Desmoglein 2 and desmocollin 2 depletions promote malignancy through distinct mechanisms in triple-negative and luminal breast cancer.

BACKGROUND: Aberrant expressions of desmoglein 2 (Dsg2) and desmocollin 2(Dsc2), the two most widely distributed desmosomal cadherins, have been found to play various roles in cancer in a context-dependent manner. Their specific roles on breast cancer (BC) and the potential mechanisms remain unclear. METHODS: The expressions of Dsg2 and Dsc2 in human BC tissues and cell lines were assessed by using bioinformatics analysis, immunohistochemistry and western blotting assays. Wound-healing and Transwell assays were performed to evaluate the cells' migration and invasion abilities. Plate colony-forming and MTT assays were used to examine the cells' capacity of proliferation. Mechanically, Dsg2 and Dsc2 knockdown-induced malignant behaviors were elucidated using western blotting assay as well as three inhibitors including MK2206 for AKT, PD98059 for ERK, and XAV-939 for ß-catenin. RESULTS: We found reduced expressions of Dsg2 and Dsc2 in human BC tissues and cell lines compared to normal counterparts. Furthermore, shRNA-mediated downregulation of Dsg2 and Dsc2 could significantly enhance cell proliferation, migration and invasion in triple-negative MDA-MB-231 and luminal MCF-7 BC cells. Mechanistically, EGFR activity was decreased but downstream AKT and ERK pathways were both activated maybe through other activated protein tyrosine kinases in shDsg2 and shDsc2 MDA-MB-231 cells since protein tyrosine kinases are key drivers of triple-negative BC survival. Additionally, AKT inhibitor treatment displayed much stronger capacity to abolish shDsg2 and shDsc2 induced progression compared to ERK inhibition, which was due to feedback activation of AKT pathway induced by ERK inhibition. In contrast, all of EGFR, AKT and ERK activities were attenuated, whereas ß-catenin was accumulated in shDsg2 and shDsc2 MCF-7 cells. These results indicate that EGFR-targeted therapy is not a good choice for BC patients with low Dsg2 or Dsc2 expression. Comparatively, AKT inhibitors may be more helpful to triple-negative BC patients with low Dsg2 or Dsc2 expression, while therapies targeting ß-catenin can be considered for luminal BC patients with low Dsg2 or Dsc2 expression. CONCLUSION: Our finding demonstrate that single knockdown of Dsg2 or Dsc2 could promote proliferation, motility and invasion in triple-negative MDA-MB-231 and luminal MCF-7 cells. Nevertheless, the underlying mechanisms were cellular context-specific and distinct.

Dividing out quantification uncertainty allows efficient assessment of differential transcript expression with edgeR.

Differential expression analysis of RNA-seq is one of the most commonly performed bioinformatics analyses. Transcript-level quantifications are inherently more uncertain than gene-level read counts because of ambiguous assignment of sequence reads to transcripts. While sequence reads can usually be assigned unambiguously to a gene, reads are very often compatible with multiple transcripts for that gene, particularly for genes with many isoforms. Software tools designed for gene-level differential expression do not perform optimally on transcript counts because the read-to-transcript ambiguity (RTA) disrupts the mean-variance relationship normally observed for gene level RNA-seq data and interferes with the efficiency of the empirical Bayes dispersion estimation procedures. The pseudoaligners kallisto and Salmon provide bootstrap samples from which quantification uncertainty can be assessed. We show that the overdispersion arising from RTA can be elegantly estimated by fitting a quasi-Poisson model to the bootstrap counts for each transcript. The technical overdispersion arising from RTA can then be divided out of the transcript counts, leading to scaled counts that can be input for analysis by established gene-level software tools with full statistical efficiency. Comprehensive simulations and test data show that an edgeR analysis of the scaled counts is more powerful and efficient than previous differential transcript expression pipelines while providing correct control of the false discovery rate. Simulations explore a wide range of scenarios including the effects of paired vs single-end reads, different read lengths and different numbers of replicates.

Benchmarking long-read RNA-sequencing analysis tools using in silico mixtures.

The lack of benchmark data sets with inbuilt ground-truth makes it challenging to compare the performance of existing long-read isoform detection and differential expression analysis workflows. Here, we present a benchmark experiment using two human lung adenocarcinoma cell lines that were each profiled in triplicate together with synthetic, spliced, spike-in RNAs (sequins). Samples were deeply sequenced on both Illumina short-read and Oxford Nanopore Technologies long-read platforms. Alongside the ground-truth available via the sequins, we created in silico mixture samples to allow performance assessment in the absence of true positives or true negatives. Our results show that StringTie2 and bambu outperformed other tools from the six isoform detection tools tested, DESeq2, edgeR and limma-voom were best among the five differential transcript expression tools tested and there was no clear front-runner for performing differential transcript usage analysis between the five tools compared, which suggests further methods development is needed for this application.

Modeling group heteroscedasticity in single-cell RNA-seq pseudo-bulk data.

Group heteroscedasticity is commonly observed in pseudo-bulk single-cell RNA-seq datasets and its presence can hamper the detection of differentially expressed genes. Since most bulk RNA-seq methods assume equal group variances, we introduce two new approaches that account for heteroscedastic groups, namely voomByGroup and voomWithQualityWeights using a blocked design (voomQWB). Compared to current gold-standard methods that do not account for group heteroscedasticity, we show results from simulations and various experiments that demonstrate the superior performance of voomByGroup and voomQWB in terms of error control and power when group variances in pseudo-bulk single-cell RNA-seq data are unequal.

RSRC2 Expression Inhibits Malignant Progression of Triple-Negative Breast Cancer by Transcriptionally Regulating SCIN Expression.

Triple-negative breast cancer (TNBC) has a shorter survival time and higher mortality rate than other molecular subtypes. RSRC2 is a newly discovered tumor suppressor gene. However, the potential functional mechanism of RSRC2 in TNBC remains unknown so far. Multiple bioinformatics databases were used. A Human Transcriptome Array 2.0 analysis, ChIP-seq analysis, ChIP-qPCR, RT-qPCR, Western blot, cell function assays in vitro and a metastatic mouse model in vivo were performed to demonstrate the role of RSRC2 in TNBC. Through the analysis of various databases, RSRC2 expression was the lowest in TNBC tissues compared to other molecular subtypes. The low expression of RSRC2 was associated with a worse prognosis for patients with breast cancer. The transcriptome array, ChIP-seq and bioinformatics analysis identified that GRHL2 and SCIN might have a close relationship with RSRC2. The functional bioinformatics enrichment analysis and functional cell experiments showed that RSRC2 was involved in cell adhesion, cell proliferation, cell migration and invasion. Furthermore, RSRC2 expression suppressed SCIN expression but not GRHL2 expression. SCIN re-expression in the RSRC2 overexpression cells or SCIN knockdown in the RSRC2 knockdown cells reversed the cellular function caused by RSRC2. Mechanistically, RSRC2 transcriptionally inhibited SCIN expression. In summary, our study reveals that RSRC2 acts as a tumor suppressor in TNBC development and progression through negatively regulating SCIN-mediated cell function, thus providing a potential target for TNBC treatment.

ENO1 expression and Erk phosphorylation in PDAC and their effects on tumor cell apoptosis in a hypoxic microenvironment.

OBJECTIVE: Hypoxia is an important feature of pancreatic ductal adenocarcinoma (PDAC). Previously, we found that hypoxia promotes ENO1 expression and PDAC invasion. However, the underlying molecular mechanism was remains unclear. METHODS: The relationship between ENO1 expression and clinicopathological characteristics was analyzed in 84 patients with PADC. The effects of CoCl2-induced hypoxia and ENO1 downregulation on the apoptosis, invasion, and proliferation of PDAC cells were evaluated in vitro and in vivo. Hypoxia- and ENO1-induced gene expression was analyzed by transcriptomic sequencing. RESULTS: The prognosis of PDAC with high ENO1 expression was poor (P < 0.05). High ENO1 expression was closely associated with histological differentiation and tumor invasion in 84 PDAC cases (P < 0.05). Hypoxia increased ENO1 expression in PDAC and promoted its migration and invasion. Apoptotic cells and the apoptosis marker caspase-3 in the CoCl2-treated ENO1-sh group were significantly elevated (P < 0.05). Transcriptomic sequencing indicated that CoCl2-induced PDAC cells initiated MAPK signaling. Under hypoxic conditions, PDAC cells upregulated ENO1 expression, thereby accelerating ERK phosphorylation and inhibiting apoptosis (P < 0.05). Consistent results were also observed in a PDAC-bearing mouse hindlimb ischemia model. CONCLUSIONS: Hypoxia-induced ENO1 expression promotes ERK phosphorylation and inhibits apoptosis, thus leading to PDAC survival and invasion. These results suggest that ENO1 is a potential therapeutic target for PDAC.

LncRNA n339260 functions in hepatocellular carcinoma progression via regulation of miRNA30e-5p/TP53INP1 expression.

BACKGROUND: Currently, the molecular mechanism of the interaction between lncRNAs and microRNAs (miRNAs) and the target of miRNAs in tumor vasculogenic mimicry (VM) formation have not been clarified. Our aim is to study the interaction between lncRNA n339260 and miRNA30e-5p in the formation of VM. METHODS: Animal xenografts were established, 104 hepatocellular carcinoma (HCC) patients' frozen tissues were obtained and HCC cells in vitro were used to observe the role of n339260 in HCC progression. RESULTS: In vivo experiment showed lncRNA n339260 promoted tumor growth and VM formation. LncRNA n339260 and miRNA30e-5p were found to be associated with VM formation, metastasis and survival time in HCC patients. In vitro experiment showed that LncRNA n339260 could inhibit miRNA30e-5p expression and TP53INP1 was found to be the downstream targets of miRNA30e-5p. Snail, MMP2, MMP9, VE-cadherin, vimentin and N-cadherin overexpression and the downregulation of TP53INP1 and E-cadherin were observed in HCCLM3 and HepG2 cells overexpressing lncRNA n339260 or in cells with decreased expression of miRNA30e-5p. CONCLUSION: LncRNA n339260 promotes the development of VM, and lncRNA n339260 may enhance Snail expression by decreasing the expression of miRNA30e-5p, thereby reducing TP53INP1 expression. Therefore, a potential lncRNA n339260- miRNA30e-5p- TP53INP1 regulatory axis was associated with HCC progression.

Epigenetic modulators of B cell fate identified through coupled phenotype-transcriptome analysis.

High-throughput methodologies are the cornerstone of screening approaches to identify novel compounds that regulate immune cell function. To identify novel targeted therapeutics to treat immune disorders and haematological malignancies, there is a need to integrate functional cellular information with the molecular mechanisms that regulate changes in immune cell phenotype. We facilitate this goal by combining quantitative methods for dissecting complex simultaneous cell phenotypic effects with genomic analysis. This combination strategy we term Multiplexed Analysis of Cells sequencing (MAC-seq), a modified version of Digital RNA with perturbation of Genes (DRUGseq). We applied MAC-seq to screen compounds that target the epigenetic machinery of B cells and assess altered humoral immunity by measuring changes in proliferation, survival, differentiation and transcription. This approach revealed that polycomb repressive complex 2 (PRC2) inhibitors promote antibody secreting cell (ASC) differentiation in both murine and human B cells in vitro. This is further validated using T cell-dependent immunization in mice. Functional dissection of downstream effectors of PRC2 using arrayed CRISPR screening uncovered novel regulators of B cell differentiation, including Mybl1, Myof, Gas7 and Atoh8. Together, our findings demonstrate that integrated phenotype-transcriptome analyses can be effectively combined with drug screening approaches to uncover the molecular circuitry that drives lymphocyte fate decisions.

Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival.

BACKGROUND: Hepatocellular carcinoma (HCC) often presents with satellite nodules, rendering current curative treatments ineffective in many patients. The heterogeneity of HCC is a major challenge in personalized medicine. The emergence of spatial transcriptomics (ST) provides a powerful strategy for delineating the complex molecular landscapes of tumours. METHODS: In this study, the heterogeneity of tissue-wide gene expression in tumour and adjacent nonneoplastic tissues using ST technology were investigated. The transcriptomes of nearly 10,820 tissue regions and identified the main gene expression clusters and their specific marker genes (differentially expressed genes, DEGs) in patients were analysed. The DEGs were analysed from two perspectives. First, two distinct gene profiles were identified to be associated with satellite nodules and conducted a more comprehensive analysis of both gene profiles. Their clinical relevance in human HCC was validated with Kaplan-Meier (KM) Plotter. Second, DEGs were screened with The Cancer Genome Atlas (TCGA) database to divide the HCC cohort into high- and low-risk groups according to Cox analysis. HCC patients from the International Cancer Genome Consortium (ICGC) cohort were used for validation. KM analysis was used to compare the overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors for OS. RESULTS: Novel markers for the prediction of satellite nodules were identified and a tumour clusters-specific marker gene signature model (6 genes) for HCC prognosis was constructed. CONCLUSION: The establishment of marker gene profiles may be an important step towards an unbiased view of HCC, and the 6-gene signature can be used for prognostic prediction in HCC. This analysis will help us to clarify one of the possible sources of HCC heterogeneity and uncover pathogenic mechanisms and novel antitumour drug targets.

TAZ promotes vasculogenic mimicry in gastric cancer through the upregulation of TEAD4.

BACKGROUND AND AIM: Vasculogenic mimicry (VM) is a unique blood supply pattern in malignant tumors that is closely associated with metastasis and poor prognosis. The Hippo signaling effector TAZ is upregulated in several cancers, promoting cancer proliferation and metastasis. This study aimed to identify the function of TAZ and its regulatory mechanism in promoting VM in gastric cancer (GC). METHODS: The expression of TAZ and TEAD4 and their correlations with overall survival and VM-related markers were analyzed in 228 cases of GC. The regulatory mechanism of TAZ and its interaction with TEAD4 in epithelial-mesenchymal transition (EMT) and VM were investigated in vitro and in vivo. RESULTS: TAZ was highly expressed in GC samples and was associated with shorter patient survival time. TAZ expression was positively correlated with TEAD4 and VM in patients with GC. TAZ enhanced the migration and invasion capacity of GC cells through EMT in vitro and upregulated the expression of VM-associated proteins, including VE-cadherin, MMP2, and MMP9, thus promoting VM formation. Overexpression of TAZ accelerated the growth of subcutaneous xenograft and promoted VM formation in vivo. Co-immunoprecipitation assays showed that TAZ can directly bind to TEAD4, and in vitro experiments showed that this binding mediates the function of TAZ in regulating EMT and VM formation in GC. CONCLUSIONS: TAZ promotes GC metastasis and VM by upregulating TEAD4 expression. Our findings expand the role of TAZ in VM and provide new theoretical support for the use of antiangiogenic therapy in the treatment of advanced GC.

The relevance between hypoxia-dependent spatial transcriptomics and the prognosis and efficacy of immunotherapy in claudin-low breast cancer.

Introduction: Hypoxia is an important characteristic of solid tumors. However, spatial transcriptomics (ST) of hypoxia-associated heterogeneity is not clear. Methods: This study integrated Spatial Transcriptomics (ST) with immunofluorescence to demonstrate their spatial distribution in human claudin-low breast cancer MDA-MB-231 engraft. ST spots were clustered with differentially expression genes. The data were combined with hypoxia-specific marker and angiogenesis marker-labeled serial sections to indicate the spatial distribution of hypoxia and hypoxia-inducted transcriptional profile. Moreover, marker genes, cluster-specific hypoxia genes, and their co-essential relationship were identified and mapped in every clusters. The clinicopathological association of marker genes of hypoxia-dependent spatial clusters was explored in 1904 breast cancers from METABRIC database. Results: The tumor from center to periphery were enriched into five hypoxia-dependent subgroups with differentially expressed genes, which were matched to necrosis, necrosis periphery, hypoxic tumor, adaptive survival tumor, and invasive tumor, respectively. Different subgroups demonstrated distinct hypoxia condition and spatial heterogeneity in biological behavior and signaling pathways. Cox regression analysis showed that the invasive tumor (cluster 0) and hypoxic tumor (cluster 6) score could be served as independent prognostic factors in claudin-low patients. KM analysis indicated that high invasive tumor (cluster 0) and hypoxic tumor (cluster 6) score was associated with poor prognoses of claudin-low patients. Further analysis showed that hypoxia-induced immune checkpoints, such as CD276 and NRP1, upregulation in invasive tumor to block infiltration and activation of B cells and CD8+ T cells to change tumor immune microenvironment. Discussion: This study reveals hypoxia-dependent spatial heterogeneity in claudin-low breast cancer and highlights its potential value as a predictive biomarker of clinical outcomes and immunotherapy response. The molecules found in this study also provided potential molecular mechanisms and therapeutic targets for subsequent studies.

Benchmarking UMI-based single-cell RNA-seq preprocessing workflows.

BACKGROUND: Single-cell RNA-sequencing (scRNA-seq) technologies and associated analysis methods have rapidly developed in recent years. This includes preprocessing methods, which assign sequencing reads to genes to create count matrices for downstream analysis. While several packaged preprocessing workflows have been developed to provide users with convenient tools for handling this process, how they compare to one another and how they influence downstream analysis have not been well studied. RESULTS: Here, we systematically benchmark the performance of 10 end-to-end preprocessing workflows (Cell Ranger, Optimus, salmon alevin, alevin-fry, kallisto bustools, dropSeqPipe, scPipe, zUMIs, celseq2, and scruff) using datasets yielding different biological complexity levels generated by CEL-Seq2 and 10x Chromium platforms. We compare these workflows in terms of their quantification properties directly and their impact on normalization and clustering by evaluating the performance of different method combinations. While the scRNA-seq preprocessing workflows compared vary in their detection and quantification of genes across datasets, after downstream analysis with performant normalization and clustering methods, almost all combinations produce clustering results that agree well with the known cell type labels that provided the ground truth in our analysis. CONCLUSIONS: In summary, the choice of preprocessing method was found to be less important than other steps in the scRNA-seq analysis process. Our study comprehensively compares common scRNA-seq preprocessing workflows and summarizes their characteristics to guide workflow users.

High expression of eIF4E is associated with tumor macrophage infiltration and leads to poor prognosis in breast cancer.

BACKGROUND: The expression and activation of eukaryotic translation initiation factor 4E (eIF4E) is associated with cell transformation and tumor initiation, but the functional role and the mechanism whereby it drives immune cell infiltration in breast cancer (BRCA) remain uncertain. METHODS: Oncomine, Timer and UALCAN were used to analyze the expression of eIF4E in various cancers. PrognoScan, Kaplan-Meier plotter, and GEPIA were utilized to analyze the prognostic value of eIF4E in select cancers. In vitro cell experiments were used to verify the role of eIF4E in promoting the progression of BRCA. ImmuCellAI and TIMER database were used to explore the relationship between eIF4E and tumor infiltrating immune cells. The expression of a macrophage marker (CD68+) and an M2-type marker (CD163+) was evaluated using immunohistochemistry in 50 invasive BRCA samples on tissue microarrays. The Human Protein Atlas (HPA) database was used to show the expression of eIF4E and related immune markers. LinkedOmics and NetworkAnalyst were used to build the signaling network. RESULTS: Through multiple dataset mining, we found that the expression of eIF4E in BRCA was higher than that in normal tissues, and patients with increased eIF4E expression had poorer survival and a higher cumulative recurrence rate in BRCA. At the cellular level, BRCA cell migration and invasion were significantly inhibited after eIF4E expression was inhibited by siRNA. Immune infiltration analysis showed that the eIF4E expression level was significantly associated with the tumor purity and immune infiltration levels of different immune cells in BRCA. The results from immunohistochemical (IHC) staining further proved that the expression of CD68+ and CD163+ were significantly increased and correlated with poor prognosis in BRCA patients (P < 0.05). Finally, interaction network and functional enrichment analysis revealed that eIF4E was mainly involved in tumor-related pathways, including the cell adhesion molecule pathway and the JAK-STAT signaling pathway. CONCLUSIONS: Our study has demonstrated that eIF4E expression has prognostic value for BRCA patients. eIF4E may act as an essential regulator of tumor macrophage infiltration and may participate in macrophage M2 polarization.

Comprehensive characterization of single-cell full-length isoforms in human and mouse with long-read sequencing.

A modified Chromium 10x droplet-based protocol that subsamples cells for both short-read and long-read (nanopore) sequencing together with a new computational pipeline (FLAMES) is developed to enable isoform discovery, splicing analysis, and mutation detection in single cells. We identify thousands of unannotated isoforms and find conserved functional modules that are enriched for alternative transcript usage in different cell types and species, including ribosome biogenesis and mRNA splicing. Analysis at the transcript level allows data integration with scATAC-seq on individual promoters, improved correlation with protein expression data, and linked mutations known to confer drug resistance to transcriptome heterogeneity.

TFPI2 Promotes Perivascular Migration in an Angiotropism Model of Melanoma.

PURPOSE: Angiotropism is the process by which cancer cells attach to and migrate along blood vessels to acquire vasculature, disseminate, and metastasize. However, the molecular basis for such vessel-tumor interactions has not been fully elucidated, partly due to limited experimental models. In this study, we aimed to observe and explore the molecular mechanism underlying angiotropism in melanoma. METHODS: To monitor the interactions of human melanoma cells with the vasculature in vivo, a murine coxenograft model was employed by co-injecting highly and poorly invasive melanoma cells subcutaneously. To identify key pathways and genes involved in the angiotropic phenotype of melanoma, analysis of differentially expressed genes (DEGs) and gene set enrichment analysis (GSEA) were performed. The role of tissue factor pathway inhibitor 2 (TFPI2) in angiotropism was evaluated by immunostaining, adhesion assay, shRNA, and in vivo tumorigenicity. Angiotropism and TFPI2 expression were examined in surgical specimens of melanoma by immunohistochemical staining. Data from The Cancer Genome Atlas (TCGA) were analyzed to explore the expression and prognostic implications of TFPI2 in uveal and cutaneous melanoma. RESULTS: Highly invasive melanoma cells spread along the branches of intratumor blood vessels to the leading edge of invasion in the coxenograft model, resembling angiotropic migration. Mechanisms underlying angiotropism were primarily associated with molecular function regulators, regulation of cell population proliferation, developmental processes, cell differentiation, responses to cytokines and cell motility/locomotion. TFPI2 downregulation weakened the perivascular migration of highly invasive melanoma cells. High levels of TFPI2 were correlated with worse and better survival in uveal and cutaneous melanoma, respectively. CONCLUSION: These results provide a straightforward in vivo model for the observation of angiotropism and suggest that TFPI2 could inhibit the angiotropic phenotype of melanoma.

Profiles of and variations in aluminum species in PAC-MC used for the removal of blooming microalgae.

Polyaluminum chloride modified clay (PAC-MC) is a safe and efficient red tide control agent that has been studied and applied worldwide. Although it is well known that the distribution of hydrolytic aluminum species in PAC affects its flocculation, little is known about the influence of particulars aluminum species on the microalgae removal efficiency of PAC-MC; this lack of knowledge creates a bottleneck in the development of more efficient MCs based on aluminum salts. The ferron method was used in this study to quantitatively analyze the distributions of and variations in different hydrolytic aluminum species during the process of microalgae removal by PAC-MC. The results showed that Ala, which made up 5%-20% of the total aluminum, and Alp, which made up 15%-55% of the total aluminum, significantly affected microalgae removal, with Pearson's correlation coefficients of 0.83 and 0.89, respectively. Most of the aluminum in the PAC-MC sank rapidly into the sediments, but the rate and velocity of settlement were affected by the dose of modified clay. The optimal dose of PAC-MC for precipitating microalgae was determined based on its aluminum profile. These results provide guidance for the precise application of PAC-MC in the control of harmful algal blooms.

Hypoxic microenvironment induced spatial transcriptome changes in pancreatic cancer.

OBJECTIVE: Hypoxia is a significant feature of solid tumors, including pancreatic ductal adenocarcinoma (PDAC). It is associated with tumor invasion, metastasis, and drug resistance. However, the spatial distribution of hypoxia-related heterogeneity in PDAC remains unclear. METHODS: Spatial transcriptomics (STs), a new technique, was used to investigate the ST features of engrafted human PDAC in the ischemic hind limbs of nude mice. Transcriptomes from ST spots in the hypoxic tumor and the control were clustered using differentially-expressed genes. These data were compared to determine the spatial organization of hypoxia-induced heterogeneity in PDAC. Clinical relevance was validated using the Tumor Cancer Genome Atlas and KM-plotter databases. The CMAP website was used to identify molecules that may serve as therapeutic targets for PDAC. RESULTS: ST showed that the tumor cell subgroups decreased to 7 subgroups in the hypoxia group, compared to 9 subgroups in the control group. Different subgroups showed positional characteristics and different gene signatures. Subgroup 6 located at the invasive front showed a higher proliferative ability under hypoxia. Subgroup 6 had active functions including cell proliferation, invasion, and response to stress. Expressions of hypoxia-related genes, LDHA, TPI1, and ENO1, induced changes. CMAP analysis indicated that ADZ-6482, a PI3K inhibitor, was targeted by the invasive subgroup in hypoxic tumors. CONCLUSIONS: This study is the first to describe hypoxic microenvironment-induced spatial transcriptome changes in PDAC, and to identify potential treatment targets for PDAC. These data will provide the basis for further investigations of the prognoses and treatments of hypoxic tumors.

The long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read differential expression analysis tools.

Application of Oxford Nanopore Technologies' long-read sequencing platform to transcriptomic analysis is increasing in popularity. However, such analysis can be challenging due to the high sequence error and small library sizes, which decreases quantification accuracy and reduces power for statistical testing. Here, we report the analysis of two nanopore RNA-seq datasets with the goal of obtaining gene- and isoform-level differential expression information. A dataset of synthetic, spliced, spike-in RNAs ('sequins') as well as a mouse neural stem cell dataset from samples with a null mutation of the epigenetic regulator Smchd1 was analysed using a mix of long-read specific tools for preprocessing together with established short-read RNA-seq methods for downstream analysis. We used limma-voom to perform differential gene expression analysis, and the novel FLAMES pipeline to perform isoform identification and quantification, followed by DRIMSeq and limma-diffSplice (with stageR) to perform differential transcript usage analysis. We compared results from the sequins dataset to the ground truth, and results of the mouse dataset to a previous short-read study on equivalent samples. Overall, our work shows that transcriptomic analysis of long-read nanopore data using long-read specific preprocessing methods together with short-read differential expression methods and software that are already in wide use can yield meaningful results.

Correction: Cao, Z., et al. The Expression and Functional Significance of Runx2 in Hepatocellular Carcinoma: Its Role in Vasculogenic Mimicry and Epithelial-Mesenchymal Transition. Int. J. Mol. Sci. 2017, 18, 500.

The author wishes to make the following corrections to this paper [...].