By Karuna Jaggar, Executive Director
I live in the San Francisco Bay Area, the land of tech—and $5 cups of coffee (and I don’t mean a cappuccino, I mean plain old coffee). But tech is doing more than driving up the cost of living, especially housing, in the Bay Area, technological advances are bringing down the cost of genetic sequencing.
The result is a heavy focus on everything from gene sequencing to genetic testing on the first official day of SABCS. General Session 1 on Wednesday morning included several presentations from different institutions who are using single cell sequencing to build an atlas, sequencing every cell type in the healthy breast and in tumor tissue.
Back when I first came to Breast Cancer Action in early 2011, I had a conversation with Dr. Susan Love who, rightly, pointed out that we need to understand the normal, healthy breast in order to really understand breast cancer. The human cell atlas is funded by Chan Zuckerberg Institute (based in the Bay Area) and is mapping all of the different human breast cells (though Dr. Love wants an anatomical as well as cellular map).
Of course, it’s critical that any breast cell atlas must capture the wide range of normal. After all, if we allow normal to be narrowly defined, suddenly a bunch of perfectly healthy people are pathologized. Getting older is normal, if we’re lucky, and so people from all different ages and different stages of life must be included so that older breasts aren’t considered abnormal. Dense breasts are normal, as are non-dense breasts. Not giving birth is normal, and so is giving birth and nursing.
It reminds me about something a midwife once said that stuck with me: after fetal heart monitors were introduced, caesarian sections dramatically increased because doctors didn’t know what was normal. Instead of improving fetal and maternal outcomes, the new technology introduced a lot of data (constant monitoring rather than occasional monitoring with a fetal stethoscope or hand-held ultrasound device) without training providers on what it meant and what is normal.
Back to breast cancer, so far researchers have only looked at a tiny handful of samples for the human breast cell atlas, and these will need expanding to capture the full range that is normal. Who is studied matters.
I also attended a special clinical science forum on cancer genetics, which underscored how complex genetic testing is. Genetic testing is already misunderstood and misused by providers and patients, and as the use of multi-gene panels expands, Dr. Susan Domchek (U Penn) warns against treating other breast cancer associated genes like BRCA genes. Each of these genes is specific and comes with its own risk profile.
Dr. Allison Kurian (Stanford) underscored the troubling fact that many surgeons and physicians don’t understand the complexity of genetic testing and, specifically, don’t understand variants of unknown significance (VUS). When asked if they would treat VUS as if they were a positive result, these providers replied they would—which Dr. Kurian says “we know is the wrong answer.”
In addition Dr. Kurian directly spoke to the ways genetic testing replicates social biases. People of color (POC) are less likely to get genetic testing and the number one reason they don’t get it is simply because their doctors don’t recommend it. When they do get tested POC are more likely to be told they have a variant of unknown significance (VUS) because genetic tests have been developed with largely white communities. Yet different ethnic groups have similar rates of hereditary risk from genetic mutations, which increase the risk of breast cancer (pathogenic findings). And I don’t need to remind you that many physicians and surgeons say they will treat patients with a VUS as if it’s a positive result, resulting in overtreatment and unnecessary harm.
Technology can amplify inequity. Who is included in studies informs what we think of as normal, and what we don’t know. How are choices explained and are the range of decisions that individual people from different backgrounds make respected and supported? Who has access? And who sets the agenda in the first place?
It’s our collective job to make sure we build our cellular atlases and our genetic databases to also meet the needs of underserved communities. Just like we should build livable cities where people who aren’t tech workers can afford a cup of coffee with their apartment.