Dataset Information

Highly sensitive detection of sentinel lymph node metastasis of breast cancer by digital PCR for RASSF1A methylation.

ABSTRACT: One?step nucleic acid amplification (OSNA) targeting cytokeratin 19 (CK19) mRNA expression and pathological examination are widely used for the intraoperative diagnosis of sentinel node (SN) metastasis. The aim of the present study was to develop a novel assay for detecting SN metastasis by targeting Ras association domain?containing protein 1 (RASSF1A) methylation in tumor cells, and to compare its performance with OSNA. Using digital PCR with methylation?specific restriction enzymes (RE?dMSP), our assay was able to detect ?3 copies of methylated DNA per well, and was ?10 times more sensitive than real?time PCR with bisulfite modification. OSNA lysates were examined using RE?dMSP and digital PCR for PIK3CA mutation, in the event that primary tumors were PIK3CA mutation?positive. RE?dMSP revealed a high concordance of 95.0% (153/161) with OSNA, and 100% (59/59) with PIK3CA mutation for detecting SN metastasis. In 11 breast cancer cell lines, the variation in methylated RASSF1A copy number was significantly lower than that of CK19 mRNA (2.8 vs. 10.5?fold; P<0.01). RE?dMSP has the potential to more accurately detect SN metastasis, and to more precisely estimate total tumor loads in SN, compared with OSNA.

SUBMITTER: Abe M

PROVIDER: S-EPMC6826319 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Highly sensitive detection of sentinel lymph node metastasis of breast cancer by digital PCR for RASSF1A methylation.

Abe Mizuho M Kagara Naofumi N Miyake Tomohiro T Tanei Tomonori T Naoi Yasuto Y Shimoda Masafumi M Shimazu Kenzo K Kim Seung Jin SJ Noguchi Shinzaburo S

Oncology reports 20191010 6

One‑step nucleic acid amplification (OSNA) targeting cytokeratin 19 (CK19) mRNA expression and pathological examination are widely used for the intraoperative diagnosis of sentinel node (SN) metastasis. The aim of the present study was to develop a novel assay for detecting SN metastasis by targeting Ras association domain‑containing protein 1 (RASSF1A) methylation in tumor cells, and to compare its performance with OSNA. Using digital PCR with methylation‑specific restriction enzymes (RE‑dMSP), ...[more]

PMID: 31638213

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Project description:Background The rate of breast-conserving surgery is very low in China, compared with that in developed countries; most breast cancer patients receive mastectomy. It is great important to explore the possibility of omitting axillary lymph node dissection (ALND) in early-stage breast cancer patients with 1 or 2 positive sentinel lymph nodes (SLNs) in China. The aim of this study was to develop a nomogram based on elastography for the prediction of the risk of non-SLN (NSLN) metastasis in early-stage breast cancer patients with 1 or 2 positive SLNs. Methods A total of 601 breast cancer patients were initially recruited. According to the inclusion and exclusion criteria, 118 early-stage breast cancer patients with 1 or 2 positive SLNs were finally enrolled and were assigned to the training cohort (n=82) and the validation cohort (n=36), respectively. In the training cohort, the independent predictors were screened by logistic regression analysis and then were used to conducted the nomogram for the prediction of NSLN metastasis in early-stage breast cancer patients with 1 or 2 positive SLNs. The calibration curves, concordance index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), and Decision curve analysis (DCA) were used to verified the performance of the nomogram. Results The multivariable analysis showed that the enrolled patients with positive HER2 expression (OR=6.179, P=0.013), Ki67≥14% (OR=8.976, P=0.015), larger lesion size (OR=1.038, P=0.045), and higher Emean (OR=2.237, P=0.006) were observed to be the independent factors of NSLN metastasis. Based on the above four independent predictors, a nomogram was conducted to predict the risk of the NSLN metastasis in early-stage breast cancer patients with 1 or 2 positive SLNs. The nomogram showed good discrimination in the prediction of NSLN metastasis, with bias-corrected C-index of 0.855 (95% CI, 0.754-0.956) and 0.853 (95% CI, 0.724-0.983) in the training and validation cohorts, respectively. Furthermore, the AUC was 0.877 (95%CI: 0.776- 0.978) and 0.861 (95%CI: 0.732-0.991), respectively, indicating a good performance of the nomogram. The calibration curve suggested a satisfactory agreement between the predictive and actual risk in both the training (χ2 = 11.484, P=0.176, HL test) and validation (χ2 = 6.247, p = 0.620, HL test) cohorts, and the obvious clinical nets were revealed by DCA. Conclusions We conducted a satisfactory nomogram model to evaluate the risk of NSLN metastasis in early-stage breast cancer patients with 1 or 2 SLN metastases. This model could be considered as an ancillary tool to help such patients to be selectively exempted from ALND.

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Dataset Information

Highly sensitive detection of sentinel lymph node metastasis of breast cancer by digital PCR for RASSF1A methylation.

Publications

Highly sensitive detection of sentinel lymph node metastasis of breast cancer by digital PCR for RASSF1A methylation.

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