Preliminary Exploration of the Relationship between Tumor Microenvironment in Malignant Ascites and Patient Prognosis

doi:10.21203/rs.3.rs-4680957/v1

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Preliminary Exploration of the Relationship between Tumor Microenvironment in Malignant Ascites and Patient Prognosis

https://doi.org/10.21203/rs.3.rs-4680957/v1

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Malignant ascites (MA) is a common complication of tumors which related to poor prognosis. With the deepening of the research on tumor microenvironment (TME), the influence of TME on prognosis is gradually understood. As a special TME, the relationship between MA and prognosis of patients need to be explored.

39 samples of MA in West China Hospital from 2018 to 2022 were collected for immunohistochemical (IHC) staining of CD4, CD8, CD11b, CD11c, CD16, CD19, CD163 and FOXP3. Through analyzing the relationship between the proportion of positive cells and the ascites-specific survival (ASS) of patients, immune cells infiltration score (ICIS) related to immune cell infiltration was established.

Based on Kruskal-Wallis H test, the expression of CD8 in MA of different tumor types was significantly different (P = 0.014), the proportion of CD8 positive cells in biliary tract tumors is significantly higher than that in gastrointestinal (GI) tract tumors (P = 0.032). According to the multivariate cox regression analysis, only whether to receive chemotherapy was an independent prognostic risk factor. ICIS 1 (CD4, CD8, CD163, FOXP3) and ICIS2 (CD4, CD8, CD11b, CD11c, CD16, CD19, CD163, FOXP3) constructed according to immune cell infiltration can effectively predict the ASS of patients (ICIS1: High expression vs low expression, HR, 0.43, 95%CI (0.22–0.84), P = 0.0065; ICIS2: high vs. low expression, HR, 0.36, 95%CI (0.16–0.79), P = 0.0007).

In general, the immune cells in MA are related to the survival of patients. The distribution model of immune cells based on TME has a good predictive value for the survival of patients.

Biological sciences/Cancer/Cancer microenvironment

Biological sciences/Cancer/Metastases

Biological sciences/Cancer/Tumour immunology

Malignant ascites

tumor microenvironment

immune cells

prediction model

MA accounts for about 10% of all ascites cases, usually caused by malignant abdominal tumors and associated with poor prognosis ¹. Ovarian cancer is the most common cause of MA, accounting for 37% of all cases with other common primary sites stomach, colon and pancreas ². The overall survival time of patients with MA is about 1–4 months. The survival time varies according to different primary sites, while patients with ovarian cancers and breast cancers have better prognosis ³.

The breakdown of the balance between the production and absorption of ascites is considered to be the main reason for MA appearance. Currently, it is believed that there are four reasons for this pathological process: 1) the production of vascular endothelial growth factor (VEGF) changes the vascular permeability; 2) tumor compresses portal vein and inferior vena cava, resulting in venous return obstruction; 3) tumor infiltrates lymphatic vessels leading to obstruction of return; 4) hypoproteinemia secondary to tumor leads to decreased colloid osmotic pressure^{1, 4}. At present, the treatment of MA is relatively limited. Traditional treatment methods includes abdominocentesis, diuretics, albumin supplementation, intraperitoneal infusion of chemotherapy drugs such as cisplatin and fluorouracil, or anti-angiogenic drugs such as bevacizumab, etc., however, these treatments have poor efficacy and many side effects such as infection, perforation and abdominal adhesion^{1, 5}.

TME is defined as the survival environment of tumor cells, which is composed of mesodermal cells, endothelial cells, immune cells, and non-cellular components such as cytokines, metabolites, exosomes, etc., which play important roles in the progression, invasion, immune escape, drug resistance and other characteristics of tumor cells⁶. Among them, immune cells is particularly important and the most widely studied. In TME, tumor cells can regulate the function of immune cells to form an immune-suppressed TME, which promote tumor survival and progression⁷. It is found that tumor infiltration lymphocyte (TIL), composed of T cells, B cells and natural killer cells (NK cells), is positively correlated with higher expression of immune checkpoints and better prognosis, and the number of infiltrated TILs gradually decreases during tumor progression^8–10. T cells are considered to be the most abundant immune cells in TME, which can be mainly divided into CD8 + T cells with cytotoxic effects and CD4 + T cells with antigen-presenting ability. In TME, activated CD8 + T cells kill cancer cells by secreting cytokines, such as granulocase, granulocin, perforin, Fas ligands, and tumor necrosis factor-α (TNF-α) ^11–14. CD4 + T helper cells (Th cells) can not only activate other immune cells, such as B cells and cytotoxic T cells, but also differentiate into a wide range of functional subsets, such as follicular helper T cell (Tfh cell) and T regulatory cell (Treg) ¹⁵. Treg, characterized by high expression of CD25 and FOXP3, plays an important role in maintaining tolerance to self-antigens and immune homeostasis via secreting transforming growth factor-β (TGF-β) and interferon-γ (IFN-γ) as well as direct cell-cell contact ^{16, 17}. Treg can also inhibit anti-tumor immunity and promote tumor progression to constitute immunosuppressive TME through inducing apoptosis of anti-tumor CD8 + T cells, producing interleukin-10 (IL-10) and inhibiting function of NK cells and Th17/Th1 transformation ^{18, 19}. NK cells are cytotoxic members of the innate lymphoid cell (ILC) family, mediating powerful anti-tumor effects ²⁰. Myeloid-derived suppressor cells (MDSC) have strong immunosuppressive effect in TME via inducible NO synthase (iNOS) and arginase (ARG)1, which hinder the proliferation of T cells and inhibit their normal function through the consumption of arginine^21–24. Meanwhile, MDSCs inhibit the function of Tregs and NK cells by secreting IL-10 and TGF-β ^25–28. In TME, Tumor-associated macrophages (TAM) mainly consist of two different subtypes, classically activated anti-tumor M1 macrophages and alternately activated pro-tumor M2 macrophages ^29–31. In the early stage of tumor, M1 macrophages are the main subtype, while after tumor formation, M2-type macrophages play a dominant role in TME ^{32, 33}. Dendritic cells (DC) are professional antigen presenting cells (APC) that play an important role in the triggering and expansion of anti-tumor immune response ^34–36. Many recent studies have shown that the increased expression of immunoreactive cells such as CD8 + cytotoxic T lymphocytes, activated CD4 + T lymphocytes, and CD16 + NK cells is positively correlated with survival time ^37–39. While immunosuppressive cells such as MDSC, CD163 + M2 TAM, CD11c + DC, Th2 cells, FOXP3 + Treg create inhibitory immune microenvironment for tumor progression ⁴⁰. In addition, there are still some cells such as B cells (CD19+) which remain to be studied.

In the process of tumor development, MA, a special tumor microenvironment, act as a bridge the process of metastasis ⁴¹. Tumor cells in MA exist in the form of single cells or multicellular spheres, in which multicellular spheres have an important effect on peritoneal dissemination due to expression of cadherin ⁴². Compared with the primary lesion or metastasis, samples of MA are easier to obtain and have less damage to patients. Currently, studies about the TME mainly focus on the primary lesion and metastasis. There are few studies on TME in MA, and its components and functions remain to be explored. In this study, IHC detection of immune cells in MA was performed to preliminarily explore the composition of immune cells and the relationship between them and the prognosis of patients. Our study will lay an important foundation for further research on the TME in MA.

Research participants

This study involved patients with MA at the West China Hospital from January 2018 to December 2022. The protocol for this study was approved by the Ethics Committees of Sichuan University and followed the guidelines of the Helsinki Declaration.

Data collection

Patients were followed up to August 2023. The survival status of patients were obtained using an outpatient system, inpatient records or telephone follow-up. Clinical and pathological data of those patients were collected and recorded. The data included pathological and histological type, differential degree of the primary tumor, among others. Clinical information, such as the anatomical site of the primary tumor, whether of the patients received surgery, chemotherapy, radiotherapy, peritoneal perfusion therapy were also recorded.

Immunohistochemistry

We selected MA samples from patients before treatment. Paraffin-embedded slides of cell mass specimens were stained and labeled. We use specific antibodies to label immune cells: anti-CD4⁺ T cells (Cell signaling technology, No. EP204), CD8⁺ T cells (Cell signaling technology, No. D8A8Y), CD11b⁺ M1-TAMs (Cell signaling technology, No. D6X1N), CD11c⁺ DCs (Cell signaling technology, No. D3V1E), CD16⁺ NK cells (Cell signaling technology, No. D1N9L), CD19⁺ B cells (Cell signaling technology, No. D4V4B), CD163⁺ M2-TAMs (Cell signaling technology, No. D6U1J) and FOXP3⁺ Tregs (Cell signaling technology, No. D2W8E). The slides were stained using hematoxylin.

Image acquisition and quantification

VS200 automatic full-slide scanner (Olympus) was used to scan the stained slides. The proportion of CD4⁺, CD8⁺, CD11b⁺, CD11c⁺, CD16⁺, CD19⁺, CD163⁺and FOXP3⁺ cells were identified by a qualified pathologist via averaging the results of 10 fields under high-power magnification (40×) using Qupath v0.5.0 software. The cutoff value of the proportion of positive cells for each immune cell subtype was calculated using the X-tile software V. 3.6.1. For ASS, the best cutoff values for high infiltration of CD4⁺, CD8⁺, CD11b⁺, CD11c⁺, CD16⁺, CD19⁺, CD163⁺and FOXP3⁺ immune cells were 13.2%, 10.8%, 42.3%, 41.5%, 44.2%, 27.5%, 74.8%, 0.7%, respectively. Each immune cell subtype was assigned a dichotomous score (high infiltration of CD4⁺, CD8⁺, CD11c⁺ and FOXP3⁺cells were scored 1, low density was scored 0; low infiltration density of CD11b⁺, CD16⁺, CD19⁺ and CD163⁺ was scored 1, high infiltration density was scored 0) based on the cutoff result. We established 2 scoring system, ICIS1 and ICIS2, based on infiltrated immune cells in MA. ICIS1 was calculated by CD4⁺, CD8⁺, CD163⁺and FOXP3⁺ immune cells and ICIS2 was calculated by CD4⁺, CD8⁺, CD11b⁺, CD11c⁺, CD16⁺, CD19⁺, CD163⁺and FOXP3⁺ immune cells.

Statistical analysis

ASS was defined as the period from the date of appearance of MA to the date of death. Rank-sum test was used to analyze the difference in infiltration density of immune cells in different subgroups. Cox regression analysis were used to determine independent prognostic factors affecting the ASS of patients. The prognostic utility of ICIS1 and ICIS2 was analyzed using Kaplan Meier curve. P < 0.05 was considered statistically significant. All statistical examinations were conducted using GraphPad Prism (version 10) and IBM SPSS software (version 20).

Basic characteristics of patients with MA

Overall, we recruited 68 patients with a mean age of 60 years old. Of these, 38 (55.88%) were female whereas 30 (44.12%) were male. There were 18 cases (46.1%) of gastric cancer, 7 cases (17.9%) of colorectal cancer, 3 cases (7.7%) of biliary tract cancer, 4 cases (10.3%) of ovarian cancer, 4 cases (10.3%) of fallopian tube cancer, and 3 cases (7.7%) of pancreatic cancer. The pathological type of 39 patients was adenocarcinoma, with 22 cases (56.4%) poorly differentiated, 9 cases (23.1%) moderately differentiated, and 8 cases (20.5%) well differentiated. The median ASS of 39 patients was 6 months, including 5 months for gastrointestinal cancer, 5 months for biliary tract cancer, 20 months for gynecological cancer, and 2 months for pancreatic cancer.

In addition to 5 patients who did not receive anti-tumor therapy due to advanced age and poor general condition, the remaining 33 patients received comprehensive anti-tumor therapy, including 18 patients who received radical surgery, 33 patients who received chemotherapy, 10 patients who received immunotherapy, 8 patients who received radiotherapy, 12 patients had been treated with antiangiogenic agents such as bevacizumab and apatinib, and 15 patients had been treated with intraperitoneal infusion. Among them, 12 gastric cancer patients received intraperitoneal infusion of paclitaxel, and the ascites was relieved. 3 patients with gastric cancer received intraperitoneal infusion of bevacizumab. 1 patient with colon cancer received intraperitoneal infusion of fluorouracil, and 2 patients with pancreatic cancer received intraperitoneal infusion of cisplatin. These clinicopathological characteristics were summarized in Table 1.

Table 1

Clinicopathological characteristics of patients
Variables	No(%)
Gender
Female	16(41%)
Male	23(59%)
Age
< 65	23(59%)
≥ 65	16(41%)
Primary site
Stomach	18(46.1%)
Colorectum	7(17.9%)
Biliary duct	3(7.7%)
Ovary	4(10.3%)
Fallopian tube	4(10.3%)
Pancreas	3(7.7%)
Degree of differentiation
High	8(20.5%)
Medium	9(23.1%)
Low	22(56.4%)
Treatment
Surgery	18(46.2%)
Chemotherapy	First-line 12(30.8%)
	Second-line 14(35.9%)
	Third-line and above 7(17.9%)
Immunotherapy	10(25.6%)
Radiotherapy	8(20.5%)
Antiangiogenic therapy	12(30.8%)
Peritoneal perfusion	15(38.5%)

Infiltrating density of immune cells

The median percentages of CD4, CD8, CD11b, CD11c, CD16, CD19, CD163 and FOXP3 positive cells were 13.22% (interquartile range, IR 2.30%-24.80%), 8.26% (IR 3.19%-11.76%) and 51.41% (IR 37.38%), 56.87% (IR 34.37%-81.06%), 47.86% (IR 21.49%-68.22%), 13.31% (IR 2.38%-26.10%), 54.43% (IR 41.60%-66.98%), 2.52% (IR 1.10%-4.47%), respectively (Fig. 1). The proportions of positive immune cells of 39 patients were demonstrated in Fig. 2.

Factors related to prognosis

According to rank-sum test, age (P = 0.017), primary site (P = 0.039) and the infiltration level of CD4 (P = 0.047), CD163 (P = 0.02) and FOXP3 (P = 0.022) were significant for prognosis. However, gender (P = 0.071), differentiation degree (P = 0.083) and the infiltration level of CD8 (P = 0.172), CD11b (P = 0.325), CD11c (P = 0.112), CD16 (P = 0.112), CD19 (P = 0.123) were not statistically different.

Factors related to infiltrating density

The percentages of CD4 (P = 0.582), CD8 (P = 0.291), CD11b (P = 0.194), CD11c (P = 0.587), CD16 (P = 0.08), CD19 (P = 0.085), CD163 (P = 0.17) and FOXP3 (P = 0.487) positive cells have no statistical difference between subgroups with diverse differentiation degree (Fig. 3A). Meanwhile, there were no significant differences in the percentages of CD4 (P = 0.93), CD11b (P = 0.294), CD11c (P = 0.609), CD16 (P = 0.13), CD19 (P = 0.187), CD163 (P = 0.431) and FOXP3 (P = 0.394) positive cells in subgroups with different primary sites. The proportion of CD8 positive cells in patients with different tumor sites was significantly different (P = 0.014), with that in biliary tract tumors significantly higher than that in digestive tract tumors (P = 0.032) (Fig. 3B).

Univariate and multivariate analysis of prognostic factors

According to univariate analysis of clinicopathological factors, infiltrating density of positive immune cells, ICIS1 and ICIS2 revealed that gender (female vs male, HR, 0.448, 95%CI (0.221–0.908), P = 0.026), age (≥ 65vs < 65, HR, 2.436, 95%CI (1.213–4.892), P = 0.012), primary site (biliary vs digestive tract, HR, 1.812, 95% CI (0.526–6.246), gynecological system vs digestive tract, HR, 0.163, 95% CI (0.047–0.565), pancreas vs digestive tract, HR, 1.953, 95% CI (0.574–6.653), P = 0.014), CD4 (high vs low, HR, 0.409, 95% CI (0.199–0.841), P = 0.015), CD8 (high vs low, HR, 0.405, 95% CI (0.183–0.898), P = 0.026), CD163 (high vs low, HR, 2.757, 95% CI (1.111–6.845), P = 0.029), FOXP3 (high vs low, HR, 0.357, 95% CI (0.159–0.806), P = 0.013), whether to receive treatment (treated vs untreated, HR, 0.196, 95% CI (0.065–0.584), P = 0.003) and chemotherapy (treated vs untreated, HR, 0.159, 95% CI (0.055–0.462), P = 0.001), ICIS1 (high vs low, HR, 0.388, 95% CI (0.185–0.811), P = 0.012) and ICIS2 (high vs low, HR, 0.32, 95% CI (0.154–0.661), P = 0.002) were significant prognostic factors. The degree of differentiation, the proportion of CD11c, CD11b, CD16, CD19 positive cells, whether to receive surgery, radiotherapy, anti-vascular therapy, immunotherapy, intraperitoneal perfusion therapy, etc., had no statistical significance for ASS.

As such only gender, age, primary site, CD4, CD8, CD163, FOXP3, whether to receive treatment and chemotherapy, ICIS1 and ICIS2 were included in multivariate cox analysis. Except whether to receive chemotherapy (treated vs untreated, HR, 0.025, 95% CI (0.001–0.058), P = 0.016), none of the other factors indicated independent predictive value for ASS (Table 2).

Table 2

Univariate and multivariate cox analysis
	Univariate Cox			Multivariate Cox
	HR	(95%CI)	P	HR	(95%CI)	P
Gender
Female vs Male	0.448	0.221–0.908	0.026	0.834	0.3-2.321	0.728
Age
≥ 65vs < 65	2.436	1.213–4.892	0.012	1.087	0.393–3.008	0.873
Primary site
Biliary tube vs GI tract	1.812	0.526–6.246	0.014	2.704	0.313–23.39	0.165
Gynecology vs GI tract	0.163	0.047–0.565		0.282	0.026–2.223
Pancreas vs GI tract	1.953	0.574–6.653		3.458	0.602–19.866
Differentiation degree
Medium vs High	2.716	0.871–8.466	0.062
Low vs High	3.365	1.227–9.227	0.062
CD4
High vs Low	0.409	0.199–0.841	0.015	0.612	0.083–4.501	0.63
CD8
High vs Low	0.405	0.183–0.898	0.026	0.951	0.144–6.293	0.959
CD11b
High vs Low	1.311	0.651–2.64	0.449
CD11c
High vs Low	0.537	0.263–1.096	0.087
CD16
High vs Low	1.918	0.955–3.856	0.067
CD19
High vs Low	2.266	0.91–5.642	0.079
CD163
High vs Low	2.757	1.111–6.845	0.029	3.268	0.52-20.599	0.207
FOXP3
High vs Low	0.357	0.159–0.806	0.013	0.413	0.107–11.602	0.201
Treatment
Treated vs Untreated	0.196	0.065–0.584	0.003	3.95	0.29652.689	0.299
Surgery
Treated vs Untreated	0.539	0.265–1.095	0.087
Chemotherapy
Treated vs Untreated	0.159	0.055–0.462	0.001	0.025	0.001–0.058	0.016
First-line vs Untreated	0.068	0.018–0.256	0.001	1.245	0.279–5.555	0.781
Second-line vs Untreated	0.252	0.084–0.757		1.576	0.434–5.727
Third-line and above vs Untreated	0.123	0.034–0.453		1.487	0.688–3.499
Immunotherapy
Treated vs Untreated	1.169	0.556–2.455	0.68
Anti-angiogenic agent
Treated vs Untreated	1.122	0.546–2.305	0.754
Radiotherapy
Treated vs Untreated	1.589	0.708–3.566	0.261
Peritoneal infusion
Treated vs Untreated	1.567	0.78–3.148	0.207
ICIS1
High vs Low	0.388	0.185–0.811	0.012	1.692	0.178-16. 088	0.647
ICIS2
High vs Low	0.32	0.154–0.661	0.002	0.942	0.261–3.399	0.927

Kaplan-Meier analysis

Kaplan-Meier survival curves were shown according to ICIS1 and ICIS2 (Fig. 4). In ICIS1, the median ASS of the high expression group and the low expression group were 10 months and 4.5 months, respectively. In ICIS2, the median ASS of the high expression group and the low expression group is 10 months and 3 months, respectively. ICIS1 and ICIS2 both predicted the survival time of patients well (ICISl 1: high vs low, HR,0.43, 95%CI(0.22–0.84),P = 0.0065; ICIS2: high vs low, HR,0.36, 95%CI(0.16–0.79),P = 0.0007).

According to the results of IHC detection of immune cells in MA, ICIS1 based on CD4, CD8, CD11b, CD163 and FOXP3 and ICIS2 based on CD4, CD8, CD11b, CD11c, CD16, CD19, CD163 and FOXP3 were constructed. Both models can predict the survival of patients well. Due to the existence of multiple subtypes of immune cells which have complex functions, previous studies that examined the relationship between common antigens and prognosis often showed divergent results. Compared with other studies, our study used a variety of antibodies to label different subtypes of immune cells, which can better reflect the interaction of diverse immune cells in TME. Due to the tissue characteristics of ascites, this study chooses to calculate the proportion of positive cells as the IHC results, which can better reflect the infiltration density of immune cells in MA. Meanwhile, compared with the traditional image J software, Qupath software has a simpler operating system, which avoid many steps of manual judgment, and reduces the subjective deviation. However, the software calculation process is not fully automated, it cannot completely avoid the confusion of subjective factors. At the same time, due to the long storage time of ascites samples, there is a certain possibility of false negative results. Because of the small size of total sample and the unbalanced composition among different tumor subgroups, the results of cox univariate analysis with no statistical difference, such as CD11c, CD11c, CD16 and CD19, were still included in ICIS2. The good predictive ability of ICIS1 and ICIS2 for ASS indicates the promising potential.

CD4 + T cells, CD8 + T cells and FOXP3 + Treg cells are important components of TILs. A study in triple-negative breast cancer also showed that high levels of tumor infiltration of CD4 + T cells and CD8 + T cells were associated with better disease-free survival and overall survival ^[51].Another study of CD4 expression in tumor lesions of 178 patients with non-small cell lung cancer showed that the increase of CD4 + T cells in tumor stroma was positively correlated with prognosis ^[50]. studies targeting FOXP3 + Treg cells also suggests that high FOXP3 expression is associated with good prognosis ^{[52, 53]}. In addition, many studies have shown that CD163 + M2 TAM invasion in tumor lesions indicates poor prognosis of patients ^[54–56]. The above conclusions were consistent with our results that high expression of CD4, CD8 and FOXP3 was associated with good prognosis, while CD163 was associated with poor prognosis. CD11b is a surface receptor mainly expressed on the surface of bone marrow-derived cells, including monocytes, macrophages, neutrophils, etc. CD11b is commonly used to assist to detetermine M1-type TAM, and increased iNOS + and CD11b + M1 effector TAM are associated with better anti-tumor responses ^[57]. At the same time, CD11b agonist can be used as a new therapeutic target to play an anti-tumor role by activating anti-tumor immune response ^{[58, 59]}. CD11c is commonly used to label DC cells. A study on the expression level of CD11c in 140 gastric cancer patients showed that high expression of CD11c was associated with longer progression-free survival and overall survival ^[60]. In addition, another study showed that the expression of CD11c was positively correlated with the expression of CD4 and CD8 in triple-negative breast cancer, which indirectly verified the immune activation effect of DC cells ^[61]. CD16 is a marker of NK cells, and high expression of CD16 in ovarian cancer is associated with longer survival time and higher chemotherapy sensitivity ^{[62, 63]}. CD19 is expressed in all B cells except a small proportion of plasma cells, and CD19 is widely used in the treatment of B-cell associated lymphoma and leukemia. However, there are few B-cell related studies in solid tumors, and a study on triple-negative breast cancer suggested that high expression of CD19 may be associated with better prognosis ^[64]. However, there was no statistical difference in the expression of CD11c, CD11b, CD16 and CD19 in our study, which may be related to the small sample size.

Recently, the study of TME is becoming more and more accurate. Some studies compared the difference of immune cells between the tumor bed center and the infiltrating edge to understand the role of immune cells in the process of tumor progression ^{[64, 67, 68]}. A study of 251 patients with gastric cancer showed that low CD8 expression at the invasive margin and high FOXP3 expression at the tumor center were associated with worse survival ^[69]. In addition, studies on the TME of metastasis have also shown good prognostic value. For example, the detection of CD3, CD8, CD20, and CD163 in colorectal cancer liver metastases and peritoneal metastases can predict the survival of patients effectively ^{[70, 71]}. However, there are few studies on the special TME, such as MA, which may be related to the low utilization of ascites specimens at present. This study not only revealed the proportion of immune cells in MA by IHC staining, but also demonstrated the value of ascites research.

In this study, the ascites samples of 39 patients were examined by immune-cell-related IHC test (CD4, CD8, CD11b, CD11c, CD16, CD19, CD163, FOXP3). Through the analysis of the relationship between the proportion of positive cells and the prognosis of patients, we found some clinicopathological factors related to ASS and establish two models that predict ASS well. At present, the research on MA is still at the preliminary stage, and needs to be further studied. To fully explore the prognostic value of MA, larger multicenter studies should be conducted to cover a wider range of sample size. At the same time, more detection indicators need to be further explored to reveal the principle of TME in MA affecting prognosis.

Acknowledgments

The authors gratefully acknowledge Li Li, Fei Chen, Chunjyan Bao and Yang Deng from the Institute of Clinical Pathology, West China Hospital, Sichuan University for processing immunohistological staining.

Declaration of interest statement

The authors report there are no competing interests to declare

Data availability statement

The datasets used in this study are available from the corresponding author upon request.

Informed consent statement

Informed consent was obtained from all subjects and/or their legal guardian(s).

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Preliminary Exploration of the Relationship between Tumor Microenvironment in Malignant Ascites and Patient Prognosis

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Abstract

Figures

Introduction

Materials and methods

Research participants

Data collection

Immunohistochemistry

Image acquisition and quantification

Statistical analysis

Results

Basic characteristics of patients with MA

Infiltrating density of immune cells

Factors related to prognosis

Factors related to infiltrating density

Univariate and multivariate analysis of prognostic factors

Kaplan-Meier analysis

Discussion

Conclusion

Declarations

References

Additional Declarations

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