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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 595 records · Page 33Linked to original sources

bioRxiv2018

CTC Marker CD117/c-kit Represents a Prostate Cancer Stem-Like Subpopulation Driving Progression, Migration, and TKI Resistance

Cancer stem-like cells (CSCs) are associated with cancer progression, metastasis, and recurrence, and may also represent a subset of circulating tumor cells (CTCs). In our prior study, CTCs in advanced prostate cancer patients were found to express CD117/c-kit in a liquid biopsy. Whether CD117 expression played an active or passive role in the aggressiveness and migration of these CTCs remained an open question. In this study, we show that CD117 expression in prostate cancer patients is associated with decreased overall and progression-free survival and that activation and phosphorylation of CD117 increases in prostate cancer patients with higher Gleason grades. To determine how CD117 expression and activation by its ligand stem cell factor (SCF, kit ligand, steel factor) alter prostate cancer aggressiveness, we used LNCaP-C4-2 and PC3-mm human prostate cancer cells, which contain a CD117+ subpopulation. We demonstrate that CD117+ cells display increased proliferation and migration. In prostaspheres, CD117 expression enhances sphere formation. In both 2D and 3D cultures, stemness marker gene expression is higher in CD117+ cells. Using xenograft limiting dilution assays and serial tumor initiation assays, we show that CD117+ cells represent a CSC population. Combined, these data indicate that CD117 expression potentially promotes tumor initiation and metastasis. Further, in cell lines, CD117 activation by SCF promotes faster proliferation and invasiveness, while blocking CD117 activation with tyrosine kinase inhibitors (TKIs) decreased progression in a context-dependent manner. We demonstrate that CD117 expression and activation drives prostate cancer aggressiveness through the CSC phenotype and TKI resistance.

cancer biology↗

bioRxiv2018

AMPKi overcomes the paradoxical activation of CRAF driven by RAF inhibitors through blocking the 14-3-3 binding to its carboxyl-terminus

The paradoxical activation of RAF kinase is the predominant challenge in cancer therapies with RAF inhibitors. The inhibitor-bound RAF molecules are able to transactivate their wild-type binding partners. 14-3-3 that binds to the carboxyl-terminus of RAF kinase has been suggested to regulate the dimer-dependent activation of RAF kinase under physiological conditions, though the molecular basis is not clear. In this study, we investigated the role of 14-3-3 in the paradoxical effect of RAF inhibitors. Firstly, we found that the 14-3-3 binding to the carboxyl-terminus of CRAF was essential for its transactivation. Further, we demonstrated that this binding enhanced the dimer affinity of CRAF. Since 14-3-3 binds to the phosphorylated motif, we next investigated and identified AMPK and CRAF itself as two putative kinases that phosphorylate redundantly the 14-3-3 binding motif of CRAF. Among RAF isoforms, CRAF plays a dominant role in the paradoxical effect of RAF inhibitors, and we thus determined whether the combinatory inhibition of AMPK and CRAF would block this effect. Indeed, our data showed that AMPKi not only blocked the RAF inhibitor-driven paradoxical activation of RAF signaling and cellular overgrowth in Ras-mutated cancer cells but also reduced the drug-resistant clones derived from BRAF(V600E)-mutated cancer cells. Finally, we showed that the 14-3-3 binding to the carboxyl-terminus of CRAF was dispensable for its catalytic function in vivo. Together, our study unraveled how 14-3-3 regulates the dimerization-driven RAF activation and identified AMPKi as a potential method to relieve the drug resistance and side effect of RAF inhibitors in cancer therapy.

cancer biology↗

bioRxiv2018

Deconvolution and phylogeny inference of structural variations in tumor genomic samples

Phylogenetic reconstruction of tumor evolution has emerged as a crucial tool for making sense of the complexity of emerging cancer genomic data sets. Despite the growing use of phylogenetics in cancer studies, though, the field has only slowly adapted to many ways that tumor evolution differs from classic species evolution. One crucial question in that regard is how to handle inference of structural variations (SVs), which are a major mechanism of evolution in cancers but have been largely neglected in tumor phylogenetics to date, in part due to the challenges of reliably detecting and typing SVs and interpreting them phylogenetically. We present a novel method for reconstructing evolutionary trajectories of SVs from bulk whole-genome sequence data via joint deconvolution and phylogenetics, to infer clonal subpopulations and reconstruct their ancestry. We establish a novel likelihood model for joint deconvolution and phylogenetic inference on bulk SV data and formulate an associated optimization algorithm. We demonstrate the approach to be efficient and accurate for realistic scenarios of SV mutation on simulated data. Application to breast cancer genomic data from The Cancer Genome Atlas (TCGA) shows it to be practical and effective at reconstructing features of SV-driven evolution in single tumors. All code can be found at https://github.com/jaebird123/tusv

cancer biology↗

bioRxiv2018

A Comprehensive Overview Of Genomic Imprinting In Breast & Its Deregulation In Cancer

Genomic imprinting, the parent-of-origin specific monoallelic expression of genes, plays an important role in growth and development. Loss of imprinting of individual genes has been found in varying cancers, yet data-analytical challenges have impeded systematic studies so far. We developed a mixture distribution model to detect monoallelically expressed loci in a genome-wide manner without the need for genotyping data, and applied the methodology on TCGA breast tissue RNA-seq data. We identified 35 putatively imprinted genes in healthy breast. In breast cancer however, HM13 was featured by significant loss of imprinting and expression upregulation, which could be linked to DNA demethylation. Other imprinted genes (25 out of 35) demonstrated consistent expression downregulation in breast cancer, which often correlated with loss of imprinting. A breast imprinted gene network, deregulated in cancer, might hence be present. In summary, our novel methodology highlights the massive deregulation of imprinting in breast cancer.

cancer biology↗

bioRxiv2018

Inhibitor of apoptosis proteins determine glioblastoma stem-like cells fate depending on oxygen level

In glioblastomas, apoptosis inhibitor proteins (IAPs) are involved in apoptotic and non-apoptotic processes. Here we used GDC-0152, a small molecule IAP inhibitor, to explore how IAPs participate in glioblastoma stem-like cell maintenance and fate under both hypoxic and normoxic environments. In hypoxia, IAPs inhibition triggered stem-like cells apoptosis and decreased proliferation in four human glioblastoma cell lines, whereas in normoxia it induced a loss of stemness and differentiation. In addition, we characterized a 3D glioblastoma spheroid model. By using MALDI images we validated that GDC-0152 penetrates in the entire sphere. TOF-SIMS analyses revealed an oxygen gradient correlated with spatial cellular heterogeneity with proliferative and apoptotic cells located close to the hypoxic core and GFAP+ cells at the periphery. Notably, Serine-Threonine Kinases activation analysis revealed that oxygen level affects signaling pathways activated by GDC-0152. In hypoxia, IAPs inhibition activated ATR whereas in normoxia it activated NF-{kappa}B. Our data brings new mechanistic insights revealing the dual role of IAPs inhibitors like GDC-0152 that are relevant to their therapeutic application in tumors like glioblastomas.

cancer biology↗

bioRxiv2018

Interconnected feedback loops among ESRP1, HAS2, and CD44 regulate epithelial-mesenchymal plasticity in cancer

Aberrant activation of epithelial-mesenchymal transition (EMT) in carcinoma cells contributes to increased migration and invasion, metastasis, drug resistance, and tumor-initiating capacity. EMT is not always a binary process, rather cells may exhibit a hybrid epithelial/mesenchymal (E/M) phenotype. ZEB1 - a key transcription factor driving EMT - can both induce and maintain a mesenchymal phenotype. Recent studies have identified two novel autocrine feedback loops utilizing ESRP1, HAS2, and CD44 that maintain high levels of ZEB1. However, how the crosstalk between these feedback loops alters the dynamics of epithelial-hybrid-mesenchymal transition remains elusive. Here, using an integrated theoretical-experimental framework, we identify that these feedback loops can enable cells to stably maintain a hybrid E/M phenotype. Moreover, computational analysis identifies the regulation of ESRP1 as a crucial node, a prediction that is validated by two complementary experiments showing that (a) overexpression of ESRP1 reverts EMT in MCF10A cells treated with TGF{beta} for 21 days, and (b) knockdown of ESRP1 in stable hybrid E/M H1975 cells drives EMT. Finally, in multiple breast cancer datasets, high levels of ESRP1, ESRP1/HAS2, and ESRP1/ZEB1 correlates with poor prognosis, supporting the relevance of ZEB1/ESRP1 and ZEB1/HAS2 axes in tumor progression. Together, our results unravel how these interconnected feedback loops act in concert to regulate ZEB1 levels and to drive the dynamics of epithelial-hybrid-mesenchymal transition.

cancer biology↗

bioRxiv2018

In situ administration of cytokine combinations induces tumor regression

Recent advances in cancer immunotherapy suggest a possibility of harnessing the immune system to defeat malignant tumors, but complex immunosuppressive microenvironment confined the therapeutic benefits to a minority of patients with solid tumors. Here we constructed a lentivector based inducible system to evaluate the therapeutic effect of cytokines in established tumors. Doxycycline (Dox) induced local expression of cytokine combinations exhibited strong synergistic effect, leading to complete regression of tumors. Notably, IL12+GMCSF+IL2 expression induced eradication of tumors in all mice tolerated with this treatment, including those bearing large tumors of ~15mm in diameter, and generated an intensive systemic antitumor immunity. Other combinations with similar immune regulatory roles also induced tumor elimination in a majority of mice. Moreover, intratumoral injection of chitosan/IL12+GMCSF+IL2 solution induced complete response in all tested syngeneic tumor models, regardless of various tumor immunograms. These results provide a versatile method for the immunotherapy of intractable malignant neoplasm.

cancer biology↗

bioRxiv2018

Generation of pulmonary neuro-endocrine cells and tumors resembling small cell lung cancers from human embryonic stem cells

SUMMARYBy blocking an important signaling pathway (called NOTCH) and interfering with expression of two tumor suppressor genes in cells derived from human embryonic stem cells, the authors have developed a model for studying highly lethal small cell lung cancers.\n\nABSTRACTCell culture models based on directed differentiation of human embryonic stem cells (hESCs) may reveal why certain constellations of genetic changes drive carcinogenesis in specialized human cell lineages. Here we demonstrate that up to 10 percent of lung progenitor cells derived from hESCs can be induced to form pulmonary neuroendocrine cells (PNECs), the putative normal precursors to small cell lung cancers (SCLCs), by inhibition of NOTCH signaling. By using small inhibitory RNAs in these cultures to reduce levels of retinoblastoma (RB) protein, the product of a gene commonly mutated in SCLCs, we can significantly expand the number of PNECs. Similarly reducing levels of TP53 protein, the product of another tumor suppressor gene commonly mutated in SCLCs, or expressing mutant KRAS or EGFR genes, did not induce or expand PNECs, consistent with lineage-specific sensitivity to loss of RB function. Tumors resembling early stage SCLC grew in immunodeficient mice after subcutaneous injection of PNEC-containing cultures in which expression of both RB and TP53 was blocked. Single-cell RNA profiles of PNECs are heterogeneous; when RB levels are reduced, the profiles show similarities to RNA profiles from early stage SCLC; when both RB and TP53 levels are reduced, the transcriptome is enriched with cell cycle-specific RNAs. Taken together, these findings suggest that genetic manipulation of hESC-derived pulmonary cells will enable studies of the initiation, progression, and treatment of this recalcitrant cancer.

cancer biology↗

bioRxiv2018

Optimizing chemo-scheduling based on tumor growth rates

We review the classic tumor growth and regression laws of Skipper and Schable based on fixed exponential growth assumptions, and Norton and Simons law based on a Gompertzian growth assumption. We then discuss ways to optimize chemotherapeutic scheduling using a Moran process evolutionary game-theory model of tumor growth that incorporates more general dynamical and evolutionary features of tumor cell kinetics. Using this model, and employing the quantitative notion of Shannon entropy which assigns high values to low-dose metronomic (LDM) therapies, and low values to maximum tolerated dose (MTD) therapies, we show that low-dose metronomic strategies can outperform maximum tolerated dose strategies, particularly for faster growing tumors. The general concept of designing different chemotherapeutic strategies for tumors with different growth characteristics is discussed.

cancer biology↗

bioRxiv2018

Competitive release in tumors

Competitive release is a bedrock principle of coevolutionary ecology and population dynamics. It is also the main mechanism by which heterogeneous tumors develop chemotherapeutic resistance. Understanding, controlling, and exploiting this important mechanism represents one of the key challenges and potential opportunities of current medical oncology. The development of sophisticated mathematical and computational models of coevolution among clonal and sub-clonal cell populations in the tumor ecosystem can guide us in predicting and shaping various responses to perturbations in the fitness landscape which is altered by chemo-toxic agents. This in turn can help us design adaptive chemotherapeutic strategies to combat the release resistant cells.

cancer biology↗

bioRxiv2018

Markov chain models of cancer metastasis

Abstract.We describe the use of Markov chain models for the purpose of quantitative forecasting of metastatic cancer progression. Each site (node) in the Markov network (directed graph) is an organ site where a secondary tumor could develop with some probability. The Markov matrix is an N x N matrix where each entry represents a transition probability of the disease progressing from one site to another during the course of the disease. The initial state-vector has a 1 at the position corresponding to the primary tumor, and 0s elsewhere (no initial metastases). The spread of the disease to other sites (metastases) is modeled as a directed random walk on the Markov network, moving from site to site with the estimated transition probabilities obtained from longitudinal data. The stochastic model produces probabilistic predictions of the likelihood of each metastatic pathway and corresponding time sequences obtained from computer Monte Carlo simulations. The main challenge is to empirically estimate the N^2 transition probabilities in the Markov matrix using appropriate longitudinal data.

cancer biology↗

bioRxiv2018

Tumour purity as a prognostic factor in colon cancer

Tumour purity is defined as the proportion of cancer cells in the tumour tissue. The impact of tumour purity on colon cancer (CC) prognosis, genetic profile and microenvironment has not been thoroughly accessed. Therefore, clinical and transcriptomic data from three public datasets, GSE17536/17537, GSE39582, and TCGA were retrospectively collected (n = 1248). Tumour purity of each sample was inferred by a computational method based on transcriptomic data. Stage III and MMR-deficient (dMMR) CC patients showed a significantly lower tumour purity. Low purity CC conferred worse survival and tumour purity was identified as an independent prognostic factor. Moreover, high tumour purity CC patients benefited more from adjuvant chemotherapy. Subsequent genomic analysis found that the mutation burden was negatively associated with tumour purity with only APC and KRAS significantly more mutated in high purity CC. However, no somatic copy number alteration event was correlated with tumour purity. Furthermore, immune-related pathways and immunotherapy-associated markers (PD-1, PD-L1, CTLA-4, LAG-3, and TIM-3) were highly enriched in low purity samples. Notably, the relative proportion of M2 macrophages and neutrophils, which indicated worse survival in CC, was negatively associated with tumour purity. Therefore, tumour purity exhibited potential value for CC prognostic stratification as well as adjuvant chemotherapy benefit prediction. The relative worse survival in low purity CC may attribute to higher mutation frequency in key pathways and purity related microenvironmental changing.\n\nSummaryLow purity colon cancer patients conferred worse survival and benefited less from adjuvant chemotherapy. The mutation burden was negatively associated with tumour purity. Low purity samples exhibited intense immune phenotype with more M2 macrophages and neutrophils infiltration.

cancer biology↗

bioRxiv2018

Targeted mutation detection in breast cancer using MammaSeqTM

BackgroundBreast cancer is the most common invasive cancer among women worldwide. Next-generation sequencing (NGS) has revolutionized the study of cancer across research labs around the globe, however genomic testing in clinical settings remain limited. Advances in sequencing reliability, pipeline analysis, accumulation of relevant data, and the reduction of costs are rapidly increasing the feasibility of NGS-based clinical decision making.\n\nMethodsWe report the development of MammaSeq, a breast cancer specific NGS panel, targeting 79 genes and 1369 mutations, optimized for use in primary and metastatic breast cancer. To validate the panel, 46 solid tumor and 14 plasma circulating-free cfDNA samples were sequenced to a mean depth of 2311X and 1820 X respectively. Variants were called using Ion Torrent Suite 4.0 and annotated with cravat CHASM. CNVKit was used to call copy number variants in the solid tumor cohort. The oncoKB Precision Oncology Database was used to identify clinically actionable variants. ddPCR was used to validate select cfDNA mutations.\n\nResultsIn cohorts of 46 solid tumors and 14 cfDNA samples from patients with advanced breast cancer we identified 592 and 43 protein coding mutations. Mutations per sample in the solid tumor cohort ranged from 1 to 128 (median 3) and the cfDNA cohort ranged from 0 to 26 (median 2.5). Copy number analysis in the solid tumor cohort identified 46 amplifications and 35 deletions. We identified 26 clinically actionable variants (levels 1-3) annotated by OncoKB, distributed across 20 out of 46 cases (40%), in the solid tumor cohort. Allele frequencies of ESR1 and FOXA1 mutations correlated with CA.27.29 levels in patient matched blood draws.\n\nConclusionsIn solid tumors biopsies and cfDNA, MammaSeq detects clinicaly actionable mutations (oncoKB levels 1-3) in 22/46 (48%) solid tumors and in 4/14 (29%) of cfDNA samples. MammaSeq is a targeted panel suitable for clinically actionable mutation detection in breast cancer.

cancer biology↗

bioRxiv2018

A Highly Efficient and Faithful MDS Patient-Derived Xenotransplantation Model for Pre-Clinical Studies

Comprehensive preclinical studies of Myelodysplastic Syndromes (MDS) have been elusive due to limited ability of MDS stem cells to engraft current immunodeficient murine hosts. We developed a novel MDS patient-derived xenotransplantation model in cytokine-humanized immunodeficient \"MISTRG\" mice that for the first time provides efficient and faithful disease representation across all MDS subtypes. MISTRG MDS patient-derived xenografts (PDX) reproduce patients' dysplastic morphology with multi-lineage representation, including erythro- and megakaryopoiesis. MISTRG MDS-PDX replicate the original sample's genetic complexity and can be propagated via serial transplantation. MISTRG MDS-PDX demonstrate the cytotoxic and differentiation potential of targeted therapeutics providing superior readouts of drug mechanism of action and therapeutic efficacy. Physiologic humanization of the hematopoietic stem cell niche proves critical to MDS stem cell propagation and function in vivo. The MISTRG MDS-PDX model opens novel avenues of research and long-awaited opportunities in MDS research.

cancer biology↗

bioRxiv2018

PET by MRI: Glucose Imaging by 13C-MRS without Dynamic Nuclear Polarization by Noise Suppression through Tensor Decomposition Rank Reduction

Metabolic reprogramming is one of the defining features of cancer and abnormal metabolism is associated with many other pathologies. Molecular imaging techniques capable of detecting such changes have become essential for cancer diagnosis, treatment planning, and surveillance. In particular, 18F-FDG (fluorodeoxyglucose) PET has emerged as an essential imaging modality for cancer because of its unique ability to detect a disturbed molecular pathway through measurements of glucose uptake. However, FDG-PET has limitations that restrict its usefulness in certain situations and the information gained is limited to glucose uptake only. 13C magnetic resonance spectroscopy theoretically has certain advantages over FDG-PET, but its inherent low sensitivity has restricted its use mostly to single voxel measurements. We show here a new method of imaging glucose metabolism in vivo that relies on a simple, but robust and efficient, post-processing procedure by the higher dimensional analog of singular value decomposition, tensor decomposition. Using this procedure, we achieve an order of magnitude increase in signal to noise in both dDNP and non-hyperpolarized non-localized experiments without sacrificing accuracy. In CSI experiments an approximately 30-fold increase was observed, enough that the glucose to lactate conversion indicative of the Warburg effect can be imaged without hyper-polarization with a time resolution of 12 s and an overall spatial resolution that compares favorably to 18F-FDG PET.

cancer biology↗

bioRxiv2018

Immune evasion and immunotherapy resistance via TGF-beta activation of extracellular matrix genes in cancer associated fibroblasts

The ability to disseminate, invade and successfully colonise other tissues is a critical hallmark of cancer that involves remodelling of the extracellular matrix (ECM) laid down by fibroblasts 1. Moreover, Cancer-Associated-Fibroblasts (CAFs) produce key growth factors and cytokines as components of the ECM that fuel tumour growth, metastasis and chemoresistance, and immune response 2-4. ECM changes also predict prognosis in pancreatic 5 and colorectal cancers 6,7. Here, we examine the landscape of ECM-gene dysregulation pan-cancer and find that a subset of ECM genes is (i) dysregulated specifically in cancer, (ii) adversely prognostic, (iii) linked to TGF-beta signalling and transcription in Cancer-Associated-Fibroblasts, (iv) enriched in immunologically active cancers, and (v) predicts responses to Immune checkpoint blockade better than mutation burden, cytolytic activity, or an interferon signature, thus identifying a novel mechanism of immune evasion for patient stratification in precision immunotherapy and pharmacological modulation.

cancer biology↗

bioRxiv2018

HIF1-alpha expressing cells induce a hypoxic-like response in neighbouring cancer cells

Hypoxia stimulates metastasis in cancer and is linked to poor patient prognosis. In tumours, oxygen levels vary and hypoxic regions exist within a generally well-oxygenated tumour. However, whilst the heterogeneous environment is known to contribute to metastatic progression, little is known about the mechanism by which heterogeneic hypoxia contributes to cancer progression. This is largely because existing experimental models do not recapitulate the heterogeneous nature of hypoxia. The primary effector of the hypoxic response is the transcription factor Hypoxia inducible factor 1-alpha (HIF1-alpha). HIF1-alpha is stabilised in response to low oxygen levels in the cellular environment and its expression is seen in hypoxic regions throughout the tumour.\n\nWe have developed a model system in which HIF1-alpha can be induced within a sub-population of cancer cells, thus enabling us to mimic the effects of heterogeneic HIF1-alpha expression.\n\nWe show that induction of HIF1-alpha not only recapitulates elements of the hypoxic response in the induced cells but also results in significant changes in proliferation, gene expression and mammosphere formation within the HIF1-alpha negative population.\n\nThese findings suggest that the HIF1-alpha expressing cells found within hypoxic regions are likely to contribute to the subsequent progression of a tumour by modifying the behaviour of cells in the non-hypoxic regions of the local micro-environment.

cancer biology↗

bioRxiv2018

A genome-wide miRNA screen identifies regulators of tetraploid cell proliferation

Tetraploid cells, which are most commonly generated by errors in cell division, are genomically unstable and have been shown to promote tumorigenesis. Recent genomic studies have estimated that [~]40% of all solid tumors have undergone a genome-doubling event during their evolution, suggesting a significant role for tetraploidy in driving the development of human cancers. To safeguard against the deleterious effects of tetraploidy, non-transformed cells that fail mitosis and become tetraploid activate both the Hippo and p53 tumor suppressor pathways to restrain further proliferation. Tetraploid cells must therefore overcome these anti-proliferative barriers to ultimately drive tumor development. However, the genetic routes through which spontaneously arising tetraploid cells adapt to regain proliferative capacity remain poorly characterized. Here, we conducted a comprehensive, gain-of-function genome-wide screen to identify miRNAs that are sufficient to promote the proliferation of tetraploid cells. Our screen identified 23 miRNAs whose overexpression significantly promotes tetraploid proliferation. The vast majority of these miRNAs facilitate tetraploid growth by enhancing mitogenic signaling pathways (e.g. miR-191-3p); however, we also identified several miRNAs that impair the p53/p21 pathway (e.g. miR-523-3p), and a single miRNA (miR-24-3p) that potently inactivates the Hippo pathway via downregulation of the tumor suppressor gene NF2. Collectively, our data reveal several avenues through which tetraploid cells may regain the proliferative capacity necessary to drive tumorigenesis.

cancer biology↗