Resistance to chemotherapy is a challenging problem for treatment of cancer patients and autophagy has been shown to mediate development of resistance. In this study we systematically screened a library of 306 known anti-cancer drugs for their ability to induce autophagy using a cell-based assay. 114 of the drugs were classified as autophagy inducers; for 16 drugs, the cytotoxicity was potentiated by siRNA-mediated knock-down of Atg7 and Vps34. These drugs were further evaluated in breast cancer cell lines for autophagy induction, and two tyrosine kinase inhibitors, Sunitinib and Erlotinib, were selected for further studies. For the pharmacological inhibition of autophagy, we have characterized here a novel highly potent selective inhibitor of Vps34, SB02024. SB02024 blocked autophagy in vitro and reduced xenograft growth of two breast cancer cell lines, MDA-MB-231 and MCF-7, in vivo. Vps34 inhibitor significantly potentiated cytotoxicity of Sunitinib and Erlotinib in MCF-7 and MDA-MB-231 in vitro in monolayer cultures and when grown as multicellular spheroids. Our data suggests that inhibition of autophagy significantly improves sensitivity to Sunitinib and Erlotinib and that Vps34 is a promising therapeutic target for combination strategies in breast cancer.

Image-based profiling has emerged as a powerful technology for various steps in basic biological and pharmaceutical discovery, but the community has lacked a large, public reference set of data from chemical and genetic perturbations. Here we present data generated by the Joint Undertaking for Morphological Profiling (JUMP)-Cell Painting Consortium, a collaboration between 10 pharmaceutical companies, six supporting technology companies, and two non-profit partners. When completed, the dataset will contain images and profiles from the Cell Painting assay for over 116,750 unique compounds, over-expression of 12,602 genes, and knockout of 7,975 genes using CRISPR-Cas9, all in human osteosarcoma cells (U2OS). The dataset is estimated to be 115 TB in size and capturing 1.6 billion cells and their single-cell profiles. File quality control and upload is underway and will be completed over the coming months at the Cell Painting Gallery: https://registry.opendata.aws/cellpainting-gallery. A portal to visualize a subset of the data is available at https://phenaid.ardigen.com/jumpcpexplorer/.

Tuberculosis has been reaffirmed as the infectious disease causing most deaths in the world. Co-infection with HIV and the increase in multi-drug resistant Mycobacterium tuberculosis strains complicate treatment and increases mortality rates, making the development of new drugs an urgent priority. In this study we have identified a promising candidate by screening antimicrobial peptides for their capacity to inhibit mycobacterial growth. This non-toxic peptide, NZX, is capable of inhibiting both clinical strains of M. tuberculosis and an MDR strain at therapeutic concentrations. The therapeutic potential of NZX is further supported in vivo where NZX significantly lowered the bacterial load with only five days of treatment, comparable to rifampicin treatment over the same period. NZX possesses intracellular inhibitory capacity and co-localizes with intracellular bacteria in infected murine lungs. In conclusion, the data presented strongly supports the therapeutic potential of NZX in future anti-TB treatment.