Introduction
Cervical cancer (CC) is one of the leading malignant tumors in United States [1,2]. Lymph node (LN) metastasis have been considered as a vital factor in the development of CC [3-6]. Patients with this stage IB1-IIA2 CC (2009 International Federation of Gynecology and Obstetrics (FIGO) stage) will undergo pelvic LN (pLN) resection [7] and cause a variety of complications, including bleeding, nerve injury, lower pelvic lymphocele and extremity lymphedema [8,9] [10,11]. Thus, it will be particularly important to further study the mechanism of CC pLN metastasis. Furthermore, preoperative assessment of pLN status in CC patients is therefore critical for clinical decision making.
Increasing evidence has demonstrated that pLN metastasis is a complex process involving tumor immune milieu [12-15]. However, molecular mechanisms behind metastasis processes remain obscure. Traditional procedures have been used to elucidate the mechanism by regularly exploring molecular pathways [14,16,17]. However, due to the tissue-destructive nature of most of these methods, the spatial distribution and temporal distribution of immune milieu in situ will not be preserved [18]. Although morphological examination including conventional immunohistochemistry (IHC) or immunofluorescence (IF) can reveal some information, its effect is extremity limited because of high inter-observer variability and the capacity to label only one marker per tissue section [19].
Multiplex immunohistochemistry / immunofluorescence (m-IHC/IF) has emerged and provides high-throughput multiplex staining and further standardized quantitative analysis for highly efficient, reproducible and cost-effective tissue studies [19-21]. It can show up to seven targets simultaneously on a single slide. Afterwards, HALO (Indica Labs, Albuquerque, USA), an image analysis system not only can be used for quantitative tissue analysis, but also can reveal the spatial location of each target [22-26].
In the current study, we sought to comprehensively compare the quantification of immune markers and their spatial orientation interrelation between CC in situ tissue with positive pLN and negative pLN. Based on differential expression of immune-related indicators, a clinical prediction model was constructed for individual preoperative prediction of pLN metastasis and an internal validation was assessed. In the future, we can predict pLN metastasis by cervical biopsy, thus avoiding its dissection and improving patients’ quality of life.