BACH2 inhibition reverses ß cell failure in type 2 diabetes models.

Type 2 diabetes (T2D) is associated with defective insulin secretion and reduced ß cell mass. Available treatments provide a temporary reprieve, but secondary failure rates are high, making insulin supplementation necessary. Reversibility of ß cell failure is a key translational question. Here, we reverse engineered and interrogated pancreatic islet-specific regulatory networks to discover T2D-specific subpopulations characterized by metabolic inflexibility and endocrine progenitor/stem cell features. Single-cell gain- and loss-of-function and glucose-induced Ca2+ flux analyses of top candidate master regulatory (MR) proteins in islet cells validated transcription factor BACH2 and associated epigenetic effectors as key drivers of T2D cell states. BACH2 knockout in T2D islets reversed cellular features of the disease, restoring a nondiabetic phenotype. BACH2-immunoreactive islet cells increased approximately 4-fold in diabetic patients, confirming the algorithmic prediction of clinically relevant subpopulations. Treatment with a BACH inhibitor lowered glycemia and increased plasma insulin levels in diabetic mice, and restored insulin secretion in diabetic mice and human islets. The findings suggest that T2D-specific populations of failing ß cells can be reversed and indicate pathways for pharmacological intervention, including via BACH2 inhibition.

A case study of an integrative genomic and experimental therapeutic approach for rare tumors: identification of vulnerabilities in a pediatric poorly differentiated carcinoma.

BACKGROUND: Precision medicine approaches are ideally suited for rare tumors where comprehensive characterization may have diagnostic, prognostic, and therapeutic value. We describe the clinical case and molecular characterization of an adolescent with metastatic poorly differentiated carcinoma (PDC). Given the rarity and poor prognosis associated with PDC in children, we utilized genomic analysis and preclinical models to validate oncogenic drivers and identify molecular vulnerabilities. METHODS: We utilized whole exome sequencing (WES) and transcriptome analysis to identify germline and somatic alterations in the patient's tumor. In silico and in vitro studies were used to determine the functional consequences of genomic alterations. Primary tumor was used to generate a patient-derived xenograft (PDX) model, which was used for in vivo assessment of predicted therapeutic options. RESULTS: WES revealed a novel germline frameshift variant (p.E1554fs) in APC, establishing a diagnosis of Gardner syndrome, along with a somatic nonsense (p.R790*) APC mutation in the tumor. Somatic mutations in TP53, MAX, BRAF, ROS1, and RPTOR were also identified and transcriptome and immunohistochemical analyses suggested hyperactivation of the Wnt/ß-catenin and AKT/mTOR pathways. In silico and biochemical assays demonstrated that the MAX p.R60Q and BRAF p.K483E mutations were activating mutations, whereas the ROS1 and RPTOR mutations were of lower utility for therapeutic targeting. Utilizing a patient-specific PDX model, we demonstrated in vivo activity of mTOR inhibition with temsirolimus and partial response to inhibition of MEK. CONCLUSIONS: This clinical case illustrates the depth of investigation necessary to fully characterize the functional significance of the breadth of alterations identified through genomic analysis.

Predicting Drug Response in Human Prostate Cancer from Preclinical Analysis of In Vivo Mouse Models.

Although genetically engineered mouse (GEM) models are often used to evaluate cancer therapies, extrapolation of such preclinical data to human cancer can be challenging. Here, we introduce an approach that uses drug perturbation data from GEM models to predict drug efficacy in human cancer. Network-based analysis of expression profiles from in vivo treatment of GEM models identified drugs and drug combinations that inhibit the activity of FOXM1 and CENPF, which are master regulators of prostate cancer malignancy. Validation of mouse and human prostate cancer models confirmed the specificity and synergy of a predicted drug combination to abrogate FOXM1/CENPF activity and inhibit tumorigenicity. Network-based analysis of treatment signatures from GEM models identified treatment-responsive genes in human prostate cancer that are potential biomarkers of patient response. More generally, this approach allows systematic identification of drugs that inhibit tumor dependencies, thereby improving the utility of GEM models for prioritizing drugs for clinical evaluation.

Hypothalamic proteoglycan syndecan-3 is a novel cocaine addiction resilience factor.

Proteoglycans like syndecan-3 have complex signaling roles in addition to their function as structural components of the extracellular matrix. Here, we show that syndecan-3 in the lateral hypothalamus has an unexpected new role in limiting compulsive cocaine intake. In particular, we observe that syndecan-3 null mice self-administer greater amounts of cocaine than wild-type mice. This effect can be rescued by re-expression of syndecan-3 in the lateral hypothalamus with an adeno-associated viral vector. Adeno-associated viral vector delivery of syndecan-3 to the lateral hypothalamus also reduces motivation for cocaine in normal mice. Syndecan-3 limits cocaine intake by modulating the effects of glial-cell-line-derived neurotrophic factor, which uses syndecan-3 as an alternative receptor. Our findings indicate syndecan-3-dependent signaling as a novel therapeutic target for the treatment of cocaine addiction.

A complementary role for ELF3 and TFL1 in the regulation of flowering time by ambient temperature.

Plants regulate their time to flowering by gathering information from the environment. Photoperiod and temperature are among the most important environmental variables. Sub-optimal, but not near-freezing, temperatures regulate flowering through the thermosensory pathway, which overlaps with the autonomous pathway. Here we show that ambient temperature regulates flowering by two genetically distinguishable pathways, one requiring TFL1 and another requiring ELF3. The delay in flowering time observed at lower temperatures was partially suppressed in single elf3 and tfl1 mutants, whereas double elf3 tfl1 mutants were insensitive to temperature. tfl1 mutations abolished the temperature response in cryptochrome mutants that are deficient in photoperiod perception, but not in phyB mutants, which have a constitutive photoperiodic response. In contrast to tfl1, elf3 mutations were able to suppress the temperature response in phyB mutants, but not in cryptochrome mutants. Gene expression profiles revealed that the tfl1 and elf3 effects are due to the activation of different sets of genes, and identified CCA1 and SOC1/AGL20 as being important cross-talk points. Finally, genome-wide gene expression analysis strongly suggests a general and complementary role for ELF3 and TFL1 in temperature signalling.