The mechanistic target of rapamycin complex 1 (mTORC1) is a key metabolic hub that controls the cellular response to environmental cues by exerting its kinase activity on multiple substrates 1 – 3 . However, whether mTORC1 responds to diverse stimuli by differentially phosphorylating specific substrates is poorly understood. Here we show that Transcription Factor EB (TFEB), a master regulator of lysosomal biogenesis and autophagy 4 , 5 , is phosphorylated by mTORC1 via a substrate-specific mechanism mediated by RagGTPases. Thus, TFEB phosphorylation is strictly dependent on amino acid-mediated activation of RagC/D GTPase but, unlike other mTORC1 substrates such as S6K and 4E-BP1, insensitive to growth factor-induced Rheb activity. This mechanism plays a crucial role in Birt-Hogg-Dubé (BHD) syndrome, a disorder caused by mutations of the RagC/D activator folliculin (FLCN) and characterized by benign skin tumors, lung and kidney cysts and renal cell carcinoma 6 , 7 . We found that constitutive activation of TFEB is the main driver of the kidney abnormalities and paradoxical mTORC1 hyperactivity observed in BHD syndrome. Remarkably, depletion of TFEB in a kidney-specific mouse model of BHD syndrome fully rescued the disease phenotype and associated lethality and normalized mTORC1 activity. Together, these findings identify a substrate-specific control mechanism of mTORC1, whose dysregulation leads to kidney cysts and cancer.

Highlights d The endothelial marker PV-1 is an independent marker of CRC recurrence d Specific tumor-resident bacteria modulate PV-1 via a virf1dependent mechanism d Increased PV-1 detection correlates with bacteria translocation and liver metastases d Migrated bacteria induce the premetastatic niche in the liver

RAB5A and RAB4 promote breast tumor cell dissemination by controlling the trafficking of proteins necessary for localized invadosome formation.

Background: The cancer transcriptome is difficult to explore due to the heterogeneity of quantitative and qualitative changes in gene expression linked to the disease status. An increasing number of "unconventional" transcripts, such as novel isoforms, non-coding RNAs, somatic gene fusions and deletions have been associated with the tumoral state. Massively parallel sequencing techniques provide a framework for exploring the transcriptional complexity inherent to cancer with a limited laboratory and financial effort. We developed a deep sequencing and bioinformatics analysis protocol to investigate the molecular composition of a breast cancer poly(A) + transcriptome. This method utilizes a cDNA library normalization step to diminish the representation of highly expressed transcripts and biology-oriented bioinformatic analyses to facilitate detection of rare and novel transcripts.