dbEMT: an epithelial-mesenchymal transition associated gene resource

Endoplasmic reticulum stress-related super enhancer promotes epithelial-mesenchymal transformation in hepatocellular carcinoma through CREB5 mediated activation of TNC

Super-enhancers (SEs) are associated with key genes that control cellular state and cell identity. Endoplasmic reticulum stress (ERS) regulates epithelial-mesenchymal transformation (EMT). However, whether SEs are involved in ERS-related activation of EMT in hepatocellular carcinoma (HCC) is unknown. In this study, we identified 17 ERS-related SEs by comparing ERS-HCC cells with untreated control cells using ChIP-seq and RNA-seq. CRISPR-Cas9 and RT-qPCR identified CAMP responsive element binding protein 5 (CREB5) as a key target of ERS-related SE. Analyses of TCGA datasets and tissue arrays showed that CREB5 mRNA and protein expression levels were higher in liver cancer tissues than in paired normal tissues. In addition, overexpression of CREB5 was associated with poor prognosis and an aggressive phenotype in patients with HCC. We also found that activation of ERS enhanced the expression of CREB5, and upregulation of CREB5 significantly increased cell proliferation, migration, and invasion, and promoted EMT, but inhibited apoptosis. More importantly, ERS activation increased the expression of several EMT markers by modulating the expression of CREB5. Mechanistically, CREB5 upregulates the transcription of tenascin-C (TNC) by directly binding to its promoter region, thereby promoting EMT in liver cancer cells. In summary, our findings suggest that ERS activation promotes EMT in liver cancer cells via SE-mediated upregulation of the CREB5/TNC pathway. This result provides a new direction for uncovering how ERS regulates EMT and a foundation for preventing the progression of EMT in HCC.

Elevated miR-221-3p inhibits epithelial-mesenchymal transition and biochemical recurrence of prostate cancer via targeting KPNA2: an evidence-based and knowledge-guided strategy

BACKGROUND

Prostate cancer (PCa) is commonly occurred among males worldwide and its prognosis could be influenced by biochemical recurrence (BCR). MicroRNAs (miRNAs) are functional regulators in carcinogenesis, and miR-221-3p was reported as one of the significant candidates deregulated in PCa. However, its regulatory pattern in PCa BCR across literature reports was not consistent, and the targets and mechanisms in PCa malignant transition and BCR are less explored.

METHODS

In this study, an evidence-based and knowledge-guided approach was proposed to decipher the role and mechanism of miR-221-3p in PCa development. First, the literature-reported inconsistency between miR-221-3p and PCa BCR was quantitatively measured by meta-analysis. Then a knowledge-guided network strategy was applied to prioritize key targets of miR-221-3p in PCa progression based both on topological and functional characterization of genes in multi-omics miRNA-mRNA and protein-protein interaction networks. Finally, a key gene was computationally identified and experimentally validated using cell line and clinical samples through EdU assay, scratch assay, transwell assay, dual-luciferase reporter assay and the epithelial-to-mesenchymal transition (EMT)-related analysis.

RESULTS

Down-regulation of miR-221-3p was correlated with a lower biochemical recurrence-free survival (BRFS) in PCa (HR: 0.72, 95%, CI: 0.64-0.81, P < 0.00001). A significant down-regulation of miR-221-3p was observed in most of the PCa cells compared with the normal control. KPNA2 was identified as a key target of miR-221-3p and it was over-expressed in all the PCa cells and human PCa tissues. Moreover, elevated miR-221-3p inhibited the proliferation, migration, invasion, and EMT of PCa cells in vitro via directly and negatively mediating KPNA2 expression.

CONCLUSIONS

miR-221-3p down-regulation was a risk factor for PCa BRFS, and its over-expression could inhibit the malignant phenotype and EMT of PCa cells by directly targeting KPNA2. Translational and personalized applications of the findings will be conducted in the future.

metsDB: a knowledgebase of cancer metastasis at bulk, single-cell and spatial levels

Cancer metastasis, the process by which tumour cells migrate and colonize distant organs from a primary site, is responsible for the majority of cancer-related deaths. Understanding the cellular and molecular mechanisms underlying this complex process is essential for developing effective metastasis prevention and therapy strategies. To this end, we systematically analysed 1786 bulk tissue samples from 13 cancer types, 988 463 single cells from 17 cancer types, and 40 252 spots from 45 spatial slides across 10 cancer types. The results of these analyses are compiled in the metsDB database, accessible at https://relab.xidian.edu.cn/metsDB/. This database provides insights into alterations in cell constitutions, cell relationships, biological pathways, molecular biomarkers, and drug responses during cancer metastasis at bulk, single-cell, and spatial levels. Users can perform cell or gene searches to obtain multi-view and multi-scale metastasis-related data. This comprehensive resource is invaluable for understanding the metastasis process and for designing molecular therapies.

Transcriptional regulators ensuring specific gene expression and decision-making at high TGFβ doses

TGFβ-signaling regulates cancer progression by controlling cell division, migration, and death. These outcomes are mediated by gene expression changes, but the mechanisms of decision-making toward specific fates remain unclear. Here, we combine SMAD transcription factor imaging, genome-wide RNA sequencing, and morphological assays to quantitatively link signaling, gene expression, and fate decisions in mammary epithelial cells. Fitting genome-wide kinetic models to our time-resolved data, we find that most of the TGFβ target genes can be explained as direct targets of SMAD transcription factors, whereas the remainder show signs of complex regulation, involving delayed regulation and strong amplification at high TGFβ doses. Knockdown experiments followed by global RNA sequencing revealed transcription factors interacting with SMADs in feedforward loops to control delayed and dose-discriminating target genes, thereby reinforcing the specific epithelial-to-mesenchymal transition at high TGFβ doses. We identified early repressors, preventing premature activation, and a late activator, boosting gene expression responses for a sufficiently strong TGFβ stimulus. Taken together, we present a global view of TGFβ-dependent gene regulation and describe specificity mechanisms reinforcing cellular decision-making.

Exploring the role of the Rab network in epithelial-to-mesenchymal transition

Motivation

Rab GTPases (Rabs) are crucial for membrane trafficking within mammalian cells, and their dysfunction is implicated in many diseases. This gene family plays a role in several crucial cellular processes. Network analyses can uncover the complete repertoire of interaction patterns across the Rab network, informing disease research, opening new opportunities for therapeutic interventions.

Results

We examined Rabs and their interactors in the context of epithelial-to-mesenchymal transition (EMT), an indicator of cancer metastasizing to distant organs. A Rab network was first established from analysis of literature and was gradually expanded. Our Python module, resnet, assessed its network resilience and selected an optimally sized, resilient Rab network for further analyses. Pathway enrichment confirmed its role in EMT. We then identified 73 candidate genes showing a strong up-/down-regulation, across 10 cancer types, in patients with metastasized tumours compared to only primary-site tumours. We suggest that their encoded proteins might play a critical role in EMT, and further in vitro studies are needed to confirm their role as predictive markers of cancer metastasis. The use of resnet within the systematic analysis approach described here can be easily applied to assess other gene families and their role in biological events of interest.

Availability and implementation

Source code for resnet is freely available at https://github.com/Unmani199/resnet.

Generation of novel lipid metabolism-based signatures to predict prognosis and immunotherapy response for colorectal adenocarcinoma

Lipid metabolism reprogramming involves in epithelial-mesenchymal transition (EMT), cancer stemness and immune checkpoints (ICs), which influence the metastasis of cancer. This study aimed to generate lipid metabolism-based signatures to predict prognosis, immunotherapy and chemotherapy response for colorectal adenocarcinoma (COAD). Transcriptome data and clinical information of COAD patients were collected from the cancer genome atlas (TCGA) database. The expression of EMT-, stem cell-, and IC-related genes were assessed between COAD and control samples. Modules and genes correlated EMT, ICs and stemness signatures were identified through weighted gene co-expression network analysis (WGCNA). Prognostic signatures were generated and then the distribution of risk genes was evaluated using single-cell RNA sequencing (scRNA-seq) data from GSE132465 dataset. COAD patients exhibited increased EMT score and stemness along with decreased ICs. Next, 12 hub genes (PIK3CG, ALOX5AP, PIK3R5, TNFAIP8L2, DPEP2, PIK3CD, PIK3R6, GGT5, ELOVL4, PTGIS, CYP7B1 and PRKD1) were found within green and yellow modules correlated with EMT, stemness and ICs. Lipid metabolism-based prognostic signatures were generated based on PIK3CG, GGT5 and PTGIS. Patients with high-risk group had poor prognosis, elevated ESTIMATEScore and StromalScore, 100% mutation rate and higher TIDE score. Samples in low-risk group had more immunogenicity on ICIs. Notably, PIK3CG was expressed in B cells, while GGT5 and PTGIS were expressed in stromal cells. This study generates lipid metabolism-based signatures correlated with EMT, stemness and ICs for predicting prognosis of COAD, and provides potential therapeutic targets for immunotherapy in COAD.

Epigenetic changes regulating the epithelial-mesenchymal transition in human trophoblast differentiation

The phenotype of human placental extravillous trophoblast (EVT) at the end of pregnancy reflects both first trimester differentiation from villous cytotrophoblast (CTB) and later gestational changes, including loss of proliferative and invasive capacity. Invasion abnormalities are central to two major placental pathologies, preeclampsia and placenta accreta spectrum, so characterization of the corresponding normal processes is crucial. In this report, our gene expression analysis, using purified human CTB and EVT cells, highlights an epithelial-mesenchymal transition (EMT) mechanism underlying CTB-EVT differentiation and provides a trophoblast-specific EMT signature. In parallel, DNA methylation profiling shows that CTB cells, already hypomethylated relative to non-trophoblast cell lineages, show further genome-wide hypomethylation in the transition to EVT. However, a small subgroup of genes undergoes gains of methylation (GOM) in their regulatory regions or gene bodies, associated with differential mRNA expression (DE). Prominent in this GOM-DE group are genes involved in the EMT, including multiple canonical EMT markers and the EMT-linked transcription factor RUNX1, for which we demonstrate a functional role in modulating the migratory and invasive capacities of JEG3 trophoblast cells. This analysis of DE associated with locus-specific GOM, together with functional studies of an important GOM-DE gene, highlights epigenetically regulated genes and pathways acting in human EVT differentiation and invasion, with implications for obstetric disorders in which these processes are dysregulated.

The lncRNA UCA1 Enhances Pancreatic Cancer EMT by Regulating miR-708-5p and miR-135b-5p: A Bioinformatics Approach

Background

Pancreatic cancer (PC) is an exceedingly malignant ailment that is not only characterized by its insidious onset and rapid progression but also by its poor therapeutic effects. Recently, emerging evidence has shed light on the significant role that non-coding RNAs (ncRNAs), particularly long ncRNAs (lncRNAs) and microRNAs (miRNAs), play in the pathogenesis of PC. This investigation aimed to construct a network of interactions between miRNAs, lncRNAs, and mRNAs, as well as to perform correlation analyses in the context of PC.

Methods

This study carried out in Kerman City, southeastern Iran in 2023. We utilized the GSE119794 dataset from the Gene Expression Omnibus (GEO) to analyze differentially expressed lncRNAs (DE-lncRNAs), miRNAs (DE-miRNAs), and mRNAs (DE-mRNAs). Following the identification of the DE-lncRNAs, DE-mRNAs, and DE-miRNAs, we proceeded to examine differentially expressed epithelialmesenchymal transition (EMT) genes. Subsequently, we utilized the RNAInter database to predict interactions among lncRNAs, miRNAs, and mRNAs. Finally, we employed Cytoscape to visualize and analyze the constructed network.

Results

14 DE-lncRNAs, 14 DE-miRNAs, 545 DE-mRNAs, and 65 DE-EMT from pancreatic cancer and its adjacent tissue RNA-Seq data were identified. 1184 EMT genes from dbEMT were obtained, among which 65 DE-EMT were assigned as EMT genes and correlated with tumor progression. One functional lncRNA (UCA1) was identified as a key functional lncRNA. The area under the ROC curve (AUC) of UCA1 and miR-708-5p were 0.79 and 0.86, respectively. Thus, it is reasonable to believe that this prognostic risk model helps predict PC metastasis.

Conclusion

UCA1 is a new lncRNA linked with EMT in PC and contributes to a better knowledge of the regulatory mechanisms related to lncRNAs in PC.

Epithelial-mesenchymal transition dysregulation in prostate cancer: Insights from molecular unraveling and epidemiological analyses in Tunisia, North Africa

INTRODUCTION

The progression of prostate cancer (PCa) has been linked worldwide, including in African populations, to the dysregulation of the epithelial-mesenchymal transition (EMT).

METHODS

To clarify the connection among EMT markers, clinicopathological parameters, and epidemiological factors, we analyzed 35 PCa specimens from patients in Tunisia, a country in North Africa, arranged by stages. We also carried out extensive molecular and epidemiological analyses.

RESULTS

Significant dysregulation of EMT genes was found, with an overexpression of ZEB-1, Twist, Snail-1, and Vimentin (p < 0.05) and underexpression of E-cadherin and β-catenin (p < 0.05). Positive correlations were observed between transcription factors and the mesenchymal marker Vimentin (p < 0.001, r = 0.574; p = 0.029, r = 0.411; and p < 0.001; r = 0.506) according to Spearman correlation analyses, whereas negative correlations were found between epithelial markers (E-cadherin, β-catenin) and Vimentin (p < 0.05; r < 0). Higher PSA, Gleason scores, and metastasis were all correlated with the dysregulation of EMT (p < 0.05). Notably, there was a positive correlation between higher consumption of tobacco (≥20 Packets per year) and Vimentin expression (p < 0.001, r = 0.854), suggesting a relationship between smoking and EMT activation in the Tunisian population. Moreover, Twist showed a positive correlation with diabetes (p < 0.001, r = 0.385), whereas no significant correlations were found between EMT markers and comorbidities such as hypertension and coronary insufficiency. These results demonstrate the intricate connection between molecular changes, epidemiological factors, and disease progression, and they emphasize the crucial role that EMT plays in promoting PCa aggressiveness in African populations, particularly in Tunisia.

CONCLUSION

In summary, understanding these correlations could help develop focused treatment plans and enhance patient outcomes for PCa management in African settings.

Genomic Landscape of Pulmonary Sarcomatoid Carcinoma

PURPOSE

Pulmonary sarcomatoid carcinoma (PSC) is a rare aggressive subtype of non-small cell lung cancer (NSCLC) with limited therapeutic strategies. We attempted to elucidate the evolutionary trajectories of PSC using multiregional and longitudinal tumor samples.

MATERIALS AND METHODS

A total of 31 patients were enrolled in this study and 11 longitudinal samples were available from them. Using whole exome sequencing data, we analyzed the mutational signatures in both carcinomatous and sarcomatous areas in primary tumors of the 31 patients and longitudinal samples obtained from 11 patients. Furthermore, digital droplet polymerase chain reaction (ddPCR), and programmed death-ligand 1 (PD-L1) immunohistochemistry using the Ventana SP263 assay were performed.

RESULTS

TP53 was identified as the most frequently altered gene in the primary (74%) and metastatic (73%) samples. MET exon 14 skipping mutations, confirmed by ddPCR, and TP53 mutations were mutually exclusive; whereas, MET exon 14 skipping mutations frequently co-occurred with MDM2 amplification. Metastatic tumors showed dissimilar genetic profiles from either primary component. During metastasis, the signatures of APOBEC decreased in metastatic lesions compared with that in primary lesions. PSC showed higher MET and KEAP1 mutations and stronger PD-L1 protein expression compared with that recorded in other NSCLCs.

CONCLUSION

Decreased APOBEC signatures and subclonal diversity were detected during malignant progression in PSC. Frequent MET mutations and strong PD-L1 expression distinguished PSC from other NSCLCs. The aggressiveness and therapeutic difficulties of PSC were possibly attributable to profound intratumoral and intertumoral genetic diversity. Next-generation sequencing could suggest the appropriate treatment strategy for PSC.

Deciphering Breast Cancer Metastasis Cascade: A Systems Biology Approach Integrating Transcriptome and Interactome Insights for Target Discovery

Breast cancer is the lead cause of cancer-related deaths among women globally. Breast cancer metastasis is a complex and still inadequately understood process and a key dimension of mortality attendant to breast cancer. This study reports dysregulated genes across metastatic stages and tissues, shedding light on their molecular interplay in disease pathogenesis and new possibilities for drug discovery. Comprehensive analyses of gene expression data from primary breast tumor, circulating tumor cells, and distant metastatic sites in the brain, lung, liver, and bone were conducted. Genes dysregulated across multiple stages and tissues were identified as metastatic cascade genes, and are further classified based on functional associations with metastasis-related mechanisms. Their interactions with HUB genes in interactome networks were scrutinized, followed by pathway enrichment analysis. Validation for their potential as targets included assessments for survival, druggability, prognostic marker status, secretome annotation, protein expression, and cell type marker association. Results displayed critical genes in the metastatic cascade and those specific to metastatic sites, revealing the involvement of the collagen degradation and assembly of collagen fibrils and other multimeric structure pathways in driving metastasis. Notably, pivotal cascade genes FABP4, CXCL12, APOD, and IGF1 emerged with high metastatic potential, linked to significant druggability and survival scores, establishing them as potential molecular targets. The significance of this research lies in its potential to uncover novel biomarkers for early detection, therapeutic targets, and a deeper understanding of the molecular mechanisms underpinning the metastatic cascade in breast cancer, and with an eye to precision/personalized medicine.

Transcriptional profile of human thymus reveals IGFBP5 is correlated with age-related thymic involution

Thymus is the main immune organ which is responsible for the production of self-tolerant and functional T cells, but it shrinks rapidly with age after birth. Although studies have researched thymus development and involution in mouse, the critical regulators that arise with age in human thymus remain unclear. We collected public human single-cell transcriptomic sequencing (scRNA-seq) datasets containing 350,678 cells from 36 samples, integrated them as a cell atlas of human thymus. Clinical samples were collected and experiments were performed for validation. We found early thymocyte-specific signaling and regulons which played roles in thymocyte migration, proliferation, apoptosis and differentiation. Nevertheless, signaling patterns including number, strength and path completely changed during aging, Transcription factors (FOXC1, MXI1, KLF9, NFIL3) and their target gene, IGFBP5, were resolved and up-regulated in aging thymus and involved in promoting epithelial-mesenchymal transition (EMT), responding to steroid and adipogenesis process of thymic epithelial cell (TECs). Furthermore, we validated that IGFBP5 protein increased at TECs and Hassall's corpuscle in both human and mouse aging thymus and knockdown of IGFBP5 significantly increased the expression of proliferation-related genes in thymocytes. Collectively, we systematically explored cell-cell communications and regulons of early thymocytes as well as age-related differences in human thymus by using both bioinformatic and experimental verification, indicating IGFBP5 as a functional marker of thymic involution and providing new insights into the mechanisms of thymus involution.

Cellular Context Dictates the Suppression or Augmentation of Triple-Negative Mammary Tumor Metastasis by NLRX1

Prior studies have defined multiple, but inconsistent, roles for the enigmatic pattern recognition receptor NLRX1 in regulating several cancer-associated biological functions. In this study, we explore the role of NLRX1 in the highly metastatic murine 4T1 mammary tumor model. We describe a functional dichotomy of NLRX1 between two different cellular contexts: expression in healthy host cells versus expression in the 4T1 tumor cells. Using Nlrx1-/- mice engrafted with 4T1 tumors, we demonstrate that NLRX1 functions as a tumor suppressor when expressed in the host cells. Specifically, NLRX1 in healthy host cells attenuates tumor growth and lung metastasis through suppressing characteristics of epithelial-mesenchymal transition and the lung metastatic niche. Conversely, we demonstrate that NLRX1 functions as a tumor promoter when expressed in 4T1 tumor cells using gain- and loss-of-function studies both in vitro and in vivo. Mechanistically, NLRX1 in the tumor cells augments 4T1 aggressiveness and metastasis through regulating epithelial-mesenchymal transition hallmarks, cell death, proliferation, migration, reactive oxygen species levels, and mitochondrial respiration. Collectively, we provide critical insight into NLRX1 function and establish a dichotomous role of NLRX1 in the 4T1 murine mammary carcinoma model that is dictated by cellular context.

Respiratory Syncytial Virus Infection Does Not Induce Epithelial-Mesenchymal Transition

Respiratory syncytial virus (RSV) infection does not cause severe disease in most of us despite suffering from multiple RSV infections during our lives. However, infants, young children, older adults, and immunocompromised patients are unfortunately vulnerable to RSV-associated severe diseases. A recent study suggested that RSV infection causes cell expansion, resulting in bronchial wall thickening in vitro. Whether the virus-induced changes in the lung airway resemble epithelial-mesenchymal transition (EMT) is still unknown. Here, we report that RSV does not induce EMT in three different in vitro lung models: the epithelial A549 cell line, primary normal human bronchial epithelial cells, and pseudostratified airway epithelium. We found that RSV increases the cell surface area and perimeter in the infected airway epithelium, which is distinct from the effects of a potent EMT inducer, transforming growth factor β1 (TGF-β1), driving cell elongation-indicative of cell motility. A genome-wide transcriptome analysis revealed that both RSV and TGF-β1 have distinct modulation patterns of the transcriptome, which suggests that RSV-induced changes are distinct from EMT. IMPORTANCE We have previously shown that RSV infects ciliated cells on the apical side of the lung airway. RSV-induced cytoskeletal inflammation contributes to an uneven increase in the height of the airway epithelium, resembling noncanonical bronchial wall thickening. RSV infection changes epithelial cell morphology by modulating actin-protein 2/3 complex-driven actin polymerization. Therefore, it is prudent to investigate whether RSV-induced cell morphological changes contribute to EMT. Our data indicate that RSV does not induce EMT in at least three different epithelial in vitro models: an epithelial cell line, primary epithelial cells, and pseudostratified bronchial airway epithelium.

RSV infection does not induce EMT

Respiratory syncytial virus (RSV) infection does not cause severe disease in most of us despite suffering from multiple RSV infections in our lives. However, infants, young children, older adults, and immunocompromised patients are unfortunately vulnerable to RSV-associated severe diseases. A recent study suggested that RSV infection causes cell expansion, resulting in bronchial wall thickening in vitro. Whether the virus-induced changes in the lung airway resemble epithelial-mesenchymal transition (EMT) is still unknown. Here, we report that RSV does not induce EMT in three different in vitro lung models: the epithelial A549 cell line, primary normal human bronchial epithelial cells, and pseudostratified airway epithelium. We found that RSV increases the cell surface area and perimeter in the infected airway epithelium, which is distinct from the effects of a potent EMT inducer, TGF-β1-driven cell elongation-indicative of cell motility. A genome-wide transcriptome analysis revealed that both RSV and TGF-β1 have distinct modulation patterns of the transcriptome, which suggests that RSV-induced changes are distinct from EMT.

An EMT-based gene signature enhances the clinical understanding and prognostic prediction of patients with ovarian cancers

BACKGROUND

Ovarian cancer (OC) is one of the most common gynecological cancers with malignant metastasis and poor prognosis. Current evidence substantiates that epithelial-mesenchymal transition (EMT) is a critical mechanism that drives OC progression. In this study, we aspire to identify pivotal EMT-related genes (EMTG) in OC development, and establish an EMT gene-based model for prognosis prediction.

METHODS

We constructed the risk score model by screening EMT genes via univariate/LASSO/step multivariate Cox regressions in the OC cohort from TCGA database. The efficacy of the EMTG model was tested in external GEO cohort, and quantified by the nomogram. Moreover, the immune infiltration and chemotherapy sensitivity were analyzed in different risk score groups.

RESULTS

We established a 11-EMTGs risk score model to predict the prognosis of OC patients. Based on the model, OC patients were split into high- and low- risk score groups, and the high-risk score group had an inevitably poor survival. The predictive power of the model was verified by external OC cohort. The nomogram showed that the model was an independent factor for prognosis prediction. Moreover, immune infiltration analysis revealed the immunosuppressive microenvironment in the high-risk score group. Finally, the EMTG model can be used to predict the sensitivity to chemotherapy drugs.

CONCLUSIONS

This study demonstrated that EMTG model was a powerful tool for prognostic prediction of OC patients. Our work not only provide a novel insight into the etiology of OC tumorigenesis, but also can be used in the clinical decisions on OC treatment.

Integrative network analysis reveals subtype-specific long non-coding RNA regulatory mechanisms in head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSC) is one of most common malignancies with high mortality worldwide. Importantly, the molecular heterogeneity of HNSC complicates the clinical diagnosis and treatment, leading to poor overall survival outcomes. To dissect the complex heterogeneity, recent studies have reported multiple molecular subtyping systems. For instance, HNSC can be subdivided to four distinct molecular subtypes: atypical, basal, classical, and mesenchymal, of which the mesenchymal subtype is characterized by upregulated epithelial-mesenchymal transition (EMT) and associated with poorer survival outcomes. Despite a wealth of studies into the complex molecular heterogeneity, the regulatory mechanism specific to this aggressive subtype remain largely unclear. Herein, we developed a network-based bioinformatics framework that integrates lncRNA and mRNA expression profiles to elucidate the subtype-specific regulatory mechanisms. Applying the framework to HNSC, we identified a clinically relevant lncRNA LNCOG as a key master regulator mediating EMT underlying the mesenchymal subtype. Five genes with strong prognostic values, namely ANXA5, ITGA5, CCBE1, P4HA2, and EPHX3, were predicted to be the putative targets of LNCOG and subsequently validated in other independent datasets. By integrative analysis of the miRNA expression profiles, we found that LNCOG may act as a ceRNA to sponge miR-148a-3p thereby upregulating ITGA5 to promote HNSC progression. Furthermore, our drug sensitivity analysis demonstrated that the five putative targets of LNCOG were also predictive of the sensitivities of multiple FDA-approved drugs. In summary, our bioinformatics framework facilitates the dissection of cancer subtype-specific lncRNA regulatory mechanisms, providing potential novel biomarkers for more optimized treatment of HNSC.

New roles for AP-1/JUNB in cell cycle control and tumorigenic cell invasion via regulation of cyclin E1 and TGF-β2

BACKGROUND

JUNB transcription factor contributes to the formation of the ubiquitous transcriptional complex AP-1 involved in the control of many physiological and disease-associated functions. The roles of JUNB in the control of cell division and tumorigenic processes are acknowledged but still unclear.

RESULTS

Here, we report the results of combined transcriptomic, genomic, and functional studies showing that JUNB promotes cell cycle progression via induction of cyclin E1 and repression of transforming growth factor (TGF)-β2 genes. We also show that high levels of JUNB switch the response of TGF-β2 stimulation from an antiproliferative to a pro-invasive one, induce endogenous TGF-β2 production by promoting TGF-β2 mRNA translation, and enhance tumor growth and metastasis in mice. Moreover, tumor genomic data indicate that JUNB amplification associates with poor prognosis in breast and ovarian cancer patients.

CONCLUSIONS

Our results reveal novel functions for JUNB in cell proliferation and tumor aggressiveness through regulation of cyclin E1 and TGF-β2 expression, which might be exploited for cancer prognosis and therapy.

Synthesis and Characterization of a Novel Peptide Targeting Human Tenon Fibroblast Cells To Modulate Fibrosis: An Integrated Empirical Approach

Fibrosis is the primary factor influencing the prognosis of glaucoma post-trabeculectomy surgery, an eye condition characterized by increased intraocular pressure (IOP). Despite advancements in surgical procedures and aftercare, it continues to be a serious impediment. During the clinical intervention of scarring, fibrosis is managed by using topical application of combined antifibrotic drugs (mitomycin C). But still, scarring remains a key problem due to minimal drug penetration and nonbioavailability. In this study, we synthesized a cell-specific peptide for modulating scarring in human tenon fibroblasts undergoing epithelial-mesenchymal transition (EMT). The peptide was also conjugated with mitomycin C in order to investigate the effect of the drug conjugation on human tenon fibroblasts from the nanofiber composite system and to evaluate the fibrosis process. Peptide VRF2019 was identified using a subtractive proteomics approach, including solubility, cell penetration, and amphipathic properties. The peptide structure was determined using circular dichroism spectroscopy. The peptide and drug was conjugated using N-ethyl-N'-(3-(dimethylamino)propyl) carbodiimide/N-hydroxysuccinimide (EDC-NHS) chemistry, and the conjugation efficiency was evaluated using high-pressure liquid chromatography. The conjugated product and polycaprolactone (PCL) were electrospun to form a composite nanofiber, which was tested for cytotoxicity and drug release on human tenon fibroblast cells. The modeled VRF2019 peptide structure formed an α-helical structure with all residues spanning the allowed regions of the Ramachandran plot. Subsequent molecular dynamics simulations also demonstrated its membrane penetration potential. The peptide uptake was also studied in human tenon fibroblast cells. High-pressure liquid chromatography (HPLC) and mass spectrometry measurements confirmed peptide-drug conjugation and stability. Furthermore, scanning electron microscopy (SEM) investigation revealed the structure and size of the PCL composite nanofiber. We infer from early research that the PCL composite nanofiber matrix can greatly increase drug delivery and bioavailability.

Efficient Selection of Enhancers and Promoters from MIA PaCa-2 Pancreatic Cancer Cells by ChIP-lentiMPRA

A library of active genome regulatory elements (putative promoters and enhancers) from MIA PaCa-2 pancreatic adenocarcinoma cells was constructed using a specially designed lentiviral vector and a massive parallel reporter assay (ChIP-lentiMPRA). Chromatin immunoprecipitation of the cell genomic DNA by H3K27ac antibodies was used for primary enrichment of the library for regulatory elements. Totally, 11,264 unique genome regions, many of which are capable of enhancing the expression of the CopGFP reporter gene from the minimal CMV promoter, were identified. The regions tend to be located near promoters. Based on the proximity assay, we found an enrichment of highly expressed genes among those associated with three or more mapped distal regions (2 kb distant from the 5'-ends of genes). It was shown significant enrichment of genes related to carcinogenesis or Mia PaCa-2 cell identity genes in this group. In contrast, genes associated with 1-2 distal regions or only with proximal regions (within 2 kbp of the 5'-ends of genes) are more often related to housekeeping functions. Thus, ChIP-lentiMPRA is a useful strategy for creating libraries of regulatory elements for the study of tumor-specific gene transcription.

Identification of a minority population of LMO2+ breast cancer cells that integrate into the vasculature and initiate metastasis

Metastasis is responsible for most breast cancer-related deaths; however, identifying the cellular determinants of metastasis has remained challenging. Here, we identified a minority population of immature THY1+/VEGFA+ tumor epithelial cells in human breast tumor biopsies that display angiogenic features and are marked by the expression of the oncogene, LMO2. Higher abundance of LMO2+ basal cells correlated with tumor endothelial content and predicted poor distant recurrence-free survival in patients. Using MMTV-PyMT/Lmo2CreERT2 mice, we demonstrated that Lmo2 lineage-traced cells integrate into the vasculature and have a higher propensity to metastasize. LMO2 knockdown in human breast tumors reduced lung metastasis by impairing intravasation, leading to a reduced frequency of circulating tumor cells. Mechanistically, we find that LMO2 binds to STAT3 and is required for STAT3 activation by tumor necrosis factor-α and interleukin-6. Collectively, our study identifies a population of metastasis-initiating cells with angiogenic features and establishes the LMO2-STAT3 signaling axis as a therapeutic target in breast cancer metastasis.

Endotype reversal as a novel strategy for screening drugs targeting familial Alzheimer's disease

While amyloid-β (Aβ) plaques are considered a hallmark of Alzheimer's disease, clinical trials focused on targeting gamma secretase, an enzyme involved in aberrant Aβ peptide production, have not led to amelioration of AD symptoms or synaptic dysregulation. Screening strategies based on mechanistic, multi-omics approaches that go beyond pathological readouts can aid in the evaluation of therapeutics. Using early-onset Alzheimer's (EOFAD) disease patient lineage PSEN1^A246E iPSC-derived neurons, we performed RNA-seq to characterize AD-associated endotypes, which are in turn used as a screening evaluation metric for two gamma secretase drugs, the inhibitor Semagacestat and the modulator BPN-15606. We demonstrate that drug treatment partially restores the neuronal state while concomitantly inhibiting cell cycle re-entry and dedifferentiation endotypes to different degrees depending on the mechanism of gamma secretase engagement. Our endotype-centric screening approach offers a new paradigm by which candidate AD therapeutics can be evaluated for their overall ability to reverse disease endotypes.

CTpathway: a CrossTalk-based pathway enrichment analysis method for cancer research

BACKGROUND

Pathway enrichment analysis (PEA) is a common method for exploring functions of hundreds of genes and identifying disease-risk pathways. Moreover, different pathways exert their functions through crosstalk. However, existing PEA methods do not sufficiently integrate essential pathway features, including pathway crosstalk, molecular interactions, and network topologies, resulting in many risk pathways that remain uninvestigated.

METHODS

To overcome these limitations, we develop a new crosstalk-based PEA method, CTpathway, based on a global pathway crosstalk map (GPCM) with >440,000 edges by combing pathways from eight resources, transcription factor-gene regulations, and large-scale protein-protein interactions. Integrating gene differential expression and crosstalk effects in GPCM, we assign a risk score to genes in the GPCM and identify risk pathways enriched with the risk genes.

RESULTS

Analysis of >8300 expression profiles covering ten cancer tissues and blood samples indicates that CTpathway outperforms the current state-of-the-art methods in identifying risk pathways with higher accuracy, reproducibility, and speed. CTpathway recapitulates known risk pathways and exclusively identifies several previously unreported critical pathways for individual cancer types. CTpathway also outperforms other methods in identifying risk pathways across all cancer stages, including early-stage cancer with a small number of differentially expressed genes. Moreover, the robust design of CTpathway enables researchers to analyze both bulk and single-cell RNA-seq profiles to predict both cancer tissue and cell type-specific risk pathways with higher accuracy.

CONCLUSIONS

Collectively, CTpathway is a fast, accurate, and stable pathway enrichment analysis method for cancer research that can be used to identify cancer risk pathways. The CTpathway interactive web server can be accessed here http://www.jianglab.cn/CTpathway/ . The stand-alone program can be accessed here https://github.com/Bioccjw/CTpathway .

Inhibitory Effects of Rhein on Renal Interstitial Fibrosis via the SHH-Gli1 Signal Pathway

Background. Rhein is the main extract of Rheum palmatum L., which has been proved to improve the renal function of chronic kidney disease, but its mechanism is not clear. Therefore, this experiment explored the potential pharmacological effect of rhein on renal interstitial fibrosis rats. Methods. This study explores the potential pharmacological action of rhein. In this work, we investigate the potential pharmacological action of rhein in unilateral urethral obstruction (UUO) rats. Thirty Sprague Dawley rats were randomly divided into three groups: sham, UUO, and rhein (rhein-treated UUO rats) groups. The left ureters of the UUO group rats were exposed and bluntly dissected. The rhein group rats were administered an intragastric gavage of rhein (2 mg·kg−1·d−1) for 14 d. Kidney function-related indicators were monitored in these rats, while indexes of pathologic aspects were determined histologically. The expression of α-SMA, TGF-β1, SHH, Gli1, and Snail was quantified using real-time polymerase chain reaction and western blotting. The NRK-49F cells were incubated with and without SHH (100 ng·ml−1) for 48 hours. The SHH-activated NRK-49F cells were incubated with cyclopamine (CNP, 20 umol L−1) or rhein (1 ng·ml−1). The Gli1 and Snail mRNA and protein level were detected. Results. In the in vivo experiment, the results exhibited that UUO caused renal pathological damages. However, these changes could be significantly reversed by the administration of rhein. Compared with the untreated UUO group, the rhein group showed reduced kidney tubular atrophy and necrosis, interstitial fibrosis, hyperplasia, and abnormal deposition of extracellular matrix. Rhein reduced the RNA and protein expression of SHH, Gli1, and Snail of the UUO rats. In the in vitro experiment, CNP or rhein treatment decreased the expression of Gli1 and Snail on mRNA and protein levels in SHH-induced NRK-49F cells, suggesting that CNP or rhein suppresses SHH-induced NRK-49F activation. Taken together, these results demonstrated that rhein suppresses SHH-Gli1-Snail signal pathway activation, with potential implications for the treatment of renal fibrosis. Conclusions. Treatment with rhein remarkably ameliorated renal interstitial fibrosis in UUO rats by regulating the SHH-Gli1-Snail signal pathway.

Reliable epithelial-mesenchymal transition biomarkers for colorectal cancer detection

Aims: To combat increases in colorectal cancer (CRC) incidence and mortality, biomarkers among differentially expressed genes (DEGs) have been identified to objectively detect cancer. However, DEGs are numerous, and additional parameters may identify more reliable biomarkers. Here, CRC DEGs were filtered into a prioritized list of biomarkers. Materials & methods: Two independent datasets (COAD-READ [n = 698] and GSE50760 [n = 36]) were input alternatively to the recently published data-driven reference method. Results were filtered based on epithelial-mesenchymal transition enrichment (χ-square statistic: 919.05; p = 2.2e-16) to produce 37 potential CRC biomarkers. Results: All 37 genes reliably classified CRC samples and ETV4, CLDN1 and CA2 together were top-ranked by DDR (accuracy: 89%; F1 score: 0.89). Conclusion: Biological and statistical information were combined to produce a better set of CRC detection biomarkers.

APE1 controls DICER1 expression in NSCLC through miR-33a and miR-130b

Increasing evidence suggests different, not completely understood roles of microRNA biogenesis in the development and progression of lung cancer. The overexpression of the DNA repair protein apurinic/apyrimidinic endodeoxyribonuclease 1 (APE1) is an important cause of poor chemotherapeutic response in lung cancer and its involvement in onco-miRNAs biogenesis has been recently described. Whether APE1 regulates miRNAs acting as prognostic biomarkers of lung cancer has not been investigated, yet. In this study, we analyzed miRNAs differential expression upon APE1 depletion in the A549 lung cancer cell line using high-throughput methods. We defined a signature of 13 miRNAs that strongly correlate with APE1 expression in human lung cancer: miR-1246, miR-4488, miR-24, miR-183, miR-660, miR-130b, miR-543, miR-200c, miR-376c, miR-218, miR-146a, miR-92b and miR-33a. Functional enrichment analysis of this signature revealed its biological relevance in cancer cell proliferation and survival. We validated DICER1 as a direct functional target of the APE1-regulated miRNA-33a-5p and miR-130b-3p. Importantly, IHC analyses of different human tumors confirmed a negative correlation existing between APE1 and Dicer1 protein levels. DICER1 downregulation represents a prognostic marker of cancer development but the mechanisms at the basis of this phenomenon are still completely unknown. Our findings, suggesting that APE1 modulates DICER1 expression via miR-33a and miR-130b, reveal new mechanistic insights on DICER1 regulation, which are of relevance in lung cancer chemoresistance and cancer invasiveness.

Epithelial-Mesenchymal Transition-Based Gene Signature and Distinct Molecular Subtypes for Predicting Clinical Outcomes in Breast Cancer

Purpose

Regulation of inducers and transcription factor families influence epithelial–mesenchymal transition (EMT), a contributing factor to breast cancer invasion and progression.

Methods

Molecular subtypes were classified based on EMT-related mRNAs using ConsensusClusterPlus package. Differences in tumor immune microenvironment and prognosis were assessed among subtypes. Based on EMT genes, a gene signature for prognosis was built using TCGA training set by performing multivariate and univariate Cox regression analyses. Prediction accuracy of the signature was validated by receiver operating characteristic (ROC) curves and overall survival analysis on internal and external datasets. By conducting univariate and multivariate Cox regression analyses, the risk signature as an independent prognostic indicator was assessed. A nomogram was constructed and validated by calibration analysis and decision curve analysis (DCA).

Results

Five molecular subtypes were characterized based on EMT genes. Patients in Cluster 2 exhibited an activated immune state and a better prognosis. An 11-EMT gene-signature was built to predict breast cancer prognosis. After validation, the signature showed independence and robustness in predicting clinical outcomes of patients. A nomogram combining the RiskScore and pTNM_stage accurately predicted 1-, 2-, 3-, and 5-year survival chance. In comparison with published model, the current model showed a higher area under the curve (AUC).

Conclusion

We characterized five breast cancer subtypes with distinct clinical outcomes and immune status. The study developed an 11-EMT gene-signature as an independent prognostic factor for predicting clinical outcomes of breast cancer.

Identification of a Twelve Epithelial-Mesenchymal Transition-Related lncRNA Prognostic Signature in Kidney Clear Cell Carcinoma

Background

Epithelial-mesenchymal transition (EMT) plays a vital role in tumor metastasis and drug resistance. It has been reported that EMT is regulated by several long noncoding RNAs (lncRNAs). We aimed to identify EMT-related lncRNAs and develop an EMT-related lncRNA prognostic signature in kidney renal clear cell carcinoma (KIRC).

Materials and Methods

In total, 530 ccRCC patients with 611 transcriptome profiles were included in this study. We first identified differentially expressed EMT-related lncRNAs. Then, all the samples with transcriptional data and clinical survival information were randomly split into training/test sets at a ratio of 1 : 1. Accordingly, we further developed a twelve differentially expressed EMT-related lncRNA prognostic signature in the training set. Following this, risk analysis, survival analysis, subgroup analysis, and the construction of the ROC curves were applied to verify the efficacy of the signature in the training set, test set, and all patients. Besides, we further investigated the differential immune infiltration, immune checkpoint expression, and immune-related functions between high-risk patients. Finally, we explored the different drug responses to targeted therapy (sunitinib and sorafenib) and immunotherapy (anti-PD1 and anti-CTLA4).

Results

A twelve differentially expressed EMT-related lncRNA prognostic signature performed superior in predicting the overall survival of KIRC patients. High-risk patients were observed with a significantly higher immune checkpoint expression and showed better responses to the targeted therapy and immunotherapy.

Conclusions

Our study demonstrates that the twelve differentially expressed EMT-related lncRNA prognostic signature could act as an efficient prognostic indicator for KIRC, which also contributes to the decision-making of the further treatment.

In Silico Analysis of Ion Channels and Their Correlation with Epithelial to Mesenchymal Transition in Breast Cancer

Simple Summary

Breast cancer involves changes in the healthy cells of the breast resulting in rapid and abnormal division of cells that later spread to other parts of the body through the process of metastasis, which involves epithelial mesenchymal transition (EMT). Ion channels play a significant role in the switch from epithelial to mesenchymal transition through their contributions to cellular motility, cell volume regulation and cell cycle progression. Comprehensive computational analyses were performed to understand the role of ion channels in tumor/metastatic samples of breast cancer and their correlation with EMT.

Abstract

Uncontrolled growth of breast cells due to altered gene expression is a key feature of breast cancer. Alterations in the expression of ion channels lead to variations in cellular activities, thus contributing to attributes of cancer hallmarks. Changes in the expression levels of ion channels were observed as a consequence of EMT. Additionally, ion channels were reported in the activation of EMT and maintenance of a mesenchymal phenotype. Here, to identify altered ion channels in breast cancer patients, differential gene expression and weighted gene co-expression network analyses were performed using transcriptomic data. Protein–protein interactions network analysis was carried out to determine the ion channels interacting with hub EMT-related genes in breast cancer. Thirty-two ion channels were found interacting with twenty-six hub EMT-related genes. The identified ion channels were further correlated with EMT scores, indicating mesenchymal phenotype. Further, the pathway map was generated to represent a snapshot of deregulated cellular processes by altered ion channels and EMT-related genes. Kaplan–Meier five-year survival analysis and Cox regressions indicated the expression of CACNA1B, ANO6, TRPV3, VDAC1 and VDAC2 to be potentially associated with poor survival. Deregulated ion channels correlate with EMT-related genes and have a crucial role in breast cancer-associated tumorigenesis. Most likely, they are potential candidates for the determination of prognosis in patients with breast cancer.

Spatially Annotated Single Cell Sequencing for Unraveling Intratumor Heterogeneity

Intratumor heterogeneity is a major obstacle to effective cancer treatment. Current methods to study intratumor heterogeneity using single-cell RNA sequencing (scRNA-seq) lack information on the spatial organization of cells. While state-of-the art spatial transcriptomics methods capture the spatial distribution, they either lack single cell resolution or have relatively low transcript counts. Here, we introduce spatially annotated single cell sequencing, based on the previously developed functional single cell sequencing (FUNseq) technique, to spatially profile tumor cells with deep scRNA-seq and single cell resolution. Using our approach, we profiled cells located at different distances from the center of a 2D epithelial cell mass. By profiling the cell patch in concentric bands of varying width, we showed that cells at the outermost edge of the patch responded strongest to their local microenvironment, behaved most invasively, and activated the process of epithelial-to-mesenchymal transition (EMT) to migrate to low-confluence areas. We inferred cell-cell communication networks and demonstrated that cells in the outermost ∼10 cell wide band, which we termed the invasive edge, induced similar phenotypic plasticity in neighboring regions. Applying FUNseq to spatially annotate and profile tumor cells enables deep characterization of tumor subpopulations, thereby unraveling the mechanistic basis for intratumor heterogeneity.

Epithelial-mesenchymal transition related genes in unruptured aneurysms identified through weighted gene coexpression network analysis

Intracranial aneurysm (IA) can cause fatal subarachnoid hemorrhage (SAH) after rupture, and identifying patients with unruptured IAs is essential for reducing SAH fatalities. The epithelial-mesenchymal transition (EMT) may be vital to IA progression. Here, identified key EMT-related genes in aneurysms and their pathogenic mechanisms via bioinformatic analysis. The GSE13353, GSE75436, and GSE54083 datasets from Gene Expression Omnibus were analyzed with limma to identify differentially expressed genes (DEGs) among unruptured aneurysms, ruptured aneurysms, and healthy samples. The results revealed that three EMT-related DEGs (ADIPOQ, WNT11, and CCL21) were shared among all groups. Coexpression modules and hub genes were identified via weighted gene co-expression network analysis, revealing two significant modules (red and green) and 14 EMT-related genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses suggested that cytokine interactions were closely related. Gene set enrichment analysis revealed that unruptured aneurysms were enriched for the terms "inflammatory response" and "vascular endothelial growth". Protein-protein interaction analysis identified seven key genes, which were evaluated with the GSE54083 dataset to determine their sensitivity and specificity. In the external validation set, we verified the differential expression of seven genes in unruptured aneurysms and normal samples. Together, these findings indicate that FN1, and SPARC may help distinguish normal patients from patients with asymptomatic IAs.

Transcriptional census of epithelial-mesenchymal plasticity in cancer

Epithelial-mesenchymal plasticity (EMP) contributes to tumor progression, promoting therapy resistance and immune cell evasion. Definitive molecular features of this plasticity have largely remained elusive due to the limited scale of most studies. Leveraging single-cell RNA sequencing data from 266 tumors spanning eight different cancer types, we identify expression patterns associated with intratumoral EMP. Integrative analysis of these programs confirmed a high degree of diversity among tumors. These diverse programs are associated with combinations of various common regulatory mechanisms initiated from cues within the tumor microenvironment. We show that inferring regulatory features can inform effective therapeutics to restrict EMP.

Glutamine-fructose-6-phosphate transaminase 2 (GFPT2) is upregulated in breast epithelial-mesenchymal transition and responds to oxidative stress

Breast cancer cells that have undergone partial epithelial–mesenchymal transition (EMT) are believed to be more invasive than cells that have completed EMT. To study metabolic reprogramming in different mesenchymal states, we analyzed protein expression following EMT in the breast epithelial cell model D492 with single-shot LFQ supported by a SILAC proteomics approach. The D492 EMT cell model contains three cell lines: the epithelial D492 cells, the mesenchymal D492M cells, and a partial mesenchymal, tumorigenic variant of D492 that overexpresses the oncogene HER2. The analysis classified the D492 and D492M cells as basal-like and D492HER2 as claudin-low. Comparative analysis of D492 and D492M to tumorigenic D492HER2 differentiated metabolic markers of migration from those of invasion. Glutamine-fructose-6-phosphate transaminase 2 (GFPT2) was one of the top dysregulated enzymes in D492HER2. Gene expression analysis of the cancer genome atlas showed that GFPT2 expression was a characteristic of claudin-low breast cancer. siRNA-mediated knockdown of GFPT2 influenced the EMT marker vimentin and both cell growth and invasion in vitro and was accompanied by lowered metabolic flux through the hexosamine biosynthesis pathway (HBP). Knockdown of GFPT2 decreased cystathionine and sulfide:quinone oxidoreductase (SQOR) in the transsulfuration pathway that regulates H₂S production and mitochondrial homeostasis. Moreover, GFPT2 was within the regulation network of insulin and EGF, and its expression was regulated by reduced glutathione (GSH) and suppressed by the oxidative stress regulator GSK3-β. Our results demonstrate that GFPT2 controls growth and invasion in the D492 EMT model, is a marker for oxidative stress, and associated with poor prognosis in claudin-low breast cancer.

•

GFPT2 is upregulated following EMT.

•

GFPT2 is a marker for claudin-low breast cancer.

•

GFPT2 affects vimentin, cell proliferation, and cell invasion.

•

GFPT2 responds to oxidative stress.

•

GFPT2 is regulated by insulin and EGF.

The enhanced cell cycle related to the response to adjuvant therapy in pancreatic ductal adenocarcinoma

A major clinical challenge for treating patients with pancreatic ductal adenocarcinoma (PDAC) is identifying those that may benefit from adjuvant chemotherapy versus those that will not. Thus, there is a need for a robust and convenient biomarker for predicting chemotherapy response in PDAC patients. In this study, network inference was conducted by integrating the differentially expressed cell cycle signatures and target genes between the basal-like subtype and classical subtype of PDAC. As a result from this statistical analysis, two dominant cell cycle genes, RASAL2 and ASPM, were identified. Based on the expression levels of these two genes, we constructed a "Enhanced Cell Cycle" scoring system (ECC score). Patients were given an ECC score, and respectively divided into ECC-high and ECC-low groups. Survival, pathway enrichment, immune environment characteristics, and chemotherapy response analysis' were performed between the two groups in a total of 891 patients across 5 cohorts. ECC-high patients exhibited shortened recurrence-free survival (RFS) and overall survival (OS) rates. In addition, it was found that adjuvant chemotherapy could significantly improve the outcome of the ECC-high patients while ECC-low patients did not benefit from adjuvant chemotherapy. It was also found that there was less CD8+ T cell, natural killer (NK) cell, M1 macrophage, and plasma cell infiltration in ECC-high patients when compared to ECC-low patients. Also, the expression of CD73, an immune suppressor gene, and it's related hypoxia pathway were elevated in the ECC-high group when compared to the ECC-low group. In conclusion, this study showed that patients characterized as ECC-high not only had reduced RFS and OS rates, but were also more sensitive to adjuvant chemotherapy and could potentially be less sensitive to immune checkpoint inhibitors. Being able to characterize patients by these parameters would allow doctors to make more informed decisions on patient treatment regimens.

Proteomic and phosphoproteomic analyses identify liver-related signaling in retinal pigment epithelial cells during EMT

Epithelial-mesenchymal transition (EMT) of the retinal pigment epithelium (RPE) is associated with several blinding retinal diseases. Using proteomics and phosphoproteomics studies of human induced pluripotent stem cell-derived RPE monolayers with induced EMT, we capture kinase/phosphatase signaling cascades 1 h and 12 h after induction to better understand the pathways mediating RPE EMT. Induction by co-treatment with transforming growth factor β and tumor necrosis factor alpha (TGNF) or enzymatic dissociation perturbs signaling in many of the same pathways, with striking similarity in the respective phosphoproteomes at 1 h. Liver hyperplasia and hepatocyte growth factor (HGF)-MET signaling exhibit the highest overall enrichment. We also observe that HGF and epidermal growth factor signaling, two cooperative pathways inhibited by EMT induction, regulate the RPE transcriptional profile.

Proteomics and Phosphoproteomics Profiling of Drug-Addicted BRAFi-Resistant Melanoma Cells

Acquired resistance to MAPK inhibitors limits the clinical efficacy in melanoma treatment. We and others have recently shown that BRAF inhibitor (BRAFi)-resistant melanoma cells can develop a dependency on the therapeutic drugs to which they have acquired resistance, creating a vulnerability for these cells that can potentially be exploited in cancer treatment. In drug-addicted melanoma cells, it was shown that this induction of cell death was preceded by a specific ERK2-dependent phenotype switch; however, the underlying molecular mechanisms are largely lacking. To increase the molecular understanding of this drug dependency, we applied a mass spectrometry-based proteomic approach on BRAFi-resistant BRAFMUT 451Lu cells, in which ERK1, ERK2, and JUNB were silenced separately using CRISPR-Cas9. Inactivation of ERK2 and, to a lesser extent, JUNB prevents drug addiction in these melanoma cells, while, conversely, knockout of ERK1 fails to reverse this phenotype, showing a response similar to that of control cells. Our analysis reveals that ERK2 and JUNB share comparable proteome responses dominated by reactivation of cell division. Importantly, we find that EMT activation in drug-addicted melanoma cells upon drug withdrawal is affected by silencing ERK2 but not ERK1. Moreover, transcription factor (regulator) enrichment shows that PIR acts as an effector of ERK2 and phosphoproteome analysis reveals that silencing of ERK2 but not ERK1 leads to amplification of GSK3 kinase activity. Our results depict possible mechanisms of drug addiction in melanoma, which may provide a guide for therapeutic strategies in drug-resistant melanoma.

Human iPS-derived pre-epicardial cells direct cardiomyocyte aggregation expansion and organization in vitro

Epicardial formation is necessary for normal myocardial morphogenesis. Here, we show that differentiating hiPSC-derived lateral plate mesoderm with BMP4, RA and VEGF (BVR) can generate a premature form of epicardial cells (termed pre-epicardial cells, PECs) expressing WT1, TBX18, SEMA3D, and SCX within 7 days. BVR stimulation after Wnt inhibition of LPM demonstrates co-differentiation and spatial organization of PECs and cardiomyocytes (CMs) in a single 2D culture. Co-culture consolidates CMs into dense aggregates, which then form a connected beating syncytium with enhanced contractility and calcium handling; while PECs become more mature with significant upregulation of UPK1B, ITGA4, and ALDH1A2 expressions. Our study also demonstrates that PECs secrete IGF2 and stimulate CM proliferation in co-culture. Three-dimensional PEC-CM spheroid co-cultures form outer smooth muscle cell layers on cardiac micro-tissues with organized internal luminal structures. These characteristics suggest PECs could play a key role in enhancing tissue organization within engineered cardiac constructs in vitro.

The authors form pre-epicardial cells (PECs) from hiPSC-derived lateral plate mesoderm on treating with BMP4, RA and VEGF, and co-culture these PECs with cardiomyocytes, inducing cardiomyocyte aggregation, proliferation and network formation with more mature structures and improved beating/contractility.

Cytomegalovirus subverts macrophage identity

Cytomegaloviruses (CMVs) have co-evolved with their mammalian hosts for millions of years, leading to remarkable host specificity and high infection prevalence. Macrophages, which already populate barrier tissues in the embryo, are the predominant immune cells at potential CMV entry sites. Here we show that, upon CMV infection, macrophages undergo a morphological, immunophenotypic, and metabolic transformation process with features of stemness, altered migration, enhanced invasiveness, and provision of the cell cycle machinery for viral proliferation. This complex process depends on Wnt signaling and the transcription factor ZEB1. In pulmonary infection, mouse CMV primarily targets and reprograms alveolar macrophages, which alters lung physiology and facilitates primary CMV and secondary bacterial infection by attenuating the inflammatory response. Thus, CMV profoundly perturbs macrophage identity beyond established limits of plasticity and rewires specific differentiation processes, allowing viral spread and impairing innate tissue immunity.

Comprehensive Transcriptomic Analysis Reveals Prognostic Value of an EMT-Related Gene Signature in Colorectal Cancer

Lymph node metastasis (LNM) is closely related to the postoperative recurrence of colorectal cancer (CRC), and greatly affects patient survival. Conducting Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA), we found that the epithelial-mesenchymal transition (EMT) signaling pathway is the signaling pathway most relevant to the process of LNM. An EMT-related gene signature was identified from a discovery dataset obtained 489 patients using LIMMA and LASSO Cox methods. Six external independent dataset analyses including a total of 1,045 CRC patients and stratification analysis showed that EMT-related gene signature could sort out those high- and low-risk CRC patients accurately. Functional analysis and loss-of-function exploration in vitro and in vivo indicated that the EMT-related-signature-associated coding genes might play functional roles in the sophisticated regulation of CRC proliferation and metastasis. Prognostic nomograms integrating the EMT-related gene signature and clinicopathological risk factors were constructed for use as numerical prediction tools to assess clinical prognosis and clinical decision-makings. The comprehensive transcriptomic analysis in this article highlights the prognostic value of an EMT-related gene signature for postoperative disease recurrence in CRC patients and reveals a potential prognostic and therapeutic biomarker for CRC.

Differential molecular response of larynx cancer cell lines to combined VPA/CDDP treatment

Successful treatment of advanced larynx squamous cell carcinoma (LSCC) remains a challenge, mainly due to limited response to chemotherapy and the phenomenon of the drug resistance. Therefore, new chemotherapeutic solutions are needed. The aim of this study was to explore benefit of combined cisplatin (CDDP) and valproic acid (VPA) therapy in patients' derived LSCC cell lines. Cell viability assay was used to establish cellular response to the drug by isobolography followed by RNA sequencing (RNAseq) analysis. Danio rerio were used for in vivo studies. Depending on the cell line, we found that the combinations of drugs resulted in synergistic or antagonistic pharmacological interaction, which was accompanied by significant changes in genes expression profiles. The presented therapeutic scheme efficiently blocked tumor growth in an in vivo model, corresponding to the in vitro performed studies. Interestingly the RK5 cell line, upon the combined treatment acquired a molecular profile typically associated with epithelial to mesenchymal transition (EMT). Hence, our studies demonstrates that patient-specific personalized therapy of larynx cancer should be considered and the combination of cisplatin and valproic acid should be explored as a potential therapeutic strategy in the treatment of larynx cancer.

Bioengineering strategies to control epithelial-to-mesenchymal transition for studies of cardiac development and disease

Epithelial-to-mesenchymal transition (EMT) is a process that occurs in a wide range of tissues and environments, in response to numerous factors and conditions, and plays a critical role in development, disease, and regeneration. The process involves epithelia transitioning into a mobile state and becoming mesenchymal cells. The investigation of EMT processes has been important for understanding developmental biology and disease progression, enabling the advancement of treatment approaches for a variety of disorders such as cancer and myocardial infarction. More recently, tissue engineering efforts have also recognized the importance of controlling the EMT process. In this review, we provide an overview of the EMT process and the signaling pathways and factors that control it, followed by a discussion of bioengineering strategies to control EMT. Important biological, biomaterial, biochemical, and physical factors and properties that have been utilized to control EMT are described, as well as the studies that have investigated the modulation of EMT in tissue engineering and regenerative approaches in vivo, with a specific focus on the heart. Novel tools that can be used to characterize and assess EMT are discussed and finally, we close with a perspective on new bioengineering methods that have the potential to transform our ability to control EMT, ultimately leading to new therapies.

Development and validation of epithelial mesenchymal transition-related prognostic model for hepatocellular carcinoma

Epithelial cell transformation (EMT) plays an important role in the pathogenesis and metastasis of hepatocellular carcinoma (HCC). We aimed to establish a genetic risk model to evaluate HCC prognosis based on the expression levels of EMT-related genes. The data of HCC patients were collected from TCGA and ICGC databases. Gene expression differential analysis, univariate analysis, and lasso combined with stepwise Cox regression were used to construct the prognostic model. Kaplan-Meier curve, receiver operating characteristic (ROC) curve, calibration analysis, Harrell's concordance index (C-index), and decision curve analysis (DCA) were used to evaluate the predictive ability of the risk model or nomogram. GO and KEGG were used to analyze differently expressed EMT genes, or genes that directly or indirectly interact with the risk-associated genes. A 10-gene signature, including TSC2, ACTA2, SLC2A1, PGF, MYCN, PIK3R1, EOMES, BDNF, ZNF746, and TFDP3, was identified. Kaplan-Meier survival analysis showed a significant prognostic difference between high- and low-risk groups of patients. ROC curve analysis showed that the risk score model could effectively predict the 1-, 3-, and 5-year overall survival rates of patients with HCC. The nomogram showed a stronger predictive effect than clinical indicators. C-index, DCA, and calibration analysis demonstrated that the risk score and nomogram had high accuracy. The single sample gene set enrichment analysis results confirmed significant differences in the types of infiltrating immune cells between patients in the high- and low-risk groups. This study established a new prediction model of risk gene signature for predicting prognosis in patients with HCC, and provides a new molecular tool for the clinical evaluation of HCC prognosis.

From Proteomic Mapping to Invasion-Metastasis-Cascade Systemic Biomarkering and Targeted Drugging of Mutant BRAF-Dependent Human Cutaneous Melanomagenesis

Simple Summary

Despite the recent advances in human malignancy therapy, metastasis and chemoresistance remain the principal causes of cancer-derived deaths. Given the fatal forms of cutaneous metastatic melanoma, we herein employed primary (WM115) and metastatic (WM266-4) melanoma cells, both obtained from the same patient, to identify novel biomarkers and therapeutic agents. Through state-of-the-art technologies including deep proteome landscaping, immunofluorescence phenotyping, and drug toxicity screening, we were able to describe new molecular programs, oncogenic drivers, and drug regimens, controlling the invasion-metastasis cascade during BRAF^V600D-dependent melanomagenesis. It proved that proteomic navigation could foster the development of systemic biomarkering and targeted drugging for successful treatment of advanced disease.

Abstract

Melanoma is classified among the most notoriously aggressive human cancers. Despite the recent progress, due to its propensity for metastasis and resistance to therapy, novel biomarkers and oncogenic molecular drivers need to be promptly identified for metastatic melanoma. Hence, by employing nano liquid chromatography-tandem mass spectrometry deep proteomics technology, advanced bioinformatics algorithms, immunofluorescence, western blotting, wound healing protocols, molecular modeling programs, and MTT assays, we comparatively examined the respective proteomic contents of WM115 primary (n = 3955 proteins) and WM266-4 metastatic (n = 6681 proteins) melanoma cells. It proved that WM115 and WM266-4 cells have engaged hybrid epithelial-to-mesenchymal transition/mesenchymal-to-epithelial transition states, with TGF-β controlling their motility in vitro. They are characterized by different signatures of SOX-dependent neural crest-like stemness and distinct architectures of the cytoskeleton network. Multiple signaling pathways have already been activated from the primary melanoma stage, whereas HIF1α, the major hypoxia-inducible factor, can be exclusively observed in metastatic melanoma cells. Invasion-metastasis cascade-specific sub-routines of activated Caspase-3-triggered apoptosis and LC3B-II-dependent constitutive autophagy were also unveiled. Importantly, WM115 and WM266-4 cells exhibited diverse drug response profiles, with epirubicin holding considerable promise as a beneficial drug for metastatic melanoma clinical management. It is the proteome navigation that enables systemic biomarkering and targeted drugging to open new therapeutic windows for advanced disease.

Prognostic implications of an autophagy-based signature in colorectal cancer

BACKGROUND

The heterogeneity of colorectal cancer (CRC) poses a significant challenge to the precise treatment of patients. CRC has been divided into 4 consensus molecular subtypes (CMSs) with distinct biological and clinical characteristics, of which CMS4 has the mesenchymal identity and the highest relapse rate. Autophagy plays a vital role in CRC development and therapeutic response.

METHODS

The gene expression profiles collected from 6 datasets were applied to this study. Network analysis was applied to integrate the subtype-specific molecular modalities and autophagy signature to establish an autophagy-based prognostic signature for CRC (APSCRC).

RESULTS

Network analysis revealed that 6 prognostic autophagy genes (VAMP7, DLC1, FKBP1B, PEA15, PEX14, and DNAJB1) predominantly regulated the mesenchymal modalities of CRC. The APSCRC was constructed by these 6 core genes and applied for risk calculation. Patients were divided into high- and low-risk groups based on APSCRC score in all cohorts. Patients within the high-risk group showed an unfavorable prognosis. In multivariate analysis, the APSCRC remained an independent predictor of prognosis. Moreover, the APSCRC achieved higher prognostic power than commercialized multigene signatures.

CONCLUSIONS

We proposed and validated an autophagy-based signature, which is a promising prognostic biomarker of CRC patients. Further prospective studies are warranted to test and validate its efficiency for clinical application.

Nanotopography as Artificial Microenvironment for Accurate Visualization of Metastasis Development via Simulation of ECM Dynamics

Metastatic progression is mediated by complex interactions between deregulated extracellular matrix (ECM) and cancer cells and remains a major challenge in cancer management. To investigate the role of ECM dynamics in promoting metastasis development, we developed an artificial microenvironment (AME) platform comprised of nanodot arrays of increasing diameter. Cells cultured on the platform showed increasing signs of mesenchymal-like cell transition as AME diameter increased, suggesting accurate simulation of ECM-mediated gene regulation. Gene expression was analyzed to determine genes significant to transition, which were then used to select appropriate small molecule drugs for time course treatments. Our results suggest that the platform can identify critical target genes as well as possible drug candidates. Overall, the AME platform allows for the study of intricate ECM-induced gene expression trends across metastasis development that would otherwise be difficult to visualize in vivo and may open new avenues toward successful personalized cancer management.

DIscBIO: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics

The growing attention toward the benefits of single-cell RNA sequencing (scRNA-seq) is leading to a myriad of computational packages for the analysis of different aspects of scRNA-seq data. For researchers without advanced programing skills, it is very challenging to combine several packages in order to perform the desired analysis in a simple and reproducible way. Here we present DIscBIO, an open-source, multi-algorithmic pipeline for easy, efficient and reproducible analysis of cellular sub-populations at the transcriptomic level. The pipeline integrates multiple scRNA-seq packages and allows biomarker discovery with decision trees and gene enrichment analysis in a network context using single-cell sequencing read counts through clustering and differential analysis. DIscBIO is freely available as an R package. It can be run either in command-line mode or through a user-friendly computational pipeline using Jupyter notebooks. We showcase all pipeline features using two scRNA-seq datasets. The first dataset consists of circulating tumor cells from patients with breast cancer. The second one is a cell cycle regulation dataset in myxoid liposarcoma. All analyses are available as notebooks that integrate in a sequential narrative R code with explanatory text and output data and images. R users can use the notebooks to understand the different steps of the pipeline and will guide them to explore their scRNA-seq data. We also provide a cloud version using Binder that allows the execution of the pipeline without the need of downloading R, Jupyter or any of the packages used by the pipeline. The cloud version can serve as a tutorial for training purposes, especially for those that are not R users or have limited programing skills. However, in order to do meaningful scRNA-seq analyses, all users will need to understand the implemented methods and their possible options and limitations.

Mutational drivers of cancer cell migration and invasion

Genomic instability and mutations underlie the hallmarks of cancer-genetic alterations determine cancer cell fate by affecting cell proliferation, apoptosis and immune response, and increasing data show that mutations are involved in metastasis, a crucial event in cancer progression and a life-threatening problem in cancer patients. Invasion is the first step in the metastatic cascade, when tumour cells acquire the ability to move, penetrate into the surrounding tissue and enter lymphatic and blood vessels in order to disseminate. A role for genetic alterations in invasion is not universally accepted, with sceptics arguing that cellular motility is related only to external factors such as hypoxia, chemoattractants and the rigidity of the extracellular matrix. However, increasing evidence shows that mutations might trigger and accelerate the migration and invasion of different types of cancer cells. In this review, we summarise data from published literature on the effect of chromosomal instability and genetic mutations on cancer cell migration and invasion.

Epigenetic targeting of neuropilin-1 prevents bypass signaling in drug-resistant breast cancer

Human epidermal growth factor receptor 2 (HER2)-amplified breast cancers are treated using targeted antibodies and kinase inhibitors, but resistance to these therapies leads to systemic tumor recurrence of metastatic disease. Herein, we conducted gene expression analyses of HER2 kinase inhibitor-resistant cell lines as compared to their drug-sensitive counterparts. These data demonstrate the induction of epithelial-mesenchymal transition (EMT), which included enhanced expression of fibroblast growth factor receptor 1 (FGFR1) and axonal guidance molecules known as neuropilins (NRPs). Immunoprecipitation of FGFR1 coupled with mass spectroscopy indicated that FGFR1 forms a physical complex with NRPs, which is enhanced upon induction of EMT. Confocal imaging revealed that FGFR1 and NRP1 predominantly interact throughout the cytoplasm. Along these lines, short hairpin RNA-mediated depletion of NRP1, but not the use of NRP1-blocking antibodies, inhibited FGFR signaling and reduced tumor cell growth in vitro and in vivo. Our results further indicate that NRP1 upregulation during EMT is mediated via binding of the chromatin reader protein, bromodomain containing 4 (BRD4) in the NRP1 proximal promoter region. Pharmacological inhibition of BRD4 decreased NRP1 expression and ablated FGF-mediated tumor cell growth. Overall, our studies indicate that NRPs facilitate aberrant growth factor signaling during EMT-associated drug resistance and metastasis. Pharmacological combination of epigenetic modulators with FGFR-targeted kinase inhibitors may provide improved outcomes for breast cancer patients with drug-resistant metastatic disease.

EMTome: a resource for pan-cancer analysis of epithelial-mesenchymal transition genes and signatures

BACKGROUND

The epithelial-mesenchymal transition (EMT) enables dissociation of tumour cells from the primary tumour mass, invasion through the extracellular matrix, intravasation into blood vessels and colonisation of distant organs. Cells that revert to the epithelial state via the mesenchymal-epithelial transition cause metastases, the primary cause of death in cancer patients. EMT also empowers cancer cells with stem-cell properties and induces resistance to chemotherapeutic drugs. Understanding the driving factors of EMT is critical for the development of effective therapeutic interventions.

METHODS

This manuscript describes the generation of a database containing EMT gene signatures derived from cell lines, patient-derived xenografts and patient studies across cancer types and multiomics data and the creation of a web-based portal to provide a comprehensive analysis resource.

RESULTS

EMTome incorporates (i) EMT gene signatures; (ii) EMT-related genes with multiomics features across different cancer types; (iii) interactomes of EMT-related genes (miRNAs, transcription factors, and proteins); (iv) immune profiles identified from The Cancer Genome Atlas (TCGA) cohorts by exploring transcriptomics, epigenomics, and proteomics, and drug sensitivity and (iv) clinical outcomes of cancer cohorts linked to EMT gene signatures.

CONCLUSION

The web-based EMTome portal is a resource for primary and metastatic tumour research publicly available at www.emtome.org .

A Blood-based Assay for Assessment of Tumor Mutational Burden in First-line Metastatic NSCLC Treatment: Results from the MYSTIC Study

PURPOSE

Tumor mutational burden (TMB) has been shown to be predictive of survival benefit in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors. Measuring TMB in the blood (bTMB) using circulating cell-free tumor DNA (ctDNA) offers practical advantages compared with TMB measurement in tissue (tTMB); however, there is a need for validated assays and identification of optimal cutoffs. We describe the analytic validation of a new bTMB algorithm and its clinical utility using data from the phase III MYSTIC trial.

PATIENTS AND METHODS

The dataset used for the clinical validation was from MYSTIC, which evaluated first-line durvalumab (anti-PD-L1 antibody) ± tremelimumab (anticytotoxic T-lymphocyte-associated antigen-4 antibody) or chemotherapy for metastatic NSCLC. bTMB and tTMB were evaluated using the GuardantOMNI and FoundationOne CDx assays, respectively. A Cox proportional hazards model and minimal P value cross-validation approach were used to identify the optimal bTMB cutoff.

RESULTS

In MYSTIC, somatic mutations could be detected in ctDNA extracted from plasma samples in a majority of patients, allowing subsequent calculation of bTMB. The success rate for obtaining valid TMB scores was higher for bTMB (809/1,001; 81%) than for tTMB (460/735; 63%). Minimal P value cross-validation analysis confirmed the selection of bTMB ≥20 mutations per megabase (mut/Mb) as the optimal cutoff for clinical benefit with durvalumab + tremelimumab.

CONCLUSIONS

Our study demonstrates the feasibility, accuracy, and reproducibility of the GuardantOMNI ctDNA platform for quantifying bTMB from plasma samples. Using the new bTMB algorithm and an optimal bTMB cutoff of ≥20 mut/Mb, high bTMB was predictive of clinical benefit with durvalumab + tremelimumab versus chemotherapy.