Honors & Awards
ASciNA Young Scientist Award, Austrian Federal Ministry of Education, Science and Research (2019)
Wissen schaf[f]t Zukunft Award, Lower Austria (2018)
Pathway to Independence Award (K99/R00), NIH/NCI (2018-2023)
Johannes Ritschl Dissertation Prize, Lower Austrian Cancer Society (2017)
Erwin Schrödinger Fellowship, Austrian Science Fund (2017-2018)
Postdoctoral Fellow, Harvard University, Program for Evolutionary Dynamics (2017)
PhD, Institute of Science and Technology Austria, Computational and Mathematical Biology (2015)
BSc, Vienna University of Technology, Computer Science (2009)
Current Research and Scholarly Interests
Cancer is an evolutionary process that typically spans multiple decades before it causes symptoms. The survival probability of patients with a tumor diagnosed early is five to ten times higher than when diagnosed at an advanced stage. The last stage of cancer progression, metastasis, is responsible for 90% of cancer-related deaths. In a tumor with billions of cells virtually any point mutation is expected to be present in a few cells. Hence, at a genetic level, not only is every cancer type different, but also every tumor of the same type and every cell of the same tumor are different. This enormous heterogeneity poses a major barrier to drug development and long-term disease control but also represents a unique opportunity to study the evolutionary principles that govern cancer initiation and progression.
My research focuses on the stochastic biological processes underlying cancer evolution, in particular those related to the initiation, progression, spread, and treatment of cancer. The goal of this research is to accurately diagnose aggressive cancers as well as to provide new insights about metastatic spread and the development of resistance against therapies. I develop computational methods and design mathematical models to generate novel hypotheses and explain observations on a mechanistic level in close collaboration with many physician‐scientists.
An analysis of genetic heterogeneity in untreated cancers.
Nature reviews. Cancer
Genetic intratumoural heterogeneity is a natural consequence of imperfect DNA replication. Any two randomly selected cells, whether normal or cancerous, are therefore genetically different. Here, we review the different forms of genetic heterogeneity in cancer and re-analyse the extent of genetic heterogeneity within seven types of untreated epithelial cancers, with particular regard to its clinical relevance. We find that the homogeneity of predicted functional mutations in driver genes is the rule rather than the exception. In primary tumours with multiple samples, 97% of driver-gene mutations in 38 patients were homogeneous. Moreover, among metastases from the same primary tumour, 100% of the driver mutations in 17 patients were homogeneous. With a single biopsy of a primary tumour in 14 patients, the likelihood of missing a functional driver-gene mutation that was present in all metastases was 2.6%. Furthermore, all functional driver-gene mutations detected in these 14 primary tumours were present among all their metastases. Finally, we found that individual metastatic lesions responded concordantly to targeted therapies in 91% of 44 patients. These analyses indicate that the cells within the primary tumours that gave rise to metastases are genetically homogeneous with respect to functional driver-gene mutations, and we suggest that future efforts to develop combination therapies have the potential to be curative.
View details for DOI 10.1038/s41568-019-0185-x
View details for PubMedID 31455892
Precancerous neoplastic cells can move through the pancreatic ductal system
2018; 561 (7722): 201-+
Most adult carcinomas develop from noninvasive precursor lesions, a progression that is supported by genetic analysis. However, the evolutionary and genetic relationships among co-existing lesions are unclear. Here we analysed the somatic variants of pancreatic cancers and precursor lesions sampled from distinct regions of the same pancreas. After inferring evolutionary relationships, we found that the ancestral cell had initiated and clonally expanded to form one or more lesions, and that subsequent driver gene mutations eventually led to invasive pancreatic cancer. We estimate that this multi-step progression generally spans many years. These new data reframe the step-wise progression model of pancreatic cancer by illustrating that independent, high-grade pancreatic precursor lesions observed in a single pancreas often represent a single neoplasm that has colonized the ductal system, accumulating spatial and genetic divergence over time.
View details for PubMedID 30177826
Minimal functional driver gene heterogeneity among untreated metastases.
Science (New York, N.Y.)
2018; 361 (6406): 1033–37
Metastases are responsible for the majority of cancer-related deaths. Although genomic heterogeneity within primary tumors is associated with relapse, heterogeneity among treatment-naive metastases has not been comprehensively assessed. We analyzed sequencing data for 76 untreated metastases from 20 patients and inferred cancer phylogenies for breast, colorectal, endometrial, gastric, lung, melanoma, pancreatic, and prostate cancers. We found that within individual patients, a large majority of driver gene mutations are common to all metastases. Further analysis revealed that the driver gene mutations that were not shared by all metastases are unlikely to have functional consequences. A mathematical model of tumor evolution and metastasis formation provides an explanation for the observed driver gene homogeneity. Thus, single biopsies capture most of the functionally important mutations in metastases and therefore provide essential information for therapeutic decision-making.
View details for PubMedID 30190408
Limited heterogeneity of known driver gene mutations among the metastases of individual patients with pancreatic cancer
2017; 49 (3): 358-366
The extent of heterogeneity among driver gene mutations present in naturally occurring metastases-that is, treatment-naive metastatic disease-is largely unknown. To address this issue, we carried out 60× whole-genome sequencing of 26 metastases from four patients with pancreatic cancer. We found that identical mutations in known driver genes were present in every metastatic lesion for each patient studied. Passenger gene mutations, which do not have known or predicted functional consequences, accounted for all intratumoral heterogeneity. Even with respect to these passenger mutations, our analysis suggests that the genetic similarity among the founding cells of metastases was higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of known driver gene mutations among metastases in the same patient has critical and encouraging implications for the success of future targeted therapies in advanced-stage disease.
View details for DOI 10.1038/ng.3764
View details for Web of Science ID 000394917800009
View details for PubMedID 28092682
Reconstructing metastatic seeding patterns of human cancers
Reconstructing the evolutionary history of metastases is critical for understanding their basic biological principles and has profound clinical implications. Genome-wide sequencing data has enabled modern phylogenomic methods to accurately dissect subclones and their phylogenies from noisy and impure bulk tumour samples at unprecedented depth. However, existing methods are not designed to infer metastatic seeding patterns. Here we develop a tool, called Treeomics, to reconstruct the phylogeny of metastases and map subclones to their anatomic locations. Treeomics infers comprehensive seeding patterns for pancreatic, ovarian, and prostate cancers. Moreover, Treeomics correctly disambiguates true seeding patterns from sequencing artifacts; 7% of variants were misclassified by conventional statistical methods. These artifacts can skew phylogenies by creating illusory tumour heterogeneity among distinct samples. In silico benchmarking on simulated tumour phylogenies across a wide range of sample purities (15-95%) and sequencing depths (25-800 × ) demonstrates the accuracy of Treeomics compared with existing methods.
View details for DOI 10.1038/ncomms14114
View details for Web of Science ID 000393096600001
View details for PubMedID 28139641
View details for PubMedCentralID PMC5290319
Origins of lymphatic and distant metastases in human colorectal cancer.
Science (New York, N.Y.)
2017; 357 (6346): 55–60
The spread of cancer cells from primary tumors to regional lymph nodes is often associated with reduced survival. One prevailing model to explain this association posits that fatal, distant metastases are seeded by lymph node metastases. This view provides a mechanistic basis for the TNM staging system and is the rationale for surgical resection of tumor-draining lymph nodes. Here we examine the evolutionary relationship between primary tumor, lymph node, and distant metastases in human colorectal cancer. Studying 213 archival biopsy samples from 17 patients, we used somatic variants in hypermutable DNA regions to reconstruct high-confidence phylogenetic trees. We found that in 65% of cases, lymphatic and distant metastases arose from independent subclones in the primary tumor, whereas in 35% of cases they shared common subclonal origin. Therefore, two different lineage relationships between lymphatic and distant metastases exist in colorectal cancer.
View details for DOI 10.1126/science.aai8515
View details for PubMedID 28684519
Evolutionary dynamics of cancer in response to targeted combination therapy
In solid tumors, targeted treatments can lead to dramatic regressions, but responses are often short-lived because resistant cancer cells arise. The major strategy proposed for overcoming resistance is combination therapy. We present a mathematical model describing the evolutionary dynamics of lesions in response to treatment. We first studied 20 melanoma patients receiving vemurafenib. We then applied our model to an independent set of pancreatic, colorectal, and melanoma cancer patients with metastatic disease. We find that dual therapy results in long-term disease control for most patients, if there are no single mutations that cause cross-resistance to both drugs; in patients with large disease burden, triple therapy is needed. We also find that simultaneous therapy with two drugs is much more effective than sequential therapy. Our results provide realistic expectations for the efficacy of new drug combinations and inform the design of trials for new cancer therapeutics. DOI:http://dx.doi.org/10.7554/eLife.00747.001.
View details for DOI 10.7554/eLife.00747
View details for Web of Science ID 000328619300005
View details for PubMedID 23805382
View details for PubMedCentralID PMC3691570
Consecutive seeding and transfer of genetic diversity in metastasis.
Proceedings of the National Academy of Sciences of the United States of America
During metastasis, only a fraction of genetic diversity in a primary tumor is passed on to metastases. We calculate this fraction of transferred diversity as a function of the seeding rate between tumors. At one extreme, if a metastasis is seeded by a single cell, then it inherits only the somatic mutations present in the founding cell, so that none of the diversity in the primary tumor is transmitted to the metastasis. In contrast, if a metastasis is seeded by multiple cells, then some genetic diversity in the primary tumor can be transmitted. We study a multitype branching process of metastasis growth that originates from a single cell but over time receives additional cells. We derive a surprisingly simple formula that relates the expected diversity of a metastasis to the diversity in the pool of seeding cells. We calculate the probability that a metastasis is polyclonal. We apply our framework to published datasets for which polyclonality has been previously reported, analyzing 68 ovarian cancer samples, 31 breast cancer samples, and 8 colorectal cancer samples from 15 patients. For these clonally diverse metastases, under typical metastasis growth conditions, we find that 10 to 150 cells seeded each metastasis and left surviving lineages between initial formation and clinical detection.
View details for DOI 10.1073/pnas.1819408116
View details for PubMedID 31239334
Clonal replacement and heterogeneity in breast tumors treated with neoadjuvant HER2-targeted therapy.
2019; 10 (1): 657
Genomic changes observed across treatment may result from either clonal evolution or geographically disparate sampling of heterogeneous tumors. Here we use computational modeling based on analysis of fifteen primary breast tumors and find that apparent clonal change between two tumor samples can frequently be explained by pre-treatment heterogeneity, such that at least two regions are necessary to detect treatment-induced clonal shifts. To assess for clonal replacement, we devise a summary statistic based on whole-exome sequencing of a pre-treatment biopsy and multi-region sampling of the post-treatment surgical specimen and apply this measure to five breast tumors treated with neoadjuvant HER2-targeted therapy. Two tumors underwent clonal replacement with treatment, and mathematical modeling indicates these two tumors had resistant subclones prior to treatment and rates of resistance-related genomic changes that were substantially larger than previous estimates. Our results provide a needed framework to incorporate primary tumor heterogeneity in investigating the evolution of resistance.
View details for PubMedID 30737380
Growth dynamics in naturally progressing chronic lymphocytic leukaemia.
2019; 570 (7762): 474–79
How the genomic features of a patient's cancer relate to individual disease kinetics remains poorly understood. Here we used the indolent growth dynamics of chronic lymphocytic leukaemia (CLL) to analyse the growth rates and corresponding genomic patterns of leukaemia cells from 107 patients with CLL, spanning decades-long disease courses. We found that CLL commonly demonstrates not only exponential expansion but also logistic growth, which is sigmoidal and reaches a certain steady-state level. Each growth pattern was associated with marked differences in genetic composition, the pace of disease progression and the extent of clonal evolution. In a subset of patients, whose serial samples underwent next-generation sequencing, we found that dynamic changes in the disease course of CLL were shaped by the genetic events that were already present in the early slow-growing stages. Finally, by analysing the growth rates of subclones compared with their parental clones, we quantified the growth advantage conferred by putative CLL drivers in vivo.
View details for DOI 10.1038/s41586-019-1252-x
View details for PubMedID 31142838
Crosstalk in concurrent repeated games impedes direct reciprocity and requires stronger levels of forgiveness.
2018; 9 (1): 555
Direct reciprocity is a mechanism for cooperation among humans. Many of our daily interactions are repeated. We interact repeatedly with our family, friends, colleagues, members of the local and even global community. In the theory of repeated games, it is a tacit assumption that the various games that a person plays simultaneously have no effect on each other. Here we introduce a general framework that allows us to analyze "crosstalk" between a player's concurrent games. In the presence of crosstalk, the action a person experiences in one game can alter the person's decision in another. We find that crosstalk impedes the maintenance of cooperation and requires stronger levels of forgiveness. The magnitude of the effect depends on the population structure. In more densely connected social groups, crosstalk has a stronger effect. A harsh retaliator, such as Tit-for-Tat, is unable to counteract crosstalk. The crosstalk framework provides a unified interpretation of direct and upstream reciprocity in the context of repeated games.
View details for PubMedID 29416030
View details for PubMedCentralID PMC5803203
Local recurrences at the anastomotic area are clonally related to the primary tumor in sporadic colorectal carcinoma.
Anastomotic recurrences (AR) occur in 2-10% of colorectal carcinoma cases after resection of primary tumor (PT). Currently, there are no molecular data investigating their genetic profile and multiple theories exist about their pathogenesis. The aim of our study was to compare the genomic profile of AR to that of the patients' corresponding matched PT and, when available, to a distant metastasis (DM).Thirty-six tumors from 14 patients were genotyped using a capture-based, next-generation assay to define the mutational status of 341 cancer-associated genes. All patients had R0 resection of their PT and AR occurred 1.1-7.0 years following PT resection. A DM or a second AR was analyzed in 8 patients. All tumors were microsatellite stable except in one patient with Lynch syndrome.A total of 254 somatic mutations were detected including 138 mutations in the microsatellite stable (MSS) cases. The most commonly mutated genes were APC, KRAS, TP53, PIK3CA, ATM and PIK3R1. In all patients with MSS tumors the AR and PT shared between 50-100% of mutations, including mutations in key driver genes, consistent with these tumors being clonally related. Genetic events private to DM were not detected in AR and phylogenetic analysis showed that ARs were more closely related to PT than DM. In the Lynch syndrome patient the PT and AR showed distinct somatic mutations consistent with independent primaries.ARs are clonally related to PT in sporadic colorectal carcinomas and do not appear to represent seeding of the anastomotic site by distant metastases.
View details for DOI 10.18632/oncotarget.17200
View details for PubMedID 28476018
- Pancreatic cancer: Pancreatic carcinogenesis - several small steps or one giant leap? Nature reviews. Gastroenterology & hepatology 2016; 14 (1): 7-8
Mutations driving CLL and their evolution in progression and relapse.
2015; 526 (7574): 525-530
Which genetic alterations drive tumorigenesis and how they evolve over the course of disease and therapy are central questions in cancer biology. Here we identify 44 recurrently mutated genes and 11 recurrent somatic copy number variations through whole-exome sequencing of 538 chronic lymphocytic leukaemia (CLL) and matched germline DNA samples, 278 of which were collected in a prospective clinical trial. These include previously unrecognized putative cancer drivers (RPS15, IKZF3), and collectively identify RNA processing and export, MYC activity, and MAPK signalling as central pathways involved in CLL. Clonality analysis of this large data set further enabled reconstruction of temporal relationships between driver events. Direct comparison between matched pre-treatment and relapse samples from 59 patients demonstrated highly frequent clonal evolution. Thus, large sequencing data sets of clinically informative samples enable the discovery of novel genes associated with cancer, the network of relationships between the driver events, and their impact on disease relapse and clinical outcome.
View details for DOI 10.1038/nature15395
View details for PubMedID 26466571
View details for PubMedCentralID PMC4815041
Biological auctions with multiple rewards
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
2015; 282 (1812): 175-182
The competition for resources among cells, individuals or species is a fundamental characteristic of evolution. Biological all-pay auctions have been used to model situations where multiple individuals compete for a single resource. However, in many situations multiple resources with various values exist and single reward auctions are not applicable. We generalize the model to multiple rewards and study the evolution of strategies. In biological all-pay auctions the bid of an individual corresponds to its strategy and is equivalent to its payment in the auction. The decreasingly ordered rewards are distributed according to the decreasingly ordered bids of the participating individuals. The reproductive success of an individual is proportional to its fitness given by the sum of the rewards won minus its payments. Hence, successful bidding strategies spread in the population. We find that the results for the multiple reward case are very different from the single reward case. While the mixed strategy equilibrium in the single reward case with more than two players consists of mostly low-bidding individuals, we show that the equilibrium can convert to many high-bidding individuals and a few low-bidding individuals in the multiple reward case. Some reward values lead to a specialization among the individuals where one subpopulation competes for the rewards and the other subpopulation largely avoids costly competitions. Whether the mixed strategy equilibrium is an evolutionarily stable strategy (ESS) depends on the specific values of the rewards.
View details for DOI 10.1098/rspb.2015.1041
View details for Web of Science ID 000362305500021
View details for PubMedID 26180069
View details for PubMedCentralID PMC4528522
Forgiver Triumphs in Alternating Prisoner's Dilemma
2013; 8 (12)
Cooperative behavior, where one individual incurs a cost to help another, is a wide spread phenomenon. Here we study direct reciprocity in the context of the alternating Prisoner's Dilemma. We consider all strategies that can be implemented by one and two-state automata. We calculate the payoff matrix of all pairwise encounters in the presence of noise. We explore deterministic selection dynamics with and without mutation. Using different error rates and payoff values, we observe convergence to a small number of distinct equilibria. Two of them are uncooperative strict Nash equilibria representing always-defect (ALLD) and Grim. The third equilibrium is mixed and represents a cooperative alliance of several strategies, dominated by a strategy which we call Forgiver. Forgiver cooperates whenever the opponent has cooperated; it defects once when the opponent has defected, but subsequently Forgiver attempts to re-establish cooperation even if the opponent has defected again. Forgiver is not an evolutionarily stable strategy, but the alliance, which it rules, is asymptotically stable. For a wide range of parameter values the most commonly observed outcome is convergence to the mixed equilibrium, dominated by Forgiver. Our results show that although forgiving might incur a short-term loss it can lead to a long-term gain. Forgiveness facilitates stable cooperation in the presence of exploitation and noise.
View details for DOI 10.1371/journal.pone.0080814
View details for Web of Science ID 000328731800009
View details for PubMedID 24349017
View details for PubMedCentralID PMC3861238
The effect of one additional driver mutation on tumor progression
2013; 6 (1): 34-45
Tumor growth is caused by the acquisition of driver mutations, which enhance the net reproductive rate of cells. Driver mutations may increase cell division, reduce cell death, or allow cells to overcome density-limiting effects. We study the dynamics of tumor growth as one additional driver mutation is acquired. Our models are based on two-type branching processes that terminate in either tumor disappearance or tumor detection. In our first model, both cell types grow exponentially, with a faster rate for cells carrying the additional driver. We find that the additional driver mutation does not affect the survival probability of the lesion, but can substantially reduce the time to reach the detectable size if the lesion is slow growing. In our second model, cells lacking the additional driver cannot exceed a fixed carrying capacity, due to density limitations. In this case, the time to detection depends strongly on this carrying capacity. Our model provides a quantitative framework for studying tumor dynamics during different stages of progression. We observe that early, small lesions need additional drivers, while late stage metastases are only marginally affected by them. These results help to explain why additional driver mutations are typically not detected in fast-growing metastases.
View details for DOI 10.1111/eva.12020
View details for Web of Science ID 000313878800004
View details for PubMedID 23396615
View details for PubMedCentralID PMC3567469
The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers
2012; 486 (7404): 537-540
Colorectal tumours that are wild type for KRAS are often sensitive to EGFR blockade, but almost always develop resistance within several months of initiating therapy. The mechanisms underlying this acquired resistance to anti-EGFR antibodies are largely unknown. This situation is in marked contrast to that of small-molecule targeted agents, such as inhibitors of ABL, EGFR, BRAF and MEK, in which mutations in the genes encoding the protein targets render the tumours resistant to the effects of the drugs. The simplest hypothesis to account for the development of resistance to EGFR blockade is that rare cells with KRAS mutations pre-exist at low levels in tumours with ostensibly wild-type KRAS genes. Although this hypothesis would seem readily testable, there is no evidence in pre-clinical models to support it, nor is there data from patients. To test this hypothesis, we determined whether mutant KRAS DNA could be detected in the circulation of 28 patients receiving monotherapy with panitumumab, a therapeutic anti-EGFR antibody. We found that 9 out of 24 (38%) patients whose tumours were initially KRAS wild type developed detectable mutations in KRAS in their sera, three of which developed multiple different KRAS mutations. The appearance of these mutations was very consistent, generally occurring between 5 and 6 months following treatment. Mathematical modelling indicated that the mutations were present in expanded subclones before the initiation of panitumumab treatment. These results suggest that the emergence of KRAS mutations is a mediator of acquired resistance to EGFR blockade and that these mutations can be detected in a non-invasive manner. They explain why solid tumours develop resistance to targeted therapies in a highly reproducible fashion.
View details for DOI 10.1038/nature11219
View details for Web of Science ID 000305760600044
View details for PubMedID 22722843
View details for PubMedCentralID PMC3436069
Evolutionary dynamics of biological auctions
THEORETICAL POPULATION BIOLOGY
2012; 81 (1): 69-80
Many scenarios in the living world, where individual organisms compete for winning positions (or resources), have properties of auctions. Here we study the evolution of bids in biological auctions. For each auction, n individuals are drawn at random from a population of size N. Each individual makes a bid which entails a cost. The winner obtains a benefit of a certain value. Costs and benefits are translated into reproductive success (fitness). Therefore, successful bidding strategies spread in the population. We compare two types of auctions. In "biological all-pay auctions", the costs are the bid for every participating individual. In "biological second price all-pay auctions", the cost for everyone other than the winner is the bid, but the cost for the winner is the second highest bid. Second price all-pay auctions are generalizations of the "war of attrition" introduced by Maynard Smith. We study evolutionary dynamics in both types of auctions. We calculate pairwise invasion plots and evolutionarily stable distributions over the continuous strategy space. We find that the average bid in second price all-pay auctions is higher than in all-pay auctions, but the average cost for the winner is similar in both auctions. In both cases, the average bid is a declining function of the number of participants, n. The more individuals participate in an auction the smaller is the chance of winning, and thus expensive bids must be avoided.
View details for DOI 10.1016/j.tpb.2011.11.003
View details for Web of Science ID 000298938200006
View details for PubMedID 22120126
View details for PubMedCentralID PMC3279759