We describe two water‐soluble ruthenium complexes, [1]Cl₂ and [2]Cl₂, that photodissociate to release a cytotoxic nicotinamide phosphoribosyltransferase (NAMPT) inhibitor with a low dose (21 J cm⁻²) of red light in an oxygen‐independent manner. Using a specific NAMPT activity assay, up to an 18‐fold increase in inhibition potency was measured upon red‐light activation of [2]Cl₂, while [1]Cl₂ was thermally unstable. For the first time, the dark and red‐light‐induced cytotoxicity of these photocaged compounds could be tested under hypoxia (1 % O₂). In skin (A431) and lung (A549) cancer cells, a 3‐ to 4‐fold increase in cytotoxicity was found upon red‐light irradiation for [2]Cl₂, whether the cells were cultured and irradiated with 1 % or 21 % O₂. These results demonstrate the potential of photoactivated chemotherapy for hypoxic cancer cells, in which classical photodynamic therapy, which relies on oxygen activation, is poorly efficient.

Annexin A1 (AnxA1) is a candidate regulator of the epithelial- to mesenchymal (EMT)-like phenotypic switch, a pivotal event in breast cancer progression. We show here that AnxA1 expression is associated with a highly invasive basal-like breast cancer subtype both in a panel of human breast cancer cell lines as in breast cancer patients and that AnxA1 is functionally related to breast cancer progression. AnxA1 knockdown in invasive basal-like breast cancer cells reduced the number of spontaneous lung metastasis, whereas additional expression of AnxA1 enhanced metastatic spread. AnxA1 promotes metastasis formation by enhancing TGFβ/Smad signaling and actin reorganization, which facilitates an EMT-like switch, thereby allowing efficient cell migration and invasion of metastatic breast cancer cells.

Over the last decade, the field of cancer metabolism has mainly focused on studying the role of tumorigenic metabolic rewiring in supporting cancer proliferation. Here, we perform the first genome‐scale computational study of the metabolic underpinnings of cancer migration. We build genome‐scale metabolic models of the NCI‐60 cell lines that capture the Warburg effect (aerobic glycolysis) typically occurring in cancer cells. The extent of the Warburg effect in each of these cell line models is quantified by the ratio of glycolytic to oxidative ATP flux (AFR), which is found to be highly positively associated with cancer cell migration. We hence predicted that targeting genes that mitigate the Warburg effect by reducing the AFR may specifically inhibit cancer migration. By testing the anti‐migratory effects of silencing such 17 top predicted genes in four breast and lung cancer cell lines, we find that up to 13 of these novel predictions significantly attenuate cell migration either in all or one cell line only, while having almost no effect on cell proliferation. Furthermore, in accordance with the predictions, a significant reduction is observed in the ratio between experimentally measured ECAR and OCR levels following these perturbations. Inhibiting anti‐migratory targets is a promising future avenue in treating cancer since it may decrease cytotoxic‐related side effects that plague current anti‐proliferative treatments. Furthermore, it may reduce cytotoxic‐related clonal selection of more aggressive cancer cells and the likelihood of emerging resistance.

Utilizing molecular data to derive functional physiological models tailored for specific cancer cells can facilitate the use of individually tailored therapies. To this end we present an approach termed PRIME for generating cell-specific genome-scale metabolic models (GSMMs) based on molecular and phenotypic data. We build >280 models of normal and cancer cell-lines that successfully predict metabolic phenotypes in an individual manner. We utilize this set of cell-specific models to predict drug targets that selectively inhibit cancerous but not normal cell proliferation. The top predicted target, MLYCD, is experimentally validated and the metabolic effects of MLYCD depletion investigated. Furthermore, we tested cell-specific predicted responses to the inhibition of metabolic enzymes, and successfully inferred the prognosis of cancer patients based on their PRIME-derived individual GSMMs. These results lay a computational basis and a counterpart experimental proof of concept for future personalized metabolic modeling applications, enhancing the search for novel selective anticancer therapies.

Tumor cell migration is a key process for cancer cell dissemination and metastasis that is controlled by signal-mediated cytoskeletal and cell matrix adhesion remodeling. Using a phagokinetic track assay with migratory H1299 cells, we performed an siRNA screen of almost 1,500 genes encoding kinases/phosphatases and adhesome- and migration-related proteins to identify genes that affect tumor cell migration speed and persistence. Thirty candidate genes that altered cell migration were validated in live tumor cell migration assays. Eight were associated with metastasis-free survival in breast cancer patients, with integrin β₃–binding protein (ITGB3BP), MAP3K8, NIMA-related kinase (NEK2), and SHC-transforming protein 1 (SHC1) being the most predictive. Examination of genes that modulate migration indicated that SRPK1, encoding the splicing factor kinase SRSF protein kinase 1, is relevant to breast cancer outcomes, as it was highly expressed in basal breast cancer. Furthermore, high SRPK1 expression correlated with poor breast cancer disease outcome and preferential metastasis to the lungs and brain. In 2 independent murine models of breast tumor metastasis, stable shRNA-based SRPK1 knockdown suppressed metastasis to distant organs, including lung, liver, and spleen, and inhibited focal adhesion reorganization. Our study provides comprehensive information on the molecular determinants of tumor cell migration and suggests that SRPK1 has potential as a drug target for limiting breast cancer metastasis.

Purpose: Therapies directed to specific molecular targets are still unmet for patients with triple-negative breast cancer (TNBC). Deubiquitinases (DUB) are emerging drug targets. The identification of highly active DUBs in TNBC may lead to novel therapies. Experimental Design: Using DUB activity probes, we profiled global DUB activities in 52 breast cancer cell lines and 52 patients9 tumor tissues. To validate our findings in vivo, we employed both zebrafish and murine breast cancer xenograft models. Cellular and molecular mechanisms were elucidated using in vivo and in vitro biochemical methods. A specific inhibitor was synthesized, and its biochemical and biological functions were assessed in a range of assays. Finally, we used patient sera samples to investigate clinical correlations. Results: Two DUB activity profiling approaches identified UCHL1 as being highly active in TNBC cell lines and aggressive tumors. Functionally, UCHL1 promoted metastasis in zebrafish and murine breast cancer xenograft models. Mechanistically, UCHL1 facilitates TGFβ signaling–induced metastasis by protecting TGFβ type I receptor and SMAD2 from ubiquitination. We found that these responses are potently suppressed by the specific UCHL1 inhibitor, 6RK73. Furthermore, UCHL1 levels were significantly increased in sera of patients with TNBC, and highly enriched in sera exosomes as well as TNBC cell–conditioned media. UCHL1-enriched exosomes stimulated breast cancer migration and extravasation, suggesting that UCHL1 may act in a paracrine manner to promote tumor progression. Conclusions: Our DUB activity profiling identified UCHL1 as a candidate oncoprotein that promotes TGFβ-induced breast cancer metastasis and may provide a potential target for TNBC treatment.