Search any biology textbook for its description of cancer and you’ll likely find the phrase “uncontrolled growth.” Rapid and unrestrained proliferation is a well-known hallmark of cancer. In fact, this is one of the reasons it is so difficult to treat, especially at metastatic or advanced stages – malignant cells just don’t stay put.
Over the years, scientists have seen hints that this deadly growth and spread is related to aberrant chromosomes within cancer cells. They found many cancer cells had errors in normal cell division, which created daughter cells with incorrect numbers of chromosomes. But exactly how these “unstable” chromosomes give rise to metastasis has remained a mystery. Until now.
Recent scientific insights combined with powerful new tools are allowing us to peer inside cells at the precise moment of cell division to understand this chromosomal instability (CIN) scientists have observed – and to learn how CIN drives cancer spread. As a result, we’re at an inflection point in opening up promising new avenues for drug discovery.
This research is what propels Volastra. And we’re not the only ones excited by this opportunity. In fact, this topic is gaining recognition as a prominent clinical research area – evidenced by a plenary session devoted to the role of CIN in cancer at the recent American Association for Cancer Research (AACR) annual meeting. Our Co-founder Samuel Bakhoum, M.D., Ph.D., and Scientific Advisory Board Member David Pellman, M.D., both presented during the session. Here are some of their key insights:
How cancer genomes evolve
Malignant cells often have an abnormal number of chromosomes, known as aneuploidy. This was one of the first signs that genetic errors may be driving the proliferation of cancer cells. For many years, scientists sought to target this aneuploidy as a way to stop cancer. However, aneuploidy is simply a snapshot of a cell’s genetic stability. In order to target the root cause of cancer growth, we need to understand why aneuploidy happens in the first place.
That’s why more recent work focuses on how the cancer genome evolves over time – and how certain changes can lead to CIN. Today’s research has shown that highly complex and mutated genomes can originate from burst-like processes, where these changes happen in one catastrophic event. Identifying and better understanding the way changes occur in the cancer genome will allow us to draw a more precise link to how they might drive cancer metastasis. In turn, this should reveal components within these processes that might be targetable with new drugs.
Quantifying CIN
A critical piece of investigating the role of CIN in cancer is being able to quantify it. Today that requires a pathologist to study a tissue sample under a microscope for about an hour, and they can only examine one sample from one patient at a time. How do we do this at scale so we can broadly analyze many more patient samples both rapidly and accurately?
Our recent partnership with Microsoft allows us to do just that. By harnessing Microsoft’s machine learning capabilities, we can automate these analyses to more quickly identify tumors with high CIN. This could help stratify patients most likely to benefit from medicines that target CIN. Additionally, we hope this technology will allow us to identify new markers of CIN that could potentially inform new drug candidates.
Creating a better model
We’re also interested in exploring how CIN affects the local tumor microenvironment. How does it impact the immune signaling pathways that typically defend our bodies against cancer spread?
We know that ongoing cellular stress as a result of CIN can alter the immune response. Rather than activating an anti-tumor immune response, chronic inflammation instead activates a non-canonical pathway called NF-kB that promotes metastasis. This leads us to explore how tumors adapt to inflammation.
To do this, we’ve developed new mouse models with altered levels of CIN that allow us to more precisely understand how CIN changes the tumor microenvironment. Data to date suggest that these models correlate very closely with what we’ve seen in human samples. This suggests we have a powerful tool to not only test our hypotheses, but to inform the design of new medicines.
Carrying progress forward
Finally, this AACR plenary session was dedicated to the memory of Angelika Amon, Ph.D., a biologist at MIT who passed away from ovarian cancer in 2020. Angelika was a pioneer in the field of cell biology, leading seminal work identifying and characterizing key signaling networks involved in cell division. Her lab also demonstrated how aneuploidy drives genome instability and mutagenesis.
As we forge ahead, we pay tribute to the scientists, like Angelika, who have paved an important path in this promising field. We believe the best tribute is to turn these insights into promising new therapies – and that’s exactly what we hope to do.