Optimized data-independent acquisition approach for proteomic analysis at single-cell level.

BACKGROUND: Single-cell proteomic analysis provides valuable insights into cellular heterogeneity allowing the characterization of the cellular microenvironment which is difficult to accomplish in bulk proteomic analysis. Currently, single-cell proteomic studies utilize data-dependent acquisition (DDA) mass spectrometry (MS) coupled with a TMT labelled carrier channel. Due to the extremely imbalanced MS signals among the carrier channel and other TMT reporter ions, the quantification is compromised. Thus, data-independent acquisition (DIA)-MS should be considered as an alternative approach towards single-cell proteomic study since it generates reproducible quantitative data. However, there are limited reports on the optimal workflow for DIA-MS-based single-cell analysis. METHODS: We report an optimized DIA workflow for single-cell proteomics using Orbitrap Lumos Tribrid instrument. We utilized a breast cancer cell line (MDA-MB-231) and induced drug resistant polyaneuploid cancer cells (PACCs) to evaluate our established workflow. RESULTS: We found that a short LC gradient was preferable for peptides extracted from single cell level with less than 2 ng sample amount. The total number of co-searching peptide precursors was also critical for protein and peptide identifications at nano- and sub-nano-gram levels. Post-translationally modified peptides could be identified from a nano-gram level of peptides. Using the optimized workflow, up to 1500 protein groups were identified from a single PACC corresponding to 0.2 ng of peptides. Furthermore, about 200 peptides with phosphorylation, acetylation, and ubiquitination were identified from global DIA analysis of 100 cisplatin resistant PACCs (20 ng). Finally, we used this optimized DIA approach to compare the whole proteome of MDA-MB-231 parental cells and induced PACCs at a single-cell level. We found the single-cell level comparison could reflect real protein expression changes and identify the protein copy number. CONCLUSIONS: Our results demonstrate that the optimized DIA pipeline can serve as a reliable quantitative tool for single-cell as well as sub-nano-gram proteomic analysis.

The combination of size-based separation and selection-free technology provides higher circulating tumour cells detection sensitivity than either method alone in patients with metastatic prostate cancer.

OBJECTIVE: To investigate the circulating tumour cells (CTCs) capture abilities of two technologies that are not dependent on cell-surface marker expression: a selection-free platform [AccuCyte® -CyteFinder® system (Rarecyte)] and a size-based platform [fluid-assisted separation technology (FAST)]. In addition, the combination of the two systems to more completely assess CTCs was investigated. PATIENTS AND METHODS: In all, 28 patients with metastatic prostate cancer were included. Two 6 mL peripheral blood samples were taken from each patient at the same time-point. The samples were then subjected to the two different technology platforms in parallel. An additional group of samples was acquired by applying the waste chamber material from the FAST-group tests (flow-through that goes through the FAST filter membrane) to the Rarecyte system for the detection any CTCs that were not captured by FAST. RESULTS: The three groups had significantly different putative CTC-positive tests, with positive rates of 29% for Rarecyte, 57% for FAST, and 79% for the combination. We also assessed CTC phenotype: 56.6% of the CTCs were cytokeratin (CK)+/epithelial cell adhesion molecule (EpCAM)-, 3.1% were CK-/EpCAM+, and 40.3% were CK+/EPCAM+. The captured CTCs diameter ranged from 5.2 to 16.9 µm. The mean CTC size from the FAST waste chamber was significantly smaller. The diameters for each of the phenotypic groups were significantly different. CONCLUSIONS: These data highlight disparities in the positive rates and enumerated CTC numbers detected by the two techniques. Notably, the combination of the two technologies resulted in the highest CTC-capture rates. Smaller CTCs were more likely to be missed by the FAST as they passed through the filter system. Sizes of CTCs varied with different cell surface marker phenotypes.

Analysis of the Circulating Tumor Cell Capture Ability of a Slit Filter-Based Method in Comparison to a Selection-Free Method in Multiple Cancer Types.

Circulating tumor cells (CTCs) are a promising biomarker for cancer liquid biopsy. To evaluate the CTC capture bias and detection capability of the slit filter-based CTC isolation platform (CTC-FIND), we prospectively compared it head to head to a selection-free platform (AccuCyte®-CyteFinder® system). We used the two methods to determine the CTC counts, CTC positive rates, CTC size distributions, and CTC phenotypes in 36 patients with metastatic cancer. Between the two methods, the median CTC counts were not significantly different and the total counts were correlated (r = 0.63, p < 0.0001). The CTC positive rate by CTC-FIND was significantly higher than that by AccuCyte®-CyteFinder® system (91.7% vs. 66.7%, p < 0.05). The median diameter of CTCs collected by CTC-FIND was significantly larger (13.0 µm, range 5.2-52.0 vs. 10.4 µm, range 5.2-44.2, p < 0.0001). The distributions of CTC phenotypes (CK+EpCAM+, CK+EpCAM- or CK-EpCAM+) detected by both methods were similar. These results suggested that CTC-FIND can detect more CTC-positive cases but with a bias toward large size of CTCs.

Tumour tissue-derived small extracellular vesicles reflect molecular subtypes of bladder cancer.

mRNA-based molecular subtypes have implications for bladder cancer prognosis and clinical benefit from certain therapies. Whether small extracellular vesicles (sEVs) can reflect bladder cancer molecular subtypes is unknown. We performed whole transcriptome RNA sequencing for formalin fixed paraffin embedded (FFPE) tumour tissues and sEVs separated from matched tissue explants, urine and plasma in patients with bladder cancer. sEVs were separated using size-exclusion chromatography, and characterized by transmission electron microscopy, nano flow cytometry and western blots, respectively. High yield of sEVs were obtained using approximately 1 g of tissue, incubated with media for 30 min. FFPE tumour tissue and tumour tissue-derived sEVs demonstrated good concordance in molecular subtype classification. All urinary sEVs were classified as luminal subtype, while all plasma sEVs were classified as Ba/Sq subtype, regardless of the molecular subtypes indicated by their matched FFPE tumour tissue. The comparison within urine sEVs, which may exclude the sample type specific background, could pick up the different biology between NMIBC and MIBC, as well as the signature genes related to molecular subtypes. Four candidate sEV-related bladder cancer-specific mRNA biomarkers, FAM71E2, OR4K5, FAM138F and KRTAP26-1, were identified by analysing matched urine sEVs, tumour tissue derived sEVs, and adjacent normal tissue derived sEVs. Compared to sEVs separated from biofluids, tissue-derived sEVs may reflect more tissue- or disease-specific biological features. Urine sEVs are promising biomarkers to be used for liquid biopsy-based molecular subtype classification, but the current algorithm needs to be modified/adjusted. Future work is needed to validate the four new bladder cancer-specific biomarkers in large cohorts.

Urinary extracellular vesicle-derived miR-126-3p predicts lymph node invasion in patients with high-risk prostate cancer.

To investigate extracellular vesicles (EVs), biomarkers for predicting lymph node invasion (LNI) in patients with high-risk prostate cancer (HRPCa), plasma, and/or urine samples were prospectively collected from 45 patients with prostate cancer (PCa) and five with benign prostatic hyperplasia (BPH). Small RNA sequencing was performed to identify miRNAs in the EVs. All patients with PCa underwent radical prostatectomy and extended pelvic lymph node dissection. Differentially expressed miRNAs were identified in patients with and without pathologically-verified LNI. The candidate miRNAs were validated in low-risk prostate cancer (LRPCa) and BPH. Four miRNA species (e.g., miR-126-3p) and three miRNA species (e.g., miR-27a-3p) were more abundant in urinary and plasma EVs, respectively, of patients with PCa. None of these miRNA species were shared between urinary and plasma EVs. miR-126-3p was significantly more abundant in patients with HR PCa with LNI than in those without (P = 0.018). miR-126-3p was significantly more abundant in the urinary EVs of patients with HRPCa than in those with LRPCa (P = 0.017) and BPH (P = 0.011). In conclusion, urinary EVs-derived miR-126-3p may serve as a good biomarker for predicting LNI in patients with HRPCa.

Urinary extracellular vesicle-derived miR-126-3p predicts lymph node invasion in patients with high-risk prostate cancer.

To investigate extracellular vesicles (EVs) biomarkers for predicting lymph node invasion (LNI) in patients with high-risk prostate cancer (HRPCa), plasma and/or urine samples were prospectively collected from 45 patients with prostate cancer (PCa) and five with benign prostatic hyperplasia (BPH). Small RNA sequencing was performed to identify miRNAs in the EVs. All patients with PCa underwent radical prostatectomy and extended pelvic lymph node dissection. Differentially-expressed miRNAs were identified in patients with and without pathologically-verified LNI. The candidate miRNAs were validated in low-risk prostate cancer (LRPCa) and BPH. Four miRNA species (e.g. miR-126-3p) and three miRNA species (e.g. miR-27a-3p) were more abundant in urinary and plasma EVs, respectively, of patients with PCa. None of these miRNA species were shared between urinary and plasma EVs. miR-126-3p was significantly more abundant in patients with HR PCa with LNI than in those without (P = 0.018). miR-126-3p was significantly more abundant in the urinary EVs of patients with HRPCa than in those with LRPCa (P = 0.017) and BPH (P = 0.011). In conclusion, urinary EVs-derived miR-126-3p may serve as a good biomarker for predicting LNI in patients with HRPCa.

Novel urinary tract obstruction marker discovery by multi-marker profiling of urinary extracellular vesicles derived from a rat UTO model.

INTRODUCTION: Congenital urinary obstruction is a common cause of end-stage renal disease in the pediatric population. However, non-invasive diagnostics to predict which patients will benefit from early intervention are lacking. METHODS: Using a rat model of upper and lower urinary tract partial obstruction and the Nanostring nCounter Fibrosis V2 Panel, we evaluated the mRNA cargo of urinary small extracellular vesicles (sEVs) and mRNA expression patterns of kidney and bladder tissues from rats with lower tract urinary obstruction and upper tract urinary obstruction. RESULTS: While mRNA hierarchical clustering of urinary sEVs was unable to differentiate upper compared to lower tract urinary obstruction, clustering was able to detect overall disease state (UUTO or LUTO) versus healthy controls. Further, urinary sEVs carried genes unique to each treatment group (UUTO: 59 genes, LUTO: 17 genes), while only one gene was uniquely carried in the control group. Notable genes of interest found in urinary sEVs were VCAM-1 and NOS1 for UUTO, Egfr for LUTO, and Pck1 for healthy controls. CONCLUSION: This study provides support that differential gene expression of urinary sEV mRNA has potential to act as biomarkers in the diagnosis and prognosis of UTO. Urinary sEVs demonstrated higher numbers of unique genes representative of injury to the kidney than that of injury to the bladder. Importantly, there were genes unique to UUTO sEVs, indicating the extent and reversibility of renal damage can be independent of the function, damage, and architecture of the bladder.

Extracellular Vesicle Uptake Assay via Confocal Microscope Imaging Analysis.

There is a need for practical assays to visualize and quantify the cells' extracellular vesicle (EV) uptake. EV uptake plays a role in intercellular communication in various research fields; cancer biology, neuroscience, and drug delivery. Many EV uptake assays have been reported in the literature; however, there is a lack of practical, detailed experimental methodology. EV uptake can be assessed by fluorescently labeling EVs to detect their location within cells. Distinguishing between internalized EVs in cells and the superficial EVs on cells is difficult, yet critical, to accurately determine the EV uptake. Therefore, an assay that efficiently quantifies EV uptake through three-dimensional (3D) fluorescence confocal microscopy is proposed in this work. Fluorescently labeled EVs were prepared using a nano-filtration-based microfluidic device, visualized by 3D confocal microscopy, and then analyzed through advanced image-processing software. The protocol provides a robust methodology for analyzing EVs on a cellular level and a practical approach for efficient analysis.

Advancements in the identification of EV derived mRNA biomarkers for liquid biopsy of clear cell renal cell carcinomas.

OBJECTIVE: To propose EV-derived mRNA as a potential diagnostic biomarker detecting the presence of clear cell renal cell carcinoma (ccRCC). There is currently no kidney cancer specific screening or diagnostic technology. Therefore, one-third of kidney cancer diagnoses occur after the cancer has metastasized and is past curative measures MATERIALS AND METHODS: Urine, plasma, normal tumor adjacent tissue, and tumor tissue was collected from a limited population of ccRCC patients. Extracellular vesicle (EV) isolation was performed on each sample, followed by mRNA extraction from isolated EVs. NanoString nCounter technology was utilized to count the mRNA transcripts present in matched plasma, urine, tumor tissue, and normal tumor adjacent tissue samples. RESULTS: 770 mRNA transcripts related to gene's affecting cancer's progression and metastasis processes were evaluated. Four EV derived mRNA transcripts (ALOX5, RBL2, VEGFA, TLK2) were found specific to urine and tumor tissue samples. CONCLUSION: Four candidate RCC-specific urine EV biomarkers were identified. However, due to the lack of a true negative control and urine collection techniques, further re-examination is necessary for validation. This study demonstrates the promise of defining disease-specific EV biomarkers in liquid biopsy patient samples.

RNA profiling of circulating tumor cells systemically captured from diagnostic leukapheresis products in prostate cancer patients.

The application of circulating tumor cells (CTCs) in both clinical practice and research has been continuously limited by the rare number of targets that can be found in a tube of peripheral blood. Diagnostic leukapheresis (DLA) was used to increase the sampling volume. AdnaTest was used to process the whole leukopak, and the RNAs of captured CTCs was then profiled by NanoString nCounter platform. Spike-in experiments and leukopaks from patients with metastatic prostate cancer were used to validate this new strategy. The whole leukopak was further concentrated five times to reduce the total volume from 150 â€‹mL to 30 â€‹mL, which enabled it to be processed by 3 separate AdnaTest kits. The spike-in experiment demonstrated a reliable capture when there were more than 100 cancer cells/10 â€‹mL of concentrated leukopak. In 1 out of 5 real patient samples, CTCs were only detected in the leukopak, but not in peripheral blood. The RNA profiling of DLA CTCs indicated a more aggressive phenotype of CTCs occurred when the patient was experiencing a disease relapse, even when the serum prostate specific antigen (PSA) level was still relatively low and CTCs in peripheral blood were not detectable. We established a new protocol, integrating DLA, AdnaTest and NanoString nCounter technology, to profile RNAs from CTCs captured from a large blood screening volume. The new protocol can process the whole leukopak with sensitive CTC capture. The RNA profiling of CTCs can provide valuable information for disease monitoring.

ROS-induced cell cycle arrest as a mechanism of resistance in polyaneuploid cancer cells (PACCs).

Cancer is responsible for the deaths of millions of people worldwide each year. Once metastasized, the disease is incurable and shows resistance to all anti-cancer therapies. The already-elevated level of reactive oxygen species (ROS) in cancer cells is further increased by therapies. The oxidative stress activates the DNA damage response (DDR) and the stressed cancer cell moves towards cell cycle arrest. Once arrested, the majority of cancer cells will undergo programmed cell death in the form of apoptosis. If the cancer cell is able to exit the cell cycle prior to cell division and enter a protected G0 state, it is able to withstand and survive therapy as a polyaneuploid cancer cell (PACC) and eventually seed resistant tumor growth.

Defining candidate mRNA and protein EV biomarkers to discriminate ccRCC and pRCC from non-malignant renal cells in vitro.

Renal cell carcinoma (RCC) accounts for over 400,000 new cases and 175,000 deaths annually. Diagnostic RCC biomarkers may prevent overtreatment in patients with early disease. Extracellular vesicles (EVs) are a promising source of RCC biomarkers because EVs carry proteins and messenger RNA (mRNA) among other biomolecules. We aimed to identify biomarkers and assess biological functions of EV cargo from clear cell RCC (ccRCC), papillary RCC (pRCC), and benign kidney cell lines. EVs were enriched from conditioned cell media by size exclusion chromatography. The EV proteome was assessed using Tandem Mass Tag mass spectrometry (TMT-MS) and NanoString nCounter technology was used to profile 770 cancer-related mRNA present in EVs. The heterogeneity of protein and mRNA abundance and identification highlighted the heterogeneity of EV cargo, even between cell lines of a similar pathological group (e.g., ccRCC or pRCC). Overall, 1726 proteins were quantified across all EV samples, including 181 proteins that were detected in all samples. In the targeted profiling of mRNA by NanoString, 461 mRNAs were detected in EVs from at least one cell line, including 159 that were present in EVs from all cell lines. In addition to a shared EV cargo signature, pRCC, ccRCC, and/or benign renal cell lines also showed unique signatures. Using this multi-omics approach, we identified 34 protein candidate pRCC EV biomarkers and 20 protein and 8 mRNA candidate ccRCC EV biomarkers for clinical validation.

Immune profiling of the bone marrow microenvironment in patients with high-risk localized prostate cancer.

Bone marrow (BM) is a primary metastatic site in prostate cancer (PC) and bone invasion is considered incurable. T cell-mediated immune surveillance is essential in controlling both tumorigenesis and initiation of metastases. Beside tropism, dissemination of PC cells to the BM may be facilitated by defects in BM immune homeostasis predisposing this niche to colonization. To evaluate the BM immune microenvironment in locally advanced, non-metastatic PC, we performed flow cytometry analysis of myeloid and lymphoid subsets in BM aspirates and peripheral blood collected during prostatectomy. Healthy BM aspirates served to establish a reference range for comparison. We found alterations in BM immune composition of PC patients, including an increased CD4/CD8 ratio, enrichment of CD4+ T cells, increased CD56+CD3+ NKT and CD56+CD3- NK yields compared to healthy controls. The lymphoid phenotype remained comparable regarding T cell activation and chemokine receptor-based polarization patterns. Additionally, we found increased B7H3 expression in the myeloid monocyte/macrophage subset and decreased DC infiltration in BM of PC patients. These findings suggest that alterations in the immune milieu may limit immune surveillance that compromise the ability of the BM microenvironment to prevent tumor dissemination, and predispose development of bone metastases in a subset of patients with localized PC.

Comprehensive evaluation of methods for small extracellular vesicles separation from human plasma, urine and cell culture medium.

One of the challenges that restricts the evolving extracellular vesicle (EV) research field is the lack of a consensus method for EV separation. This may also explain the diversity of the experimental results, as co-separated soluble proteins and lipoproteins may impede the interpretation of experimental findings. In this study, we comprehensively evaluated the EV yields and sample purities of three most popular EV separation methods, ultracentrifugation, precipitation and size exclusion chromatography combined with ultrafiltration, along with a microfluidic tangential flow filtration device, Exodisc, in three commonly used biological samples, cell culture medium, human urine and plasma. Single EV phenotyping and density-gradient ultracentrifugation were used to understand the proportion of true EVs in particle separations. Our findings suggest Exodisc has the best EV yield though it may co-separate contaminants when the non-EV particle levels are high in input materials. We found no 100% pure EV preparations due to the overlap of their size and density with many non-EV particles in biofluids. Precipitation has the lowest sample purity, regardless of sample type. The purities of the other techniques may vary in different sample types and are largely dependent on their working principles and the intrinsic composition of the input sample. Researchers should choose the proper separation method according to the sample type, downstream analysis and their working scenarios.