John Sinclair

Inhibiting EGF receptor or SRC family kinase signaling overcomes BRAF inhibitor resistance in melanoma

UNLABELLED We generated cell lines resistant to BRAF inhibitors and show that the EGF receptor (EGFR)-SRC family kinase (SFK)-STAT3 signaling pathway was upregulated in these cells. In addition to driving proliferation of resistant cells, this pathway also stimulated invasion and metastasis. EGFR inhibitors cooperated with BRAF inhibitors to block the growth of the resistant cells in vitro and in vivo, and monotherapy with the broad specificity tyrosine kinase inhibitor dasatinib blocked growth and metastasis in vivo. We analyzed tumors from patients with intrinsic or acquired resistance to vemurafenib and observed increased EGFR and SFK activity. Furthermore, dasatinib blocked the growth and metastasis of one of the resistant tumors in immunocompromised mice. Our data show that BRAF inhibitor-mediated activation of EGFR-SFK-STAT3 signaling can mediate resistance in patients with BRAF-mutant melanoma. We describe 2 treatments that seem to overcome this resistance and could deliver therapeutic efficacy in patients with drug-resistant BRAF-mutant melanoma. SIGNIFICANCE Therapies that target the driver oncogenes in cancer can achieve remarkable responses if patients are stratified for treatment. However, as with conventional therapies, patients often develop acquired resistance to targeted therapies, and a proportion of patients are intrinsically resistant and fail to respond despite the presence of an appropriate driver oncogene mutation. We found that the EGFR/SFK pathway mediated resistance to vemurafenib in BRAF -mutant melanoma and that BRAF and EGFR or SFK inhibition blocked proliferation and invasion of these resistant tumors, providing potentially effective therapeutic options for these patients.

Three-dimensional in vitro cell biology models of ovarian and endometrial cancer

Objectives:  This study aims to establish three‐dimensional (3D) cell culture models of human ovarian and endometrial cancers and to compare biological and morphological characteristics of these models with those of two‐dimensional (2D) models of the same cell lines and the primary tumours.

Quantitative profiling of serum samples using TMT protein labelling, fractionation and LC-MS/MS.

Blood-borne biomarkers are urgently required for the early detection, accurate diagnosis and prognosis of disease. Additionally, improved methods of profiling serum and plasma proteins for biomarker discovery efforts are needed. Herein, we report a quantitative method based on amino-group labelling of serum proteins (rather than peptides) with isobaric tandem mass tags (TMT) and incorporating immune-based depletion, gel-based and strong anion exchange separation of proteins prior to differential endoproteinase treatment and liquid chromatography tandem mass spectrometry. We report a generally higher level of quantitative coverage of the serum proteome compared to other peptide-based isobaric tagging approaches and show the potential of the method by applying it to a set of unique samples that pre-date the diagnosis of pancreatic cancer.

Systematic evaluation of quantotypic peptides for targeted analysis of the human kinome

In targeted proteomics it is critical that peptides are not only proteotypic but also accurately represent the level of the protein (quantotypic). Numerous approaches are used to identify proteotypic peptides, but quantotypic properties are rarely assessed. We show that measuring ratios of proteotypic peptides across biological samples can be used to empirically identify peptides with good quantotypic properties. We applied this technique to identify quantotypic peptides for 21% of the human kinome.

A combination of serum leucine-rich α-2-glycoprotein 1, CA19-9 and interleukin-6 differentiate biliary tract cancer from benign biliary strictures.

Background:Biliary tract cancer (BTC) and benign biliary strictures can be difficult to differentiate using standard tumour markers such as serum carbohydrate antigen 19-9 (CA19-9) as they lack diagnostic accuracy.Methods:Two-dimensional difference gel electrophoresis and tandem mass spectrometry were used to profile immunodepleted serum samples collected from cases of BTC, primary sclerosing cholangitis (PSC), immunoglobulin G4-associated cholangitis and healthy volunteers. The serum levels of one candidate protein, leucine-rich α-2-glycoprotein (LRG1), were verified in individual samples using enzyme-linked immunosorbent assay and compared with serum levels of CA19-9, bilirubin, interleukin-6 (IL-6) and other inflammatory markers.Results:We report increased LRG1, CA19-9 and IL-6 levels in serum from patients with BTC compared with benign disease and healthy controls. Immunohistochemical analysis also demonstrated increased staining of LRG1 in BTC compared with cholangiocytes in benign biliary disease. The combination of receiver operating characteristic (ROC) curves for LRG1, CA19-9 and IL-6 demonstrated an area under the ROC curve of 0.98. In addition, raised LRG1 and CA19-9 were found to be independent predictors of BTC in the presence of elevated bilirubin, C-reactive protein and alkaline phosphatase.Conclusion:These results suggest LRG1, CA19-9 and IL-6 as useful markers for the diagnosis of BTC, particularly in high-risk patients with PSC.

Reproducible automated phosphopeptide enrichment using magnetic TiO2 and Ti-IMAC.

Reproducible, comprehensive phosphopeptide enrichment is essential for studying phosphorylation-regulated processes. Here, we describe the application of hyper-porous magnetic TiO2 and Ti-IMAC microspheres for uniform automated phosphopeptide enrichment. Combining magnetic microspheres with a magnetic particle-handling robot enables rapid (45 min), reproducible (r2 ≥ 0.80) and high-fidelity (>90% purity) phosphopeptide purification in a 96-well format. Automated phosphopeptide enrichment demonstrates reproducible synthetic phosphopeptide recovery across 2 orders of magnitude, “well-to-well” quantitative reproducibility indistinguishable to internal SILAC standards, and robust “plate-to-plate” reproducibility across 5 days of independent enrichments. As a result, automated phosphopeptide enrichment enables statistical analysis of label-free phosphoproteomic samples in a high-throughput manner. This technique uses commercially available, off-the-shelf components and can be easily adopted by any laboratory interested in phosphoproteomic analysis. We provide a free downloadable automated phosphopeptide enrichment program to facilitate uniform interlaboratory collaboration and exchange of phosphoproteomic data sets.

Profiling signatures of ovarian cancer tumour suppression using 2D-DIGE and 2D-LC-MS/MS with tandem mass tagging

Epithelial ovarian cancer (EOC) is the most common form of gynaecological malignancy in the developed world and has a poor prognosis due to its late detection. Identifying molecular markers of the disease may provide novel approaches to screening and could enable targeted treatment and the design of novel therapies. Although blood is recognized as a highly important source of disease-related biomarkers, the complexity and dynamic range of protein abundance in body fluids has hampered proteomic biomarker discovery and alternative approaches using cell models may be more successful. Herein, we have utilized two cellular models of EOC, where transfer of normal chromosome 18 material into the EOC cell lines TOV-112D and TOV-21G induced in vitro and in vivo suppression of their tumourigenic phenotype. A combination of quantitative two-dimensional difference gel electrophoresis (2D-DIGE) and two-dimensional-liquid chromatography tandem mass spectrometry (2D-LC-MS/MS) with tandem mass tagging (TMT) was employed to examine the whole cell, secreted and crude membrane proteomes of the parental and hybrid cell models to identify differentially expressed proteins as potential markers of tumour suppression. Protein changes of interest were confirmed by immunoblotting in additional hybrid and revertant cell lines where incorporated chromosome 18 material was lost. One candidate marker was also tested in sera from a set of ovarian cancer cases and controls. We have identified a list of promising candidate biomarkers for further testing and functional characterization.

Discovery of serum biomarkers of ovarian cancer using complementary proteomic profiling strategies

Ovarian cancer is a devastating disease and biomarkers for its early diagnosis are urgently required. Serum may be a valuable source of biomarkers that may be revealed by proteomic profiling. Herein, complementary serum protein profiling strategies were employed for discovery of biomarkers that could discriminate cases of malignant and benign ovarian cancer.

A targeted glycoproteomic approach identifies cadherin-5 as a novel biomarker of metastatic breast cancer

Aberrant glycosylation has long been recognised as a hallmark of cancer, and is increasingly being exploited in biomarker discovery studies. Helix pomatia agglutinin (HPA) is known to bind aberrant glycans associated with metastatic breast cancer, and was used here to isolate glycoproteins from pooled breast cancer serum samples of (i) patients with recurrent breast cancer and (ii) patients with no sign of recurrence 5years after diagnosis of their primary tumour. Pregnancy zone protein, the polymeric immunoglobulin receptor and cadherin-5 emerged as potential markers of metastasis following proteomic identification of HPA binding glycoproteins. ELISAs were developed to verify these findings, and to assess protein glycosylation, in individual patient sera. The cadherin-5 ELISA discriminated serum samples of patients with recurrent breast cancer from those with no sign of recurrence, and analysis of cadherin-5 glycosylation by HPA also showed a significant difference between the two sample groups. The targeted glycoproteomic and validatory approach developed here has shown that when taking into account both the protein levels and HPA binding, serum cadherin-5 discriminated patients with recurrent breast cancer from those with no sign of recurrence with 90% specificity.

Integrative analysis of kinase networks in TRAIL-induced apoptosis provides a source of potential targets for combination therapy

Analysis of kinase signaling involved in TRAIL-induced cell death highlights potential targets for combination cancer therapy. Networking death signals Selective killing of cancer cells without the induction of resistance is the holy grail of cancer therapy. TRAIL is an endogenous secreted protein that promotes cell death, and cancer cells are particularly sensitive to this molecule. Unfortunately, some cancer cells evade TRAIL-induced death and develop resistance by rewiring their signaling networks. So et al. took a proteomic approach aimed at kinases, which are key regulators of cell survival and death, and mapped a protein interaction network encompassing kinases that they identified as affecting TRAIL-induced cell death. Modeling information flow through the network revealed potential targets that could be exploited to develop combination therapies with TRAIL to kill cancer cells and prevent resistance. Tumor necrosis factor–related apoptosis–inducing ligand (TRAIL) is an endogenous secreted peptide and, in preclinical studies, preferentially induces apoptosis in tumor cells rather than in normal cells. The acquisition of resistance in cells exposed to TRAIL or its mimics limits their clinical efficacy. Because kinases are intimately involved in the regulation of apoptosis, we systematically characterized kinases involved in TRAIL signaling. Using RNA interference (RNAi) loss-of-function and cDNA overexpression screens, we identified 169 protein kinases that influenced the dynamics of TRAIL-induced apoptosis in the colon adenocarcinoma cell line DLD-1. We classified the kinases as sensitizers or resistors or modulators, depending on the effect that knockdown and overexpression had on TRAIL-induced apoptosis. Two of these kinases that were classified as resistors were PX domain–containing serine/threonine kinase (PXK) and AP2-associated kinase 1 (AAK1), which promote receptor endocytosis and may enable cells to resist TRAIL-induced apoptosis by enhancing endocytosis of the TRAIL receptors. We assembled protein interaction maps using mass spectrometry–based protein interaction analysis and quantitative phosphoproteomics. With these protein interaction maps, we modeled information flow through the networks and identified apoptosis-modifying kinases that are highly connected to regulated substrates downstream of TRAIL. The results of this analysis provide a resource of potential targets for the development of TRAIL combination therapies to selectively kill cancer cells.