Biology subjects

Hu, Y.

Publications and source records attributed to Hu, Y..

At least 649 records · Page 36Linked to original sources

bioRxiv2019

Tumor Copy Number Deconvolution Integrating Bulk and Single-Cell Sequencing Data

Characterizing intratumor heterogeneity (ITH) is crucial to understanding cancer development, but it is hampered by limits of available data sources. Bulk DNA sequencing is the most common technology to assess ITH, but mixes many genetically distinct cells in each sample, which must then be computationally deconvolved. Single-cell sequencing (SCS) is a promising alternative, but its limitations -- e.g., high noise, difficulty scaling to large populations, technical artifacts, and large data sets -- have so far made it impractical for studying cohorts of sufficient size to identify statistically robust features of tumor evolution. We have developed strategies for deconvolution and tumor phylogenetics combining limited amounts of bulk and single-cell data to gain some advantages of single-cell resolution with much lower cost, with specific focus on deconvolving genomic copy number data. We developed a mixed membership model for clonal deconvolution via non-negative matrix factorization (NMF) balancing deconvolution quality with similarity to single-cell samples via an associated efficient coordinate descent algorithm. We then improve on that algorithm by integrating deconvolution with clonal phylogeny inference, using a mixed integer linear programming (MILP) model to incorporate a minimum evolution phylogenetic tree cost in the problem objective. We demonstrate the effectiveness of these methods on semi-simulated data of known ground truth, showing improved deconvolution accuracy relative to bulk data alone.

bioinformatics↗

bioRxiv2018

SCeQTL: an R package for identifying eQTL from single-cell parallel sequencing data

SummaryWith the development of single-cell sequencing technologies, parallel sequencing the transcriptome and genome is becoming available and will bring us the opportunity to uncover association between genotype and phenotype at single-cell level. Due to the special characteristics of single-cell sequencing data, new method is needed to identify eQTL from single-cell data. We developed an R package SCeQTL that uses zero-inflated negative binomial regression to do eQTL analysis on single-cell data. It can distinguish two type of gene-expression differences among different genotype groups. It can also be used for finding gene expression variations associated with other grouping factors like cell lineages or cell types.\n\nAvailabilityThe R package is available at https://github.com/XuegongLab/SCeQTL/.\n\nContactzhangxg@tsinghua.edu.cn

bioinformatics↗

bioRxiv2018

ACME: Pan-specific peptide-MHC class I binding prediction through attention-based deep neural networks

Prediction of peptide binding to MHC molecules plays a vital role in the development of therapeutic vaccines for the treatment of cancer. Although numerous computational methods have been developed to this end, several challenges still remain in predicting peptide-MHC interactions. Many previous methods are allele-specific, training separate models for individual alleles and are thus unable to yield accurate predictions for those alleles with limited training data. Despite that there exist several pan-specific algorithms that train a common model for different alleles, they only adopt simple model structures that generally have limited performance in capturing the complex underlying patterns of peptide-MHC interactions. Here we present ACME (Attention-based Convolutional neural networks for MHC Epitope binding prediction), a new pan-specific algorithm to accurately predict the binding affinities between peptides and MHC class I molecules, even for those new alleles that are not seen in the training data. Extensive tests have demonstrated that ACME can significantly outperform other state-of-the-art prediction methods with an increase of the Pearson Correlation Coefficient by up to 23 percent. In addition, its ability to identify strong-binding peptides has been experimentally validated. Moreover, by integrating the convolutional neural network with attention mechanism, ACME is able to extract interpretable patterns that can provide useful and detailed insights into the binding preferences between peptides and their MHC partners. All these results have demonstrated that ACME can provide a powerful and practically useful tool for the studies of peptide-MHC class I interactions.

bioinformatics↗

bioRxiv2018

Dynamic transcriptome profiles within spermatogonial and spermatocyte populations during postnatal testis maturation revealed by single-cell sequencing

Spermatogenesis is the process by which male gametes are formed from a self-renewing population of spermatogonial stem cells (SSCs) residing in the testis. SSCs represent less than 1% of the total testicular cell population, but must achieve a stable balance between self-renewal and differentiation. Once differentiation has occurred, the newly formed and highly proliferative spermatogonia must then enter the meiotic program in which DNA content is doubled, then halved twice to create haploid gametes. While much is known about the critical cellular processes that take place during the specialized cell division that is meiosis, much less is known about how the spermatocytes in the \"first-wave\" compare to those that contribute to long-term, \"steady-state\" spermatogenesis. Given the strictly-defined developmental process of spermatogenesis, this study was aimed at exploring the transcriptional profiles of developmental cell stages over the age of the animal. Using a combination of comprehensive germ cell sampling with high-resolution, single-cell-mRNA-sequencing, we have generated a reference dataset of germ cell gene expression. We show that discrete developmental stages possess significant differences in the transcriptional profiles from neonates compared to juveniles and adults. Importantly, these gene expression dynamics are also reflected at the protein level in their respective cell types. We also show differential utilization of many biological pathways with age in both spermatogonia and spermatocytes, demonstrating significantly different underlying gene regulatory programs in these cell types over the course of testis development and spermatogenic waves. This dataset represents the first unbiased sampling of spermatogonia and spermatocytes in the developing testis over developmental age, at high-resolution, single-cell depth. Not only does this analysis reveal previously unknown transcriptional dynamics of a highly transitional cell population, it has also begun to reveal critical differences in biological pathway utilization in developing spermatogonia and spermatocytes, including response to DNA damage and double-strand breaks.\n\nAuthor SummarySpermatogenesis is the process by which male gametes - mature spermatozoa - are produced in the testis. This process requires exquisite control over many developmental transitions, including the self-renewal of the germline stem cell population, commitment to meiosis, and ultimately, spermiogenesis. While much is known about molecular mechanisms regulating single transitions at single time points in the mouse, much less is understood about how the spermatogenic progenitor cells, spermatogonia, or the meiotic cells, spermatocytes, of the testis change over developmental age.\n\nOur single-cell-mRNA-sequencing analysis is the first to profile both spermatogonia and spermatocytes from neonatal mice through adulthood, revealing novel gene expression dynamics and differential utilization of biological pathways. These discoveries help us to understand how the spermatogenic progenitors of this population modulate their activity to adapt to a changing testicular environment. Furthermore, they also begin to explain previously-observed differences - and deficiencies - in spermatocytes that are derived from the first \"wave\" of spermatogenesis. Overall, this dataset is the first of its kind to comprehensively profile gene expression dynamics in male germ cell populations over time, enriching our understanding of the complex and highly-orchestrated process of spermatogenesis.

genomics↗

bioRxiv2018

Loss of Rap1 supports recombination-based telomere maintenance independent of RNA-DNA hybrids in fission yeast

A subset of cancers rely on telomerase-independent mechanisms to maintain their chromosome ends. The predominant \"alternative lengthening of telomeres\" pathway appears dependent on homology-directed repair (HDR) to maintain telomeric DNA. However, the molecular changes needed for cells to productively engage in telomeric HDR are poorly understood. To gain new insights into this transition, we monitored the state of telomeres during serial culture of fission yeast (Schizosaccharomyces pombe) lacking the telomerase recruitment factor Ccq1. Rad52 is loaded onto critically short telomeres shortly after germination despite continued telomere erosion, suggesting that recruitment of recombination factors is not sufficient to maintain telomeres in the absence of telomerase function. Instead, survivor formation coincides with the derepression of telomeric repeat-containing RNA (TERRA). In this context, degradation of TERRA associated with the telomere in the form of R-loops drives a severe growth crisis, ultimately leading to a novel type of survivor with linear chromosomes and altered cytological telomere characteristics, including the loss of the shelterin component Rap1 (but not the TRF1/TRF2 orthologue, Taz1) from the telomere. We demonstrate that deletion of Rap1 is protective in this context, preventing the growth crisis that is otherwise triggered by degradation of telomeric R-loops in survivors with linear chromosomes. These findings suggest that up-regulation of telomere-engaged TERRA or altered recruitment of shelterin components can support telomerase-independent telomere maintenance.

genetics↗

bioRxiv2018

A Whole-Genome Association Approach for Large-scaled Inter-species Trait

Genome wide association studies (GWAS) have provided an avenue for the association between common genetic variants and complex traits. However, using SNP as a genetic marker, GWAS has been confined to detect genetic basis traits only for within species but not for the large-scale inter-species traits. Here, we propose a practical statistical approach that is using kmer frequencies as the genetic markers to associate genetic variants with large scale inter-species traits. We applied this new approach to the trait of chromosome number in 96 mammalian proteomes, and we prioritized 130 genes including TP53 and BAD, of which 6 were candidate genes. These genes were proved to be associated with cellular reaction of DNA double-strand breaks caused by chromosome fission/fusion. Our study provides a new effective genomic strategy to perform association studies for large-scaled inter-species traits, using the chromosome number as a case. We hope this approach could provide exploration for broadly widely traits.

genomics↗

bioRxiv2018

Validation of a low-cost, carbon dioxide-based cryoablation system for percutaneous tumor ablation

Breast cancer rates are rising in low- and middle-income countries (LMICs), yet there is a lack of accessible and cost-effective treatment. As a result, the cancer burden and death rates are highest in LMICs. In an effort to meet this need, our work presents the design and feasibility of a low-cost cryoablation system using widely-available carbon dioxide as the only consumable. This system uses an 8-gauge outer-diameter needle and Joule-Thomson expansion to percutaneously necrose tissue with cryoablation. Bench top experiments characterized temperature dynamics in ultrasound gel demonstrated that isotherms greater than 2 cm were formed. Further, this system was applied to mammary tumors in an in vivo rat model and necrosis was verified by histopathology. Finally, freezing capacity under a large heat load was assessed with an in vivo porcine study, where volumes of necrosis greater than 1.5 cm in diameter confirmed by histopathology were induced in a highly perfused liver after two 7-minute freeze cycles. These results demonstrate the feasibility of a carbon-dioxide based cryoablation system for improving solid tumor treatment options in resource-constrained environments.

bioengineering↗

bioRxiv2018

Investigation of novel functions of three genes in oriental river prawn, Macrobrachium nipponense: Molecular Cloning, Expression, and In situ Hybridization Analysis

Three genes were predicted to be potentially involved in the male sexual development in M. nipponense, including the Gem-associated protein 2-like isoform X1 (GEM), Ferritin peptide, and DNA polymerase zeta catalytic subunit (Rev3). In this study, we aimed to investigate their novel functions in depth. The full-length cDNA sequence of Mn-GEM was 1,018 bp, encoding 258 amino acids. The partial Mn-Rev3 cDNA sequence was 6,832 bp, encoding 1,203 amino acids. Tissue distribution indicated that all of these three genes have higher expression level in testis and androgenic gland, implying their novel functions in male sexual development. In situ hybridization analysis further confirmed the novel roles of these three genes. Rev3 promote the testis development during the whole reproductive cycle, while GEM and ferritin only promote the activation of testis development. Besides, these three genes play essential roles in funicular structure development surrounding the androgenic gland cells, which promote and support the formation of androgenic gland cells. The expression in hepatopancreas cells also suggested their role in immune system in M. nipponense. This study advances our understanding of male sexual development in M. nipponense, as well as providing the basis for further studies of male sexual differentiation and development in crustaceans.

zoology↗

bioRxiv2018

Pathogen Detection and Microbiome Analysis of Infected Wheat Using a Portable DNA Sequencer

Fungal diseases of plants are responsible for major losses in agriculture, highlighting the need for rapid and accurate identification of plant pathogens. Disease outcomes are often defined not only by the main pathogen but are influenced by diverse microbial communities known as the microbiome at sites of infection. Here we present the first use of whole genome sequencing from a portable DNA sequencing device as a method for detection of fungal pathogens from wheat (Triticum aestivum). The data revealed that our method is robust and applicable to the diagnosis of fungal diseases including wheat stripe rust (caused by Puccinia striiformis f. sp. tritici), septoria tritici blotch (caused by Zymoseptoria tritici) and yellow leaf spot (caused by Pyrenophora tritici repentis). We also identified a bacterial genus Pseudomonas co-present with Puccinia and Zymoseptoria infections but not Pyrenophora infections. One limitation of the method is the over-representation of redundant wheat genome sequences in the sample. This could be addressed by amplicon-based sequencing approaches in future studies. Our work outlines a new approach for the detection of a broad range of plant pathogens and associated microbes using a portable sequencer, providing the basis for future development of a system for on-site disease monitoring.

plant biology↗

bioRxiv2018

Discrimination of the hierarchical structure of cortical layers in 2-photon microscopy data by combined unsupervised and supervised machine learning

The laminar organization of the cerebral cortex is a fundamental characteristic of the brain, with essential implications for cortical function. Due to the rapidly growing amount of high-resolution brain imaging data, a great demand arises for automated and flexible methods for discriminating the laminar texture of the cortex. Here, we propose a combined approach of unsupervised and supervised machine learning to discriminate the hierarchical cortical laminar organization in high-resolution 2-photon microscopic neural image data without observer bias, that is, without the prerequisite of manually labeled training data. For local cortical foci, we modify an unsupervised clustering approach to identify and represent the laminar cortical structure. Subsequently, supervised machine learning is applied to transfer the resulting layer labels across different locations and image data, to ensure the existence of a consistent layer label system. By using neurobiologically meaningful features, the discrimination results are shown to be consistent with the layer classification of the classical Brodmann scheme, and provide additional insight into the structure of the cerebral cortex and its hierarchical organization. Thus, our work paves a new way for studying the anatomical organization of the cerebral cortex, and potentially its functional organization.

neuroscience↗

bioRxiv2018

A cell atlas of the adult Drosophila midgut

Studies of the adult Drosophila midgut have provided a number of insights on cell type diversity, stem cell regeneration, tissue homeostasis and cell fate decision. Advances in single-cell RNA sequencing (scRNA-seq) provide opportunities to identify new cell types and molecular features. We used inDrop to characterize the transcriptome of midgut epithelial cells and identified 12 distinct clusters representing intestinal stem cells (ISCs), enteroblasts (EBs), enteroendocrine cells (EEs), enterocytes (ECs) from different regions, and cardia. This unbiased approach recovered 90% of the known ISCs/EBs markers, highlighting the high quality of the dataset. Gene set enrichment analysis in conjunction with electron micrographs revealed that ISCs are enriched in free ribosomes and possess mitochondria with fewer cristae. We demonstrate that a subset of EEs in the middle region of the midgut expresses the progenitor marker esg and that individual EEs are capable of expressing up to 4 different gut hormone peptides. We also show that the transcription factor klumpfuss (klu) is expressed in EBs and functions to suppress EE formation. Lastly, we provide a web-based resource for visualization of gene expression in single cells. Altogether, our study provides a comprehensive resource for addressing novel functions of genes in the midgut epithelium.

genetics↗

bioRxiv2018

Genome-wide Expression Profiling and Pathway Analysis in Cyclic Stretched Human Trabecular Meshwork Cells

PurposeRegulation of intraocular pressure is dependent upon homeostatic responses of trabecular meshwork (TM) cells to mechanical stretch. Despite the important roles of miRNAs in regulating TM function and aqueous outflow, it remains unclear how miRNA and their target genes interact in response to physiological cyclic mechanical stretch. We aimed to identify differentially expressed miRNAs and their potential targets in human TM cells in response to cyclic mechanical stress.\n\nMethodsMonolayers of TM cells from non-glaucomatous donors (n=3-6) were cultured in the presence or absence of 15% mechanical stretch, 1 cycle/s, for 6 or 24-hours using computer-controlled Flexcell Unit. We profiled the expression of 800 miRNAs using NanoString Human miRNA assays and identified differentially expressed miRNAs using the Bioconductor Limma package. We identified differentially expressed genes using Operon Human Oligo Arrays with GeneSpring software. Pathway analysis with WebGestalt identified stretch-related pathways. We used Integrative miRNA Target Finder from Ingenuity Pathway Analysis to identify potential miRNA-mRNA regulations.\n\nResultsWe identified 540 unique genes and 74 miRNAs with differential expression in TM cells upon cyclic mechanical stretch. Pathway analysis indicated the significant enrichment of genes involved in Wnt-signaling, receptor protein serine/threonine kinase signaling, TGF-{beta} pathway, and response to unfolded protein. We also identified several miRNA master regulators, including miR-19b-3p and miR-93-5p, which may act as switches to control several mechano-responsive genes.\n\nConclusionsThis study suggests that cyclic mechanical stress of TM cells triggers alterations in the expression of both mRNAs and miRNAs implicated in glaucoma-associated pathways.

genomics↗

bioRxiv2018

A draft reference genome sequence for Scutellaria baicalensis Georgi

Scutellaria baicalensis Georgi is an important medicinal plant used worldwide. Information about the genome of this species is important for scientists studying the metabolic pathways that synthesise the bioactive compounds in this plant. Here, we report a draft reference genome sequence for S. baicalensis obtained by a combination of Illumina and PacBio sequencing, which was assembled using 10 X Genomics and Hi-C technologies. We assembled 386.63 Mb of the 408.14 Mb genome, amounting to about 94.73% of the total genome size, and the sequences were anchored onto 9 pseudochromosomes with a super-N50 of 33.2 Mb. The reference genome sequence of S. baicalensis offers an important foundation for understanding the biosynthetic pathways for bioactive compounds in this medicinal plant and for its improvement through molecular breeding.

plant biology↗

bioRxiv2018

Increased rates of genomic mutation in a biofilm co-culture model of P. aeruginosa and S. aureus

Biofilms are major contributors to disease chronicity and are typically multi-species in nature. Pseudomonas aeruginosa and Staphylococcus aureus are leading causes of morbidity and mortality in a variety of chronic diseases but current in vitro dual-species biofilms models involving these pathogens are limited by short co-culture times (24 to 48 hours). Here, we describe the establishment of a stable (240 hour) co-culture biofilm model of P. aeruginosa and S. aureus that is reproducible and more representative of chronic disease.\n\nThe ability of two P. aeruginosa strains, (PAO1 and a cystic fibrosis isolate, PA21), to form co-culture biofilms with S. aureus was investigated. Co-culture was stable for longer periods using P. aeruginosa PA21 and S. aureus viability within the model improved in the presence of exogenous hemin. Biofilm co-culture was associated with increased tolerance of P. aeruginosa to tobramycin and increased susceptibility of S. aureus to tobramycin and a novel antimicrobial, HT61, previously shown to be more effective against non-dividing cultures of Staphylococcal spp. Biofilm growth was also associated with increased short-term mutation rates; 10-fold for P. aeruginosa and 500-fold for S. aureus.\n\nBy describing a reproducible 240 hour co-culture biofilm model of P. aeruginosa and S. aureus, we have shown that interspecies interactions between these organisms may influence short-term mutation rates and evolution, which could be of importance in understanding the adaptive processes that lead to the development of antimicrobial resistance.

microbiology↗

bioRxiv2018

Systems therapeutics analyses identify genomic signatures defining responsiveness to allopurinol and combination therapy for lung cancer

The ability to predict responsiveness to drugs in individual patients is limited. We hypothesized that integrating molecular information from databases would yield predictions that could be experimentally tested to develop genomic signatures for sensitivity or resistance to specific drugs. We analyzed TCGA data for lung adenocarcinoma (LUAD) patients and identified a subset where xanthine dehydrogenase expression correlated with decreased survival. We tested allopurinol, a FDA approved drug that inhibits xanthine dehydrogenase on a library of human Non Small Cell Lung Cancer (NSCLC) cell lines from CCLE and identified sensitive and resistant cell lines. We utilized the gene expression profiles of these cell lines to identify six-gene signatures for allopurinol sensitive and resistant cell lines. Network building and analyses identified JAK2 as an additional target in allopurinol-resistant lines. Treatment of resistant cell lines with allopurinol and CEP-33779 (a JAK2 inhibitor) resulted in cell death. The effectiveness of allopurinol alone or allopurinol and CEP-33779 were verified in vivo using tumor formation in NCR-nude mice. We utilized the six-gene signatures to predict five additional allopurinolsensitive NSCLC lines, and four allopurinol-resistant lines susceptible to combination therapy. We found that drug treatment of all cell lines yielded responses as predicted by the genomic signatures. We searched the library of patient derived NSCLC tumors from Jackson Laboratory to identify tumors that would be predicted to be sensitive or resistant to allopurinol treatment. Both patient derived tumors predicted to be allopurinol sensitive showed the predicted sensitivity, and the predicted resistant tumors were sensitive to combination therapy. These data indicate that we can use integrated molecular information from cancer databases to predict drug responsiveness in individual patients and thus enable precision medicine.

systems biology↗

bioRxiv2018

Altered Bacteria-Fungi Inter-Kingdom Network in Gut of Ankylosing Spondylitis Patients

Intestinal bacterial dysbiosis has been increasingly linked to Ankylosing Spondylitis (AS), which is a prototypic and best studied subtype of Spondyloarthritis (SpA). Fungi and bacteria coexist in human gut and interact with each other, although they have been shown to contribute actively to health or diseases, no studies have investigated whether fungal microbiota in AS patients is perturbed. In this study, fecal samples of 22 AS patients, with clinical and radiographic assessments, and 16 healthy controls (HCs) were collected to systematically characterize the gut microbiota and mycobiota in AS patients by 16S rDNA and ITS2-based DNA sequencing. The relationships between therapeutic regimens, disease activity, radiographic damage of AS and gut micro/mycobiome were investigated. Our results showed a distinct mycobiota pattern in AS in addition to microbiota dysbiosis. The gut mycobiome of AS patients was characterized by higher taxonomic levels of Ascomycota, especially the class of Dothideomycetes, and decreased abundance of Basidiomycota, which was mainly contributed by the decease of Agaricales. Compared to HCs, changing of the ITS2/16S biodiversity ratio, and bacteria-fungi interkingdom network were observed in AS patients. Alteration of gut mycobiota was associated with different therapeutic regimens, disease activity, as well as different degrees of radiographic damage. Moreover, we unraveled a disease-specific interkingdom network alteration in AS. Finally, we also identified some trends suggesting that different therapeutic regimens may induce changing of both bacterial and fungal microbiota in AS.\n\nIMPORTANCEHuman gut is colonized by diverse fungi (mycobiome), and they have long been suspected in the pathogenesis of Spondyloarthritis (SpA). Our study unraveled a disease-specific interkingdom network alteration in AS, suggesting that fungi, or the interkingdom interactions between bacteria and fungi, may play an essential role in AS development. However, limited by sample size and indeep mechanism studies, further large scale investigations on the characterization of gut mycobiome in AS patients are needed to form a foundation for research into the relationship between mycobiota dysbiosis and AS development.

microbiology↗

bioRxiv2018

Structural basis and mechanism of the unfolding-induced activation of an acid response chaperone HdeA

The role of protein structural disorder in biological functions is gaining increasing interests in the past decade. The bacterial acid-resistant chaperone HdeA belongs to a group of \"conditionally disordered\" protein that is activated via an order-to-disorder transition. However, the mechanism for unfolding-induced activation remains unclear due to the lack of experimental information on the unfolded state conformation and the chaperone-client interactions. Here we use advanced solution NMR methods to characterize the activated state conformation of HdeA under acidic condition and identify the client binding sites. The activated HdeA becomes largely disordered and exposes two essential hydrophobic patches of residues for client interactions. The pH-dependent chemical exchange saturation transfer (CEST) result identifies three acid-sensitive regions that act as structural locks during the activation process, revealing a multi-step activation mechanism of HdeA chaperone function at atomic level. The results highlight the role of protein disorder in chaperone function and the self-inhibitory role of ordered structures under non-stress conditions, offering new insights for further understanding the protein structure-function paradigm.

biochemistry↗

bioRxiv2018

Identification of Key Differentially Expressed MicroRNAs in Cancer Patients Through Pan-cancer Analysis

A number of microRNAs (miRNAs) functioning in gene silencing have been associated with cancer progression. However, common expression patterns of abnormally expressed miRNAs and their potential roles in multiple cancer types have not yet been evaluated. To minimize the difference of patients, we collected miRNA sequencing data of 575 patients with tumor and adjacent non-tumorous tissues from 14 cancer types from The Cancer Genome Atlas (TCGA), and performed differential expression analysis using DESeq2 and edgeR. The results showed that cancer types can be grouped based on the distribution of miRNAs with different expression patterns. We found 81 significantly differentially expressed miRNAs (SDEmiRNAs) unique to one of the 14 cancers may affect patient survival rate, and 21 key SDEmiRNAs (nine overexpressed and 12 under-expressed) associated with at least eight cancers and enriched in more than 60% of patients per cancer, including four newly identified SDEmiRNAs (hsa-mir-4746, hsa-mir-3648, hsa-mir-3687, and hsa-mir-1269a). The downstream effect of these 21 SDEmiRNAs on cellular functions was evaluated through enrichment and pathway analysis of 7,186 protein-coding gene targets from literature mining with known differential expression profiles in cancers. It enables identification of their functional similarity in cell proliferation control across a wide range of cancers and to build common regulatory networks over cancer-related pathways. This is validated by construction of a regulatory network in PI3K pathway. This study provides evidence of the value of further analysis on SDEmiRNAs as potential biomarkers and therapeutic targets for cancer diagnosis and treatment.

bioinformatics↗