Supplementary Figure 5 | Clustering (n=106) and survival analysis (n=70) on kinome mutations and CNA. (A) Disease-specific survival of patients (n=70) grouped on ARID1A status, (B) PIK3CA status and (C) ARID1A + PIK3CA status. (D) Consensus clustering, with maximum group count set to 10 and clustering optimization with 1000 repetitions maximum, shows adding of tumors (n=106) as consensus index (horizontally) and empirical cumulative distribution (vertically) for 1-10 clusters. (E) Area under the curve plot of decrease in friction from 1-10 clusters. (F) Heatmap distribution of tumors in 8 clusters. (G) Disease-specific survival of patients (n=70) in 8 clusters, (H) cluster 3 vs. other clusters. (I) Disease-specific survival in advanced stage OCCC patients (FIGO 2C-4), Log rank (Mantel-Cox) was used for statistical analysis. (J) Nonsynonymous mutation distribution in genes involved in the frequently mutated PI3K/AKT/mTOR (blue) and MAPK pathway (yellow), ERBB family of receptor tyrosine kinases (green) and DNA repair pathway (red) as well as ARID1A and PALB2 are shown with OncoPrint. CNA in each mutated gene are added. The 106 OCCC tumors that were both kinome sequenced and SNP arrayed are shown on the horizontal axis grouped on tumor clusters and ordered on total event frequency in the subsequently altered pathways. (K) Oncoprint from advanced stage patients in cluster 3 vs. other clusters, shown on the horizontal axis grouped on tumor clusters and ordered on total event frequency in the subsequent altered pathways, ordered as aforementioned.

Supplementary Figure 4 | Whole genome CNA heatmap. (A) Genome-wide CNA heatmap profiles of all 108 OCCC tumors (above), 63 ARID1A wildtype tumors (middle) and 45 ARID1A mutant tumors (below). (B) Significant CNA plot of only ARID1A wildtype tumors (n=63) and (C) only ARID1A mutant tumors (n=45) as determined by GISTIC analysis. All kinases and cancer-related genes from the kinome sequencing gene panel that were focally significantly amplified (red) or deleted (blue) are indicated along the chromosomes vertically. Chromosomal location and total amount of tumors harboring the event are annotated with each gene name. False-discovery rate (FDR) 0.05 threshold, indicated by the green line, and G-score are shown along the horizontal axis.

Supplementary Table 3 | Binomial testing of kinome sequencing variants.

Supplementary Table 1 | Gene set for kinome sequencing.

Supplementary Figure 7 | PDX alteration status and p-S6 staining. (A) Nonsynonymous mutation distribution in PDX.155, PDX.180 and PDX.247 in genes involved in the frequently mutated PI3K/AKT/mTOR (blue) and MAPK pathway (yellow), ERBB family of receptor tyrosine kinases (green) and DNA repair pathway (red) as well as ARID1A and PALB2 are shown with OncoPrint. CNA in each mutated gene are added. (B) PDX.155, (C) PDX.180 and (D) PDX.247 representative p-S6 expression after 21 days of vehicle or AZD8055 treatment.

Supplementary Figure 2 | Significantly mutated genes AKT1, PIK3R1, ERBB3, FBXW7, ATM, CHEK2 and MYO3A. Schematics of the identified novel significantly mutated genes (A) AKT1, (B) PIK3R1, (C) ERBB3, (D) FBXW7, (E) ATM, (F) CHEK2 and (G) MYO3A in OCCC. Mutation marks are shown in black (truncating), red (SIFT and PolyPhen damaging prediction), yellow (SIFT or PolyPhen damaging prediction) or white (SIFT and PolyPhen benign prediction). Mutation effects are indicated with a black spot when paired control was available and written in black (previously described mutation) or red (novel mutations).

Supplementary Figure 3 | Mutation distribution in OCCC. (A) Nonsynonymous mutation distribution in genes involved in the frequently mutated PI3K/AKT/mTOR (blue) and MAPK pathway (yellow), ERBB family of receptor tyrosine kinases (green) and DNA repair (red) pathway is shown. In this OncoPrint, kinome sequenced OCCC tumors are depicted on the horizontal axis and ordered on mutation frequency in the subsequent altered pathways, represented vertically on the right. ARID1A mutant tumors are displayed at the top. (B) BioVenn diagrams demonstrating overlap in ARID1A mutant tumors and PI3K/AKT/mTOR, MAPK and DNA repair pathway and ERBB family of receptor tyrosine kinases mutant tumors (n=103). On the right, PI3K/AKT/mTOR and MAPK pathway, the ERBB family of receptor tyrosine kinases and DNA repair pathway mutations within only ARID1A wildtype tumors (n=49) and only ARID1A mutant tumors (n=44). All data in A and B is derived from 122 kinome-sequenced OCCC tumors, overlap in BioVenn diagram circles is proportional to group overlap.

Supplementary Table 4 | Clinicopathological characteristics (n=70 patients).

Supplementary Figure 6 | mTORC1, mTORC1/2 and PI3K-mTORC1/2 inhibitor sensitivities. (A) IC50 of the mTORC1 inhibitor temsirolimus from COSMICs drug screening database in all cancer cell lines vs. ovarian cancer cell lines, horizontal lines indicate geometric mean. (B) MTT assay curves from AZD8055 (left) or everolimus (right) treatment on the aforementioned cell line panel. (C) Expression of p-AKT308, p-AKT473 and p-S6 after 24 (up) and 72h (down) exposure to 100 nM everolimus, AZD8055 or MLN0128 in the OCCC cell lines KOC7C or JHOC5 determined by Western blot. β-Actin was used as loading control. Results are representative from n=2 experiments. (D) Expression of p-AKT308, p-AKT473, p-S6 and (cleaved) PARP after 48h exposure to increasing concentrations of everolimus, AZD8055 and dactolisib in the OCCC cell lines KOC7C (up) and JHOC5 (down) determined by Western blot. β-Actin was used as loading control. Results are representative from n=2 experiments. (E) Everolimus, AZD8055, GDC0941 and selumetinib IC50 determined for 14 OCCC cell lines (ES2, KOC7C, SMOV2, JHOC5, RMG1, OVMANA, HAC2, OV207, OVTOKO, TOV21G, OVAS, OVCA429, TUOC1 and RMG2) and dactolisib IC50 determined for 7 OCCC cell lines (ES2, KOC7C, SMOV2, JHOC5, RMG1, OVMANA and HAC2) by MTT assay. Selumetinib IC50 of KOC7C was not reached at maximum used concentration of 25 uM. Horizontal lines indicate geometric mean. Data is derived from n{greater than or equal to}2 experiments. (F) Long-term proliferation assay after exposure to increasing concentrations of AZD8055 and dactolisib. Results are representative from n=3 experiments.

Abstract Purpose: Advanced-stage ovarian clear cell carcinoma (OCCC) is unresponsive to conventional platinum-based chemotherapy. Frequent alterations in OCCC include deleterious mutations in the tumor suppressor ARID1A and activating mutations in the PI3K subunit PIK3CA. In this study, we aimed to identify currently unknown mutated kinases in patients with OCCC and test druggability of downstream affected pathways in OCCC models. Experimental Design: In a large set of patients with OCCC (n = 124), the human kinome (518 kinases) and additional cancer-related genes were sequenced, and copy-number alterations were determined. Genetically characterized OCCC cell lines (n = 17) and OCCC patient–derived xenografts (n = 3) were used for drug testing of ERBB tyrosine kinase inhibitors erlotinib and lapatinib, the PARP inhibitor olaparib, and the mTORC1/2 inhibitor AZD8055. Results: We identified several putative driver mutations in kinases at low frequency that were not previously annotated in OCCC. Combining mutations and copy-number alterations, 91% of all tumors are affected in the PI3K/AKT/mTOR pathway, the MAPK pathway, or the ERBB family of receptor tyrosine kinases, and 82% in the DNA repair pathway. Strong p-S6 staining in patients with OCCC suggests high mTORC1/2 activity. We consistently found that the majority of OCCC cell lines are especially sensitive to mTORC1/2 inhibition by AZD8055 and not toward drugs targeting ERBB family of receptor tyrosine kinases or DNA repair signaling. We subsequently demonstrated the efficacy of mTORC1/2 inhibition in all our unique OCCC patient–derived xenograft models. Conclusions: These results propose mTORC1/2 inhibition as an effective treatment strategy in OCCC. Clin Cancer Res; 24(16); 3928–40. ©2018 AACR.

Macrophages display large functional and phenotypical plasticity. They can adopt a broad range of activation states depending on their microenvironment. Various surface markers are used to characterize these differentially polarized macrophages. However, this is not informative for the functions of the macrophage. In order to have a better understanding of the functional changes of macrophages upon differential polarization, we studied differences in LPS- and IL4-stimulated macrophages. The THP-1 human monocytic cell line, was used as a model system. Cells were labeled, differentiated and stimulated with either LPS or IL-4 in a quantitative SILAC proteomics set-up. The resulting sets of proteins were functionally clustered. LPS-stimulated macrophages show increased secretion of proinflammatory peptides, leading to increased pressure on protein biosynthesis and processing. IL4-stimulated macrophages show upregulation of cell adhesion and extracellular matrix remodeling. Our approach provides an integrated view of polarization-induced functional changes and proves useful for studying functional differences between subsets of macrophages. Moreover, the identified polarization specific proteins may contribute to a better characterization of different activation states in situ and their role in various inflammatory processes.

Despite developments in targeted gene sequencing and whole-genome analysis techniques, the robust detection of all genetic variation, including structural variants, in and around genes of interest and in an allele-specific manner remains a challenge. Here we present targeted locus amplification (TLA), a strategy to selectively amplify and sequence entire genes on the basis of the crosslinking of physically proximal sequences. We show that, unlike other targeted re-sequencing methods, TLA works without detailed prior locus information, as one or a few primer pairs are sufficient for sequencing tens to hundreds of kilobases of surrounding DNA. This enables robust detection of single nucleotide variants, structural variants and gene fusions in clinically relevant genes, including BRCA1 and BRCA2, and enables haplotyping. We show that TLA can also be used to uncover insertion sites and sequences of integrated transgenes and viruses. TLA therefore promises to be a useful method in genetic research and diagnostics when comprehensive or allele-specific genetic information is needed.

BACKGROUND: Obesity promotes inflammation in adipose tissue (AT) and this is implicated in pathophysiological complications such as insulin resistance, type 2 diabetes and cardiovascular disease. Although based on the classical hypothesis, necrotic AT adipocytes (ATA) in obese state activate AT macrophages (ATM) that then lead to a sustained chronic inflammation in AT, the link between human adipocytes and the source of inflammation in AT has not been in-depth and systematically studied. So we decided as a new hypothesis to investigate human primary adipocytes alone to see whether they are able to prime inflammation in AT. METHODS AND RESULTS: Using mRNA expression, human preadipocytes and adipocytes express the cytokines/chemokines and their receptors, MHC II molecule genes and 14 acute phase reactants including C-reactive protein. Using multiplex ELISA revealed the expression of 50 cytokine/chemokine proteins by human adipocytes. Upon lipopolysaccharide stimulation, most of these adipocyte-associated cytokines/chemokines and immune cell modulating receptors were up-regulated and a few down-regulated such as (ICAM-1, VCAM-1, MCP-1, IP-10, IL-6, IL-8, TNF-α and TNF-β highly up-regulated and IL-2, IL-7, IL-10, IL-13 and VEGF down-regulated. In migration assay, human adipocyte-derived chemokines attracted significantly more CD4+ T cells than controls and the number of migrated CD4+ cells was doubled after treating the adipocytes with LPS. Neutralizing MCP-1 effect produced by adipocytes reduced CD4+ migration by approximately 30%. CONCLUSION: Human adipocytes express many cytokines/chemokines that are biologically functional. They are able to induce inflammation and activate CD4+ cells independent of macrophages. This suggests that the primary event in the sequence leading to chronic inflammation in AT is metabolic dysfunction in adipocytes, followed by production of immunological mediators by these adipocytes, which is then exacerbated by activated ATM, activation and recruitment of immune cells. This study provides novel knowledge about the prime of inflammation in human obese adipose tissue, opening a new avenue of investigations towards obesity-associated type 2 diabetes.

Eur J Clin Invest 2012; 42 (4): 357–364AbstractBackground Adipose tissue is a primary site of obesity‐induced inflammation, which is emerging as an important contributor to obesity‐related diseases such as type 2 diabetes. Dietary fibre consumption appears to be protective. Short‐chain fatty acids, e.g. propionic acid, are the principal products of the colonic fermentation of dietary fibre and may have beneficial effects on adipose tissue inflammation.Materials and methods Human omental adipose tissue explants were obtained from overweight (mean BMI 28·8) gynaecological patients who underwent surgery. Explants were incubated for 24 h with propionic acid. Human THP‐1 monocytic cells were differentiated to macrophages and incubated with LPS in the presence and absence of propionic acid. Cytokine and chemokine production were determined by multiplex‐ELISA, and mRNA expression of metabolic and macrophages genes was determined by RT‐PCR.Results Treatment of adipose tissue explants with propionic acid results in a significant down‐regulation of several inflammatory cytokines and chemokines such as TNF‐α and CCL5. In addition, expression of lipoprotein lipase and GLUT4, associated with lipogenesis and glucose uptake, respectively, increased. Similar effects on cytokine and chemokine production by macrophages were observed.Conclusion We show that propionic acid, normally produced in the colon, may have a direct beneficial effect on visceral adipose tissue, reducing obesity‐associated inflammation and increasing lipogenesis and glucose uptake. Effects on adipose tissue as a whole are at least partially explained by effects on macrophages but likely also adipocytes are involved. This suggests that, in vivo, propionic acid and dietary fibres may have potential in preventing obesity‐related inflammation and associated diseases.

BACKGROUND:Insulin resistance (IR) is accompanied by chronic low grade systemic inflammation, obesity, and deregulation of total body energy homeostasis. We induced inflammation in adipose and liver tissues in vitro in order to mimic inflammation in vivo with the aim to identify tissue-specific processes implicated in IR and to find biomarkers indicative for tissue-specific IR.METHODS:Human adipose and liver tissues were cultured in the absence or presence of LPS and DNA Microarray Technology was applied for their transcriptome analysis. Gene Ontology (GO), gene functional analysis, and prediction of genes encoding for secretome were performed using publicly available bioinformatics tools (DAVID, STRING, SecretomeP). The transcriptome data were validated by proteomics analysis of the inflamed adipose tissue secretome.RESULTS:LPS treatment significantly affected 667 and 483 genes in adipose and liver tissues respectively. The GO analysis revealed that during inflammation adipose tissue, compared to liver tissue, had more significantly upregulated genes, GO terms, and functional clusters related to inflammation and angiogenesis. The secretome prediction led to identification of 399 and 236 genes in adipose and liver tissue respectively. The secretomes of both tissues shared 66 genes and the remaining genes were the differential candidate biomarkers indicative for inflamed adipose or liver tissue. The transcriptome data of the inflamed adipose tissue secretome showed excellent correlation with the proteomics data.CONCLUSIONS:The higher number of altered proinflammatory genes, GO processes, and genes encoding for secretome during inflammation in adipose tissue compared to liver tissue, suggests that adipose tissue is the major organ contributing to the development of systemic inflammation observed in IR. The identified tissue-specific functional clusters and biomarkers might be used in a strategy for the development of tissue-targeted treatment of insulin resistance in patients.

Insulin resistance (IR) is accompanied by chronic low grade systemic inflammation and deregulation of total body energy homeostasis. We induced inflammation in human adipose and liver tissue in vitro in order to mimic inflammation in vivo with the aim to identify tissue-specific processes and biomarkers implicated in IR Human adipose and liver tissues were cultured with or without LPS and DNA Microarray Technology was applied for their transcriptome analysis. Gene Ontology (GO), gene functional analysis, and prediction of genes encoding for the secretome were performed using DAVID, STRING, and SecretomeP as bioinformatics tools .The transcriptome data were validated by proteomics analysis of the inflamed adipose tissue secretome using CILAIR technology. LPS significantly affected 667 and 484 genes in adipose and liver tissues respectively. During inflammation adipose tissue, compared to liver tissue, had more significantly upregulated genes, GO terms, and functional clusters related to inflammation and angiogenesis. The secretome prediction led to identification of 399 and 236 genes in adipose and liver tissue respectively. The secretomes of both tissues shared 66 genes.The adipose tissue specific biomarkers were represented by fractalkine, tumor necrosis factor, pentraxin-related protein or interstitial collagenase (matrix metallopeptidase 1) and the liver specific biomarkers were for example chemokine (C-X-C motif) ligand 9, chemokine (C-X-C motif) ligand 3, or follistatin-like 3 (secreted glycoprotein). The transcriptome data of the inflamed adipose tissue secretome showed excellent correlation with the proteomics data. The higher number of altered proinflammatory genes, GO processes, and genes encoding for secretome during inflammation in adipose tissue compared to liver suggests that adipose tissue is the major organ in the development of systemic IR. Our study led to the identification of differential pathways and biomarkers suggesting tissue specific changes, which could be applied for tissue specific detection and treatment of IR.

Chronic inflammation of obese adipose tissue is involved in the development of insulin resistance and type 2 diabetes, probably via altered secretion of adipokines and free fatty acids. To determine how inflammation changes the adipose tissue secretome, adipose tissue was challenged with LPS, a potent immune activator. Secretome changes were analyzed by a quantitative proteomics approach: Comparison of Isotope Labeled Amino acid Incorporation Rates (CILAIR). CILAIR compares incorporation rates of 13C‐labeled lysine in secreted proteins between conditions (Mol Cell Proteomics 2009, 8:316).MethodsHuman visceral adipose tissue was divided over six dishes. 13C‐Lys containing medium was added and to three dishes also LPS (100 μg/ml). Dishes were incubated for 24 hrs. Media were collected and processed separately, involving SDS‐PAGE fractionation, in‐gel digestion of excised bands and LC‐MS/MS. Database searching with ProteinPilot (Applied Biosystems) provided identifications and C13/C12 ratios.Results37 proteins were significantly changed (p<0.05) in expression of which 19 were up‐regulated by LPS and 19 were down‐regulated. Examples of up‐regulated proteins are: Plasminogen activator inhibitor 2, Growth‐regulated alpha protein and Interleukin‐6. In addition, 12 proteins were only expressed in the inflammatory condition. Examples are: Tumor necrosis factor‐α and C‐C motif chemokine 2 and 20.ConclusionThese results indicate that inflammation profoundly changes the adipose tissue secretome. Secretion of several inflammatory cytokines and chemokines was up‐regulated as well as proteins involved in cell adhesion of attracted immune cells. These findings may have implications for the regulation of whole body insulin sensitivity and energy metabolism.

P>BackgroundDietary fibre (DF) has been shown to be protective for the development of obesity, insulin resistance and type 2 diabetes. Short-chain fatty acids, produced by colonic fermentation of DF might mediate this beneficial effect. Adipose tissue plays a key role in the regulation of energy homeostasis, therefore, we investigated the influence of the short-chain fatty acid propionic acid (PA) on leptin, adiponectin and resistin production by human omental (OAT) and subcutaneous adipose tissue (SAT). As PA has been shown to be a ligand for G-protein coupled receptor (GPCR) 41 and 43, we investigated the role of GPCR's in PA signalling.Materials and methodsHuman OAT and SAT explants were obtained from gynaecological patients who underwent surgery. Explants were incubated for 24 h with PA. Adipokine secretion and mRNA expression were determined using ELISA and RT-PCR respectively.ResultsWe found that PA significantly stimulated leptin mRNA expression and secretion by OAT and SAT, whereas it had no effect on adiponectin. Furthermore, PA reduced resistin mRNA expression. Leptin induction, but not resistin reduction, was abolished by inhibition of Gi/o-coupled GPCR signalling. Moreover, GPCR41 and GPCR43 mRNA levels were considerably higher in SAT than in OAT.ConclusionsWe demonstrate that PA stimulates expression of the anorexigenic hormone leptin and reduces the pro-inflammatory factor resistin in human adipose tissue depots. This suggests that PA is involved in regulation of human energy metabolism and inflammation and in this way may influence the development of obesity and type 2 diabetes.

subjects showed an elevated PYY in both fasting (124.7% increase) and fed (106.5% increase) states compared with the lean subjects.Food intake increased PYY in both lean and obese subjects.3) There was a positive correlation between the BMI and the serum PYY level and a negative correlation between the BMI and the ghrelin level in all the subjects in the food intake session.4) Sham-feeding did not significantly alter the serum level of PYY or ghrelin in the lean or obese subjects, but increased the score of satiety in both lean (2.20±0.39 vs. 3.70±0.32,P<0.03) and obese (2.40±0.53 vs. 4.30±0.63,P<0.02).The appetite and fullness were altered only with real food intake but not with sham-feeding.Conclusions: Obese subjects show elevated PYY and decreased ghrelin in both fasting and fed states, and an impaired postprandial ghrelin response.The absence of postprandial decrease in ghrelin may be associated with overeating in obese subjects.Cephalic stimulation (sham-feeding) may alter the feeling of satiety but not appetite or fullness, and may have minimal effects on PYY and ghrelin.

We previously characterized the visceral adipose tissue secretome (MCP 2007, 6, 589). In the present study we determined incorporation rates of 13C‐labeled lysine into newly synthesized secreted proteins. Comparison of the C13/C12 ratios in the absence and presence of insulin should offer quantitative information on the effect of insulin on the production of secreted proteins. To prove this concept, human visceral adipose tissue was cultured for 72 hrs in 13C‐Lys containing medium in the absence or presence of 60 nM insulin. Subsequently, media were collected, concentrated and fractionated by SDS‐PAGE, followed by in‐gel digestion and LC‐MS/MS analyses. The datasets shared 274 proteins of which 224 proteins contained label. After removing contaminating intracellular proteins and applying a threshold C13/C12 ratio of 0.5, 82 proteins remained. In the absence of insulin, highest label incorporation was found for Zinc‐alpha‐2‐glycoprotein. In the presence of insulin, CRISP‐11 showed the highest label incorporation. By comparing C13/C12 ratios in the absence and presence of insulin we found eight proteins that were up‐regulated by insulin, four proteins were down‐regulated and 70 showed no change. The highest increase (4.7 fold) was found for CRISP‐11. We developed a new proteomics method which allows quantitative assessment of effects of insulin or other agents on protein secretion by tissues in culture.