Christopher D. McFarland

Impact of deleterious passenger mutations on cancer progression

Cancer progression is driven by the accumulation of a small number of genetic alterations. However, these few driver alterations reside in a cancer genome alongside tens of thousands of additional mutations termed passengers. Passengers are widely believed to have no role in cancer, yet many passengers fall within protein-coding genes and other functional elements that can have potentially deleterious effects on cancer cells. Here we investigate the potential of moderately deleterious passengers to accumulate and alter the course of neoplastic progression. Our approach combines evolutionary simulations of cancer progression with an analysis of cancer sequencing data. From simulations, we find that passengers accumulate and largely evade natural selection during progression. Although individually weak, the collective burden of passengers alters the course of progression, leading to several oncological phenomena that are hard to explain with a traditional driver-centric view. We then tested the predictions of our model using cancer genomics data and confirmed that many passengers are likely damaging and have largely evaded negative selection. Finally, we use our model to explore cancer treatments that exploit the load of passengers by either (i) increasing the mutation rate or (ii) exacerbating their deleterious effects. Though both approaches lead to cancer regression, the latter is a more effective therapy. Our results suggest a unique framework for understanding cancer progression as a balance of driver and passenger mutations.

Tug-of-war between driver and passenger mutations in cancer and other adaptive processes

Significance During rapid adaptation, populations start in hostile conditions and must evolve new traits to survive. Development of cancer from a population of precancerous cells within a body is an example of such rapid adaptation. New traits required for cancer progression are acquired by driver mutations in a few key genes. Most mutations, however, are unimportant for progression and can be damaging to cancer cells, termed “passengers.” The role these damaging passengers play in cancer and other adaptive processes is unknown. Here we show that driver mutations engage in a tug-of-war with damaging passengers. This tug-of-war explains many phenomena in oncology, suggesting how to develop new therapies and target existing therapies to exploit damaging passengers. Cancer progression is an example of a rapid adaptive process where evolving new traits is essential for survival and requires a high mutation rate. Precancerous cells acquire a few key mutations that drive rapid population growth and carcinogenesis. Cancer genomics demonstrates that these few driver mutations occur alongside thousands of random passenger mutations—a natural consequence of cancer’s elevated mutation rate. Some passengers are deleterious to cancer cells, yet have been largely ignored in cancer research. In population genetics, however, the accumulation of mildly deleterious mutations has been shown to cause population meltdown. Here we develop a stochastic population model where beneficial drivers engage in a tug-of-war with frequent mildly deleterious passengers. These passengers present a barrier to cancer progression describable by a critical population size, below which most lesions fail to progress, and a critical mutation rate, above which cancers melt down. We find support for this model in cancer age–incidence and cancer genomics data that also allow us to estimate the fitness advantage of drivers and fitness costs of passengers. We identify two regimes of adaptive evolutionary dynamics and use these regimes to understand successes and failures of different treatment strategies. A tumor’s load of deleterious passengers can explain previously paradoxical treatment outcomes and suggest that it could potentially serve as a biomarker of response to mutagenic therapies. The collective deleterious effect of passengers is currently an unexploited therapeutic target. We discuss how their effects might be exacerbated by current and future therapies.

A quantitative and multiplexed approach to uncover the fitness landscape of tumor suppression in vivo

Cancer growth is a multistage, stochastic evolutionary process. While cancer genome sequencing has been instrumental in identifying the genomic alterations that occur in human tumors, the consequences of these alterations on tumor growth remain largely unexplored. Conventional genetically engineered mouse models enable the study of tumor growth in vivo, but they are neither readily scalable nor sufficiently quantitative to unravel the magnitude and mode of action of many tumor-suppressor genes. Here, we present a method that integrates tumor barcoding with ultradeep barcode sequencing (Tuba-seq) to interrogate tumor-suppressor function in mouse models of human cancer. Tuba-seq uncovers genotype-dependent distributions of tumor sizes. By combining Tuba-seq with multiplexed CRISPR–Cas9-mediated genome editing, we quantified the effects of 11 tumor-suppressor pathways that are frequently altered in human lung adenocarcinoma. Tuba-seq enables the broad quantification of the function of tumor-suppressor genes with unprecedented resolution, parallelization, and precision.

An in vivo multiplexed small-molecule screening platform

Phenotype-based small-molecule screening is a powerful method to identify molecules that regulate cellular functions. However, such screens are generally performed in vitro under conditions that do not necessarily model complex physiological conditions or disease states. Here, we use molecular cell barcoding to enable direct in vivo phenotypic screening of small-molecule libraries. The multiplexed nature of this approach allows rapid in vivo analysis of hundreds to thousands of compounds. Using this platform, we screened >700 covalent inhibitors directed toward hydrolases for their effect on pancreatic cancer metastatic seeding. We identified multiple hits and confirmed the relevant target of one compound as the lipase ABHD6. Pharmacological and genetic studies confirmed the role of this enzyme as a regulator of metastatic fitness. Our results highlight the applicability of this multiplexed screening platform for investigating complex processes in vivo.

The Damaging Effect of Passenger Mutations on Cancer Progression

Genomic instability and high mutation rates cause cancer to acquire numerous mutations and chromosomal alterations during its somatic evolution; most are termed passengers because they do not confer cancer phenotypes. Evolutionary simulations and cancer genomic studies suggest that mildly deleterious passengers accumulate and can collectively slow cancer progression. Clinical data also suggest an association between passenger load and response to therapeutics, yet no causal link between the effects of passengers and cancer progression has been established. To assess this, we introduced increasing passenger loads into human cell lines and immunocompromised mouse models. We found that passengers dramatically reduced proliferative fitness (∼3% per Mb), slowed tumor growth, and reduced metastatic progression. We developed new genomic measures of damaging passenger load that can accurately predict the fitness costs of passengers in cell lines and in human breast cancers. We conclude that genomic instability and an elevated load of DNA alterations in cancer is a double-edged sword: it accelerates the accumulation of adaptive drivers, but incurs a harmful passenger load that can outweigh driver benefit. The effects of passenger alterations on cancer fitness were unrelated to enhanced immunity, as our tests were performed either in cell culture or in immunocompromised animals. Our findings refute traditional paradigms of passengers as neutral events, suggesting that passenger load reduces the fitness of cancer cells and slows or prevents progression of both primary and metastatic disease. The antitumor effects of chemotherapies can in part be due to the induction of genomic instability and increased passenger load. Cancer Res; 77(18); 4763-72. ©2017 AACR.

Abstract 24: A genetic model of metastatic evolution: Driver and passenger mutations affect metastatic fitness

Proceedings: AACR 102nd Annual Meeting 2011‐‐ Apr 2‐6, 2011; Orlando, FL Background: The metastatic process requires that cells accomplish two feats: 1) migrate from the primary tumor into the blood stream and arrest in foreign stroma, and 2) grow from a colony of only a few cells into a metastasis of macroscopic size. This second step is highly inefficient for reasons not well understood. Our previous research in tumorigenesis found that many mildly deleterious passenger mutations accumulate in cancer and can influence neoplastic progression, yet the effect of these mutations in metastatic evolution has not been studied. Methods: We developed a model of somatic evolution of neoplastic progressions and metastatic growth. Using a modified Gillespie algorithm, individual cells in our model stochastically divide and die, occasionally acquiring advantageous driver mutations or mildly deleterious (for cancer) passenger mutations. The rate of cell division and death depend on the collective effect of accumulated passenger and driver mutations. Evolutionary pressures lead to clonal expansion and occasionally carcinogenesis. In our in silico experiments, aliquots of cells were taken from successful primary tumors and “injected” into a new micro-environment with new stromal interactions, where they were assayed for metastatic success. This allowed us to track the entire evolutionary history of metastatic cells and genomic determinants of their success. Results: Accumulation of passengers during tumorigenesis as well as metastatic progression frequently prevents initial colonies and micrometastases from developing into metastatic tumors. The population bottleneck experienced during colony formation accelerates the accumulation of deleterious passenger mutations in cancerous populations. We find that in the model, metastatic efficiency depends heavily on primary tumor size, age, and genetic diversity in a manner consistent with clinical observations. A favorable stromal environment was also critical for metastatic success. Surprisingly, we found that as the total number of mutations in neoplastic cells increased, metastatic efficiency, on average, decreased as many of these additional mutations were deleterious passengers. Conclusions: Accumulation of deleterious passenger mutations helps explain metastatic inefficiency after extravasation, as well as many other features of metastasis. Our model makes several novel predictions testable in vivo_most notably that increased mutational load may prevent or impede metastasis. Cancer treatments exploiting the deleterious effects of passenger mutations may prevent metastatic disease. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 24. doi:10.1158/1538-7445.AM2011-24

Multiplexed in vivo homology-directed repair and tumor barcoding enables parallel quantification of Kras variant oncogenicity

Large-scale genomic analyses of human cancers have cataloged somatic point mutations thought to initiate tumor development and sustain cancer growth. However, determining the functional significance of specific alterations remains a major bottleneck in our understanding of the genetic determinants of cancer. Here, we present a platform that integrates multiplexed AAV/Cas9-mediated homology-directed repair (HDR) with DNA barcoding and high-throughput sequencing to simultaneously investigate multiple genomic alterations in de novo cancers in mice. Using this approach, we introduce a barcoded library of non-synonymous mutations into hotspot codons 12 and 13 of Kras in adult somatic cells to initiate tumors in the lung, pancreas, and muscle. High-throughput sequencing of barcoded KrasHDR alleles from bulk lung and pancreas reveals surprising diversity in Kras variant oncogenicity. Rapid, cost-effective, and quantitative approaches to simultaneously investigate the function of precise genomic alterations in vivo will help uncover novel biological and clinically actionable insights into carcinogenesis.Genome editing technologies enable the rapid interrogation of genetic alterations. Here, the authors present a CRISPR/Cas9-based platform to simultaneously investigate multiple activating point mutations in de novo cancers in mice; and generate panels of Kras-variants in different tissues to induce cancer.

Mapping the in vivo fitness landscape of lung adenocarcinoma tumor suppression in mice

The functional impact of most genomic alterations found in cancer, alone or in combination, remains largely unknown. Here we integrate tumor barcoding, CRISPR/Cas9-mediated genome editing and ultra-deep barcode sequencing to interrogate pairwise combinations of tumor suppressor alterations in autochthonous mouse models of human lung adenocarcinoma. We map the tumor suppressive effects of 31 common lung adenocarcinoma genotypes and identify a landscape of context dependence and differential effect strengths.In vivo analysis of pairwise combinations of tumor suppressor losses using a barcode-based assay in mice identifies unpredicted genetic interactions and shows that the effects of tumor suppressor alterations can be context-dependent.

Passenger DNA alterations reduce cancer fitness in cell culture and mouse models

Genomic instability causes cancers to acquire hundreds to thousands of mutations and chromosomal alterations during their somatic evolution. Most of these mutations and alterations are termed passengers because they do not confer cancer phenotypes. Evolutionary simulations and cancer genomic studies suggested that mildly-deleterious passengers accumulate, collectively slow cancer progression, reduce the fitness of cancer cells and enhance the effects of therapeutics. However, these effects of passengers and their impact on clinical variables remain limited to genomic analysis. Here, to assess passengers’ effect on cell fitness and cancer, we specifically introduced increasing passenger loads into human cell lines and mouse models. We found that passenger load dramatically reduced cancer cell’s fitness in every model investigated. Passengers’ average fitness cost of ∼3% per MB, indicates that genomic instability in cancer in patients can slow tumor growth and prevent metastatic progression. We conclude that genomic instability in cancer is a double-edged sword: it accelerates the accumulation of adaptive drivers, yet incurs a harmful passenger load that can outweigh drivers’ benefit. Passenger load could be a useful biomarker for tumor aggressiveness and response to mutagenic or passenger-exacerbating therapies, including anti-tumor immunity.

Abstract IA03: Functional lung cancer genomics through in vivo genome editing

Cancer genome sequencing has been instrumental in identifying the genomic alterations that occur in human tumors. However, the functional importance of the vast majority of these alterations, both alone and in combination, remains unknown. I will describe methods that integrate tumor barcoding with CRISPR/Cas9-mediated genome editing and ultradeep barcode sequencing to interrogate multiple tumor genotypes simultaneously in autochthonous mouse models of human cancer. We initially used this method to quantify the effects of eleven of the most frequently inactivated genes in human lung adenocarcinoma on tumor growth in vivo. We also investigated the in vivo fitness advantage conferred by inactivation of each of these eleven genes in combination with inactivation of p53 or Lkb1. This map of tumor-suppressive effects for >30 common lung adenocarcinoma genotypes revealed a complex landscape of context dependence and variability in effect strength. I will also describe a platform that integrates multiplexed Cas9-mediated homology-directed repair (HDR) with DNA barcoding and high-throughput sequencing to simultaneously investigate multiple oncogenic alterations in parallel. Using this approach, we introduced a library of nonsynonymous mutations into endogenous Kras in adult somatic cells to initiate tumors. High-throughput sequencing of barcoded Kras HDR alleles from bulk tumor-bearing lung uncovered surprising diversity in Kras variant oncogenicity. These in vivo approaches may redefine our ability to understand how diverse genomic alterations impact tumor initiation, growth, malignant transformation, and therapy responses. Citation Format: Ian P. Winters, Zoe N. Rogers, Christopher D. McFarland, Pranav V. Lalgudi, Shin-Heng Chiou, Mark A. Kay, Dmitri Petrov, Monte M. Winslow. Functional lung cancer genomics through in vivo genome editing [abstract]. In: Proceedings of the Fifth AACR-IASLC International Joint Conference: Lung Cancer Translational Science from the Bench to the Clinic; Jan 8-11, 2018; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(17_Suppl):Abstract nr IA03.