A global cancer data integrator reveals principles of synthetic lethality, sex disparity and immunotherapy

BACKGROUND

Advances in cancer biology are increasingly dependent on integration of heterogeneous datasets. Large-scale efforts have systematically mapped many aspects of cancer cell biology; however, it remains challenging for individual scientists to effectively integrate and understand this data.

RESULTS

We have developed a new data retrieval and indexing framework that allows us to integrate publicly available data from different sources and to combine publicly available data with new or bespoke datasets. Our approach, which we have named the cancer data integrator (CanDI), is straightforward to implement, is well documented, and is continuously updated which should enable individual users to take full advantage of efforts to map cancer cell biology. We show that CanDI empowered testable hypotheses of new synthetic lethal gene pairs, genes associated with sex disparity, and immunotherapy targets in cancer.

CONCLUSIONS

CanDI provides a flexible approach for large-scale data integration in cancer research enabling rapid generation of hypotheses. The CanDI data integrator is available at https://github.com/GilbertLabUCSF/CanDI .

An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer

Genomic sequencing of thousands of tumors has revealed many genes associated with specific types of cancer. Similarly, large scale CRISPR functional genomics efforts have mapped genes required for cancer cell proliferation or survival in hundreds of cell lines. Despite this, for specific disease subtypes, such as metastatic prostate cancer, there are likely a number of undiscovered tumor specific driver genes that may represent potential drug targets. To identify such genetic dependencies, we performed genome-scale CRISPRi screens in metastatic prostate cancer models. We then created a pipeline in which we integrated pan-cancer functional genomics data with our metastatic prostate cancer functional and clinical genomics data to identify genes that can drive aggressive prostate cancer phenotypes. Our integrative analysis of these data reveals known prostate cancer specific driver genes, such as AR and HOXB13, as well as a number of top hits that are poorly characterized. In this study we highlight the strength of an integrated clinical and functional genomics pipeline and focus on two top hit genes, KIF4A and WDR62. We demonstrate that both KIF4A and WDR62 drive aggressive prostate cancer phenotypes in vitro and in vivo in multiple models, irrespective of AR-status, and are also associated with poor patient outcome.

Hybrid nanocarriers incorporating mechanistically distinct drugs for lymphatic CD4+ T cell activation and HIV-1 latency reversal

A proposed strategy to cure HIV uses latency-reversing agents (LRAs) to reactivate latent proviruses for purging HIV reservoirs. A variety of LRAs have been identified, but none has yet proven effective in reducing the reservoir size in vivo. Nanocarriers could address some major challenges by improving drug solubility and safety, providing sustained drug release, and simultaneously delivering multiple drugs to target tissues and cells. Here, we formulated hybrid nanocarriers that incorporate physicochemically diverse LRAs and target lymphatic CD4+ T cells. We identified one LRA combination that displayed synergistic latency reversal and low cytotoxicity in a cell model of HIV and in CD4+ T cells from virologically suppressed patients. Furthermore, our targeted nanocarriers selectively activated CD4+ T cells in nonhuman primate peripheral blood mononuclear cells as well as in murine lymph nodes, and substantially reduced local toxicity. This nanocarrier platform may enable new solutions for delivering anti-HIV agents for an HIV cure.