Single-cell RNA-seq analysis identifies markers of resistance to targeted BRAF inhibitors in melanoma cell populations.

Single-cell RNA-seq's (scRNA-seq) unprecedented cellular resolution at a genome-wide scale enables us to address questions about cellular heterogeneity that are inaccessible using methods that average over bulk tissue extracts. However, scRNA-seq data sets also present additional challenges such as high transcript dropout rates, stochastic transcription events, and complex population substructures. Here, we present a single-cell RNA-seq analysis and klustering evaluation (SAKE), a robust method for scRNA-seq analysis that provides quantitative statistical metrics at each step of the analysis pipeline. Comparing SAKE to multiple single-cell analysis methods shows that most methods perform similarly across a wide range of cellular contexts, with SAKE outperforming these methods in the case of large complex populations. We next applied the SAKE algorithms to identify drug-resistant cellular populations as human melanoma cells respond to targeted BRAF inhibitors (BRAFi). Single-cell RNA-seq data from both the Fluidigm C1 and 10x Genomics platforms were analyzed with SAKE to dissect this problem at multiple scales. Data from both platforms indicate that BRAF inhibitor-resistant cells can emerge from rare populations already present before drug application, with SAKE identifying both novel and known markers of resistance. These experimentally validated markers of BRAFi resistance share overlap with previous analyses in different melanoma cell lines, demonstrating the generality of these findings and highlighting the utility of single-cell analysis to elucidate mechanisms of BRAFi resistance.

Single-Cell Applications of Next-Generation Sequencing.

The single cell is considered the basic unit of biology, and the pursuit of understanding how heterogeneous populations of cells can functionally coexist in tissues, organisms, microbial ecosystems, and even cancer, makes them the subject of intense study. Next-generation sequencing (NGS) of RNA and DNA has opened a new frontier of (single)-cell biology. Hundreds to millions of cells now can be assayed in parallel, providing the molecular profile of each cell in its milieu inexpensively and in a manner that can be analyzed mathematically. The goal of this article is to provide a high-level overview of single-cell sequencing for the nonexpert and show how its applications are influencing both basic and applied clinical studies in embryology, developmental genetics, and cancer.

Unresolved endoplasmic reticulum stress engenders immune-resistant, latent pancreatic cancer metastases.

The majority of patients with pancreatic ductal adenocarcinoma (PDA) develop metastatic disease after resection of their primary tumor. We found that livers from patients and mice with PDA harbor single disseminated cancer cells (DCCs) lacking expression of cytokeratin 19 (CK19) and major histocompatibility complex class I (MHCI). We created a mouse model to determine how these DCCs develop. Intraportal injection of immunogenic PDA cells into preimmunized mice seeded livers only with single, nonreplicating DCCs that were CK19- and MHCI- The DCCs exhibited an endoplasmic reticulum (ER) stress response but paradoxically lacked both inositol-requiring enzyme 1α activation and expression of the spliced form of transcription factor XBP1 (XBP1s). Inducible expression of XBP1s in DCCs, in combination with T cell depletion, stimulated the outgrowth of macrometastatic lesions that expressed CK19 and MHCI. Thus, unresolved ER stress enables DCCs to escape immunity and establish latent metastases.

TGF-ß reduces DNA ds-break repair mechanisms to heighten genetic diversity and adaptability of CD44+/CD24- cancer cells.

Many lines of evidence have indicated that both genetic and non-genetic determinants can contribute to intra-tumor heterogeneity and influence cancer outcomes. Among the best described sub-population of cancer cells generated by non-genetic mechanisms are cells characterized by a CD44+/CD24- cell surface marker profile. Here, we report that human CD44+/CD24- cancer cells are genetically highly unstable because of intrinsic defects in their DNA-repair capabilities. In fact, in CD44+/CD24- cells, constitutive activation of the TGF-beta axis was both necessary and sufficient to reduce the expression of genes that are crucial in coordinating DNA damage repair mechanisms. Consequently, we observed that cancer cells that reside in a CD44+/CD24- state are characterized by increased accumulation of DNA copy number alterations, greater genetic diversity and improved adaptability to drug treatment. Together, these data suggest that the transition into a CD44+/CD24- cell state can promote intra-tumor genetic heterogeneity, spur tumor evolution and increase tumor fitness.

In-silico characterization of ECE-1 inhibitors.

Atherosclerosis is the primary cause of CAD and cerebrovascular disease. Endothelin (ET)-1 is a vasoconstrictive peptide implicated in Atherosclerosis pathology. Endothelin-converting enzyme (ECE) is a membrane metalloprotease that generates endothelin. Reported inhibitors of ECE-1 and their IC(50) values were retrieved from literature and their structures were docked with the parent protein using the Molegro virtual docker. The obtained MolDock scores of each of the compounds are hereby reported and are subject to graphical analysis in conjunction with their respective IC(50) values to characterize potent inhibitors. A search was then run in the ZINC database for compounds with similar properties. Potent inhibitors with higher Dock scores and better Ranking were isolated and are reported.