Non-Darwinian dynamics in therapy-induced cancer drug resistance

The development of drug resistance, the prime cause of failure in cancer therapy, is commonly explained by the selection of resistant mutant cancer cells. However, dynamic non-genetic heterogeneity of clonal cell populations continuously produces metastable phenotypic variants (persisters), some of which represent stem-like states that confer resistance. Even without genetic mutations, Darwinian selection can expand these resistant variants, which would explain the invariably rapid emergence of stem-like resistant cells. Here, by using quantitative measurements and modelling, we show that appearance of multidrug resistance in HL60 leukemic cells following treatment with vincristine is not explained by Darwinian selection but by Lamarckian induction. Single-cell longitudinal monitoring confirms the induction of multidrug resistance in individual cells. Associated transcriptome changes indicate a lasting stress response consistent with a drug-induced switch between high-dimensional cancer attractors. Resistance induction correlates with Wnt pathway upregulation and is suppressed by beta-catenin knockdown, revealing a new opportunity for early therapeutic intervention against the development of drug resistance.

Intestinal stem cells differentiation and its application in cancer therapy

Maxim Norkin

Colorectal cancer (CRC) is one of the deadliest cancers worldwide. Despite extensive research in the field, new therapies targeting CRC are in urgent need. CRC is a highly heterogeneous disease with high levels of intra- and inter-patient heterogeneity. Cancer stem cells are the driving force of tumor development and metastasis. One of the approaches to treat CRC is differentiation therapy thereby induction of cancer stem cell differentiation may lead to tumor regression. Intestinal normal and cancer organoids represent an ideal model for studying the differentiation process ex vivo. Gene expression profiling of drug-treated organoids can be used for quantification of the differentiation process with high precision. RNA-seq based drug-screening platforms in organoids are not yet established. Here we developed a high-throughput high-content targeted RNA-seq-based platform (TORNADO-seq) for monitoring gene expression of large gene signatures in intestinal organoids which allowed us to quantify and evaluate complex cellular phenotypes and cellular alterations upon drug treatment. We applied TORNADO-seq in drug screening in wt and cancer intestinal organoids. We found many differentiation-inducing drugs in wt organoids, including some drugs specifically enriching for certain cell phenotypes, e.g. enteroendocrine cells. Further, we applied identified differentiation-inducing drugs to cancer organoids (APClof;KRASG12D;TP53lof) and discovered that the majority of those differentiation-inducing drugs also targeted cancer organoids. Differentiation induction seems to be a common mode of action of cancer-targeting drugs. Based on gene expression profiles of treated cancer organoids, we were able to propose and confirm the mechanism of action of several drugs indicating that cancer cells may to be sensitive to alterations in the cholesterol biosynthesis pathway. In general, utilization of TORNADO-seq allows predicting connections between cellular phenotypes and signaling pathways in organoids which can be used for hypothesis generation in a variety of biological systems. The second part of the thesis is devoted to the investigation of mechanisms underlying the accumulation of genetic alterations in CRC tumors. It is not known whether cancer driver genes affect the rate of mutation acquisition. Here we performed exome sequencing of single cell-derived organoids obtained from tumors with either APClof, APClof;KRASG12D or APClof;KRASG12D;TP53lof mutation phenotypes that reflect early stages of CRC development. We discovered that presence of KRAS and P53 mutations didn't affect the number of single nucleotide substitutions (SNSs) in tumors, while the latter was increased in APC mutated tumors compared to wt cells and was highly correlated with the tumor age. P53 inactivation was highly correlated with the presence of large-scale (>10 Mb) copy number alterations (CNAs).

EPFL2021

From gut homeostasis to cancer

Freddy Radtke

The mammalian intestine has one of the highest turnover rates in the body. The intestinal epithelium is completely renewed in less than a week. It is divided into spatially distinct compartments in the form of finger-like projections and invaginations that are dedicated to specific functions. Intestinal cells are constantly produced from a stem cell reservoir that gives rise to proliferating transient amplifying cells, which subsequently differentiate and migrate to the correct compartment before dying after having fulfilled their physiological function. In recent years, a substantial body of evidence has accumulated to support the concept that signaling pathways known to be crucial for embryonic development of multiple organisms play a critical role in tightly regulating and controlling the self-renewing process of the intestine. Moreover, the same pathways appear to be deregulated in several hereditary and sporadic colorectal cancer syndromes due to activating and/or inactivating mutations of key components of such pathways. In this review we discuss recent findings demonstrating that differentiation and homeostasis of the intestine are controlled by developmental pathways such as Wnt, Notch, TGF-beta and Hedgehog, and illustrate how their deregulation contributes to intestinal neoplasia.

2006

Single-Cell Analysis of Mycobacterial Persistence Using Microfabricated Tools

Meltem Elitas

Bacterial cells behave as individuals despite being genetically identical and subject to the same environment. Although the underlying mechanisms of cellular individuality are not well understood, temporal variation of gene expression and protein levels in individual cells could act as sources for phenotypic heterogeneity of populations. Bacterial persistence in fluctuating environments relies on such diversity, allowing some individuals, by chance, to survive a challenge that would kill an unadapted and phenotypically homogeneous population. Bacterial persistence is a non-genetic, metastable phenomenon that is readily lost upon subculture of surviving cells in the absence of the environmental stress. A medically relevant example of persistence is the fractional killing of bacteria by antibiotics, whereby a subpopulation of cells survives indefinitely despite prolonged exposure to a bactericidal drug. It is hypothesized in the case of tuberculosis (TB) that drug therapy may require administration of multiple drugs for 6-9 months in order to eliminate a subpopulation of "persister" cells. The focus of this thesis is to understand how persisters tolerate antibiotics that kill their genetically identical siblings. To address this question, automated time-lapse fluorescence microcopy was applied in conjunction with microfluidic and microelectromechanical systems (MEMS) to study bacterial responses to antibiotics in real time at the single-cell level. A genetic approach was employed to identify mutants of Mycobacterium smegmatis with altered rates of persistence against the first-line anti-TB drug isoniazid (INH). A microfluidic platform was designed for high-throughput screening of transposon (Tn) mutant libraries. A pilot screen of 1,100 Tn mutants revealed 11 mutants that showed increased (persister-up, PU) or decreased (persister-down, PD) survival when exposed to isoniazid. These mutants were further characterized in comparison to wild-type cells using the single-cell microfluidics platform. This single-cell analysis revealed distinct modes of persistence within each category, which were otherwise masked at the population level. The results indicate that persistence behavior was the cumulative result of the dynamics of cell division and cell lysis. Mutants with decreased persistence exhibited behavior at single-cell level that challenges the accepted mechanism of isoniazid-mediated killing. Therefore, these results yield new insights into antibiotic persistence and isoniazid's mode of action. Persisters cannot be easily studied in non-fractionated populations of cells where they represent a small percentage of the total. As a complementary approach, a method was developed based on dielectrophoretic (DEP) purification of naturally occurred low frequency persister cells from an antibiotic-treated bacterial culture. Purification of persister cells would allow for downstream analysis using conventional bulk/population level transcriptomic and proteomic approaches. The crossover frequencies for live and dead cells were determined to enable selective trapping or release from the device. This approach enabled a proof-of-concept enrichment of live bacteria in the mixture of live and dead cells after INH treatment, based on their dielectric properties. Quantitative confirmation of the enriched/isolated cell populations was attempted using flow cytometry. The high-throughput microfluidic screening and single-cell approaches developed in this thesis could, in principal, be applied to the genetic analysis of a wide variety of dynamic cellular processes that can be imaged by time- lapse fluorescence microscopy, such as gene expression, cell division, chromosome replication and segregation, and protein localization. The biochemical analysis of live cells isolated by dielectrophoresis-based separation would provide useful information about the underlying persistence mechanism. Dielectrophoresis could also be a valuable analytical tool for mutant characterization based on their intrinsic dielectric properties, either at single-cell or population levels. In conclusion, this thesis presents several new microfabricated tools to identify and understand bacterial persistence. The thesis illustrates how integration of microfluidic tools with automated time-lapse microscopy allows hidden characteristics that are present but invisible in the macro- world of batch cultures to be examined in a quantitative and high-throughput manner in the micro-world of single-cell analysis.