ABSTRACT
Existing marker-based methods of minimal residual disease (MRD) determination in neuroblastoma do not effectively enrich for the circulating disease cell population. Given the relative size differential of neuroblastoma tumor cells over normal hematogenous cells, we hypothesized that cell size-based separation could enrich circulating tumor cells (CTCs) from blood samples and disseminated tumor cells (DTCs) from bone marrow aspirates (BMA) of neuroblastoma patients, and that their gene expression profiles could vary dynamically with various disease states over the course of treatment. Using a spiral microfluidic chip, peripheral blood of 17 neuroblastoma patients at 3 serial treatment timepoints (diagnosis, n=17; post-chemotherapy, n=11; and relapse, n=3), and bone marrow samples at diagnosis were enriched for large intact circulating cells. Profiling the resulting enriched samples with immunohistochemistry and mRNA expression of 1490 cancer-related genes via NanoString, 13 of 17 samples contained CTCs displaying cytologic atypia, TH and PHOX2B expression and/or upregulation of cancer-associated genes. Gene signatures reflecting pro-metastatic processes and the neuroblastoma mesenchymal super-enhancer state were consistently upregulated in 7 of 13 samples, 6 of which also had metastatic high-risk disease. Expression of 8 genes associated with PI3K and GCPR signaling were significantly upregulated in CTCs of patients with bone marrow metastases versus patients without. Correspondingly, in patients with marrow metastases, differentially-expressed gene signatures reflected upregulation of immune regulation in bone marrow DTCs versus paired CTCs samples. In patients who later developed disease relapse, 5 genes involved in immune cell regulation, JAK/STAT signaling and the neuroblastoma mesenchymal super-enhancer state (OLFML2B, STAT1, ARHGDIB, STAB1, TLR2) were upregulated in serial CTC samples over their disease course, despite urinary catecholamines and bone marrow aspirates not indicating the disease recurrences. In summary, using a label-free cell size-based separation method, we enriched and characterized intact circulating cells in peripheral blood indicative of neuroblastoma CTCs, as well as their DTC counterparts in the bone marrow. Expression profiles of pro-metastatic genes in CTCs correlated with the presence of bone marrow metastases at diagnosis, while longitudinal profiling identified persistently elevated expression of genes in CTCs that may serve as novel predictive markers of hematogenous MRD in neuroblastoma patients that subsequently relapse.
ABSTRACT
To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.
