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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.

Driven by the lack of targeted therapies, triple-negative breast cancers (TNBCs) have the worst overall survival of all breast cancer subtypes. Considering that cell surface proteins are favorable drug targets and are predominantly glycosylated, glycoproteome profiling has significant potential to facilitate the identification of much-needed drug targets for TNBCs. Here, we performed

The intercalated disc (ICD) is unique membrane structure that is indispensable to normal heart function, yet its structural organization is not completely understood. Previously, we showed that the ICD-bound transmembrane protein 65 (Tmem65) was required for connexin 43 (Cx43) localization and function 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 shRNA which resulted in a 90% reduction of Tmem65 expression in mouse ventricles compared to mice injected with scrambled shRNA. Tmem65 knockdown (KD) resulted in increased mortality which was accompanied by eccentric hypertrophic cardiomyopathy within 3 weeks of injection, progressing to dilated cardiomyopathy with severe cardiac fibrosis by 7 weeks post-injection. Tmem65 KD hearts displayed depressed hemodynamics, measured echocardiographically, accompanied by electrocardiogram changes (prolonged PR intervals and QRS duration) consistent with impaired conduction, which was confirmed with optical mapping of isolated hearts. Immunoprecipitation and super-resolution microscopy demonstrated a physical interaction between Tmem65 and sodium channel β subunit (β1) in mouse hearts and this interaction appeared to be required for both the establishment of perinexal nanodomain structure and the localization of both voltage-gated sodium channel 1.5 (NaV1.5) and Cx43 to ICDs. Despite the loss of NaV1.5 at the ICDs, whole-cell patch clamp electrophysiology did not reveal reductions in Na + currents but did show reduced Ca 2+ and K + currents in Tmem65 KD cardiomyocytes in comparison to control cells. We conclude that disrupting Tmem65 function results in impaired ICD structure, abnormal cardiac electrophysiology, and ultimately cardiomyopathy.

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.

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 map a multilayered genetic response to drive tumor recurrence, identifying protein tyrosine phosphatase 4A2 (PTP4A2) as a novel modulator of self-renewal, proliferation and tumorigenicity at GBM recurrence. Mechanistically, genetic perturbation or small molecule inhibition of PTP4A2 represses axon guidance activity through a dephosphorylation axis with roundabout guidance receptor 1 (ROBO1), exploiting a functional 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 dependence on a multi-targetable PTP4A2-ROBO1 signaling axis at GBM recurrence.

1AbstractBackgroundDiagnosis and prognostication of intra-axial brain tumors hinges on invasive brain sampling, which carries risk of morbidity. Minimally invasive sampling of proximal fluids, also known as liquid biopsy, can mitigate this risk.ObjectiveTo identify diagnostic and prognostic cerebrospinal fluid (CSF) proteomic signatures in glioblastoma (GBM), brain metastases (BM), and primary central nervous system lymphoma (CNSL).MethodsCSF samples were retrospectively retrieved from the Penn State Neuroscience Biorepository and profiled using shotgun proteomics. Proteomic signatures were identified using machine learning classifiers and survival analyses.ResultsUsing 30 µL CSF volumes, we recovered 755 unique proteins across 73 samples. Proteomic-based classifiers identified malignancy with area under the receiver operating characteristic (AUROC) of 0.94 and distinguished between tumor entities with AUROC ≥0.95. More clinically relevant triplex classifiers, comprised of just 3 proteins, distinguished between tumor entities with AUROC of 0.75-0.89. Novel biomarkers were identified, including GAP43, TFF3 and CACNA2D2, and characterized using single-cell RNA sequencing. Survival analyses validated previously implicated prognostic signatures, including blood brain barrier disruption.DiscussionReliable classification of intra-axial malignancies using low CSF volumes is feasible, allowing for longitudinal tumor surveillance. Based on emerging evidence, upfront implantation of CSF reservoirs in brain tumor patients warrants consideration.2Statement of SignificanceCurrent approaches to diagnosing brain tumors risk morbidity. The CSF may be an ideal liquid biopsy matrix for mitigating this risk. We report feasibility of high-throughput CSF proteomics on limited volumes from brain tumor patients with intraventricular reservoirs, demonstrate diagnostic and prognostic utility, and explore its applications in practice.

Glioblastoma (GBM) is characterized by extensive cellular and genetic heterogeneity. Its initial presentation as primary disease (pGBM) has been subject to exhaustive molecular and cellular profiling. By contrast, our understanding of how GBM evolves to evade the selective pressure of therapy is starkly limited. The proteomic landscape of recurrent GBM (rGBM), which is refractory to most treatments used for pGBM, are poorly known. We, therefore, quantified the transcriptome and proteome of 134 patient-derived pGBM and rGBM samples, including 40 matched pGBM-rGBM pairs. GBM subtypes transition from pGBM to rGBM towards a preferentially mesenchymal state at recurrence, consistent with the increasingly invasive nature of rGBM. We identified immune regulatory/suppressive genes as important drivers of rGBM and in particular 2-5-oligoadenylate synthase 2 (OAS2) as an essential gene in recurrent disease. Our data identify a new class of therapeutic targets that emerge from the adaptive response of pGBM to therapy, emerging specifically in recurrent disease and may provide new therapeutic opportunities absent at pGBM diagnosis.

Axons are complex subcellular compartments that are extremely long in relation to cell bodies, especially in peripheral nerves. Many processes are required and regulated during axon injury, including anterograde and retrograde transport, glia-to-axon macromolecular transfer, and local axonal protein synthesis. Many in vitro omics approaches have been used to gain insight into these processes, but few have been applied in vivo. Here we adapted the osmotic ex vivo axoplasm isolation method and analyzed the adult rat sciatic-nerve-extruded axoplasm by label-free quantitative proteomics before and after injury. 2087 proteins groups were detected in the axoplasm, revealing translation machinery and microtubule-associated proteins as the most overrepresented biological processes. Ribosomal proteins (73) were detected in the uninjured axoplasm and increased their levels after injury but not within whole sciatic nerves. Meta-analysis showed that detected ribosomal proteins were present in in vitro axonal proteomes. Because local protein synthesis is important for protein localization, we were interested in detecting the most abundant newly synthesized axonal proteins in vivo. With an MS/MS-BONCAT approach, we detected 42 newly synthesized protein groups. Overall, our work indicates that proteomics profiling is useful for local axonal interrogation and suggests that ribosomal proteins may play an important role, especially during injury.

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.

Glycoprotein nonmetastatic melanoma protein B (GPNMB) is known to be active in the extracellular matrix of glioblastoma and has been identified as a promising immunotherapy target for both tumor cells and immunosuppressive macrophages. Methods: Immunohistochemistry was performed on patient derived xenograft (PDX) brains and tissue samples of 16 patient matched primary/recurrent GBMs as well as 23 normal organ tissues. Whole cell proteomics was performed on 43 matched primary/recurrent GBM samples. Flow cytometry measured surface expression levels of GPNMB to confirm CAR-T accessibility. CRISPR/Cas9 was used to eliminate expression in GBM lines to measure proliferation and mouse survival times. GPNMB knockout clones were generated in GL261 and engrafted in immunocompetent mice to examine single cell transcriptomes using sciRNAseq at endpoint. A second-generation CAR-T was developed to target GPNMB-expressing populations, and efficacy was interrogated using standard in vitro assays and GBM PDX models. Results: The absence of GPNMB throughout most normal tissues validates the rationale of administering CAR-Ts as a safe modality for patients. GPNMB detected in residual tumors of PDX models treated orthotopically with CD133 CAR-Ts revealed it as a targetable subpopulation of GBM cells and a rational co-target alongside CD133 in the heterogeneous tumor. Tissue microarrays and whole cell proteomics found GPNMB to be upregulated in recurrent GBMs compared to primary (p=0.0349 and p=0.0033 respectively) while being absent in normal tissues. Single cell sequencing data of patient GBMs revealed GPNMB was also highly expressed in tumor-associated macrophages. Eliminating GPNMB in GBM cell lines decreased proliferation (P Conclusions: We show GPNMB influences tumor-intrinsic biology of GBM and is also active in macrophages in the recurrent GBM immune microenvironment. By targeting GPNMB along with CD133, combinatorial therapeutic regimens could target both the cancer stem cell hierarchy and its supportive niche. Administration of both CAR-T cell therapies to humanized mice engrafted with patient-derived GBMs will provide better cytotoxic coverage and potentially provide more durable therapeutic efficacy for GBM patients. Citation Format: Neil Savage, Franz J. Zemp, Nick Mikolajewicz, Hong Han, Chitra Venugopal, Chirayu Chokshi, Nazanin Tatari, Thomas Kislinger, Jason Moffat, Doug Mahoney, Sheila K. Singh. Investigating the functional role of GPNMB in glioblastoma and the tumor immune microenvironment and its targeted elimination using CAR-Ts [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1154.

2-Aminoethanethiol dioxygenase (ADO) is a thiol dioxygenase that plays a direct role in both metabolism and protein stability. Oxidation of the metabolite cysteamine produces hypotaurine, while oxidation of N-terminal cysteines targets protein substrates for N-degron pathway-mediated degradation. Despite these known functions, the (patho)physiological roles of ADO remain obscure. By analyzing TCGA datasets we discovered that high ADO expression is associated with poor outcome for patients with hepatocellular carcinoma (HCC) (HR 1.2, p Citation Format: Sandy C-E Lee, Andrea H. Pyo, Helia Mohammadi, Ji Zhang, Anna Dvorkin-Gheva, Lucie Malbeteau, Stephen Chung, Shahbaz Khan, Thomas Kislinger, Julie A. Reisz, Courtney Jones, Marianne Koritzinsky. ADO is essential for redox homeostasis in liver cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4783.

BackgroundChordomas are rare, clinically aggressive tumors with a median survival of 6-7 years and a high rate of disease progression despite maximal surgery and radiotherapy. Given the limited options available to prevent and treat progression and relatively poor prognosis, there remains an urgent need for the development of novel therapies to improve clinical outcomes. Cell-surface proteins are attractive therapeutic targets due to their accessible subcellular localization.MethodsHere, we used a proteomics approach to identify novel chordoma-specific cell-surface protein markers. Four established chordoma cell lines were analyzed by quantitative proteomics using a comprehensive differential ultracentrifugation organellar fractionation approach. A subtractive proteomics strategy was applied to select proteins that are plasma membrane enriched. Using commercially available antibodies, the expression profiles of these cell-surface proteins were validated across chordoma cell lines, patient surgical tissue samples, and normal tissue lysates via Western blotting. The candidates were further validated by immunohistochemical analysis in a 25-patient tissue cohort. Finally, the essentiality of these candidates for in vitro chordoma growth was evaluated.ResultsMass spectrometry-based proteomics identified 120 high-confidence cell-surface proteins in four established chordoma cell line models. Systematic data integration prioritized two chordoma-specific cell surface proteins for further interrogation. Immunohistochemistry in a richly annotated cohort of chordoma tumor tissues revealed that PLA2R1 and SLC6A12 are broadly expressed in chordoma patient samples. Higher expression of PLA2R1 correlated with poor prognosis whereas SLC6A12 expression was significantly enriched in skull-base chordomas compared to those arising in the spine. Using a siRNA-mediated knockdown of PLA2R1, we demonstrated significant inhibition of cell growth and colony-forming ability, suggesting these proteins play an essential role in chordoma biology.ConclusionWe have comprehensively elucidated the proteome of four established chordoma cell lines. Subtractive proteomics and integrative data mining revealed novel cell-surface proteins required for chordoma cell survival and associated with clinical parameters in a small chordoma tissue sample cohort.

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 sarco-endoplasmic reticulum (SR/ER) is the largest membrane-bound organelle in eukaryotic cells and plays important roles in essential cellular processes, and in development and progression of many cardiac diseases. However, many aspects of its structural organization remain largely unknown, particularly in cells with a highly differentiated SR/ER network. In a recently published study led by Lee et al. (Nat Commun 11(1):965), we reported a cardiac enriched SR/ER membrane protein REEP5 that is centrally involved in regulating SR/ER organization and cellular stress responses in cardiac myocytes. In vitro REEP5 depletion in mouse cardiac myocytes resulted in SR/ER membrane destabilization and luminal vacuolization along with decreased myocyte contractility and disrupted Ca2+ cycling. Further, in vivo CRISPR/Cas9-mediated REEP5 loss-of-function zebrafish mutants showed sensitized cardiac dysfunction to heart failure induction upon short-term verapamil treatment. Additionally, in vivo adeno-associated viral (AAV9)-induced REEP5 depletion in the mouse demonstrated cardiac dysfunction with dilated cardiac chambers, increased cardiac fibrosis, and reduced ejection fraction. These results demonstrate the critical role of REEP5 in SR/ER organization and function.

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 stem 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 an a priori, pre-existing fitness advantage, or a priori equipotency 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 GBM, and the prognostic value of interrogating the MRD state in solid cancers.

PurposeGlioblastoma (GBM) patients suffer from a dismal prognosis, with standard of care therapy inevitably leading to therapy-resistant recurrent tumors. The presence of cancer stem cells (CSCs) drives the extensive heterogeneity seen in GBM, prompting the need for novel therapies specifically targeting this subset of tumor-driving cells. Here, we identify CD70 as a potential therapeutic target for recurrent GBM CSCs.Experimental designIn the current study, we identified the relevance and functional influence of CD70 on primary and recurrent GBM cells, and further define its function using established stem cell assays. We use CD70 knockdown studies, subsequent RNAseq pathway analysis, andin vivoxenotransplantation to validate CD70’s role in GBM. Next, we developed and tested an anti-CD70 chimeric antigen receptor (CAR)-T therapy, which we validatedin vitroandin vivousing our established preclinical model of human GBM. Lastly, we explored the importance of CD70 in the tumor immune microenvironment (TIME) by assessing the presence of its receptor, CD27, in immune infiltrates derived from freshly resected GBM tumor samples.ResultsCD70 expression is elevated in recurrent GBM and CD70 knockdown reduces tumorigenicityin vitroandin vivo. CD70 CAR-T therapy significantly improves prognosisin vivo. We also found CD27 to be present on the cell surface of multiple relevant GBM TIME cell populations, notably putative M1 macrophages and CD4 T cells.ConclusionCD70 plays a key role in recurrent GBM cell aggressiveness and maintenance. Immunotherapeutic targeting of CD70 significantly improves survival in animal models and the CD70/CD27 axis may be a viable polytherapeutic avenue to co-target both GBM and its TIME.

Medulloblastoma (MB) is the most common type of malignant pediatric brain cancer. Current standard of care (SOC) involves maximal safe resection and neuraxis radiotherapy and chemotherapy in individuals older than 3 years. To date, these cytotoxic SOC combined with craniospinal irradiation led to devastating neurocognitive and developmental deficits impacting quality of life for pediatric patients. The biological heterogeneity of MB is highlighted by the existence of four distinct molecular subgroups (WNT, SHH, Group 3, and Group 4). Group 3 and Group 4 have the poorest patient outcomes because of their aggressive, metastatic nature, and so often remain treatment refractory to SOC. Group 3 has a poor prognosis due to its high incidence of leptomeningeal spread and an overall survival rate of less than 50%. The cytotoxic nature and lack of response in specific subtypes to SOC underscores the urgent need for developing and translating novel treatment options including immunotherapies. In our earlier work, we have developed a therapy-adapted patient derived xenograft (PDX) model of the Group 3 MB as the tumor cells undergoes therapy in vitro and in vivo. N-glycocapture surfaceome profiling of the MB cells through this PDX model identified Integrin α5 (ITGA5) as one of the most differentially expressed targets found at recurrence when compared to engraftment and untreated timepoints. Through shRNA knockdown and small molecule inhibition, we identify ITGA5 expression marks a MB cell subpopulation with increased self-renewal ability both in vitro and in vivo. Access to recurrent MB (rMB) post-therapy allowed us to investigate the changes in the surfaceome of MB cells using proteomics profiling to identify promising rMB-specific targets for rational development of novel immunotherapies.

BACKGROUND Invasive brain sampling is typically necessary for reliable diagnosis and prognostication of intra-axial brain tumors but carries risk of morbidity. Liquid biopsy of proximal fluids may mitigate this risk. Through direct contact with the tumor microenvironment and, as an ultra-filtrate of plasma, the cerebrospinal fluid may be the ideal matrix. Reflecting the tumor phenotype, proteomic analyses are critical. Here we identified diagnostic CSF proteomic signatures and putatively novel biomarkers for glioblastoma (GBM), brain metastases (BM), and central nervous system lymphoma (CNSL). METHODS CSF samples were retrospectively retrieved from the Penn State Neuroscience Biorepository and profiled using shotgun proteomics and the MStern approach. Proteomic signatures were identified using machine learning classifiers and survival analyses. RESULTS With as little as 30 µL of CSF, 755 unique proteins were recovered across 73 samples (22 GBM, 17 BM, 14 CNSL, 20 NPH). Proteomic-based classifiers identified malignancy with area under the receiver operating characteristic (AUROC) of 0.94 and distinguished between tumor entities with AUROC ≥0.95. More clinically relevant triplex classifiers, comprised of just 3 proteins, distinguished between tumor entities with AUROC of 0.75-0.89. Novel biomarkers were identified, including GAP43, TFF3 and CACNA2D2, and characterized using single-cell RNA sequencing. DISCUSSION Reliable classification of intra-axial malignancies using low CSF volumes is feasible, allowing for longitudinal tumor surveillance. Based on emerging evidence, upfront implantation of CSF reservoirs in brain tumor patients warrants consideration.

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.

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.

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.

Saw et al. show via the combinatorial deletion of Timp family members in mice that metalloprotease regulation of FGF-2 is a crucial event in the chondrocyte maturation program, underlying the growth plate development and bone elongation responsible for attaining proper body stature., Regulated growth plate activity is essential for postnatal bone development and body stature, yet the systems regulating epiphyseal fusion are poorly understood. Here, we show that the tissue inhibitors of metalloprotease (TIMP) gene family is essential for normal bone growth after birth. Whole-body quadruple-knockout mice lacking all four TIMPs have growth plate closure in long bones, precipitating limb shortening, epiphyseal distortion, and widespread chondrodysplasia. We identify TIMP/FGF-2/IHH as a novel nexus underlying bone lengthening where TIMPs negatively regulate the release of FGF-2 from chondrocytes to allow IHH expression. Using a knock-in approach that combines MMP-resistant or ADAMTS-resistant aggrecans with TIMP deficiency, we uncouple growth plate activity in axial and appendicular bones. Thus, natural metalloprotease inhibitors are crucial regulators of chondrocyte maturation program, growth plate integrity, and skeletal proportionality. Furthermore, individual and combinatorial TIMP-deficient mice demonstrate the redundancy of metalloprotease inhibitor function in embryonic and postnatal development.

2021 Background: Accurate diagnosis and prognostication of intra-axial brain tumors hinges on invasive brain sampling, which carries risk of morbidity. Minimally invasive sampling of proximal fluids, also known as liquid biopsy, can mitigate this risk. Although the cerebrospinal fluid (CSF) is the ideal liquid biopsy source, the traditionally high volumes required for impactful analyses have deterred progress. The objective of this study was to identify diagnostic and prognostic CSF proteomic signatures in glioblastoma (GBM), brain metastases (BM), and central nervous system lymphoma (CNSL). Methods: CSF samples were retrospectively retrieved from the Penn State Neuroscience Biorepository and profiled using shotgun proteomics with ultra-low sample volumes. Proteomic signatures were identified using machine learning classifiers and survival analyses. Results: Using 30µL CSF volumes, we recovered 800 unique peptides across 73 samples [20 normal pressure hydrocephalus (NPH, non-tumor control), 22 GBM, 17 BM, and 14 CNSL]. Externally-validated proteomic-based classifiers identified malignancy with AUROC of 0.94 and distinguished individual tumor entities from others with AUROC ≥0.96. More clinically relevant triplex classifiers, comprised of just 3 peptides, distinguished individual tumor entities with AUROC ≥0.90. Novel biomarkers were identified among the top classifiers, including TFF3 and CACNA2D2, and characterized using single-cell RNA sequencing data. Survival analyses validated previously implicated prognostic signatures, including blood brain barrier disruption. Conclusions: Reliable classification of intra-axial malignancies using ultra-low CSF volumes is feasible, which has ramifications for longitudinal tumor surveillance. Novel biomarkers identified here necessitate future validation. Based on emerging evidence, upfront implantation of CSF reservoirs in brain tumor patients warrants consideration.

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.

Meningiomas are the most common primary intracranial tumour in adults

Cancer has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrate robust, sensitive, and reproducible data generation across eleven international sites on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality., Distributed multi-omic digitization of clinical specimen across multiple sites is a prerequisite for turning molecular precision medicine into reality. Here, the authors show that coordinated proteotype data acquisition is feasible using standardized MS data acquisition and analysis strategies.

The development of functionally selective or biased ligands is a promising approach towards drugs with less side effects. Biased ligands for G protein-coupled receptors can selectively induce G protein activation or β-arrestin recruitment. The consequences of this selective action on cellular functions, however, are not fully understood. Here, we investigated the impact of five biased and balanced dopamine D2 receptor agonists and antagonists on the global protein expression in HEK293T cells by untargeted nanoscale liquid chromatography–tandem mass spectrometry. The proteome analysis detected 5290 protein groups. Hierarchical clustering and principal component analysis based on the expression levels of 1462 differential proteins led to a separation of antagonists and balanced agonist from the control treatment, while the biased ligands demonstrated larger similarities to the control. Functional analysis of affected proteins revealed that the antagonists haloperidol and sulpiride regulated exocytosis and peroxisome function. The balanced agonist quinpirole, but not the functionally selective agonists induced a downregulation of proteins involved in synaptic signaling. The β-arrestin-preferring agonist BM138, however, regulated several proteins related to neuron function and the dopamine receptor-mediated signaling pathway itself. The G protein-selective partial agonist MS308 influenced rather broad functional terms such as DNA processing and mitochondrial translation.

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 has no borders: Generation and analysis of molecular data across multiple centers worldwide is necessary to gain statistically significant clinical insights for the benefit of patients. Here we conceived and standardized a proteotype data generation and analysis workflow enabling distributed data generation and evaluated the quantitative data generated across laboratories of the international Cancer Moonshot consortium. Using harmonized mass spectrometry (MS) instrument platforms and standardized data acquisition procedures, we demonstrated robust, sensitive, and reproducible data generation across eleven sites in nine countries on seven consecutive days in a 24/7 operation mode. The data presented from the high-resolution MS1-based quantitative data-independent acquisition (HRMS1-DIA) workflow shows that coordinated proteotype data acquisition is feasible from clinical specimens using such standardized strategies. This work paves the way for the distributed multi-omic digitization of large clinical specimen cohorts across multiple sites as a prerequisite for turning molecular precision medicine into reality.

Programmed cell death 4 (PDCD4) protein is a tumor suppressor that inhibits translation through the mTOR-dependent initiation factor EIF4A, but its functional role and mRNA targets in neurons remain largely unknown. Our work identified that PDCD4 is highly expressed in axons and dendrites of CNS and PNS neurons. Using loss- and gain-of-function experiments in cortical and dorsal root ganglia primary neurons, we demonstrated the capacity of PDCD4 to negatively control axonal growth. To explore PDCD4 transcriptome and translatome targets, we used Ribo-seq and uncovered a list of potential targets with known functions as axon/neurite outgrowth regulators. In addition, we observed that PDCD4 can be locally synthesized in adult axons in vivo, and its levels decrease at the site of peripheral nerve injury and before nerve regeneration. Overall, our findings demonstrate that PDCD4 can act as a new regulator of axonal growth via the selective control of translation, providing a target mechanism for axon regeneration and neuronal plasticity processes in neurons.

Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including post-translational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics’ integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice.

Casey et al. integrate epigenomic, transcriptomic, and proteomic profiling of primary basal and luminal mammary cells to identify master epigenetic regulators of the mammary epithelium and uncover stem and progenitor cell vulnerabilities. They develop a pipeline to identify drugs that abrogate progenitor cell activity in normal and high-risk breast cancer patient samples in vitro and in vivo., The mammary epithelium depends on specific lineages and their stem and progenitor function to accommodate hormone-triggered physiological demands in the adult female. Perturbations of these lineages underpin breast cancer risk, yet our understanding of normal mammary cell composition is incomplete. Here, we build a multimodal resource for the adult gland through comprehensive profiling of primary cell epigenomes, transcriptomes, and proteomes. We define systems-level relationships between chromatin–DNA–RNA–protein states, identify lineage-specific DNA methylation of transcription factor binding sites, and pinpoint proteins underlying progesterone responsiveness. Comparative proteomics of estrogen and progesterone receptor–positive and –negative cell populations, extensive target validation, and drug testing lead to discovery of stem and progenitor cell vulnerabilities. Top epigenetic drugs exert cytostatic effects; prevent adult mammary cell expansion, clonogenicity, and mammopoiesis; and deplete stem cell frequency. Select drugs also abrogate human breast progenitor cell activity in normal and high-risk patient samples. This integrative computational and functional study provides fundamental insight into mammary lineage and stem cell biology.

Bidirectional communication between cells and their microenvironment is crucial for both normal tissue homeostasis and tumor growth. During the development of oral tongue squamous cell carcinoma (OTSCC), cancer-associated fibroblasts (CAFs) create a supporting niche by maintaining a bidirectional crosstalk with cancer cells, mediated by classically secreted factors and various nanometer-sized vesicles, termed as extracellular vesicles (EVs). To better understand the role of CAFs within the tumor stroma and elucidate the mechanism by which secreted proteins contribute to OTSCC progression, we isolated and characterized patient-derived CAFs from resected tumors with matched adjacent tissue fibroblasts (AFs). Our strategy employed shotgun proteomics to comprehensively characterize the proteomes of these matched fibroblast populations. Our goals were to identify CAF-secreted factors (EVs and soluble) that can functionally modulate OTSCC cells in vitro and to identify novel CAF-associated biomarkers. Comprehensive proteomic analysis identified 4247 proteins, the most detailed description of a pro-tumorigenic stroma to date. We demonstrated functional effects of CAF secretomes (EVs and conditioned media) on OTSCC cell growth and migration. Comparative proteomics identified novel proteins associated with a CAF-like state. Specifically, MFAP5, a protein component of extracellular microfibrils, was enriched in CAF secretomes. Using in vitro assays, we demonstrated that MFAP5 activated OTSCC cell growth and migration via activation of MAPK and AKT pathways. Using a tissue microarray of richly annotated primary human OTSCCs, we demonstrated an association of MFAP5 expression with patient survival. In summary, our proteomics data of patient-derived stromal fibroblasts provide a useful resource for future mechanistic and biomarker studies.

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.

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.

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.

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.

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.