\u27Normalizing\u27 the malignant phenotype of luminal breast cancer cells via alpha(v)beta(3)-integrin

Reestablishing tissue organization of breast cancer cells into acini was previously shown to override their malignant phenotype. In our study, we demonstrate that alpha(v)beta(3) integrin (Int-αvβ3), previously shown to play a role in cancer progression, promoted differentiation and growth arrest of organoids derived from luminal A breast cancer cells grown in their relevant three-dimensional microenvironment. These organoids differentiated into normal-like acini resembling a benign stage of breast tissue. Likewise, we demonstrate that Int-αvβ3 is selectively expressed in the epithelium of the benign stage of breast tissues, and is lost during the early stages of luminal A breast cancer progression. Notably, the organoids’ reversion into normal-like acini was mediated by cancer luminal progenitor-like cells expressing both EpCAM$^{high}$CD49f$^{low}$CD24$^{+}$ and Int-αvβ3. Furthermore, downregulation of Notch4 expression and downstream signaling was shown to mediate Int-αvβ3-induced reversion. Intriguingly, when luminal A breast cancer cells expressing Int-αvβ3 were injected into a humanized mouse model, differentiated tumors developed when compared with that generated by control cells. Hence, our data suggest that promoting differentiation of luminal A breast cancer cells by signaling emanating from Int-αvβ3 can potentially promote ‘normalization’ of their malignant phenotype and may prevent the malignant cells from progressing

Comparative Analysis of the APOL1 Variants in the Genetic Landscape of Renal Carcinoma Cells

Although the relative risk of renal cell carcinoma associated with chronic kidney injury is particularly high among sub-Saharan African ancestry populations, it is unclear yet whether the APOL1 gene risk variants (RV) for kidney disease additionally elevate this risk. APOL1 G1 and G2 RV contribute to increased risk for kidney disease in black populations, although the disease mechanism has still not been fully deciphered. While high expression levels of all three APOL1 allelic variants, G0 (the wild type allele), G1, and G2 are injurious to normal human cells, renal carcinoma cells (RCC) naturally tolerate inherent high expression levels of APOL1. We utilized CRISPR/Cas9 gene editing to generate isogenic RCC clones expressing APOL1 G1 or G2 risk variants on a similar genetic background, thus enabling a reliable comparison between the phenotypes elicited in RCC by each of the APOL1 variants. Here, we demonstrate that knocking in the G1 or G2 APOL1 alleles, or complete elimination of APOL1 expression, has major effects on proliferation capacity, mitochondrial morphology, cell metabolism, autophagy levels, and the tumorigenic potential of RCC cells. The most striking effect of the APOL1 RV effect was demonstrated in vivo by the complete abolishment of tumor growth in immunodeficient mice. Our findings suggest that, in contrast to the WT APOL1 variant, APOL1 RV are toxic for RCC cells and may act to suppress cancer cell growth. We conclude that the inherent expression of non-risk APOL1 G0 is required for RCC tumorigenicity. RCC cancer cells can hardly tolerate increased APOL1 risk variants expression levels as opposed to APOL1 G0

Niche-Dependent Gene Expression Profile of Intratumoral Heterogeneous Ovarian Cancer Stem Cell Populations

<div><p>Intratumoral heterogeneity challenges existing paradigms for anti-cancer therapy. We have previously demonstrated that the human embryonic stem cells (hESC)-derived cellular microenvironment in immunocompromised mice, enables functional distinction of heterogeneous tumor cells, including cells which do not grow into a tumor in a conventional direct tumor xenograft platform. We have identified and characterized six cancer cell subpopulations each clonally expanded from a single cell, derived from human ovarian clear cell carcinoma of a single tumor, to demonstrate striking intratumoral phenotypic heterogeneity that is dynamically dependent on the tumor growth microenvironment. These cancer cell subpopulations, characterized as cancer stem cell subpopulations, faithfully recapitulate the full spectrum of histological phenotypic heterogeneity known for human ovarian clear cell carcinoma. Each of the six subpopulations displays a different level of morphologic and tumorigenic differentiation wherein growth in the hESC-derived microenvironment favors growth of CD44+/aldehyde dehydrogenase positive pockets of self-renewing cells that sustain tumor growth through a process of tumorigenic differentiation into CD44-/aldehyde dehydrogenase negative derivatives. Strikingly, these derivative cells display microenvironment-dependent plasticity with the capacity to restore self-renewal markers and CD44 expression. In the current study, we delineate the distinct gene expression and epigenetic profiles of two such subpopulations, representing extremes of phenotypic heterogeneity in terms of niche-dependent self-renewal and tumorigenic differentiation. By combining Gene Set Enrichment, Gene Ontology and Pathway-focused array analyses with methylation status, we propose a suite of robust differences in tumor self-renewal and differentiation pathways that underlie the striking intratumoral phenotypic heterogeneity which characterize this and other solid tumor malignancies.</p> </div

Principal component analysis (PCA) and hierarchical clustering of data sets.

<p><i>A</i>, The PCA results are provided as two-dimensional representations based on contribution scores for the first two components. Discrimination between cancer cell subpopulations (CCSPs) C12 and C13 samples is shown as indicated in the color capture. <i>B</i>, Hierarchical clustering of the samples using all 48,803 probe elements on the Illumina bead chip demonstrated variability between CCSPs C12 and C13 samples.</p

Validation of the gene expression microarray data.

<p>Total RNA extracted from CCSPs C12 and C13 <i>in </i><i>vitro</i> grown cells and from C12 and C13 – derived tumors generated intramuscular (i.m) and intarteratoma (i.t) were analyzed by quantitative real-time RT-PCR using specific primers as indicated (each in 2 independent RNA samples). <i>A</i>, DNA products were separated on 2% agarose gel and <i>B</i>, the bars demonstrate the relative fold change in expression levels of 10 differentially expressed genes. ACTB and GAPDH were used for internal controls. Asterisk indicates that no KISS1R expression was observed in the C13 samples. These experiments were performed twice, each sample in quadruplicates. <i>C</i>, Bisulfit sequencing analysis of GPX3, MX1, TACSTD2, and KISS1R promoter regions in CCSPs C12 and C13. Open circles represent unmethylated CpG dinucleotides and closed circles represent methylated CpG dinucleotides. Each row is derived from an individual subclone. These experiments were performed twice, each sample in quadruplicates. </p

Data management workflow for gene expression profiling process.

<p><i>A</i>, Workflow of the analyses performed for gene expression profiling of cancer cell subpopulations (CCSPs) C12 and C13 <i>in </i><i>vitro</i> and <i>in </i><i>vivo</i>. <i>B</i>, Identification of differentially expressed genes between C12 and C13 <i>in </i><i>vitro</i> grown cells and between tumors generated intramuscular (i.m) and intrateratoma (i.t), and Gene Ontology annotations which correlate with tumors generated i.m and i.t. </p

Heat Map of differentially expressed genes ranked by Gene Set Enrichment Analysis (GSEA).

<p>The 100 most differentially expressed genes between cancer cell subpopulations (CCSPs) C12 and C13 <i>in </i><i>vitro</i> grown cells (<i>A</i>), CCSP C12-derived tumors generated intramuscular (i.m) and intrateratoma (i.t) (<i>B</i>) and CCSP C13-derived tumors generated i.m and i.t (<i>C</i>). The differential expression of genes was calculated according to the Signal-To-Noise metrics. The top 50 symbols represent genes that were elevated in tumors developed i.t. The next 50 symbols represent genes that elevated in tumors developed i.m. Genes which are located higher in each of the two 50 gene groups indicates a greater difference level than genes located at lower positions. Expression values are represented as shown in the color caption.</p