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Background The epithelial-mesenchymal transition (EMT) enables dissociation of tumour cells from the primary tumour mass, invasion through the extracellular matrix, intravasation into blood vessels and colonisation of distant organs. Cells that revert to the epithelial state via the mesenchymal-epithelial transition cause metastases, the primary cause of death in cancer patients. EMT also empowers cancer cells with stem-cell properties and induces resistance to chemotherapeutic drugs. Understanding the driving factors of EMT is critical for the development of effective therapeutic interventions. Methods This manuscript describes the generation of a database containing EMT gene signatures derived from cell lines, patient-derived xenografts and patient studies across cancer types and multiomics data and the creation of a web-based portal to provide a comprehensive analysis resource. Results EMTome incorporates (i) EMT gene signatures; (ii) EMT-related genes with multiomics features across different cancer types; (iii) interactomes of EMT-related genes (miRNAs, transcription factors, and proteins); (iv) immune profiles identified from The Cancer Genome Atlas (TCGA) cohorts by exploring transcriptomics, epigenomics, and proteomics, and drug sensitivity and (iv) clinical outcomes of cancer cohorts linked to EMT gene signatures. Conclusion The web-based EMTome portal is a resource for primary and metastatic tumour research publicly available at www.emtome.org .

Oncogenic KRAS expression generates a metabolic dependency on aerobic glycolysis, known as the Warburg effect. We report an effect of increased glycolytic flux that feeds into glycosphingolipid biosynthesis and is directly linked to KRAS oncogenic function. High resolution imaging and genetic approaches show that a defined subset of outer leaflet glycosphingolipids, including GM3 and SM4, is required to maintain KRAS plasma membrane localization, with GM3 engaging in cross-bilayer coupling to maintain inner leaflet phosphatidylserine content. Thus, glycolysis is critical for KRAS plasma membrane localization and nanoscale spatial organization. Reciprocally oncogenic KRAS selectively upregulates cellular content of these same glycosphingolipids, whose depletion in turn abrogates KRAS oncogenesis in pancreatic cancer models. Our findings expand the role of the Warburg effect beyond ATP generation and biomass building to high-level regulation of KRAS function. The positive feedforward loop between oncogenic KRAS signaling and glycosphingolipid synthesis represents a vulnerability with therapeutic potential. KRAS is a small GTPase that regulates cell proliferation. Here, the authors show that a subset of cell surface glycosphingolipids regulate KRAS plasma membrane localization by modulating inner leaflet lipid composition, uncovering a requirement for KRAS oncogenesis that may have therapeutic potential.

Background Triple-negative breast cancers (TNBCs), which lack receptors for estrogen, progesterone, and amplification of epidermal growth factor receptor 2, are highly aggressive. Consequently, patients diagnosed with TNBCs have reduced overall and disease-free survival rates compared to patients with other subtypes of breast cancer. TNBCs are characterized by the presence of cancer cells with mesenchymal properties, indicating that the epithelial to mesenchymal transition (EMT) plays a major role in the progression of this disease. The EMT program has also been implicated in chemoresistance, tumor recurrence, and induction of cancer stem cell (CSC) properties. Currently, there are no targeted therapies for TNBC, and hence, it is critical to identify the novel targets to treat TNBC. Methods A library of compounds was screened for their ability to inhibit EMT in cells with mesenchymal phenotype as assessed using the previously described Z-cad reporters. Of the several drugs tested, GSK3β inhibitors were identified as EMT inhibitors. The effects of GSK3β inhibitors on the properties of TNBC cells with a mesenchymal phenotype were assessed using qRT-PCR, flow cytometry, western blot, mammosphere, and migration and cell viability assays. Publicly available datasets also were analyzed to examine if the expression of GSK3β correlates with the overall survival of breast cancer patients. Results We identified a GSK3β inhibitor, BIO, in a drug screen as one of the most potent inhibitors of EMT. BIO and two other GSK3β inhibitors, TWS119 and LiCl, also decreased the expression of mesenchymal markers in several different cell lines with a mesenchymal phenotype. Further, inhibition of GSK3β reduced EMT-related migratory properties of cells with mesenchymal properties. To determine if GSK3β inhibitors target mesenchymal-like cells by affecting the CSC population, we employed mammosphere assays and profiled the stem cell-related cell surface marker CD44+/24− in cells after exposure to GSK3β inhibitors. We found that GSK3β inhibitors indeed decreased the CSC properties of cell types with mesenchymal properties. We treated cells with epithelial and mesenchymal properties with GSK3β inhibitors and found that GSK3β inhibitors selectively kill cells with mesenchymal attributes while sparing cells with epithelial properties. We analyzed patient data to identify genes predictive of poor clinical outcome that could serve as novel therapeutic targets for TNBC. The Wnt signaling pathway is critical to EMT, but among the various factors known to be involved in Wnt signaling, only the higher expression of GSK3β correlated with poorer overall patient survival. Conclusions Taken together, our data demonstrate that GSK3β is a potential target for TNBCs and suggest that GSK3β inhibitors could serve as selective inhibitors of EMT and CSC properties for the treatment of a subset of aggressive TNBC. GSK3β inhibitors should be tested for use in combination with standard-of-care drugs in preclinical TNBC models.

Publications comparing variant caller algorithms present discordant results with contradictory rankings. Caller performances are inconsistent and wide ranging, and dependent upon input data, application, parameter settings, and evaluation metric. With no single variant caller emerging as a superior standard, combinations or ensembles of variant callers have appeared in the literature. In this study, a whole genome somatic reference standard was used to derive principles to guide strategies for combining variant calls. Then, manually annotated variants called from the whole exome sequencing of a tumor were used to corroborate these general principles. Finally, we examined the ability of these principles to reduce noise in targeted sequencing.

Most triple negative breast cancers (TNBCs) are aggressively metastatic with a high degree of intra-tumoral heterogeneity (ITH), but how ITH contributes to metastasis is unclear. Here, clonal dynamics during metastasis were studied in vivo using two patient-derived xenograft (PDX) models established from the treatment-naive primary breast tumors of TNBC patients diagnosed with synchronous metastasis. Genomic sequencing and high-complexity barcode-mediated clonal tracking reveal robust alterations in clonal architecture between primary tumors and corresponding metastases. Polyclonal seeding and maintenance of heterogeneous populations of low-abundance subclones is observed in each metastasis. However, lung, liver, and brain metastases are enriched for an identical population of high-abundance subclones, demonstrating that primary tumor clones harbor properties enabling them to seed and thrive in multiple organ sites. Further, clones that dominate multi-organ metastases share a genomic lineage. Thus, intrinsic properties of rare primary tumor subclones enable the seeding and colonization of metastases in secondary organs in these models. It is unclear how intra-tumoral heterogeneity contributes to metastasis. Here the authors study the clonal dynamics of triple negative breast cancer metastasis using patient derived xenografts and demonstrate that primary tumor clones harbor properties that support seeding and colonization of multiple organs.

Immune evasion by cancer cells involves reshaping the tumor microenvironment (TME) via communication with non-malignant cells. However, resistance-promoting interactions during treatment remain lesser known. Here we examine the composition, communication, and phenotypes of tumor-associated cells in serial biopsies from stage II and III high-risk estrogen receptor positive (ER+ ) breast cancers of patients receiving endocrine therapy (letrozole) as single agent or in combination with ribociclib, a CDK4/6-targeting cell cycle inhibitor. Single-cell RNA sequencing analyses on longitudinally collected samples show that in tumors overcoming the growth suppressive effects of ribociclib, first cancer cells upregulate cytokines and growth factors that stimulate immune-suppressive myeloid differentiation, resulting in reduced myeloid cell- CD8 + T-cell crosstalk via IL-15/18 signaling. Subsequently, tumors growing during treatment show diminished T-cell activation and recruitment. In vitro, ribociclib does not only inhibit cancer cell growth but also T cell proliferation and activation upon co-culturing. Exogenous IL-15 improves CDK4/6 inhibitor efficacy by augmenting T-cell proliferation and cancer cell killing by T cells. In summary, response to ribociclib in stage II and III high-risk ER +  breast cancer depends on the composition, activation phenotypes and communication network of immune cells. The CDK4/6 inhibitor ribociclib holds promise in cancer therapy but how cell cycle inhibitory drugs affect the anti-tumor immune response remains a question. Here authors show that poor response of early-stage estrogen receptor positive breast cancers to ribociclib is caused by changes in the immune cell composition and cancer-cell-immune-cell communication in the tumors rather than intrinsic cancer cell resistance to cell cycle inhibition.

Pancreatic ductal adenocarcinoma (PDAC) is the third leading cause of cancer-related death in the United States. Despite the high prevalence of Kras mutations in pancreatic cancer patients, murine models expressing the oncogenic mutant Kras (Krasmut) in mature pancreatic cells develop PDAC at a low frequency. Independent of cell of origin, a second genetic hit (loss of tumor suppressor TP53 or PTEN) is important for development of PDAC in mice. We hypothesized ectopic expression and elevated levels of oncogenic mutant Kras would promote PanIN arising in pancreatic ducts. To test our hypothesis, the significance of elevating levels of K-Ras and Ras activity has been explored by expression of a CAG driven LGSL-KrasG12V allele (cKras) in pancreatic ducts, which promotes ectopic Kras expression. We predicted expression of cKras in pancreatic ducts would generate neoplasia and PDAC. To test our hypothesis, we employed tamoxifen dependent CreERT2 mediated recombination. Hnf1b:CreERT2;KrasG12V (cKrasHnf1b/+) mice received 1 (Low), 5 (Mod) or 10 (High) mg per 20 g body weight to recombine cKras in low (cKrasLow), moderate (cKrasMod), and high (cKrasHigh) percentages of pancreatic ducts. Our histologic analysis revealed poorly differentiated aggressive tumors in cKrasHigh mice. cKrasMod mice had grades of Pancreatic Intraepithelial Neoplasia (PanIN), recapitulating early and advanced PanIN observed in human PDAC. Proteomics analysis revealed significant differences in PTEN/AKT and MAPK pathways between wild type, cKrasLow, cKrasMod, and cKrasHigh mice. In conclusion, in this study, we provide evidence that ectopic expression of oncogenic mutant K-Ras in pancreatic ducts generates early and late PanIN as well as PDAC. This Ras rheostat model provides evidence that AKT signaling is an important early driver of invasive ductal derived PDAC. In this study, the authors provide evidence that ectopic expression of oncogenic mutant Kras in pancreatic ducts generates early and late (PanIN) and pancreatic ductal adenocarcinoma (PDAC) . They characterized this Ras rheostat model which reveals elevated Kras mutation frequency and loss of PTEN are important drivers of PanIN and invasive ductal derived PDAC.

Tumors are comprised of subpopulations of cancer cells that harbor distinct genetic profiles and phenotypes that evolve over time and during treatment. By reconstructing the course of cancer evolution, we can understand the acquisition of the malignant properties that drive tumor progression. Unfortunately, recovering the evolutionary relationships of individual cancer cells linked to their phenotypes remains a difficult challenge. To address this need, we have developed PhylinSic, a method that reconstructs the phylogenetic relationships among cells linked to their gene expression profiles from single cell RNA-sequencing (scRNA-Seq) data. This method calls nucleotide bases using a probabilistic smoothing approach and then estimates a phylogenetic tree using a Bayesian modeling algorithm. We showed that PhylinSic identified evolutionary relationships underpinning drug selection and metastasis and was sensitive enough to identify subclones from genetic drift. We found that breast cancer tumors resistant to chemotherapies harbored multiple genetic lineages that independently acquired high K-Ras and β-catenin, suggesting that therapeutic strategies may need to control multiple lineages to be durable. These results demonstrated that PhylinSic can reconstruct evolution and link the genotypes and phenotypes of cells across monophyletic tumors using scRNA-Seq.

Background The RhoA activating protein Net1 contributes to breast cancer cell proliferation, motility, and invasion in vitro, yet little is known about its roles in mammary gland tumorigenesis and metastasis. Methods Net1 knockout (KO) mice were bred to mice with mammary gland specific expression of the polyoma middle T antigen (PyMT) oncogene. Mammary gland tumorigenesis and lung metastasis were monitored. Individual tumors were assessed for proliferation, apoptosis, angiogenesis, RhoA activation, and activation of PyMT-dependent signaling pathways. Primary tumor cells from wild-type and Net1 KO mice were transplanted into the mammary glands of wild-type, nontumor-bearing mice, and tumor growth and metastasis were assessed. Gene expression in wild-type and Net1 KO tumors was analyzed by gene ontology enrichment and for relative activation of gene expression signatures indicative of signaling pathways important for breast cancer initiation and progression. A gene expression signature indicative of Net1 function was identified. Human breast cancer gene expression profiles were screened for the presence of a Net1 gene expression signature. Results We show that Net1 makes fundamental contributions to mammary gland tumorigenesis and metastasis. Net1 deletion delays tumorigenesis and strongly suppresses metastasis in PyMT-expressing mice. Moreover, we observe that loss of Net1 reduces cancer cell proliferation, inhibits tumor angiogenesis, and promotes tumor cell apoptosis. Net1 is required for maximal RhoA activation within tumors and for primary tumor cell motility. Furthermore, the ability of PyMT to initiate oncogenic signaling to ERK1/2 and PI3K/Akt1 is inhibited by Net1 deletion. Primary tumor cell transplantation indicates that the reduction in tumor angiogenesis and lung metastasis observed upon Net1 deletion are tumor cell autonomous effects. Using a gene expression signature indicative of Net1 activity, we show that Net1 signaling is activated in 10% of human breast cancers, and that this correlates with elevated proliferation and PI3K pathway activity. We also demonstrate that human breast cancer patients with a high Net1 gene expression signature experience shorter distant metastasis-free survival. Conclusions These data indicate that Net1 is required for tumor progression in the PyMT mouse model and suggest that Net1 may contribute to breast cancer progression in humans.

Tumour profiling advances Molecular tumour profiling is one way in which effective targeted cancer treatment regimes might be developed. Two groups report significant developments in this direction. Bild et al . studied gene expression patterns that reflect the activation of various oncogenic (cancer-causing) signal transduction pathways. Using combinations of these pathway signatures, they predict which patients with breast, lung or ovarian cancer have a particularly poor prognosis. The ability to identify molecular pathways that are deregulated in a particular cancer in this way might be used to predict its sensitivity to specific therapeutic drugs. Solit et al . studied tumour cells with mutations in the RAS and BRAF genes, thought to cause cancer at least in part by activating the MEK/ERK signalling pathway. They show that tumours with the BRAF mutation, but not RAS, are highly sensitive to PD0325901, an MEK inhibitor that is in early-stage clinical trials in patients with melanoma, colon, breast and lung cancers. So by testing for the presence of BRAF mutations it may be possible to identify those patients most likely to benefit from this type of drug. The development of an oncogenic state is a complex process involving the accumulation of multiple independent mutations that lead to deregulation of cell signalling pathways central to the control of cell growth and cell fate 1 , 2 , 3 . The ability to define cancer subtypes, recurrence of disease and response to specific therapies using DNA microarray-based gene expression signatures has been demonstrated in multiple studies 4 . Various studies have also demonstrated the potential for using gene expression profiles for the analysis of oncogenic pathways 5 , 6 , 7 , 8 , 9 , 10 , 11 . Here we show that gene expression signatures can be identified that reflect the activation status of several oncogenic pathways. When evaluated in several large collections of human cancers, these gene expression signatures identify patterns of pathway deregulation in tumours and clinically relevant associations with disease outcomes. Combining signature-based predictions across several pathways identifies coordinated patterns of pathway deregulation that distinguish between specific cancers and tumour subtypes. Clustering tumours based on pathway signatures further defines prognosis in respective patient subsets, demonstrating that patterns of oncogenic pathway deregulation underlie the development of the oncogenic phenotype and reflect the biology and outcome of specific cancers. Predictions of pathway deregulation in cancer cell lines are also shown to predict the sensitivity to therapeutic agents that target components of the pathway. Linking pathway deregulation with sensitivity to therapeutics that target components of the pathway provides an opportunity to make use of these oncogenic pathway signatures to guide the use of targeted therapeutics.