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.