The tumor microenvironment (TME) profoundly influences tumorigenesis, with gene expression in the breast TME capable of predicting clinical outcomes. The TME is complex and includes distinct cancer-associated fibroblast (CAF) subtypes whose contribution to tumorigenesis remains unclear. Here, we identify a subset of myofibroblast CAFs (myCAF) that are senescent (senCAF) in mouse and human breast tumors. Utilizing the MMTV-PyMT;INK-ATTAC (INK) mouse model, we found that senCAF-secreted extracellular matrix specifically limits natural killer (NK) cell cytotoxicity to promote tumor growth. Genetic or pharmacologic senCAF elimination unleashes NK cell killing, restricting tumor growth. Finally, we show that senCAFs are present in HER2+, ER+, and triple-negative breast cancer and in ductal carcinoma in situ (DCIS) where they predict tumor recurrence. Together, these findings demonstrate that senCAFs are potently tumor promoting and raise the possibility that targeting them by senolytic therapy could restrain breast cancer development. Significance: senCAFs limit NK cell-mediated killing, thereby contributing to breast cancer progression. Thus, targeting senCAFs could be a clinically viable approach to limit tumor progression. See related article by Belle et al., p. 1324.

Phosphatase and tensin homologue (PTEN) protein levels are critical for tumor suppression. However, the search for a recurrent cancer-associated gene alteration that causes PTEN degradation has remained futile. In this study, we show that Importin-11 (Ipo11) is a transport receptor for PTEN that is required to physically separate PTEN from elements of the PTEN degradation machinery. Mechanistically, we find that the E2 ubiquitin-conjugating enzyme and IPO11 cargo, UBE2E1, is a limiting factor for PTEN degradation. Using in vitro and in vivo gene-targeting methods, we show that Ipo11 loss results in degradation of Pten, lung adenocarcinoma, and neoplasia in mouse prostate with aberrantly high levels of Ube2e1 in the cytoplasm. These findings explain the correlation between loss of IPO11 and PTEN protein in human lung tumors. Furthermore, we find that IPO11 status predicts disease recurrence and progression to metastasis in patients choosing radical prostatectomy. Thus, our data introduce the IPO11 gene as a tumor-suppressor locus, which is of special importance in cancers that still retain at least one intact PTEN allele.

CRISPR is a versatile gene editing tool which has revolutionized genetic research in the past few years. Optimizing sgRNA design to improve the efficiency of target/DNA cleavage is critical to ensure the success of CRISPR screens. By borrowing knowledge from oligonucleotide design and nucleosome occupancy models, we systematically evaluated candidate features computed from a number of nucleic acid, thermodynamic and secondary structure models on real CRISPR datasets. Our results showed that taking into account position-dependent dinucleotide features improved the design of effective sgRNAs with area under the receiver operating characteristic curve (AUC) >0.8, and the inclusion of additional features offered marginal improvement (∼2% increase in AUC). Using a machine-learning approach, we proposed an accurate prediction model for sgRNA design efficiency. An R package predictSGRNA implementing the predictive model is available at http://www.ams.sunysb.edu/~pfkuan/softwares.html#predictsgrna .