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bioRxiv2016

Fitness-valley crossing in subdivided asexual populations

Adaptations may require multiple mutations that are beneficial only in combination. To adapt, a lineage must acquire mutations that are individually neutral or deleterious before gaining the beneficial combination, thereby crossing a plateau or valley, respectively, in the mapping from genotype to fitness. Spatial population structure can facilitate plateau and valley crossing by allowing neutral and deleterious lineages to survive longer and produce more beneficial mutants. Here, we analyze adaptation across a two-mutation plateau or valley in an asexual population that is subdivided into discrete subpopulations, or demes, connected by migration. We describe how subdivision alters the dynamics of adaptation from those in an equally sized unstructured population and give a complete quantitative description of these dynamics for the island migration model. Subdivision can significantly decrease the waiting time for the adaptation if demes and migration rates are small enough that single-mutant lineages fix in one or more demes before producing the beneficial double mutant. But, the potential decrease is small in very large populations and may also be limited by the slow spread of the beneficial mutant in extremely subdivided populations. Subdivision has a smaller effect on the probability that the population adapts very quickly than on the mean time to adapt, which has important consequences in some applications, such as the development of cancer. Our results provide a general and intuitive framework for predicting the effects of spatial structure in other models and in natural populations.

Evolutionary Biology↗

bioRxiv2017

The SMuSh pathway is essential for survival during growth-induced compressive mechanical stress

Cells that proliferate within a confined environment build up mechanical compressive stress. For example, mechanical pressure emerges in the naturally space-limited tumor environment. However, little is known about how cells sense and respond to mechanical compression. We developed microfluidic bioreactors to enable the investigation of the effects of compressive stress on the growth of the genetically tractable model organism Saccharomyces cerevisiae. We used this system to determine that compressive stress is partly partly sensed through a module consisting of the mucin Msb2, and the cell wall protein Sho1, which act together as a sensor module in one of the two major osmosensing pathways in budding yeast. This signal is transmitted via the MAPKKK kinase Ste11. Thus, we term this mechanosensitive pathway the SMuSh pathway, for Ste11 through Mucin / Sho1 pathway. The SMuSh pathway delays cells in the G1 phase of the cell cycle and improves cell survival in response to growth-induced pressure. We also found that the Cell Wall Integrity (CWI) pathway contributes to the response to mechanical compressive stress. These latter results are confirmed in complimentary experiments in the accompanying manuscript from Mishra et al. When both the SMuSh and the CWI pathways are deleted, cells fail to adapt to compressive stress and all cells lyse at relatively low pressure when grown in confinement. Thus, we define a network that is essential for cell survival during growth under pressure. We term this new mechanosensory system the SCWISh (Survival through the CWI and SMuSh) network.\n\nSignificance StatementGrowth in confined environments leads to the build up of compressive mechanical stresses, which are relevant to diverse fields, from cancer to microbiology. In contrast to tensile stress, little is known about the molecular integration of compressive stresses. In this study, we elucidate the SMuSh pathway, which, together with the Cell Wall Integrity pathway, is essential for viability of the budding yeast S. cerevisiae when growing under mechanical pressure. Pressure-sensing requires the transmembrane mucin, Msb2, which is linked to the actin cortex. Our result raises the intriguing question of whether mucins, widely conserved in eukaryotes and frequently misregulated in cancers, might sense compressive stresses in other organisms, including humans.

cell biology↗

bioRxiv2018

The tumor suppressor FBW7 and the vitamin D receptor are mutual cofactors.

The E3 ligase FBW7 targets drivers of cell cycle progression such as c-MYC for proteasomal degradation. It is frequently mutated in cancer, and is a tumor suppressor. Extensive epidemiological data links vitamin D deficiency to increased incidence of several cancers, although the underlying cancer-preventive mechanisms are poorly understood. Here, we show that hormonal 1,25-dihydroxyvitamin D3 (1,25D) rapidly stimulates the interaction of the VDR with FBW7, and that of FBW7 with c-MYC. In contrast, it blocks the association of FBW7 with c-MYC antagonist MXD1. 1,25D also enhances the association of FBW7, proteasome subunits, and ubiquitin with DNA-bound c-MYC, consistent with induced degradation of c-MYC on DNA. In addition to c-MYC, 1,25D accelerates the turnover of other FBW7 target proteins. Intriguingly, FBW7 is essential for optimal VDR gene expression. It is also recruited to VDR targets genes, and its depletion attenuates 1,25D-stimulated VDR DNA binding, transactivation, and cell cycle arrest. Thus, the VDR and FBW7 are mutual cofactors, which provides a molecular basis for the cancer-preventive actions of vitamin D through accelerated turnover of FBW7 target proteins.

molecular biology↗

bioRxiv2018

SORLA-driven endosomal trafficking regulates the oncogenic fitness of HER2

Human epidermal growth factor receptor 2 (HER2) is an oncogene targeted by several kinase inhibitors and therapeutic antibodies. Endosomal trafficking of many other receptor tyrosine kinases regulates their oncogenic signaling, but the prevailing view is that HER2 is retained on the cell surface. Here we reveal that in cancer cells Sortilin related receptor 1 (SORLA; SORL1) forms a complex with HER2 and regulates its subcellular distribution by promoting recycling of endosomal HER2 back to plasma membrane. Expression of SORLA in cancer cell lines and bladder cancers correlates with HER2 levels. Depletion of SORLA targets HER2 to late endosomal/lysosomal compartments, impairs HER2-driven signaling and in vivo tumor growth. SORLA silencing also disrupts normal lysosome function and sensitizes anti-HER2 therapy sensitive and resistant cancer cells to lysosome-targeting cationic amphiphilic drugs. These findings reveal potentially important SORLA-dependent endosomal trafficking-linked vulnerabilities in HER2-driven cancers.

cell biology↗

bioRxiv2018

Mutant p53 triggers a dynamin-1/APPL1 endosome feedback loop that regulates β1 integrin recycling and migration

Multiple mechanisms contribute to cancer cell progression and metastatic activity, including changes in endocytic trafficking and signaling of cell surface receptors. We report that gain-of-function (GOF) mutant p53 expression enhances {beta} integrin and EGF receptor recycling and increases cell migration by triggering a positive feedback loop involving the activation of dynamin-1 (Dyn1) and accumulation of a spatially-restricted subpopulation of APPL1-positive perimeter endosomes. DNM1 is upregulated at both the mRNA and protein levels in a manner dependent on expression of GOF mutant p53. Perimeter APPL1 endosomes are required for rapid recycling of EGFR and {beta}1 integrins and modulate Akt signaling and Dyn1 activation to create the positive feedback loop that culminates in increased focal adhesion turnover and cell migration. Thus, Dyn1- and Akt-dependent perimeter APPL1 endosomes function as a nexus, integrating signaling and receptor trafficking, that can be co-opted by cancer cells for mutant p53-driven migration and invasion.

cell biology↗

bioRxiv2018

A Cyclin A - Myb-MuvB - Aurora B network regulates the choice between mitotic cycles and polyploid endoreplication cycles.

Cells switch to polyploid endoreplication cycles during development, wound healing, and cancer. We used integrated approaches in Drosophila to determine how mitotic cycles are remodeled into endoreplication cycles, and how similar this remodeling is between developmental and induced endoreplicating cells (devECs and iECs). We found that while only devECs had a dampened E2F1 transcriptome, repression of a Cyclin A - Myb-MuvB - Aurora B mitotic network promoted endoreplication in both devECs and iECs. Cyclin A associated with and activated Myb-MuvB to induce transcription of mitotic genes, with expression of one, Aurora B, being key for mitotic commitment. Knockdown of Cyclin A, Myb, Aurora B, or downstream cytokinetic proteins induced distinct types of endoreplication, suggesting that repression of different mitotic network steps may explain the known diversity of polyploid cycles. These findings reveal how remodeling of a mitotic network promotes polyploid cycles that contribute to development, wound healing, and cancer.

developmental biology↗

bioRxiv2019

A pseudo-meiotic centrosomal function of TEX12 in cancer

Cell division by meiosis involves an extraordinary chromosome choreography including pairing, synapsis and crossing over between homologous chromosomes1, 2. The many meiosis-specific genes involved in these processes also constitute a latent toolbox of chromosome remodelling and recombination factors that may be exploited through aberrant expression in cancer3, 4. Here, we report that TEX12, a structural protein involved in meiotic chromosome synapsis5-7, is aberrantly expressed in human cancers, with high TEX12 levels correlating with poor prognosis. We find that TEX12 knock-down causes proliferative failure in multiple cancer cell lines, and confirm its role in the early stages of oncogenesis through murine cancer models. Remarkably, somatically expressed TEX12 localises to centrosomes, leading to altered centrosome number and structure, features associated with cancer development. Further, we identify TEX12 in meiotic centrin-rich bodies, likely precursors of the mitotic centrosome, suggesting that this may represent an additional cellular function of TEX12 in meiosis that has been previously overlooked. Thus, we propose that an otherwise meiotic function of TEX12 in centrosome duplication is responsible for promoting oncogenesis and cellular proliferation in cancer, which may be targeted for novel cancer therapeutics and diagnostics.

cell biology↗

bioRxiv2018

MiR-505-3p is a Repressor of the Puberty Onset in Female Mice

Puberty onset is a complex trait regulated by multiple genetic and environmental factors. In this study, we narrowed a puberty related QTL down to a 1.7 Mb region on chromosome X in female mice and inferred miR-505-3p as the functional gene.\n\nWe conducted ectopic expression of miR-505-3p in the hypothalamus of prepubertal female mice through lentivirus-mediated orthotopic injection. The impact of miR-505-3p on female puberty was evaluated by the measurement of pubertal events and histological analysis. The results showed that female mice with overexpression of miR-505-3p in the hypothalamus manifested later puberty onset timing both in vaginal opening and ovary maturation, followed by weaker fertility lying in the longer interval time between mating and delivery, higher abortion rate and smaller litter size. We also constructed miR-505-3p knockout mice by CRISPR/Cas9 technology. MiR-505-3p knockout female mice showed earlier vaginal opening timing, higher serum gonadotrophin and higher expression of puberty-related gene, as well as its target gene Srsf1 in the hypothalamus than their wild type littermates.\n\nSrsf1 was proved to be the target gene of miR-505-3p that played the major role in this process. The results of RIP-seq (RNA Immunoprecipitation-sequencing) showed that SF2, the protein product of Srsf1 gene, mainly bound to ribosome protein (RP) mRNAs in GT1-7 cells. The collective evidence implied that miR-505-3p/SRSF1/RP could play a role in the sexual maturation regulation of mammals.\n\nAuthor summaryThe puberty onset in mammals is a vital biological process that signals the acquisition of reproductive capacity. The initiation of puberty is triggered by the activation of hypothalamic pulsatile GnRH surge. The dysregulation of pubertal development shows relevance to later health risks of type 2 diabetes, cardiovascular disease, breast cancer and other health disorders. Recent progress indicates that a lot of genes play a role in the excitatory or inhibitory regulation of GnRH release. However, the detailed pathway of pubertal timing remains unclear. Our previous studies isolated an X-linked QTL that was associated with the timing of puberty in mice. In this study, we proved that miR-505-3p was a female puberty onset regulator based on data from positional cloning, ectopic expression and knockout mouse models. We also assigned Srsf1 as the functional target gene of miR-505-3p underlying this process. The results of RIP-seq showed that SF2, the protein of Srsf1 gene, preferential bound to ribosome protein (RP) mRNAs in GT1-7 cells. We propose that miR-505-3p/SF2/RP could play a role in the sexual maturation regulation of mammals.

genetics↗

bioRxiv2018

Specific Eph Receptor-Cytoplasmic Effector Signaling Mediated by SAM-SAM Domain Interactions

The Eph receptor tyrosine kinase (RTK) family is the largest subfamily of RTKs playing critical roles in many developmental processes such as tissue patterning, neurogenesis and neuronal circuit formation, angiogenesis, etc. How the 14 Eph proteins, via their highly similar cytoplasmic domains, can transmit diverse and sometimes opposite cellular signals upon engaging ephrins is a major unresolved question. Here we systematically investigated the bindings of each SAM domain of Eph receptors to the SAM domains from SHIP2 and Odin, and uncover a highly specific SAM-SAM interaction-mediated cytoplasmic Eph-effector binding pattern. Comparative X-ray crystallographic studies of several SAM-SAM heterodimer complexes, together with biochemical and cell biology experiments, not only revealed the exquisite specificity code governing Eph/effector interactions but also allowed us to identify SAMD5 as a new Eph binding partner. Finally, these Eph/effector SAM heterodimer structures can explain numerous Eph SAM mutations identified in patients suffering from cancers and other diseases.

biophysics↗

bioRxiv2016

Context-specificity in causal signaling networks revealed by phosphoprotein profiling

SummarySignaling networks downstream of receptor tyrosine kinases are among the most extensively studied biological networks. However, it remains unclear whether signaling networks depend on biological context. Signaling networks encode causal influences - and not just correlations - between network components. Here, using a causal framework and systematic time-course assays of signaling proteins, we investigate the context-specificity of signaling networks in a cell line system. We focus on a well-defined set of signaling proteins profiled in four breast cancer cell lines under eight stimulus conditions and inhibition of specific kinases. The data, spanning multiple pathways and comprising approximately 70,000 phosphoprotein and 260,000 protein measurements, provide a wealth of testable, context-specific hypotheses, several of which we validate in independent experiments. Furthermore, the data provide a resource for computational methods development, permitting empirical assessment of causal network learning in a complex, mammalian setting.

Systems Biology↗

bioRxiv2017

Origins of fractional control in regulated cell death

Individual cells in clonal populations often respond differently to environmental changes; for binary phenotypes, such as cell death, this can be measured as a fractional response. These types of responses have been attributed to cell-intrinsic stochastic processes and variable abundances of biochemical constituents, such as proteins, but the influence of organelles has yet to be determined. We use the response to TNF-related apoptosis inducing ligand (TRAIL) and a new statistical framework for determining parameter influence on cell-to-cell variability through the inference of variance explained, DEPICTIVE, to demonstrate that variable mitochondria abundance correlates with cell survival and determines the fractional cell death response. By quantitative data analysis and modeling we attribute this effect to variable effective concentrations at the mitochondria surface of the pro-apoptotic protein Bax. Further, we demonstrate that inhibitors of antiapoptotic Bcl-2 family proteins, used in cancer treatment, may increase the diversity of cellular responses, enhancing resistance to treatment.

systems biology↗

bioRxiv2018

Mass Action Kinetic Model of Apoptosis by TRAIL-Functionalized Leukocytes

1 AbstractO_ST_ABSBackgroundC_ST_ABSMetastasis through the bloodstream contributes to poor prognosis in many types of cancer. A unique approach to target and kill colon, prostate, and other epithelial-type cancer cells in the blood has been recently developed that causes circulating leukocytes to present the cancer-specific, liposome-bound Tumor Necrosis Factor (TNF)-related apoptosis inducing ligand (TRAIL) on their surface along with E - selectin adhesion receptors. This approach, demonstrated both in vitro with human blood and in mice, mimics the cytotoxic activity of natural killer cells. The resulting liposomal TRAIL-coated leukocytes hold promise as an effective means to neutralize circulating tumor cells that enter the bloodstream with the potential to form new metastases.\n\nResultsThe computational biology study reported here examines the mechanism of this effective signal delivery, by considering the kinetics of the coupled reaction cascade, from TRAIL binding death receptor to eventual apoptosis. In this study, a collision of bound TRAIL with circulating tumor cells (CTCs) is considered and compared to a prolonged exposure of CTCs to soluble TRAIL. An existing computational model of soluble TRAIL treatment was modified to represent the kinetics from a diffusion-limited 3D reference frame into a 2D collision frame with advection and adhesion to mimic the E - selectin and membrane bound TRAIL treatment. Thus, the current model recreates the new approach of targeting cancer cells within the blood. The model was found to faithfully reproduce representative observations from experiments of liposomal TRAIL treatment under shear. The model predicts apoptosis of CTCs within 2 hr when treated with membrane bound TRAIL, while apoptosis in CTCs treated with soluble TRAIL proceeds much more slowly over the course of 10 hrs, consistent with previous experiments. Given the clearance rate of soluble TRAIL in vivo, this model predicts that the soluble TRAIL method would be rendered ineffective, as found in previous experiments.\n\nConclusionThis study therefore indicates that the kinetics of the coupled reaction cascade of liposomal E - selectin and membrane bound TRAIL colliding with CTCs can explain why this new approach to target and kill cancer cells in blood is much more effective than its soluble counterpart.

bioengineering↗

bioRxiv2018

Diagnostic value of blood gene expression-based classifiers as exemplified for acute myeloid leukemia

ABSTRACTAcute Myeloid Leukemia (AML) is a severe, mostly fatal hematopoietic malignancy. Despite nearly two decades of promising results using gene expression profiling, international recommendations for diagnosis and differential diagnosis of AML remain based on classical approaches including assessment of morphology, immunophenotyping, cytochemistry, and cytogenetics. Concerns about the translation of whole transcriptome profiling include the robustness of derived predictors when taking into account factors such as study- and site-specific effects and whether achievable levels of accuracy are sufficient for practical use. In the present study, we sought to shed light on these issues via a large-scale analysis using machine learning methods applied to a total of 12,029 samples from 105 different studies. Taking advantage of the breadth of data and the now much improved understanding of high-dimensional modeling, we show that AML can be predicted with high accuracy. High-dimensional approaches - in which multivariate signatures are learned directly from genome-wide data with no prior biological knowledge - are highly effective and robust. We explore also the relationship between predictive signatures, differential expression and known AML-related genes. Taken together, our results support the notion that transcriptome assessment could be used as part of an integrated genomic approach in cancer diagnosis and treatment to be implemented early on for diagnosis and differential diagnosis of AML.\n\nOne Sentence SummaryBlood gene expression data and machine learning were used to develop robust and accurate classifiers for diagnosis and differential diagnosis of acute myeloid leukemia based on analysis of more than 12,000 samples derived from more than 100 individual studies

genomics↗

bioRxiv2017

Molecular characterization of breast cancer cell response to metabolic drugs

Metabolic reprogramming is a hallmark of cancer. We and other authors have previously shown that breast cancer subtypes present metabolism differences. In this study, breast cancer cell lines were treated with metformin and rapamycin. The response was heterogeneous across various breast cancer cells, leading to cell cycle disruption in specific conditions. The molecular effects of these treatments were characterized using sublethal doses, SNP genotyping and mass spectrometry-based proteomics. Protein expression was analyzed using probabilistic graphical models, showing that treatments elicit various responses in some biological processes, providing insights into cell responses to metabolism drugs. Moreover, a flux balance analysis approach using protein expression values was applied, showing that predicted growth rates were comparable with cell viability measurements and suggesting an increase in reactive oxygen species response enzymes due to metformin treatment. In addition, a method to assess flux differences in whole pathways was proposed. Our results show that these various approaches provide complementary information, which can be used to suggest hypotheses about the drugs mechanisms of action and the response to drugs that target metabolism.

systems biology↗

bioRxiv2017

Deficiency of global genome nucleotide excision repair explains mutational signature observed in cancer

Nucleotide excision repair (NER) is one of the main DNA repair pathways that protect cells against genomic damage. Disruption of this pathway can contribute to the development of cancer and accelerate aging. Tumors deficient in NER are more sensitive to cisplatin treatment. Characterization of the mutational consequences of NER-deficiency may therefore provide important diagnostic opportunities. Here, we analyzed the somatic mutational profiles of adult stem cells (ASCs) from NER-deficient Ercc1-/{Delta} mice, using whole-genome sequencing analysis of clonally derived organoid cultures. Our results indicate that NER-deficiency increases the base substitution load in liver, but not in small intestinal ASCs, which coincides with a tissue-specific aging-pathology observed in these mice. The mutational landscape changes as a result of NER-deficiency in ASCs of both tissues and shows an increased contribution of Signature 8 mutations, which is a pattern with unknown etiology that is recurrently observed in various cancer types. The scattered genomic distribution of the acquired base substitutions indicates that deficiency of global-genome NER (GG-NER) is responsible for the altered mutational landscape. In line with this, we observed increased Signature 8 mutations in a GG-NER-deficient human organoid culture in which XPC was deleted using CRISPR-Cas9 gene-editing. Furthermore, genomes of NER-deficient breast tumors show an increased contribution of Signature 8 mutations compared with NER-proficient tumors. Elevated levels of Signature 8 mutations may therefore serve as a biomarker for NER-deficiency and could improve personalized cancer treatment strategies.

molecular biology↗

bioRxiv2018

Allele-specific genome editing using CRISPR-Cas9 causes off-target mutations in diploid yeast

Targeted DNA double-strand breaks (DSBs) with CRISPR-Cas9 have revolutionized genetic modification by enabling efficient genome editing in a broad range of eukaryotic systems. Accurate gene editing is possible with near-perfect efficiency in haploid or (predominantly) homozygous genomes. However, genomes exhibiting polyploidy and/or high degrees of heterozygosity are less amenable to genetic modification. Here, we report an up to 99-fold lower gene editing efficiency when editing individual heterozygous loci in the yeast genome. Moreover, Cas9-mediated introduction of a DSB resulted in large scale loss of heterozygosity affecting DNA regions up to 360 kb that resulted in introduction of nearly 1700 off-target mutations, due to replacement of sequences on the targeted chromosome by corresponding sequences from its non-targeted homolog. The observed patterns of loss of heterozygosity were consistent with homology directed repair. The extent and frequency of loss of heterozygosity represent a novel mutagenic side-effect of Cas9-mediated genome editing, which would have to be taken into account in eukaryotic gene editing. In addition to contributing to the limited genetic amenability of heterozygous yeasts, Cas9-mediated loss of heterozygosity could be particularly deleterious for human gene therapy, as loss of heterozygous functional copies of anti-proliferative and pro-apoptotic genes is a known path to cancer.

molecular biology↗

bioRxiv2018

Uncovering missed indels by leveraging unmapped reads

In current practice, Next Generation Sequencing (NGS) applications start with mapping/aligning short reads to the reference genome, with the aim of identifying genetic mutations. While most short reads can be mapped to the reference genome accurately by existing alignment tools, a significant number remain unmapped and excluded from downstream analyses thus potentially discarding important biological information hidden in the unmapped reads. This paper describes Genesis-indel, a computational pipeline that explores the unmapped reads to identify novel indels that are initially missed in the alignment procedure. Genesis-indel is applied to the unmapped reads of 30 Breast Cancer patients from TCGA. Results show that the unmapped reads are conserved between the two subtypes of breast cancer investigated in this study and might contribute to the divergence between the subtypes. Genesis-indel is able to leverage the unmapped reads to identify 72,997 small to large novel high-quality indels previously not found in the original alignments and among them, 16,141 have not been annotated in the widely used mutation database. Statistical analysis shows that these new indels mostly altered the oncogenes and tumor suppressor genes. Functional annotation further reveals that these indels are strongly correlated to pathways of cancer and can have high to moderate impact on protein functions. Additionally, these indels overlap with the genes that are missed in the indels from the originally mapped reads and contribute to the tumorigenesis in multiple carcinomas.

bioinformatics↗

bioRxiv2018

Pan-Cancer modelling of genomic alterations through gene expression

Cancer is a disease often characterized by the presence of multiple genomic alterations, which trigger altered transcriptional patterns and gene expression, which in turn sustain the processes of tumorigenesis, tumor progression and tumor maintenance. The links between genomic alterations and gene expression profiles can be utilized as the basis to build specific molecular tumorigenic relationships. In this study we perform pan-cancer predictions of the presence of single somatic mutations and copy number variations using machine learning approaches on gene expression profiles. We show that gene expression can be used to predict genomic alterations in every tumor type, where some alterations are more predictable than others. We propose gene aggregation as a tool to improve the accuracy of alteration prediction models from gene expression profiles. Ultimately, we show how this principle can be beneficial in intrinsically noisy datasets, such as those based on single cell sequencing. Author SummaryIn this article we show that transcript abundance can be used to predict the presence or absence of the majority of genomic alterations present in human cancer. We also show how these predictions can be improved by aggregating genes into small networks to counteract the effects of transcript measurement noise.

systems biology↗