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. 2014 Oct;6(10):1279-93.
doi: 10.15252/emmm.201404208.

"V体育平台登录" Epithelial-mesenchymal transition spectrum quantification and its efficacy in deciphering survival and drug responses of cancer patients

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Epithelial-mesenchymal transition spectrum quantification and its efficacy in deciphering survival and drug responses of cancer patients

Tuan Zea Tan et al. EMBO Mol Med. 2014 Oct.

Abstract

Epithelial-mesenchymal transition (EMT) is a reversible and dynamic process hypothesized to be co-opted by carcinoma during invasion and metastasis. Yet, there is still no quantitative measure to assess the interplay between EMT and cancer progression. Here, we derived a method for universal EMT scoring from cancer-specific transcriptomic EMT signatures of ovarian, breast, bladder, lung, colorectal and gastric cancers VSports手机版. We show that EMT scoring exhibits good correlation with previously published, cancer-specific EMT signatures. This universal and quantitative EMT scoring was used to establish an EMT spectrum across various cancers, with good correlation noted between cell lines and tumours. We show correlations between EMT and poorer disease-free survival in ovarian and colorectal, but not breast, carcinomas, despite previous notions. Importantly, we found distinct responses between epithelial- and mesenchymal-like ovarian cancers to therapeutic regimes administered with or without paclitaxel in vivo and demonstrated that mesenchymal-like tumours do not always show resistance to chemotherapy. EMT scoring is thus a promising, versatile tool for the objective and systematic investigation of EMT roles and dynamics in cancer progression, treatment response and survival. .

Keywords: drug response; epithelial‐mesenchymal transition; gene expression signature; microarray; prognosis V体育安卓版. .

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Figures

Figure 1
Figure 1. Derivation and application of cancer-specific epithelial-mesenchymal transition (EMT) signature
  1. A six-step scheme illustrating the generation of a cancer-specific EMT signature. Note that tumours and cell lines have their own cancer-specific EMT signatures. (Top right panel) Red and green bars on sample enrichment score (ES) bar chart indicate, respectively, mesenchymal-like (Mes) and epithelial-like (Epi) samples selected for building the BinReg EMT signature. (Middle right panel) Heatmap of the EMT signature from Significance Analysis of Microarray (SAM)/Receiver Operating Characteristics (ROC) analysis. The colour bar shows the EMT phenotype probability of cell line or tumour samples, sorted from most Epi to most Mes VSports注册入口. Red and green bars indicate Mes and Epi samples selected for SAM/ROC analysis. (Bottom right panel) Plots of empirical cumulative distribution function of Mes (red) and Epi (green) gene sets.

  2. Dot plot of EMT score (mean ± SEM) for breast cancer cell lines (n = 34) with spindle- and non-spindle-like morphologies. Mann–WhitneyU-testP-value is shown V体育官网入口.

  3. Immunohistochemistry staining heatmap of Oestrogen Receptor (ER), Progesterone Receptor (PR), and Epi (CDH1, ERBB2, CK19) as well as Mes (CK5, VIM, CDH2) markers (black = low, red = high, white = no data). Breast cancer cell lines (n = 39) are aligned from the most Epi to most Mes based on the EMT score, as shown by the bar chart. Dot plot is the-log10P-value of two-sample Kolmogorov–Smirnov test. Arbitrary threshold ofP < 0. 001 was used to define Epi, intermediate and Mes cell lines. Breast cancer cell line microarrays and subtype are from GSE16795 (Hollestelleet al, 2010). Subtype colour code: blue, Luminal; maroon, Basal VSports在线直播.

Figure 2
Figure 2. Derivation and application of generic epithelial-mesenchymal transition (EMT) signature
  1. Circos plot illustrating the generic EMT signature: the overlap of ovarian (blue), breast (purple), lung (green), colorectal (yellow), bladder (red) and gastric (orange) cancer-specific EMT signatures is shown. Links indicate overlapping genes (red = mesenchymal, green = epithelial). Heatmap on the inner ring indicates weight computed based on Significance Analysis of Microarray (SAM) fold-change, false discovery rate, Receiver Operating Characteristics (ROC) and number of samples of a gene in each cancer-specific EMT signature (red = high, blue = low weight). On the outermost ring, genes are represented by ticks and aligned from the highest SAM fold-change to the lowest for each cancer type. Selected genes are labelled.

  2. EMT score (mean ± SEM;y-axis) of breast cancer molecular subtypes as predicted using ssGSEA and signature from Pratet al (2010) in non-laser-capture micro-dissected (non-LCM) cohort (= 3,992; upper panel) and LCM cohort (= 417; lower panel). The Mann–WhitneyU-testP-value of binary comparison for each subtype is given. Colour code: maroon, Basal; yellow, Claudin-low; light blue, Luminal-A; dark blue, Luminal-B; orange, ERBB2+; green, Normal-like. N.A, not applicable. Note that noP-value is available for Claudin-low and Normal-like subtypes in lower panel becausen < 3.

Figure 3
Figure 3. Epithelial-mesenchymal transition (EMT) scores in different cancers types
Scatter plot of EMT scores (mean ± SEM;y-axis) of various cancers in clinical samples (upper panel) and cell lines (lower panel) sorted by cancer type and mean EMT score. EMT score nearer to +1.0 is more mesenchymal-like (Mes), whereas EMT score nearer to −1.0 is more epithelial-like (Epi). EMT scores of overlapping cell lines in Cancer Cell Line Encyclopedia (CCLE) (Barretinaet al, 2012) and SANGER/COSMIC (Garnettet al, 2012) collections were averaged.
Figure 4
Figure 4. Correlation of Epithelial-mesenchymal transition (EMT) scores and survival
A, B Plot of log2 hazard ratio (HR; mean ± 95% confidence interval) comparing (A) overall survival (OS) and (B) disease-free survival (DFS) of Epi and Mes tumours in different cancers and cohorts. DFS includes progression-free, recurrence-free and distant metastasis-free survival (cohorts inclusive of distant metastasis-free survival were indicated with *). CorrespondingP-values from the log-rank test are given next to each cohort, and those with significant differences (P < 0.05) are marked red. Log2 HR < 0.0 indicates Epi tumours with survival benefit, whereas log2 HR > 0.0 indicates Mes tumours with survival benefit. Meta-analysisP-value for effect or heterogeneity was computed using DerSimonian–Laird binary random effect (for overall) or Peto fixed effect method (for individual cancer).
Figure 5
Figure 5. Generic epithelial-mesenchymal transition (EMT) and drug sensitivity
  1. Bar plots of breast (= 270; left panel) and ovarian (= 328; right panel) cancers stratified by EMT status and clinical response based on response evaluation criteria in solid tumours (RECIST). Regimen was neoadjuvant doxorubicin and cyclophosphamide for breast cancer, and platinum-based adjuvant/progression/recurrence chemotherapy for ovarian cancer. Percentage distribution of EMT status is given in each clinical response group. Abbreviation: CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease. Green, epithelial-like (Epi); orange, intermediate; red, mesenchymal-like (Mes).

  2. Volcano plot of EMT correlation with drug sensitivity regardless of cancer type.Rho ∈ [−1.0, +1.0] (x-axis) and-log10P-value (y-axis) were computed by Spearman's correlation coefficient test. Dashed line ofP-value = 0.1 is plotted. Red and green indicate higher drug resistance in Mes tumours (Rho ∈ [0, +1.0]) and Epi tumours (Rho ∈ [−1.0, 0]), respectively.

  3. Kaplan–Meier analysis comparing overall survival (left panel) and disease-free survival (right panel) of Epi (green) and Mes (red) ovarian cancer patients who underwent a treatment regimen with (dark colour) or without (light colour) paclitaxel.P-value reported was computed by log-rank test. Abbreviation: HR = hazard ratio.

References

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