A rigorous multi-laboratory study of known PDAC biomarkers identifies increased sensitivity and specificity over CA19-9 alone.

A blood test that enables surveillance for early-stage pancreatic ductal adenocarcinoma (PDAC) is an urgent need. Independent laboratories have reported PDAC biomarkers that could improve biomarker performance over CA19-9 alone, but the performance of the previously reported biomarkers in combination is not known. Therefore, we conducted a coordinated case/control study across multiple laboratories using common sets of blinded training and validation samples (132 and 295 plasma samples, respectively) from PDAC patients and non-PDAC control subjects representing conditions under which surveillance occurs.

A Rigorous Multi-Laboratory Study of Known PDAC Biomarkers Identifies Increased Sensitivity and Specificity Over CA19-9 Alone.

A blood test that enables surveillance for early-stage pancreatic ductal adenocarcinoma (PDAC) is an urgent need. Independent laboratories have reported PDAC biomarkers that could improve biomarker performance over CA19-9 alone, but the performance of the previously reported biomarkers in combination is not known. Therefore, we conducted a coordinated case/control study across multiple laboratories using common sets of blinded training and validation samples (132 and 295 plasma samples, respectively) from PDAC patients and non-PDAC control subjects representing conditions under which surveillance occurs.

A polyamine-centric, blood-based metabolite panel predictive of poor response to CAR-T cell therapy in large B cell lymphoma.

Anti-CD19 chimeric antigen receptor (CAR) T cell therapy for relapsed or refractory (r/r) large B cell lymphoma (LBCL) results in durable response in only a subset of patients. MYC overexpression in LBCL tumors is associated with poor response to treatment. We tested whether an MYC-driven polyamine signature, as a liquid biopsy, is predictive of response to anti-CD19 CAR-T therapy in patients with r/r LBCL.

Mining the Immunopeptidome for Antigenic Peptides in Cancer.

Although harnessing the immune system for cancer therapy has shown success, response to immunotherapy has been limited. The immunopeptidome of cancer cells presents an opportunity to discover novel antigens for immunotherapy applications. These neoantigens bind to MHC class I and class II molecules.

A Blood-Based Metabolite Panel for Distinguishing Ovarian Cancer from Benign Pelvic Masses.

Purpose: To assess the contributions of circulating metabolites for improving upon the performance of the risk of ovarian malignancy algorithm (ROMA) for risk prediction of ovarian cancer among women with ovarian cysts.

Experimental Design: Metabolomic profiling was performed on an initial set of sera from 101 serous and nonserous ovarian cancer cases and 134 individuals with benign pelvic masses (BPM). Using a deep learning model, a panel consisting of seven cancer-related metabolites [diacetylspermine, diacetylspermidine, N-(3-acetamidopropyl)pyrrolidin-2-one, N-acetylneuraminate, N-acetyl-mannosamine, N-acetyl-lactosamine, and hydroxyisobutyric acid] was developed for distinguishing early-stage ovarian cancer from BPM.

Coffee Intake, Caffeine Metabolism Genotype, and Survival Among Men with Prostate Cancer.

Background: Coffee intake may lower prostate cancer risk and progression, but postdiagnosis outcomes by caffeine metabolism genotype are not well characterized.

Objective: To evaluate associations between coffee intake, caffeine metabolism genotype, and survival in a large, multicenter study of men with prostate cancer.

Design, Setting, And Participants: Data from The PRACTICAL Consortium database for 5727 men with prostate cancer from seven US, Australian, and European studies were included.

A Deep Learning Approach to Re-create Raw Full-Field Digital Mammograms for Breast Density and Texture Analysis.

Purpose: To develop a computational approach to re-create rarely stored for-processing (raw) digital mammograms from routinely stored for-presentation (processed) mammograms.

Materials And Methods: In this retrospective study, pairs of raw and processed mammograms collected in 884 women (mean age, 57 years ± 10 [standard deviation]; 3713 mammograms) from October 5, 2017, to August 1, 2018, were examined. Mammograms were split 3088 for training and 625 for testing.

Protein citrullination as a source of cancer neoantigens.

Background: Citrulline post-translational modification of proteins is mediated by protein arginine deiminase (PADI) family members and has been associated with autoimmune diseases. The role of PADI-citrullinome in immune response in cancer has not been evaluated. We hypothesized that PADI-mediated citrullinome is a source of neoantigens in cancer that induces immune response.

Pan-Cancer Early Detection: Hype or Hope?

Universal cancer screening based on circulating DNA, proteins, metabolites, or other combinations has the potential to revolutionize early cancer detection, especially for cancers with no available screening modalities. Two recent publications in Science and Annals of Oncology highlight the potential benefits and limitations of single-test, multiple cancer screens.

β-Catenin maintains lung epithelial progenitors after lung specification.

The entire lung epithelium arises from SRY box 9 (SOX9)-expressing progenitors that form the respiratory tree and differentiate into airway and alveolar cells. Despite progress in understanding their initial specification within the embryonic foregut, how these progenitors are subsequently maintained is less clear. Using inducible, progenitor-specific genetic mosaic mouse models, we showed that β-catenin (CTNNB1) maintains lung progenitors by promoting a hierarchical lung progenitor gene signature, suppressing gastrointestinal (GI) genes, and regulating NK2 homeobox 1 (NKX2.

HSP90 inhibition enhances cancer immunotherapy by upregulating interferon response genes.

T-cell-based immunotherapies are promising treatments for cancer patients. Although durable responses can be achieved in some patients, many patients fail to respond to these therapies, underscoring the need for improvement with combination therapies. From a screen of 850 bioactive compounds, we identify HSP90 inhibitors as candidates for combination with immunotherapy.

Baseline and longitudinal plasma caveolin-1 level as a biomarker in active surveillance for early-stage prostate cancer.

Objectives: To evaluate the role of caveolin-1 (Cav-1) as a predictor of disease reclassification (DR) in men with early prostate cancer undergoing active surveillance (AS).

Patients And Methods: We analysed archived plasma samples prospectively collected from patients with early prostate cancer in a single-institution AS study. Of 825 patients enrolled, 542 had ≥1 year of follow-up.

Mass spectrometry based proteomics for absolute quantification of proteins from tumor cells.

In-depth quantitative profiling of the proteome and sub-proteomes of tumor cells has relevance to tumor classification, the development of novel therapeutics, and of prognostic and predictive markers and to disease monitoring. In particular the tumor cell surface represents a highly relevant compartment for the development of targeted therapeutics and immunotherapy. We have developed a proteomic platform to profile tumor cells that encompasses enrichment of surface membrane proteins, intact protein fractionation and label-free mass spectrometry based absolute quantification.

Mining the pre-diagnostic antibody repertoire of TgMMTV-neu mice to identify autoantibodies useful for the early detection of human breast cancer.

Background: The use of autoantibodies for the early detection of breast cancer has generated much interest as antibodies can be readily assayed in serum when antigen levels are low. Ideally, diagnostic autoantibodies would be identified in individuals who harbored pre-invasive disease/high risk lesions leading to malignancy. Prospectively collected human serum samples from these individuals are rare and not often available for biomarker discovery.

Proteomic profiling of the tumor microenvironment: recent insights and the search for biomarkers.

Although gain of oncogene functions and loss of tumor suppressor functions are driving forces in tumor development, the tumor microenvironment, comprising the extracellular matrix, surrounding stroma, signaling molecules and infiltrating immune and other cell populations, is now also recognized as crucial to tumor development and metastasis. Many interactions at the tumor cell-environment interface occur at the protein level. Proteomic approaches are contributing to the definition of the protein constituents of the microenvironment and their sources, modifications, interactions and turnover, as well as providing information on how these features relate to tumor development and progression.

Impact of protein stability, cellular localization, and abundance on proteomic detection of tumor-derived proteins in plasma.

Tumor-derived, circulating proteins are potentially useful as biomarkers for detection of cancer, for monitoring of disease progression, regression and recurrence, and for assessment of therapeutic response. Here we interrogated how a protein's stability, cellular localization, and abundance affect its observability in blood by mass-spectrometry-based proteomics techniques. We performed proteomic profiling on tumors and plasma from two different xenograft mouse models.

Progress in mining the human proteome for disease applications.

Currently available technologies allow in-depth analysis of multiple facets of the proteome that have clinical relevance and that complement current genomics-based approaches. Although some progress has been made in our knowledge of the human proteome in health and in disease, there is an urgent need to chart a coherent road map with clearly defined milestones to guide proteomics efforts. Areas of emphasis include: (1) building resources, (2) filling gaps in our understanding of biological variation, and (3) systematically characterizing proteome alterations that occur in well-defined disease states, all of which require an organized and collaborative effort.

A systems approach to the proteomic identification of novel cancer biomarkers.

The proteomics field has experienced rapid growth with technologies achieving ever increasing accuracy, sensitivity, and throughput, and with availability of computational tools to address particular applications. Given that the proteome represents the most functional component encoded for in the genome, a systems approach to disease investigations and biomarker identification benefits substantially from integration of proteome level studies. Here we present proteomic approaches that have allowed systematic searches for potential cancer markers by integrating cancer cell profiling with additional sources of data, as illustrated with recent studies of ovarian cancer.

BiomarkerDigger: a versatile disease proteome database and analysis platform for the identification of plasma cancer biomarkers.

We have developed a proteome database (DB), BiomarkerDigger (http://biomarkerdigger.org) that automates data analysis, searching, and metadata-gathering function. The metadata-gathering function searches proteome DBs for protein-protein interaction, Gene Ontology, protein domain, Online Mendelian Inheritance in Man, and tissue expression profile information and integrates it into protein data sets that are accessed through a search function in BiomarkerDigger.

Electrospray mass spectrometry for quantitative plasma proteome analysis.

Electrospray ionization mass spectrometry (ESI-MS) is an efficient soft ionization procedure for macro biomolecules. However, it is a rather delicate process to produce charged molecules for mass-to-charge ratio (m/z) based measurement. In this chapter, the mechanism of ESI is briefly presented, and the experimental pipeline for quantitative profiling of plasma proteins (prefractionation immunodepletion, protein isotope tagging, 2D-HPLC separation of intact proteins, and LC-MS) is presented as applied by our group in studies of cancer biomarker discovery.

Autoantibody profiling for cancer detection.

Despite substantial progress in the understanding of the pathogenesis of cancer, the development and implementation of strategies for early cancer detection have lagged behind. Harnessing the immune response to tumor antigens is particularly useful for early detection because the immune response occurs early during tumor development and affords signal amplification with the end product, namely reactive immunoglobulins, being released into the circulation allowing easy access through the blood. This article presents recent developments in autoantibody profiling with a focus on proteomic approaches and applications to lung cancer.