Analysis Of RNA Sequencing Data Research Articles

Single-cell RNA-sequencing data analysis reveals a highly correlated triphasic transcriptional response to SARS-CoV-2 infection

Single-cell RNA sequencing (scRNA-seq) is currently one of the most powerful techniques available to study the transcriptional response of thousands of cells to an external perturbation. Here, we perform a pseudotime analysis of SARS-CoV-2 infection using publicly available scRNA-seq data from human bronchial epithelial cells and colon and ileum organoids. Our results reveal that, for most genes, the transcriptional response to SARS-CoV-2 infection follows a non-linear pattern characterized by an initial and a final down-regulatory phase separated by an intermediate up-regulatory stage. A correlation analysis of transcriptional profiles suggests a common mechanism regulating the mRNA levels of most genes. Interestingly, genes encoded in the mitochondria or involved in translation exhibited distinct pseudotime profiles. To explain our results, we propose a simple model where nuclear export inhibition of nsp1-sensitive transcripts will be sufficient to explain the transcriptional shutdown of SARS-CoV-2 infected cells.

KIAA1429 regulates alternative splicing events of cancer-related genes in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) remains one of the most fatal malignancies with high morbidity and mortality rates in the world, whose molecular pathogenesis is incompletely understood. As an RNA-binding protein participating in the processing and modification of RNA, KIAA1429 has been proved to be implicated in the pathogenesis of multiple cancers. However, how KIAA1429 functions in alternative splicing is not fully reported. In the current study, multi-omics sequencing data were used to analyze and decipher the molecular functions and the underlying mechanisms of KIAA1429 in HCC samples. RNA sequencing data (RNA-seq) analysis demonstrated that in HCCLM3 cells, alternative splicing (AS) profiles were mediated by KIAA1429. Regulated AS genes (RASGs) by KIAA1429 were enriched in cell cycle and apoptosis-associated pathways. Furthermore, by integrating the RNA immunoprecipitation and sequencing data (RIP-seq) of KIAA1429, we found that KIAA1429-bound transcripts were highly overlapping with RASGs, indicating that KIAA1429 could globally regulate the alternative splicing perhaps by binding to their transcripts in HCCLM3 cells. The overlapping RASGs were also clustered in cell cycle and apoptosis-associated pathways. In particular, we validated the regulated AS events of three genes using clinical specimens from HCC patients, including the exon 6 of BPTF gene and a marker gene of HCC. In summary, our results shed light on the regulatory functions of KIAA1429 in the splicing process of pre-mRNA and provide theoretical basis for the targeted therapy of HCC.

Strategy for RNA-Seq Experimental Design and Data Analysis.

Ribonucleic acids (RNAs) are fundamental molecules that control regulation and expression of the genome and therefore the function of a cell. Robust analysis and quantification of RNA transcripts hold critical importance in understanding cell function, altered phenotypes in different biological context, for understanding and targeting diseases. The development of RNA-sequencing (RNA-Seq) now provides opportunities to analyze the expression and function of RNA molecules at an unprecedented scale. However, the strategy for RNA-Seq experimental design and data analysis can substantially differ depending on the biological application. The design choice could also have significant impact for downstream results and interpretation of data. Here we describe key critical considerations required for RNA-Seq experimental design and also describe a step-by-step bioinformatics workflow detailing the different steps required for RNA-Seq data analysis. We believe this article will be a valuable guide for designing and analyzing RNA-Seq data to address a wide range of different biological questions.

RNA Sequencing Analysis of Saliva exRNA.

Next-generation sequencing (NGS) methodologies are rapidly developing. However, RNA Sequencing of saliva is challenging due to low abundance and integrity of extracellular RNA, as well as large amounts of bacterial RNAs that may be encountered in saliva. In addition, the literature about human salivary extracellular RNA is very scarce. Therefore, in our chapter, we present the most appropriate protocols for saliva collection, pre- and post-processing, including bioinformatic analysis of salivary RNA Sequencing data. However, the choice of the proper method for RNA extraction, cDNA library preparation, and computational pipeline can make a significant impact on the final quality of data and their interpretation.

Two-sample test with g-modeling and its applications.

Many real data analyses involve two-sample comparisons in location or in distribution. Most existing methods focus on problems where observations are independently and identically distributed in each group. However, in some applications the observed data are not identically distributed but associated with some unobserved parameters which are identically distributed. To address this challenge, we propose a novel two-sample testing procedure as a combination of the -modeling density estimation introduced by Efron and the two-sample Kolmogorov-Smirnov test. We also propose efficient bootstrap algorithms to estimate the statistical significance for such tests. We demonstrate the utility of the proposed approach with two biostatistical applications: the analysis of surgical nodes data with binomial model and differential expression analysis of single-cell RNA sequencing data with zero-inflated Poisson model.

Genome-Scale Identification, Classification, and Expression Profiling of MYB Transcription Factor Genes in Cinnamomum camphora.

The camphor tree (Cinnamomum camphora (L.) Presl.) is the representative species of subtropical evergreen broadleaved forests in eastern Asia and an important raw material for essential oil production worldwide. Although MYBs have been comprehensively characterized and their functions have been partially resolved in many plants, it has not been explored in C. camphora. In this study, 121 CcMYBs were identified on 12 chromosomes in the whole genome of C. camphora and found that CcMYBs were mainly expanded by segmental duplication. They were divided into 28 subgroups based on phylogenetic analysis and gene structural characteristics. In the promoter regions, numerous cis-acting elements were related to biological processes. Analysis of RNA sequencing data from seven tissues showed that CcMYBs exhibited different expression profiles, suggesting that they have various roles in camphor tree development. In addition, combined with the correlation analysis of structural genes in the flavonoid synthesis pathway, we identified CcMYBs from three subgroups that might be related to the flavonoid biosynthesis pathway. This study systematically analyzed CcMYBs in C. camphora, which will set the stage for subsequent research on the functions of CcMYBs during their lifetime and provide valuable insights for the genetic improvement of camphor trees.

GPR183 antagonism reduces macrophage infiltration in influenza and SARS-CoV-2 infection.

Severe viral respiratory infections are often characterised by extensive myeloid cell infiltration and activation and persistent lung tissue injury. However, the immunological mechanisms driving excessive inflammation in the lung remain poorly understood. To identify the mechanisms that drive immune cell recruitment in the lung during viral respiratory infections and identify novel drug targets to reduce inflammation and disease severity. Preclinical murine models of influenza A virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Oxidised cholesterols and the oxysterol-sensing receptor GPR183 were identified as drivers of monocyte/macrophage infiltration to the lung during influenza A virus (IAV) and SARS-CoV-2 infection. Both IAV and SARS-CoV-2 infection upregulated the enzymes cholesterol 25-hydroxylase (CH25H) and cytochrome P450 family 7 subfamily member B1 (CYP7B1) in the lung, resulting in local production of the oxidised cholesterols 25-hydroxycholesterol (25-OHC) and 7α,25-dihydroxycholesterol (7α,25-OHC). Loss-of-function mutation of Gpr183 or treatment with a GPR183 antagonist reduced macrophage infiltration and inflammatory cytokine production in the lungs of IAV- or SARS-CoV-2-infected mice. The GPR183 antagonist significantly attenuated the severity of SARS-CoV-2 infection and viral loads. Analysis of single-cell RNA-sequencing data on bronchoalveolar lavage samples from healthy controls and COVID-19 patients with moderate and severe disease revealed that CH25H, CYP7B1 and GPR183 are significantly upregulated in macrophages during COVID-19. This study demonstrates that oxysterols drive inflammation in the lung via GPR183 and provides the first preclinical evidence for the therapeutic benefit of targeting GPR183 during severe viral respiratory infections.

CD8 T Cells Mediate Host Death Following Lcmv Clone 13 Infection in Dgkα Deficiency

Diacylglycerol is a potent element of intracellular secondary signaling cascades whose production is enhanced by cell surface receptor agonism and function is regulated by enzymatic degradation by diacylglycerol kinases. In T cells, stringent regulation of the activity of this second messenger maintains an appropriate balance between effector function and anergy. In our study, we demonstrate that the DGKα is an indispensable regulator of T cell receptor-mediated activation of CD8 T cells in LCMV Clone 13 viral infection. In the absence of DGKα in mice, LCMV Clone 13 viral inoculation, a noncytopathic infection, resulted in a pathologic, proinflammatory state and host mortality. This was first observed in a systemic loss of function model, where significant mortality observed in DGKα-/- mice following LCMV Clone 13 when compared to wildtype (73% vs 6%, respectively, p < 0.0001). A similar trend towards increased post-infection mortality was observed in mice with CD8 T cell specific DGKα deficiency. The model was generated by chimeric bone marrow transplant of CD8-/- and DGKα-/- bone marrow, so that reconstituted marrow contained a DGKα deficiency specific to CD8 T cells. When compared to mice transplanted with DGKα sufficient bone marrow, increased mortality was observed in mice with CD8 T cell specific absence of DGKα (20% vs 80%, respectively, p=0.07). In contrast, when systemic DGKα-/- mice were treated with a CD8 depleting antibody prior to LCMV Clone 13 infection, none of the CD8 depleted mice suffered mortality, demonstrating DGKα-deficient CD8 T cells are necessary for the observed mortality. Next, an immunophenotype of the systemic knockout model during LCMV Clone 13 infection was established to determine the mechanism behind the increased mortality. This revealed a significant increase in the frequency of antigen (glycoprotein 33-41) specific CD8 T cells, and a significant decrease in serum viral load when compared to a similarly infected wildtype mouse. No appreciable differences in frequency of Treg or Th1 CD4 T cells were observed, but there was a discordant increase in Tfh CD4 T cells and a decrease in germinal center B cells. Myeloid subsets of macrophages, monocytes, and granulocytes were similar between infected DGKα-/- mice and wildtype controls. Following LCMV Clone 13 infection, transcriptomic analysis of RNA sequencing data gathered from sorted virus-specific, DGKα-deficient CD8 T cells revealed an enrichment of multiple cell cycling gene sets, and transcriptional upregulation of genes associated with glycolysis, effector function, and TCR signaling as compared to DGKα-sufficient, virus-specific CD8 T cells. These transcriptomic differences were confirmed phenotypically in vivo following competitive adoptive transfer of virus-specific, wildtype and DGKα-/- CD8 T cells into the same host. Following LCMV Clone 13 infection, a significant expansion of DGKα-/- virus-specific CD8 T cells occurred as compared to DGKα replete virus-specific CD8 T cells. Further, those deficient in DGKα displayed enhanced effector function, evidenced by significantly increased per-cell production of granzyme B and interferon gamma. In total, our data demonstrate that CD8 T cell expression of DGKα is necessary to prevent immunopathologic host death in the setting of LCMV Clone 13 infection. In its absence in CD8 T cells, a noncytopathic viral infection can propagate an overwhelming, mortal proinflammatory phenotype.

Tumor Necrosis Factor from Leukemic Microenvironment Provides Non-Leukemic Hematopoietic Stem Cells with Megakaryocyte Lineage Bias

Background: Acute myeloid leukemia (AML) is characterized by proliferation of malignant cells and impairment of normal hematopoiesis, leading to the severe bone marrow failure. Although genetic abnormalities and pathogenesis of AML are now investigated in detail, the precise mechanism impairing normal hematopoiesis in AML is not fully elucidated yet. Hematopoietic stem cells (HSC) retain the self-renewal capacity together with multipotent differentiation potential into all mature blood cells, playing a major role in maintaining the normal hematopoiesis. The ability of HSC is maintained by complex network of intrinsic factors and external stimulation from microenvironment called as HSC niche. According to these backgrounds, we hypothesized that the impairment of normal hematopoiesis in AML is caused by abnormal function of non-leukemic (nl) HSC. To verify this hypothesis, we isolated nl-HSC and HSC niche cells from MLL-AF9-induced AML mice and further analyzed their function and gene expression profiles. Results: The frequencies of nl-HSC/hematopoietic progenitor fraction (Lin-cKit+Sca1+ cells, HSPC) were significantly increased at the initiation phase of leukemic proliferation in AML mice (leukemic cells : 10-30% in BM)（normal: 0.76+/-0.34%, AML: 2.07 +/-0.93 %, p<0.001）. Surface expression level of CD41 was also upregulated (normal: 15.1+/- 0.526%, AML: 25.4+/- 9.28%, p<0.05). Interestingly, the results of in vitro culture of nl-HSPC demonstrated that they proliferated more efficiently than HSPC from normal mouse BM, and that they tended to differentiate into megakaryocyte (MgK) lineage. Gene set enrichment analysis revealed that MgK-related gene sets and several inflammatory cytokines signaling pathways, including tumor necrosis factor (TNF) pathway, were statistically enriched in nl-HSC. These data suggested that nl-HSC/HSPC retain the MgK-biased character. On the other hands, the gene expression profiles of perivascular stromal cells (ICAM1+CD31-CD45-TER119-cells) in AML mice demonstrated the significantly decreased expression of HSC-supporting factors (e.g., lpl, ptn, rspo2, angptl4, kitl, cxcl12), when compared with those in normal mice. These data suggested that the changes of multiple external humoral factors from leukemic environment induce functional alternation of nl-HSC. To further investigate the role of inflammatory humoral factors in HSC self-renew and differentiation, we next utilized polyvinyl alcohol (PVA)-based ex vivo HSC expansion system and focused on the role of TNF signaling. In the analysis of highly purified normal HSC (CD150+CD48-CD34-cKit+Sca1+Lin-cells) with PVA, TNF alpha increased both proliferation and MgK differentiation. UMAP analysis of single cell RNA sequence data for ex vivo-expanded HSCs with TNF alpha showed the increased frequencies of the clusters expressing MgK-related genes (e.g., itga2b and gp1ba) and relatively decreased immature HSC related genes (e.g., hlf and procr). The results of competitive repopulation assay using ex-vivo expanded normal HSC with TNF alpha stimulation in HSC promoted myeloid differentiation of HSC, rather than self-renew and expansion of HSC. Conclusion: Our data suggested that TNF alpha from leukemic microenvironment may play a key role for the driver signaling of HSCs to MgK, eventually resulting in the impairment of normal HSC maintenance.

Abstract C060: Adipose-tumor crosstalk alters tumor immune profile by promoting PDAC CXCL5 secretion

Abstract Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death in the US, due to late detection and limited therapeutic options. While the main cause of PDAC remains unknown, obesity has been shown to be a major risk factor. However, the molecular mechanisms behind adipose-tumor crosstalk are still being elucidated. Therefore, understanding the crosstalk between adipose and PDAC is critical for improving therapeutic approaches. We hypothesize that factors secreted by the adipose tissue reprogram pancreatic cancer cells to drive tumor growth and anti-tumor immunity. We observed enhanced proliferation in cells treated with conditioned media made from adipose tissue collected from PDAC [MV1] patients. Subsequent analysis determined that PDAC cells also secrete high levels of CXCL5 in response to stimulation with adipose conditioned media. Pathway analysis of RNA-sequencing data from conditioned-media-treated human PDAC cell lines implicated IL-1β and TNF-α as being involved in the resulting transcript changes. Using recombinant IL-1β, we stimulated CXCL5 secretion from multiple PDAC cell lines. Additionally, we found an enhanced secretion of IL-1β from obese adipose tissue compared to that from lean adipose and, using an anti-IL-1β blocking antibody we were able to partially depress the CXCL5 secretion from cells stimulated with adipose conditioned media. Because CXCL5 is a known neutrophil activating and attracting protein, we used CRISPR to engineer CXCL5 deficient murine PDAC cells. To determine the effect of tumor-derived CXCL5 on PDAC growth and immune recruitment, we orthotopically injected non-targeting-control and CXCL5-KO K8484 cells into wild-type, syngeneic, obese mice. While CXCL5-KO tumors displayed a similar size, we observed a significant change in the tumor immune profile. Despite an increase in the pro-tumorigenic monocytic myeloid derived suppressor cells (MDSCs), we found that the CXCL5-KO tumors exhibited a significantly enhanced CD8+ T cell infiltration. However, a high percentage of these CD8+ T cells were PD-1 positive, implicating an exhausted phenotype. Subsequently, we treated wildtype and CXCL5 deficient PDAC bearing obese mice with an anti-PD-1 antibody to promote T-cell re-activation, which resulted in a significantly reduced growth of the CXCL5 deficient tumors. In conclusion, obesity and adipose derived factors directly induce tumor cells to support immune suppression and drive PDAC progression. Citation Format: R. McKinnon Walsh, Joseph Ambrose, Bailey A. Bye, Austin E. Eades, Jarrid L. Jack, Mariana T. Ruckert, Appolinaire A. Olou, Fanuel Messaggio, Prabhakar Chalise, Dong Pei, Michael N. VanSaun. Adipose-tumor crosstalk alters tumor immune profile by promoting PDAC CXCL5 secretion [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr C060.

Gene Expression Analysis Reveals a Subset of TP53mutant-like AML with Wild Type TP53 and Poor Prognosis

Introduction Acute myeloid leukemia (AML) is a fatal blood cancer with a 2-year survival rate of less than 50%. AML with TP53 mutations (TP53mut) has a particularly poor prognosis with a 1-year survival rate of less than 10%. Gene expression profiling (GEP) has been used to identify poor prognostic features in AML and other cancers. In acute lymphoblastic leukemia (ALL), GEP has been instrumental in defining new molecular subgroups with poor prognostic features such as Ph-like ALL. Because TP53mut AML is uniquely treatment refractory, we hypothesize that this AML subtype harbors a distinct GEP and TP53 wild type (TP53wt) AMLs that express features of the TP53mut GEP would have similarly poor clinical outcomes. Methods and results: We analyzed RNA sequencing data of AML samples that have associated mutational profiling in the BEAT-AML (n=413) and TCGA (n=178) datasets. We compared the GEP of TP53mut and TP53 wild type (TP53wt) samples. Using unsupervised hierarchical clustering methods, we detected no significant clustering according to TP53 status. Therefore, we applied a machine-learning approach to detect whether a unique TP53mut GEP could be detected. Using the BEAT-AML dataset, we randomly divided the samples in half to generate training and testing datasets. The TCGA dataset was reserved as a validation dataset. We trained a Ridge regression model on the training dataset using 10-fold cross validation to define a model that could be used to classify TP53mut and TP53wt cases. We evaluated our model on the test dataset and found that this model was highly accurate in distinguishing TP53mut versus TP53wt cases (93% sensitivity and 97% specificity). When we applied this model to the validation dataset, we found a similar performance (93% sensitivity and 99% specificity) demonstrating that this model robustly defines a TP53mut GEP that generalizes across datasets. Although our machine learning model exhibited high accuracy in distinguishing TP53mut samples from TP53wt samples, we noted there was a cohort of TP53wt samples that were consistently scored highly by our classifier, suggesting they had features that made them TP53 mutant-like (TP53mut-like). Interestingly, we found that the TP53wt cases with the highest scores (representing highest similarity to the TP53mut profile) shared several clinical features with TP53mut samples. Most notably, the survival rate of TP53mut-like cases (TP53wt cases with high scores) was significantly lower than TP53wt cases with low scores. In the BEAT-AML dataset, we observed that the 42 TP53wt samples with the highest score had worse overall survival (OS) rates among the TP53wt cases (median survival: 347 days versus 568 days, p=0.014). We reasoned that these TP53mut-like may represent a previously unappreciated subtype, and thus, we specifically trained a Ridge regression model to distinguish these TP53mut-like cases from TP53wt in the BEAT-AML dataset. This model was also highly accurate when tested on the held-out BEAT-AML samples (87.50% sensitivity and 95.52% specificity). When applying the resulting TP53mut-like model to the TCGA GEP data, we found that the 23 TP53wt patients with the highest scores had the worse OS rate among the TP53wt cases (median survival 335 days versus 800 days, p=0.031). Furthermore, we find that the TP53mut-like cases displayed other similar features to TP53mut cases. For example, TP53mut and TP53mut-like samples have higher LSC17 scores (Ng et al. Nature 2016) relative to TP53wt cases (p<0.0001). Clinically, we find that TP53mut cases have lower bone marrow blast percentage and white blood cell count (WBC) relative to TP53wt cases in both datasets (consistent with prior reports [Tashakori et al. Blood 2022]). Accordingly, TP53mut-like cases also have lower bone marrow blast percentage (35 versus 63%, p<0.0001) and WBC (22 versus 42%, p<0.0001) relative to TP53wt cases. The cytogenetic profiles of TP53mut-like cases resembled those of TP53mut cases, but these cytogenetic profiles were insufficient identify TP53mut-like cases and were detected in some TP53wt cases. Finally, we identified a panel of 15 genes whose expression identifies TP53mut-like cases. Conclusion: We use a statistical regression model to define the GEP of TP53mut AML and define a new subset of TP53mut-like AML that lacks TP53 mutations but shares many of the same clinical and laboratory features of TP53mut AML, including poor survival. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Sequencing and Variant Detection of Eight Abundant Plant-Infecting Tobamoviruses across Southern California Wastewater.

Tobamoviruses are agriculturally relevant viruses that cause crop losses and have infected plants in many regions of the world. These viruses are frequently found in municipal wastewater, likely coming from human diet and industrial waste across wastewater catchment areas. As part of a large wastewater-based epidemiology study across Southern California, we analyzed RNA sequence data from 275 influent wastewater samples obtained from eight wastewater treatment plants with a catchment area of approximately 16 million people from July 2020 to August 2021. We assembled 1,083 high-quality genomes, enumerated viral sequencing reads, and detected thousands of single nucleotide variants from eight common tobamoviruses: bell pepper mottle virus, cucumber green mottle mosaic virus, pepper mild mottle virus, tobacco mild green mosaic virus, tomato brown rugose fruit virus, tomato mosaic virus, tomato mottle mosaic virus, and tropical soda apple mosaic virus. We show that single nucleotide variants had amino acid-altering consequences along with synonymous mutations, which represents potential evolution with functional consequences in genomes of these viruses. Our study shows the importance of wastewater sequencing to monitor the genomic diversity of these plant-infecting viruses, and we suggest that our data could be used to continue tracking the genomic variability of such pathogens. IMPORTANCE Diseases caused by viruses in the genus Tobamovirus cause crop losses around the world. As with other viruses, mutation occurring in the virus's genomes can have functional consequences and may alter viral infectivity. Many of these plant-infecting viruses have been found in wastewater, likely coming from human consumption of infected plants and produce. By sequencing RNA extracted from influent wastewater obtained from eight wastewater treatment plants in Southern California, we assembled high-quality viral genomes and detected thousands of single nucleotide variants from eight tobamoviruses. Our study shows that Tobamovirus genomes vary at many positions, which may have important consequences when designing assays for the detection of these viruses by agricultural or environmental scientists.

MODL-05. DISCOVERY OF DYNAMIC MINIMAL RESIDUAL DISEASE STATES IN ADULT GLIOBLASTOMA USING SINGLE CELL TECHNOLOGY

Abstract Persister states are proposed oncogenic substrates of disease recurrence in cancer. Recent concepts suggest persisters may occur in dynamic states of the cell cycle (such as cycling and non-cycling states). We therefore investigated biological programs at the post-treatment minimal residual disease (MRD) state following standard chemoradiotherapy in patient-derived xenograft models of GBM. Our analysis of single cell RNA sequencing (scRNA-seq) data from 2704 tumor cells (929 cells post treatment, 1775 matched controls) yielded a cellular profile for non-cycling and cycling persister states. We validated these programs in 3 independent scRNA-seq datasets of human glioblastoma specimens consisting of over 16,000 cells from various genetic backgrounds, including an internal two patient-matched primary and recurrent GBM pairs with over 13,000 cells. Finally, we determined that clones identified based on large scale chromosomal rearrangements converge on previously identified persister states including the dynamic states discovered in our study. Our results provide new evidence towards dynamic persister states in glioblastoma, further analysis of these dynamic states is critical to targeting this incurable disease.

Identification and validation of a signature based on macrophage cell marker genes to predict recurrent miscarriage by integrated analysis of single-cell and bulk RNA-sequencing.

Recurrent miscarriage (RM) is a chronic, heterogeneous autoimmune disease that has serious social and personal consequences. No valid and reliable diagnostic markers or therapeutic targets for RM have been identified. Macrophages impact the innate immune system and can be used as diagnostic and prognostic markers for many diseases. We first collected 16 decidua and villi tissue samples from 5 normal patients and 3 RM patients for single-cell RNA sequencing data analysis and identified 1293 macrophage marker genes. We then screened a recurrent miscarriage cohort (GSE165004) for 186 macrophage-associated marker genes that were significantly differentially expressed between RM patients and the normal pregnancy endometrial tissues, and performed a functional enrichment analysis of differentially expressed genes. We then identified seven core genes (ACTR2, CD2AP, MBNL2, NCSTN, PUM1, RPN2, and TBC1D12) from the above differentially expressed gene group that are closely related to RM using the LASSO, Random Forest and SVM-RFE algorithms. We also used GSE26787 and our own collection of clinical specimens to further evaluate the diagnostic value of the target genes. A nomogram was constructed of the expression levels of these seven target genes to predict RM, and the ROC and calibration curves showed that our nomogram had a high diagnostic value for RM. These results suggest that ACTR2 and NCSTN may be potential targets for preventative RM treatments.

Triptonide Inhibits the Cervical Cancer Cell Growth via Downregulating the RTKs and Inactivating the Akt-mTOR Pathway.

The high incidence and mortality of cervical cancer (CC) require an urgent need for exploring novel valuable therapeutics. Triptonide (TN) is a small molecule monomer extracted from the Chinese herb Tripterygium wilfordii Hook. Our results showed that TN, at only nanomolar concentrations, strongly inhibited growth, colony formation, proliferation, migration, and invasion of established and primary human cervical cancer cells. TN induced apoptosis and cell cycle arrest in cervical cancer cells. Moreover, cervical cancer cell in vitro migration and invasion were suppressed by TN. It was however noncytotoxic and proapoptotic to normal cervical epithelial cells and human skin fibroblast cells. Gene set enrichment analysis (GSEA) of RNA sequencing data of differentially expressed genes (DEGs) in TN-treated cervical cancer cells implied that DEGs were enriched in the receptor tyrosine kinase (RTK) signaling and PI3K-Akt-mTOR cascade. In cervical cancer cells, RTKs, including EGFR and PDGFRα, were significantly downregulated and Akt-mTOR activation was largely inhibited after TN treatment. In vivo, oral administration of TN significantly inhibited subcutaneous cervical cancer xenograft growth in nude mice. EGFR and PDGFRα downregulation as well as Akt-mTOR inactivation was detected in TN-treated HeLa xenograft tumor tissues. Thus, TN inhibits human cervical cancer cell growth in vitro and in vivo. Its anticervical cancer activity was associated with RTK downregulation and Akt-mTOR inactivation.

YTHDF1 regulates endoplasmic reticulum stress, NF-κB, MAPK and PI3K-AKT signaling pathways in inflammatory osteoclastogenesis

Abnormal increases in osteoclast differentiation and activity contribute to excessive bone resorption in inflammatory bone diseases. The specific m6A-binding protein YT521-B homology domain family 1 (YTHDF1) participates in many physiopathological processes by regulating mRNA stability or translation. However, whether YTHDF1 is involved in the regulation of inflammatory osteoclastogenesis remains a mystery. This study revealed that YTHDF1 expression was upregulated during lipopolysaccharide (LPS)-stimulated osteoclast differentiation. Knockdown of Ythdf1 inhibited osteoclast formation, bone resorption and the expression of osteoclast-related genes (Tnfrsf11a, Traf6, Mmp9 and Acp5). Analysis of RNA sequencing data showed that the genes downregulated by Ythdf1 knockdown were closely associated with endoplasmic reticulum (ER) stress and osteoclast differentiation. Western blotting confirmed that Ythdf1 depletion suppressed activation of the ER stress-related PERK, IRE1α and ATF6 signaling pathways. The ER stress activator tunicamycin (Tm) partially rescued the decreased expression of Mmp9 and Acp5 caused by Ythdf1 deficiency. Meanwhile, Ythdf1 depletion inhibited the phosphorylation levels of key proteins in the NF-κB, MAPK and PI3K-AKT signaling pathways and decreased the mRNA stability of Tnfrsf11a, which is the major upstream signaling molecule that mediates the activation of these pathways during osteoclast differentiation. In conclusion, our findings suggest that Ythdf1 knockdown inhibits inflammatory osteoclast differentiation and function by suppressing ER stress signaling pathways. Ythdf1 knockdown also inactivates the signaling pathways involved in osteoclast differentiation by inhibiting Tnfrsf11a mRNA stability. These findings will help shed light on the molecular mechanisms of m6A-mediated epigenetic regulation in inflammatory osteoclastogenesis.

Biallelic TUFT1 variants cause woolly hair, superficial skin fragility and desmosomal defects.

Desmosomes are complex cell junction structures that connect intermediate filaments providing strong cell-to-cell adhesion in tissues exposed to mechanical stress. To identify causal variants in individuals with woolly hair and skin fragility of unknown genetic cause. This research was conducted using whole-genome sequencing, whole-exome sequencing, clinical phenotyping, haplotype analysis, single-cell RNA sequencing data analysis, immunofluorescence microscopy and transmission electron microscopy. We identified homozygous predicted loss-of-function tuftelin-1 (TUFT1) variants in nine individuals, from three families, with woolly hair and skin fragility. One donor splice-site variant, c.60+1G>A, was present in two families, while a frameshift variant, p.Gln189Asnfs*49, was found in the third family. Haplotype analysis showed the c.60+1G>A substitution to be a founder variant in the Irish population that likely arose approximately 20 generations ago. Human and mouse single-cell RNA sequencing data showed TUFT1 expression to be enriched in the hair dermal sheath and keratinocytes. TUFT1 expression was highly correlated with genes encoding desmosomal components implicated in diseases with phenotypes that overlap with the cohort presented here. Immunofluorescence showed tuftelin-1 to be mainly localized to the peripheral cell membranes of keratinocytes in normal skin. Skin samples from individuals with TUFT1 variants showed markedly reduced immunoreactivity for tuftelin-1, with a loss of the keratinocyte cell membrane labelling. Light microscopy revealed keratinocyte adhesion, mild hyperkeratosis and areas of superficial peeling. Transmission electron microscopy showed panepidermal acantholysis with widening of intercellular spaces throughout the epidermis and desmosomal detachment through the inner plaques. Biallelic loss-of-function TUFT1 variants cause a new autosomal recessive skin/hair disorder characterized by woolly hair texture and early-onset skin fragility. Tuftelin-1 has a role in desmosomal integrity and function.

45. Deconstruction of pancreatic ductal adenocarcinoma identifies survival-associated tumor microenvironmental communities

Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest cancers worldwide. Bulk and single-cell technologies have recently been leveraged to better understand its genomic underpinnings. The PDAC tumor microenvironment (TME) has also been explored, revealing an immunosuppressive milieu. However, efforts to utilize TME features to facilitate more effective treatments have largely failed. Here, we performed single-cell RNA sequencing (scRNA-seq) on a cohort of treatment-naive PDAC biopsy samples (n=22) and surgical samples (n=6), integrated with 3 public datasets (n=49), resulting in ∼150,000 individual cells from 77 patients. Based on expression markers and differentiation status, we divided the resulting tumor cellular clusters into 5 molecular subtypes: Basal, Mixed Basal/Classical, Less differentiated Classical, More differentiated Classical, and ADEX. We then queried these 5 tumor cell profiles along with 15 scRNA-seq-derived tumor microenvironmental cellular profiles in 391 bulk RNA-seq samples from 4 published datasets of localized PDAC with associated clinical metadata using CIBERSORTx. Through unsupervised clustering analysis of the resulting cell state fractions, we identified 7 unique clustering patterns, which we term communities, representing combinations of tumor cellular and microenvironmental cell states that are correlated with overall survival, tumor ecotypes, and tumor cellular differentiation status. Overall, discovered tumor microenvironmental communities from high-dimensional analysis of PDAC RNA sequencing data reveal new connections between tumor microenvironmental composition and patient survival that could lead to better upfront risk stratification and more personalized clinical decision-making.

ER whorls triggered by GhCNX6 were discovered involved in drought stress on cotton

Drought stress is the main abiotic stress causing damage to cotton growth and severe yield loss. Under environmental stress conditions, the endoplasmic reticulum (ER) folding environment is disturbed, resulting in the accumulation of unfolded/misfolded proteins, causing ER stress and triggering the unfolded protein response (UPR). Analysis of drought RNA-sequencing data revealed a Gh_D09G2402.1 ( GhCNX ) gene involved in ER protein processing. Through the observation of the ultrastructure of the ER under drought stress in cotton, the characteristic structure of the endoplasmic reticulum whorl was found. Virus-induced gene silencing (VIGS) mediated GhCNX6 silenced cotton plants were found highly sensitive to drought stress. Arabidopsis thaliana plants overexpressing GhCNX6 showed stronger tolerance to drought stress, indicating that the GhCNX6 gene is involved in the action mechanism of cotton drought stress and enhances the tolerance to drought stress. Drought stress leads to ER stress response, and the resulting ER whorl and CNX gene play a role in the ER protein processing pathway, thereby regulating the mechanism of cotton response to drought stress. This study will help to further explore the mechanism of cotton drought resistance. • Endoplasmic reticulum whorls found in cotton under drought stress. • First preliminary verification of GhCNX6 positively responding to drought stress. • The regulatory mechanism of GhCNX6 and ER whorls under drought stress.

Personalized targeted therapy prescription in colorectal cancer using algorithmic analysis of RNA sequencing data

Background:Overall survival of advanced colorectal cancer (CRC) patients remains poor, and gene expression analysis could potentially complement detection of clinically relevant mutations to personalize CRC treatments.Methods:We performed RNA sequencing of formalin-fixed, paraffin-embedded (FFPE) cancer tissue samples of 23 CRC patients and interpreted the data obtained using bioinformatic method Oncobox for expression-based rating of targeted therapeutics. Oncobox ranks cancer drugs according to the efficiency score calculated using target genes expression and molecular pathway activation data. The patients had primary and metastatic CRC with metastases in liver, peritoneum, brain, adrenal gland, lymph nodes and ovary. Two patients had mutations in NRAS, seven others had mutated KRAS gene. Patients were treated by aflibercept, bevacizumab, bortezomib, cabozantinib, cetuximab, crizotinib, denosumab, panitumumab and regorafenib as monotherapy or in combination with chemotherapy, and information on the success of totally 39 lines of therapy was collected.Results:Oncobox drug efficiency score was effective biomarker that could predict treatment outcomes in the experimental cohort (AUC 0.77 for all lines of therapy and 0.91 for the first line after tumor sampling). Separately for bevacizumab, it was effective in the experimental cohort (AUC 0.87) and in 3 independent literature CRC datasets, n = 107 (AUC 0.84–0.94). It also predicted progression-free survival in univariate (Hazard ratio 0.14) and multivariate (Hazard ratio 0.066) analyses. Difference in AUC scores evidences importance of using recent biosamples for the prediction quality.Conclusion:Our results suggest that RNA sequencing analysis of tumor FFPE materials may be helpful for personalizing prescriptions of targeted therapeutics in CRC.