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Additional file 3: Figure S2. (File format .ppt). Identification and validation of the CSPG4 gene expression signature in STS samples. A/ Identification of the signature in the Chibon’s learning set (N=310). Left, Volcano-plot showing the 379 genes differentially expressed between “CSPG4-high” versus “CSPG4-low” STS samples. Middle, box plot of classification score (Pearson correlation, r) between both CSPG4 classes (Student t-test) associated with cross-table between observed and predicted CSPG4 groups (Fisher’s exact test). B/ Validation in the remaining public data sets (N=1,068). Box plot of classification score (Pearson correlation, r) between both CSPG4 classes (Student t-test) associated with cross-table between observed and predicted CSPG4 groups (Fisher’s exact test).

Additional file 6: Figure S5. (File format .ppt). Comparison of methylation site profiles between the “CSPG4-high” (N=101) and “CSPG4-low” (N=118) tumors. A/ Heatmap of methylation sites in which the 450,000 probes were sorted by chromosomal location and the 219 STS samples were sorted by their CSPG4 expression level. B/ Supervised analysis of methylation levels between the “CSPG4-high” vs. “CSPG4-low” tumors. The bar plotted values represent the –log10 corrected p-values of the Student t-test of the 84 significant probes with greater methylation in “CSPG4-high” (red) or in “CSPG4-low” (green).

Additional file 2: Figure S1. (File format .ppt). CSPG4 expression in clinical STS samples and cancer cell lines. A/ Box plot of mRNA expression levels in the 1,378 STS clinical samples. B/ Spearman’s rank correlation coefficient (rho) between mRNA (RNAseq data) and protein (RPPA) expression in 343 cancer cell lines (grey) including four sarcoma cell lines (orange).

Additional file 5: Figure S4. (File format .ppt). Distribution of mutations of the top 45 mutated genes in STS samples and comparison between the “CSPG4-high” (N=119) and “CSPG4-low” (N=126) tumors. A/ Heatmap of mutations across 45 genes with mutation rate greater than 3% over all patients. Genes were sorted according their global mutation rate (blue bar plot to the right) and the 245 tumors were sorted by their CSPG4 mRNA expression level. B/ Bar plot of mutation frequency according to the “CSPG4-high” (red) or “CSPG4-low” (green) status. Orange plotted values represent the -log10 p-values of the Fisher’s exact test. The vertical dashed orange line represents the significance threshold (i.e. p

Additional file 4: Figure S3. (File format .ppt). Comparison of the CNA profiles between the “CSPG4-high” (N=123) and “CSPG4-low” (N=132) tumors. A/ Heatmap of CNA in which the 24,776 genes were sorted by chromosomal location and the 255 STS samples were sorted by their CSPG4 mRNA expression level. B/ Left, frequency plots of CNA in both CSPG4 classes following four CNA levels: one-copy-gain (red), amplification (dark red), one-copy loss (green) and homozygous deletion (dark green). Loss alteration frequencies were negatively weighted. Right, supervised analysis of CNA frequencies between “CSPG4-high” vs. “CSPG4-low” tumors. Plotted values represent the –log10 corrected p-values of the Fisher’s exact test weighted by the sign of the odds ratio for each CNA level. The vertical orange lines represents the significance thresholds (i.e. q

Additional file 1. PERMED-01 protocol. The protocol of PERMED-01 trial.

Additional file 4: Supplementary Figures. Contains four Supplementary Figures showing the cancer types profiled and further NGA and aCGH results.

Additional file 2: Supplementary methods. Contains additional methods regarding the trial design, the genome analyses, the molecular precision oncology report and molecular tumor board, and the statistical analyses.

To clarify the function of cyclin A2 in colon homeostasis and colorectal cancer (CRC), we generated mice deficient for cyclin A2 in colonic epithelial cells (CEC). Colons of those mice displayed architectural changes in the mucosa, and signs of inflammation as well as an increased proliferation of CEC associated with the appearance of low- and high-grade dysplasia. The main initial events triggering those alterations in cyclin A2 deficient CEC appear to be abnormal mitoses and DNA damage. Cyclin A2 deletion in CEC promoted the development of dysplasia and adenocarcinomas in the murine colitis-associated cancer model. We next explored the status of cyclin A2 expression in clinical CRC samples at the mRNA and protein level and found higher expression in tumors of stage I and II patients compared to those of stage III and IV. A meta-analysis of 11 transcriptome datasets comprising 2,239 primary CRC tumors displayed different CCNA2 (the mRNA coding for cyclin A2) expression levels among the CRC tumor subtypes with highest in CMS1 and lowest in CMS4. Moreover, high expression of CCNA2 was found to be a new independent prognosis factor for CRC tumors.

Additional file 4: Supplementary Figures. Contains four Supplementary Figures showing the cancer types profiled and further NGA and aCGH results.

The association between pancreatic ductal adenocarcinoma (PDAC) location (head vs. Body/Tail (B/T)) and clinical outcome remains controversial. We collected clinicopathological and gene expression data from 249 resected PDAC samples from public data sets, and we compared data between 208 head and 41 B/T samples. The 2-year overall survival (OS) was better for the head than for the B/T PDACs (44 vs. 27%, p = 0.043), especially when comparing tumors with similar TNM classification (T3/4N0M0: 67% vs. 17%, p = 0.002) or from the same molecular class (squamous subtype: 31% vs. 0%, p &lt, 0.0001). Bailey&rsquo, s molecular subtypes were differentially distributed within the two groups, with the immunogenic subtype being underrepresented in the &ldquo, B/T&rdquo, group (p = 0.005). Uni- and multivariate analyses indicated that PDAC anatomic location was an independent prognostic factor. Finally, the supervised analysis identified 334 genes differentially expressed. Genes upregulated in the &ldquo, head&rdquo, group suggested lymphocyte activation and pancreas exocrine functions. Genes upregulated in the &ldquo, group were related to keratinocyte differentiation, in line with the enrichment for squamous phenotype. We identified a robust gene expression signature (GES) associated with B/T PDAC location, suggesting that head and B/T PDAC are different. This GES could serve as an indicator for differential therapeutic management based on PDAC location.

Figure S1. Related to Fig. 2: Heatmap of the H3K27me3 level in a new cohort of 78 NPM1mut CN-AML patients. Figure S2. Related to Fig. 2: Analysis of H3K27me3 HIST1 status in CD34low and CD34high sorted blasts. Figure S3 Related to Fig. 4. Representative Integrative Genomics Viewer (IGV) tracks of H3K27me3 signal obtained from ChIP-chip data published in Tiberi et al., 2015 Figure S4. Related to Fig. 5: Histone protein extraction in NPM1mut patients. Figure S5. Related to Fig. 5:Total protein abundance of each histone types determined by IBAQ label-free quantification method. Figure S6 related to Fig. 6. Effect of H1-3 KD on histone H1 subtype mRNA and protein expression. Figure S7 related to Fig. 6. Effect of H1d KD on CD11b expression in shRNA1 (clones KD#2 and KD#3) and in shRNA2 conditions. Figure S7 related to Figure 6. Effect of H1d KD on CD11b expression in shRNA1 (clones KD#2 and KD#3) and in shRNA2 conditions

Table S1. Clinical and molecular characteristics in the GOELAMS Cohort (n = 46) according to H3K27me3 HIST1 status. Table S2. Multivariate analyses in the validation CN-AML cohort (n = 46). Table S3. Univariate and Multivariate Analyses for 3-HIST1-mRNA signature in TCGA and Metzeler cohorts. Table S4. Clinical characteristics of NPM1mut patients selected for transcriptomic analysis.

Clinical trials have shown the benefits of FGFR inhibitors; notably, the oral pan-FGFR inhibitor JNJ-42756493 (erdafitinib) has recently been the first FGFR kinase inhibitor to receive US FDA approval for the treatment of patients with advanced or metastatic urothelial carcinoma. Our objectives were to show that the FGFR pathway is involved in liposarcoma (LPS) pathogenesis and to investigate the therapeutic potential of erdafitinib for LPS patients. LPS is the most common soft tissue sarcoma. Among LPS, well-differentiated/dedifferentiated LPS (WD/DDLPS) are the most frequent types. DDLPS have metastatic potential and a poor prognosis with a five-year mortality rate of 30%. Standard chemotherapies are inefficient and new therapeutic options are needed. FRS2, a crucial adaptor protein of the FGFR signaling pathway is overexpressed in most WD/DDLPS suggesting involvement of the FGFR pathway in LPS tumorigenesis. Immunohistochemistry was used to perform an exhaustive analysis of the expression pattern of FGFR1-4 in WD/DDLPS both in a large collection of 421 primary tumors and in our in-house panel of validated human WDLPS and DDLPS cell lines. Cells were exposed to erdafitinib - as a single agent or in combination - and apoptosis and signalling pathway perturbations were monitored by flow cytometry and western blotting. Xenograft mouse models were used to confirm our in vitro results in the in vivo setting. We have detected a high expression of FGFR1 and/or FGFR4 in a significant percentage of WDLPS and DDLPS and demonstrated that this expression is correlated with poor prognosis. Exposure of LPS cells to erdafitinib induced a decrease in cell viability, cell cycle arrest in G1 and apoptosis. Erdafitinib treatment had a strong inhibitory effect on the ERK1/2 pathway whereas the PI3K/AKT pathway was less affected. The PI3K/mTOR antagonist BEZ235 was not synergistic with erdafitinib in DDLPS cells. MDM2 overexpression being the hallmark of WD/DDLPS, we investigated the effects of the MDM2-TP53 interaction inhibitor RG7388 (idasanutlin) in combination with erdafitinib. Interestingly, we found that the combination of RG7388 and erdafitinib exerts a highly synergistic effect on both viability and apoptosis in all our WDLPS and DDLPS cell lines. We are currently investigating the mechanics of the synergy between the FGFR and the MDM2 antagonists. We confirmed the inhibitory effect of erdafitinib on tumor growth using a DDLPS xenograft model. Finally and importantly, we report the efficacy of FGFR inhibition in two metastatic DDLPS patients heavily pretreated and refractory to several lines of treatment with notably one patient on erdafitinib showing stable disease for 15 weeks. In conclusion, we have shown that the FGFR pathway has therapeutic potential for a subset of DDLPS patients and that FGFR expression might constitute a powerful biomarker to select patients for clinical trials testing FGFR inhibitors. Citation Format: Bérengère Dadone-Montaudié, Audrey Laroche-Clary, Aline Mongis, Vanessa Chaire, Ilaria Di Mauro, Renaud Schiappa, Emmanuel Chamorey, Bertucci François, Florence Pedeutour, Finetti Pascal, Jean-François Michiels, Antoine Italiano, Laurence Bianchini. Analysis of the role of FGFR signaling in liposarcomas: Dual targeting of FGFR and MDM2 is synergistic [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5185.

Introduction treatments targeting the Human Epidermal Growth Factor Receptor 2 (HER2/ERBB2) have improved the natural history of HER2-positive breast cancer. However, except HER2 protein expression and gene amplification, there is no predictive biomarker to guide the HER2-targeted therapies. We developed Parallel reaction monitoring (PRM) a powerful approach, to quantify and evaluate key proteins involved in the HER2 pathway and/or anti-HER2 treatment sensitivity. Results in BCLs, PRM measurements correlated with western blot immunocytochemistry and transcriptomic data. At baseline, higher expression of HER2, EGFR, PTEN and HER3 but lower expression of phospho-HER2 correlated with trastuzumab sensitivity. Under trastuzumab, PRM demonstrated a decrease in HER2 and an increase in phospho-HER2, which correlated with drug sensitivity. The opposite was observed under lapatinib. HER2 quantification was also correlated with immunohistochemistry in PDXs and clinical breast cancer samples. Discussion in conclusion, PRM-based assay, developed to quantify proteins of the HER2 pathway in breast cancer samples revealed a large magnitude of expression, which may have relevance in terms of treatment sensitivity. Materials and Methods we first evaluated PRM in term of sensitivity, linearity and reproducibility. PRM was then applied to breast cancer cell lines (BCLs) including BCLs exposed to anti-HER2 agents, patient-derived xenografts (PDXs) and frozen breast cancer samples.

Background Chronic lung rejection is characterized by obliterative bronchiolitis (OB) diagnosed based on spirometric criteria reflecting an already advanced process. Biologic markers such as bronchoalveolar lavage (BAL) neutrophilia or increased levels of chemokines (interleukin-8, RANTES [regulated on activation: normal T cell expressed and secreted]) have been proposed as early diagnosis tools. However, BAL is too invasive to be used as a routine strategy. Induced sputum (IS), however, is a non-invasive method of recovering bronchial cells. Methods The aim of this study was to compare BAL and IS differential cellular counts as well as IL-8 and RANTES levels between patients with bronchiolitis obliterans syndrome (BOS), recipients with good outcome and well-preserved lung function (non-BOS) and non-transplanted controls. We compared 34 BAL and IS findings obtained consecutively from 34 lung transplant recipients (LTRs), including 22 non-BOS and 12 BOS patients. Results IS results were compared with 19 samples from non-transplanted controls. IS was well tolerated. There was no correlation between BAL and sputum cell populations. BAL neutrophils and IL-8 levels were increased in BOS, and these parameters were positively correlated. Moreover, BAL neutrophils and IL-8 levels were both negatively correlated with respiratory function. Sputum evaluation allows discrimination of BOS from non-BOS by the presence of higher neutrophil and eosinophil counts. Moreover, IS neutrophils and eosinophils were both correlated with lung function parameters. In contrast to BAL, IL-8 level in sputum was not a useful predictive marker of BOS development. IS RANTES levels were higher in BOS than in healthy recipients and correlated significantly with IS eosinophils. Conclusions IS and BAL provide different but complementary data. In this study, IS appeared to be a useful, non-invasive tool for LTR monitoring. Furthermore, IS provides new insights into BOS pathogenesis, especially with regard to implication of eosinophils and its chemokine, RANTES, at the bronchial level.

Supplementary material and methods. Includes more detailed information about the methodology of the shRNA screens and the supplementary Tables 2 and 3. (DOCX 815 kb)

Supplementary material and methods. Includes more detailed information about the methodology of the shRNA screens and the supplementary Tables 2 and 3. (DOCX 815 kb)

International audience; Background: Prognosis of localised gastrointestinal stromal tumour (GIST) is heterogeneous, notably for patients with AFIP intermediate or high risk of relapse, who are candidates to adjuvant imatinib. We hypothesised that gene expression profiles might improve the prognostication and help to refine the indications for imatinib.Methods: We collected gene expression and histoclinical data of 146 pre-treatment localised GIST samples treated with surgery alone. We searched for a gene expression signature (GES) predictive for relapse-free survival (RFS) and compared its performances to that of three published prognostic proliferation-based GES (Genomic Grade Index (GGI), 16-Kinase, and CINSARC) and AFIP classification. We also analysed a data set from 28 patients with advanced GIST treated with neo-adjuvant imatinib.Results: We identified a 275-gene GES (gene expression signature) predictive of RFS in a learning set and validated its robustness in an independent set. However, the GGI outperformed its prognostic performances, and those of the two other signatures and the AFIP intermediate-risk classification in two independent tests sets in uni- and multivariate analyses. Importantly, GGI could split the AFIP intermediate/high-risk samples into two groups with different RFS. Genomic Grade Index 'high-risk' tumours were more proliferative and genetically unstable than 'low-risk' tumours, and more sensitive to imatinib.Conclusion: GGI refines the prediction of RFS in localised GIST and might help tailor adjuvant imatinib.

Oncogenic kinases of myeloproliferative disorders induce both protein synthesis and G1 activators