Apigenin and Rutaecarpine reduce the burden of cellular senescence in bone marrow stromal stem cells.

Introduction: Osteoporosis is a systemic age-related disease characterized by reduced bone mass and microstructure deterioration, leading to increased risk of bone fragility fractures. Osteoporosis is a worldwide major health care problem and there is a need for preventive approaches. Methods and results: Apigenin and Rutaecarpine are plant-derived antioxidants identified through functional screen of a natural product library (143 compounds) as enhancers of osteoblastic differentiation of human bone marrow stromal stem cells (hBMSCs). Global gene expression profiling and Western blot analysis revealed activation of several intra-cellular signaling pathways including focal adhesion kinase (FAK) and TGFß. Pharmacological inhibition of FAK using PF-573228 (5 µM) and TGFß using SB505124 (1µM), diminished Apigenin- and Rutaecarpine-induced osteoblast differentiation. In vitro treatment with Apigenin and Rutaecarpine, of primary hBMSCs obtained from elderly female patients enhanced osteoblast differentiation compared with primary hBMSCs obtained from young female donors. Ex-vivo treatment with Apigenin and Rutaecarpine of organotypic embryonic chick-femur culture significantly increased bone volume and cortical thickness compared to control as estimated by µCT-scanning. Discussion: Our data revealed that Apigenin and Rutaecarpine enhance osteoblastic differentiation, bone formation, and reduce the age-related effects of hBMSCs. Therefore, Apigenin and Rutaecarpine cellular treatment represent a potential strategy for maintaining hBMSCs health during aging and osteoporosis.

Long non-coding RNA AC099850.4 correlates with advanced disease state and predicts worse prognosis in triple-negative breast cancer.

Our understanding of the function of long non-coding RNAs (lncRNAs) in health and disease states has evolved over the past decades due to the many advances in genome research. In the current study, we characterized the lncRNA transcriptome enriched in triple-negative breast cancer (TNBC, n = 42) and estrogen receptor (ER+, n = 42) breast cancer compared to normal breast tissue (n = 56). Given the aggressive nature of TNBC, our data revealed selective enrichment of 57 lncRNAs in TNBC. Among those, AC099850.4 lncRNA was chosen for further investigation where it exhibited elevated expression, which was further confirmed in a second TNBC cohort (n = 360) where its expression correlated with a worse prognosis. Network analysis of AC099850.4high TNBC highlighted enrichment in functional categories indicative of cell cycle activation and mitosis. Ingenuity pathway analysis on the differentially expressed genes in AC099850.4high TNBC revealed the activation of the canonical kinetochore metaphase signaling pathway, pyridoxal 5'-phosphate salvage pathway, and salvage pathways of pyrimidine ribonucleotides. Additionally, upstream regulator analysis predicted the activation of several upstream regulator networks including CKAP2L, FOXM1, RABL6, PCLAF, and MITF, while upstream regulator networks of TP53, NUPR1, TRPS1, and CDKN1A were suppressed. Interestingly, elevated expression of AC099850.4 correlated with worse short-term relapse-free survival (log-rank p = 0.01). Taken together, our data are the first to reveal AC099850.4 as an unfavorable prognostic marker in TNBC, associated with more aggressive clinicopathological features, and suggest its potential utilization as a prognostic biomarker and therapeutic target in TNBC.

Therapeutic targeting of the TPX2/TTK network in colorectal cancer.

BACKGROUND: While the increased screening, changes in lifestyle, and recent advances in treatment regimen have decreased colorectal cancer (CRC) mortality, metastatic disease and recurrence remains a major clinical challenge. In the era of precision medicine, the identification of actionable novel therapeutic targets could ultimately offer an alternative treatment strategy for CRC. METHODS: RNA-Seq was conducted using the illumina platform, while bioinformatics analyses were conducted using CLC genomics workbench and iDEP.951. Colony forming unit, flow cytometry, and fluorescent microscopy were used to assess cell proliferation, cell cycle distribution, and cell death, respectively. The growth potential of CRC cells under 3-dimensional (3D) conditions was assessed using Matrigel. STRING database (v11.5) and Ingenuity Pathway Analysis (IPA) tool were used for network and pathway analyses. CRISPR-Cas9 perturbational effects database was used to identify potential therapeutic targets for CRC, through integration with gene-drug interaction database. Structural modeling and molecular docking were used to assess the interaction between candidate drugs and their targets. RESULTS: In the current study, we investigated the therapeutic potential of targeting TPX2, TTK, DDX39A, and LRP8, commonly upregulated genes in CRC identified through differential expression analysis in CRC and adjacent non-cancerous tissue. Targeted depletion of TPX2 and TTK impaired CRC proliferation, cell cycle progression, and organoid formation under 3D culture conditions, while suppression of DDX39A and LRP8 had modest effects on CRC colony formation. Differential expression analysis and bioinformatics on TPX2 and TTK-deficient cells identified cell cycle regulation as the hallmark associated with loss of TPX2 and TTK. Elevated expression of TPX2 and TTK correlated with an oncogenic state in tumor tissue from patients with colon adenocarcinoma, thus corroborating an oncogenic role for the TPX2/TTK network in the pathogenesis of CRC. Gene set enrichment and pathway analysis of TPX2high/TTKhigh CRC identified numerous additional gene targets as integral components of the TPX2/TTK network. Integration of TPX2/TTK enriched network with CRISPR-Cas9 functional screen data identified numerous novel dependencies for CRC. Additionally, gene-drug interaction analysis identified several druggable gene targets enriched in the TPX2/TTK network, including AURKA, TOP2A, CDK1, BIRC5, and many others. CONCLUSIONS: Our data has implicated an essential role for TPX2 and TTK in CRC pathogenesis and identified numerous potential therapeutic targets and their drug interactions, suggesting their potential clinical use as a novel therapeutic strategy for patients with CRC. Video Abstract.

Transcriptome profiling and network enrichment analyses identify subtype-specific therapeutic gene targets for breast cancer and their microRNA regulatory networks.

Previous studies have suggested that breast cancer (BC) from the Middle East and North Africa (MENA) is presented at younger age with advanced tumor stage, indicating underlying biological differences. Given the scant transcriptomic data on BC from the MENA region and to better understand the biology of this disease, we performed mRNA and microRNA (miRNA) transcriptomic profiling on a local cohort of BC (n = 96) from Qatar. Our data revealed the differentially expressed genes and miRNAs as function of BC molecular subtypes (HR+, HER2+, HER2+HR+, and TNBC), tumor grade (GIII vs GI-II), patients' age (young (≤40) vs old (>40)), and ethnicity (MENA vs non-MENA). Our profiling data revealed close similarity between TNBC and HER2+, while the transcriptome of HER2+HR+ tumor was resemblant of that from HR+ tumors. Network analysis identified complex miRNA-mRNA regulatory networks in each BC molecular subtype, in high vs low grade tumors, in tumors from young vs old patients, and in tumors from MENA vs non-MENA, thus implicating miRNA-mediated gene regulation as an essential mechanism in shaping the transcriptome of BC. Integration of our transcriptomic data with CRISPR-Cas9 functional screen data and the OncoKB database identified numerous dependencies and therapeutic vulnerabilities in each BC molecular subtype, while CDC123 was functionally validated as potential therapeutic target for TNBC. Cox regression survival analyses identified mRNA and miRNA-based signatures predicative of worse and better relapse free survival (RFS), which were validated in larger BC cohorts. Our data provides comprehensive transcriptomic profiling and unraveled the miRNA-mRNA regulatory networks in BC patients from the region and identified novel actionable gene targets, employing integrated approach. Findings from the current study have potential implications to improve the current standard-of-care for BC from the MENA as well as patients from other ethnicities.

Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes.

Breast cancer (BC) is a heterogeneous disease, which is primarily classified according to hormone receptors and HER2 expression. Despite the many advances in BC diagnosis and management, the identification of novel actionable therapeutic targets expressed by cancerous cells has always been a daunting task due to the large heterogeneity of the disease and the presence of non-cancerous cells (i.e., immune cells and stromal cells) within the tumor microenvironment. In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER+), HER2+, ER+HER2+, and triple-negative BC (TNBC) subtypes from a total of 49,899 single cells' publicly available transcriptomic data derived from 26 BC patients. Restricting the analysis to EPCAM+Lin- tumor epithelial cells, we identified the enriched gene sets in each BC molecular subtype. Integration of single-cell transcriptomic with CRISPR-Cas9 functional screen data identified 13 potential therapeutic targets for ER+, 44 potential therapeutic targets for HER2+, and 29 potential therapeutic targets for TNBC. Interestingly, several of the identified therapeutic targets outperformed the current standard of care for each BC subtype. Given the aggressive nature and lack of targeted therapies for TNBC, elevated expression of ENO1, FDPS, CCT6A, TUBB2A, and PGK1 predicted worse relapse-free survival (RFS) in basal BC (n = 442), while elevated expression of ENO1, FDPS, CCT6A, and PGK1 was observed in the most aggressive BLIS TNBC subtype. Mechanistically, targeted depletion of ENO1 and FDPS halted TNBC cell proliferation, colony formation, and organoid tumor growth under 3-dimensional conditions and increased cell death, suggesting their potential use as novel therapeutic targets for TNBC. Differential expression and gene set enrichment analysis in TNBC revealed enrichment in the cycle and mitosis functional categories in FDPShigh, while ENO1high was associated with numerous functional categories, including cell cycle, glycolysis, and ATP metabolic processes. Taken together, our data are the first to unravel the unique gene signatures and to identify novel dependencies and therapeutic vulnerabilities for each BC molecular subtype, thus setting the foundation for the future development of more effective targeted therapies for BC.

Reciprocal interplays between MicroRNAs and pluripotency transcription factors in dictating stemness features in human cancers.

The interplay between microRNAs (miRNAs) and pluripotency transcription factors (TFs) orchestrates the acquisition of cancer stem cell (CSC) features during the course of malignant transformation, rendering them essential cancer cell dependencies and therapeutic vulnerabilities. In this review, we discuss emerging themes in tumor heterogeneity, including the clonal evolution and the CSC models and their implications in resistance to cancer therapies, and then provide thorough coverage on the roles played by key TFs in maintaining normal and malignant stem cell pluripotency and plasticity. In addition, we discuss the reciprocal interactions between miRNAs and MYC, OCT4, NANOG, SOX2, and KLF4 pluripotency TFs and their contributions to tumorigenesis. We provide our view on the potential to interfere with key miRNA-TF networks through the use of RNA-based therapeutics as single agents or in combination with other therapeutic strategies, to abrogate the CSC state and render tumor cells more responsive to standard and targeted therapies.

Identification of a Gene Panel Predictive of Triple-Negative Breast Cancer Response to Neoadjuvant Chemotherapy Employing Transcriptomic and Functional Validation.

Triple-negative breast cancer (TNBC) patients exhibiting pathological complete response (pCR) have better clinical outcomes compared to those with residual disease (RD). Therefore, robust biomarkers that can predict pCR may help with triage and resource prioritization in patients with TNBC. Herein, we identified a gene panel predictive of RD and pCR in TNBC from the discovery (n = 90) treatment-naive tumor transcriptomic data. Eight RD-derived genes were identified as TNBC-essential genes, which were highly predicative of overall survival (OS) and relapse-free survival (RFS) in an additional cohort of basal breast cancer (n = 442). Mechanistically, targeted depletion of the eight genes reduced the proliferation potential of TNBC cell models, while most remarkable effects were for combined SLC39A7, TIMM13, BANF1, and MVD knockdown in conjunction with doxorubicin. Orthogonal partial least squares-discriminant analysis (OPLS-DA) and receiver operating characteristic curve (ROC) analyses revealed significant predictive power for the identified gene panels with an area under the curve (AUC) of 0.75 for the validation cohort (n = 50) to discriminate RD from pCR. Protein-Protein Interaction (PPI) network analysis of the pCR-derived gene signature identified an 87-immune gene signature highly predictive of pCR, which correlated with better OS, RFS, and distant-metastasis-free survival (DMFS) in an independent cohort of basal and, to a lesser extent, HER2+ breast cancer. Our data have identified gene signatures predicative of RD and pCR in TNBC with potential clinical implications.

LncRNA-Based Classification of Triple Negative Breast Cancer Revealed Inherent Tumor Heterogeneity and Vulnerabilities.

Triple negative breast cancer (TNBC) represents a diverse group of cancers based on their gene expression profiles. While the current mRNA-based classification of TNBC has contributed to our understanding of the heterogeneity of this disease, whether such heterogeneity can be resolved employing a long noncoding RNA (lncRNA) transcriptome has not been established thus far. Herein, we used iterative clustering and guide-gene selection (ICGS) and uniform manifold approximation and projection (UMAP) dimensionality reduction analysis on a large cohort of TNBC transcriptomic data (TNBC = 360, normal = 88) and classified TNBC into four main clusters: LINC00511-enriched, LINC00393-enriched, FIRRE-enriched, and normal tissue-like. Delving into associated gene expression profiles revealed remarkable differences in canonical, casual, upstream, and functional categories among different lncRNA-derived TNBC clusters, suggesting functional consequences for altered lncRNA expression. Correlation and survival analysis comparing mRNA- and lncRNA-based clustering revealed similarities and differences between the two classification approaches. To provide insight into the potential role of the identified lncRNAs in TNBC biology, CRISPR-Cas9 mediated LINC00511 promoter deletion reduced colony formation and enhanced the sensitivity of TNBC cells to paclitaxel, suggesting a role for LINC00511 in conferring tumorigenicity and resistance to therapy. Our data revealed a novel lncRNA-based classification of TNBC and suggested their potential utilization as disease biomarkers and therapeutic targets.

Long non-coding RNA and RNA-binding protein interactions in cancer: Experimental and machine learning approaches.

Understanding the complex and specific roles played by non-coding RNAs (ncRNAs), which comprise the bulk of the genome, is important for understanding virtually every hallmark of cancer. This large group of molecules plays pivotal roles in key regulatory mechanisms in various cellular processes. Regulatory mechanisms, mediated by long non-coding RNA (lncRNA) and RNA-binding protein (RBP) interactions, are well documented in several types of cancer. Their effects are enabled through networks affecting lncRNA and RBP stability, RNA metabolism including N6-methyladenosine (m6A) and alternative splicing, subcellular localization, and numerous other mechanisms involved in cancer. In this review, we discuss the reciprocal interplay between lncRNAs and RBPs and their involvement in epigenetic regulation via histone modifications, as well as their key role in resistance to cancer therapy. Other aspects of RBPs including their structural domains, provide a deeper knowledge on how lncRNAs and RBPs interact and exert their biological functions. In addition, current state-of-the-art knowledge, facilitated by machine and deep learning approaches, unravels such interactions in better details to further enhance our understanding of the field, and the potential to harness RNA-based therapeutics as an alternative treatment modality for cancer are discussed.

Transcriptional landscape associated with TNBC resistance to neoadjuvant chemotherapy revealed by single-cell RNA-seq.

Triple-negative breast cancer (TNBC) resistance to neoadjuvant chemotherapy (NAC) represents a major clinical challenge; therefore, delineating tumor heterogeneity can provide novel insight into resistance mechanisms and potential therapeutic targets. Herein, we identified the transcriptional landscape associated with TNBC resistance to NAC at the single-cell level by analyzing publicly available transcriptome data from more than 5,000 single cells derived from four extinction (responders) and four persistence (non-responders) patients, revealing remarkable tumor heterogeneity. Employing iterative clustering and guide-gene selection (ICGS) and uniform manifold approximation and projection (UMAP), we classified TNBC single cells into several clusters based on their distinct gene signatures. The presence of clusters indicative of immune cell activation was a hallmark of the extinction group pre-NAC, while post NAC, the extinction tissue consisted mostly of breast, omental fat, and fibroblasts. The persistent gene signatures of pre-NAC resembled the gene signature of lung epithelial, mammary, and salivary glands and acute myeloid leukemia blast cells, which were associated with enhanced cellular movement and activation of FOXM1, NOTCH1, and MYC and suppression of tumor necrosis factor (TNF) and IFNG mechanistic networks. Multivariate survival analysis identified persistence-derived three-gene signature (KIF5BhighHLA-ClowIGHG2low) predictive of relapse-free survival (hazard ratio [HR]: 2.2 [1.6-3.2, p < 0.0001]) in a second cohort of 360 TNBC patients. Mechanistically, loss of function of several upregulated genes in the persistent group (BYSL, FDPS, ENO1, MED20, MRPL9, MRPL37, NDUFB11, PMVK, MYC, and GSTP1) inhibited MDA-MB-231 and BT-549 TNBC models' colony-forming unit (CFU) potential and enhanced their sensitivity to paclitaxel. Our data unraveled the transcriptional portrait associated with NAC resistance, identified several key genes, and suggested their potential utilization as prognostic markers and therapeutic targets in TNBC.

Transcriptional alterations of protein coding and noncoding RNAs in triple negative breast cancer in response to DNA methyltransferases inhibition.

BACKGROUND: DNA methylation plays a crucial role in multiple cellular processes such as gene regulation, chromatin stability, and genetic imprinting. In mammals, DNA methylation is achieved by DNA methyltransferases (DNMTs). A number of studies have associated alterations in DNMT activity to tumorigenesis; however, the exact role of DNMTs in shaping the genome in triple negative breast cancer (TNBC) is still being unraveled. METHODS: In the current study, we employed two DNMT inhibitors (Decitabine and 5-Azacytidine), two TNBC models (MDA-MB-231 and BT-549) and whole transcriptome RNA-Seq and characterized the transcriptional alterations associated with DNMT inhibition. Colony forming unit (CFU), flow cytometry, and fluorescent microscopy were used to assess cell proliferation, cell cycle distribution, and cell death, respectively. Ingenuity pathway analysis (IPA) was used for network and pathway analyses. RESULTS: Remarkably, DNMT inhibition induced the expression of genes involved in endoplasmic reticulum response to stress, response to unfolder protein, as well as cobalamin metabolic processes. In contrast, suppression of cellular processes related to cell cycle and mitosis were hallmarks of DNMT inhibition. Concordantly, DNMT inhibition led to significant inhibition of TNBC cell proliferation, G2-M cell cycle arrest and induction of cell death. Mechanistically, DNMT inhibition activated TP53, NUPR1, and NFkB (complex) networks, while RARA, RABL6, ESR1, FOXM1, and ERBB2 networks were suppressed. Our data also identified the long noncoding RNA (lncRNA) transcriptional portrait associated with DNMT inhibition and identified 25 commonly upregulated and 60 commonly downregulated lncRNAs in response to Decitabine and 5-Azacytidinec treatment in both TNBC models. TPT1-AS1 was the most highly induced (6.3 FC), while MALAT1 was the most highly suppressed (- 7.0 FC) lncRNA in response to DNMT inhibition. CONCLUSIONS: Taken together, our data provides a comprehensive view of transcriptome alterations in the coding and noncoding transcriptome in TNBC in response to DNMT inhibition.

Epigenetic regulation of triple negative breast cancer (TNBC) by TGF-ß signaling.

TGFß signaling plays crucial role during development and cancer, however the role for TGFß signaling in regulating the noncoding part of the human genome in triple negative breast cancer (TNBC) is still being unraveled. Herein, we provide the transcriptional landscape of TNBC in response to TGFß activation and subsequent inhibition employing SB431542, selective TGFß1 Receptor ALK5 Inhibitor. Our data revealed 72 commonly upregulated [fold change (FC) ≥ 2.0], including PLAU, TPM1, TAGLN, COL1A1, TGFBI, and SNAI1, and 53 downregulated (FC ≤ 2.0) protein coding genes in BT-549 and MDA-MB-231 models in response to TGFß1 activation. Alignment to the geocode (V33) identified 41 upregulated (FC ≥ 2.0) and 22 downregulated (FC ≤ 2.0) long non-coding RNA (lncRNA) in response to TGFß1 activation, which were inhibited by concurrent treatment with SB431542. To place our data from the in vitro models into their clinical context, we identified AC015909.1, AC013451.1, CYP1B1-AS1, AC004862.1, LINC01824, AL138828.1, B4GALT1-AS1, AL353751.1, AC090826.3, AC104695.4, ADORA2A-AS1, PTPRG-AS1, LINC01943, AC026954.3, TPM1-AS, ZFPM2-AS1, AC007362.1, AC112721.2, MALAT1, AL513314.2, AC112721.1, AC010343.3, LINC01711, and MAP3K2-DT lncRNA expression to positively correlate with TGFß1 expression in a cohort of 360 TNBC patients. To provide mechanistic insight into lncRNA regulation by TGFß signaling, SMAD2/3 ChIp-Seq data from BT-549 TNBC model retrieved from Gene Expression Omnibus (GEO) revealed direct binding of SMAD2/SMAD3 to the promoter of AC112721.1, AC112721.2, MALAT1, HHIP-AS1, LINC00472, and SLC7A11, suggesting their direct regulation by TGFß1/SMAD2/SMAD3 pathway. Interestingly, AC112721.1, AC112721.2 exhibited higher expression in TNBC compared to normal breast tissue suggesting a possible role for those lncRNA in TNBC biology. Our miRNA analysis in the BT-549 model in response to exogenous TGFB1 revealed several affected miRNAs (2.0 ≤ FC ≤ 2.0), whose expression pattern was reversed in the presence of SB431542, suggesting those miRNA as plausible targets for TGFß regulation. In particular, we observed hsa-miR-1275 to be downregulated in response to TGFB1 which was highly predicted to regulate PCDH1, FIBCD1, FXYD7, GDNF, STC1, EDN1, ZSWIM4, FGF1, PPP1R9B, NUAK1, PALM2AKAP2, IGFL3, and SPOCK1 whose expression were upregulated in response to TGFß1 stimulus. On the other hand, hsa-miR-181b-5p was among the top upregulated miRNAs in response to TGFB1, which is also predicted to regulate CDKN1B, TNFRSF11B, SIM1, and ARSJ in the BT-549 model. Taken together, our data is the first to provide such in depth analysis of lncRNA and miRNA epigenetic changes in response to TGFß signaling in TNBC.

Molecular subtyping and functional validation of TTK, TPX2, UBE2C, and LRP8 in sensitivity of TNBC to paclitaxel.

Triple-negative breast cancer (TNBC) patients exhibit variable responses to chemotherapy, suggesting an underlying molecular heterogeneity. In the current study, we analyzed publicly available transcriptome data from 360 TNBC and 88 normal breast tissues, which revealed activation of nucleosome and cell cycle as the hallmarks of TNBC. Mechanistic network analysis identified activation of FOXM1 and ERBB2, and suppression of TP53 and NURP1 networks in TNBC. Employing Iterative Clustering and Guide-gene Selection (ICGS), Uniform Manifold Approximation and Projection (UMAP), and dimensionality reduction analyses, we classified TNBC into seven molecular subtypes, each exhibiting a unique molecular signature, including immune infiltration (CD19, CD8, and macrophages) and mesenchymal signature, which correlated with variable disease outcomes in a larger cohort (1,070) of BC. Mechanistically, depletion of TTK, TPX2, UBE2C, CDCA7, MELK, NFE2L3, DDX39A, and LRP8 led to substantial inhibition of colony formation of TNBC models, which was further enhanced in the presence of paclitaxel. Our data provide novel insights into the molecular heterogeneity of TNBC and identified TTK, TPX2, UBE2C, and LRP8 as main drivers of TNBC tumorigenesis.

Single-cell long noncoding RNA (lncRNA) transcriptome implicates MALAT1 in triple-negative breast cancer (TNBC) resistance to neoadjuvant chemotherapy.

Cumulative evidence suggests added benefit for neoadjuvant chemotherapy (NAC) in a subset of triple-negative breast cancer (TNBC) patients. Herein we identified the long noncoding RNA (lncRNA) transcriptional landscape associated with TNBC resistance to NAC, employing 1758 single cells from three extinction and three persistence TNBC patients. Using Iterative Clustering and Guide-gene Selection (ICGS) and uniform manifold approximation and projection (UMAP) dimensionality reduction analysis, we observed single cells derived from each patient to largely cluster together. Comparing the lncRNA transcriptome from single cells through the course of NAC treatment revealed minimal overlap based on lncRNA transcriptome, suggesting substantial effects of NAC on lncRNA transcription. The differential analysis revealed upregulation of 202 and downregulation of 19 lncRNAs in the persistence group, including upregulation of five different transcripts encoding for the MALAT1 lncRNA. CRISPR/Cas9-mediated MALAT1 promoter deletion in BT-549 TNBC model enhanced sensitivity to paclitaxel and doxorubicin, suggesting a role for MALAT1 in conferring resistance. Mechanistically, whole transcriptome analysis of MALAT1-KO cells revealed multiple affected mechanistic networks as well as oxidative phosphorylation canonical and angiogenesis functional category. Interestingly, lncRNA profiling of MALAT1-depleted TNBC also revealed a number of altered lncRNAs in response to MALAT1 deletion, suggesting a reciprocal relationship between MALAT1 and a number of lncRNAs, including NEAT1, USP3-AS1, and LINC-PINT, in TNBC. Elevated expression of MALAT1, USP3-AS1, and LINC-PINT correlated with worse clinical outcomes in BC patients. Our data revealed the lncRNA transactional portrait and highlighted a complex regulatory network orchestrated by MALAT1 in the context of TNBC resistance to NAC therapy.

Single-Cell Transcriptome Analysis Highlights a Role for Neutrophils and Inflammatory Macrophages in the Pathogenesis of Severe COVID-19.

Cumulative data link cytokine storms with coronavirus disease 2019 (COVID-19) severity. The precise identification of immune cell subsets in bronchoalveolar lavage (BAL) and their correlation with COVID-19 disease severity are currently being unraveled. Herein, we employed iterative clustering and guide-gene selection 2 (ICGS2) as well as uniform manifold approximation and projection (UMAP) dimensionality reduction computational algorithms to decipher the complex immune and cellular composition of BAL, using publicly available datasets from a total of 68,873 single cells derived from two healthy subjects, three patients with mild COVID-19, and five patients with severe COVID-19. Our analysis revealed the presence of neutrophils and macrophage cluster-1 as a hallmark of severe COVID-19. Among the identified gene signatures, IFITM2, IFITM1, H3F3B, SAT1, and S100A8 gene signatures were highly associated with neutrophils, while CCL8, CCL3, CCL2, KLF6, and SPP1 were associated with macrophage cluster-1 in severe-COVID-19 patients. Interestingly, although macrophages were also present in healthy subjects and patients with mild COVID-19, they had different gene signatures, indicative of interstitial and cluster-0 macrophage (i.e., FABP4, APOC1, APOE, C1QB, and NURP1). Additionally, MALAT1, NEAT1, and SNGH25 were downregulated in patients with mild and severe COVID-19. Interferon signaling, FCγ receptor-mediated phagocytosis, IL17, and Tec kinase canonical pathways were enriched in patients with severe COVID-19, while PD-1 and PDL-1 pathways were suppressed. A number of upstream regulators (IFNG, PRL, TLR7, PRL, TGM2, TLR9, IL1B, TNF, NFkB, IL1A, STAT3, CCL5, and others) were also enriched in BAL cells from severe COVID-19-affected patients compared to those from patients with mild COVID-19. Further analyses revealed genes associated with the inflammatory response and chemotaxis of myeloid cells, phagocytes, and granulocytes, among the top activated functional categories in BAL from severe COVID-19-affected patients. Transcriptome data from another cohort of COVID-19-derived peripheral blood mononuclear cells (PBMCs) revealed the presence of several genes common to those found in BAL from patients with severe and mild COVID-19 (IFI27, IFITM3, IFI6, IFIT3, MX1, IFIT1, OASL, IFI30, OAS1) or to those seen only in BAL from severe-COVID-19 patients (S100A8, IFI44, IFI44L, CXCL8, CCR1, PLSCR1, EPSTI1, FPR1, OAS2, OAS3, IL1RN, TYMP, BCL2A1). Taken together, our data reveal the presence of neutrophils and macrophage cluster-1 as the main immune cell subsets associated with severe COVID-19 and identify their inflammatory and chemotactic gene signatures, also partially reflected systemically in the circulation, for possible diagnostic and therapeutic interventions.

MicroRNA-3148 acts as molecular switch promoting malignant transformation and adipocytic differentiation of immortalized human bone marrow stromal cells via direct targeting of the SMAD2/TGFß pathway.

MicroRNAs (miRs/miRNAs) play a key role in posttranscriptional regulation of gene expression and are implicated in a number of physiological and pathological conditions, including cellular malignant transformation. In the current study, we investigated the role of miR-3148 in regulating human stromal (mesenchymal) stem cell (hMSC) differentiation and transformation. Stable expression of miR-3148 in telomerized hMSC (hMSC-miR-3148) led to significant increase in in vitro adipocytic differentiation and suppression of osteoblastic differentiation. Concordantly, global gene expression profiling revealed significant enrichment in cholesterol biosynthesis pathway, and pathways related to enhanced cell movement and survival, whereas processes related to bone and connective tissue developments, cell death, apoptosis, and necrosis were downregulated. Global proteomic analysis using 2D-DIGE followed by mass spectrometry (MS) revealed significant changes in protein expression in hMSC-miR-3148 and enrichment in protein networks associated with carcinogenesis. Functional studies revealed that hMSC-miR-3148 exhibited enhanced in vitro cell proliferation, colony formation, migration, invasion, sphere formation, doxorubicin resistance, and increased active number of cells in S and G2/M cell cycle phases and formed sarcoma-like tumors with adipocyte infiltration when implanted into immunocompromised mice. SMAD2 was identified as bone fide gene target for miR-3148 using qRT-PCR, Western blotting, and UTR-based reporter assay. In agreement with our data, SMAD2 expression was downregulated in 47% of patients with soft tissue sarcoma. Bioinformatics analysis revealed that elevated miR-3148 expression correlates with poor prognosis in several human cancer types, including sarcoma. Our study identified miR-3148 as factor regulating hMSC differentiation and is involved in promoting malignant transformation of telomerized hMSC.

Protein Coding and Long Noncoding RNA (lncRNA) Transcriptional Landscape in SARS-CoV-2 Infected Bronchial Epithelial Cells Highlight a Role for Interferon and Inflammatory Response.

The global spread of COVID-19, caused by pathogenic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) underscores the need for an imminent response from medical research communities to better understand this rapidly spreading infection. Employing multiple bioinformatics and computational pipelines on transcriptome data from primary normal human bronchial epithelial cells (NHBE) during SARS-CoV-2 infection revealed activation of several mechanistic networks, including those involved in immunoglobulin G (IgG) and interferon lambda (IFNL) in host cells. Induction of acute inflammatory response and activation of tumor necrosis factor (TNF) was prominent in SARS-CoV-2 infected NHBE cells. Additionally, disease and functional analysis employing ingenuity pathway analysis (IPA) revealed activation of functional categories related to cell death, while those associated with viral infection and replication were suppressed. Several interferon (IFN) responsive gene targets (IRF9, IFIT1, IFIT2, IFIT3, IFITM1, MX1, OAS2, OAS3, IFI44 and IFI44L) were highly upregulated in SARS-CoV-2 infected NBHE cell, implying activation of antiviral IFN innate response. Gene ontology and functional annotation of differently expressed genes in patient lung tissues with COVID-19 revealed activation of antiviral response as the hallmark. Mechanistic network analysis in IPA identified 14 common activated, and 9 common suppressed networks in patient tissue, as well as in the NHBE cell model, suggesting a plausible role for these upstream regulator networks in the pathogenesis of COVID-19. Our data revealed expression of several viral proteins in vitro and in patient-derived tissue, while several host-derived long noncoding RNAs (lncRNAs) were identified. Our data highlights activation of IFN response as the main hallmark associated with SARS-CoV-2 infection in vitro and in human, and identified several differentially expressed lncRNAs during the course of infection, which could serve as disease biomarkers, while their precise role in the host response to SARS-CoV-2 remains to be investigated.

MicroRNA Expression Profiling on Paired Primary and Lymph Node Metastatic Breast Cancer Revealed Distinct microRNA Profile Associated With LNM.

Breast cancer (BC) is the foremost cause of cancer-related deaths in women. BC patients are oftentimes presented with lymph node metastasis (LNM), which increases their risk of recurrence. Compelling data have recently implicated microRNAs in promoting BC metastasis. Therefore, the identification of microRNA (miRNA)-based molecular signature associated with LNM could provide an opportunity for a more personalized treatment for BC patients with high risk of LNM. In current study, we performed comprehensive miRNA profiling in matched primary breast and LNM and identified 40 miRNAs, which were differentially expressed in LNM compared to primary tumors. The expression of 14 miRNAs (Up: hsa-miR-155-5p, hsa-miR-150-5p, hsa-miR-146a-5p, hsa-miR-142-5p and down: hsa-miR-200a-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-205-5p, hsa-miR-210-3p, hsa-miR-214-3p, hsa-miR-141-3p, hsa-miR-127-3p, hsa-miR-125a-5p, and hsa-let-7c-5p) was subsequently validated in a second cohort of 32 breast and 32 matched LNM tumor tissues. Mechanistically, forced expression of hsa-miR-205-5p, or hsa-miR-214-3p epigenetically inhibited MDA-MB-231 cell proliferation, colony formation, and cell migration. Global gene expression profiling on MDA-MB-231 cells overexpressing hsa-miR-205-5p, or hsa-miR-214-3p in combination with in silico target prediction and ingenuity pathway analyses identified multiple bona fide targets for hsa-miR-205-5p, hsa-miR-214-3p affecting cellular proliferation and migration. Interestingly, interrogation of the expression levels of hsa-miR-205 and hsa-miR-214 in the METABRIC breast cancer dataset revealed significantly poor overall survival in patients with downregulated expression of miR-205 [HR = 0.75 (0.61-0.91)], p = 0.003 and hsa-miR-214 [HR = 0.74 (0.59-0.93) p = 0.008]. Our data unraveled the miRNA-transcriptional landscape associated with LNM and provide novel insight on the role of several miRNAs in promoting BC LNM, and suggest their potential utilization in the clinical management of BC patients.

Transgelin is a poor prognostic factor associated with advanced colorectal cancer (CRC) stage promoting tumor growth and migration in a TGFß-dependent manner.

Colorectal cancer (CRC) is the fourth most common cancer type globally. Investigating the signaling pathways that maintain cancer cell phenotype can identify new biomarkers for targeted therapy. Aberrant transforming growth factor-ß (TGFß) signaling has been implicated in CRC progression, however, the exact mechanism by which TGFß exerts its function is still being unraveled. Herein, we investigated TAGLN expression, prognostic value, and its regulation by TGFß in CRC. While TAGLN was generally found to be downregulated in CRC, elevated expression of TAGLN was associated with advanced CRC stage and predicted poor overall survival (hazard ratio (HR) = 1.8, log-rank test P-value = 0.014) and disease-free survival (HR = 1.6, log-rank test P-value = 0.046), hence implicating TAGLN as poor prognostic factor in CRC. Forced expression of TAGLN was associated with enhanced CRC cell proliferation, clonogenic growth, cell migration and in vivo tumor formation in immunocompromised mice, while targeted depletion of TAGLN exhibited opposing biological effects. Global gene expression profiling of TAGLN-overexpressing or TAGLN-deficient CRC cell lines revealed deregulation of multiple cancer-related genes and signaling pathways. Transmission electron microscopy (TEM) revealed ultrastructural changes due to loss of TAGLN, including disruption of actin cytoskeleton organization and aberrant actin filament distribution. Hierarchical clustering, principle component, and ingenuity pathway analyses revealed distinct molecular profile associated with TAGLNhigh CRC patients with remarkable activation of a number of mechanistic networks, including SMARCA4, TGFß1, and P38 MAPK. The P38 MAPK was the top predicted upstream regulator network promoting cell movement through regulation of several intermediate molecules, including TGFß1. Concordantly, functional categories associated with cellular movement and angiogenesis were also enriched in TAGLNhigh CRC, supporting a model for the molecular mechanisms linking TGFß-induced upregulation of TAGLN and CRC tumor progression and suggesting TAGLN as potential prognostic marker associated with advanced CRC pathological stage.

SOX4: Epigenetic regulation and role in tumorigenesis.

Sex-determining region Y-related (SRY) high-mobility group box 4 (SOX4) is a member of the group C subfamily of SOX transcription factors and promotes tumorigenesis by endowing cancer cells with survival, migratory, and invasive capacities. Emerging evidence has highlighted an unequivocal role for this transcription factor in mediating various signaling pathways involved in tumorigenesis, epithelial-to-mesenchymal transition (EMT), and tumor progression. During the last decade, numerous studies have highlighted the epigenetic interplay between SOX4-targeting microRNAs (miRNAs), long noncoding RNAs (lncRNAs) and SOX4 and the subsequent modulation of tumorigenesis, invasion and metastasis. In this review, we summarize the current state of knowledge about the role of SOX4 in cancer development and progression, the epigenetic regulation of SOX4, and the potential utilization of SOX4 as a diagnostic and prognostic biomarker and its depletion as a therapeutic target.