Molecular Insights Into Colorectal Carcinoma

Colorectal carcinoma (CRC) is one of the most common type of cancers and a leading cause of cancer-related deaths worldwide and in the United States. CRC is a heterogeneous disease with a well-characterized stepwise accumulation molecular alteration associated with adenoma formation and progression to carcinoma. We review the genomic and epigenomic pathways, including chromosomal instability, microsatellite instability, and epigenetic instability or CpG island methylator phenotype, their characteristics, and prognosis. We describe the four consensus molecular subtypes of CRC established by the international Colorectal Cancer Subtyping Consortium, their mechanisms to develop cancer, molecular characterization, clinical features, and prognosis. Finally, we review currently used predictive biomarkers.

Identification of Cell Types from Single-Cell Transcriptomic Data

Unprecedented technological advances in single-cell RNA-sequencing (scRNA-seq) technology have now made it possible to profile genome-wide expression in single cells at low cost and high throughput. There is substantial ongoing effort to use scRNA-seq measurements to identify the "cell types" that form components of a complex tissue, akin to taxonomizing species in ecology. Cell type classification from scRNA-seq data involves the application of computational tools rooted in dimensionality reduction and clustering, and statistical analysis to identify molecular signatures that are unique to each type. As datasets continue to grow in size and complexity, computational challenges abound, requiring analytical methods to be scalable, flexible, and robust. Moreover, careful consideration needs to be paid to experimental biases and statistical challenges that are unique to these measurements to avoid artifacts. This chapter introduces these topics in the context of cell-type identification, and outlines an instructive step-by-step example bioinformatic pipeline for researchers entering this field.