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Results for “Cancer Biology”

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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 271 records · Page 15Linked to original sources

bioRxiv2020

Virtual-freezing fluorescence imaging flow cytometry

By virtue of the combined merits of flow cytometry and fluorescence microscopy, imaging flow cytometry (IFC) has become an established tool for cell analysis in diverse biomedical fields such as cancer biology, microbiology, immunology, hematology, and stem cell biology. However, the performance and utility of IFC are severely limited by the fundamental trade-off between throughput, sensitivity, and spatial resolution. For example, at high flow speed (i.e., high throughput), the integration time of the image sensor becomes short, resulting in reduced sensitivity or pixel resolution. Here we present an optomechanical imaging method that overcomes the trade-off by virtually "freezing" the motion of flowing cells on the image sensor to effectively achieve 1,000 times longer exposure time for microscopy-grade fluorescence image acquisition. Consequently, it enables high-throughput IFC of single cells at >10,000 cells/s without sacrificing sensitivity and spatial resolution. The availability of numerous information-rich fluorescence cell images allows high-dimensional statistical analysis and accurate classification with deep learning, as evidenced by our demonstration of unique applications in hematology and microbiology.

cell biology↗

bioRxiv2020

MutSignatures: An R Package for Extraction and Analysis of Cancer Mutational Signatures

Cancer cells accumulate somatic mutations as result of DNA damage and inaccurate repair mechanisms. Different genetic instability processes result in distinct non-random patterns of DNA mutations, also known as mutational signatures. We developed mutSignatures, an integrated R-based computational framework aimed at deciphering DNA mutational signatures. Our software provides advanced functions for importing DNA variants, computing mutation types, and extracting mutational signatures via non-negative matrix factorization. We applied mutSignatures to analyze somatic mutations found in smoking-related cancer datasets. We characterized mutational signatures that were consistent with those reported before in independent investigations. Our work demonstrates that selected mutational signatures correlated with specific clinical and molecular features across different cancer types, and revealed complementarity of specific mutational patterns that has not previously been identified. In conclusion, we propose mutSignatures as a powerful open-source tool for detecting the molecular determinants of cancer and gathering insights into cancer biology and treatment.

bioinformatics↗

bioRxiv2020

Single-shot Mesoporous Silica Rods Scaffold for Induction of Humoral Responses Against Small Antigens

Vaccines have shown significant promise in eliciting protective and therapeutic responses. However, most effective vaccines require several booster shots, and it is challenging to generate potent responses against small molecules and synthetic peptide antigens often used to increase target specificity and improve vaccine stability. As continuous antigen uptake and processing by APCs and persistent toll-like receptor (TLR) priming have been shown to amplify antigen specific humoral immunity, we explored whether a single injection of a mesoporous silica micro-rod (MSR) vaccine containing synthetic molecules and peptides can effectively generate potent and durable antigen-specific humoral immunity. A single injection of the MSR vaccine against a gonadotropin-releasing hormone (GnRH) decapeptide elicited highly potent anti-GnRH response that lasted for over 12 months. The MSR vaccine generated higher titers than bolus or alhydrogel alum vaccine formulations. Moreover, a MSR vaccine directed against a Her2/neu peptide within the Trastuzumab binding domain showed immunoreactivity to native Her2 protein on tumor cell surface and, when directed against nicotine, generated long-term anti-nicotine antibodies. Mechanistically, we found that the MSR vaccine induced persistent germinal center (GC) B-cell activity for more than 3 weeks after a single injection, generation of memory B cells, and that at least 7 days of immunostimulation by the vaccine was required to generate an effective humoral response. Together, these data suggest that the MSR vaccine represents a promising technology for synthetic antigen vaccines to bypass the need for multiple immunizations and enhance long-term production of antibodies against endogenous antigens in the context of reproductive biology, cancer, and chronic addiction.

bioengineering↗

bioRxiv2020

CReSCENT: CanceR Single Cell ExpressioN Toolkit

CReSCENTCanceR Single Cell ExpressioN Toolkit (https://crescent.cloud), is an intuitive and scalable web portal incorporating a containerized pipeline execution engine for standardized analysis of single-cell RNA sequencing (scRNA-seq) data. While scRNA-seq data for tumour specimens are readily generated, subsequent analysis requires high-performance computing infrastructure and user expertise to build analysis pipelines and tailor interpretation for cancer biology. CReSCENT uses public data sets and preconfigured pipelines that are accessible to computational biology non-experts and are user-editable to allow optimization, comparison, and reanalysis for specific experiments. Users can also upload their own scRNA-seq data for analysis and results can be kept private or shared with other users.

bioinformatics↗

bioRxiv2020

A Proteogenomic workflow reveals distinct molecular phenotypes related to breast cancer appearance

Proteogenomics approaches have enabled the generation of extensive information levels when compared to single omics technology studies, although burdened by massive experimental efforts. Here, we developed four improvements of a data independent acquisition mass spectrometry proteogenomics workflow to reveal distinct molecular phenotypes related to breast cancer appearance. We confirm mutational processes detectable at the protein level and highlight quantitation and pathway complementarity between RNA and protein data. Our analyses also validated previously established enrichments of estrogen receptor-dependent molecular features relating to transcription factor expression, and provided evidence for molecular differences related to the presence of mammographic appearances in spiculated tumors. In addition, several transcript-protein pairs displayed radically different abundance correlations depending on the overall clinical and pathological properties of the tumor. These results demonstrate that there are differentially regulated protein networks in clinically relevant sample groups, and that these protein networks influence both cancer biology as well as the abundance of potential biomarkers and drug targets.

systems biology↗

bioRxiv2020

In silico molecular target prediction unveils mebendazole as a potent MAPK14 inhibitor

The concept of polypharmacology involves the interaction of drug molecules with multiple molecular targets. It provides a unique opportunity for the repurposing of already-approved drugs to target key factors involved in human diseases. Herein, we used an in silico target prediction algorithm to investigate the mechanism of action of mebendazole, an anti-helminthic drug, currently repurposed in the treatment of brain tumors. First, we confirmed that mebendazole decreased the viability of glioblastoma cells in vitro. Our in silico approach unveiled 21 putative molecular targets for mebendazole, including 12 proteins significantly up-regulated at the gene level in glioblastoma as compared to normal brain tissue. Validation experiments were performed on three major kinases involved in cancer biology: ABL1, MAPK1/ERK2 and MAPK14/p38α. Mebendazole could inhibit the activity of these kinases in vitro in a dose-dependent manner, with a high potency against MAPK14. Its direct binding to MAPK14 was further validated in vitro and inhibition of MAPK14 kinase activity was confirmed in live glioblastoma cells. Consistent with biophysical data, molecular modeling suggested that mebendazole was able to bind to the catalytic site of MAPK14. Finally, gene silencing demonstrated that MAPK14 is involved in glioblastoma tumor spheroid growth and response to mebendazole treatment. This study thus highlighted the role of MAPK14 in the anticancer mechanism of action of mebendazole and provides further rationale for the pharmacological targeting of MAPK14 in brain tumors. It also opens new avenues for the development of novel MAPK14/p38α inhibitors to treat human diseases.Significance Statement This study provides a framework to investigate drug polypharmacology by rapidly identifying novel molecular targets of already-approved drugs. It unveils a new mechanism involved in the anticancer activity of anti-helminthic drug, mebendazole, which is currently being repurposed for the treatment of brain tumors. By helping to decipher the mechanism(s) of action of repurposed drugs in their new indications, this approach could contribute to the development of safer and more effective therapeutic strategies in oncology and beyond.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pharmacology and toxicology↗

bioRxiv2020

Multi-sample Full-length Transcriptome Analysis of 22 Breast Cancer Clinical Specimens with Long-Read Sequencing

Although transcriptome alteration is considered as one of the essential drivers of carcinogenesis, conventional short-read RNAseq technology has limited researchers from directly exploring full-length transcripts, only focusing on individual splice sites. We developed a pipeline for Multi-Sample long-read Transcriptome Assembly, MuSTA, and showed through simulations that it enables construction of transcriptome from the transcripts expressed in target samples and more accurate evaluation of transcript usage. We applied it to 22 breast cancer clinical specimens to successfully acquire cohort-wide full-length transcriptome from long-read RNAseq data. By comparing isoform existence and expression between estrogen receptor positive and triple-negative subtypes, we obtained a comprehensive set of subtype-specific isoforms and differentially used isoforms which consisted of both known and unannotated isoforms. We have also found that exon-intron structure of fusion transcripts tends to depend on their genomic regions, and have found three-piece fusion transcripts that were transcribed from complex structural rearrangements. For example, a three-piece fusion transcript resulted in aberrant expression of an endogenous retroviral gene, ERVFRD-1, which is normally expressed exclusively in placenta and supposed to protect fetus from maternal rejection, and expression of which were increased in several TCGA samples with ERVFRD-1 fusions. Our analyses of real clinical specimens and simulated data provide direct evidence that full-length transcript sequencing in multiple samples can add to our understanding of cancer biology and genomics in general.

genomics↗

bioRxiv2020

Exosomes are predominantly loaded with mRNA transcript encoding cytoplasmic proteins and exclude mRNA transcript encoding nuclear proteins

Exosomes are nanovesicles ([~]30-150 nm diameters) released via an endocytic pathway in almost all mammalian cell types. Exosomes are composed of a lipid bilayer membrane that encloses RNA, miRNA, proteins and DNA. This manuscript unravels how exosome cargo is collected by a highly precise process delineating two separate mRNA transcript entities encoding cytoplasmic and nuclear proteins separately. Ultracentrifuge isolated exosomes were directly converted into cDNA (Exo-cDNA), by a method developed in our laboratory. Cellular RNA was extracted from each cell line and cDNA was prepared (Cell-cDNA). We amplified mRNA transcripts translating cytoplasmic proteins CD10 and CXCR4 and mRNA transcripts translating nuclear proteins such as proliferating cell nuclear antigen (PCNA), CREB-BP, activation induced cytidine deaminase (AID), and terminal deoxynucleotidyl transferase (TdT). We amplified all four different mRNA transcripts (PCNA, CREB-BP, AID, and TdT) from cellular cDNA but none from exosomal cDNA (Exo-cDNA). These findings suggest that exosomes carry mRNA transcripts encoding cytoplasmic proteins only but mRNA transcripts encoding nuclear proteins could not be detected. This important observation could prove to be crucial for the exosome research community since it sheds light on one of the limitations relating to the use of exosomes as biomarkers in cancer biology and other diseases. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=118 SRC="FIGDIR/small/227223v2_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@102c790org.highwire.dtl.DTLVardef@17bcabdorg.highwire.dtl.DTLVardef@3b5ac0org.highwire.dtl.DTLVardef@c303c8_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2020

H3k27ac-HiChIP in prostate cell lines identifies risk genes for prostate cancer susceptibility

Genome-wide association studies (GWAS) have identified more than 140 prostate cancer (PrCa) risk regions which provide potential insights into causal mechanisms. Multiple lines of evidence show that a significant proportion of PrCa risk can be explained by germline causal variants that dysregulate nearby target genes in prostate-relevant tissues thus altering disease risk. The traditional approach to explore this hypothesis has been correlating GWAS variants with steady-state transcript levels, referred to as expression quantitative trait loci (eQTLs). In this work, we assess the utility of chromosome conformation capture (3C) coupled with immunoprecipitation (HiChIP) to identify target genes for PrCa GWAS risk loci. We find that interactome data confirms previously reported PrCa target genes identified through GWAS/eQTL overlap (e.g., MLPH). Interestingly, HiChIP identified links between PrCa GWAS variants and genes well-known to play a role in prostate cancer biology (e.g., AR) that are not detected by eQTL-based methods. We validate these findings through CRISPR interference (CRISPRi) perturbation of the variant-containing regulatory elements for NKX3-1 and AR in the LNCaP cell line. Our results demonstrate that looping data harbor additional information beyond eQTLs and expand the number of PrCa GWAS loci that can be linked to candidate susceptibility genes.

genomics↗

bioRxiv2020

The comprehensive roadmaps of reprogramming and transformation unveiled antagonistic roles for bHLH transcription factors in the control of cellular plasticity

Coordinated changes of cellular identity and plasticity are critical for pluripotent reprogramming (PR) and malignant transformation (MT). However, the molecular circuitries orchestrating these modifications, as well as their degree of analogy during reprogramming and transformation, remain unknown. To address this question, we generated "repro-transformable" mice models and dissected comparatively the early events underpinning PR - mediated by Oct4, Sox2, Klf4, c-Myc - and MT - triggered by oncogenic Ras and c-Myc. Transcriptomic analyses allowed the identification of a unique set of markers - the cell surface glycoprotein Thy1 and the transcription factor (TF) Bcl11b - that are commonly downregulated during PR and MT and delineate cellular intermediates (CI) highly amenable to generate pluripotent or malignant derivatives. Comprehensive transcriptomic, epigenomic and functional analyses of different CI, prone or refractory to PR/MT, unveiled that cellular plasticity acquisition precedes the broad extinction of cellular identity. It also demonstrated the existence of specific and shared molecular features of PR and MT while ensuring the identification of broad-range regulators of cellular plasticity. As a proof-of-concept, we revealed that the basic helix-loop-helix (bHLH) class A TF Atoh8 constrains rodent and human iPS cells generation as well as MT and direct neuron conversion. Mechanistically, this TF hampers the reactivation of the pluripotent network during PR and limits the acquisition of phenotypic plasticity during MT. Furthermore, an integrated analysis of Atoh8 genome-wide binding, alongside the other bHLH TFs c-Myc, Ascl1 and MyoD promoting reprogramming/transdifferentiation, unveiled how Atoh8 constrains cellular plasticity by occupying a specific subset of MEF enhancers and by finetuning WNT signalling activity. Collectively, by deconvoluting the early steps of the reprogramming and transformation roadmaps, this integrated study uncoupled changes of cellular plasticity and identity to shed light on novel insights into reprogramming and cancer biology. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=161 SRC="FIGDIR/small/424606v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1718383org.highwire.dtl.DTLVardef@1714ab8org.highwire.dtl.DTLVardef@e0958borg.highwire.dtl.DTLVardef@7a0643_HPS_FORMAT_FIGEXP M_FIG C_FIG One-sentence summaryComparative roadmaps of cellular plasticity acquisition during pluripotent reprogramming and malignant transformation.

cell biology↗

bioRxiv2021

Chronos: a CRISPR cell population dynamics model

CRISPR loss of function screens are a powerful tool to interrogate cancer biology but are known to exhibit a number of biases and artifacts that can confound the results, such as DNA cutting toxicity, incomplete phenotype penetrance and screen quality bias. Computational methods that more faithfully model the CRISPR biological experiment could more effectively extract the biology of interest than typical current methods. Here we introduce Chronos, an algorithm for inferring gene knockout fitness effects based on an explicit model of the dynamics of cell proliferation after CRISPR gene knockout. Chronos is able to exploit longitudinal CRISPR data for improved inference. Additionally, it accounts for multiple sources of bias and can effectively share information across screens when jointly analyzing large datasets such as Project Achilles and Score. We show that Chronos outperforms competing methods across a range of performance metrics in multiple types of experiments.

bioinformatics↗

bioRxiv2021

The Orb6-Sts5 Axis Regulates Stress Granule Formation and Heat Stress Response in Fission Yeast

Cellular response to environmental fluctuations, such as increased temperature, is crucial in promoting cell survival and plays an increasingly recognized role in cancer biology. Important cellular functions altered by heat stress are cell polarization and protein translation. Previous studies have shown that heat stress alters the dynamics of Cdc42, a key regulator of cell polarization in eukaryotes, and promotes RNP granule formation, reprogramming protein translation. The biological mechanisms underlying these vast changes are only partially known. Here, we report that conserved NDR kinase Orb6, a homologue of mammalian STK38, responds to heat stress and regulates heat stress resilience by modulating Cdc42 dynamics and promoting stress granule assembly. Also, we discovered a finely tuned mechanism whereby stress-activated MAP kinase Sty1 negatively regulates Orb6 kinase and Orb6 C-terminal phosphorylation during heat stress. Orb6 inhibition by Sty1 increases the sensitivity of the cell to heat stress in a temperature-specific manner, fostering increased stress resilience and metabolic adaptation. These observations highlight the role of NDR kinase in the process of heat adaptation and thermotolerance during environmental cell exposure to elevated temperatures. Summary statementNuclear Dbf2-related kinase Orb6 inhibition by stress-activated protein kinase Sty1 promotes heat stress resilience in a temperature specific manner.

cell biology↗

bioRxiv2021

Functional single cell selection and annotated profiling of dynamically changing cancer cells

A method connecting single cell genomic or transcriptomic profiles to functional cellular characteristics, in particular time-varying phenotypic changes, would be transformative for single cell and cancer biology. Here, we present fSCS: functional single cell selection. This technology combines a custom-built ultrawide field-of-view optical screening microscope, fast automated image analysis and a new photolabeling method, phototagging, using a newly synthesized visible-light-photoactivatable dye. Using fSCS, we screen, selectively photolabel and isolate cells of interest from large heterogeneous populations based on functional dynamics like fast migration, morphological variation, small molecule uptake or cell division. We combined fSCS with single cell RNA sequencing for functionally annotated transcriptomic profiling of fast migrating and spindle-shaped MCF10A cells with or without TGF{beta} induction. We identified critical genes and pathways driving aggressive migration as well as mesenchymal-like morphology that could not be detected with state-of-the-art single cell transcriptomic analysis. fSCS provides a crucial upstream selection paradigm for single cell sequencing independent of biomarkers, allows enrichment of rare cells and can facilitate the identification and understanding of molecular mechanisms underlying functional phenotypes.

bioengineering↗

bioRxiv2021

A Poor Research Landscape Hinders the Progression of Knowledge and Treatment of Reproductive Diseases

Reproductive diseases have gone under the radar for many years, resulting in insufficient diagnostics and treatments. Infertility rates are rising, preeclampsia claims over 70 000 maternal and 500 000 neonatal lives globally per year, and endometriosis affects 10% of all reproductive-aged women but is often undiagnosed for many years. Changes in policy have been enacted to mitigate the gender inequality in research investigators and subjects of medical research. However, the disparities in reproductive research advancement still exist. Here, we analyzed the reproductive science research landscape in attempt to quantify the gravity of the current situation. We find that non-reproductive organs are annually researched 5-20 times more than reproductive organs leading to an exponentially increasing relative knowledge gap in reproductive sciences. Additionally, reproductive organs (breast and prostate) are mainly researched when there is a disease-focus, leading to a lack of basic understanding of the reproductive organs. This gap in knowledge affects reproductive syndromes, as well as other bodily systems and research areas, such as cancer biology and regenerative medicine. Action must be taken by current researchers, funding organizations, and educators to combat this longstanding disregard of reproductive science.

physiology↗

bioRxiv2021

Semi-automated computational assessment of cancer organoid viability using rapid live-cell microscopy

The creation of patient-derived cancer organoids represents a key advance in preclinical modeling and has recently been applied to a variety of human solid tumor types. However, conventional methods used to assess cellular viability in tissue specimens are poorly suited for the evaluation of cancer organoids because they are time-intensive and involve tissue destruction. To address this issue, we established a suite of 3-dimensional patient-derived glioma organoids, treated them with chemoradiotherapy, stained organoids with non-toxic cell dyes, and imaged them using a rapid laser scanning confocal microscopy method termed "Apex Imaging". We then developed and tested a fragmentation algorithm to quantify heterogeneity in the topography of the organoids as a potential surrogate marker of viability. This algorithm, SSDquant, provides a 3-dimensional visual representation of the organoid surface and a numerical measurement of the sum-squared distance (SSD) from the derived mass center of the organoid. We tested whether SSD scores correlate with traditional immunohistochemistry-derived cell viability markers (cellularity and cleaved caspase 3 expression) and observed statistically significant associations between them using linear regression analysis. Our work describes a quantitative, non-invasive approach for the serial measurement of patient-derived cancer organoid viability, thus opening new avenues for the application of these models to studies of cancer biology and therapy.

bioinformatics↗

bioRxiv2022

GPC3-Unc5D complex structure and role in cell migration

Neural migration is a critical step during brain development that requires the interactions of cell-surface guidance receptors. Cancer cells often hijack these mechanisms to disseminate. Here we reveal crystal structures of Uncoordinated-5 receptor D (Unc5D) in complex with morphogen receptor glypican-3 (GPC3), forming an octameric glycoprotein complex. In the complex, four Unc5D molecules pack into an antiparallel bundle, flanked by four GPC3 molecules. Central glycan-glycan interactions are formed by N-linked glycans emanating from GPC3 (N241 in human) and C-mannosylated tryptophans of the Unc5D thrombospondin-like domains. MD simulations, mass-spectrometry and structure-based mutants validate the crystallographic data. Anti-GPC3 nanobodies enhance or weaken Unc5-GPC3 binding. Using these tools in vivo, we show that Unc5/GPC3 guide migrating pyramidal neurons in the mouse cortex, and cancer cells in an embryonic xenograft neuroblastoma model. The results demonstrate a conserved structural mechanism of cell-guidance, with the potential for wide- ranging biomedical implications in development and cancer biology.

neuroscience↗

bioRxiv2022

Cell cycle progression defects and impaired DNA damage signaling drive enlarged cells into senescence

Cellular senescence plays an important role in development, ageing, and cancer biology. Senescence is associated with increased cell size, but how this contributes to permanent cell cycle exit is poorly understood. Using reversible G1 cell cycle arrests combined with growth rate modulation, we examined the effects of excess cell size on cell cycle progression in human cells. We show that enlarged cells paradoxically have high levels of G1/S regulators relative to cells that were maintained at physiological size but also induce p21, which restrains cell cycle entry and protects against cell division failure. Furthermore, we find that enlarged cells bear an increased propensity for DNA breakage and concomitant DNA damage repair defects that are established during G1. Based on these observations, we propose that impaired DNA damage repair pathways prime enlarged cells for persistent replication-acquired damage, ultimately leading to catastrophic cell cycle failure and permanent cell cycle exit.

cell biology↗

bioRxiv2022

Tumour growth: Bayesian parameter calibration of a multiphase porous media model based on in vitro observations of Neuroblastoma spheroid growth in a hydrogel microenvironment

To unravel processes that lead to the growth of solid tumours, it is necessary to link knowledge of cancer biology with the physical properties of the tumour and its interaction with the surrounding microenvironment. Our understanding of the underlying mechanisms is however still imprecise. We therefore developed computational physics-based models, which incorporate the interaction of the tumour with its surroundings based on the theory of porous media. However, the experimental validation of such models represents a challenge to its clinical use as a prognostic tool. This study combines a physics-based model with in vitro experiments based on microfluidic devices used to mimic a 3D tumour microenvironment. By conducting a global sensitivity analysis, we identify the most influential input parameters and infer their posterior distribution based on Bayesian calibration. The resulting probability density is in agreement with the scattering of the experimental data and thus validates the modelling approach. Using the proposed workflow, we demonstrate that we can indirectly characterise the mechanical properties of neuroblastoma spheroids that cannot feasibly be measured experimentally.

bioengineering↗