Eryngium billardieri Extract and Fractions Induces Apoptosis in Cancerous Cells

Background: Eryngium is genus flowering plants in the Umbelliferae family having pharmacological properties such as anti-inflammatory and anti-diabetic. Given the nature of melanoma and breast cancers in recent years and the fact that the anti-cancer properties of Eryngium billardieri on mentioned cell lines have not been studied, the present study conducted to explore these properties. Objective: The mechanisms of cytotoxicity and apoptosis of aerial parts of various extracts and fractions of E. billardieri on cancerous cells and normal cells were investigated. Methods: Samples were collected from natural habitats, dried and then extracted by Soxhlet apparatus with solvents of n-Hex, DCM and methanol, respectively. The cytotoxic effects of the extracts were investigated by MTT method on MCF7, B16 and HFF-2 classes for 24 and 48 hours. Flowcytometry, was also used to investigate the mechanism of cytotoxicity and confirming by Real-time PCR of p53 and Bax genes, which codes apoptosis regulator proteins. Meanwhile, volatile compounds of extracts were identified by GC-MS method. Results: The obtained data showed that the n-Hex extract of E. billardieri on B-16 and MCF7 cell lines and dichromethane extract on MCF7 cell line had the most significant cytotoxic effect compared to DMSO control (p value <0.001). Our finding showed that the mechanism of n-Hex extract with 80% and 100% vlc fractions on B16 induced apoptotic compared to HFF-2 control cells, moreover, n-Hex extract and 80% vlc fraction on MCF7 was apoptotic. The major compounds of n-Hex, DCM and 80% and 100% fractions of n-Hex extract obtained from GC-MS are non-terpenoid. Conclusion: Non-terpenoids compounds of E. billardieri can be the responsible for showing the most cytotoxic effects on MCF7 and B16 cell lines with apoptotic mechanism and n-Hex extract had the most significant inhibitory effect on cancerous cells compared to the HFF-2 control cells by the mechanism of apoptosis.

Improved SNV Discovery in Barcode-Stratified scRNA-seq Alignments

Currently, the detection of single nucleotide variants (SNVs) from 10 x Genomics single-cell RNA sequencing data (scRNA-seq) is typically performed on the pooled sequencing reads across all cells in a sample. Here, we assess the gaining of information regarding SNV assessments from individual cell scRNA-seq data, wherein the alignments are split by cellular barcode prior to the variant call. We also reanalyze publicly available data on the MCF7 cell line during anticancer treatment. We assessed SNV calls by three variant callers—GATK, Strelka2, and Mutect2, in combination with a method for the cell-level tabulation of the sequencing read counts bearing variant alleles–SCReadCounts (single-cell read counts). Our analysis shows that variant calls on individual cell alignments identify at least a two-fold higher number of SNVs as compared to the pooled scRNA-seq; these SNVs are enriched in novel variants and in stop-codon and missense substitutions. Our study indicates an immense potential of SNV calls from individual cell scRNA-seq data and emphasizes the need for cell-level variant detection approaches and tools, which can contribute to the understanding of the cellular heterogeneity and the relationships to phenotypes, and help elucidate somatic mutation evolution and functionality.

Design, Synthesis and Biological Evaluation of Aromatase Inhibitors based on Sulfonates and Sulfonamides of Resveratrol

A library of sulfonate and sulfonamide derivatives of Resveratrol was synthesized and tested for its aromatase inhibitory potential. Interestingly, sulfonate derivatives were found to be more active than sulfonamide bioisosteres with IC50 values in the low micromolar range. The sulfonate analogues 1b–c and 1j exhibited good in vitro antiproliferative activity on the MCF7 cell line, evidenced by MTT and LDH release assays. Structure–activity relationships suggested that electronic and lipophilic properties could have a different role in promoting the biological response for sulfonates and sulfonamides, respectively. Docking studies disclosed the main interactions at a molecular level of detail behind the observed inhibition of the more active compounds whose chemical stability has been evaluated with nano-liquid chromatography. Finally, 1b–c and 1j were highlighted as sulfonates to be further developed as novel and original aromatase inhibitors.

Improved SNV discovery in barcode-stratified scRNA-seq alignments

Single cell SNV analysis is an emerging and promising strategy to connect cell-level genetic variation to cell phenotypes. At the present, SNV detection from 10x Genomics scRNA-seq data is typically performed on the pooled sequencing reads across all cells in a sample. Here, we assess the gain of information of SNV assessments from individual cell scRNA-seq data, where the alignments are split by barcode prior to the variant call. For our analyses we use publicly available sequencing da-ta on the human breast cancer cell line MCF7 cell line generated at consequent time-points during anticancer treatment. We analysed SNV calls by three popular variant callers, GATK, Strelka2 and Mutect2, in combination with a method for cell-level tabulation of the sequencing read counts bearing SNV alleles, SCReadCounts. Our analysis shows that variant calls on individual cell alignments identify at least two-fold higher number of SNVs as compared to the pooled scRNA-seq. We demonstrate that scSNVs exclusively called in the single cell alignments (scSNVs) are substantially enriched in novel genetic variants and in coding functional annotations, in particular, stop-codon and missense substitutions. Furthermore, we find that the expression of some scSNVs correlates with the expression of their harbouring gene (cis-scReQTLs). Overall, our study indicates an immense potential of SNV calls from individual cell scRNA-seq data and emphasizes on the need of cell-level variant detection approaches and tools. Given the growing accumulation of scRNA-seq datasets, cell-level variant assessments are likely to significantly contribute to the understanding of the cellular heterogeneity and the relationship between genetics variants and functional phenotypes. In addition, cell-level variant assessments from scRNA-seq can be highly informative in cancer where they can help elucidate somatic mutations evolution and functionality.

Integrative analysis of structural variations using short-reads and linked-reads yields highly specific and sensitive predictions

Genetic diseases are driven by aberrations of the human genome. Identification of such aberrations including structural variations (SVs) is key to our understanding. Conventional short-reads whole genome sequencing (cWGS) can identify SVs to base-pair resolution, but utilizes only short-range information and suffers from high false discovery rate (FDR). Linked-reads sequencing (10XWGS) utilizes long-range information by linkage of short-reads originating from the same large DNA molecule. This can mitigate alignment-based artefacts especially in repetitive regions and should enable better prediction of SVs. However, an unbiased evaluation of this technology is not available. In this study, we performed a comprehensive analysis of different types and sizes of SVs predicted by both the technologies and validated with an independent PCR based approach. The SVs commonly identified by both the technologies were highly specific, while validation rate dropped for uncommon events. A particularly high FDR was observed for SVs only found by 10XWGS. To improve FDR and sensitivity, statistical models for both the technologies were trained. Using our approach, we characterized SVs from the MCF7 cell line and a primary breast cancer tumor with high precision. This approach improves SV prediction and can therefore help in understanding the underlying genetics in various diseases.

Activating transcription factor-2 (ATF2) is a key determinant of resistance to endocrine treatment in an in vitro model of breast cancer

Background Activating transcription factor-2 (ATF2), a member of the leucine zipper family of DNA binding proteins, has been implicated as a tumour suppressor in breast cancer. However, its exact role in breast cancer endocrine resistance is still unclear. We have previously shown that silencing of ATF2 leads to a loss in the growth-inhibitory effects of tamoxifen in the oestrogen receptor (ER)-positive, tamoxifen-sensitive MCF7 cell line and highlighted that this multi-faceted transcription factor is key to the effects of tamoxifen in an endocrine sensitive model. In this work, we explored further the in vitro role of ATF2 in defining the resistance to endocrine treatment. Materials and methods We knocked down ATF2 in TAMR, LCC2 and LCC9 tamoxifen-resistant breast cancer cell lines as well as the parental tamoxifen sensitive MCF7 cell line and investigated the effects on growth, colony formation and cell migration. We also performed a microarray gene expression profiling (Illumina Human HT12_v4) to explore alterations in gene expression between MCF7 and TAMRs after ATF2 silencing and confirmed gene expression changes by quantitative RT-PCR. Results By silencing ATF2, we observed a significant growth reduction of TAMR, LCC2 and LCC9 with no such effect observed with the parental MCF7 cells. ATF2 silencing was also associated with a significant inhibition of TAMR, LCC2 and LCC9 cell migration and colony formation. Interestingly, knockdown of ATF2 enhanced the levels of ER and ER-regulated genes, TFF1, GREB1, NCOA3 and PGR, in TAMR cells both at RNA and protein levels. Microarray gene expression identified a number of genes known to mediate tamoxifen resistance, to be differentially regulated by ATF2 in TAMR in relation to the parental MCF7 cells. Moreover, differential pathway analysis confirmed enhanced ER activity after ATF2 knockdown in TAMR cells. Conclusion These data demonstrate that ATF2 silencing may overcome endocrine resistance and highlights further the dual role of this transcription factor that can mediate endocrine sensitivity and resistance by modulating ER expression and activity.