When the epidemiologists juxtaposed smoking behavior onto this network and followed the pattern of smoking over decades, a notable phenomenon emerged: circles of relationships were found to be more powerful predictors of the dynamics of smoking than nearly any other factor. Entire networks stopped smoking concordantly, like whole circuits flickering off. A family that dined together was also a family that quit together. When highly connected “socializers” stopped smoking, the dense social circle circumscribed around them also slowly stopped as a group. As a result, smoking gradually became locked into the far peripheries of all networks, confined to the “loners” with few social contacts, puffing away quietly in the distant and isolated corners of the town.
The smoking-network study offers, to my mind, a formidable challenge to simplistic models of cancer prevention. Smoking, this model argues, is entwined into our social DNA just as densely and as inextricably as oncogenes are entwined into our genetic material. The cigarette epidemic, we might recall, originated as a form of metastatic behavior—one site seeding another site seeding another. Soldiers brought smoking back to postwar Europe; women persuaded women to smoke; the tobacco industry, sensing opportunity, advertised cigarettes as a form of social glue that would “stick” individuals into cohesive groups. The capacity of metastasis is thus built into smoking. If entire networks of smokers can flicker off with catalytic speed, then they can also flicker on with catalytic speed. Sever the ties that bind the nonsmokers of Framingham (or worse, nucleate a large social network with a proselytizing smoker), and then, cataclysmically, the network might alter as a whole.
This is why even the most successful cancer-prevention strategies can lapse so swiftly. When the Red Queen’s feet stop spinning even temporarily, she does not maintain her position; the world around her, counter-spinning, pushes her off-balance. So it is with cancer prevention. When antitobacco campaigns lose their effectiveness or penetrance—as has recently happened among teens in America or in Asia—smoking often returns like an old plague. Social behavior metastasizes, eddying out from its center toward the peripheries of social networks. Mini-epidemics of smoking-related cancers are sure to follow.
The landscape of carcinogens is not static either. We are chemical apes: having discovered the capacity to extract, purify, and react molecules to produce new and wondrous molecules, we have begun to spin a new chemical universe around ourselves. Our bodies, our cells, our genes are thus being immersed and reimmersed in a changing flux of molecules—pesticides, pharmaceutical drugs, plastics, cosmetics, estrogens, food products, hormones, even novel forms of physical impulses, such as radiation and magnetism. Some of these, inevitably, will be carcinogenic. We cannot wish this world away; our task, then, is to sift through it vigilantly to discriminate bona fide carcinogens from innocent and useful bystanders.
This is easier said than done. In 2004, a rash of early scientific reports suggested that cell phones, which produce radio frequency energy, might cause a fatal form of brain cancer called a glioma. Gliomas appeared on the same side of the brain that the phone was predominantly held, further tightening the link. An avalanche of panic ensued in the media. But was this a falsely perceived confluence of a common phenomenon and a rare disease—phone usage and glioma? Or had epidemiologists missed the “nylon stockings” of the digital age?
In 2004, an enormous British study was launched to confirm these ominous early reports. “Cases”—patients with gliomas—were compared to “controls”—men and women with no gliomas—in terms of cell phone usage. The study, reported in 2006, appeared initially to confirm an increased risk of right-sided brain cancers in men and women who held their phone on their right ear. But when researchers evaluated the data meticulously, a puzzling pattern emerged: right-sided cell phone use reduced the risk of left-sided brain cancer. The simplest logical explanation for this phenomenon was “recall bias”: patients diagnosed with tumors unconsciously exaggerated the use of cell phones on the same side of their head, and selectively forgot the use on the other side. When the authors corrected for this bias, there was no detectable association between gliomas and cell phone use overall. Prevention experts, and phone-addicted teenagers, may have rejoiced—but only briefly. By the time the study was completed, new phones had entered the market and swapped out old phones—making even the negative results questionable.
The cell phone case is a sobering reminder of the methodological rigor needed to evaluate new carcinogens. It is easy to fan anxiety about cancer. Identifying a true preventable carcinogen, estimating the magnitude of risk at reasonable doses and at reasonable exposures, and reducing exposure through scientific and legislative intervention—keeping the legacy of Percivall Pott alive—is far more complex.
“Cancer at the fin de siècle,” as the oncologist Harold Burstein described it, “resides at the interface between society and science.” It poses not one but two challenges. The first, the “biological challenge” of cancer, involves “harnessing the fantastic rise in scientific knowledge . . . to conquer this ancient and terrible illness.” But the second, the “social challenge,” is just as acute: it involves forcing ourselves to confront our customs, rituals, and behaviors. These, unfortunately, are not customs or behaviors that lie at the peripheries of our society or selves, but ones that lie at their definitional cores: what we eat and drink, what we produce and exude into our environments, when we choose to reproduce, and how we age.
Thirteen Mountains
“Every sickness
is a musical problem,”
so said Novalis,
“and every cure
a musical solution.”
—W. H. Auden
The revolution in cancer research can be summed up in a single sentence: cancer is, in essence, a genetic disease.
—Bert Vogelstein
When I began writing this book, in the early summer of 2004, I was often asked how I intended to end it. Typically, I would dodge the question or brush it away. I did not know, I would cautiously say. Or I was not sure. In truth, I was sure, although I did not have the courage to admit it to myself. I was sure that it would end with Carla’s relapse and death.
I was wrong. In July 2009, exactly five years after I had looked down the microscope into Carla’s bone marrow and confirmed her first remission, I drove to her house in Ipswich, Massachusetts, with a bouquet of flowers. It was an overcast morning, excruciatingly muggy, with a dun-colored sky that threatened rain but would not deliver any. Just before I left the hospital, I glanced quickly at the first note that I had written on Carla’s admission to the hospital in 2004. As I had written that note, I recalled with embarrassment, I had guessed that Carla would not even survive the induction phase of chemotherapy.
But she had made it; a charring, private war had just ended. In acute leukemia, the passage of five years without a relapse is nearly synonymous with a cure. I handed her the azaleas and she stood looking at them speechlessly, almost numb to the enormity of her victory. Once, earlier this year, preoccupied with clinical work, I had waited two days before calling her about a negative bone marrow biopsy. She had heard from a nurse that the results were in, and my delay had sent her into a terrifying spiral of depression: in twenty-four hours she had convinced herself that the leukemia had crept back and my hesitation was a signal of impending doom.
Oncologists and their patients are bound, it seems, by an intense subatomic force. So, albeit in a much smaller sense, this was a victory for me as well. I sat at Carla’s table and watched her pour a glass of water for herself, unpurified and straight from the sink. She glowed radiantly, her eyes half-closed, as if the compressed autobiography of the last five years were flashing through a private and internal cinema screen. Her children played with their Scottish terrier in the next room, blissfully oblivious of the landmark date that had just passed for their mother. All of this was for the best. “The purpose of my book,” Susan Sontag concluded in Illness as Metaphor, “was to calm the imagination, not to incite it.?
?? So it was with my visit. Its purpose was to declare her illness over, to normalize her life—to sever the force that had locked us together for five years.
I asked Carla how she thought she had survived her nightmare. The drive to her house from the hospital that morning had taken me an hour and a half through a boil of heavy traffic. How had she managed, through the long days of that dismal summer, to drive to the hospital, wait in the room for hours as her blood tests were run, and then, told that her blood counts were too low for her to be given chemotherapy safely, turn back and return the next day for the same pattern to be repeated?
“There was no choice,” she said, motioning almost unconsciously to the room where her children were playing. “My friends often asked me whether I felt as if my life was somehow made abnormal by my disease. I would tell them the same thing: for someone who is sick, this is their new normal.”
Until 2003, scientists knew that the principal distinction between the “normalcy” of a cell and the “abnormalcy” of a cancer cell lay in the accumulation of genetic mutations—ras, myc, Rb, neu, and so forth—that unleashed the hallmark behaviors of cancer cells. But this description of cancer was incomplete. It provoked an inevitable question: how many such mutations does a real cancer possess in total? Individual oncogenes and tumor suppressors had been isolated, but what was the comprehensive set of such mutated genes that exists in any true human cancer?
The Human Genome Project, the full sequence of the normal human genome, was completed in 2003. In its wake comes a far less publicized but vastly more complex project: fully sequencing the genomes of several human cancer cells. Once completed, this effort, called the Cancer Genome Atlas, will dwarf the Human Genome Project in its scope. The sequencing effort involves dozens of teams of researchers across the world. The initial list of cancers to be sequenced includes brain, lung, pancreatic, and ovarian cancer. The Human Genome Project will provide the normal genome, against which cancer’s abnormal genome can be juxtaposed and contrasted.
The result, as Francis Collins, the leader of the Human Genome Project describes it, will be a “colossal atlas” of cancer—a compendium of every gene mutated in the most common forms of cancer: “When applied to the 50 most common types of cancer, this effort could ultimately prove to be the equivalent of more than 10,000 Human Genome Projects in terms of the sheer volume of DNA to be sequenced. The dream must therefore be matched with an ambitious but realistic assessment of the emerging scientific opportunities for waging a smarter war.” The only metaphor that can appropriately describe this project is geological. Rather than understand cancer gene by gene, the Cancer Genome Atlas will chart the entire territory of cancer: by sequencing the entire genome of several tumor types, every single mutated gene will be identified. It will represent the beginnings of the comprehensive “map” so hauntingly presaged by Maggie Jencks in her last essay.
Two teams have forged ahead in their efforts to sequence the cancer genome. One, called the Cancer Genome Atlas consortium, has multiple interconnected teams spanning several labs in several nations. The second is Bert Vogelstein’s group at Johns Hopkins, which has assembled its own cancer genome sequencing facility, raised private funding for the effort, and raced ahead to sequence the genomes of breast, colon, and pancreatic tumors. In 2006, the Vogelstein team revealed the first landmark sequencing effort by analyzing thirteen thousand genes in eleven breast and colon cancers. (Although the human genome contains about twenty thousand genes in total, Vogelstein’s team initially had tools to assess only thirteen thousand.) In 2008, both Vogelstein’s group and the Cancer Genome Atlas consortium extended this effort by sequencing hundreds of genes of several dozen specimens of brain tumors. As of 2009, the genomes of ovarian cancer, pancreatic cancer, melanoma, lung cancer, and several forms of leukemia have been sequenced, revealing the full catalog of mutations in each tumor type.
Perhaps no one has studied the emerging cancer genome as meticulously or as devotionally as Bert Vogelstein. A wry, lively, irreverent man in blue jeans and a rumpled blazer, Vogelstein recently began a lecture on the cancer genome in a packed auditorium at Mass General Hospital by attempting to distill the enormous array of discoveries in a few slides. Vogelstein’s challenge was that of the landscape artist: How does one convey the gestalt of a territory (in this case, the “territory” of a genome) in a few broad strokes of a brush? How can a picture describe the essence of a place?
Vogelstein’s answer to these questions borrows beautifully from an insight long familiar to classical landscape artists: negative space can be used to convey expanse, while positive space conveys detail. To view the landscape of the cancer genome panoramically, Vogelstein splayed out the entire human genome as if it were a piece of thread zigzagging across a square sheet of paper. (Science keeps eddying into its past: the word mitosis—Greek for “thread”—is resonant here again.) In Vogelstein’s diagram, the first gene on chromosome one of the human genome occupies the top left corner of the sheet of paper, the second gene is below it, and so forth, zigzagging through the page, until the last gene of chromosome twenty-three occupies the bottom right corner of the page. This is the normal, unmutated human genome stretched out in its enormity—the “background” out of which cancer arises.
Against the background of this negative space, Vogelstein placed mutations. Every time a gene mutation was encountered in a cancer, the mutated gene was demarcated as a dot on the sheet. As the frequency of mutations in any given gene increased, the dots grew in height into ridges and hills and then mountains. The most commonly mutated genes in breast cancer samples were thus represented by towering peaks, while genes rarely mutated were denoted by small hills or flat dots.
Viewed thus, the cancer genome is at first glance a depressing place. Mutations litter the chromosomes. In individual specimens of breast and colon cancer, between fifty to eighty genes are mutated; in pancreatic cancers, about fifty to sixty. Even brain cancers, which often develop at earlier ages and hence may be expected to accumulate fewer mutations, possess about forty to fifty mutated genes.
Only a few cancers are notable exceptions to this rule, possessing relatively few mutations across the genome. One of these is an old culprit, acute lymphoblastic leukemia: only five or ten genetic alterations cross its otherwise pristine genomic landscape.* Indeed, the relative paucity of genetic aberrancy in this leukemia may be one reason that this tumor is so easily felled by cytotoxic chemotherapy. Scientists speculate that genetically simple tumors (i.e., those carrying few mutations) might inherently be more susceptible to drugs, and thus intrinsically more curable. If so, the strange discrepancy between the success of high-dose chemotherapy in curing leukemia and its failure to cure most other cancers has a deep biological explanation. The search for a “universal cure” for cancer was predicated on a tumor that, genetically speaking, is far from universal.
In contrast to leukemia, the genomes of the more common forms of cancer, Vogelstein finds, are filled with genetic bedlam—mutations piled upon mutations upon mutations. In one breast cancer sample from a forty-three-year-old woman, 127 genes were mutated—nearly one in every two hundred genes in the human genome. Even within a single type of tumor, the heterogeneity of mutations is daunting. If one compares two breast cancer specimens, the set of mutated genes is far from identical. “In the end,” as Vogelstein put it, “cancer genome sequencing validates a hundred years of clinical observations. Every patient’s cancer is unique because every cancer genome is unique. Physiological heterogeneity is genetic heterogeneity.” Normal cells are identically normal; malignant cells become unhappily malignant in unique ways.
Yet, characteristically, where others see only daunting chaos in the littered genetic landscape, Vogelstein sees patterns coalescing out of the mess. Mutations in the cancer genome, he believes, come in two forms. Some are passive. As cancer cells divide, they accumulate mutations due to accidents in the copying of DNA, but these mutations have no impact on the biology of cancer. They stick to
the genome and are passively carried along as the cell divides, identifiable but inconsequential. These are “bystander” mutations or “passenger” mutations. (“They hop along for the ride,” as Vogelstein put it.)
Other mutations are not passive players. Unlike the passenger mutations, these altered genes directly goad the growth and the biological behavior of cancer cells. These are “driver” mutations, mutations that play a crucial role in the biology of a cancer cell.
Every cancer cell possesses some set of driver and passenger mutations. In the breast cancer sample from the forty-three-year-old woman with 127 mutations, only about ten might directly be contributing to the actual growth and survival of her tumor, while the rest may have been acquired due to gene-copying errors in cancer cells. But while functionally different, these two forms of mutations cannot easily be distinguished. Scientists can identify some driver genes that directly goad cancer’s growth using the cancer genome. Since passenger mutations occur randomly, they are randomly spread throughout the genome. Driver mutations, on the other hand, strike key oncogenes and tumor suppressors, and only a limited number of such genes exist in the genome. These mutations—in genes such as ras, myc, and Rb—recur in sample upon sample. They stand out as tall mountains in Vogelstein’s map, while passenger mutations are typically represented by the valleys. But when a mutation occurs in a previously unknown gene, it is impossible to predict whether that mutation is consequential or inconsequential—driver or passenger, barnacle or engine.