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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.

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.

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.

Invading cancer cells adapt their migration phenotype in response to mechanical and biochemical cues from the extracellular matrix. For instance, mesenchymal migration is associated with strong cell-matrix adhesions and an elongated morphology, while amoeboid migration is associated with minimal cell-matrix adhesions and a rounded morphology. However, it remains challenging to elucidate the role of matrix mechan-ics and biochemistry, since these are both dependent on ECM protein concentration. Here, we demonstrate a composite silk fibroin and collagen I hydrogel where stiffness and microstructure can be systematically tuned over a wide range. Using an overlay assay geometry, we show that the invasion of metastatic breast cancer cells exhibits a biphasic dependence on silk fibroin concentration at fixed collagen I concentration, first increasing as the hydrogel stiffness increases, then decreasing as the pore size of silk fibroin decreases. Indeed, mesenchymal morphology exhibits a similar biphasic depen-dence on silk fibroin concentration, while amoeboid morphologies were favored when cell-matrix adhesions were less effective. We used exogenous biochemical treatment to perturb cells towards increased contractility and a mesenchymal morphology, as well as to disrupt cytoskeletal function and promote an amoeboid morphology. Overall, we envision that this tunable biomaterial platform in a 96-well plate format will be widely applicable to screen cancer cell migration against combinations of designer biomaterials and targeted inhibitors.

PurposeGlioblastoma (GBM) patients suffer from a dismal prognosis, with standard of care therapy inevitably leading to therapy-resistant recurrent tumors. The presence of brain tumor initiating cells (BTICs) 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 BTICs.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 utilize CD70 knockdown studies, subsequent RNAseq pathway analysis, and in vivo xenotransplantation to validate CD70’s role in GBM. Next, we developed and tested an anti-CD70 CAR-T therapy, which we validated in vitro and in vivo using 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 tumorigenicity in vitro and in vivo. CD70 CAR-T therapy significantly improves prognosis in vivo. We also found CD27 to be present on the cell surface of multiple relevant GBM TIME cell populations.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 poly-therapeutic avenue to co-target both GBM and its TIME.

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.

Epithelial tissues mechanically deform the surrounding extracellular matrix during embryonic development, wound repair, and tumor invasion. Ex vivo measurements of such multicellular tractions within three-dimensional (3D) biomaterials could elucidate collective dissemination during disease progression, and enable preclinical testing of targeted anti-migration therapies. However, past 3D traction measurements have been low throughput due to the challenges of imaging and analyzing information-rich 3D material deformations. Here, we demonstrate a method to profile multicellular clusters in a 96-well plate format based on spatially heterogeneous contractile, protrusive, and circumferential tractions. As a case study, we profile multicellular clusters across varying states of the epithelial-mesenchymal transition, revealing a successive loss of protrusive and circumferential tractions, as well as the formation of localized contractile tractions with elongated cluster morphologies. These cluster phenotypes were biochemically perturbed using drugs, biasing towards traction signatures of different epithelial or mesenchymal states. This higher-throughput analysis is promising to systematically interrogate and perturb aberrant mechanobiology, which could be utilized with human patient samples to guide personalized therapies.

Although the relationship between genotype and the tumor environment remains unclear, tumors evolve in specific contexts such that the genotypes and tumor environment shape each other to create an ecosystem. We aim to improve classification of tumors by considering the whole tumor ecosystem by combining genotypes with components of the extracellular matrix (ECM) to develop new prognostic markers and improve targeting of treatments. Collagens are major components of the tumor environment that do far more than just form structures. The function of the full panoply of 43 collagen genes in tumors remains underappreciated. Using the TCGA dataset, we find that mRNA expression of the 43 collagen genes classifies tumors by their cell of origin very similarly as published reports. K-means clustering in each tumor type by collagen mRNA expression revealed classifications strongly associated with overall survival, specific pathways, and immune cell signatures. The collagen defined groups were strongly associated with specific somatic mutations, copy number changes, ploidy and aneuploidy levels. The collagen clusters also revealed specific immunoenvironments, suggesting which tumors were most likely to respond to immunotherapy. To further evaluate these enrichments, we developed a machine learning model to predict which tumors have high or low aneuploidy and specific gain or loss of chromosome arms based on collagen expression, highlighting the connection between collagen expression and specific cancer genomes with areas under the curve above 0.8 for many tumor types including all the GI tumors. Notably, clusters with high total collagen were typically associated with lower aneuploidy levels and tumors with high aneuploidy were grouped in clusters with a mix of minor collagens, and lower collagen type I. These data support a model where tumors with high collagen type I environments have lower aneuploidy and ploidy levels compared to tumors with higher expression of tissue specific minor collagens. The classifier is driven by expression of minor, non-collagen type I, collagens that typically have very specific expression in normal tissue and become dysregulated in many tumors. These findings strongly suggest minor collagens are critical components defining disease progression, the cancer genome and should be included in pre-clinical studies to model the actual human tumor environment and to improve drug development. Preliminary proof-of-concept data for one such minor collagen, COL7A1, will be presented. In sum, these findings demonstrate how classification of tumors by collagens identified strong links between specific cancer genomes and the tumor ECM. Citation Format: Alexander Brodsky, Kevin S. Guo, Amanda Khoo, Vahid Agbortoko, Dongfang Yang, Elizabeth Y. Wu, Ian Y. Wong. Classification of tumors by collagen expression reveals genotype-tumor ECM interactions [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 PO019.

Cancer cell invasion through the extracellular matrix is associated with metastatic spread and therapeutic resistance. In carcinomas, the detachment and dissemination of individual cells has been associated with an epithelial-mesenchymal transition, but tumors can also invade using collective, multicellular phenotypes. This malignant tumor progression is also associated with alignment and stiffening of the surrounding extracellular matrix. Historically, tumor invasion has been investigated using 2D monolayer culture, small animal models or patient histology. These assays have been complemented by the use of natural biomaterials such as reconstituted basement membrane and collagen I. More recently, engineered materials with well-defined physical, chemical and biomolecular properties have enabled more controlled microenvironments. In this review, we highlight recent developments in multicellular tumor invasion based on microfabricated structures or hydrogels. We emphasize the role of interfacial geometries, biomaterial stiffness, matrix remodeling, and co-culture models. Finally, we discuss future directions for the field, particularly integration with precision measurements of biomaterial properties and single cell heterogeneity, standardization and scale-up of these platforms, as well as integration with patient-derived samples.

At present, little is known about how endothelial cells respond to spatial variations in fluid shear stress such as those that occur locally during embryonic development, at heart valve leaflets, and at sites of aneurysm formation. We built an impinging flow device that exposes endothelial cells to gradients of shear stress. Using this device, we investigated the response of microvascular endothelial cells to shear-stress gradients that ranged from 0 to a peak shear stress of 9–210 dyn/cm2. We observe that at high confluency, these cells migrate against the direction of fluid flow and concentrate in the region of maximum wall shear stress, whereas low-density microvascular endothelial cells that lack cell-cell contacts migrate in the flow direction. In addition, the cells align parallel to the flow at low wall shear stresses but orient perpendicularly to the flow direction above a critical threshold in local wall shear stress. Our observations suggest that endothelial cells are exquisitely sensitive to both magnitude and spatial gradients in wall shear stress. The impinging flow device provides a, to our knowledge, novel means to study endothelial cell migration and polarization in response to gradients in physical forces such as wall shear stress.

Peripheral arterial disease (PAD) is characterized by reduced limb blood flow due to arterial obstruction. Current treatment includes surgical or endovascular procedures, the failure of which may result in amputation of the affected limb. An emerging therapeutic approach is cell therapy to enhance angiogenesis and tissue survival. Small clinical trials of adult progenitor cell therapies have generated promising results, although large randomized clinical trials using well-defined cells have not been performed. Intriguing pre-clinical studies have been performed using vascular cells derived from human embryonic stem cells (hESC) or human induced pluripotent stem cells (hiPSCs). In particular, hiPSC-derived vascular cells may be a superior approach for vascular regeneration. The regulatory roadmap to the clinic will be arduous, but achievable with further understanding of the reprogramming and differentiation processes; with meticulous attention to quality control; and perseverance.