Effect of short-term storage of blood samples on gene expression in lung cancer patients.

OBJECTIVES: The stability of gene transcripts associated with the presence of circulating tumor cells (CTCs) has been predominantly studied in cultured cancer cell lines added to blood samples under artificial conditions. In the present study the effect of storage on CTC-related transcripts was assessed in blood samples taken from patients with non-small lung cancer (n=58). METHODS: The blood samples were split in two equal parts to compare the gene expression with and without storage for 24 h at ambient temperature without preservative added. After enrichment using the microfluidic Parsortix® technology, the expression levels of selected genes were assessed using quantitative PCR following a gene-specific pre-amplification. The prognostic relevance of each gene in fresh and stored blood samples was evaluated using the R-package Survminer. RESULTS: Some genes were either not affected (TWIST1, CDH5, CK19) or upregulated upon storage (NANOG, MET, UCHL1) but still associated with poor prognosis. In contrast, ERBB3, PTHLH, EpCAM, and TERT were no longer associated with the overall survival of the patients. CONCLUSIONS: The study demonstrates the surprising stability of CTC-related transcripts, which makes overnight shipping of native blood samples possible. Careful verification is required when using model systems - such as normal blood spiked with tumor cells - or other CTC-related markers, as individual transcripts may respond differently to storage.

Polymer-Ligand-Based ELISA for Robust, High-Throughput, Quantitative Detection of p53 Aggregates.

A growing number of diseases are being linked to protein misfolding and amyloid formation. Recently, p53 was also shown to associate into amyloid aggregates, raising the question of whether cancer development is associated with protein aggregation as well. However, a lack of suitable tools has hampered the evaluation of their clinical relevance. Herein, we report an enzyme-linked-immunosorbent-assay (ELISA) system based on a polyionic, high-molecular-weight ligand that specifically captures aggregated oligomers and amyloid proteins. We proved that naturally occurring tetramers of p53 are not bound, but high-molecular-weight aggregates are bound and subsequently detected. For the first time, this assay allows the quantitative detection of p53 aggregates from cell lysates, which was demonstrated using 22 ovarian-cancer cell lines as well as 7 patient-derived tumor tissues. The levels of p53 aggregates within the missense-mutated tissue samples varied more than 12-fold. This simple, robust method allows studying the abundance and clinical relevance of protein aggregates. This could help our understanding of the role of protein misfolding in cancer or even in predicting therapy responses to aggregation-targeting drugs.

Amyloid-like p53 as prognostic biomarker in serous ovarian cancer-a study of the OVCAD consortium.

TP53 is the most commonly mutated gene in cancer and has been shown to form amyloid-like aggregates, similar to key proteins in neurodegenerative diseases. Nonetheless, the clinical implications of p53 aggregation remain unclear. Here, we investigated the presence and clinical relevance of p53 aggregates in serous ovarian cancer (OC). Using the p53-Seprion-ELISA, p53 aggregates were detected in 46 out of 81 patients, with a detection rate of 84.3% in patients with missense mutations. High p53 aggregation was associated with prolonged progression-free survival. We found associations of overall survival with p53 aggregates, but they did not reach statistical significance. Interestingly, p53 aggregation was significantly associated with elevated levels of p53 autoantibodies and increased apoptosis, suggesting that high levels of p53 aggregates may trigger an immune response and/or exert a cytotoxic effect. To conclude, for the first time, we demonstrated that p53 aggregates are an independent prognostic marker in serous OC. P53-targeted therapies based on the amount of these aggregates may improve the patient's prognosis.

A comparison of four technologies for detecting p53 aggregates in ovarian cancer.

The tumor suppressor protein p53 is mutated in half of all cancers and has been described to form amyloid-like structures, commonly known from key proteins in neurodegenerative diseases. Still, the clinical relevance of p53 aggregates remains largely unknown, which may be due to the lack of sensitive and specific detection methods. The aim of the present study was to compare the suitability of four different methodologies to specifically detect p53 aggregates: co-immunofluorescence (co-IF), proximity ligation assay (PLA), co-immunoprecipitation (co-IP), and the p53-Seprion-ELISA in cancer cell lines and epithelial ovarian cancer tissue samples. In 7 out of 10 (70%) cell lines, all applied techniques showed concordance. For the analysis of the tissue samples co-IF, co-IP, and p53-Seprion-ELISA were compared, resulting in 100% concordance in 23 out of 30 (76.7%) tissue samples. However, Co-IF lacked specificity as there were samples, which did not show p53 staining but abundant staining of amyloid proteins, highlighting that this method demonstrates that proteins share the same subcellular space, but does not specifically detect p53 aggregates. Overall, the PLA and the p53-Seprion-ELISA are the only two methods that allow the quantitative measurement of p53 aggregates. On the one hand, the PLA represents the ideal method for p53 aggregate detection in FFPE tissue, which is the gold-standard preservation method of clinical samples. On the other hand, when fresh-frozen tissue is available the p53-Seprion-ELISA should be preferred because of the shorter turnaround time and the possibility for high-throughput analysis. These methods may add to the understanding of amyloid-like p53 in cancer and could help stratify patients in future clinical trials targeting p53 aggregation.

Cancer Stem Cell-Like Circulating Tumor Cells Are Prognostic in Non-Small Cell Lung Cancer.

Despite recent advances in the treatment of non-small cell lung cancer (NSCLC), less than 10% of patients survive the first five years when the disease has already spread at primary diagnosis. METHODS: Blood samples were taken from 118 NSCLC patients at primary diagnosis or at progression of the disease before the start of a new treatment line and enriched for circulating tumor cells (CTCs) by microfluidic Parsortix™ (Angle plc, Guildford GU2 7AF, UK) technology. The gene expression of epithelial cancer stem cell (CSC), epithelial to mesenchymal (EMT), and lung-related markers was assessed by qPCR, and the association of each marker with overall survival (OS) was evaluated using log-rank tests. RESULTS: EpCAM was the most prevalent transcript, with 53.7% positive samples at primary diagnosis and 25.6% at recurrence. EpCAM and CK19, as well as NANOG, PROM1, TERT, CDH5, FAM83A, and PTHLH transcripts, were associated with worse OS. However, only the CSC-specific NANOG and PROM1 were related to the outcome both at primary diagnosis (NANOG: HR 3.21, 95%CI 1.02-10.14, p = 0.016; PROM1: HR 4.23, 95% CI 0.65-27.56, p = 0.007) and disease progression (NANOG: HR 4.17, 95%CI 0.72-24.14, p = 0.025; PROM1: HR 4.77, 95% CI 0.29-78.94, p = 0.032). CONCLUSIONS: The present study further underlines the relevance of the molecular characterization of CTCs. Our multi-marker analysis highlighted the prognostic value of cancer stem cell-related transcripts at primary diagnosis and disease progression.