SIRPα and PD1 expression on tumor-associated macrophage predict prognosis of intrahepatic cholangiocarcinoma

RNA-seq was analyzed as our previously described [22‐24]. Briefly, the Limma package (version 3.40.2) of R software was used to study the differential expression of mRNAs [25]. The adjusted P-value was analyzed to correct for false positive results in TCGA or GTEx. “Adjusted P < 0.05 and Log2 (Fold Change) > 1 or Log2 (Fold Change) <  − 1” were defined as the thresholds for the screening of differential mRNA expression. To further confirm the underlying function of potential targets, the data was analyzed via functional enrichment. The Kyoto Encyclopedia of Genes and Genomes (KEGG) Enrichment Analysis is a practical resource for analytical study of gene functions and associated high-level genome functional information. To better understand the carcinogenesis of mRNA, the ClusterProfiler package (version: 3.18.0) in R was employed to analyze to enrich the KEGG pathway.

Thirty-six ICCs from TCGA datasets were included in this study. Overall survival time (OS) was compared between the high and low TAM-related markers by Kaplan–Meier analysis as previously described [26, 27]. The software is survival and survminer packages in R. The median was selected as the cutoff value for high or low TAM-related markers.

CIBERSORT, QUANTISEQ, and MCPCOUTER, which was used to analyze the immune cells infiltration in ICCs as previously described [28‐31]. The immunedeconv, an R package was implemented by R foundation for statistical computing (2020) version 4.0.3 and software packages ggplot2 and pheatmap. And these methods were used in the present study.

The sample consisted of 81 consecutive ICC patients who underwent curative resection from June 2, 2016 and December 30, 2019 at the affiliated cancer hospital of Zhengzhou University. This study was approved by the Ethics Committee at the affiliated cancer hospital of Zhengzhou University. All methods and procedures associated with this study were conducted in accordance with the Good Clinical Practice guidelines and accorded with the ethical principles of the Declaration of Helsinki as well as local laws. All enrolled patients were pathologically diagnosed with ICC and were not administered any anti-cancer treatments before surgery. After surgery, follow-ups were made on the patients to examine tumor status every 3 months for the first 2 years and every 6 months from year 3 to year 5. After 5 years, follow-ups were performed every year. The last follow-up took place on October 1, 2021.

Formalin-fixed and paraffin-embedded sections of intrahepatic cholangiocarcinoma tissue and paracancerous tissue (5 μm thick) were dewaxed and rehydrated. Antigen retrieval was performed by heating the slides in 10 mM Tris buffer with 1 mM EDTA (pH 9) in a streamer for 20 min. Inhibition of endogenous peroxidase activity was achieved by immersion in 3% H₂O₂ for 5 min. After washing with Tris-buffered saline (TBS) containing Tween, endogenous biotin was inhibited by sequential incubation with 0.1% anti-biotin protein and 0.01% biotin (Dako, Glostrup, Denmark), respectively, for 10 min at room temperature. Other non-specific binding sites were blocked with 3% skimmed milk powder for 30 min at room temperature. The tissue section of the intrahepatic cholangiocarcinoma tissue and paracancerous tissue were incubated with the monoclonal mouse antibody anti-human CD68 (Abcam, Clone# EPR20545, Cat# ab213363), SIRPα (Abcam, Clone# EPR22930-163, Cat# ab260039), PD1(Abcam, Clone# NAT105, Cat# ab52587), and SIGLEC10 (ThermoFisher, Cat# PA5-55,501) for one night at 4 ℃. Subsequently, the sections were serially rinsed and incubated with second antibodies. Immunohistochemical staining was evaluated independently by two experienced pathologists blinded to the patients’ clinical characteristics and outcomes. A histochemistry score (H-score) based on a combination of the percentage of positive stained cells and their staining intensity was calculated for the semiquantitative analysis as previously described [32‐34]. H-Score(H-SCORE = ∑percentage[0–100%] × intensity (1–3)) = (percentage of weak intensity cells × 1) + (percentage of moderate intensity cells × 2) + (percentage of strong intensity cells × 3).The median H-score was selected as the cutoff value for high or low CD68, SIRPα, PD1, and SIGLEC10 expression.

Follow-up and survival analysis of ICC Patients were consistent with previous studies [13, 35]. After surgery, the patients were checked regularly. In the first two years, follow-up evaluations were measured every 3 months. From 2 to 5 years after surgery, the follow-up tests of ICC patients were examined every 6 months. Beyond 5 years, the follow-up tests of ICC patients were measured every year. The follow-up tests included complete blood examinations, tumor biomarkers, and chest and abdominal computed tomography scans. If follow-up evaluations revealed metastatic disease and/or local recurrences, other therapies were applied, including conventional therapies (surgery, chemotherapy, and radiotherapy) as well as targeted and immunotherapy. Disease-free survival (DFS) was calculated from the date of surgery to the time of recurrence or metastasis, and patients who were alive and in a stable state were censored at the time of last contact [13, 35]. Overall survival (OS) was calculated using the date of surgery to the time of death, and patients who were alive at the time of last contact were censored [13, 35]. DFS and OS were calculated using the Kaplan–Meier analysis. The final follow-up was performed on October 1, 2021.

GraphPad Prism 9.0 software (GraphPad Software, Inc.) and SPSS® 24.0 software were used to perform the statistical analysis. Quantification of CD68, SIRPα, PD1, and SIGLEC10 density were analyzed via t-test. DFS and OS were calculated using the Kaplan–Meier estimator. Univariable and multivariable Cox proportional hazards regression models were used to estimate hazard ratios along with associated confidence intervals and p-values. Student’s t-test and chi-square (χ2) test were employed for inferential statistical analysis. For all data, P < 0.05 was used to indicate a statistically significant difference.

To begin this study, we first retrieved the transcriptome profiling data of ICC patients from the Cancer Genome Atlas (TCGA) database. Nine normal and 36 tumor samples were included. Next, the data was analyzed using R software to study the differential expression of mRNAs. A total of 16,897 genes were identified, and 10,196 were distinguished as differentially expressed mRNAs (DEmRNAs) (Fig. 1A), of which 9,371 were upregulated and 825 were downregulated (Fig. 1B). Enriched KEGG signaling pathways were selected to demonstrate the primary biological actions of major potential mRNA. The upregulated pathways potentially related to TAMs include lysome and endocytosis (Fig. 1C). The downregulated pathways potentially related to TAMs include the PPAR signaling pathway (Fig. 1D). These results suggested that TAMs may play a significant role in the progression of ICCs.

Next, we analyzed the characterization of the tumor-infiltrating immune cells (TIICs) signature in ICCs using three methods, CIBERSORT, QUANTISEQ, and MCPCOUTER as previously described [28‐31]. MCPCOUTER analysis demonstrated that macrophages/monocytes significantly increased in ICCs (Fig. 2A). CIBERSORT analysis showed increased infiltration of M0 macrophages in ICCs, and decreased infiltration of M2 macrophages in ICCs, while there was no significant difference in the infiltration of M1 macrophages (Fig. 2B). However, QUANTISEQ analysis indicated that both M1 and M2 macrophages significantly increased in ICCs (Fig. 2C). Then, we analyzed the expression of macrophage-related markers. CD68 is considered the gold standard marker of human total macrophages, and the expression of CD68 increases in ICC patients compared with normal controls, which is consistent with the TIICs analysis (Fig. 2D). We then analyzed the expression levels of M1 and M2 markers between normal and cancer tissues. Due to the increased scavenging capabilities of M2 macrophages, CD163, CD206, VCAM1, ARG1, IL-10, and CD204 have been proposed as markers of M2-type macrophages [36]. While M1 macrophages have been reported to have increased antigen processing, presentation, and killing properties. And IL-1β, iNOS, TNF, IL12A and B, CD80, CD83, and CD40 are considered typical markers of M1 macrophages [37]. When analyzing the expression levels of M1 markers between ICC and normal control, we found that iNOS, TNF, IL12A, and IL12B significantly increased, but IL-1β did not change (Fig. 2E). Furthermore, the M2 markers of CD163, IL10, and VCAM1 did not change between ICC patients and normal control. CD206 increased in ICC compared with normal control, but ARG1 decreased in ICC (Fig. 2F). Taken together, these findings suggest that M1 or M2 macrophages may not be a good biomarker to predict the progression of ICCs. Phagocytosis checkpoints, including PDCD1, LILRB1, SIGLEC10, and SIRPα are significantly for the function of TAMs in many cancers [14‐17]. Finally, we examined the expression of phagocytosis checkpoints expressed by TAMs. Notably, of these four phagocytosis checkpoints, the expression of PDCD1, SIGLEC10, and SIRPα significantly increased in ICC compared with normal control. However, there was no significant difference in LILRB1 expression (Fig. 2G).

We examined the prognostic impact of differentially expressed M1, M2 markers and phagocytosis checkpoints in cancer tissues in ICC patients from the Cancer Genome Atlas (TCGA) database. The Kaplan–Meier survival analysis and log-rank test were used to compare the survival rates between high expression (N = 18) and low expression (N = 18) groups of ICC patients. Interestingly, the Kaplan–Meier analysis indicated that patients exhibited a similar survival time based on the expression levels of iNOS, TNF, IL12A, IL12B, ARG1, CD206, CD68, SIRPα, PDCD1, and SIGLEC10 (Fig. 3A–C).

Given that the TCGA database had limited data on ICC patients, we sought to assess the role of “don’t eat me” molecules by using data from additional patients in China. A total of 81 patients between June 2, 2016 and December 30, 2019 were used in this study, including 47 (58.02%) males and 34 (41.98%) females. The median age was 61 years. All the patients received surgery. Prior to surgery, 20 (24.69%) patients had HBV infections, 10 (12.35%) patients had cirrhosis, and two patients had a history of hepatitis C infections. A total of 62 (78.48%) patients had elevated serum CA19-9, seven patients had elevated serum CEA (8.64%), and 55 (67.9%) patients had elevated serum CA724. Additionally, 69 patients had elevated serum total bilirubin, 72 patients had elevated serum direct bilirubin, and 49 patients had elevated serum indirect bilirubin. Moreover, 56 patients had elevated serum alanine transaminase (ALT), and 50 patients had elevated serum aspartate transaminase (AST). Finally, 14 patients were classified as Child–Pugh grade A, and 67 patients were Child–Pugh grade B.

Regarding tumors, all patients had a solitary tumor, and seven patients had larger tumors (> 5 cm). A total of 54 patients were TNM stage I or II, while 27 patients were TNM stage III. In addition, 54.32% of tumors had high to intermediate histopathological grading, and 45.68% of tumors had intermediate to low histopathological grading. In addition, 19.75% of patients had lymph node invasion, and 20.99% of patients had microvascular invasion. Patients’ detailed clinicopathologic characteristics are showed in Table 1.

To further confirm the expression pattern of SIRPα, PD1, and SIGLEC10 in TAMs in ICCs, 81 ICC tissues and 81 paracancerous tissues were obtained from our hospital. First, H&E staining was performed to prove that the tissues taken were indeed paracancerous and cancerous. Then, immunohistochemistry (IHC) was performed with anti-CD68, anti-SIRPα, anti-SIGLEC10, and anti-PD1 antibodies to detect the phagocytosis checkpoints expression pattern in ICCs. IHC images of representative CD68, SIRPα, SIGLEC10, and PD1 from cancerous and paraneoplastic tissues are shown in Fig. 4A, C, E and G, receptively. H-score was used to semi-quantify the expression of CD68, SIRPα, SIGLEC10, and PD1. Quantitative analysis indicated that the H-scores of CD68, SIRPα, and PD1 in cancerous tissues significantly increased compared with paraneoplastic tissues (Fig. 4B, D, F, H), but this was not the case for SIGLEC10. These results reveal that ICC patients may highly express SIRPα and PD1 on TAMs in cancerous tissues.

The expression levels of CD68, SIRPα, and PD1 are diverse in each sample of ICCs. The median H-score was selected as the cutoff value for high or low expression of CD68, SIRPα, and PD1. Based on the cut-off value of each molecule, we divided the ICCs into high expression (CD68^high, SIRPα^high, and PD1^high) and low expression subgroups (CD68^low, SIRPα^low, and PD1^low). It is worth noting that high CD68 expression as well as high SIRPα were positively correlated with high TNM stage, lymph node invasion, high Child–Pugh stage, microvascular invasion, and HBV infection (Tables 2, 3). Consistent with previous studies, high PD1 expression was positively correlated with high TNM stage, lymph node invasion, and HBV infection (Table 4).

The final follow-up occurred on October 1, 2021. Up to October 1, 2021, all the patients died. The 1-year and 5-year OS rates among the 81 patients were 51.85% (42/81) and 12.35% (10/81), respectively. The 1-year and 5-year cumulative recurrence rates were 44.44% (36/81) and 100% (81/81), respectively. CD68^high, PD1^high, and SIRPα^high ICCs had shorter DFS (Fig. 5A–C) and OS (Fig. 5D–F) than CD68^low, PD1^low, and SIRPα^low patients (P < 0.05). The significance of PD1 expression in T cells among ICC patients has been reported in previous studies [38].

We also analyzed the prognostic roles of high expression of both CD68 and PD1 in ICC patients. Interestingly, ICC patients with high expression of both CD68 and PD1 showed a poorer prognosis compared to patients with high expression of only CD68 or PD1 and patients with low expression of both CD68 and PD1 (Fig. 5G,  P < 0.05). Similarly, ICC patients with high expression of both CD68 and SIRPα showed a poorer prognosis than patients with high expression of only CD68 or SIRPα and patents with low expression of both CD68 and SIRPα (Fig. 5H,  P < 0.05).

Univariate analysis showed that high TNM stage, lymph node invasion, high Child–Pugh stage, microvascular invasion, and HBV infection were risk factors for DFS and OS (Table 5). Notably, CD68, PD1, and SIRPα in ICCs were also correlated with DFS and OS (Table 5).

These risk factors from the univariate analysis were adopted as covariates in a multivariate Cox proportional hazards model. High TNM stage, lymph node invasion, high Child–Pugh stage, microvascular invasion, HBV infection, CD68, PD1, and SIRPα were independent prognostic indicators for DFS and OS. Along with combined expression of CD68/PD1 and CD68/SIRPα, the hyperactivated phagocytosis checkpoints was also an independent prognostic predictor for both DFS and OS (Table 6).