Fuhai Li

Epithelial-to-mesenchymal transition is not required for lung metastasis but contributes to chemoresistance.

The role of epithelial-to-mesenchymal transition (EMT) in metastasis is a longstanding source of debate, largely owing to an inability to monitor transient and reversible EMT phenotypes in vivo. Here we establish an EMT lineage-tracing system to monitor this process in mice, using a mesenchymal-specific Cre-mediated fluorescent marker switch system in spontaneous breast-to-lung metastasis models. We show that within a predominantly epithelial primary tumour, a small proportion of tumour cells undergo EMT. Notably, lung metastases mainly consist of non-EMT tumour cells that maintain their epithelial phenotype. Inhibiting EMT by overexpressing the microRNA miR-200 does not affect lung metastasis development. However, EMT cells significantly contribute to recurrent lung metastasis formation after chemotherapy. These cells survived cyclophosphamide treatment owing to reduced proliferation, apoptotic tolerance and increased expression of chemoresistance-related genes. Overexpression of miR-200 abrogated this resistance. This study suggests the potential of an EMT-targeting strategy, in conjunction with conventional chemotherapies, for breast cancer treatment.The role of epithelial to mesenchymal transition (EMT) in metastasis is a longstanding source of controversy, largely due to an inability to monitor transient and reversible EMT phenotypes in vivo. We established an EMT lineage tracing system to monitor this process, using a mesenchymal-specific Cre-mediated fluorescent marker switch system in spontaneous breast-to-lung metastasis models. We confirmed that within a predominantly epithelial primary tumor, a small portion of tumor cells undergo EMT. Strikingly, lung metastases mainly consisted of non-EMT tumor cells maintaining their epithelial phenotype. Inhibiting EMT by overexpressing miR-200 did not impact lung metastasis development. However, EMT cells significantly contribute to recurrent lung metastasis formation after chemotherapy. These cells survived cyclophosphamide treatment due to reduced proliferation, apoptotic tolerance, and elevated expression of chemoresistance-related genes. Overexpression of miR-200 abrogated this resistance. This study suggests the potential of an EMT-targeting strategy, in conjunction with conventional chemotherapies, for breast cancer treatment.

Reprogramming of the tumour microenvironment by stromal PTEN-regulated miR-320

PTEN (Phosphatase and tensin homolog deleted on chromosome 10) expression in stromal fibroblasts suppresses epithelial mammary tumours, but the underlying molecular mechanisms remain unknown. Using proteomic and expression profiling, we show that Pten loss from mammary stromal fibroblasts activates an oncogenic secretome that orchestrates the transcriptional reprogramming of other cell types in the microenvironment. Downregulation of miR-320 and upregulation of one of its direct targets, ETS2 (v-ets erythroblastosis virus E26 oncogene homolog 2) are critical events in Pten-deleted stromal fibroblasts responsible for inducing this oncogenic secretome, which in turn promotes tumour angiogenesis and tumour-cell invasion. Expression of the Pten–miR-320–Ets2-regulated secretome distinguished human normal breast stroma from tumour stroma and robustly correlated with recurrence in breast cancer patients. This work reveals miR-320 as a critical component of the Pten tumour-suppressor axis that acts in stromal fibroblasts to reprogramme the tumour microenvironment and curtail tumourxa0progression.

Trisomy represses Apc(Min)-mediated tumours in mouse models of Down's syndrome.

Epidemiological studies spanning more than 50 yr reach conflicting conclusions as to whether there is a lower incidence of solid tumours in people with trisomy 21 (Down’s syndrome). We used mouse models of Down’s syndrome and of cancer in a biological approach to investigate the relationship between trisomy and the incidence of intestinal tumours. ApcMin-mediated tumour number was determined in aneuploid mouse models Ts65Dn, Ts1Rhr and Ms1Rhr. Trisomy for orthologues of about half of the genes on chromosome 21 (Hsa21) in Ts65Dn mice or just 33 of these genes in Ts1Rhr mice resulted in a significant reduction in the number of intestinal tumours. In Ms1Rhr, segmental monosomy for the same 33 genes that are triplicated in Ts1Rhr resulted in an increased number of tumours. Further studies demonstrated that the Ets2 gene contributed most of the dosage-sensitive effect on intestinal tumour number. The action of Ets2 as a repressor when it is overexpressed differs from tumour suppression, which requires normal gene function to prevent cellular transformation. Upregulation of Ets2 and, potentially, other genes involved in this kind of protective effect may provide a prophylactic effect in all individuals, regardless of ploidy.

A Screen for Morphological Complexity Identifies Regulators of Switch-like Transitions between Discrete Cell Shapes

The way in which cells adopt different morphologies is not fully understood. Cell shape could be a continuous variable or restricted to a set of discrete forms. We developed quantitative methods to describe cell shape and show that Drosophila haemocytes in culture are a heterogeneous mixture of five discrete morphologies. In an RNAi screen of genes affecting the morphological complexity of heterogeneous cell populations, we found that most genes regulate the transition between discrete shapes rather than generating new morphologies. In particular, we identified a subset of genes, including the tumour suppressor PTEN, that decrease the heterogeneity of the population, leading to populations enriched in rounded or elongated forms. We show that these genes have a highly conserved function as regulators of cell shape in both mouse and human metastatic melanoma cells.

Label-free high-resolution imaging of prostate glands and cavernous nerves using coherent anti-Stokes Raman scattering microscopy

A custom built coherent anti-Stokes Raman scattering (CARS) microscope was used to image prostatic glands and nerve structures from 17 patients undergoing radical prostatectomy. Imaging of glandular and nerve structures showed distinctive cellular features that correlated to histological stains. Segmentation of cell nucleus was performed to establish a cell feature-based model to separate normal glands from cancer glands. In this study, we use a single parameter, average cell neighbor distance based on CARS imaging, to characterize normal and cancerous glandular structures. By combining CARS with our novel classification model, we are able to characterize prostate glandular and nerve structures in a manner that potentially enables real-time, intra-operative assessment of surgical margins and neurovascular bundles. As such, this method could potentially improve outcomes following radical prostatectomy.

DrugComboRanker: drug combination discovery based on target network analysis

Motivation: Currently there are no curative anticancer drugs, and drug resistance is often acquired after drug treatment. One of the reasons is that cancers are complex diseases, regulated by multiple signaling pathways and cross talks among the pathways. It is expected that drug combinations can reduce drug resistance and improve patients’ outcomes. In clinical practice, the ideal and feasible drug combinations are combinations of existing Food and Drug Administration-approved drugs or bioactive compounds that are already used on patients or have entered clinical trials and passed safety tests. These drug combinations could directly be used on patients with less concern of toxic effects. However, there is so far no effective computational approach to search effective drug combinations from the enormous number of possibilities. Results: In this study, we propose a novel systematic computational tool DrugComboRanker to prioritize synergistic drug combinations and uncover their mechanisms of action. We first build a drug functional network based on their genomic profiles, and partition the network into numerous drug network communities by using a Bayesian non-negative matrix factorization approach. As drugs within overlapping community share common mechanisms of action, we next uncover potential targets of drugs by applying a recommendation system on drug communities. We meanwhile build disease-specific signaling networks based on patients’ genomic profiles and interactome data. We then identify drug combinations by searching drugs whose targets are enriched in the complementary signaling modules of the disease signaling network. The novel method was evaluated on lung adenocarcinoma and endocrine receptor positive breast cancer, and compared with other drug combination approaches. These case studies discovered a set of effective drug combinations top ranked in our prediction list, and mapped the drug targets on the disease signaling network to highlight the mechanisms of action of the drug combinations. Availability and implementation: The program is available on request. Contact: stwong@tmhs.org

Pten in the breast tumor microenvironment: modeling tumor-stroma coevolution.

Solid human tumors and their surrounding microenvironment are hypothesized to coevolve in a manner that promotes tumor growth, invasiveness, and spread. Mouse models of cancer have focused on genetic changes in the epithelial tumor cells and therefore have not robustly tested this hypothesis. We have recently developed a murine breast cancer model that ablates the PTEN tumor suppressor pathway in stromal fibroblasts. Remarkably, the model resembles human breast tumors both at morphologic and molecular levels. We propose that such models reflect subtypes of tumor-stromal coevolution relevant to human breast cancer, and will therefore be useful in defining the mechanisms that underpin tumor-stroma cross-talk. Additionally, these models should also aid in molecularly classifying human breast tumors on the basis of both the microenvironment subtypes they contain as well as on the tumor subtype.

Image-Based Chemical Screening Identifies Drug Efflux Inhibitors In Lung Cancer Cells

Cancer cells with active drug efflux capability are multidrug resistant and pose a significant obstacle for the efficacy of chemotherapy. Moreover, recent evidence suggests that high drug efflux cancer cells (HDECC) may be selectively enriched with stem-like cancer cells, which are believed to be the cause for tumor initiation and recurrence. There is a great need for therapeutic reagents that are capable of eliminating HDECCs. We developed an image-based high-content screening (HCS) system to specifically identify and analyze the HDECC population in lung cancer cells. Using the system, we screened 1,280 pharmacologically active compounds that identified 12 potent HDECC inhibitors. It is shown that these inhibitors are able to overcome multidrug resistance (MDR) and sensitize HDECCs to chemotherapeutic drugs, or directly reduce the tumorigenicity of lung cancer cells possibly by affecting stem-like cancer cells. The HCS system we established provides a new approach for identifying therapeutic reagents overcoming MDR. The compounds identified by the screening may potentially be used as potential adjuvant to improve the efficacy of chemotherapeutic drugs.

Transcriptome Analysis of Individual Stromal Cell Populations Identifies Stroma-Tumor Crosstalk in Mouse Lung Cancer Model

Emerging studies have begun to demonstrate that reprogrammed stromal cells play pivotal roles in tumor growth, metastasis, and resistance to therapy. However, the contribution of stromal cells to non-small-cell lung cancer (NSCLC) has remained underexplored. We used an orthotopic model of Kras-driven NSCLC to systematically dissect the contribution of specific hematopoietic stromal cells in lung cancer. RNA deep-sequencing analysis of individually sorted myeloid lineage and tumor epithelial cells revealed cell-type-specific differentially regulated genes, indicative of activated stroma. We developed a computational model for crosstalk signaling discovery based on ligand-receptor interactions and downstream signaling networks and identified known and novel tumor-stroma paracrine and tumor autocrine crosstalk-signaling pathways in NSCLC. We provide cellular and molecular insights into components of the lung cancer microenvironment that contribute toxa0carcinogenesis. This study has the potential for development of therapeutic strategies that target tumor-stroma interactions and may complement conventional anti-cancer treatments.

Differential Diagnosis of Lung Carcinoma With Coherent Anti-Stokes Raman Scattering Imaging

Aimed at bridging imaging technology development with cancer diagnosis, this paper first presents the prevailing challenges of lung cancer detection and diagnosis, with an emphasis on imaging techniques. It then elaborates on the working principle of coherent anti-Stokes Raman scattering microscopy, along with a description of pathologic applications to show the effectiveness and potential of this novel technology for lung cancer diagnosis. As a nonlinear optical technique probing intrinsic molecular vibrations, coherent anti-Stokes Raman scattering microscopy offers an unparalleled, label-free strategy for clinical cancer diagnosis and allows differential diagnosis of fresh specimens based on cell morphology information and patterns, without any histology staining. This powerful feature promises a higher biopsy yield for early cancer detection by incorporating a real-time imaging feed with a biopsy needle. In addition, molecularly targeted therapies would also benefit from early access to surgical specimen with high accuracy but minimum tissue consumption, therefore potentially saving specimens for follow-up diagnostic tests. Finally, we also introduce the potential of a coherent anti-Stokes Raman scattering-based endoscopy system to support intraoperative applications at the cellular level.