm

Posted in Science Blog

A guest column in Beaker

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14 August 2013

This morning I had a guest column published in Beaker, the award-winning science blog of the Sanford-Burnham Medical Research Institute.

I was asked to offer my thoughts on the process of science and discovery, and first thing that came to mind was a quote by Samuel L. Clemens (Mark Twain):

“A man who carries a cat by the tail learns something he can learn in no other way.”

More here.


Written by Ryon

August 14th, 2013 at 11:14 am

Posted in Science Blog