PMID: 27765066

Microenvironment Cell Populations (MCP)-counter, a transcriptome-based computational method that robustly quantifies the abundance of immune and non-immune stromal cell populations in a heterogeneous tissue sample.
MCP-counter is available as an R package. From a gene expression matrix, it produces for each sample an abundance score for CD3+ T cells, CD8+ T cells, cytotoxic lymphocytes, NK cells, B lymphocytes, cells originating from monocytes (monocytic lineage), myeloid dendritic cells, neutrophils, as well as endothelial cells and fibroblasts.

优势：
only MCP-counter was able to accurately reflect the difference in immune cell abundances across simulated mixtures, while CIBERSORT (accurately) estimated stable proportions of each immune cell population within the leukocytic fraction of the simulated mixtures.

We implemented MCP-counter as an R package called “MCPcounter”. Users should call the “MCPcounter.estimate” function, which takes a normalized gene expression matrix as its first argument and the type of features that should be mapped to selected TM (probe sets, HUGO symbols, ENTREZ ID) as its second argument.
We used mapped TM to “probe sets” to compute MCP-counter scores for Affymetrix Human Genome U133 Plus 2.0 and Affymetrix 133A samples, and HUGO symbol identifiers for samples obtained on Affymetrix HuGene 1.0 ST, Illumina Hiseq, and other gene expression platforms.
This package is available Zenodo (https://doi.org/10.5281/zenodo.61372).

Cellular senescence and senolytics: the path to the clinic

The senescent cell fate can be triggered by a number of stressors including DNA damage, cancerous mutations or oncogene activation, mitochondrial dysfunction, reactive metabolites, hyperoxia or hypoxia, proteotoxic stress, extracellular signals, infections, mechanical or shear stresses that deform cells, resistance exercise and factors secreted by other senescent cells.

Senescence-associated secretory phenotype.png

Because those 30–70% of senescent cells that have a proapoptotic, tissue-destructive SASP are themselves resistant to apoptosis, it was hypothesized that such senescent cells depend on antiapoptotic, pro-survival pathways to avoid self-destruction.

First- and second-generation senolytic strategies.

Bioinformatic analyses identified 46 compounds that target SCAP pathways as being potentially senolytic¹⁴.