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IHC of TGFBI and POSTN

Supplementary Tables 10 - 14

Supplemental Figures and Supplemental Methods

Supplementary Tables 15 - 25

CIBERSORT results of the TGFBI high/low samples in the TCGA and ICGC datasets

Supplementary Tables 4 - 9

Legend of supplementary tables

Supplementary Tables 1 - 3

Cholangiocarcinoma is a form of hepatobiliary cancer with an abysmal prognosis. Despite advances in our understanding of cholangiocarcinoma pathophysiology and its genomic landscape, targeted therapies have not yet made a significant impact on its clinical management. The low response rates of targeted therapies in cholangiocarcinoma suggest that patient heterogeneity contributes to poor clinical outcome. Here we used mass spectrometry–based phosphoproteomics and computational methods to identify patient-specific drug targets in patient tumors and cholangiocarcinoma-derived cell lines. We analyzed 13 primary tumors of patients with cholangiocarcinoma with matched nonmalignant tissue and 7 different cholangiocarcinoma cell lines, leading to the identification and quantification of more than 13,000 phosphorylation sites. The phosphoproteomes of cholangiocarcinoma cell lines and patient tumors were significantly correlated. MEK1, KIT, ERK1/2, and several cyclin-dependent kinases were among the protein kinases most frequently showing increased activity in cholangiocarcinoma relative to nonmalignant tissue. Application of the Drug Ranking Using Machine Learning (DRUML) algorithm selected inhibitors of histone deacetylase (HDAC; belinostat and CAY10603) and PI3K pathway members as high-ranking therapies to use in primary cholangiocarcinoma. The accuracy of the computational drug rankings based on predicted responses was confirmed in cell-line models of cholangiocarcinoma. Together, this study uncovers frequently activated biochemical pathways in cholangiocarcinoma and provides a proof of concept for the application of computational methodology to rank drugs based on efficacy in individual patients.Significance:Phosphoproteomic and computational analyses identify patient-specific drug targets in cholangiocarcinoma, supporting the potential of a machine learning method to predict personalized therapies.

Supplementary Figures (S1A-B, S2, S3, S4A-C and Table S1 & S2.

Supplementary Data from Suppression of Endothelial Cell FAK Expression Reduces Pancreatic Ductal Adenocarcinoma Metastasis after Gemcitabine Treatment

Despite substantial advances in the treatment of solid cancers, resistance to therapy remains a major obstacle to prolonged progression-free survival. Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers, with a high level of liver metastasis. Primary PDAC is highly hypoxic, and metastases are resistant to first-line treatment, including gemcitabine. Recent studies have indicated that endothelial cell (EC) focal adhesion kinase (FAK) regulates DNA-damaging therapy–induced angiocrine factors and chemosensitivity in primary tumor models. Here, we show that inducible loss of EC-FAK in both orthotopic and spontaneous mouse models of PDAC is not sufficient to affect primary tumor growth but reduces liver and lung metastasis load and improves survival rates in gemcitabine-treated, but not untreated, mice. EC-FAK loss did not affect primary tumor angiogenesis, tumor blood vessel leakage, or early events in metastasis, including the numbers of circulating tumor cells, tumor cell homing, or metastatic seeding. Phosphoproteomics analysis showed a downregulation of the MAPK, RAF, and PAK signaling pathways in gemcitabine-treated FAK-depleted ECs compared with gemcitabine-treated wild-type ECs. Moreover, low levels of EC-FAK correlated with increased survival and reduced relapse in gemcitabine-treated patients with PDAC, supporting the clinical relevance of these findings. Altogether, we have identified a new role of EC-FAK in regulating PDAC metastasis upon gemcitabine treatment that impacts outcome.Significance:These findings establish the potential utility of combinatorial endothelial cell FAK targeting together with gemcitabine in future clinical applications to control metastasis in patients with pancreatic ductal adenocarcinoma.

Supplementary Figure from Suppression of Endothelial Cell FAK Expression Reduces Pancreatic Ductal Adenocarcinoma Metastasis after Gemcitabine Treatment

Despite substantial advances in the treatment of solid cancers, resistance to therapy remains a major obstacle to prolonged progression-free survival. Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive cancers, with a high level of liver metastasis. Primary PDAC is highly hypoxic, and metastases are resistant to first-line treatment, including gemcitabine. Recent studies have indicated that endothelial cell (EC) focal adhesion kinase (FAK) regulates DNA-damaging therapy–induced angiocrine factors and chemosensitivity in primary tumor models. Here, we show that inducible loss of EC-FAK in both orthotopic and spontaneous mouse models of PDAC is not sufficient to affect primary tumor growth but reduces liver and lung metastasis load and improves survival rates in gemcitabine-treated, but not untreated, mice. EC-FAK loss did not affect primary tumor angiogenesis, tumor blood vessel leakage, or early events in metastasis, including the numbers of circulating tumor cells, tumor cell homing, or metastatic seeding. Phosphoproteomics analysis showed a downregulation of the MAPK, RAF, and PAK signaling pathways in gemcitabine-treated FAK-depleted ECs compared with gemcitabine-treated wild-type ECs. Moreover, low levels of EC-FAK correlated with increased survival and reduced relapse in gemcitabine-treated patients with PDAC, supporting the clinical relevance of these findings. Altogether, we have identified a new role of EC-FAK in regulating PDAC metastasis upon gemcitabine treatment that impacts outcome. Significance: These findings establish the potential utility of combinatorial endothelial cell FAK targeting together with gemcitabine in future clinical applications to control metastasis in patients with pancreatic ductal adenocarcinoma.

Background KMT2A-rearranged (KMT2A-R) is an aggressive and chemo-refractory acute leukemia which mostly affects children. Transcriptomics-based characterization and chemical interrogation identified kinases as key drivers of survival and drug resistance in KMT2A-R leukemia. In contrast, the contribution and regulation of phosphatases is unknown. We explored the role of SET, the endogenous inhibitor of SER/THR phosphatase PP2A in KMT2A-R leukemia. Material and Methods The expression of SET was analysed in a large acute myeloid leukemia (AML)- RNA-seq dataset and in primary KMT2A-R samples and aged matched-controls. Stable SET knockdown (KD) was established by RNA interference in three KMT2A wild-type (wt) and four KMT2A-R leukemic cell lines. Gene and protein expression were analysed by RT-qPCR, ChiP, IP and western blot. RNA-seq and phospho-proteomics were employed to evaluate the effect of the SET-PP2A inhibitor FTY720 on global protein phosphorylation and gene expression. The cellular impact of FTY720 was evaluated by analysing proliferation, cell cycle and apoptosis in leukemic cell lines and by colony formation assay in two patient-derived xenograft (PDX). Results SET mRNA was found expressed in blasts from KMT2A-R-patients and in leukemic stem cells. SET protein interacted with both KMT2A wt and fusion proteins. Knockdown of SET inhibited the transcription of KMT2A target genes HOXA9 and HOXA10and abolished the self-renewal of KMT2A-R leukemic cells. Pharmacological inhibition of SET by FTY720 disrupted SET-PP2A interaction leading to cell cycle arrest, apoptosis and increased sensitivity to chemotherapy in KMT2A-R-leukemic models. Phospho-proteomic and western blot analyses revealed that FTY720 reduced the activity of kinases regulated by PP2A, including ERK1, GSK3b, ARKB, and led to degradation of MYC, supporting the hypothesis of a feedback loop among SET, PP2A and MYC. The RNA-seq indicated that FTY720 reduced the activity of signalling pathways implicated in gene transcription and it compromised the expression of several genes belonging to the KMT2A-R leukemia signature. Conclusions Taken together our results identify SET as a novel player in KMT2A-R leukemia and provide evidence that SET antagonism could serve as a novel strategy to treat this aggressive leukemia.

The tumor microenvironment evolves during malignant progression, with major changes in nonmalignant cells, cytokine networks, and the extracellular matrix (ECM). In this study, we aimed to understand how the ECM changes during neoplastic transformation of serous tubal intraepithelial carcinoma lesions (STIC) into high-grade serous ovarian cancers (HGSOC). Analysis of the mechanical properties of human fallopian tubes (FT) and ovaries revealed that normal FT and fimbria had a lower tissue modulus, a measure of stiffness, than normal or diseased ovaries. Proteomic analysis of the matrisome fraction between FT, fimbria, and ovaries showed significant differences in the ECM protein TGF beta induced (TGFBI, also known as βig-h3). STIC lesions in the fimbria expressed high levels of TGFBI, which was predominantly produced by CD163-positive macrophages proximal to STIC epithelial cells. In vitro stimulation of macrophages with TGFβ and IL4 induced secretion of TGFBI, whereas IFNγ/LPS downregulated macrophage TGFBI expression. Immortalized FT secretory epithelial cells carrying clinically relevant TP53 mutations stimulated macrophages to secrete TGFBI and upregulated integrin αvβ3, a putative TGFBI receptor. Transcriptomic HGSOC datasets showed a significant correlation between TGFBI expression and alternatively activated macrophage signatures. Fibroblasts in HGSOC metastases expressed TGFBI and stimulated macrophage TGFBI production in vitro. Treatment of orthotopic mouse HGSOC tumors with an anti-TGFBI antibody reduced peritoneal tumor size, increased tumor monocytes, and activated β3-expressing unconventional T cells. In conclusion, TGFBI may favor an immunosuppressive microenvironment in STICs that persists in advanced HGSOC. Furthermore, TGFBI may be an effector of the tumor-promoting actions of TGFβ and a potential therapeutic target. Significance: Analysis of ECM changes during neoplastic transformation reveals a role for TGFBI secreted by macrophages in immunosuppression in early ovarian cancer.

Cholangiocarcinoma is a form of hepatobiliary cancer with an abysmal prognosis. Despite advances in our understanding of cholangiocarcinoma pathophysiology and its genomic landscape, targeted therapies have not yet made a significant impact on its clinical management. The low response rates of targeted therapies in cholangiocarcinoma suggest that patient heterogeneity contributes to poor clinical outcome. Here we used mass spectrometry–based phosphoproteomics and computational methods to identify patient-specific drug targets in patient tumors and cholangiocarcinoma-derived cell lines. We analyzed 13 primary tumors of patients with cholangiocarcinoma with matched nonmalignant tissue and 7 different cholangiocarcinoma cell lines, leading to the identification and quantification of more than 13,000 phosphorylation sites. The phosphoproteomes of cholangiocarcinoma cell lines and patient tumors were significantly correlated. MEK1, KIT, ERK1/2, and several cyclin-dependent kinases were among the protein kinases most frequently showing increased activity in cholangiocarcinoma relative to nonmalignant tissue. Application of the Drug Ranking Using Machine Learning (DRUML) algorithm selected inhibitors of histone deacetylase (HDAC; belinostat and CAY10603) and PI3K pathway members as high-ranking therapies to use in primary cholangiocarcinoma. The accuracy of the computational drug rankings based on predicted responses was confirmed in cell-line models of cholangiocarcinoma. Together, this study uncovers frequently activated biochemical pathways in cholangiocarcinoma and provides a proof of concept for the application of computational methodology to rank drugs based on efficacy in individual patients. Significance: Phosphoproteomic and computational analyses identify patient-specific drug targets in cholangiocarcinoma, supporting the potential of a machine learning method to predict personalized therapies.

In response to tissue injury, within seconds the ultra-large glycoprotein von Willebrand factor (VWF) is released from endothelial storage organelles (Weibel−Palade bodies) into the lumen of the blood vasculature, where it leads to the recruitment of platelets. The marked size of VWF multimers represents an unprecedented burden on the secretory machinery of endothelial cells (ECs). ECs have evolved mechanisms to overcome this, most notably an actomyosin ring that forms, contracts, and squeezes out its unwieldy cargo. Inhibiting the formation or function of these structures represents a novel therapeutic target for thrombotic pathologies, although characterizing proteins associated with such a dynamic process has been challenging. We have combined APEX2 proximity labeling with an innovative dual loss-of-function screen to identify proteins associated with actomyosin ring function. We show that p21 activated kinase 2 (PAK2) recruits septin hetero-oligomers, a molecular interaction that forms a ring around exocytic sites. This cascade of events controls actomyosin ring function, aiding efficient exocytic release. Genetic or pharmacological inhibition of PAK2 or septins led to inefficient release of VWF and a failure to form platelet-catching strings. This new molecular mechanism offers additional therapeutic targets for the control of thrombotic disease and is highly relevant to other secretory systems that employ exocytic actomyosin machinery.

Poly(ADP-ribose) polymerase 1 (PARP-1) is a nuclear enzyme that catalyze the transfer of ADP-ribose units from NAD+ to several target proteins involved in cellular stress responses. Using WRL68 (HeLa derivate) cells, we previously showed that PARP-1 activation induced by oxidative stress after H2O2 treatment lead to depletion of cellular NAD+ and ATP, which promoted cell death. In this work, LC–MS/MS-based phosphoproteomics in WRL68 cells showed that the oxidative damage induced by H2O2 increased the phosphorylation of YAP1, a transcriptional co-activator involved in cell survival, and modified the phosphorylation of other proteins involved in transcription. Genetic or pharmacological inhibition of PARP-1 in H2O2-treated cells reduced YAP1 phosphorylation and degradation and increased cell viability. YAP1 silencing abrogated the protective effect of PARP-1 inhibition, indicating that YAP1 is important for the survival of WRL68 cells exposed to oxidative damage. Supplementation of NAD+ also reduced YAP1 phosphorylation, suggesting that the loss of cellular NAD+ caused by PARP-1 activation after oxidative treatment is responsible for the phosphorylation of YAP1. Finally, PARP-1 silencing after oxidative treatment diminished the activation of the metabolic sensor AMPK. Since NAD+ supplementation reduced the phosphorylation of some AMPK substrates, we hypothesized that the loss of cellular NAD+ after PARP-1 activation may induce an energy stress that activates AMPK. In summary, we showed a new crucial role of PARP-1 in the response to oxidative stress in which PARP-1 activation reduced cell viability by promoting the phosphorylation and degradation of YAP1 through a mechanism that involves the depletion of NAD+.

Understanding how oncogenic mutations rewire regulatory-protein networks is important for rationalizing the mechanisms of oncogenesis and for individualizing anticancer treatments. We report a chemical phosphoproteomics method to elucidate the topology of kinase-signaling networks in mammalian cells. We identified >6,000 protein phosphorylation sites that can be used to infer >1,500 kinase-kinase interactions and devised algorithms that can reconstruct kinase network topologies from these phosphoproteomics data. Application of our methods to primary acute myeloid leukemia and breast cancer tumors quantified the relationship between kinase expression and activity, and enabled the identification of hitherto unknown kinase network topologies associated with drug-resistant phenotypes or specific genetic mutations. Using orthogonal methods we validated that PIK3CA wild-type cells adopt MAPK-dependent circuitries in breast cancer cells and that the kinase TTK is important in acute myeloid leukemia. Our phosphoproteomic signatures of network circuitry can identify kinase topologies associated with both phenotypes and genotypes of cancer cells.

The extracellular matrix (ECM) is a complex meshwork of insoluble fibrillar proteins and signaling factors interacting together to provide architectural and instructional cues to the surrounding cells. Alterations in ECM organization or composition and excessive ECM deposition have been observed in diseases such as fibrosis, cardiovascular diseases, and cancer. We provide here optimized protocols to solubilize ECM proteins from normal or tumor tissues, digest the proteins into peptides, analyze ECM peptides by mass spectrometry, and interpret the mass spectrometric data. In addition, we present here two novel R-script-based web tools allowing rapid annotation and relative quantification of ECM proteins, peptides, and intensity/abundance in mass spectrometric data output files. We illustrate this protocol with ECMs obtained from two pairs of tissues, which differ in ECM content and cellularity: triple-negative breast cancer and adjacent mammary tissue, and omental metastasis from high-grade serous ovarian cancer and normal omentum. The complete proteomics data set generated in this study has been deposited to the public repository ProteomeXchange with the data set identifier: PXD005554.

A common limitation of cancer treatments is chemotherapy resistance. We have previously identified that endothelial cell (EC)-specific deletion of focal adhesion kinase (FAK) sensitises tumour cells to DNA-damaging therapies, reducing tumour growth in mice. The present study addressed the kinase activity dependency of EC FAK sensitisation to the DNA-damaging chemotherapeutic drug, doxorubicin. FAK is recognised as a therapeutic target in tumour cells, leading to the development of a range of inhibitors, the majority being ATP competitive kinase inhibitors. We demonstrate that inactivation of EC FAK kinase domain (kinase dead; EC FAK-KD) in established subcutaneous B16F0 tumours improves melanoma cell sensitisation to doxorubicin. Doxorubicin treatment in EC FAK-KD mice reduced the percentage change in exponential B16F0 tumour growth further than in wild-type mice. There was no difference in tumour blood vessel numbers, vessel perfusion or doxorubicin delivery between genotypes, suggesting a possible angiocrine effect on the regulation of tumour growth. Doxorubicin reduced perivascular malignant cell proliferation, while enhancing perivascular tumour cell apoptosis and DNA damage in tumours grown in EC FAK-KD mice 48 h after doxorubicin injection. Human pulmonary microvascular ECs treated with the pharmacological FAK kinase inhibitors defactinib, PF-562,271 or PF-573,228 in combination with doxorubicin also reduced cytokine expression levels. Together, these data suggest that targeting EC FAK kinase activity may alter angiocrine signals that correlate with improved acute tumour cell chemosensitisation. © 2021 The Authors. The Journal of Pathology published by John WileySons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

LC3 (Light Chain 3) is a key player of autophagy, a major stress-responsive proteolysis pathway promoting cellular homeostasis. It coordinates the formation and maturation of autophagosomes and recruits cargo to be further degraded upon autophagosome-lysosome fusion. To orchestrate its functions, LC3 binds to multiple proteins from the autophagosomes’ inner and outer membranes, but the full extent of these interactions is not known. Moreover, LC3 has been increasingly reported in other cellular locations than the autophagosome, with cellular outcome not fully understood and not all related to autophagy. Furthermore, novel functions of LC3 as well as autophagy can occur in cells growing in a normal medium thus in non-stressed conditions. A better knowledge of the molecule in proximity to LC3 in normal growth conditions will improve the understanding of LC3 function in autophagy and in other cell biology function. Using an APEX2 based proteomic approach, we have detected 407 proteins in proximity to the well-characterised LC3B isoform in non-stress conditions. These include known and novel LC3B proximity proteins, associated with various cell localisation and biological functions. Sixty-nine of these proteins contain a putative LIR (LC3 Interacting Region) including 41 not reported associated to autophagy. Several APEX2 hits were validated by co-immunoprecipitation and co-immunofluorescence. This study uncovers the LC3B global interactome and reveals novel LC3B interactors, irrespective of LC3B localisation and function. This knowledge could be exploited to better understand the role of LC3B in autophagy and non-autophagy cellular processes.

Rheumatoid arthritis (RA) is a progressive degenerative disorder that leads to joint destruction. Available treatments only target the inflammatory component with minimal impact on joint repair. We recently uncovered a previously unappreciated family of pro-resolving mediators, the maresin conjugate in tissue regeneration (MCTR), that display both immunoregulatory and tissue-protective activities. Thus, we queried whether the production of these autacoids is disrupted in RA patients and whether they can be useful in treating joint inflammation and promoting joint repair.Using a highly phenotyped RA cohort we evaluated plasma MCTR concentrations and correlated these to clinical markers of disease activity. To evaluate the immunoregulatory and tissue reparative activities we employed both in vivo models of arthritis and organ culture models.Herein, we observed that plasma MCTR3 concentrations were negatively correlated with joint disease activity and severity in RA patients. Evaluation of the mechanisms engaged by this mediator in arthritic mice demonstrated that MCTR3 reprograms monocytes to confer enduring joint protective properties. Single cell transcriptomic profiling and flow cytometric evaluation of macrophages from mice treated with MCTR3-reprogrammed monocytes revealed a role for Arginase-1 (Arg-1) in mediating their joint reparative and pro-resolving activities. Arg-1 inhibition reversed both the anti-arthritic and tissue reparative actions of MCTR3-reprogrammed monocytes.Our findings demonstrate that circulating MCTR3 levels are negatively correlated with disease in RA. When administered to mice in vivo, MCTR3 displayed both anti-inflammatory and joint reparative activities, protecting both cartilage and bone in murine arthritis. These activities were, at least in part, mediated via the reprogramming of mononuclear phagocyte responses.This work was supported by funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant no: 677542) and the Barts Charity (grant no: MGU0343) to J.D. J.D. is also supported by a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (grant 107613/Z/15/Z).

PI3K-mammalian target of rapamycin and MAPK/ERK kinase (MEK)/mitogen-activated protein kinase (MAPK) are the most frequently dysregulated signaling pathways in cancer. A problem that limits the success of therapies that target individual PI3K-MAPK members is that these pathways converge to regulate downstream functions and often compensate each other, leading to drug resistance and transient responses to therapy. In order to overcome resistance, therapies based on cotreatments with PI3K/AKT and MEK/MAPK inhibitors are now being investigated in clinical trials, but the mechanisms of sensitivity to cotreatment are not fully understood. Using LC-MS/MS-based phosphoproteomics, we found that eukaryotic elongation factor 2 kinase (eEF2K), a key convergence point downstream of MAPK and PI3K pathways, mediates synergism to cotreatment with trametinib plus pictilisib (which target MEK1/2 and PI3Kα/δ, respectively). Inhibition of eEF2K by siRNA or with a small molecule inhibitor reversed the antiproliferative effects of the cotreatment with PI3K plus MEK inhibitors in a cell model-specific manner. Systematic analysis in 12 acute myeloid leukemia cell lines revealed that eEF2K activity was increased in cells for which PI3K plus MEKi cotreatment is synergistic, while PKC potentially mediated resistance to such cotreatment. Together, our study uncovers eEF2K activity as a key mediator of responses to PI3Ki plus MEKi and as a potential biomarker to predict synergy to cotreatment in cancer cells.

Paediatric low-grade gliomas (pLGGs) are the most common type of childhood CNS tumours. Our study included pilocytic astrocytomas (PAs; KIAA1549:BRAF), glioneuronal tumours (GNTs; BRAFV600E) and location-matched controls. We initially performed kinase substrate enrichment analysis (KSEA) to infer differential kinase activity, which allowed us to identify altered signalling networks in the two tumour types. Here we report the integration of these kinase signalling networks together with total proteomics, transcription factor enrichment analysis (TFEA) and transcriptomics (coding and non-coding). Total proteomic profiling confirmed an increase in proteins involved in cell cycle, inflammatory response and signal transduction in PAs, whilst there was an increase in proteins promoting cell growth, immune response and inflammation in GNTs. TFEA was performed using the DoRothEA database to identify master transcriptional regulators. We observed significant activation of transcription factors (TFs) that are direct targets of MAPK signalling in both tumour types. Notable differences include the higher activation of NF-kB/STAT TFs in PAs and the increased activation of RFX1/2 in GNTs. Next, we constructed kinase-TF networks and identified multiple kinases targeting STAT3 in PAs and STAT1/3 in GNTs. Pathway analysis of RNA-Sequencing data showed enrichment of NF-kB in both tumours and repression of E2F target genes (PA) and reduced expression of MYC target genes (GNT). We developed a BRAF-OIS signature and found 23 genes commonly enriched in both tumour types, highlighting shared senescence-associated targets. MicroRNA profiling identified upregulation of microRNAs that target MAPK and NF-kB signalling networks, and many down-regulated microRNAs with tumour suppressive roles. Finally, we identified several lncRNAs known to be differentially expressed in glioma and, whilst their mechanism(s) of action are varied, they are thought to act with other well-established regulators to fine-tune cellular processes. Taken together, we present a comprehensive signalling network as a framework for studying pLGGs.

Glioblastoma (GBM) is the most common and aggressive intrinsic brain tumour in adults. Epigenetic mechanisms controlling normal brain development are often dysregulated in GBM. Among these, BMI1, a structural component of the Polycomb Repressive Complex 1 (PRC1), which promotes the H2AK119ub catalytic activity of Ring1B, is upregulated in GBM and its tumorigenic role has been shown

Glioblastoma (GBM) is the most common and aggressive intrinsic brain tumour in adults. Epigenetic mechanisms controlling normal brain development are often dysregulated in GBM. Among these, BMI1, a structural component of the Polycomb Repressive Complex 1 (PRC1), which promotes the H2AK119ub catalytic activity of Ring1B, is upregulated in GBM and its tumorigenic role has been shown in vitro and in vivo. Here, we have used protein and chromatin immunoprecipitation followed by mass spectrometry (MS) analysis to elucidate the protein composition of PRC1 in GBM and transcriptional silencing of defining interactors in primary patient-derived GIC lines to assess their functional impact on GBM biology. We identify novel regulatory functions in mRNA splicing and cholesterol transport which could represent novel targetable mechanisms in GBM.

Summary Protein kinases lie at the heart of cell-signaling processes and are often mutated in disease. Kinase target recognition at the active site is in part determined by a few amino acids around the phosphoacceptor residue. However, relatively little is known about how most preferences are encoded in the kinase sequence or how these preferences evolved. Here, we used alignment-based approaches to predict 30 specificity-determining residues (SDRs) for 16 preferences. These were studied with structural models and were validated by activity assays of mutant kinases. Cancer mutation data revealed that kinase SDRs are mutated more frequently than catalytic residues. We have observed that, throughout evolution, kinase specificity has been strongly conserved across orthologs but can diverge after gene duplication, as illustrated by the G protein-coupled receptor kinase family. The identified SDRs can be used to predict kinase specificity from sequence and aid in the interpretation of evolutionary or disease-related genomic variants., Graphical Abstract, Highlights • 30 kinase specificity-determining residues (SDRs) predicted across 16 specificities • SDRs structurally rationalized and experimentally validated • SDRs often mutated in cancer, with different SDRs targeted in different specificities • Specificity conserved between orthologs, but SDRs can diverge between paralogs, Kinase substrate preferences are partly determined by specificity determinants in the kinase domain. However, for many specificities, the determinant residues are unknown. Bradley et al. used a sequence-based approach to predict specificity determinants across many kinases. The residues studied will aid in the interpretation of disease and evolutionary variants.

Cancer‐associated fibroblasts (CAFs) are considered the most abundant type of stromal cells in pancreatic ductal adenocarcinoma (PDAC), playing a critical role in tumour progression and chemoresistance; however, a druggable target on CAFs has not yet been identified. Here we report that focal adhesion kinase (FAK) activity (evaluated based on 397 tyrosine phosphorylation level) in CAFs is highly increased compared to its activity in fibroblasts from healthy pancreas. Fibroblastic FAK activity is an independent prognostic marker for disease‐free and overall survival of PDAC patients (cohort of 120 PDAC samples). Genetic inactivation of FAK within fibroblasts (FAK kinase‐dead, KD) reduces fibrosis and immunosuppressive cell number within primary tumours and dramatically decreases tumour spread. FAK pharmacologic or genetic inactivation reduces fibroblast migration/invasion, decreases extracellular matrix (ECM) expression and deposition by CAFs, modifies ECM track generation and negatively impacts M2 macrophage polarization and migration. Thus, FAK activity within CAFs appears as an independent PDAC prognostic marker and a druggable driver of tumour cell invasion., Understanding how cancer‐associated fibroblasts (CAFs) promote PDAC progression is of major interest given the poor prognosis of patients. This study identifies a druggable key regulator of CAF‐induced tumour cell metastasis and a prognostic factor: the protein Focal Adhesion Kinase (FAK).

Artificial intelligence and machine learning (ML) promise to transform cancer therapies by accurately predicting the most appropriate therapies to treat individual patients. Here, we present an approach, named Drug Ranking Using ML (DRUML), which uses omics data to produce ordered lists of >400 drugs based on their anti-proliferative efficacy in cancer cells. To reduce noise and increase predictive robustness, instead of individual features, DRUML uses internally normalized distance metrics of drug response as features for ML model generation. DRUML is trained using in-house proteomics and phosphoproteomics data derived from 48 cell lines, and it is verified with data comprised of 53 cellular models from 12 independent laboratories. We show that DRUML predicts drug responses in independent verification datasets with low error (mean squared error < 0.1 and mean Spearman’s rank 0.7). In addition, we demonstrate that DRUML predictions of cytarabine sensitivity in clinical leukemia samples are prognostic of patient survival (Log rank p, Artificial intelligence and machine learning promise to transform cancer therapies by accurately predicting the most appropriate drugs to treat individual patients. Here, the authors present an approach which uses omics data to produce ordered lists of drugs based on their effectiveness in decreasing cancer cell proliferation.

Widespread mammographic screening programs and improved self-monitoring allow for breast cancer to be detected earlier than ever before. Breast-conserving surgery is a successful treatment for select women. However, up to 40% of women develop local recurrence after surgery despite apparently tumor-free margins. This suggests that morphologically normal breast may harbor early alterations that contribute to increased risk of cancer recurrence. We conducted a comprehensive transcriptomic and proteomic analysis to characterize 57 fresh-frozen tissues from breast cancers and matched histologically normal tissues resected proximal to (p