Altered growth factor responses in phospho-protein-driven signaling networks are crucial to cancer cell survival and pathology. Profiles of cancer cell signaling networks might therefore identify mechanisms by which such cells interpret environmental cues for continued growth. Using multiparameter flow cytometry, we monitored phospho-protein responses to environmental cues in acute myeloid leukemia at the single cell level. By exposing cancer cell signaling networks to potentiating inputs, rather than relying upon the basal levels of protein phosphorylation alone, we could discern unique cancer network profiles that correlated with genetics and disease outcome. Strikingly, individual cancers manifested multiple cell subsets with unique network profiles, reflecting cancer heterogeneity at the level of signaling response. The results revealed a dramatic remodeling of signaling networks in cancer cells. Thus, single cell measurements of phospho-protein responses reveal shifts in signaling potential of a phospho-protein network, allowing for categorizing of cell network phenotypes by multidimensional molecular profiles of signaling.

Metastasis underlies the majority of cancer-related deaths. Thus, furthering our understanding of the molecular mechanisms that enable tumor cell dissemination is a vital health issue. Epithelialto-mesenchymal transitions (EMTs) endow carcinoma cells with enhanced migratory and survival attributes that facilitate malignant progression. Characterization of EMT effectors is likely to yield new insights into metastasis and novel avenues for treatment. We show that the presence of the receptor tyrosine kinase Axl in primary breast cancers independently predicts strongly reduced overall patient survival, and that matched patient metastatic lesions show enhanced Axl expression. We demonstrate that Axl is strongly induced by EMT in immortalized mammary epithelial cells that establishes an autocrine signaling loop with its ligand, Gas6. Epiallelic RNA interference analysis in metastatic breast cancer cells delineated a distinct threshold of Axl expression for mesenchymal-like in vitro cell invasiveness and formation of tumors in foreign and tissue-engineered microenvironments in vivo. Importantly, in two different optical imagingbased experimental breast cancer models, Axl knockdown completely prevented the spread of highly metastatic breast carcinoma cells from the mammary gland to lymph nodes and several major organs and increased overall survival. These findings suggest that Axl represents a downstream effector of the tumor cell EMT that is required for breast cancer metastasis. Thus, the detection and targeted treatment of Axl-expressing tumors represents an important new therapeutic strategy for breast cancer.carcinoma | receptor tyrosine kinase | breast cancer

We present an individualized systems medicine (ISM) approach to optimize cancer drug therapies one patient at a time. ISM is based on (i) molecular profi ling and ex vivo drug sensitivity and resistance testing (DSRT) of patients' cancer cells to 187 oncology drugs, (ii) clinical implementation of therapies predicted to be effective, and (iii) studying consecutive samples from the treated patients to understand the basis of resistance. Here, application of ISM to 28 samples from patients with acute myeloid leukemia (AML) uncovered fi ve major taxonomic drug-response subtypes based on DSRT profi les, some with distinct genomic features (e.g., MLL gene fusions in subgroup IV and FLT3 -ITD mutations in subgroup V). Therapy based on DSRT resulted in several clinical responses. After progression under DSRT-guided therapies, AML cells displayed signifi cant clonal evolution and novel genomic changes potentially explaining resistance, whereas ex vivo DSRT data showed resistance to the clinically applied drugs and new vulnerabilities to previously ineffective drugs. SIGNIFICANCE:Here, we demonstrate an ISM strategy to optimize safe and effective personalized cancer therapies for individual patients as well as to understand and predict disease evolution and the next line of therapy. This approach could facilitate systematic drug repositioning of approved targeted drugs as well as help to prioritize and de-risk emerging drugs for clinical testing.