Search

Background Chordomas are rare malignant bone cancers of the skull-base and spine. Patient survival is variable and not reliably predicted using clinical factors or molecular features. This study identifies prognostic epigenetic chordoma subtypes that are detected noninvasively using plasma methylomes. Methods Methylation profiles of 68 chordoma surgical samples were obtained between 1996 and 2018 across three international centers along with matched plasma methylomes where available. Results Consensus clustering identified two stable tissue clusters with a disease-specific survival difference that was independent of clinical factors in a multivariate Cox analysis (HR = 14.2, 95%CI: 2.1–94.8, P = 0.0063). Immune-related pathways with genes hypomethylated at promoters and increased immune cell abundance were observed in the poor-performing “Immune-infiltrated” subtype. Cell-to-cell interaction plus extracellular matrix pathway hypomethylation and higher tumor purity were observed in the better-performing “Cellular” subtype. The findings were validated in additional DNA methylation and RNA sequencing datasets as well as with immunohistochemical staining. Plasma methylomes distinguished chordomas from other clinical differential diagnoses by applying fifty chordoma-versus-other binomial generalized linear models in random 20% testing sets (mean AUROC = 0.84, 95%CI: 0.52–1.00). Tissue-based and plasma-based methylation signals were highly correlated in both prognostic clusters. Additionally, leave-one-out models accurately classified all tumors into their correct cluster based on plasma methylation data. Conclusions Here, we show the first identification of prognostic epigenetic chordoma subtypes and first use of plasma methylome-based biomarkers to noninvasively diagnose and subtype chordomas. These results may transform patient management by allowing treatment aggressiveness to be balanced with patient risk according to prognosis.

Prostate cancer is the second most frequently diagnosed non-skin cancer in men worldwide. Patient outcomes are remarkably heterogeneous and the best existing clinical prognostic tools such as International Society of Urological Pathology Grade Group, pretreatment serum PSA concentration and T-category, do not accurately predict disease outcome for individual patients. Thus, patients newly diagnosed with prostate cancer are often overtreated or undertreated, reducing quality of life and increasing disease-specific mortality. Biomarkers that can improve the risk stratification of these patients are, therefore, urgently needed. The ideal biomarker in this setting will be non-invasive and affordable, enabling longitudinal evaluation of disease status. Prostatic secretions, urine and blood can be sources of biomarker discovery, validation and clinical implementation, and mass spectrometry can be used to detect and quantify proteins in these fluids. Protein biomarkers currently in use for diagnosis, prognosis and relapse-monitoring of localized prostate cancer in fluids remain centred around PSA and its variants, and opportunities exist for clinically validating novel and complimentary candidate protein biomarkers and deploying them into the clinic. Biomarkers that can improve risk stratification of patients with prostate cancer are urgently needed. In this Review, Khoo et al. outline mass spectrometry technologies that enable the systematic discovery and targeted validation of protein-based biomarkers in prostate-associated fluids.

Meningiomas are the most common primary intracranial tumour in adults1. Patients with symptoms are generally treated with surgery as there are no effective medical therapies. The World Health Organization histopathological grade of the tumour and the extent of resection at surgery (Simpson grade) are associated with the recurrence of disease; however, they do not accurately reflect the clinical behaviour of all meningiomas2. Molecular classifications of meningioma that reliably reflect tumour behaviour and inform on therapies are required. Here we introduce four consensus molecular groups of meningioma by combining DNA somatic copy-number aberrations, DNA somatic point mutations, DNA methylation and messenger RNA abundance in a unified analysis. These molecular groups more accurately predicted clinical outcomes compared with existing classification schemes. Each molecular group showed distinctive and prototypical biology (immunogenic, benign NF2 wild-type, hypermetabolic and proliferative) that informed therapeutic options. Proteogenomic characterization reinforced the robustness of the newly defined molecular groups and uncovered highly abundant and group-specific protein targets that we validated using immunohistochemistry. Single-cell RNA sequencing revealed inter-individual variations in meningioma as well as variations in intrinsic expression programs in neoplastic cells that mirrored the biology of the molecular groups identified. Multi-omics datasets are integrated to generate a unified and clinically informed molecular classification of meningiomas.

Cancer metabolism adapts the metabolic network of its tissue of origin. However, breast cancer is not a disease of a single origin. Multiple epithelial populations serve as the culprit cell of origin for specific breast cancer subtypes, yet our knowledge of the metabolic network of normal mammary epithelial cells is limited. Using a multi-omic approach, here we identify the diverse metabolic programmes operating in normal mammary populations. The proteomes of basal, luminal progenitor and mature luminal cell populations revealed enrichment of glycolysis in basal cells and of oxidative phosphorylation in luminal progenitors. Single-cell transcriptomes corroborated lineage-specific metabolic identities and additional intra-lineage heterogeneity. Mitochondrial form and function differed across lineages, with clonogenicity correlating with mitochondrial activity. Targeting oxidative phosphorylation and glycolysis with inhibitors exposed lineage-rooted metabolic vulnerabilities of mammary progenitors. Bioinformatics indicated breast cancer subtypes retain metabolic features of their putative cell of origin. Thus, lineage-rooted metabolic identities of normal mammary cells may underlie breast cancer metabolic heterogeneity and targeting these vulnerabilities could advance breast cancer therapy.

Triple negative breast cancer (TNBC) stands out due to its aggressive course and high metastatic rates. No consistent protein biomarker has been described for TNBC, resulting in a scarcity of adjuvant therapies for the afflicted patients. Hence, there is an urgent need to determine novel TNBC-associated proteins for the development of new therapeutics and the identification of novel molecular mechanisms driving this malignancy. Cell surface proteins represent attractive targets for novel therapies, due to their easily accessible localization and their involvement in essential signaling pathways. Objectives: We aimed to uncover novel TNBC-associated cell surface proteins involved in carcinogenesis and metastasis for the development of novel targeted therapeutics. Rationale: Taking advantage of the fact that cell surface proteins are often N-glycosylated, we employed hydrazide chemistry to isolate N-glycopeptides. The glycoproteome of six immortalized TNBC cell lines and five ‘healthy’ controls (HC) (the immortalized cell line MCF10A and four patient-derived human mammary epithelial cell lines) was analyzed using LC-MS/MS and label-free quantification. A data mining strategy was employed to select candidates of interest. We knocked-down (k.d.) the top five candidates of interest (using siRNA technology) and evaluated cell growth using growth-curve analysis. Plexin B3 (PLXNB3) was selected for subsequent functional validations. The effects of PLXNB3 k.d. (using siRNA and CRISPR technology) on cancer cell growth, apoptosis and adhesion were interrogated using western blotting and standard cell biology protocols.Results: The N-glycoproteomics approach led to the identification of 1044 glycoproteins, with over 70% described as plasma membrane/secreted proteins. Gene Ontology analysis revealed that the TNBC-associated glycoproteome was enriched in biological processes such as: mesenchyme development, MAPK signaling, positive regulation of proliferation and regulation of neuron projection development. Candidates of interest were selected from our list by focusing on those plasma membrane proteins that were enriched in TNBC cells compared to HC according to our label-free quantified proteomics data, and that showed limited expression in healthy tissues according to the Human Protein Atlas. We further restricted the list of candidates to those proteins whose k.d. impaired cancer cell growth, with little effect on the HC. PLXNB3, an understudied protein typically expressed in healthy neuronal tissues, was selected for in depth functional analysis. Elevated mRNA PLXNB3 levels in breast cancer patients is associated with poorer overall survival compared to low mRNA expression (Integrated TCGA Pan-Cancer Clinical Data Resource, 2018). PLXNB3 k.d. (using siRNA and CRISPR technologies) impaired TNBC cell growth (in both adherent and spheroid cultures) and was associated with elevated levels of cleaved-caspase 3 and cleaved-caspase 7 compared to scrambled controls. Furthermore, PLXNB3 k.d. negatively impacted TNBC cell adhesion to extracellular matrixes compared to scrambled controls. Subsequent tests will evaluate PLXNB3’s role in tumor growth and metastasis in vivo, using orthotopic tumor models in immunocompromised mice. Citation Format: Laura Kuhlmann, Ankit Sinha, Vladimir Ignatchenko, Andrew Macklin, Lydia Liu, Meinusha Govindarajan, Amanda Khoo, Salvador Mejia-Guerrero, Jennifer Cruickshank, Hal Berman, Thomas Kislinger. Identification of cell surface proteins in triple negative breast cancer for the development of novel targeted therapies [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS18-31.

High-grade serous carcinoma (HGSC) is the most prevalent and aggressive subtype of ovarian cancer. The large degree of clinical heterogeneity within HGSC has justified deviations from the traditional one-size-fits-all clinical management approach. However, the majority of HGSC patients still relapse with chemo-resistant cancer and eventually succumb to their disease, evidence that further work is needed to improve patient outcomes. Advancements in high-throughput technologies have enabled novel insights into biological complexity, offering a large potential for informing precision medicine efforts. Here, we review the current landscape of clinical management for HGSC and highlight applications of high-throughput biological approaches for molecular subtyping and the discovery of putative blood-based biomarkers and novel therapeutic targets. Additionally, we present recent improvements in model systems and discuss how their intersection with high-throughput platforms and technological advancements is positioned to accelerate the realization of precision medicine in HGSC.

The intercalated disc (ICD) is unique membrane structure that is indispensable to normal heart function. However, its structural organization is not well understood. Previously, we showed that the ICD-bound transmembrane protein 65 (Tmem65) was required for connexin 43 (Cx43) localization in cultured mouse neonatal cardiomyocytes. Here, we investigated the role of Tmem65 in ICD organization in vivo . A mouse model was established by injecting CD1 mouse pups (3-7 days after birth) with recombinant adeno-associated virus 9 (rAAV9) harboring Tmem65 (or scrambled) shRNA. Quantitative polymerase chain reaction (qPCR) and immunoblots confirmed greater than 85% reduction in Tmem65 expression (7.1±0.7% remained for Tmem65 proteins; 14.4±2.5% remained for Tmem65 transcripts, n =4) in mouse ventricles compared to control hearts. Tmem65 knockdown (KD) mice exhibited heart failure-like symptoms as early as 3 weeks post viral administration. Specifically, Tmem65 KD mice developed eccentric hypertrophic cardiomyopathy in 3 weeks and dilated cardiomyopathy with severe cardiac fibrosis in 7 weeks, as confirmed by H&E and Masson’s Trichrome staining. Echocardiography and electrocardiography, respectively, showed depressed hemodynamics (19.27±1.46ml/min for cardiac output in control hearts vs. 6.63±0.52ml/min for Tmem65 KD hearts, n =6) and impaired conduction, including prolonged PR (22.7±1.85ms in control hearts vs. 28.89±3.85ms in Tmem65 KD hearts, n≥8), QRS intervals (10.47±0.42ms in control hearts vs. 16.35±0.36ms in Tmem65 KD hearts, n≥8), and slowed heart rate (415±10bpm in control hearts vs. 347±16bpm in Tmem65 KD hearts, n≥8) in Tmem65 KD mouse hearts. Immunoprecipitation and super-resolution microscopy confirmed the physical interaction and localization between Tmem65 and voltage-gated sodium channel β subunit (β1) at the ICD and this interaction was evidently required for the establishment of perinexal nanodomains and voltage-gated sodium channel 1.5 (NaV1.5) localization to the ICD. Disrupting Tmem65 function, thus, impaired perinexal structure, reduced conduction velocity, and ultimately resulted in cardiomyopathy in vivo .

To model the problem of radiation resistance in prostate cancer, cell lines mimicking a clinical course of conventionally fractionated or hypofractionated radiotherapy have been generated. Proteomic analysis of radiation resistant and radiosensitive DU145 prostate cancer cells detected 4410 proteins. Over 400 proteins were differentially expressed across both radiation resistant cell lines and pathway analysis revealed enrichment in epithelial to mesenchymal transition, glycolysis and hypoxia. From the radiation resistant protein candidates, the cell surface protein CD44 was identified in the glycolysis and epithelial to mesenchymal transition pathways and may serve as a potential therapeutic target.

Oncogenesis is driven by germline, environmental and stochastic factors. It is unknown how these interact to produce the molecular phenotypes of tumors. We therefore quantified the influence of germline polymorphisms on the somatic epigenome of 589 localized prostate tumors. Predisposition risk loci influence a tumor’s epigenome, uncovering a mechanism for cancer susceptibility. We identified and validated 1,178 loci associated with altered methylation in tumoral but not nonmalignant tissue. These tumor methylation quantitative trait loci influence chromatin structure, as well as RNA and protein abundance. One prominent tumor methylation quantitative trait locus is associated with AKT1 expression and is predictive of relapse after definitive local therapy in both discovery and validation cohorts. These data reveal intricate crosstalk between the germ line and the epigenome of primary tumors, which may help identify germline biomarkers of aggressive disease to aid patient triage and optimize the use of more invasive or expensive diagnostic assays. Genetic variants in the germ line modulate DNA methylation in tumors and contribute to the aggressiveness of prostate cancer.

It has long been assumed that all normal cells have the same capacity to engage homologous recombination (HR) and non-homologous end joining (NHEJ) to repair DNA double-strand breaks (DSBs), a concept exploited for DNA-damaging chemotherapeutics. We show that mammary epithelial lineage dictates the DSB repair pathway choice. Primary mammary proteomes and DSB repair enumeration by γ-H2AX, Rad51 and DNA-PKc foci reveal that NHEJ operates in all epithelial cells, but high-fidelity HR is restricted to the luminal lineage. This translates to divergent poly (ADP-ribose) polymerase inhibitor (PARPi) vulnerability of mammary epithelial progenitor activity in both mouse and human, irrespective of the BRCA1/2 status. Proteome-defined lineage-specific signatures correlate to breast cancer subtypes and predict PARPi response of triple-negative human breast cancer xenografts. These intrinsically divergent HR characteristics of mammary cell types underpin a new strategy for identifying PARPi responders.

SummaryPancreatic ductal adenocarcinoma (PDAC) remains resistant to most treatments and demonstrates a complex pathobiology. Here, we deconvolute regional heterogeneity in the human PDAC tumor microenvironment (TME), a long-standing obstacle, to define precise stromal contributions to PDAC progression. Large scale integration of histology-guided multiOMICs with clinical data sets and functional in vitro models uncovers two microenvironmental programs in PDAC that were anchored in fibroblast differentiation states. These sub-tumor microenvironments (subTMEs) co-occurred intratumorally and were spatially confined, producing patient-specific cellular and molecular heterogeneity associated with shortened patient survival. Each subTME was uniquely structured to support discrete aspects of tumor biology: reactive regions rich in activated fibroblast communities were immune-hot and promoted aggressive tumor progression while deserted regions enriched in extracellular matrix supported tumor differentiation yet were markedly chemoprotective. In conclusion, PDAC regional heterogeneity derives from biologically distinct reactive and protective TME elements with a defined, active role in PDAC progression.Graphical Abstract & Key findingsPDAC regional heterogeneity originates in sub-tumor microenvironments (subTMEs)SubTMEs exhibit distinct immune phenotypes and CAF differentiation statesDifferent subTMEs are either tumor-promoting or chemoprotectiveIntratumoral subTME co-occurrence links stromal heterogeneity to patient outcome

In the current study we examined several proteomic- and RNA-Seq-based datasets of cardiac-enriched, cell-surface and membrane-associated proteins in human fetal and mouse neonatal ventricular cardiomyocytes. By integrating available microarray and tissue expression profiles with MGI phenotypic analysis, we identified 173 membrane-associated proteins that are cardiac-enriched, conserved amongst eukaryotic species, and have not yet been linked to a ‘cardiac’ Phenotype-Ontology. To highlight the utility of this dataset, we selected several proteins to investigate more carefully, including FAM162A, MCT1, and COX20, to show cardiac enrichment, subcellular distribution and expression patterns in disease. We performed three-dimensional confocal imaging analysis to validate subcellular localization and expression in adult mouse ventricular cardiomyocytes. FAM162A, MCT1, and COX20 were expressed differentially at the transcriptomic and proteomic levels in multiple models of mouse and human heart diseases and may represent potential diagnostic and therapeutic targets for human dilated and ischemic cardiomyopathies. Altogether, we believe this comprehensive cardiomyocyte membrane proteome dataset will prove instrumental to future investigations aimed at characterizing heart disease markers and/or therapeutic targets for heart failure.

Cells exhibit a broad spectrum of functions driven by differences in molecular phenotype. Understanding the heterogeneity between and within cell types has led to advances in our ability to diagnose and manipulate biological systems. Heterogeneity within and between tumors still poses a challenge to the development and efficacy of therapeutics. In this Perspective we review the toolkit of protein-level experimental approaches for investigating cellular heterogeneity. We describe how innovative approaches and technical developments have supported the advent of bottom-up single-cell proteomic analysis and present opportunities and challenges within cancer research. Finally, we introduce the concept of "precision proteomics" and discuss how the advantages and limitations of various experimental approaches render them suitable for different biological systems and questions.

Cancer is the second most common cause of death worldwide and its heterogeneity complicates therapy. Standard cytotoxic regiments disrupt rapidly dividing cells, regardless of their neoplastic status. The introduction of less toxic targeted therapies has partially contributed to the observed decrease in cancer-related mortality. Cell-surface proteins represent attractive targets for therapy, due to their easily-accessible localization and their involvement in essential signaling pathways, often dysregulated in cancer. Despite their clinical appeal, cell-surface proteins are often underrepresented in standard proteomic data sets, due to their poor solubility and lower expression levels compared to intracellular proteins. Areas covered: This review will summarize some of the available techniques for enriching the cell-surface proteome, and discuss their advantages, limitations and applicability to clinical sample-testing. Moreover, we discuss currently available strategies for the development of novel targeted therapies in cancer. Expert commentary: The interest in elucidating the cancer-associated surfaceome is growing and will likely benefit from recent advancements in instrument sensitivity, method development, and a growing body of high-quality proteomics databases. Multiomics studies, in combination with functional validations (e.g. dropout screens), and evaluation of the healthy surfaceome, will likely aid in the selection of relevant targets for future therapy development.

Intratumoral heterogeneity is a critical frontier in understanding how the tumor microenvironment (TME) propels malignant progression. We recently deconvoluted regional heterogeneity in the human PDAC stroma to assess its role in disease progression and discovered two types of ‘sub-tumor microenvironments’ (subTMEs), called ‘reactive’ and ‘deserted’. These histologically definable tissue states exhibit strong regional relationships with tumor immunity, subtypes, differentiation, and treatment response. Here, we set out to define their cell biological underpinnings through a combination of subTME-specific cancer-associated fibroblast (CAF) models, integrative histopathology, quantitative image analysis, multiOMICs, scRNAseq, and controlled functional assays. Remarkably, the growth patterns of CAF cultures closely recapitulated the characteristic histomorphology of their originating subTMEs, and these distinct phenotypes were accompanied by behavioral differences. Unsupervised graph-based clustering of scRNAseq profiles showed that CAFs largely grouped by their originating subTME yet comprised up to 10 individual clusters. The subTME-specific multi-subpopulation CAF communities self-organized into distinct ‘coordinated states’, represented by cluster-overarching functional profiles and distinct morpho-histological and behavioral phenotypes. These differences originated in cellular differentiation trajectories, with an ‘intermediate’ transitory state evident both in single cell transcriptomics and in situ. Noticeably, this CAF differentiation potential was associated with distinct tumor-related functions and, similar to stem cells, was marked by RNA diversity and pluripotency markers. Therefore, regional TME programs in PDAC appear to result largely from transitions between subpopulation-overarching fibroblast differentiation states that guide multifaceted CAF and immune cell communities into recurrent tissue self-organizational units. Citation Format: Barbara T. Grünwald, Curtis McCloskey, Antoine Devisme, Foram Vyas, Geoffroy Andrieux, Kazeera Aliar, Faiyaz Notta, Grainne O’Kane, Julie Wilson, Jennifer Knox, Sandra Fischer, Thomas Kislinger, Melanie Boerries, Steven Gallinger, Rama Khokha. Fibroblast differentiation trajectories elicit regional tissue states in pancreatic cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-107.

Resistance to genotoxic therapies and tumor recurrence are hallmarks of glioblastoma (GBM), an aggressive brain tumor. Here, we explore the functional drivers of post-treatment recurrent GBM. By conducting genome-wide CRISPR-Cas9 screens in patient-derived GBM models, we uncover distinct genetic dependencies in recurrent tumor cells that were absent in their patient-matched primary predecessors, accompanied by increased mutational burden and differential transcript and protein expression. These analyses support parallel tumor-intrinsic mechanisms of treatment resistance which rely on acquisition of immunosuppressive capacity, including a defective mismatch repair pathway, ablation of PTEN activity, and a novel combination of de novo mutations in SWI/SNF components. We map a multilayered genetic and functional response to resist chemoradiotherapy and drive tumor recurrence, identifying protein tyrosine phosphatase 4A2 (PTP4A2) as a novel driver of self-renewal, proliferation and tumorigenicity at GBM recurrence. Mechanistically, genetic perturbation and a small molecule inhibitor of PTP4A2 repress axon guidance activity through a dephosphorylation axis with roundabout guidance receptor 1 (ROBO1) and exploit a genetic dependency on ROBO signaling. Importantly, engineered anti-ROBO1 single-domain antibodies also mimic the effects of PTP4A2 inhibition. We conclude that functional reprogramming drives tumorigenicity and present a dependence on a PTP4A2-ROBO1 signaling axis at GBM recurrence.

BACKGROUND Chordomas are malignant bone cancers arising from the skull-base and spine that are rare but cause devastating central nervous system morbidities. Survival is highly variable despite surgery and radiotherapy as 10% live under 1 year and 30-35% survive over 20 years. There are currently no reliable prognostic factors and this limits our ability to tailor patient treatment to their risk. Accordingly, this work identifies epigenetic prognostic chordoma subgroups that are detectable non-invasively through plasma methylomes to guide treatment. METHODS A total of 68 chordoma surgical specimens resected between 1996-2018 across three international centres underwent DNA methylation profiling. Cell-free methylated tumor DNA immunoprecipitation and high-throughput sequencing was performed on available matched plasma samples. RESULTS Two stable tumor clusters were identified through consensus clustering of tissue methylation data. Clusters had statistically significantly different disease-specific survivals (log-rank p=0.0062) independent of clinical factors in a multivariable Cox analysis (HR=16.5, 95%CI: 2.8-96, p=0.0018). The poorer-performing “Immune-infiltrated” cluster had genes hypomethylated at promoters, typically resulting in transcription, within immune-related pathways and higher immune cell abundance within tumors. The better-performing “Cellular” cluster showed higher tumor cellularity plus cell-to-cell interaction and extracellular matrix pathway hypomethylation. Fifty chordoma-versus-other binomial generalized linear models built using plasma methylome data distinguished chordomas from meningiomas and spinal metastases, as representative clinical differential diagnoses, in random left-out 20% testing sets (mean AUROC=0.84, 95%CI: 0.52-1.00). Plasma-based methylation signatures were highly correlated with tissue-based signals within both poor-performing (median r=0.69, 95%CI: 0.66-0.72) and better-performing cluster tumors (median r=0.67, 95%CI: 0.62-0.72). CONCLUSIONS The first identification of two distinct prognostic epigenetic chordoma subgroups is shown here with “Immune-infiltrated” tumors having a poorer prognosis than “Cellular” tumors. Plasma methylomes can be utilized for non-invasive chordoma diagnosis and subtyping. This work may transform chordoma treatment decision-making by guiding surgical planning in advance to match resection aggressiveness with patient prognosis.

Recurrence of solid tumors renders patients vulnerable to a distinctly advanced, highly treatment-refractory disease state that has an increased mutational burden and novel oncogenic drivers not detected at initial diagnosis. Improving outcomes for recurrent cancers requires a better understanding of cancer cell populations that expand from the post-therapy, minimal residual disease (MRD) state. We profiled barcoded tumor cell populations through therapy at tumor initiation/engraftment, MRD and recurrence in our therapy-adapted, patient-derived xenograft models of glioblastoma (GBM). Tumors showed distinct patterns of recurrence in which clonal populations exhibited either a priori, pre-existing fitness, or equipotent fitness acquired through therapy. Characterization of the MRD state by single-cell and bulk RNA sequencing revealed a tumor-intrinsic immunomodulatory signature with strong prognostic significance at the transcriptomic level and in proteomic analysis of cerebrospinal fluid (CSF) collected from GBM patients at all stages of disease. Our results provide insight into the innate and therapy-driven dynamics of human glioblastoma, and the prognostic value of the interrogating of the MRD state in solid cancers.

Intratumoral heterogeneity is a critical frontier in understanding how the tumor microenvironment (TME) propels malignant progression. Here, we deconvolute the human pancreatic TME through large-scale integration of histology-guided regional multiOMICs with clinical data and patient-derived preclinical models. We discover "subTMEs," histologically definable tissue states anchored in fibroblast plasticity, with regional relationships to tumor immunity, subtypes, differentiation, and treatment response. "Reactive" subTMEs rich in complex but functionally coordinated fibroblast communities were immune hot and inhabited by aggressive tumor cell phenotypes. The matrix-rich "deserted" subTMEs harbored fewer activated fibroblasts and tumor-suppressive features yet were markedly chemoprotective and enriched upon chemotherapy. SubTMEs originated in fibroblast differentiation trajectories, and transitory states were notable both in single-cell transcriptomics and in situ. The intratumoral co-occurrence of subTMEs produced patient-specific phenotypic and computationally predictable heterogeneity tightly linked to malignant biology. Therefore, heterogeneity within the plentiful, notorious pancreatic TME is not random but marks fundamental tissue organizational units.

Cancer metabolism adapts the metabolic network of its tissue-of-origin. However, breast cancer is not a disease of a singular origin. Multiple epithelial populations serve as the culprit cell-of-origin for specific breast cancer subtypes, yet knowledge surrounding the metabolic network of normal mammary epithelial cells is limited. Here, we show that mammary populations have cell type-specific metabolic programs. Primary human breast cell proteomes of basal, luminal progenitor, and mature luminal populations revealed their unique enrichment of metabolic proteins. Luminal progenitors had higher abundance of electron transport chain subunits and capacity for oxidative phosphorylation, whereas basal cells were more glycolytic. Targeting oxidative phosphorylation and glycolysis with inhibitors exposed distinct metabolic vulnerabilities of the mammary lineages. Computational analysis indicated that breast cancer subtypes retain metabolic features of their putative cell-of-origin. Lineage-restricted metabolic identities of normal mammary cells partly explain breast cancer metabolic heterogeneity and rationalize targeting subtype-specific metabolic vulnerabilities to advance breast cancer therapy.

Intercalated discs (ICDs) are unique and functionally indispensible to the heart, but its structural organization remains less understood. Previously, we showed that an ICD-bound transmembrane protein 65 (Tmem65) was required for Connexin 43 (Cx43) localization in cultured mouse neonatal cardiomyocytes, and that reduced Tmem65 was associated with a decrease and internalization of Cx43, and impaired electrical conduction between neighboring cardiomyocytes. Here, we investigated the role of Tmem65 in vivo by injecting CD1 mice with recombinant adeno-associated virus 9 (rAAV9) harboring Tmem65 (or scrambled) shRNA. Quantitative polymerase chain reactions and immunoblots confirmed greater than 90% reduction in Tmem65 expression in mouse ventricles compared to control samples. Immunoblots and immunofluorescence showed reduced and internalized Cx43 in Tmem65 knockdown (KD) hearts compared to controls, respectively. Kaplain-Meier survival plot showed that all Tmem65 KD mice died within 7 weeks (> 50% death 3 weeks post viral injection), whereas no death was seen in control mice. Tmem65 KD mice developed eccentric hypertrophic cardiomyopathy in 3 weeks and dilated cardiomyopathy with severe cardiac fibrosis in 7 weeks as confirmed by H&E and Masson’s Trichrome staining. Echocardiography also confirmed ventricular dilatation and showed a 60% reduction in cardiac output (19.27±1.46 mL/min in control vs. 6.63±0.52 mL/min in Tmem65 KD mice, pin vivo .

DNA sequencing has identified recurrent mutations that drive the aggressiveness of prostate cancers. Surprisingly, the influence of genomic, epigenomic, and transcriptomic dysregulation on the tumor proteome remains poorly understood. We profiled the genomes, epigenomes, transcriptomes, and proteomes of 76 localized, intermediate-risk prostate cancers. We discovered that the genomic subtypes of prostate cancer converge on five proteomic subtypes, with distinct clinical trajectories. ETS fusions, the most common alteration in prostate tumors, affect different genes and pathways in the proteome and transcriptome. Globally, mRNA abundance changes explain only ∼10% of protein abundance variability. As a result, prognostic biomarkers combining genomic or epigenomic features with proteomic ones significantly outperform biomarkers comprised of a single data type.

Glioblastoma (GBM) is characterized by extensive cellular and genetic heterogeneity. A wealth of literature describes the biology of primary GBM (p-GBM), but we currently lack an understanding of how GBM evolves through therapy to become a very different tumor at recurrence, which may explain why therapies against p-GBM fail to work in recurrent GBM (r-GBM). Therefore, to understand the evolution of r-GBM, we aimed to characterize patient-matched p-GBM and r-GBM proteome and identify potential therapeutic targets for r-GBM. We collected one of the world’s largest patient-matched p-GBM and r-GBM samples from the Hamilton Health Sciences for gene expression profiling, proteomic analyses and tissue microarray (TMA) construction. Nano-String analysis was performed for GBM subtype identification. Furthermore, patient demographics was generated for survival analysis. The top potential therapeutic targets for r-GBM were identified by proteomic analysis and were validated on TMA using immunohistochemistry. The essentiality of each protein in r-GBM were assessed using CRISPR KO studies and the top hit were selected for pre-clinical testing. 6798 proteins were detected by shotgun, label-free proteomic analyses. Differential expression analysis on the surface proteins revealed a distinct set of proteins overexpressed in r-GBM among which 7 proteins were selected as top potential therapeutic targets for r-GBM. Besides, the patients were grouped based on survival rate and the differential expression analysis revealed significantly enriched proteins and pathways in short-term survivors which cause aggressive phenotypes in GBM. In addition, consensus clustering identified five protein clusters which show distinction between primary vs recurrent tumors. Our data also strongly supports a preponderance of immune regulatory/suppressive genes as important drivers of r-GBM. This study resulted in identification of diagnostic and predictive biomarkers which is extremely complementary and instructive for the development of new poly-therapeutic paradigms for GBM patients at the recurrent level and will lead to improvement of patient’s survival. Citation Format: Nazanin Tatari, Shahbaz Khan, Julie Livingstone, Chitra Venugopal, Jennifer Chan, Cynthia Hawkins, John Provias, Jian-Qiang Lu, Kjetil Ask, Thomas Kislinger, Sheila Singh. Uncovering the evolution of Glioblastoma proteome landscape from primary to the recurrent stage for development of novel diagnostic and predictive biomarkers [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr PO052.

Glioblastoma (GBM) is a highly fatal brain cancer where mortality is predominantly caused by disease recurrence and lack of second-line therapies. Here, utilizing genome-wide CRISPR-Cas9 screening, we uncover treatment-based conditional genetic interactions modulating sensitivity to combined radiation therapy (RT) and temozolomide (TMZ), the standard of care treatment administered to over 70% of glioblastoma patients. To investigate therapy-induced changes in the functional landscape of glioblastoma stem cells (GSCs) without confounding patient-to-patient differences, we systematically mapped genetic dependencies in patient-matched pre-treatment primary and post-treatment recurrent GSCs. This comparison highlights a remodelling of genes and pathways regulating tumor cell survival at disease relapse, arming recurrent GSCs with newly acquired genetic drivers and further loss of tumor suppressors. Among these genes, we identify PTP4A2, encoding protein tyrosine phosphatase 4A2, as a major regulator of stemness and tumorigenicity in recurrent GSCs. Genetic perturbation or pharmacological inhibition of PTP4A2 influences the phosphorylation status and expression of interacting proteins belonging to axonal guidance pathways, as phosphoproteomic studies showed specific enrichment in axon guidance regulator Roundabout Guidance Receptor 1 (ROBO1) in recurrent GSCs. We therefore designed and developed efficacious Camelid biotinylated single-domain antibody (bio-sdAb) and tetrameric complexes targeting human ROBO1 (MKRo-20). Subsequently, we orthotopically engrafted recurrent GSCs into immunocompromised mice and administered local treatments of tetrameric MKRo-20. All mice treated with tetrameric MKRo-20 were rendered tumor free, suggesting that modulation of ROBO1 with bio-sdAbs presents a new immunotherapeutic strategy to target recurrent glioblastoma. Our work reveals a context-specific dependence on axonal guidance through a PTP4A2-ROBO axis in recurrent glioblastoma, highlighting new avenues of therapeutic intervention for second-line therapy in GBM. This abstract is also being presented as PO025. Citation Format: Chirayu Chokshi, David Tieu, Kevin Brown, Chitra Venugopal, Lina Liu, Laura Kuhlman, Katherine Chan, Amy Tong, Neil Savage, Dillon McKenna, Nikoo Aghaei, Minomi Subapanditha, Joseph M Salamoun, Martin Rossotti, Peter Wipf, Elizabeth Sharlow, John S. Lazo, Thomas Kislinger, Kevin Henry, Yu Lu, Jason Moffat, Sheila K. Singh. The functional genomic landscape of recurrent glioblastoma [abstract]. In: Abstracts: AACR Virtual Special Conference: Tumor Immunology and Immunotherapy; 2020 Oct 19-20. Philadelphia (PA): AACR; Cancer Immunol Res 2021;9(2 Suppl):Abstract nr PR009.

Availability of lung cancer models that closely mimic human tumors remains a significant gap in cancer research, as tumor cell lines and mouse models may not recapitulate the spectrum of lung cancer heterogeneity seen in patients. We aimed to establish a patient-derived tumor xenograft (PDX) resource from surgically resected non-small cell lung cancer (NSCLC). Fresh tumor tissue from surgical resection was implanted and grown in the subcutaneous pocket of non-obese severe combined immune deficient (NOD SCID) gamma mice. Subsequent passages were in NOD SCID mice. A subset of matched patient and PDX tumors and non-neoplastic lung tissues were profiled by whole exome sequencing, single nucleotide polymorphism (SNP) and methylation arrays, and phosphotyrosine (pY)-proteome by mass spectrometry. The data were compared to published NSCLC datasets of NSCLC primary and cell lines. 127 stable PDXs were established from 441 lung carcinomas representing all major histological subtypes: 52 adenocarcinomas, 62 squamous cell carcinomas, one adeno-squamous carcinoma, five sarcomatoid carcinomas, five large cell neuroendocrine carcinomas, and two small cell lung cancers. Somatic mutations, gene copy number and expression profiles, and pY-proteome landscape of 36 PDXs showed greater similarity with patient tumors than with established cell lines. Novel somatic mutations on cancer associated genes were identified but only in PDXs, likely due to selective clonal growth in the PDXs that allows detection of these low allelic frequency mutations. The results provide the strongest evidence yet that PDXs established from lung cancers closely mimic the characteristics of patient primary tumors.

Pancreatic ductal adenocarcinoma (PDAC) remains mostly untreatable while its incidence is on the rise. PDAC stroma should be a reservoir for novel therapeutic targets. Yet, stromal cellular complexity and an extensive intratumoral heterogeneity in human patients have left the functions of PDAC stroma poorly understood and likely hamper its targeting. Here, we set out to deconvolute regional heterogeneity in human PDAC stroma and assess its role in disease progression. Using resected & advanced biospecimens with known patient outcome, we mapped the stromal and epithelial landscapes of PDAC by combining integrative histopathology, quantitative image analysis of a 30-marker IHC panel, genomics and proteomics, machine learning, scRNAseq of PDAC-derived fibroblasts, and controlled functional assays. This histology-guided multidimensional approach revealed two overarching types of sub-tumormicroenvironments (subTMEs) in PDAC, present across stages and primary and metastatic sites. These subTMEs co-occurred intratumourally but were spatially confined, producing patient-specific cellular and molecular heterogeneity in PDAC stroma. SubTME-resolved IHC characterization of PDAC specimens and multiplexed functional analyses with subTME-specific patient-derived fibroblasts and organoids then identified how both microenvironmental programs were uniquely structured to support crucial aspects of tumour biology. Forming a complementary stromal support system, reactive subTME regions rich in fibroblasts and immune cells were vascularized and promoted features of aggressive tumour progression, while protective subTME regions enriched in ECM supported tumour differentiation yet were markedly chemoprotective and translated into poor treatment response during 1st line chemotherapy. Consequently, tumours benefited from concomitant presence of both subTMEs and patients with phenotypically heterogenous stroma displayed shortened survival. Our patient-matched multidimensional data were then used to train a Random Forest model for prediction of subTME presence from bulk RNAseq samples. This again stratified PDAC patients in the independent TCGA cohort into distinct clinical outcomes by stromal phenotypic heterogeneity. In conclusion, we have delineated human PDAC stroma to subtype its heterogeneity into phenotypically distinct reactive and protective elements. This defines the active role of two overarching sub-microenvironment types in PDAC progression and sets a path towards developing novel stroma-instructed therapies. Citation Format: Barbara T. Grünwald, Antoine Devisme, Foram Vyas, Geoffroy Andrieux, Gun Ho Jang, Kazeera Aliar, Curtis McCloskey, Andrew Macklin, Joan Miguel Romero, Laura Tamblyn, Nikolina Radulovich, Peter Bronsert, Grainne O’Kane, Julie Wilson, Jennifer Knox, Sandra Fischer, Thomas Kislinger, Melanie Boerries, Steven Gallinger, Rama Khokha. Stromal phenotypic heterogeneity fosters pancreatic cancer progression [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PR-002.

Author(s): Otto, Joseph J; Correll, Vanessa L; Engstroem, Hampus A; Hitefield, Naomi L; Main, Brian P; Albracht, Brenna; Johnson-Pais, Teresa; Yang, Li Fang; Liss, Michael; Boutros, Paul C; Kislinger, Thomas; Leach, Robin J; Semmes, Oliver J; Nyalwidhe, Julius O | Abstract: PurposeThe rs17632542 single nucleotide polymorphism (SNP) results in lower serum prostate specific antigen (PSA) levels which may further mitigate against its clinical utility as a prostate cancer biomarker. Post-digital rectal exam (post-DRE) urine is a minimally invasive fluid that is currently utilized in prostate cancer diagnosis. To detect and quantitate the variant protein in urine.Experimental designFifty-three post-DRE urines from rs17632542 genotyped individuals processed and analyzed by liquid chromatography/mass spectrometry (LC-MS) in a double-blinded randomized study. The ability to distinguish between homozygous wild-type, heterozygous, or homozygous variant is examined before unblinding.ResultsStable-isotope labeled peptides are used in the detection and quantitation of three peptides of interest in each sample using parallel reaction monitoring (PRM). Using these data, groupings are predicted using hierarchical clustering in R. Accuracy of the predictions show 100% concordance across the 53 samples, including individuals homozygous and heterozygous for the SNP.Conclusions and clinical relevanceThe study demonstrates that MS based peptide variant quantitation in urine could be useful in determining patient genotype expression. This assay provides a tool to evaluate the utility of PSA variant (rs17632542) in parallel with current and forthcoming urine biomarker panels.

The contribution of basal and luminal cells to cancer progression and metastasis is poorly understood. We report generation of reporter systems driven by either keratin-14 (K14) or keratin-8 (K8) promoter that not only express a fluorescent protein but also an inducible suicide gene. Transgenic mice express the reporter genes in the right cell compartments of mammary gland epithelia and respond to treatment with toxins. In addition, we engineered the reporters into 4T1 metastatic mouse tumor cell line and demonstrate that K14+ cells, but not K14− or K8+, are both highly invasive in three-dimensional (3D) culture and metastatic in vivo. Treatment of cells in culture, or tumors in mice, with reporter-targeting toxin inhibited both invasive behavior and metastasis in vivo. RNA sequencing (RNA-seq), secretome, and epigenome analysis of K14+ and K14− cells led to the identification of amphoterin-induced protein 2 (Amigo2) as a new cell invasion driver whose expression correlated with decreased relapse-free survival in patients with TP53 wild-type (WT) breast cancer., Author summary Most, if not all, cancer-related deaths result from metastasis. The differentiation states of the cancer epithelial cells are thought to be a critical determinant of metastasis. Epithelial cancer cells with a basal cell type are more aggressive in forming metastasis than cancer cells with luminal cell type. Very little is known about how the differentiation states impact metastasis or the molecular mechanisms involved. In this study, we develop and characterize new reporters that fluorescently mark cells in luminal or basal status. These reporters are also coupled to “suicide genes,” which can be used to inducibly and selectively eliminate cells expressing the reporters. We find that elimination of the basal cell type dramatically decreases metastasis and identify amphoterin-induced protein 2 (Amigo2) as a new regulator of cell invasion in basal cells.

Head and neck squamous cell carcinoma (HNSCC) is a highly heterogeneous disease that develops via one of the two primary carcinogenic routes: chemical carcinogenesis through exposure to tobacco and alcohol or virally induced tumorigenesis. Human papillomavirus (HPV)–positive (HPV+) and HPV-negative (HPV−) HNSCCs represent distinct clinical entities, with the latter associated with significantly inferior outcome. The biologic basis of these different outcomes is an area of intense investigation; their therapeutic regimens are currently also being reevaluated, which would be significantly facilitated by reliable biomarkers for stratification. With the advent of the omics era and accelerated development of targeted therapies, there are unprecedented opportunities to address the challenges in the management of HNSCC. As summarized herein, side-by-side molecular characterization of HPV+ versus HPV− HNSCC has revealed distinct molecular landscapes, novel prognostic signatures, and potentially targetable biologic pathways. In particular, we focus on the evidence acquired from genome-wide omics pertinent to our understanding of the clinical behavior of HNSCC and on insights into personalized treatment opportunities. Integrating, mining, and validating these data toward clinically meaningful outcomes for patients with HNSCC in conjunction with systematic verification of the functional relevance of these findings are critical steps toward the design of personalized therapies. Cancer Res; 75(3); 480–6. ©2014 AACR.

International audience; BACKGROUND: Glioblastoma (GBM) is almost invariably fatal due to failure of standard therapy. The relapse of GBM following surgery, radiation, and systemic temozolomide (TMZ) is attributed to the ability of glioma stem cells (GSCs) to survive, evolve, and repopulate the tumor mass, events on which therapy exerts a poorly understood influence.METHODS: Here we explore the molecular and cellular evolution of TMZ resistance as it emerges in vivo (xenograft models) in a series of human GSCs with either proneural (PN) or mesenchymal (MES) molecular characteristics.RESULTS: We observed that the initial response of GSC-initiated intracranial xenografts to TMZ is eventually replaced by refractory growth pattern. Individual tumors derived from the same isogenic GSC line expressed divergent and complex profiles of TMZ resistance markers, with a minor representation of O6-methylguanine DNA methyltransferase (MGMT) upregulation. In several independent TMZ-resistant tumors originating from MES GSCs we observed a consistent diminution of mesenchymal features, which persisted in cell culture and correlated with increased expression of Nestin, decline in transglutaminase 2 and sensitivity to radiation. The corresponding mRNA expression profiles reflective of TMZ resistance and stem cell phenotype were recapitulated in the transcriptome of exosome-like extracellular vesicles (EVs) released by GSCs into the culture medium.CONCLUSIONS: Intrinsic changes in the tumor-initiating cell compartment may include loss of subtype characteristics and reciprocal alterations in sensivity to chemo- and radiation therapy. These observations suggest that exploiting therapy-induced changes in the GSC phenotype and alternating cycles of therapy may be explored to improve GBM outcomes.

The complexities of tumor genomes are rapidly being uncovered, but how they are regulated into functional proteomes remains poorly understood. Standard proteomics workflows use databases of known proteins, but these databases do not capture the uniqueness of the cancer transcriptome, with its point mutations, unusual splice variants and gene fusions. Onco-proteogenomics integrates mass spectrometry-generated data with genomic information to identify tumor-specific peptides. Linking tumor-derived DNA, RNA and protein measurements into a central-dogma perspective has the potential to improve our understanding of cancer biology.

© 2014 Nature America, Inc. All rights reserved., Polymorphous low-grade adenocarcinoma (PLGA) is the second most frequent type of malignant tumor of the minor salivary glands. We identified PRKD1 hotspot mutations encoding p.Glu710Asp in 72.9% of PLGAs but not in other salivary gland tumors. Functional studies demonstrated that this kinase-activating alteration likely constitutes a driver of PLGA., This work was supported in part by an IDEAS grant from Princess Margaret Hospital, the Head and Neck Translational Research Program (I.W., B.A.C., P.C.B. and J.D.M.), the Ontario Institute for Cancer Research and the government of Ontario (P.C.B. and J.D.M.) and by a Terry Fox Research Institute New Investigator Award (P.C.B.). C.H. and F.-F.L. acknowledge support from the Wharton family, Joe's Team, Gordon Tozer, the Campbell Family Institute for Cancer Research and the Ministry of Health and Long-Term Planning, Canada.

Molecular communication between cancer cells and its stromal microenvironment is a key factor for cancer progression. Alongside classic secretory pathways, it has recently been proposed that small membranous vesicles are alternative mediators of intercellular communication. Exosomes carry an effector-rich proteome with the ability to modulate various functional properties of the recipient cell. In this study, exosomes isolated from four epithelial ovarian cancer cell lines (OVCAR3, OVCAR433, OVCAR5 and SKOV3) were characterized using mass spectrometry-based proteomics. Using an optimized workflow consisting of efficient exosome solubilization and the latest generation of proteomic instrumentation, we demonstrate improved detection depth. Systematic comparison of our cancer cell line exosome proteome against public data (Exocarta) and the recently published NCI 60 proteome revealed enrichment of functional categories related to signaling biology and biomarker discovery.

As the most common primary brain tumor in adults causing death, Glioblastoma (GBM) remains a therapeutic challenge. Unchanged for almost two decades, standard therapy is ineffective at preventing disease relapse with a median patient survival of < 15 months. Stem cell-like subpopulations of tumor cells, known as brain tumor initiating cells (BTICs), evade standard therapy and lead to relapse. Whereas previous studies largely focus on pre-treatment primary GBM (pGBM), we conducted a panel of genome-wide CRISPR-Cas9 gene knockout screens to determine modulators of treatment resistance and de novo genetic vulnerabilities arising at disease recurrence. Using our in vitro model of conventional therapy, we identified genes modulating sensitivity and resistance to Temozolomide and/or radiation therapy in patient-derived pGBM BTICs. Genes modulating sensitivity belong to Fanconi anaemia nuclear complex, interstrand cross link repair, and regulation of stem cell maintenance and differentiation. Following in vitro validation of gene knockouts conferring treatment sensitization in multiple pGBM BTIC lines, we continued to conduct the first genome-wide CRISPR-Cas9 screens in patient-derived rGBM BTICs. Focusing on genetic vulnerabilities arising de novo at disease relapse, we introduce the context-specific role of protein tyrosine phosphatase 4A2 (PTP4A2) in rGBM. Genetic knockout or small molecule targeting of PTP4A2 leads to a context-specific vulnerability of rGBM self renewal capacity and in vivo tumorigenecity. To continue our analysis of treatment-refractory GBM and overcome intertumoral heterogeneity, we conducted genome-wide CRISPR-Cas9 gene knockout screens and whole cell proteomics on patient-matched pGBM and rGBM BTICs. With >1000 differentially essential genes, combined functional genetic and proteomic analyses implicates genes involved in mRNA splicing, nucleotide metabolism, and activation of gene expression by sterol regulatory element-binding protein. Together, our functional genetic approach elucidates novel genes regulating treatment resistance and disease recurrence in GBM.

Background: Glioblastoma (GBM) is the most common malignant primary adult brain tumor, characterized by extensive cellular and genetic heterogeneity. Even with surgery, temozolomide chemotherapy and radiation, tumor re-growth and patient relapse are inevitable, with a median survivorship of just 15 months. Genomic profiling studies have shown that clonal evolution within GBM may be driven by cancer treatment, such that the recurrence may no longer resemble the genetic landscape of the original primary tumor. Furthermore, intratumoral heterogeneity associated with clonal evolution complicates biomarker discovery and treatment personalization and underlies treatment failure. Thus, modeling clonal heterogeneity and evolution to understand cancer progression is critical for the development of effective therapeutic approaches. We aim to identify new therapeutic targets that drive clonal evolution in treatment-refractory GBM and develop novel and empirical therapeutic paradigms targeting recurrent GBM. Experimental Procedure: We employed a transcriptomic, proteomic and functional genomics approach to discover and validate genes that drive GBM recurrence. Using a therapy-adapted patient-derived xenograft (PDX) model of treatment-refractory GBM, we profiled the transcriptomic and proteomic landscape of treatment-naïve primary GBM through conventional chemotherapy and radiation therapy, and into recurrence. To complement the transcriptomic data, we used an unbiased genome-wide CRISPR-Cas9 screening platform to identify genes essential for self-renewal in recurrent GBM, as well as to identify novel sensitizers and suppressors of conventional therapy. Furthermore, we coupled cellular DNA barcoding technology with our PDX model to profile the clonal evolution of tumor cells through therapy. Results: Integrative analysis of deep sequencing and surface proteomics of tumor cells harvested at tumor formation, minimal residual disease after chemoradiotherapy, and tumor recurrence from the PDX model resulted in the identification of novel therapeutic targets in treatment-refractory GBM. Using CRISPR, potential targets were knocked out in patient-derived GBMs in order to characterize the effect on self-renewal and tumor formation. We report the successful barcoding of patient-derived primary, treatment-naïve GSCs at a single cell resolution that were expanded into clonal populations, intracranially engrafted in immunodeficient mice and treated with SoC therapy. Conclusion: We have generated a translational pipeline from initial target discovery, through target validation, to building new biotherapeutics against novel targets, and preclinical testing in our PDX model of treatment-resistant GBM. A promising lead panel of biotherapeutic modalities is being translated into early clinical development, generating targeted therapies and hope for future GBM patients. Note: This abstract was not presented at the meeting. Citation Format: Parvez Vora, Chitra Venugopal, Chirayu Chokshi, Maleeha Qazi, Nazanin Tatari, Kevin Brown, Nicholas Yelle, Jarrett Adams, David Tieu, Mathieu Seyfrid, Mohini Singh, Neil Savage, Minomi Subapanditha, David Bakhshinyan, Laura Kuhlmann, Thomas Kislinger, Sachdev Sidhu, Jason Moffat, Sheila Kumari Singh. A glioblastoma translational pipeline: discovery of novel tumor antigens that drive GBM recurrence [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 570.

Exosomes and microvesicles (MVs) are nanometer-sized, membranous vesicles secreted from many cell types into their surrounding extracellular space and into body fluids. These two classes of extracellular vesicles are regarded as a novel mechanism through which cancer cells, including virally infected cancer cells, regulate their micro-environment via the horizontal transfer of bioactive molecules: proteins, lipids, and nucleic acids (DNA, mRNA, micro-RNAs; oncogenic cargo hence often referred to as oncosomes). In head and neck cancer (HNC), exosomes and MVs have been described in Epstein Barr Virus (EBV)-associated nasopharyngeal cancer (NPC), as well as being positively correlated with oral squamous cell carcinoma (OSCC) progression. It has therefore been suggested that HNC-derived vesicles could represent a useful source for biomarker discovery, enriched in tumor antigens and cargo; hence fundamentally important for cancer progression. This current review offers an overall perspective on the roles of exosomes and MVs in HNC biology, focusing on EBV-associated NPC and OSCC. We also highlight the importance of saliva as a proximal and easily accessible bio-fluid for HNC detection, and propose that salivary vesicles might serve as an alternative model in the discovery of novel HNC biomarkers.

Expressed prostatic secretions (EPS) are proximal fluids of the prostate that are increasingly being utilized as a clinical source for diagnostic and prognostic assays for prostate cancer (PCa). These fluids contain an abundant amount of microvesicles reflecting the secretory function of the prostate gland, and their protein composition remains poorly defined in relation to PCa. Using expressed prostatic secretions in urine (EPS-urine), exosome preparations were characterized by a shotgun proteomics procedure. In pooled EPS-urine exosome samples, ~900 proteins were detected. Many of these have not been previously observed in the soluble proteome of EPS generated by our labs or other related exosome proteomes. We performed systematic comparisons of our data against previously published, prostate-related proteomes, and global annotation analyses to highlight functional processes within the proteome of EPS-urine derived exosomes. The acquired proteomic data have been deposited to the Tranche repository and will lay the foundation for more extensive investigations of PCa derived exosomes in the context of biomarker discovery and cancer biology.

Biomarkers are rapidly gaining importance in personalized medicine. Although numerous molecular signatures have been developed over the past decade, there is a lack of overlap and many biomarkers fail to validate in independent patient cohorts and hence are not useful for clinical application. For these reasons, identification of novel and robust biomarkers remains a formidable challenge. We combine targeted proteomics with computational biology to discover robust proteomic signatures for prostate cancer. Quantitative proteomics conducted in expressed prostatic secretions from men with extraprostatic and organ-confined prostate cancers identified 133 differentially expressed proteins. Using synthetic peptides, we evaluate them by targeted proteomics in a 74-patient cohort of expressed prostatic secretions in urine. We quantify a panel of 34 candidates in an independent 207-patient cohort. We apply machine-learning approaches to develop clinical predictive models for prostate cancer diagnosis and prognosis. Our results demonstrate that computationally guided proteomics can discover highly accurate non-invasive biomarkers., Proteomic technologies are capable of identifying thousands of proteins in biological samples, but biomarker applications are lagging. Here the authors use Multiple Reaction Monitoring Mass Spectrometry to delineate peptide signatures that accurately distinguish between defined prostate cancer patient risk groups.

In recent years there has been tremendous interest in both the basic biology and applications of extracellular vesicles (EVs) in translational cancer research. This includes a better understanding of their biogenesis and mechanisms of selective cargo packaging, their precise roles in horizontal communication, and their application as non-invasive biomarkers. The rapid advances in next-generation omics technologies are the driving forces for these discoveries. In this review, the authors focus on recent results of EV research in ovarian cancer. A deeper understanding of ovarian cancer-derived EVs, the types of cargo molecules and their biological roles in cancer growth, metastases and drug resistance, could have significant impact on the discovery of novel biomarkers and innovative therapeutics. Insights into the role of EVs in immune regulation could lead to novel approaches built on EV-based immunotherapy.

Renal cell carcinoma comprises 2 to 3% of malignancies in adults with the most prevalent subtype being clear-cell RCC (ccRCC). This type of cancer is well characterized at the genomic and transcriptomic level and is associated with a loss of VHL that results in stabilization of HIF1. The current study focused on evaluating ccRCC stage dependent changes at the proteome level to provide insight into the molecular pathogenesis of ccRCC progression. To accomplish this, label-free proteomics was used to characterize matched tumor and normal-adjacent tissues from 84 patients with stage I to IV ccRCC. Using pooled samples 1551 proteins were identified, of which 290 were differentially abundant, while 783 proteins were identified using individual samples, with 344 being differentially abundant. These 344 differentially abundant proteins were enriched in metabolic pathways and further examination revealed metabolic dysfunction consistent with the Warburg effect. Additionally, the protein data indicated activation of ESRRA and ESRRG, and HIF1A, as well as inhibition of FOXA1, MAPK1 and WISP2. A subset analysis of complementary gene expression array data on 47 pairs of these same tissues indicated similar upstream changes, such as increased HIF1A activation with stage, though ESRRA and ESRRG activation and FOXA1 inhibition were not predicted from the transcriptomic data. The activation of ESRRA and ESRRG implied that HIF2A may also be activated during later stages of ccRCC, which was confirmed in the transcriptional analysis. This combined analysis highlights the importance of HIF1A and HIF2A in developing the ccRCC molecular phenotype as well as the potential involvement of ESRRA and ESRRG in driving these changes. In addition, cofilin-1, profilin-1, nicotinamide N-methyltransferase, and fructose-bisphosphate aldolase A were identified as candidate markers of late stage ccRCC. Utilization of data collected from heterogeneous biological domains strengthened the findings from each domain, demonstrating the complementary nature of such an analysis. Together these results highlight the importance of the VHL/HIF1A/HIF2A axis and provide a foundation and therapeutic targets for future studies. (Data are available via ProteomeXchange with identifier PXD003271 and MassIVE with identifier MSV000079511.).

Current protocols for the screening of prostate cancer cannot accurately discriminate clinically indolent tumors from more aggressive ones. One reliable indicator of outcome has been the determination of organ-confined versus nonorgan-confined disease but even this determination is often only made following prostatectomy. This underscores the need to explore alternate avenues to enhance outcome prediction of prostate cancer patients. Fluids that are proximal to the prostate, such as expressed prostatic secretions (EPS), are attractive sources of potential prostate cancer biomarkers as these fluids likely bathe the tumor. Direct-EPS samples from 16 individuals with extracapsular (n = 8) or organ-confined (n = 8) prostate cancer were used as a discovery cohort, and were analyzed in duplicate by a nine-step MudPIT on a LTQ-Orbitrap XL mass spectrometer. A total of 624 unique proteins were identified by at least two unique peptides with a 0.2% false discovery rate. A semiquantitative spectral counting algorithm identified 133 significantly differentially expressed proteins in the discovery cohort. Integrative data mining prioritized 14 candidates, including two known prostate cancer biomarkers: prostate-specific antigen and prostatic acid phosphatase, which were significantly elevated in the direct-EPS from the organ-confined cancer group. These and five other candidates (SFN, MME, PARK7, TIMP1, and TGM4) were verified by Western blotting in an independent set of direct-EPS from patients with biochemically recurrent disease (n = 5) versus patients with no evidence of recurrence upon follow-up (n = 10). Lastly, we performed proof-of-concept SRM-MS-based relative quantification of the five candidates using unpurified heavy isotope-labeled synthetic peptides spiked into pools of EPS-urines from men with extracapsular and organ-confined prostate tumors. This study represents the first efforts to define the direct-EPS proteome from two major subclasses of prostate cancer using shotgun proteomics and verification in EPS-urine by SRM-MS.

Urinary expressed prostatic secretion or "EPS-urine" is proximal tissue fluid that is collected after a digital rectal exam (DRE). EPS-urine is a rich source of prostate-derived proteins that can be used for biomarker discovery for prostate cancer (PCa) and other prostatic diseases. We previously conducted a comprehensive proteome analysis of direct expressed prostatic secretions (EPS). In the current study, we defined the proteome of EPS-urine employing Multidimensional Protein Identification Technology (MudPIT) and providing a comprehensive catalogue of this body fluid for future biomarker studies. We identified 1022 unique proteins in a heterogeneous cohort of 11 EPS-urines derived from biopsy negative noncancer diagnoses with some benign prostatic diseases (BPH) and low-grade PCa, representative of secreted prostate and immune system-derived proteins in a urine background. We further applied MudPIT-based proteomics to generate and compare the differential proteome from a subset of pooled urines (pre-DRE) and EPS-urines (post-DRE) from noncancer and PCa patients. The direct proteomic comparison of these highly controlled patient sample pools enabled us to define a list of prostate-enriched proteins detectable in EPS-urine and distinguishable from a complex urine protein background. A combinatorial analysis of both proteomics data sets and systematic integration with publicly available proteomics data of related body fluids, human tissue transcriptomic data, and immunohistochemistry images from the Human Protein Atlas database allowed us to demarcate a robust panel of 49 prostate-derived proteins in EPS-urine. Finally, we validated the expression of seven of these proteins using Western blotting, supporting the likelihood that they originate from the prostate. The definition of these prostatic proteins in EPS-urine samples provides a reference for future investigations for prostatic-disease biomarker studies.

Epithelial ovarian cancer (EOC) is the most common gynecological cancer and the ninth most common cancer overall. Major problems associated with EOC include poorly characterized disease progression, disease heterogeneity, lack of early detection markers and the development of chemoresistance. Early detection and treatment of EOC would significantly benefit from routine screening tests on available biofluids. We built on our experience in analyzing ovarian cancer ascites and present an analysis pipeline that combines discovery-based proteomics, bioinformatics prioritization and targeted proteomics quantification using Selected Reaction Monitoring Mass Spectrometry (SRM-MS). Ascitic fluids from patients with serous-type epithelial ovarian cancer were analyzed using comprehensive shotgun proteomics and compared to noncancerous ascitic fluids from patients with benign ovarian tumors. Integration of our data with published mRNA transcriptomic and proteomic data sets led to a panel of 51 candidate proteins. Systematic SRM-MS assay development was performed for a subset of these proteins using both synthetic peptides (13 proteins) and stable isotope labeled standards (4 proteins). Subsequently, precise relative quantification by stable isotope dilution-SRM (SID-SRM) in independent ascites and serum samples was performed as a proof-of-concept validation. The analysis strategy outlined here lays the foundation for future experiments using both larger numbers of patient samples and additional candidate proteins, and provides a template for the proteomics-based discovery of cancer biomarkers.

Nonsmall cell lung carcinoma (NSCLC) accounts for 80% of lung cancers. The most prevalent subtypes of NSCLC are adenocarcinoma (ADC) and squamous cell carcinoma (SCC), which combined account for approximately 90%. Ten resected NSCLC patient tumors (5 ADC and 5 SCC) were directly introduced into severely immune deficient (NOD-SCID) mice, and the resulting xenograft tumors were analyzed by standard histology and immunohistochemistry (IHC) and by proteomics profiling. Mass spectrometry (MS) methods involving 1- and 2-dimensional LC-MS/MS, and multiplexed selective reaction monitoring (SRM, or MRM), were applied to identify and quantify the xenograft proteomes. Hierarchical clustering of protein profiles distinguished between the ADC and SCC subtypes. The differential expression of 178 proteins, including a comprehensive panel of intermediate filament keratin proteins, was found to constitute a distinctive proteomic signature associated with the NSCLC subtypes. Epidermal growth factor receptor (EGFR) was expressed in ADC and SCC xenografts, and EGFR network activation was assessed by phosphotyrosine profiling by Western blot analysis and SRM measurement of EGFR levels, and mutation analysis. A multiplexed SRM/MRM method provided relative quantification of several keratin proteins, EGFR and plakophilin-1 in single LC-MS/MS runs. The protein quantifications by SRM and MS/MS spectral counting were associated with superior dynamic range and reproducibility but were otherwise consistent with orthogonal methods including IHC and Western immuno blotting. These findings illustrate the potential to develop a comprehensive MS-based platform in oncologic pathology for better classification and potentially treatment of NSCLC patients.

Purpose: Neuroblastoma (NB) is an aggressive tumor of the developing peripheral nervous system that remains difficult to cure in the advanced stages. The poor prognosis for high-risk NB patients is associated with common disease recurrences that fail to respond to available therapies. NB tumor-initiating cells (TICs), isolated from metastases and primary tumors, may escape treatment and contribute to tumor relapse. New therapies that target the TICs may therefore prevent or treat tumor recurrences. Experimental Design: We undertook a system-level characterization of NB TICs to identify potential drug targets against recurrent NB. We used next-generation RNA sequencing and/or human exon arrays to profile the transcriptomes of 11 NB TIC lines from six NB patients, revealing genes that are highly expressed in the TICs compared with normal neural crest-like cells and unrelated cancer tissues. We used gel-free two-dimensional liquid chromatography coupled to shotgun tandem mass spectrometry to confirm the presence of proteins corresponding to the most abundant TIC-enriched transcripts, thereby providing validation to the gene expression result. Results: Our study revealed that genes in the BRCA1 signaling pathway are frequently misexpressed in NB TICs and implicated Aurora B kinase as a potential drug target for NB therapy. Treatment with a selective AURKB inhibitor was cytotoxic to NB TICs but not to the normal neural crest-like cells. Conclusion: This work provides the first high-resolution system-level analysis of the transcriptomes of 11 primary human NB TICs and identifies a set of candidate NB TIC-enriched transcripts for further development as therapeutic targets. Clin Cancer Res; 16(18); 4572–82. ©2010 AACR.

It is expected that clinically obtainable fluids that are proximal to organs contain a repertoire of secreted proteins and shed cells reflective of the physiological state of that tissue and thus represent potential sources for biomarker discovery, investigation of tissue-specific biology, and assay development. The prostate gland secretes many proteins into a prostatic fluid that combines with seminal vesicle fluids to promote sperm activation and function. Proximal fluids of the prostate that can be collected clinically are seminal plasma and expressed prostatic secretion (EPS) fluids. In the current study, MudPIT-based proteomics was applied to EPS obtained from nine men with prostate cancer and resulted in the confident identification of 916 unique proteins. Systematic bioinformatics analyses using publicly available microarray data of 21 human tissues (Human Gene Atlas), the Human Protein Atlas database, and other published proteomics data of shed/secreted proteins were performed to systematically analyze this comprehensive proteome. Therefore, we believe this data will be a valuable resource for the research community to study prostate biology and potentially assist in the identification of novel prostate cancer biomarkers. To further streamline this process, the entire data set was deposited to the Tranche repository for use by other researchers.

Chemotherapeutic agents as they are used today have limited effectiveness against prostate cancer, but may potentially be used in new combinations with more efficacious results. Mitoxantrone, used for palliation of prostate cancer, has recently been found by our group to improve the susceptibility of primary prostate cancer cells to killing through the Fas-mediated death pathway. Here we used a shotgun proteomics approach to first profile the entire prostate cancer proteome and then identify specific factors involved in this mitoxantrone response. Peptides derived from primary prostate cancer cells treated with or without 100 nM mitoxantrone were analyzed by multidimensional protein identification technology (MudPIT). Strict limits and data filtering hierarchies were applied to identify proteins with high confidence. We identified 1498 proteins belonging to the prostate cancer proteome, 83 of which were significantly upregulated and 27 of which were markedly downregulated following mitoxantrone treatment. These proteins perform diverse functions, including ceramide production, tumour suppression, and oxidative reduction. Detailed proteomic analyses of prostate cancer cells and their response to mitoxantrone will further our understanding of its mechanisms of action. Identification of proteins influenced by treatment with mitoxantrone or other compounds may lead to the development of more effective drug combinations against prostate cancer.

Epithelial ovarian cancer is the leading cause of cancer-related death among gynecological cancers due to the asymptomatic nature of the disease, a lack of early detection markers and the development of resistance to current chemotherapeutic agents. Currently available tests (CA-125, transvaginal ultrasound or combination of both) lack the sensitivity and specificity to be useful as an efficient screening tool for surveillance of the general population. Thus, there is an urgent need for the development and validation of new molecular markers that would be both specific and sensitive indicators of disease onset, as well as progression. Proteomic profiling has emerged as a powerful tool to study ovarian cancer in an unbiased way at the molecular level, to monitor the effects of given treatment options and for the discovery of biomarkers. In this review we discuss the challenges associated with proteomics-based biomarker discovery and some recent concepts to potentially overcome these hurdles. Recent proteomics work on ovarian cancer cells and tissues will be discussed in light of obtaining new insights into fundamental biological processes, as well as their potential integration with ongoing biomarker discovery pipelines.

Defective mobilization of Ca2+ by cardiomyocytes can lead to cardiac insufficiency, but the causative mechanisms leading to congestive heart failure (HF) remain unclear. In the present study we performed exhaustive global proteomics surveys of cardiac ventricle isolated from a mouse model of cardiomyopathy overexpressing a phospholamban mutant, R9C (PLN-R9C), and exhibiting impaired Ca2+ handling and death at 24 weeks and compared them with normal control littermates. The relative expression patterns of 6190 high confidence proteins were monitored by shotgun tandem mass spectrometry at 8, 16, and 24 weeks of disease progression. Significant differential abundance of 593 proteins was detected. These proteins mapped to select biological pathways such as endoplasmic reticulum stress response, cytoskeletal remodeling, and apoptosis and included known biomarkers of HF (e.g. brain natriuretic peptide/atrial natriuretic factor and angiotensin-converting enzyme) and other indicators of presymptomatic functional impairment. These altered proteomic profiles were concordant with cognate mRNA patterns recorded in parallel using high density mRNA microarrays, and top candidates were validated by RT-PCR and Western blotting. Mapping of our highest ranked proteins against a human diseased explant and to available data sets indicated that many of these proteins could serve as markers of disease. Indeed we showed that several of these proteins are detectable in mouse and human plasma and display differential abundance in the plasma of diseased mice and affected patients. These results offer a systems-wide perspective of the dynamic maladaptions associated with impaired Ca2+ homeostasis that perturb myocyte function and ultimately converge to cause HF.