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At least 19 recordsLinked to original sources

bioRxiv2026

Spatial epigenomics reveals ancestry-associated regulatory states linked to aggressive prostate cancer biology

Prostate cancer (PCa) exhibits substantial biological heterogeneity, including population associated differences in tumor aggressiveness and clinical outcomes. Although socioeconomic and environmental factors contribute to these disparities, intrinsic tumor regulatory programs may also influence disease behavior. Here, we investigated whether differences in chromatin regulation contribute to distinct tumor states in Black and White men with localized PCa. We performed spatial chromatin accessibility profiling (ATAC-seq) of prostatectomy specimens from Black and White patients receiving equal healthcare access at the Center for Prostate Disease Research (USUHS) and Walter Reed National Military Medical Center. Tumors showed distinct chromatin accessibility landscapes between the two populations, with tumors from Black patients exhibiting reduced accessibility of motifs associated with the chromatin architectural regulator CTCF and enrichment of motifs linked to epithelial-mesenchymal transition and inflammatory programs. Reduced CTCF expression was independently validated by immunohistochemistry in 99 prostatectomy specimens. These findings identify population-associated differences in chromatin regulation in localized PCa and suggest that altered CTCF-associated regulation, inflammatory signaling, and epithelial plasticity may contribute to the biological heterogeneity underlying ancestry-dependent PCa disparities.

cancer biology↗

bioRxiv2024

Investigating the impact of the interstitial fluid flow and hypoxia interface on cancer biology using a spheroid-on-chip perfusion system

Solid tumours are complex and heterogeneous systems, which exist in a dynamic biophysical microenvironment. Conventional cancer research methods have long relied on two-dimensional (2D) static cultures which neglect the dynamic, three-dimensional (3D) nature of the biophysical tumour microenvironment (TME), especially the role and impact of interstitial fluid flow (IFF). To address this, we undertook a transcriptome-wide analysis of the impact of IFF-like perfusion flow using a spheroid-on-chip microfluidic platform, which allows 3D cancer spheroids to be integrated into extracellular matrices (ECM)-like hydrogels and exposed to continuous perfusion, to mimic IFF in the TME. Importantly, we have performed these studies both in experimental (normoxia) and pathophysiological (hypoxia) oxygen conditions. Our data indicated that gene expression was altered by flow when compared to static conditions, and for the first time showed that these gene expression patterns differed in different oxygen tensions, reflecting a differential role of spheroid perfusion in IFF-like flow in tumour-relevant hypoxic conditions in the biophysical TME. We were also able to identify factors primarily linked with IFF-like conditions which are linked with prognostic value in cancer patients and therefore could correspond to a potential novel biomarker of IFF in cancer. This study therefore highlights the need to consider relevant oxygen conditions when studying the impact of flow in cancer biology, as well as demonstrating the potential of microfluidic models of flow to identify IFF-relevant tumour biomarkers.

cancer biology↗

bioRxiv2017

Co-mutation and exclusion analysis in human tumors, a means for cancer biology studies and treatment design

BackgroundMalignant tumors originate from genomic and epigenomic alterations, which lead to loss of control of the cellular circuitry. These alterations relate with each other in patterns of mutual exclusion and co-occurrence that affect prognosis and treatment response and highlight the need for multitargeted therapy. However, to the best of our knowledge, there are no systematic reports in the literature of co-dependent and mutually exclusive mutations across all types of cancer. In addition, the studies reported so far generally deal with whole genes instead of specific mutations, ignoring the fact that different alterations in the same gene can have widely different effects.\n\nResultsHere we present a systematic analysis of co-dependencies of somatic mutations across all cancer types. Combining multi testing with conditional and expected mutational probabilities, we have found pairs and networks of co-mutations and exclusions, some of them in particular types of cancer and others widespread. We have also determined that driver loci are present in more types of cancer than non driver loci, that they tend to pair within a single gene and that those pairs are more often exclusions than co-mutations.\n\nConclusionsBased on this properties, we propose new drivers that warrant experimental validation. Our analysis is potentially relevant for cancer biology and classification, as well as for the rational selection of multitargeted therapeutic approaches.

cancer biology↗

bioRxiv2018

Rapid proteotyping reveals cancer biology and drug response determinants in the NCI-60 cells

We describe the rapid and reproducible acquisition of quantitative proteome maps for the NCI-60 cancer cell lines and their use to reveal cancer biology and drug response determinants. Proteome datasets for the 60 cell lines were acquired in duplicate within 30 working days using pressure cycling technology and SWATH mass spectrometry. We consistently quantified 3,171 proteotypic proteins annotated in the SwissProt database across all cell lines, generating a data matrix with 0.1% missing values, allowing analyses of protein complexes and pathway activities across all the cancer cells. Systematic and integrative analysis of the genetic variation, mRNA expression and proteomic data of the NCI-60 cancer cell lines uncovered complementarity between different types of molecular data in the prediction of the response to 240 drugs. We additionally identified novel proteomic drug response determinants for clinically relevant chemotherapeutic and targeted therapies. We anticipate that this study represents a significant advance toward the translational application of proteotypes, which reveal biological insights that are easily missed in the absence of proteomic data.

systems biology↗

bioRxiv2026

Beyond Histology: A Unified Transcriptomic Atlas Defines Lung Cancer Biologic States and Subtypes

Lung cancer encompasses multiple histological entities with substantial molecular heterogeneity that remain incompletely resolved at population scale. Here, we constructed a unified reference landscape of lung cancer by analyzing raw RNA sequencing data from 1,824 tumors spanning adenocarcinoma (n=966), squamous cell carcinoma (n=628), small cell lung cancer (n=150), and unclassified non small cell lung cancer (n=80). Following batch correction, samples were analyzed using consensus clustering and visualized with PaCMAP to generate a molecular atlas annotated with clinical and biological metadata. Rather than segregating by pathological diagnosis, tumors organized along conserved transcriptional axes defined by tumor-intrinsic biology including proliferative or metabolic programs and immune-infiltrated states. Consensus clustering resolved nine robust molecular clusters, including an adenocarcinoma-associated subgroup, a neuroendocrine-like adenocarcinoma marked by ASCL1 activation, immune-associated regions, and bifurcation of both small cell and squamous carcinomas into biologically distinct states. Spatially restricted expression of selected clinically relevant transcripts nominated state-specific therapeutic hypotheses requiring future functional and clinical validation. Projection of patient tumors and patient-derived xenografts onto the atlas demonstrated preservation of transcriptional identity and enabled quantitative assessment of model fidelity. This integrated framework organizes lung cancer as a structured continuum of transcriptional states and provides a reference resource for biological interpretation and future translational studies.

bioinformatics↗

bioRxiv2026

Evolutionary algorithms accelerate de novo design of potent Nectin-4-specific cancer biologics

Recent advances in AI-based structural biology have made de novo protein binder design increasingly effective, yet performance remains highly target dependent. For instance, the cancer surface antigen Nectin-4, an immunoglobulin-like cell adhesion protein, proved particularly challenging for RFdiffusion-based minibinder generation, yielding substantially fewer high-quality candidates than related targets. To address this bottleneck, we integrated an evolutionary genetic algorithm (GA) with AI-driven design. GA selection with tunable stringency was coupled with diversification via partial diffusion or direct sequence editing, enabling efficient exploration of sequence-structure space and rapid enrichment of promising candidates. This AI-GA pipeline quickly produced large and diverse minibinder panels with very good in silico quality metrics and is compatible with inputs from multiple design algorithms. Pooled, large-scale experimental screening identified highly stable Nectin-4 minibinders with single-digit nanomolar down to subnanomolar affinities. Lead binders were further engineered into Nectin-4-specific flow cytometry detection reagents and potent bispecific T cell engagers, demonstrating functional activity beyond binding. Together, these results show that evolutionary refinement can unlock challenging targets and accelerate de novo protein design for next-generation cancer biologics.

bioengineering↗

bioRxiv2016

Ordinary Differential Equations in Cancer Biology

Ordinary differential equations (ODEs) provide a classical framework to model the dynamics of biological systems, given temporal experimental data. Qualitative analysis of the ODE model can lead to further biological insight and deeper understanding compared to traditional experiments alone. Simulation of the model under various perturbations can generate novel hypotheses and motivate the design of new experiments. This short paper will provide an overview of the ODE modeling framework, and present examples of how ODEs can be used to address problems in cancer biology.

Systems Biology↗

bioRxiv2016

How Cancer Genomics Drives Cancer Biology: Does Synthetic Lethality Explain Mutually Exclusive Oncogenic Mutations?

Large-scale analyses of cancer genomes are revealing patterns of mutations that suggest biologically significant ideas about many aspects of cancer, including carcinogenesis, classification, and preventive and therapeutic strategies. Among those patterns is \"mutual exclusivity\", a phenomenon observed when two or more mutations that are commonly observed in samples of a type of cancer are not found combined in individual tumors. We have been studying a striking example of mutual exclusivity: the absence of co-existing mutations in the KRAS and EGFR proto-oncogenes in human lung adenocarcinomas, despite the high individual frequencies of such mutations in this common type of cancer. Multiple lines of evidence suggest that toxic effects of the joint expression of KRAS and EGFR mutant oncogenes, rather than loss of any selective advantages conferred by a second oncogene that operates through the same signaling pathway, are responsible for the observed mutational pattern. We discuss the potential for understanding the physiological basis of such toxicity, for exploiting it therapeutically, and for extending the studies to other examples of mutual exclusivity.

cancer biology↗

bioRxiv2023

Subtype-specific circadian clock dysregulation modulates breast cancer biology, invasiveness, and prognosis.

Studies in shift workers and model organisms link circadian disruption to breast cancer. However, molecular rhythms in non-cancerous and cancerous human breast tissues are largely unknown. We reconstructed rhythms informatically, integrating locally collected, time-stamped biopsies with public datasets. For non-cancerous tissue, the inferred order of core-circadian genes matches established physiology. Inflammatory, epithelial-mesenchymal transition (EMT), and estrogen responsiveness pathways show circadian modulation. Among tumors, clock correlation analysis demonstrates subtype-specific changes in circadian organization. Luminal A organoids and informatic ordering of Luminal A samples exhibit continued, albeit disrupted rhythms. However, CYCLOPS magnitude, a measure of global rhythm strength, varied widely among Luminal A samples. Cycling of EMT pathway genes was markedly increased in high-magnitude Luminal A tumors. Patients with high-magnitude tumors had reduced 5-year survival. Correspondingly, 3D Luminal A cultures show reduced invasion following molecular clock disruption. This study links subtype-specific circadian disruption in breast cancer to EMT, metastatic potential, and prognosis.

cancer biology↗

bioRxiv2024

The Role of ISG15 in Cancer Biology: Systematic Evaluation of ISG15 Expression and Its Molecular Interactions in a Pan-Cancer Context

Background: Interferon-stimulated gene 15 (ISG15) is a ubiquitin-like modifier induced by inflammatory cues, yet its functional relevance in cancer remains unclear and context dependent. Although frequently used as an interferon marker, whether ISG15 reflects effective antitumor immunity or dysfunctional immune states across cancers has not been systematically resolved. Methods: We performed an integrative pan-cancer analysis using TCGA, CPTAC, GEO, and immunotherapy and single-cell RNA-seq cohorts. ISG15 was examined at transcriptomic, proteomic, epigenetic, genetic, immune-infiltration, and phosphoproteomic levels. Survival-modeling, mutation and copy-number analyses, pathway-enrichment, protein-protein interaction networks, and kinase enrichment were used to define functional associations, with focused comparisons between renal clear cell carcinoma (KIRC) and chromophobe carcinoma (KICH). Results: ISG15 was upregulated in all studied cancers but downregulated in KICH. Its prognostic associations were bidirectional, correlating with poor survival in KIRC, LIHC, COAD, and LGG, yet favorable outcomes in SKCM, MESO, and OV. In KIRC, high ISG15 was associated with early promoter hypomethylation, interferon signaling, immune infiltration, T-cell exhaustion signatures, and broad immune-associated phosphokinase activity. In contrast, KICH showed preserved methylation, weak interferon coupling, limited immune engagement, and phosphoproteomic enrichment of structural and trafficking pathways. Genetic alterations and deep deletions of ISG15 were associated with shorter progression-free survival. Conclusion: This study indicates that ISG15 is associated with dysfunctional immune states rather than a direct effector of tumor control. These findings highlight ISG15 as a context-specific biomarker whose functional impact likely depends on tumor type and microenvironment, warranting further mechanistic and experimental validation.

bioinformatics↗

bioRxiv2020

Pan-Cancer chromatin analysis of the human vtRNA genes uncovers their association with cancer biology.

The vault RNAs (vtRNAs) are a class of 84-141 nt eukaryotic non-coding RNAs transcribed by RNA polymerase III, named for their association with the conserved vault particle, a riboprotein complex whose function remains poorly understood. Of the 4 human vtRNA genes, the three clustered at locus 1, i.e. vtRNA1-1, vtRNA1-2 and vtRNA1-3, are integral components of the vault particle, while vtRNA2-1 is a more divergent homologue located in a second locus. Gene expression studies of vtRNAs in large cancer cohorts have been hindered by the failure of vtRNA sequencing using conventional transcriptomic approaches. However, since the vtRNAs transcription is regulated by DNA methylation, the analysis of the chromatin status of their promoters is a suitable surrogate approach to study their expression. Here we infer the landscape of vtRNA expression in cancer from the genome-wide DNA methylation (Illumina Infinium Human Methylation 450 K BeadChip) and chromatin accessibility (ATAC-seq) data of The Cancer Genome Atlas (TCGA). On average, vtRNA1-1 has the most accessible chromatin, followed by vtRNA1-2, vtRNA2-1 and vtRNA1-3. The correlation of the chromatin status of the vtRNA promoters and the binding sites of a common core of transcription factors stands for their transcriptional co-regulation by factors related to viral infection. Yet, vtRNA2-1 is the most independently regulated vtRNA homologue across tissue types. VtRNA1-1 and vtRNA1-3 chromatin status does not significantly change in cancer, though vtRNA1-3 promoter has repressive chromatin marks in a few cancer types. However, vtRNA2-1 and vtRNA1-2 expression are widely deregulated in neoplastic tissues and is compatible with a broad oncogenic role of vtRNA1-2, and both tumor suppressor and oncogenic functions of vtRNA2-1 depending of tissue contexts. Yet, vtRNA1-1, vtRNA1-2 and vtRNA2-1 promoter DNA methylation predicts a shorter patient overall survival cancer-wide. In addition, gene ontology analyses of co-regulated genes identifies a chromosome 5 regulatory domain controlling vtRNA1-1 and neighboring genes, and epithelial differentiation, immune and thyroid cancer gene sets for vtRNA1-2, vtRNA2-1 and vtRNA1-3 respectively. Furthermore, vtRNA expression patterns are associated with cancer immune subtypes. Finally, vtRNA1-2 expression is positively associated with cell proliferation and wound healing, in agreement with its oncogenic expression profile. Overall, our study presents the landscape of vtRNA expression cancer-wide, identifying co-regulated gene networks and ontological pathways associated with the different vtRNA genes that may account for their diverse roles in cancer.

cancer biology↗

bioRxiv2025

Somatostatin Receptor 2 Overexpression in Hepatocellular Carcinoma: Implications for Cancer Biology and Theranostic Applications

(1) BackgroundSomatostatin receptor 2 (SSTR2) is overexpressed in various tumors, including hepatocellular carcinoma (HCC), yet its role in tumorigenesis remains unclear. This study examines the roles of SSTR2 in the molecular pathology of HCC and explores its potential as a target for SSTR2-directed radiopharmaceuticals in this malignancy. (2) MethodsSSTR2 expression was analyzed across 22 malignancies using TNMplot and specifically in HCC through The Human Protein Atlas. Transcriptomic data, protein expression, and copy number alterations in HCC patients with varying SSTR2 levels were compared using The Cancer Genome Atlas (TCGA). Gene Ontology (GO) enrichment analysis was performed using SRplot, while survival analysis was conducted with GEO datasets. (3) ResultsMost HCC patients exhibit moderate levels of SSTR2 expression. Elevated SSTR2 expression is associated with worse overall and disease-specific survival, as well as the activation of pathways involved in tumor growth and metastasis. Furthermore, SSTR2 expression is linked to key oncogenes and receptor tyrosine kinases. (4) ConclusionsSSTR2 in HCC signifies an oncogenic network and represents a promising therapeutic target to inhibit tumor invasion and serve as a theranostic biomarker. HCC patients with elevated SSTR2 expression could benefit from SSTR2-targeted theranostics, enabling enhanced tumor detection and more effective therapy.

cancer biology↗

bioRxiv2023

Complete Synthesis and Stereochemical Assignment of Novel Curcuphenol Analogues Possessing Anti-Metastatic Cancer Biological Activity

For eons, turmeric and curcumin have been used as culinary spices and as traditional medicines and as vogue dietary supplements for a growing list of disorders, including arthritis, digestive disorders, respiratory infections, allergies, liver disease, depression and cancer. The activities of these spices are commonly attributed to curcuminoids; however, the medical applications of this class of compounds has been limited due to the low water solubility, chemical instability, acid lability, poor absorption, rapid catabolism by enzymes of the diverse curcuminoids contained in turmeric and curcumin extracts. Furthermore, identifying the bio-active curcuminoids with unique molecular entities responsible for specific medicinal benefit is at its infancy. To overcome these many issues and substantially advance this area of inquiry, we created a water-soluble achiral curcuphenol analogue and a water-soluble racemic analogue that have enhanced chemical characteristics and biological performance, and we subsequently demonstrated their ability to reverse the immune-escape phenotype, a process that enables tumours to hide from host immune responses and thereby provides tumours a significant growth advantage to metastatic tumours. The discovery that curcuphenols can reverse tumour immune-escape mechanisms and thereby reduce tumour growth, provides a rationale for the development of advanced dissecting nutraceuticals and bioceuticals for unique chemical entities as therapeutic building blocks to synthesize analogues with optimal chemical characteristics capable of harnessing the power of the immune system to extinguish metastatic cancers and beyond.

biochemistry↗

bioRxiv2024

Cell 3D Positioning by Optical encoding (C3PO) and its application to spatial transcriptomics

Current state-of-the-art spatial omics approaches suffer from the drawback that they are tissue section-based and thus inherently 2-dimensional. A full understanding of biological processes will only be possible when such data is available in 3-dimensions (3D). Here, we introduce Cell 3D Positioning by Optical encoding (C3PO) - the first technique capable of reconstructing the 3D positions of cells in a tissue, after they have been fully dissociated for single-cell omics analysis. It imposes a Cartesian coordinate system of positions on the tissue and cells of interest, before dissociation. This is created by multiple orthogonal spatial gradients of active fluorophores, carefully shaped by a 3D bleaching method, such that each position in the tissue is encoded by a unique fluorescent address. Upon dissociation of the tissue the fluorescent addresses of the cells can be read via an appropriate device (such as a FACS machine) to computationally reconstruct the tissue in 3D, before omics are performed downstream. Here, we show two proof-of-principle results for C3PO. First, pure C3PO without omics, to reconstruct the 3D geometry of a developing mouse limb bud. Second, an application of C3PO to spatial transcriptomics, revealing the expression patterns of 73 genes with interesting gene expression patterns in the developing limb.. C3PO is a genuinely novel approach to reconstruct the original 3D positions of cells in a tissue after dissociation. Combined with transcriptomics, it can play a significant role in the study of any tissue or organ in which 3D structure and geometry is important, such as developmental biology, cancer biology and neuroscience. It is not an omics technique per se, and in the future could be combined with the growing family of other omics technologies. One sentence summaryC3PO is a novel optical technique that can preserve the 3D positional coordinates of cells after tissue dissociation, enabling a radically new approach to spatial transcriptomics.

molecular biology↗

bioRxiv2024

OneSC: A computational platform for recapitulating cell state transitions

Computational modelling of cell state transitions has been a great interest of many in the field of developmental biology, cancer biology and cell fate engineering because it enables performing perturbation experiments in silico more rapidly and cheaply than could be achieved in a wet lab. Recent advancements in single-cell RNA sequencing (scRNA-seq) allow the capture of high- resolution snapshots of cell states as they transition along temporal trajectories. Using these high-throughput datasets, we can train computational models to generate in silico synthetic cells that faithfully mimic the temporal trajectories. Here we present OneSC, a platform that can simulate synthetic cells across developmental trajectories using systems of stochastic differential equations govern by a core transcription factors (TFs) regulatory network. Different from the current network inference methods, OneSC prioritizes on generating Boolean network that produces faithful cell state transitions and steady cell states that mimic real biological systems. Applying OneSC to real data, we inferred a core TF network using a mouse myeloid progenitor scRNA-seq dataset and showed that the dynamical simulations of that network generate synthetic single-cell expression profiles that faithfully recapitulate the four myeloid differentiation trajectories going into differentiated cell states (erythrocytes, megakaryocytes, granulocytes and monocytes). Finally, through the in-silico perturbations of the mouse myeloid progenitor core network, we showed that OneSC can accurately predict cell fate decision biases of TF perturbations that closely match with previous experimental observations.

systems biology↗

bioRxiv2019

High-Spatial-Resolution Multi-Omics Atlas Sequencing of Mouse Embryos via Deterministic Barcoding in Tissue

We present DBiT-seq -Deterministic Barcoding in Tissue for spatial omics sequencing - for co-mapping of mRNAs and proteins in a formaldehyde-fixed tissue slide via NGS sequencing. Parallel microfluidic channels were used to deliver DNA barcodes to the surface of a tissue slide and crossflow of two sets of barcodes A1-50 and B1-50 followed by ligation in situ yielded a 2D mosaic of tissue pixels, each containing a unique full barcode AB. Application to mouse embryos revealed major tissue types in early organogenesis as well as fine features like microvasculature in a brain and pigmented epithelium in an eye field. Gene expression profiles in 10m pixels conformed into the clusters of single-cell transcriptomes, allowing for rapid identification of cell types and spatial distributions. DBiT-seq can be adopted by researchers with no experience in microfluidics and may find applications in a range of fields including developmental biology, cancer biology, neuroscience, and clinical pathology. In BriefMicrofluidic deterministic barcoding of mRNAs and proteins in tissue slides followed by high-throughput sequencing enables the construction of a high-spatial-resolution multi-omics atlas at the genome scale. Application to mouse embryos (E10-12) identified major tissue types in early organogenesis and revealed fine tissue features such as retinal pigmented epithelium and endothelial microvasculature at the cellular level. HighlightsO_LIDeterministic barcoding in tissue enables NGS-based spatial multi-omics mapping. C_LIO_LIDBiT-seq identified spatial patterning of major tissue types in mouse embryos. C_LIO_LIDBiT-seq revealed fine features such as retinal pigmented epithelium and microvascular endothelium at the cellular level. C_LIO_LIDirect integration with scRNA-seq data allows for rapid cell type identification. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/788992v2_ufig1.gif" ALT="Figure 1"> View larger version (77K): org.highwire.dtl.DTLVardef@41d937org.highwire.dtl.DTLVardef@11bdc46org.highwire.dtl.DTLVardef@1aa143org.highwire.dtl.DTLVardef@51755c_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2022

Tumor Spheroids Layered in an Imageable Cancer Environment (T-SLICE): a novel in vitro platform to study tumor biology

Cancer treatment is shifting towards precise medicine informed by tumor genetics and structural features. In recent years, it has become increasingly recognized that patient tumors--even those of the same tissue origin--can differ substantially between patients and respond differently to treatment. Given this, it is necessary to design therapies that target the heterogeneity of tumors. When investigating novel therapeutics in the laboratory, conventional cell culture models do not adequately recapitulate this heterogeneity and therefore may not accurately represent drug responses. Recent advances in miniaturized organ-on-a-chip models have been able to generate more complex microenvironments for in vitro studies. However, many of these models do not resemble the scale of clinically relevant tumors and pose a high barrier to use because they are technically complex. To facilitate mechanistic studies of the tumor microenvironment (TME), we designed T-SLICE, a chip made using commercially available elastomers and designed to fit in a standard 6-well plate. This simple 3-D tumor model incorporates microfluidic principles into a fully customizable TME, wherein cells drive the formation of biochemical gradients akin to those observed within a real tumor. In T-SLICE, spheroids are seeded atop a monolayer of fibroblasts situated between two closely spaced coverslips (300-700 {micro}m). The restrictive gap height limits the permeation of oxygen (O2) and hinders the removal of carbon dioxide (CO2) and metabolic waste, which leads to the generation of tumor-like hypoxic gradients. We demonstrate that T-SLICE establishes cell-driven oxygen gradients leading to the formation of a hypoxic core, with further impacts on cellular viability, mitochondrial membrane potential (MMP), and proliferation. T-SLICE cultures can be imaged live or fixed and stained for immunohistochemistry (IHC). These features of T-SLICE make it an accessible and faithful model of a tumors heterogeneity and open the possibility for more faithful testing of novel therapeutics in the context of a realistic TME.

bioengineering↗

bioRxiv2017

De novo organelle biogenesis in the cyanobacterium TDX16 released from the green alga Haematococcus pluvialis

It is believed that eukaryotes arise from prokaryotes, which means that organelles can form in the latter. Such events, however, had not been observed previously. Here, we report the biogenesis of organelles in the endosymbiotic cyanobacterium TDX16 that escaped from its senescent/necrotic host cell of green alga Haematococcus pluvialis. In brief, organelle biogenesis in TDX16 initiated with cytoplasm compartmentalization, followed by de-compartmentalization, DNA allocation, and re-compartmentalization, as such two composite organelles-the primitive chloroplast and primitive nucleus sequestering minor and major fractions of cellular DNA respectively were formed. Thereafter, the eukaryotic cytoplasmic matrix was built up from the matrix extruded from the primitive nucleus; mitochondria were assembled in and segregated from the primitive chloroplast, whereby the primitive nucleus and primitive chloroplast matured into nucleus and chloroplast respectively; while most mitochondria turned into double-membraned vacuoles after matrix degradation. Results of pigment analyses, 16S rRNA and genome sequencing revealed that TDX16 is a phycocyanin-containing cyanobacterium resembling Chroococcidiopsis thermalis, which had acquired 9,017,401bp DNAs with 10301 genes form its host. Therefore, organelle biogenesis in TDX16 was achieved by hybridizing the acquired eukaryotic DNAs with its own ones and expressing the hybrid genome.\n\nOrganelle biogenesis in TDX16 results in its transition into a new eukaryotic alga TDX16-DE, which provides a reference to re-understand the development, structure, function and association of organelles in eukaryotes and the reasons behind them, and has implications on other sections of biology, particularly cancer biology and evolutionary biology: (1) the formation and maturation of the small organelle-less nascent cancer cells share striking similarities with TDX16 development and transition, so, it is most likely that cancer cells arise from bacteria; (2) organelle biogenesis in TDX16 uncovers a way of new organelle and new single-celled eukaryote formation, and in light of which, the ancestral organelles were likely formed in rather than transformed form the endosymbiotic prokaryotes that had acquired their hosts DNAs.

cell biology↗