Curious Dr. George | Plumbing the Core and Nibbling at the Margins of Cancer

Generic Drugs vs. Biosimilar Biologics

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Y. Tony Yang, ScD, LLM, MPH., Associate Professor, Department of Health Administration and Policy, George Mason University, Fairfax, Virginia. Charles Bennett, MD, PhD, M.P.P., Smart State and Frank P and Jose M Fletcher Chair, Medication Safety and Efficacy, Smart State Center of Economic Excellence, University of South Carolina and the Hollings National Cancer Institute Designated Cancer Center of the Medical University of South Carolina, Charleston, South Carolina.

Q: Are biosimilars the same as generic versions of biologics? Will they be approved by the FDA? Are they safe? Are they cheaper? What about the intellectual property rights of the manufacturer of the reference biologics? If they are only slightly less expensive than the reference biologics, why would anyone prescribe them- particularly if we are not certain that they are as safe as the reference biologic?
A: Biosimilars are NOT generic versions of biologics. Biosimilars are HIGHLY SIMILAR to the reference product they were compared to, but have allowable non-clinical differences. Differently, generic drugs are copies of brand-name drugs, have the identical active ingredient, and are the same as those brand name drugs in dosage form, safety, strength, route of administration, quality, performance characteristics and intended use. Biosimilars are produced from a living organism; therefore, it is impossible to produce an exact copy of the reference biologic. Two biosimilars are approved in the U.S. as of July 2016: one is marketed (Zarxio, a Neupogen biosimilar) and the other is involved with patent litigation (a Remicaide biosimilar approved in April). A third and fourth biosimilar received unanimous votes in July of support from FDA’s Arthritis Advisory Committee (a Humira and an Enbrel biosimilar) although patent litigation may occur before marketing is allowed to begin.
For years, biosimilars have been approved and safely used by patients in Europe, Japan, Australia and other countries. While the regulations for approval are similar internationally, Europe has been way out in front on approving biosimilars and the U.S. is just entering this market. The biosimilar approval in developed countries relies on each country’s regulatory agency’s previous findings that the agency-approved reference biologic is safe and effective.
Although biosimilars in the U.S. are not expected to provide the 70-80 percent savings we have seen with traditional generics, biosimilars have historically cost at least 20-30 percent less than the reference product, which can cost over $100,000 per year. Zarxio came to market in the U.S. at a 15 percent lower cost than its reference biologic. That implies the price differential between a biologic and its biosimilar is more likely to approximate the competition in a multi-brand category of drugs rather than between a reference drug and its generic. Nevertheless, these cost savings from biologics help give patients access to these complex drugs. By improving access to biologics through biosimilars, more patients have the potential to receive life-changing treatments. The reduced cost of biosimilars will also lead to substantial cost-savings in the broader healthcare market. Although it remains to be seen as the biosimilar pipeline continues to mature in the U.S., it is estimated that the U.S. health care system has the potential to save up to $250 billion by 2024. These savings create resources to enable access to other innovative treatments, improving the lives of all patients.
Biosimilars were first allowed under the Biologics Price Competition and Innovation Act (BCPIA), a section of the sweeping 2010 Affordable Care Act. The BPCIA acknowledges the significance of promoting innovation, but it also provides a pathway for competition once monopoly protection ends. Biologics can acquire patent protection, which lasts for 20 years from the date the patent application is filed. The BPCIA stipulates a 12-year market exclusivity and a 4-year data exclusivity beginning when the biologic drug secures FDA marketing approval. Each exclusivity can be extended 6 months for pediatric applications. A biosimilar cannot be marketed until the 12-year exclusivity expires. These exclusivity protections are designated to stimulate biologic research and development. However, if the politically controversial Trans-Pacific Partnership between the U.S. and 11 other Asia-Pacific countries is approved, exclusivity could drop to 5 years. Stay tuned and the next few years should be exciting times for biosimilar approvals and uptake in the U.S.
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Curious Dr. George | Plumbing the Core and Nibbling at the Margins of Cancer

Driver and Passenger Mutations in Cancer Cell Genes

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Michelle Turski, PhD, Senior Scientific Knowledge Engineer, CollabRx

Q: What are the similarities and differences between “driver” mutations and “passenger” mutations and in what common malignancies is that distinction most important?
A: The commonly accepted definition of a driver mutation is a mutation within a gene that confers a selective growth advantage (thus promoting cancer development), while passenger mutations are those that do not provide a growth advantage. Independent of context, the type of mutation observed is not a factor in differentiating between a driver versus a passenger mutation. However depending upon whether the driver gene is classified as an oncogene or tumor suppressor, the type of mutation observed can play a role in determining whether it is a driver or passenger. For instance, driver mutations in oncogenes tend to be missense mutations at specific codons or focal amplifications, while nonsense or frameshift mutations or focal deletions are often the hallmark driver mutation type in tumor suppressors. Driver mutations have a tendency to occur in protein-coding regions of genes and within important functional domains of the protein, although it’s increasingly being recognized that non-coding mutations, like splice-site or promoter mutations, can also be driver mutations. Thus, using mutation location as a discriminatory factor may be becoming a less reliable indicator of whether a mutation is a driver or passenger. Additionally, driver mutations are often somatic in origin, with germline mutations often fast-tracked to the passenger bucket; however, a cautionary note should be inserted here as there are very clear examples of where germline mutations are driver mutations (e.g. BRCA1/2 in familial breast and ovarian cancer or TP53 mutations in Li-Fraumeni syndrome).
In terms of the ‘how’, there are generally two methods or approaches to classifying a mutation as a driver or passenger: 1) by frequency (driver mutations should be mutated in a greater proportion of cancer samples than would be expected from the background mutation rate) and/or 2) by prediction of functional impact (either via in-silico algorithms or cell/model-based assays). Each method is fraught with caveats and disadvantages or challenges, however the gold standard of evidence that a mutation is a driver is experimental evidence demonstrating that the mutation produces a cellular phenotype that provides a selective growth advantage to the cell. Thus, importantly, bioinformatic methods cannot provide definitive classification of mutations as either driver or passenger but can be a means by which to prioritize mutations for functional testing.
Because driver mutations are by definition those resulting in cancer initiation and/or progression, they are seen as the ‘achilles’ heel’ of tumors, sought after as targets for drugs, and used in making therapeutic decisions. Thus, being able to make distinctions about whether a mutation is driver or passenger is important for any malignancy. However, being able to make this distinction is harder in some cancer types than others. For example, lung cancer has a much higher mutational burden than acute myeloid leukemia (AML), which makes the identification of driver mutations in lung cancer more difficult than in AML. Passenger mutations perhaps shouldn’t be dismissed entirely, as emerging data and theories suggest that passenger mutations can transform into driver mutations (so-called “latent drivers” or “mini-drivers”, amongst other proposed terms), especially within the context of resistant and/or recurrent disease. However given the high number of passenger mutations usually present in tumors, it will be hard to discriminate between those passengers likely to ‘stay put’ and those with hidden driver potential, requiring more investigative studies.
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Curious Dr. George | Plumbing the Core and Nibbling at the Margins of Cancer

Patients and Physicians Should Share Decisions in Oncology

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Brian Klepper, PhD, CEO and Founding Principal of Health Value Direct

Q: Many of us have been touched by the publication of your sensitive but serious criticism of your wife’s care once her ultimately lethal peritoneal cancer had spread. How do you propose that oncologists, patients and their families should best practice “shared decision making”?
A: Sad but true, most cancer patients today unknowingly enter highly conflicted treatment environments where, as a practical matter, the ideal of shared decision making may run counter to the provider organization’s interests. Cancer care is such lucrative business that more than one in four health systems is now building a cancer center. Physicians or the health systems they work for typically profit from the drugs they prescribe, which often lack evidence of efficacy. These vectors often result in care decisions that accrue more to the health system’s than the patient’s benefit.
Patients should assume that their physicians have their best interests at heart but, in complicated, unfamiliar territory, insist on asking hard questions. Doctors are increasingly aware that their role includes making patients aware of their options, but they, like all of us, may also have inherent biases that manifest in what treatments they urge for their patients.
Physicians can be optimistic about outcomes and patients may be unreasonably hopeful, so an honest evidence-based assessment of current realities is critical. What benefits will the treatment realistically buy the patient and how much of an ordeal will it induce? What are the odds of success and what, exactly, is the definition of success in each case? The goal is to arrive at care decisions based not just on abstract notions of what works better, but on results that will be meaningful to the patient’s and family’s lives.
Treatments that buy a few extra days or months may not be worth it if adverse effects make that additional life miserable. And palliative care data over the past few years has shown that stopping after failed 1st or 2nd line chemotherapy often lengthens life by 2-3 months and improves quality of life over conventional therapy.
It would be particularly useful to know whether the vast majority of cancer patients who have gone through aggressive therapy and are about to die believe in hindsight that it was worth it. That voice of experience would be critical new information for patients, and validate or counter many physicians’ arguments that they prescribe all-but-hopeless treatments because many patients demand any chance. Of course, studies are less fundable when they aspire to less treatment and are not in the care community’s financial interests.
In Being Mortal, Atul Gawande MD’s profound and wonderful book, he presents 5 questions for patients at the end of life, developed by Susan Block, a palliative care physician at the Dana Farber Cancer Institute in Boston.

  1. What is your understanding of where you are and of your illness?
  2. What are your fears about what is to come?
  3. What are your goals as time runs out?
  4. What tradeoffs are you willing to make?
  5. What would a good day look like?

The beauty of these questions is their deep humanity. They clarify the patients’ understanding, worries and priorities for the patient and family, and help clinicians know what matters most to them. My wife Elaine referred to them as “perfect questions.”
In British Medical Journal, Richard Lehman MD sums up the shared decision making problem this way. “We urgently need every paper about a new oncology drug trial to incorporate a comparative infographic, compiled by an independent author from the individual patient data. This could probably be done for the same cost as a single course of the treatment.”
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Curious Dr. George | Plumbing the Core and Nibbling at the Margins of Cancer

Targeted Therapy for Waldenstrom’s Macroglobulinemia

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Javier Munoz MD, FACP, Hematologist/Oncologist at Banner MD Anderson Cancer Center in Gilbert, AZ and Hematology-Oncology Adjunct Assistant Professor at the University of Texas MD Anderson Cancer Center in Houston TX

Q: A 76-year-old male is referred to you. His labs at presentation showed anemia and elevated immunoglobulin M. A bone marrow biopsy showed lymphoplasmacytic lymphoma with MYD88 gene mutation. He received a rituximab-based chemotherapy regimen frontline although his disease relapsed with worsening anemia and increased Ig M levels. The patient has no siblings. How do you manage his care?
A: My recommendation at this point would be to prescribe the Bruton tyrosine inhibitor (BTK) ibrutinib. The U.S. Food and Drug Administration granted accelerated approval to ibrutinib (420 mg daily) for patients with lymphoplasmacytic lymphoma in 2015. Clinical response correlates with the presence of mutations in the MYD88 and CXCR4 genes which are commonly seen in this hematologic condition.
What is the difference between Waldenström’s macroglobulinemia (WM) and lymphoplasmacytic lymphoma?
There are some differences even though the terms are used interchangeably by some. Lymphoplasmacytic lymphoma is a neoplasm of small B lymphocytes, plasmacytoid lymphocytes, and plasma cells that usually involve the bone marrow. Waldenström’s macroglobulinemia is a lymphoplasmacytic lymphoma with bone marrow involvement and monoclonal immunoglobulin M of any concentration. This particular case is better defined as WM.
What is the molecular basis for using ibrutinib in WM?
Whole genome sequencing has revealed highly prevalent somatic mutations in WM. MYD88 L265P is highly present in patients with WM and supports malignant growth via signaling involving BTK. Ibrutinib inhibits BTK and induces apoptosis of WM cells bearing MYD88. WHIM-like mutations in CXCR4 are also present in patients with WM, and their expression induces BTK activity and confers decreased sensitivity to ibrutinib.
What is the expected clinical response to ibrutinib in patients with WM?
The overall response rate was 90% in the original paper by Treon et al; and the highest responses were seen in patients with MYD88 mutation (100%). It is expected the hemoglobin will increase and the immunoglobulin M will decrease in this patient after exposure to ibrutinib.
Do you see any novel possibilities for targeted therapy in hematologic diseases?
We have been trying hard to emulate the imatinib story in CML that would work just as well in other malignancies but it has been very difficult to do so. There are case reports and some ongoing clinical trials trying to match a medication to a particular mutation in hematologic diseases. BRAF mutations have been reported in patients with lymphoma, leukemia, and multiple myeloma. Particularly, BRAF mutations are extremely frequent in patients with Hairy cell leukemia and we may have a therapeutic signal with BRAF inhibitors in such condition with clinical trials underway. MYD88 mutations have been reported in patients with lymphoproliferative disorders as lymphoplasmacytic lymphoma and Diffuse Large B-Cell Lymphoma (particularly the activated B-cell subtype). Some medications, as the BTK inhibitor ibrutinib, seem to work better in patients with WM that carry MYD88 mutations as explained above. Immunotherapy is currently stealing the show across the board in multiple malignancies but responses are not necessarily ever-lasting. Immunotherapy as checkpoint inhibitors have been said to “release the brakes” of the immune system. We need to support rationally-designed trials to overcome resistance to single-agent therapy so perhaps combination studies of immunotherapy plus targeted agents may be a possible avenue for progress in this field.
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Curious Dr. George | Plumbing the Core and Nibbling at the Margins of Cancer

Using Patient Navigators to Improve Cancer Care

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Valerie Fraser Cancer Research Advocate/­Patient Navigator;
Inflammatory Breast Cancer International Consortium (IBC-IC)
Huntington Woods, Michigan

Q: What are Patient Navigators and why are they sometimes necessary for some cancer patients. How do the best programs work?
A: As precision medicine, information technology and an increasingly savvy internet society merge, there will be a greater expectation that patients be involved, informed and engaged with their healthcare team. Navigators will be pivotal in this process, both those that are within the healthcare system and increasingly those that are lay navigators outside of the system. Lay navigators are often resourceful survivors or caregivers themselves, experienced in research and the health care process, with critical skills, resources and most importantly the “heart connection” that patients will need throughout their cancer experience.
Accessing resources and seeking quality care for those diagnosed with cancer is a demanding and complicated process. A patient’s survival can be impacted by critical decisions, so there’s the pressure to get it right. The reality of receiving a cancer diagnosis begins with an avalanche of emotion, anxiety and uncertainty both for the patient and their family. Many patients will inevitably encounter barriers along the way and face important crossroads critical to their care. Often they will feel buried and paralyzed under the weight of a system focused on time and process and may feel uncomfortable with their ability to question or evaluate the process. With multiple experts and treatments involved, it is often difficult to transition levels of care. Many also experience long term side effects following treatment, impacting their transition from patient to survivor.
Patient navigators are resourceful problem solvers there to guide patients through a difficult experience often never encountered before. They help to prevent and eliminate barriers to quality care and treatment, locate resources and often act as a communication liaison between the patient and the care team. A navigator can help support patient satisfaction through their compassionate guidance, often having first hand experience as a cancer patient themselves, resulting in improved quality of care and overall outcomes. Navigators are also self-advocacy educators and encourage patient empowerment improving a patient’s overall outlook, engagement and quality of life. Studies have shown this is often a win-win for the patient, their care team and their treating institutions.
The best navigation programs are those that are resource and information rich and designed from a patient perspective. A navigation program must be adaptable and broad so as to provide the best information, resources and guidance while at the same time engage and empower patients in the process. Personalized needs assessment and evaluation of patient satisfaction throughout the navigation intervention supports optimal outcomes. As addressed in the landmark 2005 IOM report “From Cancer Patient to Cancer Survivor: Lost in Transition” the key components of delivering high quality cancer care must include patient needs, values, preferences and engagement with the care process.
Cancer is unwanted, unplanned, unscheduled and a very personal experience for those diagnosed. Patients are faced with critical decisions while dealing with overwhelming stress. A navigation plan must be designed around the individual and their unique needs. The best programs will be focused on clearing away barriers and uncertainty while rebuilding a pathway to patient empowerment and survivorship.
Patient Navigation is a rapidly growing and evolving industry especially in cancer care. A patient navigation requirement is now part of the Commission on Cancer institutional accreditation to ensure patient-centered care. Health care institutions and cancer centers developing their programs, often assign nurses to fill these positions who focus on patients at that particular institution. Salaries for Oncology Nurse Navigators can average anywhere from $67,000+ annually . Private/Professional Patient Navigators work independently as consultants with various organizations and individually one-on-one with patients. Their fees are often hourly and can vary based upon the scope of their services, demographics, background and experience, etc..
Patient Navigators are filling important roles in an increasingly complex cancer health care system. Their involvement in patient-centered care will undoubtedly continue to grow and add value to a health care system striving to better serve their cancer patients. However, their real impact will be in the immeasurable value they provide to patients and families on the receiving end of a life threatening cancer diagnosis often overwhelmed and lost in the maze of the cancer experience and process.
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Curious Dr. George | Plumbing the Core and Nibbling at the Margins of Cancer

CollabRx and the 2016 Cancer Moonshot

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George Lundberg, MS, MD, ScD, MASCP, FCAP, Chief Medical Officer and Editor in Chief, CollabRx, a Rennova Health Company; Editor at Large, Medscape; Executive Adviser, Cureus; Consulting Professor of Pathology and Health Research and Policy, Stanford University; President and Chair, The Lundberg Institute; @glundberg

Q: Did the CollabRx vision of 2008-2010 foretell the 2016 Cancer Moonshot?
A: True history is difficult to confirm. Its representation depends in large part on who recorded “his-story.” Even Socrates, who, amazingly, did not himself write, is known mostly because of the extensive writings by his students.
Did Richard Nixon, in declaring “War on Cancer” in 1972, calling for vast research to find a cancer cure foretell the Obama-Biden 2016 “Moonshot”? Perhaps, since it also was a presidential decree.
It takes many threads to weave a tapestry.
Jay Martin (Marty) Tenenbaum PhD, himself both a former Stanford professor and pioneering internet entrepreneur as well as a metastatic melanoma survivor, founded CollabRx as a privately held, for profit company in 2008.
When Marty conceived CollabRx, he envisioned breaking down the silos of process that inhibited movement of positive research results from “the bench to the bedside” to enable a far shorter time than the extant 16 years. Blending-merging the wonders of advanced information technology and the Internet with the increasing wonders of molecular oncology was to be the method.
The goal was always to “defeat cancer, one patient at a time.”
Jeff Shrager, PhD (still with Cancer Commons) and Smruti Vidwans, PhD (still Chief Science Officer of CollabRx) were early hires.
John Wilbanks (an initial CollabRx Editorial Advisory Board member) is credited with founding “Science Commons” in 2006, as a part of the Creative Commons concept.
Wilbanks and Tenenbaum announced/described “Health Commons” in June 2008.
John Niederhuber, MD, Director of the National Cancer Institute, in the March 17, 2010 issue of JAMA, published “Translating Discovery to Patient Care”, nicely summarizing many of these cancer issues and opportunities. He left the NCI Directorship in July 2010.
From 2004-2011 caBIG was an NCI program that was envisioned to accomplish many of the goals described by Niederhuber and envisioned by Tenenbaum. But after spending >$350 000 000 with little to show for the money, caBIG was replaced.
I joined CollabRx on March 2, 2010.
On April 1, 2010, I participated in an Institute of Medicine program in Washington, DC on “The Learning Healthcare System in 2010 and Beyond”. I mentioned the CollabRx and Cancer Commons concept in my lecture and many people expressed interest.
Tenenbaum, Shrager and I announced Cancer Commons in MedPage Today on July 12, 2010. “The goal of Cancer Commons is to provide patients and physicians with the latest information, tools and resources they need to obtain the best possible outcome and to capture and aggregate the results over all studied patients to improve cancer treatment generally.”
The first real product of CollabRx (in addition to appointing dozens of stellar collaborating editorial board members) was the PLOS ONE paper “A Melanoma Molecular Disease Model” (MDM) on March 30, 2011. This paper portrayed a model describing how to envision cancer by genomes, mutations, and pathways. Harvard’s Keith Flaherty and David Fisher teamed with Smruti Vidwans and other CollabRx authors in this groundbreaking effort.
In order to enable utilization of the new MDM, we harked back to the May 5, 1975 beginning of The JAMA series called “Toward Optimal Laboratory Use” (TOLU) which introduced the concept of algorithms and decision trees and tables to physicians that truly did foretell CollabRx “Therapy Finders.”
Following the TOLU model, CollabRx invented “User Guides” for physicians and patients to use as open access interactive web apps at www.collabrx.com, subset Melanoma Therapy Finder
intended to facilitate shared decision making by patients and physicians together at this most difficult time, dealing with advanced cancer. Lung cancer, colorectal cancer and breast cancer web apps followed. The CollabRx Therapy Finder concept incorporated the new biomarkers, recognized practical therapeutic onco-genomics and was based upon cancer site/organ of origin.
On April 1, 2011, The Scientist Magazine (Sarah Green editor) published my “Thought Experiment” called “Medical Publishing for an N of One.” I, an aficionado of large-scale clinical trials as the gold standard for evidence in medicine, had completely acquiesced to the notion that cancer is thousands of different possibly unique diseases with mutational and other …omic designators.
Parallel to these developments, CollabRx science, led by Vidwans, also invented and built a complex, deep, up to date and highly automated Genetic Variant Annotation (GVA) Service that can be agnostic to organ of cancer origin and utilized a “Pan-Cancer” genomic approach, with a different kind of editorial board called “Pan Cancer” headed by Razelle Kurzrock. The GVA is intended to bridge the interpretation-action gap between the NGS laboratory findings and the practicing physician.
In 2012 CollabRx was acquired by Tegal (which adopted the CollabRx name) and moved to San Francisco. New CEO Thomas R. Mika. Cancer Commons by this time had transitioned from a not for profit initiative into a 501c3 corporation and remained in Palo Alto with Tenenbaum.
By 2014, CollabRx announced a new product, CancerRx, as a mobile app extension of the previously exclusively web-based Therapy Finder apps.
There can be little doubt but that the well funded and widely publicized ASCO product called CancerLinQ formally launched in 2016 after years of planning draws heavily in concept from the early thinking of Cancer Commons.
Listening in person to Vice President Joe Biden exhort the ASCO membership in June 2016 to cooperate, collaborate, break down the silos, share, place beating cancer ahead of promoting your institution, company, career, financial gain, etc. sounded a great deal like Marty and me exhorting the IT planning leaders of ASCO in Alexandria, VA in April 2010, and others subsequently, to help us bring the CollabRx and Cancer Commons visions to reality.
We can all hope that the upshot of the Joe and Jill Biden call to double the rate of progress in the fight against cancer (10 years compressed into 5) has a better outcome for many cancer patients, and not only for the American Cancer Industrial Complex, than did the war declared by Richard Nixon in 1971.
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Curious Dr. George | Plumbing the Core and Nibbling at the Margins of Cancer

Sun Exposure and Skin Cancer Risk

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David Polsky, MD, PhD, Professor of Dermatology and Pathology;
Alfred W. Kopf, MD, Professor of Dermatologic Oncology; Director, Pigmented Lesion Section; The Ronald O. Perelman Dept of Dermatology; New York University School of Medicine; NYU Langone Medical Center

Q: Summer sun season is upon us. What role, if any, does sun exposure have in the causation of cutaneous: 1) Actinic keratosis? 2) Squamous cell carcinoma? 3) Basal cell carcinoma? 4) Malignant melanoma? How completely should humans try to eliminate sun exposure lifelong?
A: The potential health effects (both benefits and harms) of sun exposure have been the subject of much controversy over the last 100 years. In the early 20th century when dietary sources of vitamin D were more limited, sun exposure was thought to promote both bone health and optimal health overall. Early epidemiologic studies, and later laboratory investigations demonstrated a definitive causal link between ultraviolet light exposure (i.e. the damaging wavelengths from sunlight) and skin tumors. Unfortunately, the genie was out of the bottle, and everybody wanted to be tan due to the mistaken belief that it was a sign of good health.
Interestingly, the contribution of sun exposure in different skin cancers varies.
Actinic keratosis: These extremely common skin growths are potentially pre-cancerous pre-cursors of squamous cell carcinoma. They occur on the same skin sites as squamous cell carcinoma (described below) and have a high rate of ultraviolet light-induced mutations.
Squamous cell carcinoma: This malignant tumor has the most direct relationship between sunlight and cancer. These growths occur on the face, arms and hands; skin sites that have received high cumulative levels of sun exposure. In addition, epidemiologic studies found a strong association of squamous cell carcinoma and outdoor occupations. Ultraviolet light-induced mutations are seen in more than 80% to 90% of these growths.
Basal Cell Carcinoma: This skin cancer is also linked to sun exposure, but not as directly as squamous cell carcinoma. The rate of ultraviolet light-induced mutations is lower in basal cell carcinoma than squamous cell carcinoma, and some studies suggest that skin cells’ ability to repair ultraviolet light-induced DNA damage is critical in preventing basal cell carcinoma. In contrast to squamous cell carcinoma, intensive sun exposure in childhood and adolescence may play an important role in basal cell carcinoma.
Cutaneous melanoma: While most cases are clearly caused by sunlight, melanoma is a heterogeneous disease. Some forms are associated with long-term chronic sun exposure; the more common form is associated with indoor occupations and intermittent, intense sun exposure (i.e. sunburns) in childhood and/or adulthood. Rare forms that occur on mucosal surfaces and the palms and soles are unlikely to be associated with sun exposure. Besides sun exposure related risk factors, having a large number of moles and/or atypical/dysplastic moles/nevi is even more important in identifying individuals with an increased chance of developing melanoma.
So how completely should humans try to eliminate sun exposure lifelong, and what are the most effective methods? Clearly sun exposure contributes to all forms of skin cancer so individuals, especially those with fair skin should protect themselves. Patients with light skin and hair color have higher risks because they have relatively low levels of the skin pigment melanin that protects skin cells from sun-induced DNA damage. Patients with lower levels of melanin sustain more DNA damage per minute of sun exposure than darker skinned individuals. To reduce skin damage caused by ultraviolet light, protective clothing should be the major strategy (e.g. long sleeves, long pants, hat, etc.). Nowadays, specialized lightweight sun protective clothing is available for different types of activities (e.g. water sports, golf, hiking, etc.). For skin that cannot be covered by clothing, use a high SPF, broad-spectrum sunscreen. SPF means sun protection factor, a measure of how well a sunscreen blocks ultraviolet B radiation, the wavelengths that cause sun burn. While SPF numbers roughly translate into how many times longer you can stay in the sun without burning, most people apply less than half the amount used to develop the numbers. Also sunscreens may lose effectiveness throughout the day. Experts typically recommend an SPF of at least 30 to insure a minimal level of protection. ‘Broad spectrum’ sunscreens have ingredients that also block ultraviolet A radiation which contributes to skin cancer and photoaging but doesn’t cause sunburns. Apply sunscreen generously in the morning and at midday to insure adequate sun protection throughout the day. Finally, planning outdoor activities to avoid the midday sun between 10AM and 4PM, is an effective strategy but may be impractical.
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Curious Dr. George | Plumbing the Core and Nibbling at the Margins of Cancer

Is there a Better Descriptive Name than Personalized Medicine?

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Jerald P. Radich, MD, Director of the Molecular Oncology Lab at the Fred Hutchinson Cancer Research Center, and Professor of Medicine at the University of Washington School of Medicine, Seattle, Washington.

Q: What’s in a name? Should “it” be “Personalized Medicine,” “Precision Medicine,” or perhaps, “Accurate Medicine”?
A: Much of what we do in my laboratory at the Fred Hutchinson Cancer Research Center revolves around the genetics of response and relapse in leukemia. I often describe this as the biology of luck. Why do some good risk patients fail to respond to therapy, while some patients with characteristics of very poor risk nevertheless respond well? This phenomenon is often ascribed to deity, diet, or luck.
One must hope that there is some biology behind the differential response we see in patients. This then is the heart of “personalized” or “precision” medicine. Words matter, however, and in this case, neither of these trendy phrases passes muster. The term “personalized medicine” suggests that prior to the current revolutionary approach, we did not consider our patients to be unique. This is both wrong and insulting. I cannot remember a time where personal features like age, physical condition, comorbidities, and social elements were not as much a part of treatment considerations as were leukemia cell type and cytogenetic findings. A quote ascribed to both Hippocrates (400 BCE) and/or Caleb Parry (18th century) says it well: “It is much more important to know what kind of patient has a disease than to know what kind of disease a patient has.”
”Precision medicine” is a misnomer. If you imagine a target, precision means how tightly the arrows are clustered, whereas accuracy describes the proximity of the arrows to the bull’s eye. Therefore, you could have a very precise diagnostic assay but not be anywhere near the target (truth).
Thus a byline slogan for precision medicine could be “We’re reproducible wrong!” Famed British economist John Maynard Keynes once keenly observed, “I’d rather be vaguely right than precisely wrong.” Other terms that might be considered for this field of contemporary medicine and that are improvements include “accurate medicine” (though admittedly, that doesn’t sound very snappy), “bespoke medicine” (imagine a stylish and perfectly tailored suit), or perhaps simply modernmedicine or good medicine.
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Curious Dr. George | Plumbing the Core and Nibbling at the Margins of Cancer

Seeing the Forest for the Trees: How Cancer Evolution Affects Treatment

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Lisandra E. West, PhD, Senior Scientific Knowledge Engineer, CollabRx.

Q: How might current thinking on tumor evolution/heterogeneity and sequential mutational profiling inform optimal therapy selection?
A: I’d like to share some learnings from ASCO, 2016:
To help think about tumor evolution over the course of time and treatment of cancer, I’m a fan of the palm tree analogy (made by Charles Swanton, ASCO 2016). Early genetic alterations that occur in the developing tumor are “trunk” genetic events that are present in every cancer cell in the tumor. Trunk driver mutations may be predictive of drug sensitivity or intrinsic resistance. As the tumor continues to grow some cells will develop additional mutations that will be shared by their progeny cells within the tumor. To continue the palm tree analogy, this results in a branching effect, with each branch representing a sub-clonal population of tumor cells that have new acquired mutations not shared with the original trunk cells or cells in branches that evolved earlier. Swanton cites an earlier study (Landau et al, Cell, 2013) that demonstrated that acquisition of subclonal driver mutations (occurring in the tree branches) results in significantly reduced survival over time as compared to patients whose tumors lack subclonal drivers.
How does subclonal heterogeneity (many tree branches) affect response to targeted therapy? Swanton cited a study (Pearson et al, Cancer Discovery, (2016)) that showed that the best response to FGFR inhibitor therapy occurred in patients whose tumors were homogenous (having few or no branches) for FGFR amplification. Non-responding tumors had sub-clonal heterogeneous FGFR amplification AND presence of FGFR non-amplified tumor cells. This work indicates that targeting trunk or early clonal events is important because response to targeted therapy is better when a greater proportion of cancer cells in the patient share genetic alterations. Interestingly, the overlap of mutations from two different metastatic sites biopsied from the same patient showed that percentage of mutations shared between sites decreases after therapy (venn diagrams presented by Alexandra Snyder, MD, at ASCO 2016). That is to say, there is higher diversity in mutational profiles from different metastatic sites after treatment. This indicates cancer evolution over the course of treatment(s), and leads to questions about whether molecular data from a single biopsy site can be sufficient to inform treatment decision making as cancer progresses.
Thus, therapy drives tumor heterogeneity, which then fosters polyclonal cancer therapy resistance. In a study of patients with metastatic CRC treated with EGFR antibodies, liquid biopsy and sequencing demonstrated that KRAS, NRAS, BRAF, and EGFR mutations were present in post-treatment circulating tumor DNA, whereas they had been absent in pretreatment cfDNA (Bettegowda et al, Science Translational Medicine (2014)). Treatment with a PI3K inhibitor has been shown to select for sub-clones that harbor inactivating PTEN mutations which confer resistance to PIK3CA inhibitor treatment (Juric et al, Nature (2013)). Chemotherapy damages DNA and causes mutations in tumor cells that persist after treatment. These cells go on to form sub-clonal populations that are resistant to drug treatment. In a heterogeneous tumor, drug resistant subclones take over and become the dominant cancer clones that ultimately cause cancer recurrence. Quite remarkably (at least to me), Swanton suggested consideration of treating a patient to stable disease, versus maximal tumor response, based on the idea that treating to maximal tumor response may provoke the rise of a resistant and untreatable subclonal cancer cell population – to the detriment of the patient.
An emerging mechanism fueling tumor diversity and subclonal evolution is genomic DNA cytosine deamination catalyzed by members of the AID/APOBEC family of DNA deaminases which induce genomic damage through their DNA deaminating activity. Deregulation of APOBEC enzymes causes a general mutator phenotype that gives rise to the non-random somatic mutations observed in cancer, ultimately manifesting as diverse and heterogeneous tumor subclones (Mcgranahan et al, Science Translational Medicine (2015); De Bruin et al, Science (2014)). Systemic drug treatment provides selective pressure that gives clones harboring resistance-conferring mutations a competitive growth advantage. We are beginning to understand that it will be necessary to predict and target tumor evolution over the course of treatment. This will require measuring (through ongoing liquid biopsies?) cancer’s subclonal structure that mitigates drug resistance.
Importantly we are beginning to find evidence that lots of mutations in cancer (mutational load/burden) or heterogeneity itself may represent an “Achilles heel” in cancer (Charles Swanton, ASCO 2016). Mutational burden is emerging as a predictive biomarker for sensitivity to checkpoint inhibitor immunotherapy in several cancer types including non-small cell lung cancer and melanoma. Detecting mutational burden, monitoring tumor evolution, and timing and sequencing of immunotherapy with targeted therapies seem likely to be areas of intense investigation moving forward in cancer research.
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Curious Dr. George | Plumbing the Core and Nibbling at the Margins of Cancer

Multiple Sequential Biopsies now Standard of Care in NSCLC

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Gregory Otterson, MD, Professor of Internal Medicine; Interim Division Director of Medical Oncology; Co-Director, Thoracic Oncology Program; Program Director, Hematology & Medical Oncology Fellowship Program; The Ohio State University Wexner Medical Center.

Q: How has the introduction of molecular testing of non small cell lung cancer (NSCLC) altered therapy and outcomes?
A: The understanding of lung cancer as a genetic disease has been developing over at least 30 years. The technology (and cost of this technology) to utilize this understanding has only been developed over the last 10 years, and importantly, along with the technical ability to test for molecular/genetic abnormalities has been the development of a new generation of targeted agents that can specifically target these abnormalities.
In 2004, several groups described mutations with the epidermal growth factor receptor (EGFR) in patients who had sustained substantial responses to EGFR targeted tyrosine kinase inhibitors (TKIs). At this time, a number of TKIs had been approved for treatment of non-small cell lung cancer without respect to mutations. Over the next months and years, clinicians started to understand the frequency and clinical characteristics of these mutations – seen in adenocarcinomas from patients with a light or never smoking history, and especially those from East Asia. The concept of “clinical selection” of patients most likely to benefit from these agents developed between 2004 and 2009. This strategy changed forever however in 2009 with the publication of the IPASS (Iressa Pan Asia Study) which compared gefitinib (Iressa®) to standard platinum based chemotherapy in patients with a light or never smoking lung adenocarcinoma. This study demonstrated conclusively that clinical selection was inadequate – patients with the sensitizing EGFR mutations had profound benefit from the TKI, while those with the same clinical features, but lacking the mutation, had essentially no benefit from the TKI. Multiple subsequent studies have confirmed the benefit from EGFR TKI treatment in patients with molecular selection.
More recently, the development of additional TKIs against the anaplastic lymphoma kinase (ALK) and ROS1 genes have been developed SOLELY in patients who express the molecular abnormality – i.e. the drug and the molecular test have been developed concurrently. The co-development of drug and diagnostic test has revolutionized the diagnostic evaluation of patients with lung cancer because the benefit seen in patients with the abnormality (compared with those without the abnormality) is profoundly different. We expect a response rate exceeding 60% in patients treated with the matched TKI, while those without the molecular abnormality can expect little more than placebo effect benefit, and the standard treatment ought to be cytotoxic chemotherapy. More important than the response rate, the DURATION of response and the overall survival is substantially improved (at least double) in patients matched with the appropriate drug for the defined molecular abnormality (compared with patients not bearing the mutation or treated with the targeted agent).
In the last 2-3 years, several major developments have “moved the goalpost;” the development of second (and third) generation TKIs that are targeted to specific resistance mutations, and the ability to perform sequencing from cell free DNA in blood and other biological samples. Interestingly, while the responsiveness of tumors with specific molecular abnormalities to agents targeted to these abnormalities is profound, the duration of these responses is, on average, less than a year. Essentially all tumors will eventually develop resistance. The mechanism(s) of resistance are profoundly different depending upon the specific targeted gene – for example resistance to EGFR TKIs is most commonly (approximately 60% of the time) via a secondary EGFR mutation (T790M) which acts as a “gatekeeper” mutation preventing binding of the 1st/2nd generation TKI from accessing their binding pocket. Osimertinib (Tagrisso®) is an interesting EGFR TKI with the interesting property of being specific for mutant EGFR proteins (including T790M) and was recently approved by virtue of its ability to “rescue” patients who have progressed after initial responsiveness to the first generation TKI. Importantly, the approval (and insurance coverage) for this agent is dependent upon the demonstration of the presence of this mutation – meaning that, unlike the situation 10+ years ago, it is now considered the STANDARD OF CARE to biopsy patients at multiple time points during the course of their disease.
The second important recent development has been the ability to detect miniscule amounts of tumor DNA (and the corresponding mutation spectrum) from non-tumor tissue (most commonly blood, but also urine and other more accessible bio-specimens). The ability to detect mutations in cell free DNA samples provides an easier and safer mechanism to monitor patients and to detect resistance mutations.
The future of molecular analysis of tumors, and the integration of this technology with the other major treatment revolution in the last 10 years (immunotherapy/checkpoint inhibitors) is a story that remains to be told. Molecular analysis of NSCLC is undoubtedly only going to grow in importance.
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.