Much interest is currently focused on the emerging role of tumorstroma interactions essential for supporting tumor progression. Carcinoma-associated fibroblasts (CAFs), frequently present in the stroma of human breast carcinomas, include a large number of myofibroblasts, a hallmark of activated fibroblasts. These fibroblasts have an ability to substantially promote tumorigenesis. However, the precise cellular origins of CAFs and the molecular mechanisms by which these cells evolve into tumor-promoting myofibroblasts remain unclear. Using a coimplantation breast tumor xenograft model, we show that resident human mammary fibroblasts progressively convert into CAF myofibroblasts during the course of tumor progression. These cells increasingly acquire two autocrine signaling loops, mediated by TGF-β and SDF-1 cytokines, which both act in autostimulatory and cross-communicating fashions. These autocrine-signaling loops initiate and maintain the differentiation of fibroblasts into myofibroblasts and the concurrent tumor-promoting phenotype. Collectively, these findings indicate that the establishment of the self-sustaining TGF-β and SDF-1 autocrine signaling gives rise to tumor-promoting CAF myofibroblasts during tumor progression. This autocrine-signaling mechanism may prove to be an attractive therapeutic target to block the evolution of tumor-promoting CAFs.CXCR4 | Smad | tumor microenvironment | alpha-smooth muscle actin M yofibroblasts are often observed in the stroma of various human carcinomas that include those of the breast (1). The presence of these cells in large numbers is also associated with higher-grade malignancy and poor prognosis in patients (2-4). Myofibroblasts express α-smooth muscle actin (α-SMA) that distinguishes these cells from fibroblasts and represents a hallmark of activated fibroblasts (5-10). The activated myofibroblast state of stromal fibroblasts also correlates with their ability to promote tumor growth (11)(12)(13)(14). Although different types of mesenchymal cells and epithelial cells are proposed to be precursors of the myofibroblasts present in tumors (15-20), their precise cellular origins and functional contributions to tumor growth still remain unclear.In recent years, the tumor-promoting roles of stromal fibroblasts and α-SMA-positive myofibroblasts, collectively termed carcinoma-associated fibroblasts (CAFs), have been studied (21). CAFs, when inoculated with carcinoma cells, have potently promoted the in vivo proliferation of carcinoma cells and tumor growth in mouse xenograft models (14,(21)(22)(23)(24)(25). We previously demonstrated that CAFs, prepared directly from invasive human mammary carcinomas, contain substantial numbers of myofibroblasts that secrete elevated levels of the proangiogenic chemokine, stromal cell-derived factor-1 (SDF-1, also called CXCL12) (14). SDF-1 signaling via its cognate receptor CXCR4, expressed on the surface of carcinoma cells, directly boosts the proliferation of these cells and can stimulate neoangiogenesis by recruiting circulating endot...

The vast majority of cancer next-generation sequencing data consist of bulk samples composed of mixtures of cancer and normal cells. To study tumor evolution, subclonal reconstruction approaches based on machine learning are used to separate subpopulation of cancer cells and reconstruct their ancestral relationships. However, current approaches are entirely data-driven and agnostic to evolutionary theory. We demonstrate that systematic errors occur in subclonal reconstruction if tumor evolution is not accounted for, and that those errors increase when multiple samples are taken from the same tumor. To address this issue, we present a novel approach for model-based subclonal reconstruction that combines data-driven machine learning with evolutionary theory. Using public, synthetic and newly generated data, we show the method is more robust and accurate than current techniques in both single-sample and multi-region sequencing data. With careful data curation and interpretation, we show how the method allows minimizing the confounding factors that affect non-evolutionary methods, leading to a more accurate recovery of the evolutionary history of human tumors..

SummaryBreast cancers (BCs) typically express estrogen receptors (ERs) but frequently exhibit de novo or acquired resistance to hormonal therapies. Here, we show that short-term treatment with the anti-estrogens tamoxifen or fulvestrant decrease cell proliferation but increase BC stem cell (BCSC) activity through JAG1-NOTCH4 receptor activation both in patient-derived samples and xenograft (PDX) tumors. In support of this mechanism, we demonstrate that high ALDH1 predicts resistance in women treated with tamoxifen and that a NOTCH4/HES/HEY gene signature predicts for a poor response/prognosis in 2 ER+ patient cohorts. Targeting of NOTCH4 reverses the increase in Notch and BCSC activity induced by anti-estrogens. Importantly, in PDX tumors with acquired tamoxifen resistance, NOTCH4 inhibition reduced BCSC activity. Thus, we establish that BCSC and NOTCH4 activities predict both de novo and acquired tamoxifen resistance and that combining endocrine therapy with targeting JAG1-NOTCH4 overcomes resistance in human breast cancers.

Numerous models have been developed to quantify the combined effect of various risk factors to predict either risk of developing breast cancer, risk of carrying a high-risk germline genetic mutation, specifically in the BRCA1 and BRCA2 genes, or the risk of both. These breast cancer risk models can be separated into those that utilize mainly hormonal and environmental factors and those that focus more on hereditary risk. Given the wide range of models from which to choose, understanding what each model predicts, the populations for which each is best suited to provide risk estimations, the current validation and comparative studies that have been performed for each model, and how to apply them practically is important for clinicians and researchers seeking to utilize risk models in their practice. This review provides a comprehensive guide for those seeking to understand and apply breast cancer risk models by summarizing the majority of existing breast cancer risk prediction models including the risk factors they incorporate, the basic methodology in their development, the information each provides, their strengths and limitations, relevant validation studies, and how to access each for clinical or investigative purposes.

Drug resistance mediated by clonal evolution is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at a cost of decreased fecundity or increased sensitivity to another drug. These evolutionary trade-offs can be exploited using 'evolutionary steering' to control the tumour population and delay resistance. However, recapitulating cancer evolutionary dynamics experimentally remains challenging. Here, we present an approach for evolutionary steering based on a combination of single-cell barcoding, large populations of 10 8-10 9 cells grown without re-plating, longitudinal nondestructive monitoring of cancer clones, and mathematical modelling of tumour evolution. We demonstrate evolutionary steering in a lung cancer model, showing that it shifts the clonal composition of the tumour in our favour, leading to collateral sensitivity and proliferative costs. Genomic profiling revealed some of the mechanisms that drive evolved sensitivity. This approach allows modelling evolutionary steering strategies that can potentially control treatment resistance.

Transforming growth factor-beta (TGF-β) is a pleiotropic cytokine with the capability to act as tumour suppressor or tumour promoter depending on the cellular context. TGF-beta receptor type-2 (TGFBR2) is the ligand-binding receptor for all members of the TGF-β family. Data from mouse model experiments demonstrated that loss of Tgfbr2 expression in mammary fibroblasts was linked to tumour initiation and metastasis. Using a randomised tamoxifen trial cohort including in total 564 invasive breast carcinomas, we examined TGFBR2 expression (n=252) and phosphorylation level of downstream target SMAD2 (pSMAD2) (n=319) in cancer-associated fibroblasts (CAFs) and assessed links to clinicopathological markers, prognostic and treatment-predictive values. The study revealed that CAF-specific TGFBR2 expression correlated with improved recurrence-free survival. Multivariate analysis confirmed CAF-TGFBR2 to be an independent prognostic marker (multivariate Cox regression, hazard ratio: 0.534, 95% (CI): 0.360-0.793, P=0.002). CAF-specific pSMAD2 levels, however, did not associate with survival outcome. Experimentally, TGF-β signalling in fibroblasts was modulated using a TGF-β ligand and inhibitor or through lentiviral short hairpin RNA-mediated TGFBR2-specific knockdown. To determine the role of fibroblastic TGF-β pathway on breast cancer cells, we used cell contact-dependent cell growth and clonogenicity assays, which showed that knockdown of TGFBR2 in CAFs resulted in increased cell growth, proliferation and clonogenic survival. Further, in a mouse model transfected CAFs were co-injected with MCF7 and tumour weight and proportion was monitored. We found that mouse xenograft tumours comprising TGFBR2 knockdown fibroblasts were slightly bigger and displayed increased tumour cell capacity. Overall, our data demonstrate that fibroblast-related biomarkers possess clinically relevant information and that fibroblasts confer effects on breast cancer cell growth and survival. Regulation of tumour-stromal cross-talk through fibroblastic TGF-β pathway may depend on fibroblast phenotype, emphasising the importance to characterise tumour microenvironment subtypes.

Notch and Wnt are highly conserved signalling pathways that are used repeatedly throughout animal development to generate a diverse array of cell types. However, they often have opposing effects on cell-fate decisions with each pathway promoting an alternate outcome. Commonly, a cell receiving both signals exhibits only Wnt pathway activity. This suggests that Wnt inhibits Notch activity to promote a Wnt-ON/Notch-OFF output; but what might underpin this Notch regulation is not understood. Here, we show that Wnt acts via Dishevelled to inhibit Notch signalling, and that this crosstalk regulates cell-fate specification in vivo during Xenopus development. Mechanistically, Dishevelled binds and directly inhibits CSL transcription factors downstream of Notch receptors, reducing their activity. Furthermore, our data suggest that this crosstalk mechanism is conserved between vertebrate and invertebrate homologues. Thus, we identify a dual function for Dishevelled as an inhibitor of Notch signalling and an activator of the Wnt pathway that sharpens the distinction between opposing Wnt and Notch responses, allowing for robust cell-fate decisions.

Background Glioblastoma is the most common and aggressive adult brain malignancy against which conventional surgery and chemoradiation provide limited benefit. Even when a good treatment response is obtained, recurrence inevitably occurs either locally (∼80%) or distally (∼20%), driven by cancer clones that are often genomically distinct from those in the primary tumour. Glioblastoma cells display a characteristic infiltrative phenotype, invading the surrounding tissue and often spreading across the whole brain. Cancer cells responsible for relapse can reside in two compartments of residual disease that are left behind after treatment: the infiltrated normal brain parenchyma and the sub-ventricular zone. However, these two sources of residual disease in glioblastoma are understudied because of the difficulty in sampling these regions during surgery. Patient and methods Here, we present the results of whole-exome sequencing of 69 multi-region samples collected using fluorescence-guided resection from 11 patients, including the infiltrating tumour margin and the sub-ventricular zone for each patient, as well as matched blood. We used a phylogenomic approach to dissect the spatio-temporal evolution of each tumour and unveil the relation between residual disease and the main tumour mass. We also analysed two patients with paired primary-recurrence samples with matched residual disease. Results Our results suggest that infiltrative subclones can arise early during tumour growth in a subset of patients. After treatment, the infiltrative subclones may seed the growth of a recurrent tumour, thus representing the ‘missing link’ between the primary tumour and recurrent disease. Conclusions These results are consistent with recognised clinical phenotypic behaviour and suggest that more specific therapeutic targeting of cells in the infiltrated brain parenchyma may improve patient’s outcome.