Pan-Immune-Inflammation Value is a novel prognostic biomarker in advanced Gastric Cancer Patients

doi:10.21203/rs.3.rs-5235727/v1

Background: Advanced gastric cancer (GC) is a common malignancy with a poor prognosis, which remains the leading cause of cancer death worldwide. Identifying novel biomarkers is needed to predict survival for this highly progressive cancer. Many studies have confirmed that pan-immune-inflammation value (PIV) is related to the prognosis of various tumors in recent years. However, the prognostic value of PIV remains unclear in gastric cancer. The purpose of this study was to discuss the prognostic role of PIV in stage III and IV gastric cancer.

Methods: The clinical data of 646 patients with gastric cancer after gastrectomy were retrospectively analyzed. The calculation method of PIV is PIV=neutrophil count (10⁹/L) × platelet count (10⁹/L) × monocyte count (10⁹/L)/lymphocyte count (10⁹/L). Patients were divided into high and low PIV group by cut-off value based on receiver operating characteristic (ROC) curve. Effects of PIV and other IIB on survival were analyzed based on the ROC curves. Kaplan-Meier method was plotted to indicate the value of immune-inflammatory biomarkers (IIBs) in predicting the overall survival of gastric cancer. The overall survival (OS) in advanced gastric cancer patients were analyzed and univariate and multivariate statistics were used to evaluate the prognostic value.

Results: PIV had the most significantly predictive value in advanced GC patients compared with other peripheral blood parameters and IIBs. Cases in the high PIV group were more likely to have low serum albumin (Alb) level, larger tumor size compared with those in the low PIV group. PIV was identified an independent prognostic indicator for survival outcome in advanced GC patients in univariate and multivariate models.

Conclusions: This study confirmed that PIV can reflect the prognosis of advanced GC patients who have undergone gastrectomy, suggesting a potential application of PIV in GC treatment outcomes. Compared to other IIb indicators, PIV is more sensitive as a prognostic indicator. PIV will also provide some insight into the underlying mechanisms of immune and inflammatory effects in GC development and progression.

Trial registration: This study was a retrospective analysis, which has no intervention on human participants.

gastric cancer

pan-immune-inflammation value

prognosis

overall survival

prognosis

Gastric cancer (GC) is one of the most leading cause of cancer-related mortality worldwide and ranking as the third most common cancer in China[1]. Despite advances in diagnosis and treatment, GC remains an aggressive malignancy with poor prognosis[2]. In accordance with the guidelines of international oncology, perioperative chemoradiotherapy regimen is very important in patients with GC, including adjuvant and neoadjuvant treatment[3]. However, due to the clinical heterogeneous of GC, the response of patients who are received the standard therapy is variable. Approximately 50% of patients may not benefit from the treatment and eventually develop a risk of recurrence[4,5]. Therefore, it’s urgently needed to determine appropriate biomarkers for a better prognostic evaluation and prediction for treatment outcomes.

Inflammation and immunity are considered as cancer hallmarks and proved to play a crucial role in tumor development[6]. Recently, several immune-inflammatory markers have been evaluated to investigate their prognostic role in different cancers[7–9]. These markers are generally shown as chronic systemic inflammatory markers, which are calculated by some parameters obtained from circulating blood elements from peripheral blood specimens, such as lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), and etc[10]. However, since more evidence have elucidated the complex interplay among immunity, inflammation and cancer, using a composite biomarker that includes all the immune-inflammatory elements has been found to show a more obvious correlation with clinical outcomes in several cancers[11]. Of note, the pan-immune-inflammation value (PIV) combines all the inflammatory populations, including the platelets, monocytes, neutrophils, and lymphocytes, which is considered as a newer biomarker to obtain a more robust prognostic power[12].

However, the prognostic role of PIV in patients Who Receive Curative Gastrectomy during Perioperative Period of GC is rarely reported. Here we aimed to retrospectively review the characteristics of GC patients and investigate the potential role of PIV as a predictive biomarker in these patients who underwent curative gastrectomy during Perioperative Period.

Patient selection

In current retrospective study, 646 patients who underwent curative gastrectomy were included at the First and Second Affiliated Hospital of Harbin Medical University between December 2018 and October 2023. The inclusion criteria were as follows: (a) pathologically confirmed primary gastric adenocarcinoma; (b) stage III-IV according to the American Joint Committee on Cancer (AJCC) 8th edition [13]; (c) patients underwent D2 gastrectomy and. The exclusion criteria were as follows: (a) patients who suffered with hematological disorders; (b) patients who received immunomodulatory treatment; (c) patients treated with neoadjuvant chemotherapy or radiotherapy before operation. A total of 646 eligible patients were included in this study. All preoperative laboratory data were retrieved. This study was approved by the Ethics Committee of Second Affiliated Hospital of Harbin Medical University, and all patients had written informed consent.

Data collection

All medical and surgical records were retrospectively reviewed and clinicopathological data of participants were collected from the patients’ records including gender age, tumor size, T stage, N stage, M stage, TNM stage, tumor location, surgical approach, CEA, CA19-9, CA125, AFP, Alb. Divide gastric cancer into gastric body cancer, gastric fundus cancer, and gastric antral cancer by location. The number of blood cells in the blood routine including lymphocytes, neutrophils, monocytes, and platelets. The patient’s laboratory data were collected one week before surgery (at first diagnosis, before any treatment). For each patient, the pretreatment PIV was calculated using Fucà’s original formula[14]: PIV=neutrophil count (10⁹/L) × platelet count (10⁹/L) × monocyte count (10⁹/L)/lymphocyte count (10⁹/L). NLR=neutrophil count (10⁹/L)/lymphocyte count (10⁹/L); SII= [neutrophil count (10⁹/L) ×platelet count (10⁹/L)]/lymphocyte count (10⁹/L); PLR= platelet count (10⁹/L)/ lymphocyte count (10⁹/L); MLR= monocyte count (10⁹/L)/lymphocyte count (10⁹/L). Tumor staging is based on the American Joint Committee on Cancer (AJCC) 8th edition gastric cancer classification.

Statistical Analysis

ROC curve analysis was performed to determine the cut-off values for PIV, NLR, MLR, and PLR. Correlations between high or low PIV groups and clinicopathological features were analyzed using the c² or the Fisher's exact test when appropriate. Kaplan-Meier curves were used to visualize survival probabilities over time, the log-rank test was employed to compare survival curves between groups based on the indicator. The Cox regression analyses were conducted to evaluate the influence of clinic-pathological parameters on clinical survival outcomes. All statistical analyses were performed using SPSS 20.0 statistics software (IBM, USA). Statistical significance was defined as p < 0.05.

Patient Characteristics

A total of 646 patients with advanced stage III-IV gastric cancer who received Curative Gastrectomy during Perioperative Period were enrolled in this study, and the clinicopathological characteristics of the patients are shown in Table 1. Laparotomy was performed in 295 (45.7%) patients while the others received laparoscopic operation. Briefly, the patients age ranged from 23-89 years. Among all patients, there were 170 (26.3 %) females and 476 (73.7 %) males. 366(56.7%) patients with tumor size larger than 5cm. Of all 646 patients stage III 461(71.4%) and stage IV 185(28.6%), 112(17.3) patients without lymph node metastasis, 48(7.4%) patients with 1-2 lymph node metastases, 133(20.6%) patients with 3-6 lymph node metastases and 353(54.6%) patients with more than 6. 183(28.3%) patients had distant metastases.（Table 1）

Table 1. Clinicopathological characteristics of advanced GC patients

Characteristics		%
Characteristics	n=646	%
Gender
Male	476	73.7
Female	170	26.3
Age, y
23-60	248	38.4
61-89	398	61.6
Size
≤5	280	43.3
>5	366	56.7
TNM
3	461	71.4
4 N 0 1 2 3	185 112 48 133 353	28.6 17.3 7.4 20.6 54.6
M
0	463	71.7
1	183	28.3
Location
body of stomach	184	28.5
antrum of stomach fundus of stomach	402 60	62.2 9.3
Surgical Approach
laparotomy	295	45.7
laparoscopic	351	54.3

Comparison of prognosis between PIV and its components and other IIBs

Of all components including LYM(AUC=0.423) MON(AUC=0.632) PLT(AUC=0.636) and NEU(AUC=0.669), PIV(AUC=0.725) shows a better prognostic value (Fig 1a).

When compared with other IIBs (SII NLR PLR and MLR), PIV has the largest AUC (0.725), which shows advantage in predictive value over SII(AUC=0.714) NLR(AUC=0.672) PLR(AUC=0.664) and MLR(AUC=0.670) (Fig 1b).

Correlation between PIV and clinicopathological characteristics of advanced gastric cancer patients

There were statistically significant differences in tumor size. While analysis of our data shows that gender, age, location and TNM stage correlate little with PIV (p＞0.05, Table 2). Patients in the high PIV group were more likely to have larger tumor sizes than those in the low PIV group. (Table 2)

Table 2. Correlation between PIV and clinicopathological characteristics of advanced GC patients

Characteristics	Low PIV (n = 303)	High PIV (n = 343)	P-value
Gender
Male	229	247	0.304
Female	74	96
Age, y
≤ 60	117	131	0.912
> 60	186	212
Size
≤5	105	175	＜0.005
＞5	198	168
Location
body of stomach	85	99	0.912
antrum of stomach fundus of stomach	191 27	211 33
TNM
3	212	249	0.461
4	91	94
M
0	213	250	0.466
1	90	93
N
0	53	59	0.158
1	23	25
2	66	67
3 X	123 38	166 26

Pearson’s correlation coefficient showed that PIV was positively correlated with CEA (r = 0.468, p < 0.05), and CA19-9 (r = 0.137, p < 0.05), negatively correlated with Alb (r = −0.126, p < 0.05). However, PIV was not correlated with CA125 or AFP (r = 0.120, and −0.140; p > 0.05) (Table 3). In addition, cases in the high PIV group were more likely to have low Alb level, larger tumor size compared with those in the low PIV group.

Table 3. Pearson’s correlation coefficient

Variables

median(range)

r

p-value

CEA

2.39(0.2-1000)

0.468

＜0.05

CA19-9

CA125

AFP

Alb

12.46(0.6-1000)

15.31(1.87-1713)

2.32(0.5-1000)

36.5(14.4-51.6)

0.137

0.120

-0.140

-0.126

＜0.05

0.188

0.775

＜0.05

Kaplan-Meier curves of survival and subgroup analyses

The survival curves of GC are shown in Fig.2. The overall survival curve (38.9% vs. 78.4%, p < 0.01) was significantly worse in patients with high PIV than those in the low group. To better understand the effect of PIV prognosis between TNM3 and TNM4 stage, we performed subgroup analyses and confirmed the statistically significant differences between stage III(Fig.3a) and IV(Fig.3b) (TNM III: 48.6% vs. 92.4%, p＜0.01; TNM IV: 32.8% vs. 78.4%, p＜0.01).

As a result of univariate and multivariate analyses, PIV all appeared as an independent predictor in OS outcomes (Table 4). Besides, in multivariate analysis comprising the variables, tumor size and TNM stages caused a statistically significant difference in OS survival outcomes (Table 4). These results indicated that PIV was an independent value to predict survival in advanced GC patients.

Table 4. Univariate and Multivariate analysis of prognostic factors for overall survival in advanced GC patients

Covariate

Univariable

Multivariable

HR

(95%CI)

P-value

HR

(95%CI)

P-value

Age, y

Gender

Tumor size

TNM stage

Location

Surgical Approach

CEA

CA125

CA19-9

AFP

Alb

PIV

MLR

NLR

PLR

1.015

(0.791-1.302)

0.950

(0.721-1.252)

2.629

(1.990-3.472)

4.454

(3.482-5.697)

0.962

(0.783-1.182)

0.767

(0.600-0.979)

1.002

(1.001-1.003)

1.000

（0.999-1.001）

1.001

（1.001-1.002）

1.002

（1.000-1.003）

0.958

（0.937-0.978）

1.000

(1.000-1.001)

2.522

(2.147-2.962)

1.079

(1.065-1.093)

1.002

(1.001-1.003)

0.907

0.714

＜0.001

0.712

0.330

＜0.001

0.971

＜0.001

0.035

＜0.001

0.001

0.985

(0.502-1.933)

0.851

(0.402-1.801)

3.740

(1.725-8.108)

5.196

(2.538-10.638)

1.152

(0.703-1.888)

1.602

(0.769-3.338)

0.994

(0.989-0.998)

0.996

(0.992-1.001)

1.001

(1.000-1.003)

1.003

(1.000-1.005)

0.956

(0.894-1.022)

1.001

(1.000-1.001)

0.943

(0.348-2.557)

1.019

(0.925-1.122)

1.000

(0.997-1.003)

0.985

0.673

0.001

0.573

0.208

0.010

0.094

0.097

0.017

0.188

0.005

0.908

0.705

0.861

In the current retrospective study, we demonstrated a inflammation-based biomarker PIV, as an independent predictor for these GC patients for the first time. PIV was associated with several clinicopathological characteristics of GC and had an extensive influence on OS outcomes, suggesting that PIV might be useful for more accurate stratification and individualized treatment for GC patients receiving Curative Gastrectomy during Perioperative Period. When compared with other traditional IIB indicators, PIV has a more sensitive prognostic ability.

Since GC is a heterogeneous cancer with poor prognosis, it’s of great value to investigate a practical biomarker to find out the patients who can benefit from perioperative regimen for GC after curative gastrectomy. Inflammation plays an important role in various stages of tumor development[15]. In today's continuously advancing medical technology, accurate prediction of the condition of cancer patients has important clinical significance[16]. Compared with traditional IIB indicators, PIV, as a newly proposed inflammation indicator in 2020, has a guiding role in the prognosis of patients with metastatic colorectal cancer[17]. In subsequent studies, PIV has been confirmed to reflect the prognosis of various malignant tumors, including renal cell carcinoma, lung cancer, renal cell cancer, and prostate cancer[7–9,18,19].

The role of tumor microenvironment (TME) on tumor growth and progression have been well known in the last two decades, due to the complex interplay between large numbers of inflammatory or fibroblastic cells and tumor cells[20]. Previous studies have demonstrated that some immunological elements facilitate TME by producing pro-tumor cytokines and forming a dense tumor stroma[21]. In general, peripheral blood lymphocytes reflect the immune activation status and are responsible for antitumor-specific immune response[22]. However, circulating monocytes are sources of many immunosuppressive cells, including tumor-associated macrophages (TAMs) and myeloid-derived suppressor cells (MDSCs), which were associated with immunosuppression and tumor progression[23]. Additionally, neutrophils also make great contribution to tumor cell proliferation and migration by secreting cytokines, chemokines, and growth factors and inhibiting CD8⁺T lymphocyte-mediated antitumor activity[24]. Finally, platelets are other cells promoting cancer-favored microenvironment and correlating with tumor metastasis and adverse outcomes[25]. Therefore, systemic and local inflammation of solid cancers has shown a landscape and several systemic inflammatory response indicators have been researched for their prognostic value in cancer patients, especially in GC patients, who underwent a poor clinical outcomes even if receiving gastrectomy and perioperative chemoradiotherapy regimen[26,27]. In this regard, several blood-derived immune-inflammatory indexes which are easy-to obtain have been explored and shown significant prognostic usefulness, including LMR, NLR, MLR, and PLR indexes[28]. When compared with these common IIBs, our results suggested that PIV has the largest AUC, which was the best index for Inflammatory prognosis analysis.

In this research, we found that high PIV was connected with low Alb and large tumor size. We suspect that high PIV index indicate that patients are in a state of pro-tumor inflammation, in which the tumor volume grows and the body's consumption increases resulting in a decrease in serum protein. In the process of tumorigenesis, the balance of pro-tumor and anti-tumor effects always affects the occurrence and development of tumor, PIV can also be used as a tumor evaluation factor. By analyzing the data of stage III and IV gastric cancer patients, we found that the OS in the low PIV group was significantly higher than that in the high PIV group, which indicate an outstanding ability to judge patient outcomes.

Limitations of this study are as follows. As a single-center retrospective study, results may be biased, lack external validation, and may not be representative of the broader population. Although we take the patient's blood indicators before surgery, PIV alone is an indicator of inflammation, which is influenced by the patient's overall body state. This study demonstrated the effect of PIV on the prognosis of gastric cancer, but external experimental confirmation was lacking. Considering these problems, PIV as a prognostic indicator of gastric cancer still needs to be validated by more experiments.

AUC	Area Under Curves
GC	Gastric Cancer
MLR	Monocyte to Lymphocyte Ratio
IIB	Immune-inflammatory biomarker
NLR	Neutrophil to Lymphocyte Ratio
OS	Overall Survival
PIV	Pan Immune-inflammation Value
PLR	Platelet to Lymphocyte Ratio
TME	Tumor Microenvironment
MDSC LYM MON PLT NEU TAM	Myeloid-derived suppressor cells Lymphocyte Monocyte Platelet Neutrophil Tumor-associated macrophage

Ethics approval and consent to participate

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki. The studies involving human participants were reviewed and approved by YJSKY2023-157. This study was approved by the Ethics Committee of Second Affiliated Hospital of Harbin Medical University, and all patients had written informed consent.

Consent for publication

Not applicable

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Competing interests

The authors declare that they have no conflict of interest.

Funding

This work was supported by the Haiyan Foundation of Harbin Medical University Cancer Hospital under Grant No.JJZD2024-18, Harbin Medical University Cancer Hospital Top Young Talent Project under Grant No.BJQN2021-03

Authors’ contributions

WM: designed and analyzed data, and contributed writing; NX: designed and analyzed data, and contributed writing; WX, HY, LJ: analyzed data; WF: designed and supervised research, analyzed data, and wrote the paper.

Acknowledgements

Not applicable

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No competing interests reported.

Pan-Immune-Inflammation Value is a novel prognostic biomarker in advanced Gastric Cancer Patients

Status:

Version 1

Abstract

Figures

Background

Methods

Results

Discussion

Conclusions

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1