After excluding conjunctivitis, keratitis, dry eye and some other ocular inflammatory diseases, eighty-five patients (37 males and 48 females; average age, 46.3±9.1 years) whose primary pterygia were located in nasal sides were included in the study. All patients underwent excision by the bare sclera technique and combined with conjunctival transplantation in the Department of Ophthalmology at the Third Affiliated Hospital of Sun Yat-sen University. The head, neck and a part of body (approximate 3mm from limbus) of the pterygia were collected as pterygium samples. Twenty-three nasal-side epibulbar conjunctival segments (patients average age, 21±8.6 years, 10 males and 13 females) excised during strabismus surgery near the limbus, were used as control tissues. Forty-eight pterygia and eight epibulbar conjunctival tissues were used for quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). Fourteen pterygia and six epibulbar conjunctival tissue were used for immunohistochemistry. And twenty-three pterygia and nine epibulbar conjunctival tissue were used for immunofluorescence.
The grading and size of pterygia
Pterygia were defined as a radially oriented fibrovascular lesion crossing the nasal or temporal limbus [14, 15]. Grading of pterygia was performed as previous3,14. Briefly, Grade 1 denoted a pterygium in which episcleral vessels underlying the body of the pterygium were unobscured and with mild clinical signs of inflammation (conjunctival congestion and edema). Grade 2 was defined as vessels partially visible with moderate inflammation, and Grade 3 as vessels wholly obscured with severe signs of inflammation (Figure 1).
Total area was measured with computer software to circle the area of pterygia and circulated automatically. The extent of two intersecting points between pterygia and cornea was measured as the width of pterygia. And the horizontal extension from pterygia to cornea limbus was recognized as the extension of pterygia (millimeters).
The quantitative evaluation of general redness and blood vessels of pterygium
The degree of visible blood vessels in the pterygium and general redness were quantitatively analyzed by an automatic recognition program. The algorithm mainly adopted a traditional image processing method. Binarization contour extractions of pterygium images were implemented for obtaining the edge information of blood vessels. The HSV color model was used to extract the red pixels to obtain the hyperaemic regions. The interference information was eliminated by morphological method which was usually used for picture processing. By counting the number of pixels in the characteristic area and obtaining the area (unit: pixel), the proportion of blood vessels in the pterygium and general redness could be calculated respectively (Microsoft Visual C++, version 14.1, USA). What’s more, the composite result of general redness, and blood vessels of pterygium was considered as the average of those two proportion.
Quantitative real-time PCR
TRIzol (Invitrogen, United States) was used for total RNA extraction and purification. Reverse transcription into cDNA was performed with a reverse transcriptase kit (Fermentas, St. Leon-Rot, Germany) according to the manufacturer’s instructions. The primer sequences used for CCR7, C-C motif ligand 19 (CCL19), C-C motif ligand 21 (CCL21) and Human Tubulin Beta (TUBB) are listed in Table 1. The Quantitative real-time PCR was performed with the StepOne Real-Time PCR System (Applied Biosystems, Alameda, CA, USA) according to the manufacturer’s instructions. For the qRT-PCR analysis, the parameters consisted of predenaturation at 95°C for 60 seconds, followed by 40 cycles of denaturation at 95°C for 10 seconds, annealing, and extension at 60°C for 30 seconds. Then, a melt curve analysis was conducted to assess amplification specificity. Threshold cycle (CT) values were calculated for each well using the software of the real-time thermocycler. Gene expression and the fold change in gene expression were calculated using the ΔΔCt method. The ΔCt data were calculated using GAPDH as the housekeeping gene, and the fold change was calculated using the 2−ΔΔCt method. samples were used as controls and processed and analyzed separately using the same method.
Immunohistochemistry and Immunofluorescence
After being fixed in 4% paraformaldehyde for 24h, samples were embedded in paraffin, serially sectioned at a thickness of 5μm, and rehydrated with graded ethanol-water mixtures. These excised segments were washed by distilled water. Endogenous peroxidase activity was blocked by incubating the sections with 30 mL/L hydrogen peroxidase for 30 min. For antigen retrieval, these tissue sections were autoclaved at 121°C in 10 mmol/L citrate buffer (pH 6.0) for 5 min. Then, these sections were allowed to cool at room temperature for 30 min.
For immunohistochemistry, each sample was cut into 10 sections and each section was eight-micrometer. These sections were incubated overnight at 4°C with a mouse anti-human CCR7 antibody (1:100, Abcam PLC, Cambridge, UK), and a goat anti-mouse IgG antibody (1:500, Abcam PLC, Cambridge, UK) was used as the secondary antibody. These slides were incubated with diaminobenzidine (DAB) and counterstained with hematoxylin. The color of CCR7+ cells was brown after staining. Next, the sections were analyzed using standard light microscopy (Carl Zeiss, Oberkochen, Germany) under 200X and 400X magnification.
For immunofluorescence, these sections were double-stained and the following antibodies were used: a rabbit anti-human CCR7 antibody, a mouse anti-human MHCII (major histocompatibility complex class II) antibody, a mouse anti-human CD11c antibody, a goat anti-human CD11b antibody (1:100, Abcam PLC, Cambridge, UK) and a goat anti-human CCL21 antibody. Then, an Alexa Fluor 488-conjugated donkey anti-rabbit IgG antibody (1:500, Abcam PLC, Cambridge, UK) was used to detect the anti-CCR7 antibody. An Alexa Fluor 555-conjugated donkey anti-goat IgG antibody was used as the secondary antibody for the anti-CD11b and an Alexa Fluor 555-conjugated goat anti-mouse IgG antibody was used to detect staining with the anti-MHCII and anti-CD11c antibodies. Epifluorescence microscopy (Carl Zeiss, Oberkochen, Germany) was used for examination. Pictures of the same location in one section were taken in two excitation wavelengths under 400X magnification. Next, the two pictures were merged and if the proteins were located, it would show yellow.
Mann-Whitney and Bonferroni’s test were used to analyze differences in the PCR, results between the grades of pterygia and normal conjunctiva. Spearman’s analysis was used to analyze the association among CCR7, CCL19 and CCL21. Linear regression was used to analyze the association between CCR7 and the characters of pterygium, and between the proportion of blood vessels in the ocular surface and CCR7. Values are shown as the mean ± SD. All reported P-values are 2-tailed, and statistical significance was defined at the α=0.05 level. All analyses were performed using SPSS software (version 26.0; SPSS, Inc., Chicago, IL).