Biology subjects

Pozo, K.

Publications and source records attributed to Pozo, K..

3 recordsLinked to original sources

bioRxiv2020

ASCL1 represses a latent osteogenic program in small cell lung cancer in multiple cells of origin

ASCL1 is a neuroendocrine-lineage-specific oncogenic driver of small cell lung cancer (SCLC), highly expressed in a significant fraction of tumors. However, ~25% of human SCLC are ASCL1-low and associated with low-neuroendocrine fate and high MYC expression. Using genetically-engineered mouse models (GEMMs), we show that alterations in Rb1/Trp53/Myc in the mouse lung induce an ASCL1+ state of SCLC in multiple cells of origin. Genetic depletion of ASCL1 in MYC-driven SCLC dramatically inhibits tumor initiation and progression to the NEUROD1+ subtype of SCLC. Surprisingly, ASCL1 loss converts tumors to a SOX9+ mesenchymal/neural-crest-stem-like state that can differentiate into RUNX2+ bone tumors. ASCL1 represses SOX9 expression, as well as WNT and NOTCH developmental pathways, consistent with human gene expression data. Together, SCLC demonstrates remarkable cell fate plasticity with ASCL1 repressing the emergence of non-endodermal stem-like fates that have the capacity for bone differentiation.

cancer biology↗

bioRxiv2020

Lineage transcription factors co-regulate subtype-specific genes providing a roadmap for systematic identification of small cell lung cancer vulnerabilities

Lineage-defining transcription factors (LTFs) play key roles in tumor cell growth, making them highly attractive, but currently "undruggable", small cell lung cancer (SCLC) vulnerabilities. Delineating LTF genomic binding sites and associated chromatin features would provide important insights into SCLC dependencies. Here we map super-enhancers (SEs) across multiple patient-derived SCLC preclinical models, and find SE patterns are sufficient to classify the models into the recently defined, LTF-based, SCLC subtypes. 3D-chromatin conformation analysis identified genes associated with SEs that define subtype-specific tumor signatures with genes functioning in diverse processes. Focusing on ASCL1-high SCLC (SCLC-A), we found ASCL1 physically interacts with NKX2-1 and PROX1. These factors bind overlapping genomic regions, and co-regulate a set of genes, including genes encoding cell surface proteins, SCN3A and KCNB2 enriched in SCLC-A. Genetic depletion of NKX2-1 or PROX1 alone, or in combinations with ASCL1, did not inhibit SCLC growth more than that achieved by depleting ASCL1 alone. We demonstrate the SE signature supports the LTF classification of SCLC, identify NKX2-1 and PROX1 as ASCL1 co-factors, and substantiate the central importance of ASCL1 as a key dependency factor in the majority of SCLC. The LTF and SE gene sets provide a molecular roadmap for future ASCL1 therapeutic targeting studies.

cancer biology↗

bioRxiv2019

Phosphoprotein-based Biomarkers as Predictors for Cancer Therapy

Disparities in cancer patient responses have prompted widespread searches to identify differences in sensitive vs. non-sensitive populations and form the basis of personalized medicine. This customized approach is dependent upon the development of pathway-specific therapeutics in conjunction with biomarkers that predict patient responses. Here, we show that Cdk5 drives growth in subgroups of human patients with multiple types of neuroendocrine neoplasms. Phosphoproteomics and high throughput screening identified novel phosphorylation sites downstream of Cdk5. These phosphorylation events serve as biomarkers of Cdk5 activity and effectively pinpoint Cdk5-driven tumors. Toward achieving targeted therapy, we demonstrate that mouse models of neuroendocrine cancer are responsive to selective Cdk5 inhibitors and biomimetic nanoparticles are effective vehicles for enhanced tumor targeting and reduction of drug toxicity. Finally, we show that biomarkers of Cdk5-dependent tumors effectively predict response to anti-Cdk5 therapy in patient-derived xenografts. Thus, a phosphoprotein-based diagnostic assay combined with Cdk5-targeted therapy is a rational treatment approach for neuroendocrine malignancies.

cancer biology↗