Periodic Reporting for period 4 - CombaTCancer (Rational combination therapies for metastatic cancer)
Período documentado: 2022-09-01 hasta 2024-05-31
Tumor progression largely depends on intrinsic cancer cell signals that drive tumor growth and enable the tumor to evade destruction by the immune system. These dependencies are targeted by two primary therapeutic approaches: targeted therapies, which inhibit oncogenic signaling pathways within cancer cells, and immunotherapies, which stimulate the immune system to attack cancer cells. While both approaches have shown remarkable success in certain patient subgroups, challenges such as therapy resistance and low response rates persist. Combining different therapies presents a promising strategy to overcome these challenges, but the rational combination and optimal sequencing of therapies are often hindered by a lack of molecular understanding of resistance mechanisms and the dynamic interactions between cancer cells and immune cells as tumors evolve.
The overarching goal of "CombaTCancer" was (1) to understand how resistance to therapies emerges, and (2) to gain insights into how oncogenic signaling pathways—and their inhibition through targeted therapies—affect immune cells within the tumor microenvironment. Our vision and mission are to provide a scientific foundation for guiding rational combination therapies and to identify the optimal sequencing of therapies to achieve durable responses in cancer patients.
Aligned with this vision, our data and technologies are beginning to offer a comprehensive view of the cell states that drive therapy resistance, influence immune responses, and ultimately impact treatment outcomes. Recently, we have made significant progress in several areas: (1) We developed novel lineage tracing and clone isolation technologies that allow us to track the evolutionary trajectory of tumor cells through therapy response and resistance. (2) We demonstrated that resistance to targeted RAFi/MEKi therapies is often acquired in surviving persister cells and identified new molecular drivers and therapeutic targets. (3) We uncovered that tumor cells acquiring resistance to targeted therapy simultaneously develop cross-resistance to immunotherapy, despite the distinct mechanisms of these therapies. (4) We identified a complete cascade of molecular pathways and cellular hierarchies by which cancer cells establish and maintain an immune-evasive tumor microenvironment that confers resistance to immunotherapies and provided crucial new insights into the fundamental principles of anti-tumor immunity.
Our future work will build on these concepts, models, and tools to deepen our understanding of the cancer cell and immune cell states that confer therapy resistance and impair immune function, thereby driving disease progression.
The overarching goal of "CombaTCancer" was (1) to understand how resistance to therapies emerges, and (2) to gain insights into how oncogenic signaling pathways—and their inhibition through targeted therapies—affect immune cells within the tumor microenvironment. Our vision and mission are to provide a scientific foundation for guiding rational combination therapies and to identify the optimal sequencing of therapies to achieve durable responses in cancer patients.
Aligned with this vision, our data and technologies are beginning to offer a comprehensive view of the cell states that drive therapy resistance, influence immune responses, and ultimately impact treatment outcomes. Recently, we have made significant progress in several areas: (1) We developed novel lineage tracing and clone isolation technologies that allow us to track the evolutionary trajectory of tumor cells through therapy response and resistance. (2) We demonstrated that resistance to targeted RAFi/MEKi therapies is often acquired in surviving persister cells and identified new molecular drivers and therapeutic targets. (3) We uncovered that tumor cells acquiring resistance to targeted therapy simultaneously develop cross-resistance to immunotherapy, despite the distinct mechanisms of these therapies. (4) We identified a complete cascade of molecular pathways and cellular hierarchies by which cancer cells establish and maintain an immune-evasive tumor microenvironment that confers resistance to immunotherapies and provided crucial new insights into the fundamental principles of anti-tumor immunity.
Our future work will build on these concepts, models, and tools to deepen our understanding of the cancer cell and immune cell states that confer therapy resistance and impair immune function, thereby driving disease progression.
The first part of the ERC Starting Grant CombaTCancer focused on addressing a longstanding question in oncology: Do resistant clones pre-exist in therapy-naïve tumors, or does therapy itself induce resistance? To address this question, we created the CaTCH lineage tracing technology (Umkehrer et al., Nature Biotechnology, 2020). CaTCH enables precise mapping of the lineage history of millions of cells and facilitates the isolation any clone as rare as 0.002% through a CRIPRa activatable BC-linked GFP reporter with exceptional purity (98%, ~20,000-fold enrichment), allowing the direct functional comparison of resistant clones with their therapy-naive founder clones.
In its initial applications, CaTCH provided critical insights into resistance mechanisms to targeted RAF/MEK inhibitor therapy in vivo. Our findings revealed that resistance is often acquired during treatment rather than pre-existing. While in most clones resistance emerged due to altered signaling output, we also identified de novo mutations in the MAPK pathway in resistant clones, which were absent in their treatment-naïve counterparts, offering experimental evidence that resistance conferring mutations can be acquired during drug treatment. These data challenge the prevailing notion that drug-resistance mutations generally pre-exist before therapy and suggest potential preventive strategies. CaTCH is now extensively utilized in our lab and globally for advancing research in therapy resistance, metastasis, and immune evasion.
The second part of CombaTCancer was dedicated to understanding how targeted therapies reshape the entire tumor-immune ecosystem. We developed novel, clinically relevant models and discovered that when BRAF-mutated melanomas acquire resistance to MAPK pathway-targeted therapies, they also develop cross-resistance to immunotherapy, despite the distinct modes of action of these treatments (Haas et al., Nature Cancer, 2021). We demonstrated that this cross-resistance is mediated by an immune-evasive tumor microenvironment (TME), provided mechanistic insights into the drivers of cross-resistance and potential therapeutic strategies to overcome it. Supported by recent prospective clinical trials, the work by us and others has influenced clinical practice by emphasizing the prioritization of immunotherapy as a first-line treatment.
These studies have opened up several exciting avenues for further research. Most recently, we used our models to explore how cancer cells shape a TME that is either permissive or suppressive of a T cell response. Our findings have provided crucial new insights into the fundamental principles of anti-tumor immunity, reshaping our understanding of immunity in both health and disease (in revision).
Beyond these discoveries, the technologies established within the CombaTCancer framework have enabled us to extend our research to cancer types where little is known about the drivers and mechanism-based treatments. For example, we identified new therapeutic entry points for rare skin cancers (Leiendecker et al., EMBO Molecular Medicine 2020) and uncovered a new oncogenic virus (Human papillomavirus 42) as the driver of a rare skin cancer (digital papillary adenocarcinoma). Through machine learning approaches, we found that oncogenic papillomaviruses induce a germ cell-like program in cancer cells, which we are working towards exploiting both diagnostically and therapeutically (Leiendecker et al., Cancer Discovery, 2023).
In its initial applications, CaTCH provided critical insights into resistance mechanisms to targeted RAF/MEK inhibitor therapy in vivo. Our findings revealed that resistance is often acquired during treatment rather than pre-existing. While in most clones resistance emerged due to altered signaling output, we also identified de novo mutations in the MAPK pathway in resistant clones, which were absent in their treatment-naïve counterparts, offering experimental evidence that resistance conferring mutations can be acquired during drug treatment. These data challenge the prevailing notion that drug-resistance mutations generally pre-exist before therapy and suggest potential preventive strategies. CaTCH is now extensively utilized in our lab and globally for advancing research in therapy resistance, metastasis, and immune evasion.
The second part of CombaTCancer was dedicated to understanding how targeted therapies reshape the entire tumor-immune ecosystem. We developed novel, clinically relevant models and discovered that when BRAF-mutated melanomas acquire resistance to MAPK pathway-targeted therapies, they also develop cross-resistance to immunotherapy, despite the distinct modes of action of these treatments (Haas et al., Nature Cancer, 2021). We demonstrated that this cross-resistance is mediated by an immune-evasive tumor microenvironment (TME), provided mechanistic insights into the drivers of cross-resistance and potential therapeutic strategies to overcome it. Supported by recent prospective clinical trials, the work by us and others has influenced clinical practice by emphasizing the prioritization of immunotherapy as a first-line treatment.
These studies have opened up several exciting avenues for further research. Most recently, we used our models to explore how cancer cells shape a TME that is either permissive or suppressive of a T cell response. Our findings have provided crucial new insights into the fundamental principles of anti-tumor immunity, reshaping our understanding of immunity in both health and disease (in revision).
Beyond these discoveries, the technologies established within the CombaTCancer framework have enabled us to extend our research to cancer types where little is known about the drivers and mechanism-based treatments. For example, we identified new therapeutic entry points for rare skin cancers (Leiendecker et al., EMBO Molecular Medicine 2020) and uncovered a new oncogenic virus (Human papillomavirus 42) as the driver of a rare skin cancer (digital papillary adenocarcinoma). Through machine learning approaches, we found that oncogenic papillomaviruses induce a germ cell-like program in cancer cells, which we are working towards exploiting both diagnostically and therapeutically (Leiendecker et al., Cancer Discovery, 2023).
Overall, our work has made significant strides in understanding the biology of cancer cells and immune cells and their dynamic changes in all phases of therapy, from therapy-naive tumors, the poorly understood, yet critical phases of active therapy response and therapy resistance. Through the development of innovative technologies such as the CaTCH lineage tracing system, and novel mouse models we have gained unprecedented insights into the origins and mechanisms of therapy resistance. Supported by clinical trials and extensive preclinical and clinical data, these insights have already begun to influence clinical practice, demonstrating the critical role of preclinical mouse models in elucidating clinically relevant biology.
The tools and models developed through CombaTCancer" are now widely used by our team and by researchers around the world to test new therapeutic concepts. We continue to push the boundaries by developing and applying cutting-edge technologies and concepts to provide both scientific evidence to guide and accelerate the development of new combination therapy strategies and mechanistic insights into fundamental molecular principles, from gene regulation to immunity.
The tools and models developed through CombaTCancer" are now widely used by our team and by researchers around the world to test new therapeutic concepts. We continue to push the boundaries by developing and applying cutting-edge technologies and concepts to provide both scientific evidence to guide and accelerate the development of new combination therapy strategies and mechanistic insights into fundamental molecular principles, from gene regulation to immunity.