Background
Axillary lymph node dissection (ALND) was introduced as a standard surgical procedure for breast cancer in the 1800s and played a significant role in patients’ staging, prognosis assessment, regional disease control, and treatment direction [
1,
2]. However, with the aid of new screening methods, more early stage patients with no invasion of axillary lymph nodes (ALN) have been able to be identified in recent years. For these patients, instead of reducing the incidence of recurrence or improving survival, ALND was found to be associated with increased risk of adverse effects such as lymphedema, limited mobility, neuropathic pain, numbness, and sensory loss [
3‐
5]. To solve this dilemma, sentinel lymph node biopsy (SLNB), a less invasive surgery with equivalent clinical value, was developed and has readily become a routine surgery in early breast cancer patients [
6,
7].
As the first site of tumor cell infiltration via lymphatic vessels, sentinel lymph nodes (SLN) with no detectable metastasis are seen as safety indicator, thus, making ALND unnecessary. On the other hand, if SLN is positive for metastasis, ALND is still recommended to clarify the status of the remaining non-sentinel lymph nodes (NSLNs) in the axilla [
8,
9]. Nevertheless, it was reported that 40–70 % of SLN positive patients were actually free of metastasis in their NSLNs [
10,
11]. In order to avoid the over-treatment suffering brought about by ALND, it has become imperative for breast cancer surgeons to find effective methods that can distinguish SLN positive patients with low probability of NSLN invasion from those with high probability of NSLN invasion.
Among these methods, predictive models based on retrospective analysis of patients’ clinical characteristics (e.g., age, histological type, tumor size, lymphovascular invasion, and hormone receptor status), such as the nomogram of Memorial Sloan-Kettering Cancer Center [
12] and the scoring systems of MD Anderson [
13], Tenon [
14], Cambridge [
15], and Stanford [
16], were the most frequently mentioned ones. However, the routine clinical practice and patient characteristics varied among different hospitals, thereby, greatly influencing the accuracy, consistency, and repeatability of these models and hampering their extensive application. On the other hand, it was hypothesize that tumor with specific gene expression or fusion may have more invasive behavior and thus possess with higher possibility of metastasis in lymph node. Therefore, some scientists were dedicated to search for biomarkers that can predict NSLN status [
17‐
23], but until recently, the available choices remained limited and their practical value still needed additional verification.
In present study, next-generation RNA sequencing (RNA-Seq) was utilized to compare gene expression level differences for breast cancer metastasized to the SLN between patients with and without NSLN invasion. To our knowledge, it is the first time that NSLN prediction markers were screened according to gene expression profiling of the SLN metastasis. Although further validation is required in the future, these markers could broaden our understanding of the mechanisms of breast cancer metastasis to the lymph nodes and might provide assistance in decision making when choosing appropriate surgery strategies for SLN positive breast cancer patients.
Discussion
Because of growing evidence for its benefits and its minor side effects in patients, SLNB has readily replaced ALND and has become the routine procedure for surgical axillary staging in early breast cancer patients [
6,
7]. For SLN negative patients, it is now widely accepted that ALND can be omitted [
8,
9]. Because 40–70 % of SLN positive patients were reported to be free of metastasis in their NSLN, ALND in these patients remains controversial [
10,
11]. In order to avoid the physical discomfort and potential complications associated with ALND in these patients, an effective method to predict the status of NSLN has become the urgent demand for breast surgeon. In contrast to the existing predictive models that are based on retrospective analysis of patients’ clinical characteristics [
12‐
16], molecular tests may hold significant promise because they are more objective, more standardized, and easier to popularize [
17‐
23]. Unfortunately, currently available markers remain limited and their practical value still needs additional verification.
Recently, the utilization of RNA-Seq in breast cancer has illustrated its power in revealing the variation landscape of the breast transcriptome and in finding regulatory interactions among cancer-related molecules [
29,
30]. As a powerful next-generation sequencing technology, RNA-Seq can profile a full set of transcripts including mRNAs, small RNAs, and other non-coding RNAs qualitatively and quantitatively, providing a snapshot of gene expression patterns and regulatory elements in a cell, tissue, or organism. Compared with microarrays, RNA-Seq possesses the advantages of being high-throughput, cost effective, and of having superior accuracy. In addition, without relying on prior sequence information, RNA-Seq can profile gene expression based on the entire transcript (not a few segments). It can also identify novel isoforms and exons, allele-specific expression, mutations, and fusion transcripts [
31]. These advantages make it ideal for studying complex diseases, particularly cancer. Despite its growing application in breast cancer, to the best of our knowledge, the present study is the first one using RNA sequencing to screen for potential markers predicting NSLN status in patients with metastatic SLN.
The major function and most distinctive feature of RNA-Seq is measuring gene expression variance, which captures the genetic differences among patients. The most interesting observation in our study is that four KLK subfamily members (
KLK10,
KLK11,
KLK12, and
KLK13) were up-regulated in the NSLN positive group, suggesting their potential role in lymph node metastasis. The KLK gene family includes 15 highly conserved secreted serine proteases with similar structural characteristics, whose dysregulation was reported to be closely associated with endocrine-related cancer, such as prostate, breast, and ovarian cancers [
32]. Although previous studies have demonstrated the crucial role of
KLK10 and
KLK11 in breast cancer patients’ relapse, disease progression and shorter survival rates [
32,
33], a potential role for the KLK gene family in lymph node metastasis was first proposed in the present study. More studies are required to further confirm these results.
On the other hand, for the down-regulated genes in the NSLN positive group, B cell antigen receptor (BCR) signaling pathway, including some B cell surface molecules (CD22, CD72, Igα, Igβ, CD19, and CD21) and a few downstream regulated genes (
SYK,
LYN,
BTK, and
PTPN6), may be worthy of further attention. It is known that the BCR signal pathway is vital for the development and survival of B lymphocytes and that defective BCR signaling can result not only in impaired B cell development and immunodeficiency but also in a predisposition to autoimmunity [
34]. Although the BCR signaling pathway was previously reported to play significant roles in chronic lymphocytic leukemia [
35], this is the first time that it is linked with NSLN metastasis in breast cancer.
In contrast to the down- and up- regulated genes, the presence of specifically expressed genes and fusion genes may be more useful to the breast cancer surgeon, because they are relatively easier to analyze and their detection could be carried out during surgery, thereby, facilitating the implementation of appropriate surgery strategies for breast cancer patients in a timelier manner. For specifically expressed genes, two protein-coding genes,
FABP1 and
CYP2A13 which were expressed in the NSLN negative and positive groups, respectively, were worthy of further investigation.
FABP1 was reported to correlate with non-alcoholic fatty liver disease [
36], and
CYP2A13 was found to be involved in the development and progression of lung adenocarcinoma [
37]; however, neither of them was previously associated with NSLN metastasis. For fusion genes, the most frequently seen in the NSLN positive group was
IGLL5, which was identified as one of the best predictors for relapse-free survival with >85 % accuracy in breast cancer patients [
38]. This observation suggests that those rearrangements occurring in
IGLL5 might be linked to the process of metastasis.
As a well-known biomarker for cell proliferation, Ki-67 plays a significant role in prognosis prediction [
39] and has been routinely used in the subtyping of breast cancer [
28]. However, we could not screen enough patients in the NSLN negative group using the recommended cut-off of 14 % [
28]. Taking into consideration that such a cut-off was arbitrarily determined and still needed further confirmation, we broadened the requirement to 20 %. Even so, only six patients were finally screened, which may inevitably influence the strength of our results. Therefore, further verification in subsequent studies is required. Moreover, other subtypes of breast cancer (such as HER2 positive) were not evaluated in the present study and may need additional investigation, since their intrinsic metastatic mechanism may be completely different.
Lastly, we should note that predicting NSLN status with molecular biomarkers is based on the hypothesis that tumor with specific gene expression or fusion may have more invasive behavior and thus possess with higher possibility of metastasis in lymph node. However, specific gene expression or fusion in SLN does not necessarily mean the invasion of NSLN and that merely represents some kind of possibility. Therefore, as regards for the practical value of the biomarkers that screened in present study, additional verification should be warranted in the future.
Competing interests
The authors declare that they have no competing interests.
Authors’ contributions
FL analyzed the patients’ clinical data and collected the SLN samples. HQ analyzed the sequencing data and drafted the manuscript. QL collected the SLN samples and participated in RNA extraction. YY participated in data alignment and uploaded the raw data. XR constructed the cDNA library for sequencing. BZ drew the line delineating tumor position on the reverse side of each slide. YL drafted the manuscript. CY, HZ, XF, and XH participated in the design and coordination of the study. All authors have read and approved the final manuscript.