The Outlier’s Message, and Evolutionary Science in Breast Cancer
This past week I read several attitude-altering articles about breast cancer.
The first lesson, if I might call it that – in the way an oncologist can learn from variations in her patients’ pathology and clinical outcomes – comes from the case of Katherine Russell Rich, who died last week at the age of 56. As reported by Katherine O’Brien in the I Hate Breast Cancer Blog, Rich lived with metastatic BC (MBC) for 18 years. That’s phenomenal, was my first reaction to this news. The prognosis for MBC is said to be around 3 years, and Rich lived for 18 years beyond her tumor’s recurrence with stage IV disease.
As sad and unsatisfactory as this outcome may seem, and it is, Rich’s story offers hope for life beyond the 3 or 4 or 5 years some women with MBC pray, “ask” or otherwise bargain for, fingers-crossed…
As she detailed in an O article, Rich’s initial diagnosis came when she was 32 years old, in 1988. The Times, in an obituary, tells of her lumpectomy, chemo and radiation. In 1993 her cancer came back in bones including her spine. She had a bone marrow transplant, but the disease progressed. Ultimately, she coursed through various and some archaic hormone treatments.
Along the way, she lost or quit a job in publishing, or both, and traveled to India, and authored two books. In a 2010 first-person story about her case, she told of updating her status – of being alive – at Breastcancer.org each year. She wrote:
…I tell the women how deeply I believe there’s no such thing as false hope: all hope is valid, even for people like us, even when hope would no longer appear to be sensible.
Life itself isn’t sensible, I say. No one can say with ultimate authority what will happen — with cancer, with a job that appears shaky, with all reversed fortunes — so you may as well seize all glimmers that appear.
My take, as an oncologist and former clinician, is that patients sometimes surprise you. Hard to know which woman will respond to a non-targeted treatment, or even a drug like an estrogen modulator, without trying. And I wonder – and this is speculative, but maybe, likely, the two together – doctor and patient – worked together to see what worked in Rich’s case over nearly 2 decades, and what didn’t work.
If a drug helps, keep it going; if it hurts, stop. There are so many algorithms in medicine, and molecular tools, but maybe the bottom line is how the, one, your patient is doing.
Which leads me to another post, by Dr. David Gorski, a breast cancer surgeon and researcher who blogs as Orac – what once was imagined as a fabulously capable information processor, at Respectful Insolence. He describes how tough it can be to define, and thereby target or destroy, any individual patient’s breast tumor because the cancer cells are constantly changing. Within each woman’s tumor, an evolution-like process is ongoing, leading to selection of treatment-resistant cells. This is not news in oncology; the concept has been understood for years as it applies to “liquid” tumors like leukemia, as he points out.
In breast cancer, understanding the complexity of each case is more recent. Gorski considers a genetic analysis of 104 triple negative breast cancer (TNBC) cases presented at the recent AACR meeting and published last week in Nature:
“…The 59 scientists involved in this study expected to see similar gene profiles when they mapped on computer the genomes of 100 tumours.
But to their amazement they found no two genomes were similar, never mind the same. “Seeing these tumours at a molecular level has taught us we’re dealing with a continuum of different types of breast cancer here, not just one,” explains Steven Jones, co-author of this study.
…TNBC is not a single disease. In fact, even an individual TNBC tumor is not a single disease. Tumor cells evolve as they proliferate, so that the cells in them are genetically heterogeneous. The cells growing in one area of a tumor can and often do harbor markedly different genetic mutations from the cells growing in another part of the tumor…
The team found that each tumor displayed multiple “clonal genotypes,” suggesting that the cancer would have to be treated as multiple diseases, rather than a single entity.
So besides that there are distinct subtypes of breast cancer, those labeled as TNBC are diverse and contain variation within; each patient harbors sub-clones of malignant cells that, in principle, respond differently to treatment.
Putting these links together –
The message from Katherine O’Brien, who lives with MBC and blogs about it, is that one outlier – like Katherine Russell Rich – can provide hope to other patients and, maybe, clues for scientists about why she lived for so long with metastatic BC. The message from Orac, a physician-scientist blogger, is how hard it is to pinpoint an individual breast tumor’s molecular aspects, because the disease is so mutable and diverse.
The problem, and this reflects evolution in my thinking over a long while, is that published data – the gold standard, what supports EBM – are largely limited to findings based on trials of groups. We understand now, better than we did 10 or 20 years ago, that each patient’s tumor is unique and can evolve over time, naturally or in response to therapy. Clinical trials, though rigorously planned and elaborately structured, are incredibly expensive and flip-floppy, disappointing overall.
What I’m thinking –
Algorithms – except in the broadest sense – may not offer the optimal approach to cancer treatment. Maybe the median doesn’t matter so much as we’d thought.
Here’s a ~retro idea: In 2012, maybe the ideal and most cost-effective oncology practice would blend low-tech observations – like findings on physical examination and how the patient’s feeling – with occasional, high-tech analyses – like markers for genetic drift within a tumor. If doctors are well-trained and non-robotic, in either the literal or figurative sense, and if they lack COIs regarding treatment decisions, they’d provide better, more effective and personalized treatments than what’s typically offered based on evidence reached through elaborate, costly clinical trials of many patients with similar but non-identical cancers.
All for now,
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