Non-canonical functions of SNAIL drive context-specific cancer progression.

SNAIL is a key transcriptional regulator in embryonic development and cancer. Its effects in physiology and disease are believed to be linked to its role as a master regulator of epithelial-to-mesenchymal transition (EMT). Here, we report EMT-independent oncogenic SNAIL functions in cancer. Using genetic models, we systematically interrogated SNAIL effects in various oncogenic backgrounds and tissue types. SNAIL-related phenotypes displayed remarkable tissue- and genetic context-dependencies, ranging from protective effects as observed in KRAS- or WNT-driven intestinal cancers, to dramatic acceleration of tumorigenesis, as shown in KRAS-induced pancreatic cancer. Unexpectedly, SNAIL-driven oncogenesis was not associated with E-cadherin downregulation or induction of an overt EMT program. Instead, we show that SNAIL induces bypass of senescence and cell cycle progression through p16INK4A-independent inactivation of the Retinoblastoma (RB)-restriction checkpoint. Collectively, our work identifies non-canonical EMT-independent functions of SNAIL and unravel its complex context-dependent role in cancer.

Deep Learning Reveals Cancer Metastasis and Therapeutic Antibody Targeting in the Entire Body.

Reliable detection of disseminated tumor cells and of the biodistribution of tumor-targeting therapeutic antibodies within the entire body has long been needed to better understand and treat cancer metastasis. Here, we developed an integrated pipeline for automated quantification of cancer metastases and therapeutic antibody targeting, named DeepMACT. First, we enhanced the fluorescent signal of cancer cells more than 100-fold by applying the vDISCO method to image metastasis in transparent mice. Second, we developed deep learning algorithms for automated quantification of metastases with an accuracy matching human expert manual annotation. Deep learning-based quantification in 5 different metastatic cancer models including breast, lung, and pancreatic cancer with distinct organotropisms allowed us to systematically analyze features such as size, shape, spatial distribution, and the degree to which metastases are targeted by a therapeutic monoclonal antibody in entire mice. DeepMACT can thus considerably improve the discovery of effective antibody-based therapeutics at the pre-clinical stage. VIDEO ABSTRACT.

Developing anti-neoplastic biotherapeutics against eIF4F.

Biotherapeutics have revolutionized modern medicine by providing medicines that would not have been possible with small molecules. With respect to cancer therapies, this represents the current sector of the pharmaceutical industry having the largest therapeutic impact, as exemplified by the development of recombinant antibodies and cell-based therapies. In cancer, one of the most common regulatory alterations is the perturbation of translational control. Among these, changes in eukaryotic initiation factor 4F (eIF4F) are associated with tumor initiation, progression, and drug resistance in a number of settings. This, coupled with the fact that systemic suppression of eIF4F appears well tolerated, indicates that therapeutic agents targeting eIF4F hold much therapeutic potential. Here, we discuss opportunities offered by biologicals for this purpose.

Gain- and Loss-of-Function Mutations in the Breast Cancer Gene GATA3 Result in Differential Drug Sensitivity.

Patterns of somatic mutations in cancer genes provide information about their functional role in tumourigenesis, and thus indicate their potential for therapeutic exploitation. Yet, the classical distinction between oncogene and tumour suppressor may not always apply. For instance, TP53 has been simultaneously associated with tumour suppressing and promoting activities. Here, we uncover a similar phenomenon for GATA3, a frequently mutated, yet poorly understood, breast cancer gene. We identify two functional classes of frameshift mutations that are associated with distinct expression profiles in tumours, differential disease-free patient survival and gain- and loss-of-function activities in a cell line model. Furthermore, we find an estrogen receptor-independent synthetic lethal interaction between a GATA3 frameshift mutant with an extended C-terminus and the histone methyltransferases G9A and GLP, indicating perturbed epigenetic regulation. Our findings reveal important insights into mutant GATA3 function and breast cancer, provide the first potential therapeutic strategy and suggest that dual tumour suppressive and oncogenic activities are more widespread than previously appreciated.