Andrew L Paek

Interests

Research

The dynamics of key signaling pathways in response to chemotherapy treatmentThe cellular response to chemotherapy treatment is often enacted by signaling hubs. These are signaling proteins that respond to multiple upstream pathways and integrate this information in order to decide between different cell fates. Single-cell studies have shown that the dynamics of these proteins (how their abundance or location changes over time) can encode information and dictate cell fate. We follow the dynamics of signaling proteins in response to chemotherapy in order to determine what patterns are associated with terminal cell fates. Dynamic patterns can reveal the architecture of signaling networks and point to potential targets to control these patterns. We leverage this information to devise strategies to push cancer cells to terminal cell fates by manipulating the dynamics of signaling proteins.

Courses

Scholarly Contributions

Journals/Publications

• Zhang, Y., Huynh, J. M., Liu, G. S., Ballweg, R., Aryeh, K. S., Paek, A. L., & Zhang, T. (2019). Designing combination therapies with modeling chaperoned machine learning. PLoS computational biology, 15(9), e1007158.
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  Chemotherapy resistance is a major challenge to the effective treatment of cancer. Thus, a systematic pipeline for the efficient identification of effective combination treatments could bring huge biomedical benefit. In order to facilitate rational design of combination therapies, we developed a comprehensive computational model that incorporates the available biological knowledge and relevant experimental data on the life-and-death response of individual cancer cells to cisplatin or cisplatin combined with the TNF-related apoptosis-inducing ligand (TRAIL). The model's predictions, that a combination treatment of cisplatin and TRAIL would enhance cancer cell death and exhibit a "two-wave killing" temporal pattern, was validated by measuring the dynamics of p53 accumulation, cell fate, and cell death in single cells. The validated model was then subjected to a systematic analysis with an ensemble of diverse machine learning methods. Though each method is characterized by a different algorithm, they collectively identified several molecular players that can sensitize tumor cells to cisplatin-induced apoptosis (sensitizers). The identified sensitizers are consistent with previous experimental observations. Overall, we have illustrated that machine learning analysis of an experimentally validated mechanistic model can convert our available knowledge into the identity of biologically meaningful sensitizers. This knowledge can then be leveraged to design treatment strategies that could improve the efficacy of chemotherapy.
• Chakrabarti, S., Paek, A. L., Reyes, J., Lasick, K. A., Lahav, G., & Michor, F. (2018). Hidden heterogeneity and circadian-controlled cell fate inferred from single cell lineages. Nature communications, 9(1), 5372.
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  The origin of lineage correlations among single cells and the extent of heterogeneity in their intermitotic times (IMT) and apoptosis times (AT) remain incompletely understood. Here we developed single cell lineage-tracking experiments and computational algorithms to uncover correlations and heterogeneity in the IMT and AT of a colon cancer cell line before and during cisplatin treatment. These correlations could not be explained using simple protein production/degradation models. Sister cell fates were similar regardless of whether they divided before or after cisplatin administration and did not arise from proximity-related factors, suggesting fate determination early in a cell's lifetime. Based on these findings, we developed a theoretical model explaining how the observed correlation structure can arise from oscillatory mechanisms underlying cell fate control. Our model recapitulated the data only with very specific oscillation periods that fit measured circadian rhythms, thereby suggesting an important role of the circadian clock in controlling cellular fates.
• Islam, S., Paek, A. L., Hammer, M., Rangarajan, S., Ruijtenbeek, R., Cooke, L., Weterings, E., & Mahadevan, D. (2018). Drug-induced aneuploidy and polyploidy is a mechanism of disease relapse in MYC/BCL2-addicted diffuse large B-cell lymphoma. Oncotarget, 9(89), 35875-35890.
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  Double-hit (DH) or double-expresser (DE) lymphomas are high-grade diffuse large B-cell lymphomas (DLBCL) that are mostly incurable with standard chemo-immunotherapy due to treatment resistance. The generation of drug-induced aneuploid/polyploid (DIAP) cells is a common effect of anti-DLBCL therapies (e.g. vincristine, doxorubicin). DIAP cells are thought to be responsible for treatment resistance, as they are capable of re-entering the cell cycle during off-therapy periods. Previously we have shown that combination of alisertib plus ibrutinib plus rituximab can partially abrogate DIAP cells and induce cell death. Here, we provide evidence that DIAP cells can re-enter the cell cycle and escape cell death during anti-DLBCL treatment. We also discuss MYC/BCL2 mediated molecular mechanism that underlie treatment resistance. We isolated aneuploid/polyploid populations of DH/DE-DLBCL cells after treatment with the aurora kinase (AK) inhibitor alisertib. Time-lapse microscopy of single polyploid cells revealed that following drug removal, a subset of these DIAP cells divide and proliferate by reductive cell divisions, including multipolar mitosis, meiosis-like nuclear fission and budding. Genomic, proteomic, and kinomic profiling demonstrated that alisertib-induced aneuploid/polyploid cells up-regulate DNA damage, DNA replication and immune evasion pathways. In addition, we identified amplified receptor tyrosine kinase and T-cell receptor signaling, as well as MYC-mediated dysregulation of the spindle assembly checkpoints . We infer that these factors contribute to treatment resistance of DIAP cells. These findings provide opportunities to develop novel DH/DE-DLBCL therapies, specifically targeting DIAP cells.
• Ballweg, R., Paek, A. L., & Zhang, T. (2017). A dynamical framework for complex fractional killing. Scientific reports, 7(1), 8002.
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  When chemotherapy drugs are applied to tumor cells with the same or similar genotypes, some cells are killed, while others survive. This fractional killing contributes to drug resistance in cancer. Through an incoherent feedforward loop, chemotherapy drugs not only activate p53 to induce cell death, but also promote the expression of apoptosis inhibitors which inhibit cell death. Consequently, cells in which p53 is activated early undergo apoptosis while cells in which p53 is activated late survive. The incoherent feedforward loop and the essential role of p53 activation timing makes fractional killing a complex dynamical challenge, which is hard to understand with intuition alone. To better understand this process, we have constructed a representative model by integrating the control of apoptosis with the relevant signaling pathways. After the model was trained to recapture the observed properties of fractional killing, it was analyzed with nonlinear dynamical tools. The analysis suggested a simple dynamical framework for fractional killing, which predicts that cell fate can be altered in three possible ways: alteration of bifurcation geometry, alteration of cell trajectories, or both. These predicted categories can explain existing strategies known to combat fractional killing and facilitate the design of novel strategies.
• Paek, A. L., Liu, J. C., Loewer, A., Forrester, W. C., & Lahav, G. (2016). Cell-to-Cell Variation in p53 Dynamics Leads to Fractional Killing. Cell, 165(3), 631-42.
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  Many chemotherapeutic drugs kill only a fraction of cancer cells, limiting their efficacy. We used live-cell imaging to investigate the role of p53 dynamics in fractional killing of colon cancer cells in response to chemotherapy. We found that both surviving and dying cells reach similar levels of p53, indicating that cell death is not determined by a fixed p53 threshold. Instead, a cell's probability of death depends on the time and levels of p53. Cells must reach a threshold level of p53 to execute apoptosis, and this threshold increases with time. The increase in p53 apoptotic threshold is due to drug-dependent induction of anti-apoptotic genes, predominantly in the inhibitors of apoptosis (IAP) family. Our study underlines the importance of measuring the dynamics of key players in response to chemotherapy to determine mechanisms of resistance and optimize the timing of combination therapy.
• U'Ren, J. M., Wisecaver, J. H., Paek, A. L., Dunn, B. L., & Hurwitz, B. L. (2015). Draft Genome Sequence of the Ale-Fermenting Saccharomyces cerevisiae Strain GSY2239. Genome announcements, 3(4).
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  Saccharomyces cerevisiae strain GSY2239 is derived from an industrial yeast strain used to ferment ale-style beer. We present here the 11.5-Mb draft genome sequence for this organism.
• Carr, A. M., Paek, A. L., & Weinert, T. (2011). DNA replication: failures and inverted fusions. Seminars in cell & developmental biology, 22(8), 866-74.
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  DNA replication normally follows the rules passed down from Watson and Crick: the chromosome duplicates as dictated by its antiparallel strands, base-pairing and leading and lagging strand differences. Real-life replication is more complicated, fraught with perils posed by chromosome damage for one, and by transcription of genes and by other perils that disrupt progress of the DNA replication machinery. Understanding the replication fork, including DNA structures, associated replisome and its regulators, is key to understanding how cells overcome perils and minimize error. Replication fork error leads to genome rearrangements and, potentially, cell death. Interest in the replication fork and its errors has recently gained added interest by the results of deep sequencing studies of human genomes. Several pathologies are associated with sometimes-bizarre genome rearrangements suggestive of elaborate replication fork failures. To try and understand the links between the replication fork, its failure and genome rearrangements, we discuss here phases of fork behavior (stall, collapse, restart and fork failures leading to rearrangements) and analyze two examples of instability from our own studies; one in fission yeast and the other in budding yeast.
• Kaochar, S., Paek, A. L., & Weinert, T. (2010). Genetics. Replication error amplified. Science (New York, N.Y.), 329(5994), 911-3.
• Paek, A. L., & Weinert, T. (2010). Choreography of the 9-1-1 checkpoint complex: DDK puts a check on the checkpoints. Molecular cell, 40(4), 505-6.
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  Checkpoint proteins respond to DNA damage by halting the cell cycle until the damage is repaired. In this issue of Molecular Cell, Furuya et al. (2010) provide evidence that checkpoint proteins need to be removed from sites of damage in order to properly repair it.
• Paek, A. L., Jones, H., Kaochar, S., & Weinert, T. (2010). The role of replication bypass pathways in dicentric chromosome formation in budding yeast. Genetics, 186(4), 1161-73.
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  Gross chromosomal rearrangements (GCRs) are large scale changes to chromosome structure and can lead to human disease. We previously showed in Saccharomyces cerevisiae that nearby inverted repeat sequences (∼20-200 bp of homology, separated by ∼1-5 kb) frequently fuse to form unstable dicentric and acentric chromosomes. Here we analyzed inverted repeat fusion in mutants of three sets of genes. First, we show that genes in the error-free postreplication repair (PRR) pathway prevent fusion of inverted repeats, while genes in the translesion branch have no detectable role. Second, we found that siz1 mutants, which are defective for Srs2 recruitment to replication forks, and srs2 mutants had opposite effects on instability. This may reflect separate roles for Srs2 in different phases of the cell cycle. Third, we provide evidence for a faulty template switch model by studying mutants of DNA polymerases; defects in DNA pol delta (lagging strand polymerase) and Mgs1 (a pol delta interacting protein) lead to a defect in fusion events as well as allelic recombination. Pol delta and Mgs1 may collaborate either in strand annealing and/or DNA replication involved in fusion and allelic recombination events. Fourth, by studying genes implicated in suppression of GCRs in other studies, we found that inverted repeat fusion has a profile of genetic regulation distinct from these other major forms of GCR formation.
• Paek, A. L., Kaochar, S., Jones, H., Elezaby, A., Shanks, L., & Weinert, T. (2009). Fusion of nearby inverted repeats by a replication-based mechanism leads to formation of dicentric and acentric chromosomes that cause genome instability in budding yeast. Genes & development, 23(24), 2861-75.
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  Large-scale changes (gross chromosomal rearrangements [GCRs]) are common in genomes, and are often associated with pathological disorders. We report here that a specific pair of nearby inverted repeats in budding yeast fuse to form a dicentric chromosome intermediate, which then rearranges to form a translocation and other GCRs. We next show that fusion of nearby inverted repeats is general; we found that many nearby inverted repeats that are present in the yeast genome also fuse, as does a pair of synthetically constructed inverted repeats. Fusion occurs between inverted repeats that are separated by several kilobases of DNA and share >20 base pairs of homology. Finally, we show that fusion of inverted repeats, surprisingly, does not require genes involved in double-strand break (DSB) repair or genes involved in other repeat recombination events. We therefore propose that fusion may occur by a DSB-independent, DNA replication-based mechanism (which we term "faulty template switching"). Fusion of nearby inverted repeats to form dicentrics may be a major cause of instability in yeast and in other organisms.
• Weinert, T., Kaochar, S., Jones, H., Paek, A., & Clark, A. J. (2009). The replication fork's five degrees of freedom, their failure and genome rearrangements. Current opinion in cell biology, 21(6), 778-84.
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  Genome rearrangements are important in pathology and evolution. The thesis of this review is that the genome is in peril when replication forks stall, and stalled forks are normally rescued by error-free mechanisms. Failure of error-free mechanisms results in large-scale chromosome changes called gross chromosomal rearrangements, GCRs, by the aficionados. In this review we discuss five error-free mechanisms a replication fork may use to overcome blockage, mechanisms that are still poorly understood. We then speculate on how genome rearrangements may occur when such mechanisms fail. Replication fork recovery failure may be an important feature of the oncogenic process. (Feedback to the authors on topics discussed herein is welcome.).
• Bolusani, S., Ma, C. H., Paek, A., Konieczka, J. H., Jayaram, M., & Voziyanov, Y. (2006). Evolution of variants of yeast site-specific recombinase Flp that utilize native genomic sequences as recombination target sites. Nucleic acids research, 34(18), 5259-69.
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  As a tool in directed genome manipulations, site-specific recombination is a double-edged sword. Exquisite specificity, while highly desirable, makes it imperative that the target site be first inserted at the desired genomic locale before it can be manipulated. We describe a combination of computational and experimental strategies, based on the tyrosine recombinase Flp and its target site FRT, to overcome this impediment. We document the systematic evolution of Flp variants that can utilize, in a bacterial assay, two sites from the human interleukin 10 gene, IL10, as recombination substrates. Recombination competence on an end target site is acquired via chimeric sites containing mixed sequences from FRT and the genomic locus. This is the first time that a tyrosine site-specific recombinase has been coaxed successfully to perform DNA exchange within naturally occurring sequences derived from a foreign genomic context. We demonstrate the ability of an Flp variant to mediate integration of a reporter cassette in Escherichia coli via recombination at one of the IL10-derived sites.
• Ghosh, S. K., Hajra, S., Paek, A., & Jayaram, M. (2006). Mechanisms for chromosome and plasmid segregation. Annual review of biochemistry, 75, 211-41.
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  The fundamental problems in duplicating and transmitting genetic information posed by the geometric and topological features of DNA, combined with its large size, are qualitatively similar for prokaryotic and eukaryotic chromosomes. The evolutionary solutions to these problems reveal common themes. However, depending on differences in their organization, ploidy, and copy number, chromosomes and plasmids display distinct segregation strategies as well. In bacteria, chromosome duplication, likely mediated by a stationary replication factory, is accompanied by rapid, directed migration of the daughter duplexes with assistance from DNA-compacting and perhaps translocating proteins. The segregation of unit-copy or low-copy bacterial plasmids is also regulated spatially and temporally by their respective partitioning systems. Eukaryotic chromosomes utilize variations of a basic pairing and unpairing mechanism for faithful segregation during mitosis and meiosis. Rather surprisingly, the yeast plasmid 2-micron circle also resorts to a similar scheme for equal partitioning during mitosis.
• Konieczka, J. H., Paek, A., Jayaram, M., & Voziyanov, Y. (2004). Recombination of hybrid target sites by binary combinations of Flp variants: mutations that foster interprotomer collaboration and enlarge substrate tolerance. Journal of molecular biology, 339(2), 365-78.
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  Strategies of directed evolution and combinatorial mutagenesis applied to the Flp site-specific recombinase have yielded recombination systems that utilize bi-specific hybrid target sites. A hybrid site is assembled from two half-sites, each harboring a distinct binding specificity. Satisfying the two specificities by a binary combination of Flp variants, while necessary, may not be sufficient to elicit recombination. We have identified amino acid substitutions that foster interprotomer collaboration between partner Flp variants to potentiate strand exchange in hybrid sites. One such substitution, A35T, acts specifically in cis with one of the two partners of a variant pair, Flp(K82M) and Flp(A35T, R281V). The same A35T mutation is also present within a group of mutations that rescue a Flp variant, Flp(Y60S), that is defective in establishing monomer-monomer interactions on the native Flp target site. Strikingly, these mutations are localized to peptide regions involved in interdomain and interprotomer interactions within the recombination complex. The same group of mutations, when transferred to the context of wild-type Flp, can relax its specificity to include non-native target sites. The hybrid Flp systems described here mimic the naturally occurring XerC/XerD recombination system that utilizes two recombinases with distinct DNA binding specificities. The ability to overcome the constraints of binding site symmetry in Flp recombination has important implications in the targeted manipulations of genomes.

Proceedings Publications

• Paek, A. L. (2019, December). Weakly Supervised Deep Learning for Detecting and Counting Dead Cells in Microscopy Images. In IEEE International Conference On Machine Learning And Applications, 1737-1743.

Presentations

• Paek, A. L. (2018, January). Measuring protein dynamics in single cells reveals mechanisms of chemotherapy resistance. University of Arizona Cancer Center, Hematology/Oncology Grand Rounds,. University of Arizona Cancer Center.