Literature DB >> 28910822

A new molecular-based lymph node staging classification determines the prognosis of breast cancer patients.

Tomo Osako1,2, Takuji Iwase3, Masaru Ushijima4, Rika Yonekura2,3, Shinji Ohno3, Futoshi Akiyama1,2.   

Abstract

BACKGROUND: The one-step nucleic acid amplification (OSNA) assay is a novel molecular method that can detect metastasis in a whole lymph node based on cytokeratin 19 mRNA copy number. This cohort study aimed to establish an OSNA-based nodal staging (pN(mol)) classification for breast cancer.
METHODS: The cohort consisted of 1039 breast cancer patients who underwent sentinel node (SN) biopsy using the OSNA assay. Cutoff value of the SN tumour burden stratifying distant disease-free survival (DDFS) was determined, and predictive factors for DDFS and breast cancer-specific survival (BCSS) were investigated. pN(mol) classification of the SN status was defined as: pN0(mol)(sn), SN negative; pN1mi(mol)(sn), SN positive and tumour burden <cutoff-value; and pN1(mol)(sn), tumour burden ⩾cutoff-value. Median follow-up time; 68.3 months.
RESULTS: Cutoff value of the SN tumour burden was 2810 copies per μl. Of the 1039 patients, 798, 95, and 146 had pN0(mol)(sn), pN1mi(mol)(sn), and pN1(mol)(sn) status, respectively. Five-year DDFS and BCSS rates were lower for pN1(mol)(sn) patients than for pN1mi(mol)(sn) patients (87.7% vs 98.8%, P=0.001 and 93.1% vs 98.8%, P=0.044, respectively). Multivariate analyses revealed the pN(mol) classification was most significant predictor for DDFS and BCSS.
CONCLUSIONS: The molecular-based pN classification determines the prognosis of breast cancer patients and could guide therapeutic decision making.

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Year:  2017        PMID: 28910822      PMCID: PMC5680460          DOI: 10.1038/bjc.2017.311

Source DB:  PubMed          Journal:  Br J Cancer        ISSN: 0007-0920            Impact factor:   7.640


Axillary lymph node status is one of the most powerful prognostic factors in breast cancer (Fisher ). Accurate and reproducible pathological node staging (pN) classification is an important determinant of the prognosis and therapeutic decision making for breast cancer patients. Sentinel lymph node (SN) biopsy has been the standard axillary staging procedure for clinically node-negative patients since the early 1990s (Lyman ). To prevent false-negative diagnoses, pathologists began to perform a more detailed evaluation of a fewer amount of lymph nodes, which are most likely to contain metastasis (Giuliano ). The intensive examination of SNs resulted in an increase in the detection of low-volume metastases (Weaver ). The Cancer Staging Manual of the American Joint Committee on Cancer (AJCC), 6th edition, in 2002 (Green ) classified these low-volume metastases into isolated tumour cells (ITC) and micrometastases. ITC was classified as pN0(i+) with deposits ⩽0.2 mm, and micrometastasis was classified as pN1mi with deposits >0.2 mm to ⩽2 mm. Moreover, in the 7th edition of the AJCC Staging Manual in 2010 (Edge ), T1 with lymph node spread confined to micrometastasis (pN1mi) was downstaged from Stage IIA to Stage IB. However, published studies have reported divergent and conflicting results regarding the prognostic significance of ITC and micrometastasis as defined by the AJCC Staging Manual (Patani & Mokbel, 2011; Salhab ). These divergent and conflicting results can be attributed to the fact that the AJCC pN classification is based on histopathological findings. Conventional histopathological examinations are limited in their ability to accurately quantify the total metastatic volume of a lymph node. Even if a node is step-sectioned and histologically evaluated at each cut surface, the information gathered is incomplete, since only a small part of the node is analysed. Furthermore, histopathological examination procedures for SNs are non-standardised, and the inter-observer reproducibility of measuring metastatic tumour volume is low (Cserni ). The one-step nucleic acid amplification (OSNA) assay (Sysmex, Kobe, Japan) was developed to overcome the limitations of histopathological examination of lymph nodes. This assay can assess the whole lymph node and yields the quantitative data in the form of the cytokeratin 19 (CK19) mRNA copy number (Tsujimoto ). Calibration and validation studies (Tamaki ; Tsujimoto ) have provided reasonable evidence that the CK19 mRNA copy numbers detected by the OSNA assay are good estimates of macrometastasis, micrometastasis, and negative, as defined by the AJCC Staging Manual (Edge ). We have shown that the OSNA whole-node assay detects more cases of SN metastases, particularly micrometastasis, than conventional histological examinations (Osako ; Osako ). Therefore, the OSNA whole-node assay would enable us to more accurately and reproducibly determine the prognosis of breast cancer patients than the current AJCC pN classification based on histopathological examinations. In order to establish a new molecular-based pN (pN(mol)) classification using the OSNA assay, this retrospective cohort study was designed to determine and validate the prognostic cutoff values of the metastatic tumour burden in the SN, as quantified by the CK19 mRNA copy number.

Patients and methods

Patients

The retrospective cohort included patients with clinically and radiologically node-negative invasive breast cancer who underwent SN biopsy and whose whole SNs were examined using the OSNA assay at the Cancer Institute Hospital (Tokyo, Japan) between April 2009 and June 2011. The exclusion criteria were as follows: (1) SN mapping without the use of a radioisotope tracer, (2) bilateral breast cancer, (3) heterochronous ipsilateral breast cancer recurrence, (4) previous excision of a primary tumour, and (5) neoadjuvant drug therapy. The written general consent was obtained from each of the patients, and this study was approved by the Institutional Review Board of the Cancer Institute Hospital. The pathological tumour staging (pT) classification was classified according to the 7th edition of the AJCC Staging Manual (Edge ). Hormone receptor status and human epidermal growth factor receptor-2 (HER2) status were defined according to the American Society of Clinical Oncology/College of American Pathologists guidelines (Hammond ; Wolff ). The labelling index value for Ki67 was evaluated by estimating the % of positive nuclei within the areas of highest labelling density.

SN biopsy

Lymphoscintigraphy using 99mTc-phytate was performed one day prior to the surgery, and a vital blue dye, indigo carmine, was injected into the peri-tumoural space or areola at the time of surgery. Before surgery for the primary tumour, the SNs were identified using a hand-held gamma-probe with guidance from staining of the vessels and nodes. Radioactive and/or blue nodes were considered to be SNs and were excised. When the SN(s) were positive, additional axillary lymph node dissection was performed.

OSNA assay

Each of the whole lymph nodes were homogenised with 4 ml lysis buffer solution (Lynorhag; Sysmex) and centrifuged at 10 000 g at room temperature (Tsujimoto ). A total of 2 μl supernatant was analysed with an automated molecular detection system, the RD-100i System (Sysmex) and the LynoampBC Kit (Sysmex). The degree of amplification was detected on the basis of a reaction by-product, pyrophosphate. The resultant change in turbidity upon precipitation of magnesium pyrophosphate was then correlated with the CK19 mRNA copy number per μl of the original lysate via a standard curve established beforehand with three calibrators containing different CK19 mRNA copy numbers. Standard positive and negative control samples were used for quality assurance in every assay run. Lymph nodes that exceeded the specified maximum weight of 600 mg were cut into two or more pieces and processed separately. The number of CK19 mRNA copies per μl in the measurement sample and the 1:10 diluted sample were calculated; the result was determined based on these copy numbers. When the reaction was inhibited in the measurement sample, the copy numbers in the diluted sample were employed for this determination. Lymph nodes with CK19 mRNA <250 copies per μl were considered to be negative, including ITC, and lymph nodes with CK19 mRNA 250–5000 copies per μl or ⩾5000 copies per μl were considered to be equivalent to AJCC micrometastasis or macrometastasis, respectively (Tsujimoto ). Tsujimoto et al. determined these cutoff values by measuring CK19 mRNA in 23-mm3-size metastatic tumour tissues and histopathologically positive and negative lymph nodes using the OSNA assay. In their clinical validation study, half of each lymph node was assessed by the OSNA assay and the remaining half was paraffin embedded for three-level histological examination with CK19 immunostaining, and an overall concordance rate between those methods was 98.2% (Tsujimoto ).

pN classifications of the SN status

Two pN classifications of the SN status were evaluated: that is, the AJCC pN classification and the new pN(mol) classification. For applying the OSNA assay results to the AJCC pN classification (Edge ), each of the SNs was classified into negative, micrometastasis or macrometastasis using the original cutoff values (<250, 250–5000, and ⩾5000 copies per μl, respectively). For defining the new pN(mol) classification, a cutoff value for the tumour burden in the SN stratifying distant disease-free survival (DDFS) was determined. When more than one SN specimen was examined, the total copy number was considered as the tumour burden. The pN(mol) classification of the SN status was defined as follows: pN0(mol)(sn), SN negative; pN1mi(mol)(sn), SN positive and the total copy number pN1(mol)(sn), SN positive and the total copy number ⩾cutoff-value.

Detection of non-SN metastasis

Non-SNs in the axillary dissection materials were examined with routine histology or the OSNA assay according to the study period. Between April 2009 and September 2009, non-SN metastasis was detected with single-section histopathology. Between September 2009 and June 2011, each non-SN was examined with the OSNA whole-node assay for clinical research (Osako ; Osako ).

Adjuvant treatment and follow-up

After the surgery, the patients received a combination of routine adjuvant treatments according to international standards and the national guideline, based on tumour characteristics, including hormone receptor status, HER2 status, lymph node status, and surgical treatment. Patients were followed-up with a clinical examination, mammography, and ultrasonography.

Statistical analyses

To compare the frequencies of non-SN metastasis, we performed two-sample test for equality of proportions with continuity correction. DDFS and breast cancer-specific survival (BCSS) were used as prognostic endpoints. DDFS was defined as the period from surgery to distant metastasis of breast cancer, and BCSS was defined as the period from surgery to breast cancer death. The cumulative survival rates were calculated by the Kaplan–Meier method. To define the new pN(mol) classification, an optimal cutoff value for the tumour burden in the SN was determined according to the maximally selected log-rank statistics analysis. For validating the prognostic impact of the pN(mol) classification on DDFS and BCSS, univariate log-rank tests and multivariate Cox proportional hazards regression models were used. Multivariate analysis was used for the significant factors from the univariate analyses, and the optimal models were selected by Akaike’s Information Criterion. P-values <0.05 were considered to be significant, and the confidence intervals (CI) were set at the 95% level. All statistical analyses were performed with R statistical software (version 3.3.2, http://www.r-project.org/).

Results

Patient characteristics

Between April 2009 and June 2011, 1296 patients with invasive breast cancer underwent SN biopsy using the OSNA whole-node assay, and 1039 of them did not meet the exclusion criteria. The demographic characteristics of the entire cohort are presented in Table 1. Of the 1039 patients, 319 (30.7%) received adjuvant cytotoxic chemotherapy, and 117 (36.7%), 4 (1.3%), 194 (60.8%), and 4 (1.3%) of them received anthracycline-containing regimen alone, taxane-containing regimen alone, both the anthracycline and taxane, and other regimens, respectively. The median follow-up time was 68.3 months (range, 2.0–85.8).
Table 1

Patient characteristics according to the molecular-based pN classification of the sentinel node status

   pN0(mol)(sn)
pN1mi(mol)(sn)
pN1(mol)(sn)
CharacteristicNo.%No.%No.%No.%
No. of patients1039100.0%798(76.8%)95(9.1%)146(14.1%)
Age (years)        
 ⩽median (25–53)53751.7%41652.1%4345.3%7853.4%
 >median (54–89)50248.3%38247.9%5254.7%6846.6%
Breast surgery        
 Partial mastectomy65262.8%52565.8%5658.9%7148.6%
 Total mastectomy38737.2%27334.2%3941.1%7551.4%
pT classification        
 pT1a23822.9%21827.3%1414.7%64.1%
 pT1b23222.3%19424.3%2122.1%1711.6%
 pT1c40038.5%28836.1%4042.1%7249.3%
 pT216415.8%9612.0%2021.1%4832.9%
 pT350.5%20.3%00.0%32.1%
Nuclear grade        
 144743.0%35644.6%4042.1%5134.9%
 238737.2%28235.3%4042.1%6544.5%
 320519.7%16020.1%1515.8%3020.5%
Lymphovascular invasion        
 −75472.6%63779.8%5658.9%6141.8%
 +28527.4%16120.2%3941.1%8558.2%
Oestrogen receptor        
 +84180.9%63379.3%8589.5%12384.2%
 −19819.1%16520.7%1010.5%2315.8%
Progesterone receptor        
 +70267.6%52565.8%7477.9%10370.5%
 −33732.4%27334.2%2122.1%4329.5%
HER2        
 −91488.0%70688.5%8791.6%11981.5%
 +12111.6%8811.0%88.4%2718.5%
 Unknown40.4%40.5%00.0%00.0%
Ki67 labelling index (%)        
 ⩽median (0.1–15.4)52150.1%41251.6%4850.5%6141.8%
 >median (15.5–93.8)51849.9%38648.4%4749.5%8558.2%
AJCC pN(sn) classification        
 pN0(sn)79876.8%798100.0%
 pN1mi(sn)10910.5%95100.0%149.6%
 pN1(sn)12612.1%12686.3%
 pN2(sn)60.6%64.1%
Positive SN ratio        
 ⩽0.590286.8%798100.0%5760.0%4732.2%
 0.5–1.0161.5%11.1%1510.3%
 =1.012111.6%3738.9%8457.5%
AJCC pN classification (SN+non-SN)        
 pN079876.8%798100.0%
 pN1mi949.0%8286.3%128.2%
 pN110910.5%1010.5%9967.8%
 pN2282.7%33.2%2517.1%
 pN3101.0%106.8%
Adjuvant systemic therapy        
 None19318.6%18322.9%22.1%85.5%
 Cytotoxic chemotherapy31930.7%13116.4%6164.2%12787.0%
 Endocrine therapy74371.5%54368.0%8286.3%11880.8%
 Anti-HER2 therapy737.0%415.1%77.4%2517.1%

Abbreviations: AJCC=American Joint Committee on Cancer; HER2=human epidermal growth factor receptor-2; SN, sentinel lymph node.

pN(mol) classification of the SN status

The best discriminative cutoff value of the metastatic tumour burden for stratifying DDFS was 2810 copies per μl (Figure 1). Using this cutoff value, of the 1039 patients, 798 (76.8%), 95 (9.1%), and 146 (14.1%) had pN0(mol)(sn), pN1mi(mol)(sn), and pN1(mol)(sn) status, respectively. The demographic characteristics of each category are presented in Table 1.
Figure 1

Cutoff value of the metastatic tumour burden in the sentinel node for stratifying distant disease-free survival.

Non-SN status of SN-positive patients

Apart from one patient with pN1mi(mol)(sn) disease, all of the SN-positive patients underwent additional axillary dissection. Macrometastases in non-SN were more frequently found in pN1(mol)(sn) patients than in pN1mi(mol)(sn) patients (47 out of 146, 32.2% vs 13 out of 94, 13.8%, P=0.002) (Figure 2). However, there was no difference in the frequency of non-SN metastasis (micro- and macrometastasis) between pN1mi(mol)(sn) patients and pN1(mol)(sn) patients (41 out of 94, 43.6% vs 73 out of 146, 50.0%, P=0.40). Regarding the examination method for non-SN, the OSNA assay detected more cases of non-SN micrometastasis than the single-section histology.
Figure 2

The non-SN status of pN1mi(mol)(sn) patients and pN1(mol)(sn) patients according to the examination method for the non-SNs. Abbreviations: SN=sentinel lymph node; OSNA=one-step nucleic acid amplification.

*One patient did not undergo additional axillary dissection; **P<0.01; † difference in the frequency of non-SN metastasis (micro- and macrometastasis).

Distant disease-free survival

Five-year DDFS rates were lower for pN1(mol)(sn) patients than for pN0(mol)(sn) patients (87.7% vs 98.0%, hazard ratio (HR) 6.94 (3.50–13.77), P<0.001) and for pN1mi(mol)(sn) patients (87.7% vs 98.8%, HR 12.95 (1.73–95.00), P=0.001) (Figure 3A). There was no significant 5-year DDFS difference between pN1mi(mol)(sn) and pN0(mol)(sn) patients (98.8% vs 98.0%, HR 0.55 (0.07–5.15), P=0.56).
Figure 3

Distant disease-free survival (A) and breast cancer-specific survival (B) according to the pN(mol) classification of the sentinel node status. *P<0.05; **P<0.01.

In the univariate analysis, in addition to the pN(mol)(sn) status, DDFS was significantly related to breast surgery procedure, pT classification, grade, hormone-receptor status, Ki67 labelling index, AJCC pN(sn) classification, positive SN ratio, non-SN status, and adjuvant cytotoxic and endocrine therapies (Table 2). On the other hand, DDFS was not significantly related to age, lymphovascular invasion, HER2 status, and adjuvant anti-HER2 therapy. In the multivariable analysis, pN(mol)(sn) classification, progesterone receptor status, pT classification, and Ki67 labelling index remained significant (Table 3).
Table 2

Univariate analysis of predictive factors for distant disease-free survival and for breast cancer-specific survival

 Distant disease-free survival
Breast cancer-specific survival
  95% CI
  95% CI
 
CharacteristicHazard ratioLowerUpperPHazard ratioLowerUpperP
Age
⩽median1.00   1.00   
>median1.790.903.580.0941.280.463.520.629
Breast surgery
Partial mastectomy1.00   1.00   
Total mastectomy4.172.008.73<0.001**2.580.927.240.063
pT classification
pT11.00   1.00   
pT2 or pT35.342.7310.47<0.001**5.952.1616.41<0.001**
Nuclear grade
1 or 21.00   1.00   
33.871.977.58<0.001**3.741.3610.330.006**
Lymphovascular invasion
1.00   1.00   
+1.870.943.700.0663.001.098.280.025*
Oestrogen receptor
+1.00   1.00   
3.111.576.16<0.001**3.861.4010.650.005**
Progesterone receptor
+1.00   1.00   
3.941.957.96<0.001**4.291.4712.570.004**
HER2
− or unknown1.00   1.00   
+1.020.362.910.9680.540.074.120.545
Ki67 labelling index
⩽median1.00   1.00   
>median4.041.769.28<0.001**6.731.5229.850.002**
Molecular-based pN classification
pN0(mol)(sn) or pN1mi(mol)(sn)1.00   1.00   
pN1(mol)(sn)7.303.7214.32<0.001**9.423.3526.46<0.001**
AJCC pN(sn) classification
pN0(sn) or  pN1mi(sn)1.00   1.00   
pN1(sn) or  pN2(sn)5.672.8811.17<0.001**8.012.9022.08<0.001**
Positive SN ratio
⩽0.51.00   1.00   
>0.54.772.419.44<0.001**5.792.1015.98<0.001**
Non-SN metastasis
1.00   1.00   
+3.571.717.48<0.001**5.722.0316.12<0.001**
Non-SN macrometastasis
1.00   1.00   
+3.741.559.020.002 **6.221.9819.54<0.001**
Adjuvant systemic therapy
None1.00   1.00   
Cytotoxic chemotherapy2.551.305.000.005 **2.550.927.030.061
Endocrine therapy0.480.240.950.028 *0.330.120.920.025*
Anti-HER2 therapy0.840.203.500.8060.000.000.000.284

Abbreviations: AJCC=American Joint Committee on Cancer; CI=confidence interval; HER2=human epidermal growth factor receptor-2; SN=sentinel lymph node.

*P<0.05; **P<0.01; †no event.

Table 3

Multivariate analysis of predictive factors for distant disease-free survival and for breast cancer-specific survival

 Distant disease-free survival
Breast cancer-specific survival
  95% CI
  95% CI
 
CharacteristicHazard ratioLowerUpperPHazard ratioLowerUpperP
Molecular-based pN classification7.563.4116.75<0.001**7.192.4621.04<0.001**
Progesterone receptor3.831.887.81<0.001**3.751.2711.070.017*
pT classification3.441.657.16<0.001**3.121.098.950.034*
Ki67 labelling index2.491.075.800.034*4.150.9218.660.063
Cytotoxic chemotherapy0.520.241.150.106

Abbreviation: CI=confidence intervals.

*P<0.05; **P<0.01.

Breast cancer-specific survival

Five-year BCSS rates were lower for pN1(mol)(sn) patients than for pN0(mol)(sn) patients (93.1% vs 99.4%, HR 10.06 (3.37–30.02), P<0.001) and for pN1mi(mol)(sn) patients (93.1% vs 98.8%, HR 6.30 (0.80–49.70), P=0.044) (Figure 3B). There was no significant 5-year BCSS difference between pN1mi(mol)(sn) and pN0(mol)(sn) patients (98.8% vs 99.4%, HR 1.70 (0.20–14.54), P=0.63). In the univariate analysis, in addition to the pN(mol)(sn) status, BCSS was significantly related to pT classification, grade, lymphovascular invasion, hormone-receptor status, Ki67 labelling index, AJCC pN(sn) classification, positive SN ratio, non-SN status, and adjuvant endocrine therapy (Table 2). On the other hand, BCSS was not significantly related to age, breast surgery procedure, HER2 status, and adjuvant cytotoxic and anti-HER2 therapies. In the multivariable analysis, pN(mol)(sn) classification, progesterone receptor status, and pT classification remained significant (Table 3).

Discussion

As far as we know, the present study is the first report to establish a new molecular-based lymph node staging classification for breast cancer without using any histopathological examinations. The new pN(mol) classification is characterised by a total quantification of the metastatic tumour burden in the SN based on the CK19 mRNA copy number using the OSNA whole-node assay, which can more accurately and reproducibly evaluate the metastatic volume than conventional histopathological examinations. Using the pN(mol) classification, pN1(mol)(sn) patients showed a significantly worse prognosis than pN0(mol)(sn) or pN1mi(mol)(sn) patients, and the SN status was the most powerful prognostic factor in early-stage breast cancer. The prognostic cutoff value was set at 2,810 copies per μl of CK19 mRNA, which is within the range of the tumour burden equivalent to AJCC micrometastasis (250–5000 copies per μl) (Tsujimoto ). Therefore, patients with AJCC micrometastasis can possibly be divided into a good prognosis group and a poor prognosis group according to the metastatic volume. However, conventional histopathological examinations are limited in their ability to accurately and reproducibly evaluate the micrometastasis in a lymph node. This may be attributed to the divergent and conflicting results of the prognostic significance of AJCC micrometastasis in previous studies (Salhab ). On the other hand, the OSNA assay can accurately and reproducibly evaluate the small metastatic volume, thus the pN(mol) classification could precisely determine patient’s prognosis. A Spanish group has recently proposed the prognostic cutoff value of 25 000 copies per μl (Peg ), which is higher than the cutoff value obtained in the present study (2810 copies per μl). The Spanish group determined the cutoff value by quartering the tumour burdens and testing each of the quartile points for statistical significance. In the present study, however, the optimal cutoff value was more precisely determined by selecting the minimum P-value of all possible cutoff points shown in the Figure 1. Applying the Spanish cutoff value to the Figure 1, this cutoff value is statistically significant (P=8.31e-8), but the cutoff value of 2810 copies per μl is more significant for stratifying patient survival (P=1.18e-11) than the Spanish cutoff value. In addition, another group has recently proposed a similar cutoff value (2150 copies per μl) as the present study for predicting non-SN metastasis (Terrenato ). Thus, we believe that our cutoff value can more accurately stratify patient survival than the Spanish cutoff value. pN1mi(mol)(sn) patients showed similar prognosis to pN0(mol)(sn) patients, even though pN1(mol)(sn) patients showed significantly worse prognosis than pN0(mol)(sn) or pN1mi(mol)(sn) patients. According to the Dutch MIRROR study, micrometastases in regional lymph nodes are associated with a reduced disease-free survival rate among early-stage breast cancer patients who did not receive adjuvant therapy; however, adjuvant therapy improved survival (de Boer ). However, because of the present retrospective study design, it is unknown if pN1mi(mol)(sn) patients show worse survival than pN0(mol)(sn) patients without adjuvant chemotherapy, or if pN1mi(mol)(sn) patients intrinsically show similar survival to pN0(mol)(sn) patients despite of adjuvant chemotherapy. Prospective studies are needed to elucidate the prognostic impact of pN1mi(mol)(sn) status. Using the pN(mol) classification, the SN status can be the most powerful predictive factor for determining both disease-free and cause-specific survival. After the American College of Surgeons Oncology Group Z-0011 randomised trial (Giuliano ), additional axillary dissection can be omitted for clinically node-negative patients who have one or two positive SNs and who are receiving adjuvant systemic chemotherapy and breast-conserving surgery with tangential irradiation (NCCN, 2016). Therefore, the pN(mol) classification of the SN status is useful to predict the prognosis of patients who omit additional axillary dissection after positive SN biopsy. However, the non-SN status in axillary dissection material was not a prognostic factor in the multivariate analysis. This may be because non-SN metastasis, especially macrometastasis, is strongly associated with the SN tumour burden, quantified using the OSNA assay (Osako ), and the pN(mol) classification of the SN status can be a cofounding factor for the association between non-SN status and prognosis. However, one study has shown that identifying tumour spread to non-SNs beyond SNs appears to be an important determinant of patient outcome, and is independent of the number of involved nodes (Jakub ). We have reported clinical research in which all of the SNs and non-SNs were evaluated by the OSNA whole-node assay without using any histopathological examination (Osako ; Osako ). Follow-up of this cohort may clarify the prognostic impact of the non-SN tumour burden and the total axillary metastatic burden. There are two potential limitations for the establishment of the pN(mol) classification. First, the present study did not directly compare the prognostic influence of the OSNA-based pN(mol) classification with the current histology-based AJCC pN classification. We found that the AJCC pN classification using the OSNA assay results was less significantly associated with prognosis than the pN(mol) classification. Retrospective or prospective studies are necessary for demonstrating the advantage of the pN(mol) classification over the histology-based AJCC pN classification. Second, we adapted the total copy number in the SN for the pN(mol) classification because several previous studies have reported that the total copy number in the SN determines non-SN metastasis (Peg ; Terrenato ). However, the maximum copy number in the SN (cutoff value of 2500 copies per μl) had a similar prognostic impact as the total copy number (unpublished data). The maximum copy number can possibly be used for the pN(mol) classification as a surrogate for the total copy number. In conclusion, a new molecular-based lymph node staging classification for breast cancer has been established using the prognostic cutoff value of the SN tumour burden, quantified using the OSNA assay. The SN status using the pN(mol) classification is the most powerful prognostic factor in early-stage breast cancer. The pN(mol) classification could more accurately and reproducibly determine the prognosis than the current pN classification, and may help to guide more precise therapeutic decision making for breast cancer patients.
  20 in total

1.  Metastasis detection in sentinel lymph nodes: comparison of a limited widely spaced (NSABP protocol B-32) and a comprehensive narrowly spaced paraffin block sectioning strategy.

Authors:  Donald L Weaver; Uyen Phuong Le; Stacey L Dupuis; Katherine A E Weaver; Seth P Harlow; Takamaru Ashikaga; David N Krag
Journal:  Am J Surg Pathol       Date:  2009-11       Impact factor: 6.394

2.  Role of total tumour load of sentinel lymph node on survival in early breast cancer patients.

Authors:  Vicente Peg; Irene Sansano; Begoña Vieites; Laia Bernet; Rafael Cano; Alicia Córdoba; Magdalena Sancho; María Dolores Martín; Felip Vilardell; Alicia Cazorla; Martín Espinosa-Bravo; José Manuel Pérez-García; Javier Cortés; Isabel T Rubio; Santiago Ramón Y Cajal
Journal:  Breast       Date:  2017-02-28       Impact factor: 4.380

3.  Axillary dissection vs no axillary dissection in women with invasive breast cancer and sentinel node metastasis: a randomized clinical trial.

Authors:  Armando E Giuliano; Kelly K Hunt; Karla V Ballman; Peter D Beitsch; Pat W Whitworth; Peter W Blumencranz; A Marilyn Leitch; Sukamal Saha; Linda M McCall; Monica Morrow
Journal:  JAMA       Date:  2011-02-09       Impact factor: 56.272

4.  Molecular detection of lymph node metastases in breast cancer patients: results of a multicenter trial using the one-step nucleic acid amplification assay.

Authors:  Yasuhiro Tamaki; Futoshi Akiyama; Takuji Iwase; Tomoyo Kaneko; Hitoshi Tsuda; Kazuhiko Sato; Shigeto Ueda; Masayuki Mano; Norikazu Masuda; Masashi Takeda; Masahiko Tsujimoto; Katsuhide Yoshidome; Hideo Inaji; Hiromu Nakajima; Yoshifumi Komoike; Tatsuki R Kataoka; Seigo Nakamura; Koyu Suzuki; Koichiro Tsugawa; Kenichi Wakasa; Tsuyoshi Okino; Yo Kato; Shinzaburo Noguchi; Nariaki Matsuura
Journal:  Clin Cancer Res       Date:  2009-04-07       Impact factor: 12.531

5.  Micrometastases or isolated tumor cells and the outcome of breast cancer.

Authors:  Maaike de Boer; Carolien H M van Deurzen; Jos A A M van Dijck; George F Borm; Paul J van Diest; Eddy M M Adang; Johan W R Nortier; Emiel J T Rutgers; Caroline Seynaeve; Marian B E Menke-Pluymers; Peter Bult; Vivianne C G Tjan-Heijnen
Journal:  N Engl J Med       Date:  2009-08-13       Impact factor: 91.245

6.  Sentinel node tumour burden quantified based on cytokeratin 19 mRNA copy number predicts non-sentinel node metastases in breast cancer: molecular whole-node analysis of all removed nodes.

Authors:  Tomo Osako; Takuji Iwase; Kiyomi Kimura; Rie Horii; Futoshi Akiyama
Journal:  Eur J Cancer       Date:  2012-12-19       Impact factor: 9.162

7.  One-step nucleic acid amplification for intraoperative detection of lymph node metastasis in breast cancer patients.

Authors:  Masahiko Tsujimoto; Kadzuki Nakabayashi; Katsuhide Yoshidome; Tomoyo Kaneko; Takuji Iwase; Futoshi Akiyama; Yo Kato; Hitoshi Tsuda; Shigeto Ueda; Kazuhiko Sato; Yasuhiro Tamaki; Shinzaburo Noguchi; Tatsuki R Kataoka; Hiromu Nakajima; Yoshifumi Komoike; Hideo Inaji; Koichiro Tsugawa; Koyu Suzuki; Seigo Nakamura; Motonari Daitoh; Yasuhiro Otomo; Nariaki Matsuura
Journal:  Clin Cancer Res       Date:  2007-08-15       Impact factor: 12.531

8.  Relation of number of positive axillary nodes to the prognosis of patients with primary breast cancer. An NSABP update.

Authors:  B Fisher; M Bauer; D L Wickerham; C K Redmond; E R Fisher; A B Cruz; R Foster; B Gardner; H Lerner; R Margolese
Journal:  Cancer       Date:  1983-11-01       Impact factor: 6.860

9.  Incidence and possible pathogenesis of sentinel node micrometastases in ductal carcinoma in situ of the breast detected using molecular whole lymph node assay.

Authors:  T Osako; T Iwase; K Kimura; K Masumura; R Horii; F Akiyama
Journal:  Br J Cancer       Date:  2012-05-08       Impact factor: 7.640

10.  A cut-off of 2150 cytokeratin 19 mRNA copy number in sentinel lymph node may be a powerful predictor of non-sentinel lymph node status in breast cancer patients.

Authors:  Irene Terrenato; Valerio D'Alicandro; Beatrice Casini; Letizia Perracchio; Francesca Rollo; Laura De Salvo; Simona Di Filippo; Franco Di Filippo; Edoardo Pescarmona; Marcello Maugeri-Saccà; Marcella Mottolese; Simonetta Buglioni
Journal:  PLoS One       Date:  2017-02-10       Impact factor: 3.240

View more
  9 in total

1.  Performance of a new system using a one-step nucleic acid amplification assay for detecting lymph node metastases in breast cancer.

Authors:  Kenzo Shimazu; Tomonori Tanei; Yasuhiro Tamaki; Toshiaki Saeki; Akihiko Osaki; Takahiro Hasebe; Yasuhiko Tomita; Motonari Daito; Mayuko Kobayashi; Shinzaburo Noguchi
Journal:  Med Oncol       Date:  2019-05-06       Impact factor: 3.064

2.  One-Step Nucleic Acid Amplification System in Comparison to the Intraoperative Frozen Section and Definitive Histological Examination Among Breast Cancer Patients: A Retrospective Survival Study.

Authors:  Serena Bertozzi; Ambrogio P Londero; Michela Bulfoni; Luca Seriau; Diane Agakiza; Alberto Pasqualucci; Michela Andretta; Maria Orsaria; Laura Mariuzzi; Carla Cedolini
Journal:  Front Oncol       Date:  2022-05-18       Impact factor: 5.738

3.  Elucidation of inhibitory effects on metastatic sentinel lymph nodes of breast cancer during One-Step Nucleic Acid Amplification.

Authors:  Yoshiya Horimoto; Masahiko Tanabe; Saiko Kazuno; Yoshiki Miura; Kaoru Mogushi; Hiroshi Sonoue; Atsushi Arakawa; Kazunori Kajino; Toshiyuki Kobayashi; Mitsue Saito
Journal:  Sci Rep       Date:  2018-05-15       Impact factor: 4.379

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

Authors:  Mizuho Abe; Naofumi Kagara; Tomohiro Miyake; Tomonori Tanei; Yasuto Naoi; Masafumi Shimoda; Kenzo Shimazu; Seung Jin Kim; Shinzaburo Noguchi
Journal:  Oncol Rep       Date:  2019-10-10       Impact factor: 3.906

5.  How Different Are the Molecular Mechanisms of Nodal and Distant Metastasis in Luminal A Breast Cancer?

Authors:  Petr Lapcik; Anna Pospisilova; Lucia Janacova; Peter Grell; Pavel Fabian; Pavel Bouchal
Journal:  Cancers (Basel)       Date:  2020-09-16       Impact factor: 6.639

6.  Detection of lymph node metastasis in non-small cell lung cancer using the new system of one-step nucleic acid amplification assay.

Authors:  Naoko Ose; Yukiyasu Takeuchi; Yasushi Sakamaki; Yoshihisa Kadota; Koji Urasaki; Hiromi Tsuji; Kunimitsu Kawahara; Mayuko Noguchi; Yasushi Shintani
Journal:  PLoS One       Date:  2022-03-21       Impact factor: 3.240

7.  A prediction model for early systemic recurrence in breast cancer using a molecular diagnostic analysis of sentinel lymph nodes: A large-scale, multicenter cohort study.

Authors:  Tomo Osako; Masaaki Matsuura; Daisuke Yotsumoto; Shin Takayama; Koji Kaneko; Mina Takahashi; Kenzo Shimazu; Katsuhide Yoshidome; Kazuya Kuraoka; Masayuki Itakura; Mayumi Tani; Takashi Ishikawa; Yasuyo Ohi; Takayuki Kinoshita; Nobuaki Sato; Masahiko Tsujimoto; Seigo Nakamura; Hitoshi Tsuda; Shinzaburo Noguchi; Futoshi Akiyama
Journal:  Cancer       Date:  2022-02-28       Impact factor: 6.921

8.  Prediction of tumor mutation burden in breast cancer based on the expression of ER, PR, HER-2, and Ki-67.

Authors:  Junnan Xu; Xiangyu Guo; Mingxi Jing; Tao Sun
Journal:  Onco Targets Ther       Date:  2018-04-19       Impact factor: 4.147

9.  Tumor Mutation Burden Prediction Model in Egyptian Breast Cancer patients based on Next Generation Sequencing.

Authors:  Auhood Nassar; Ahmed M Lymona; Mai M Lotfy; Amira Salah El-Din Youssef; Marwa Mohanad; Tamer M Manie; Mina M G Youssef; Iman G Farahat; Abdel-Rhaman N Zekri
Journal:  Asian Pac J Cancer Prev       Date:  2021-07-01
  9 in total

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