“What doesn’t kill you makes you stronger” is not just a cute saying for a throw pillow or gym shirt — it’s an actual biological phenomenon.
A fundamental law of nature dictates that anything alive is wired to survive so it can pass its genetics on to the next generation. Whether bugs surviving on crops after pesticides, microbes surviving in animals after antibiotics, or small mammals surviving after a meteor wiped out the dinosaurs, life finds a way to overcome insurmountable pressures in order to survive
Cancer often works in the same way — drugging it can simply make it stronger. By hitting a tumor with a therapy, we create a pressure for the malignancy to resist it. To ensure its own survival, the tumor will evolve until the drug no longer works, making the cancer even more difficult to kill.
Cancer developing resistance to our arsenal of drugs is responsible for up to 90% of cancer deaths each year. Unfortunately, our outdated assumptions about how cancers evolve resistance has led to failures in finding therapeutic strategies to overcome it. This creates an enormous barrier to improving our standard of care and saving lives.
The model we have been working off of, known as the clonal expansion model, was developed in the 1970s, before next-generation sequencing, machine learning, and advanced microscopy could unlock the secrets of biology. Tumors were viewed as a product of overgrowth without pruning; cancer cells were allowed to divide without our bodies stopping them. As they move from a single abnormal cell to a full-blown disease, the messiness of biology creates a chance to introduce mutations at each cell division. What was first a homogenous mass of cells becomes multiple subpopulations, each with a unique mutation as well as all the mutations of its ancestors.
This creates a Darwinian problem. Under clonal expansion assumptions, some of these variations are primed to allow a subpopulation of the cancer to resist the drug, even just slightly. These cells do not die — or can even continue to grow — as the therapy decimates the rest of the population. What we see as regression of the disease is unfortunately just us selecting the cells that are resistant to the therapy — survival of the fittest happening within our bodies.
In this old model of tumor evolution, this refined cancer will continue to generate variations, thereby not only remaining resistant to the first treatment but also potentially evolving resistance to new ones. Drugging tumors under this outdated assumption is like hitting a moving target — doctors are in a constant arms race with the disease, adding new drugs to the treatment regimen dynamically to hopefully kill all the cancer cells.
Modern biotechnology has given us an unprecedented view into the early life of a tumor that has turned the 1970s model on its head. We can now follow a tumor as it starts from a small set of cells to a much bigger and deadlier mass.
Based on 70’s science, we would expect to see few subpopulations at the beginning of a tumor because there haven’t been enough cell divisions to allow for the mutations that create this variation. Surprisingly, we see there are actually about the same number of subpopulations throughout the life of the tumor — the tumor isn’t really evolving!
Based on a huge pile of evidence that started to amass in 2015, we now know that early cancerous cells undergo a mutational burst or a cataclysmic genomic rearrangement that induce many subpopulations to be generated at the tumor’s genesis, which then grow out to be a heterogeneous tumor (see below). It’s like the Big Bang that started our universe — the variations exploded out from at the earliest time points and expanded rapidly to become what we observe in the doctor’s office.
Cancer evolves differently than we assumed, so we need to rethink how to build therapies to target it. The cancer isn’t cleverly evolving resistance to our drugs — that resistance exists from the beginning. Looking back, we shouldn’t be that surprised — even when killing cancer cells in a petri dish, we rarely destroy all of them, indicating some inherent heterogeneity at the onset.
It turns out doctors aren’t trying to hit a moving target but deciding which fixed targets to attack to get the best clinical results. In other words, doctors don’t need to be so dynamic in their treatment strategy — they simply need to find a multi-targeted therapy that avoids selecting for a highly aggressive subpopulation. So how do we overcome resistance with this fresh look at cancer evolution?
Enter resistanceBio who have embraced this new research to generate multi-targeted Resistance Therapies (RTs). The founders, Nicholas Goldner and Christopher Bulow, come from the world of antibiotic resistance where identifying multi-targeted therapies that take into account treatment over time is common practice. With this mindset and approach, resistanceBio has built a platform that harnesses evolution to overcome resistance in all its manifestations.
Knowing that even cancers modeled in a petri-dish have this Big Bang dynamic, resistanceBio has developed their novel and proprietary ResCu (Resistance Culturing) platform to identify these multi-targeted therapies more rapidly and scalably than ever before. ResCu starts with highly customized culture conditions for their in vitro cancer models. These ResCu conditions are applied to a library of cancer cell lines, creating an enormous biobank of cancer models that resistanceBio can tap into.
These aren’t just your average cultures; each one is a dynamic mosaic of various subpopulations that accurately represents the way a tumor thrives over time. With their novel culturing method, resistanceBio can have a model ready in a matter of weeks, whereas current pharma methods would require months or years to achieve similar results.
ResCu allows them to quickly and accurately model the kinds of resistances that pharma actually sees in clinical trials or worse when the drug is in market. By simply adding a single therapy into the ResCu culture, the drug reshapes the subpopulation like it would in a real tumor. A prescribed cancer drug may have a 75% relapse that takes months or even years to recognize, resulting in lives unnecessarily lost from these resistances and pharma losing out on the opportunity to save these patients in a second round of therapy. The resistance that takes years or decades for patient studies to identify can be found by resistanceBio in a single week.
Once identified, resistanceBio performs a multi-omics measurement to find the cause of the resistance. In probing the genome and transcriptome, they learn where the in vitro tumor as a whole left itself open while resisting this drug, giving them an idea of how to exploit these resistances and turning what was once thought to be cancer’s superpower into its Achilles heel.
Drugs that can exploit these specific weaknesses are then screened in the same treated ResCu system. But these aren’t average drug combos — they attack multiple interdependent systems of cancer. Screening these well-thought-out drugs that were designed with processes rather than targets in mind, ResCu finds multi-targeted therapies consisting of multiple drugs hitting even more processes (e.g. 3 drugs hitting 8 processes). Even more exciting, the multi-omics platform gives resistanceBio novel biomarkers that tell them exactly which patients will respond to treatment.
This way, patients who relapse to a first line therapy can be saved in another round of therapy developed by resistanceBio’s ResCu system. Working together, the biobank and the speed at which ResCu can make resistant cell populations compounds their advantage, meaning that it takes resistanceBio 6 months where other companies take 3 years. This speed helps ensure we will soon live in a world where “resistant cancers” are a thing of the past and those 90% of cancer deaths are avoided altogether.
At Fifty Years, our sweet spot is supporting founders at the earliest stages building deep tech companies that can generate huge financial outcomes and create massive positive impact.
- Deep tech: Nicholas and Christopher have dedicated their lives to thinking about resistance’s connection to human health in all its forms and apply that knowledge to create ResCu. Nicholas has a PhD in Molecular Cell Biology and Christopher has a PhD in Genomics, both from Washington University in St. Louis.
- $1B yearly revenue potential: In the US alone, nearly 500,000 people develop resistant cancer a year, at a huge cost to pharma as potentially useful therapies fail in the clinic. resistanceBio breathes life back into these drugs, rescuing assets and therapeutic programs.
- Massive positive societal impact: The vast majority of cancer deaths come from a resistance to first line therapy. ResistanceBio solves this problem, quickly finding drugs that can improve patient outcomes and save millions of lives.
Inspired by their technology and vision for its future, Fifty Years was excited to partner with resistanceBio in their seed round.