FAM120A couples SREBP-dependent transcription and splicing of lipogenesis enzymes downstream of mTORC1.

The mechanistic target of rapamycin complex 1 (mTORC1) is a master regulator of cell growth that stimulates macromolecule synthesis through transcription, RNA processing, and post-translational modification of metabolic enzymes. However, the mechanisms of how mTORC1 orchestrates multiple steps of gene expression programs remain unclear. Here, we identify family with sequence similarity 120A (FAM120A) as a transcription co-activator that couples transcription and splicing of de novo lipid synthesis enzymes downstream of mTORC1-serine/arginine-rich protein kinase 2 (SRPK2) signaling. The mTORC1-activated SRPK2 phosphorylates splicing factor serine/arginine-rich splicing factor 1 (SRSF1), enhancing its binding to FAM120A. FAM120A directly interacts with a lipogenic transcription factor SREBP1 at active promoters, thereby bridging the newly transcribed lipogenic genes from RNA polymerase II to the SRSF1 and U1-70K-containing RNA-splicing machinery. This mTORC1-regulated, multi-protein complex promotes efficient splicing and stability of lipogenic transcripts, resulting in fatty acid synthesis and cancer cell proliferation. These results elucidate FAM120A as a critical transcription co-factor that connects mTORC1-dependent gene regulation programs for anabolic cell growth.

Quantitative self-assembly prediction yields targeted nanomedicines.

Development of targeted nanoparticle drug carriers often requires complex synthetic schemes involving both supramolecular self-assembly and chemical modification. These processes are generally difficult to predict, execute, and control. We describe herein a targeted drug delivery system that is accurately and quantitatively predicted to self-assemble into nanoparticles based on the molecular structures of precursor molecules, which are the drugs themselves. The drugs assemble with the aid of sulfated indocyanines into particles with ultrahigh drug loadings of up to 90%. We devised quantitative structure-nanoparticle assembly prediction (QSNAP) models to identify and validate electrotopological molecular descriptors as highly predictive indicators of nano-assembly and nanoparticle size. The resulting nanoparticles selectively targeted kinase inhibitors to caveolin-1-expressing human colon cancer and autochthonous liver cancer models to yield striking therapeutic effects while avoiding pERK inhibition in healthy skin. This finding enables the computational design of nanomedicines based on quantitative models for drug payload selection.

Identification of novel target genes involved in Indian Fanconi anemia patients using microarray.

Fanconi anemia (FA) is a genetic disorder characterized by progressive bone marrow failure and a predisposition to cancers. Mutations have been documented in 15 FA genes that participate in the FA-BRCA DNA repair pathway, a fundamental pathway in the development of the disease and the presentation of its characteristic symptoms. Certain symptoms such as oxygen sensitivity, hematological abnormalities and impaired immunity suggest that FA proteins could participate in or independently control other pathways as well. In this study, we identified 9 DNA repair genes that were down regulated in a genome wide analysis of 6 Indian Fanconi anemia patients. Functional clustering of a total of 233 dysregulated genes identified key biological processes that included regulation of transcription, DNA repair, cell cycle and chromosomal organization. Microarray data revealed the down regulation of ATXN3, ARID4A and ETS-1, which were validated by RTPCR in a subsequent sample set of 9 Indian FA patients. Here we report for the first time a gene expression profile of Fanconi anemia patients from the Indian population and a pool of genes that might aid in the acquisition and progression of the FA phenotype.