Cell Phase Identification in a Three-Dimensional Engineered Tumor Model by Infrared Spectroscopic Imaging

Cell cycle progression plays a vital role in regulating proliferation, metabolism, and apoptosis. Three-dimensional (3D) cell cultures have emerged as an important class of in vitro disease models, and incorporating the variation occurring from cell cycle progression in these systems is critical. Here, we report the use of Fourier transform infrared (FT-IR) spectroscopic imaging to identify subtle biochemical changes within cells, indicative of the G1/S and G2/M phases of the cell cycle. Following previous studies, we first synchronized samples from two-dimensional (2D) cell cultures, confirmed their states by flow cytometry and DNA quantification, and recorded spectra. We determined two critical wavenumbers (1059 and 1219 cm–1) as spectral indicators of the cell cycle for a set of isogenic breast cancer cell lines (MCF10AT series). These two simple spectral markers were then applied to distinguish cell cycle stages in a 3D cell culture model using four cell lines that represent the main stages of cancer progression from normal cells to metastatic disease. Temporal dependence of spectral biomarkers during acini maturation validated the hypothesis that the cells are more proliferative in the early stages of acini development; later stages of the culture showed stability in the overall composition but unique spatial differences in cells in the two phases. Altogether, this study presents a computational and quantitative approach for cell phase analysis in tissue-like 3D structures without any biomarker staining and provides a means to characterize the impact of the cell cycle on 3D biological systems and disease diagnostic studies using IR imaging

Table S3 from Long Noncoding RNA MALAT1 Promotes Hepatocellular Carcinoma Development by SRSF1 Upregulation and mTOR Activation

Table S3. IPA enriched pathways based on RNA-seq analysis</p

Table S1 from Long Noncoding RNA MALAT1 Promotes Hepatocellular Carcinoma Development by SRSF1 Upregulation and mTOR Activation

Table S1: List of primers oligos and siRNAs</p

Table S2 from Long Noncoding RNA MALAT1 Promotes Hepatocellular Carcinoma Development by SRSF1 Upregulation and mTOR Activation

Table S2. Full list of Up- and Down regulated genes in the RNA seq analysis</p

Supplementary Materials and Methods and Supplementary Figure Legends from Long Noncoding RNA MALAT1 Promotes Hepatocellular Carcinoma Development by SRSF1 Upregulation and mTOR Activation

Supplementary information text: Methods and figure legends</p

Figures S1-S8 from Long Noncoding RNA MALAT1 Promotes Hepatocellular Carcinoma Development by SRSF1 Upregulation and mTOR Activation

Figure S1: Knockdown of MALAT1 inhibits proliferation of liver progenitor and HCC cells. Figure S2: Effect of MALAT1 expression on splicing of endogenous SRSF1 targets. Figure S3. Differential gene expression based on RNA-seq data. Figure S4. Enriched pathways and networks activated by overexpression of MALAT1 based on RNA-seq analysis. Figure S5 Enriched pathways activated by MALAT1 overexpression based on RNA-seq analysis. Figure S6. Validation of MALAT1 up- and down-regulated genes identified by RNA-seq analysis. Figure S7. Knockdown of MALAT1 down-regulates c-Myc protein levels. Figure S8. Knockdown of SRSF1 inhibits oncogenesis downstream to MALAT1 and only partially inhibits transformation by oncogenic Ras.</p

Supplementary Data from The <i>BRCA1</i> Pseudogene Negatively Regulates Antitumor Responses through Inhibition of Innate Immune Defense Mechanisms

supplementary figures and table</p