Assessment of a six gene panel for the molecular detection of circulating tumor cells in the blood of female cancer patients

<p>Abstract</p> <p>Background</p> <p>The presence of circulating tumor cells (CTC) in the peripheral blood of cancer patients has been described for various solid tumors and their clinical relevance has been shown. CTC detection based on the analysis of epithelial antigens might be hampered by the genetic heterogeneity of the primary tumor and loss of epithelial antigens. Therefore, we aimed to identify new gene markers for the PCR-based detection of CTC in female cancer patients.</p> <p>Methods</p> <p>Gene expression of 38 cancer cell lines (breast, ovarian, cervical and endometrial) and of 10 peripheral blood mononuclear cell (PBMC) samples from healthy female donors was measured using microarray technology (Applied Biosystems). Differentially expressed genes were identified using the maxT test and the 50% one-sided trimmed maxT-test. Confirmatory RT-qPCR was performed for 380 gene targets using the AB TaqMan^®Low Density Arrays. Then, 93 gene targets were analyzed using the same RT-qPCR platform in tumor tissues of 126 patients with primary breast, ovarian or endometrial cancer. Finally, blood samples from 26 healthy women and from 125 patients (primary breast, ovarian, cervical, or endometrial cancer, and advanced breast cancer) were analyzed following OncoQuick enrichment and RNA pre-amplification. Likewise, <it>hMAM </it>and <it>EpCAM </it>gene expression was analyzed in the blood of breast and ovarian cancer patients. For each gene, a cut-off threshold value was set at three standard deviations from the mean expression level of the healthy controls to identify potential markers for CTC detection.</p> <p>Results</p> <p>Six genes were over-expressed in blood samples from 81% of patients with advanced and 29% of patients with primary breast cancer. <it>EpCAM </it>gene expression was detected in 19% and 5% of patients, respectively, whereas <it>hMAM </it>gene expression was observed in the advanced group (39%) only. Multimarker analysis using the new six gene panel positively identified 44% of the cervical, 64% of the endometrial and 19% of the ovarian cancer patients.</p> <p>Conclusions</p> <p>The panel of six genes was found superior to <it>EpCAM </it>and <it>hMAM </it>for the detection of circulating tumor cells in the blood of breast cancer, and they may serve as potential markers for CTC derived from endometrial, cervical, and ovarian cancers.</p

Methylated APC and GSTP1 genes in serum DNA correlate with the presence of circulating blood tumor cells and are associated with a more aggressive and advanced breast cancer disease

<p>Abstract</p> <p>Background</p> <p>Tumor-related methylated DNA and circulating tumor cells (CTC) in the peripheral blood might be of prognostic importance in breast cancer. Thus, the aim of our study was to examine free methylated DNA and CTC in the blood from breast cancer patients and to correlate it with clinicopathological features known to influence prognosis.</p> <p>Materials and methods</p> <p>We prospectively obtained serum samples from 85 patients with breast cancer and 22 healthy volunteers. Sera were analysed by methylation specific PCR (MethyLight PCR) for five genes: adenomatous polyposis coli (APC), ras association domain family protein 1A (RASSF1A), estrogen receptor 1 (ESR1), CDKN2A (p16) and glutathione s-transferase pi 1 (GSTP1). Beta actin (ACTB) served as control. In parallel matched peripheral blood of 63 patients was used to assay for circulating tumor cells in the peripheral blood by a modified immunomagnetic AdnaTest BreastCancerSelect with PCR detection for EPCAM, MUC1, MGB1 and SPDEF.</p> <p>Results</p> <p>We found a hypermethylation in the APC gene in 29% (25/85), in RASSF1A in 26% (22/85), in GSTP1 in 18% (14/76) and in ESR1 in 38% (32/85) of all breast cancer patients. No hypermethylation of CDKN2A was found (0/25). Blood samples of patients were defined CTC positive by detecting the EPCAM 13% (8/63), MUC1 16% (10/63), MGB 9% (5/55), SPDEF 12% (7/58) and in 27% detecting one or more genes (15/55). A significant difference was seen in methylated APC DNA between cancer patients and healthy volunteers. Moreover, methylated APC, RASSF1 and CTC were significantly different in metastatic versus non-metastatic disease. In addition, the presence of methylated APC, RASSF1A and CTC correlated significantly with AJCC-staging (p = 0.001, p = 0.031 and 0.002, respectively). High incidences of methylations were found for the genes RASSF1 and ESR1 in healthy individuals (both 23% 5/22). Methylated GSTP1 was predominantly found in the serum of patients with large primaries (p = 0.023) and was highly significantly correlated with positive Her2/<it>neu </it>status (p = 0.003). Elevated serum CA15.3 was strongly correlated with methylated APC and CTC detection (both p = 0.000). Methylated ESR1 failed to exhibit significant correlations with any of the above mentioned parameters. The presence of CTC in peripheral blood was significantly associated with methylated APC (p = 0.012) and methylated GSTP1 (p = 0.001).</p> <p>Conclusion</p> <p>The detection of methylated APC and GSTP1 DNA in serum correlated with the presence of CTC in the blood of breast cancer patients. Both methylated DNA and CTC correlated with a more aggressive tumor biology and advanced disease.</p

What Can Be Learnt about Disease Progression in Breast Cancer Dormancy from Relapse Data?

Breast cancer patients have an anomalously high rate of relapse many years-up to 25 years-after apparently curative surgery removed the primary tumour. Disease progression during the intervening years between resection and relapse is poorly understood. There is evidence that the disease persists as dangerous, tiny metastases that remain at a growth restricted, clinically undetectable size until a transforming event restarts growth. This is the starting point for our study, where patients who have metastases that are all tiny and growth-restricted are said to have cancer dormancy. Can long-term follow-up relapse data from breast cancer patients be used to extract knowledge about the progression of the undetected disease? Here, we evaluate whether this is the case by introducing and analysing four simple mathematical models of cancer dormancy. These models extend the common assumption that a random transforming event, such as a mutation, can restart growth of a tiny, growth-restricted metastasis; thereafter, cancer dormancy progresses to detectable metastasis. We find that physiopathological details, such as the number of random transforming events that metastases must undergo to escape from growth restriction, cannot be extracted from relapse data. This result is unsurprising. However, the same analysis suggested a natural question that does have a surprising answer: why are interesting trends in long-term relapse data not more commonly observed? Further, our models indicate that (a) therapies which induce growth restriction among metastases but do not prevent increases in metastases' tumourigenicity may introduce a time post-surgery when more patients are prone to relapse; and (b), if a number of facts about disease progression are first established, how relapse data might be used to estimate clinically relevant variables, such as the likely numbers of undetected growth-restricted metastases. This work is a necessary, early step in building a quantitative mechanistic understanding of cancer dormancy