Back to Journals » Cancer Management and Research » Volume 12

The Prognostic Value of Inflammation Factors in Hepatocellular Carcinoma Patients with Hepatic Artery Interventional Treatments: A Retrospective Study

Authors Guo L, Ren H, Pu L, Zhu X, Liu Y, Ma X 

Received 12 April 2020

Accepted for publication 26 June 2020

Published 13 August 2020 Volume 2020:12 Pages 7173—7188


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Chien-Feng Li

Linghong Guo,1,2,* Honghong Ren,2,* Lutong Pu,2 Xingyu Zhu,2 Yin Liu,1,3,4 Xuelei Ma1

1Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 2West China School of Medicine, Sichuan University, Chengdu, People’s Republic of China; 3Department of Pharmacology, West China School of Basic Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, People’s Republic of China; 4Department of Anesthesiology, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Xuelei Ma
Department of Biotherapy, Cancer Center West China Hospital, Sichuan University, No. 37, Guoxue Alley, Chengdu, Sichuan 610041, People’s Republic of China
Tel/ Fax +86-28-85475576
Email [email protected]

Background: Hepatic artery interventional therapy has been recognized as the first choice for advanced liver cancer. However, reliable prognostic markers are still lacking. In the present study, we aimed to evaluate the prognostic value of inflammation factors including neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR) and monocyte to lymphocyte ratio (MLR) in hepatocellular carcinoma (HCC) patients with hepatic artery interventional treatments.
Methods: Patients undergoing hepatic artery interventional therapy after being diagnosed with HCC between 2007 and 2014 were enrolled. Pre-treatment NLR, PLR and MLR were calculated, and all factors including gender, age, TNM stage, BCLC staging, inflammation factors, LDH, ALP, CEA, AFP, hepatitis, liver cirrhosis, portal vein involvement, surgical history and hepatic artery interventional treatment on overall survival (OS) were evaluated by the univariate and multivariate Cox proportional hazards analyses.
Results: Overall, 407 patients were included. The optimal cutoff values determined by receiver operating characteristic (ROC) curve analyses for NLR, PLR and MLR were 3.82, 140.00 and 0.27, respectively. High NLR was associated with worse OS (median survival time: high NLR group 9 vs low NLR group 19 months, HR 1.842, 95% CI: 1.457– 2.329, P< 0.001). Elevated PLR was negatively correlated with OS (8 vs 18 months, HR 1.677, 95% CI: 1.302– 2.161, P< 0.001). Patients in high MLR group had a worse OS (10 vs 21 months, HR 1.626, 95% CI: 1.291– 2.048, P< 0.001). In multivariate analysis, NLR, LDH, ALP and portal vein involvement were independent prognostic factors for OS of HCC patients after hepatic artery interventional therapy. In addition, for patients in BCLC stage A and B, higher NLR, PLR and MLR were all significantly negatively correlated to median survival time (NLR: 17 vs 26 months, HR: 1.739 (95% CI: 1.279– 2.365), P< 0.001; PLR: 18 vs 26 months, HR: 1.681 (95% CI: 1.245– 2.271), P=0.001; MLR: 20 vs 26 months, HR: 1.589 (95% CI: 1.185– 2.129), P=0.002).
Conclusion: Elevated pre-treatment NLR, PLR and MLR were associated with worse survival time in HCC patients after hepatic artery interventional therapy. Among them, NLR was an independent prognostic factor for OS.

Keywords: hepatocellular carcinoma, neutrophils, platelets, lymphocytes, inflammation, prognosis


Hepatocellular carcinoma (HCC) is the most common type of primary liver malignancy with high mortality.1 According to a report of cancer statistics in China, there were 0.365 million newly diagnosed HCC and 0.319 million patients dying from HCC every year. Another study revealed that 50.5% of emerging HCC patients in the world were Chinese.2 Primary hepatectomy can be a potential curative treatment for HCC patients; however, according to current practice guidelines for the management of HCC, it is limited to patients harboring early-stage tumors and patients without portal hypertension or increased bilirubin levels.3,4 This has made hepatic artery interventional therapies including transcatheter arterial embolization (TAE), transcatheter arterial infusion (TAI) and transcatheter arterial chemoembolization (TACE) become important treatment options for patients with heavy disease burden.5 However, since interventional therapies are accompanied by repeated ischemic injury to liver parenchyma and adverse events, post-embolization survival outcomes remain poor.6,7 Therefore, it is urgent to establish the prognostic factors to better stratify patients who are likely to benefit from the treatments.

Currently, several clinical factors including tumor markers and portal vein involvement have been proposed for diagnostic, prognostic or monitoring use in liver cancer. Among them, α-fetoprotein (AFP) was most studied. AFP was usually used for early detection of HCC in patients with cirrhosis or chronic hepatitis.8 Post-treatment monitoring with AFP in HCC patients is also recommended.9 A Japanese survey showed that AFP concentration, portal and hepatic vein involvement were independent prognostic factors for HCC patients undergoing liver resection.10 However, these factors have not been validated in HCC patients undergoing hepatic artery interventional therapy and there are few studies exploring prognostic factors for HCC patients undergoing hepatic artery interventional therapy.11 Recent studies have reported the role of chronic inflammation in cancer progression.12 Cancer-related inflammation affects tumor proliferation by promoting angiogenesis and secreting different growth factors.13 HCC can develop on a background of inflammation. Previous studies have confirmed the underlying impact of repeated hepatitis virus infection on the development of HCC.14 Therefore, the systematic inflammatory state might serve as a surrogate marker of tumor clinical pathology in HCC patients. Neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) are calculated as the absolute count of neutrophil (platelet) divided by the absolute count of lymphocytes. As the reflection of systemic inflammatory response, NLR and PLR have been widely investigated as new prognostic indicators to evaluate the survival outcomes in many cancers, including gastric cancer and non-small cell lung cancer.15,16 Recently, the prognostic significance of NLR and PLR as predictive biomarkers for patients affected by HCC undergoing transcatheter arterial chemoembolization (TACE) has also been reported.17 Results of this study manifested that high PLR and NLR were correlated with poor prognosis in recurrent hepatocellular carcinoma patients treated with TACE. However, the sample size was quite small, and therefore the conclusion needs to be further tested. In addition, the monocyte-lymphocyte ratio (MLR) has been reported to be a prognostic factor for various cancers including colon cancer, lymphoma and nasopharyngeal carcinoma.1821 But few studies are investigating the prognostic effect of MLR on HCC patients underwent hepatic artery interventional therapy.

In this study, we retrospectively analyzed a large sample of patients to investigate the prognostic roles of NLR, PLR, MLR and other potential prognostic factors in HCC patients who had undergone interventional treatments.

Patients and Methods

Patients and Data Recording

In this retrospective study, patients between the ages of 18 and 75 who were pathologically diagnosed with primary hepatocellular carcinoma (HCC) and underwent hepatic artery interventional therapy at West China Hospital from September 2007 to July 2014 were included. Exclusion criteria were diagnosis with cholangiocarcinoma, mixed hepatocarcinomatous or secondary HCC, active infection during the time of blood sample preparation, severe coagulation disorders, serious hemorrhage, receiving any medication that might seriously infected inflammatory markers or loss of regular follow-up. The last follow-up was on September 29, 2018. A total of 407 patients were eventually included in the study. Hepatic artery interventional therapy of enrolled patients included transcatheter arterial embolization (TAE), transcatheter arterial infusion (TAI) and transcatheter arterial chemoembolization (TACE). Our study was approved by the Medical Ethics Committee of West China Hospital, Sichuan University, and all the patients signed informed consent.

Latest clinical and laboratory data within 1 week prior to hepatic artery interventional therapy of enrolled patients were obtained from electronic medical records. Specifically, we extracted patient characteristics including age, sex, diagnoses, pathology reports, imaging result, treatment, TNM stage, Barcelona Clinic Liver Cancer Staging (BCLC staging), infectious status of viral hepatitis B and C, liver cirrhosis, portal vein involvement, alkaline phosphatase (ALP), carcinoembryonic antigen (CEA), lactate dehydrogenase (LDH), AFP, neutrophil count, lymphocyte count, monocyte count and platelet count. NLR was defined as the ratio of neutrophil count to lymphocyte count. PLR was defined as the ratio of platelet count to lymphocyte count. MLR was defined as the ratio of monocyte count to lymphocyte count. The primary endpoint in our study was overall survival time.

Definition of Procedures

Transcatheter arterial chemoembolization (TACE) involves selective insertion of a catheter into the tumor’s target blood supply artery, and injection of an appropriate amount of embolic particles coated with chemotherapeutic drugs, thus occluding the target artery of tumor tissues and inducing cytotoxicity.22 It is mostly used for the treatment of liver cancer, including primary or metastatic liver cancer and postoperative recurrence of liver cancer.23

Transcatheter arterial infusion (TAI) involves catheter-based delivery of chemotherapeutic drugs to improve the local drug concentration and reduce the systemic reaction, suitable for the treatment of cancer patients who cannot be resected or undergo palliative resection.24,25

Transcatheter arterial embolization (TAE) is performed by injecting various embolization agents into the artery to block the arterial blood supply of the tumor.23 It is mostly used for liver cancer that cannot be surgically removed and is also used for liver diseases such as hepatic hemangioma, hepatic arteriovenous fistula, etc.23,26

Statistical Analysis

Data analyses were performed on SPSS 21.0. The Pearson Chi-squared test was used to compare categorical variables. Receiver operating characteristic (ROC) curve analyses were conducted to determine the optimal cutoff values of NLR, PLR and MLR. Survival curves were estimated by Kaplan-Meier method and differences between groups were determined by the Log rank test. Univariate analysis and multivariate cox regression analysis were performed to assess potential prognostic factors. Multivariate cox regression analysis was performed with the forward LR (forward stepwise regression based on maximum likelihood estimation) method. To further clarify the role of NLR, PLR and MLR in HCC patients without macrovascular invasion and/or extrahepatic disease, we separately performed univariate analysis and multivariate cox regression analysis based on the BCLC classification. All tests were two-sided, and a p-value less than 0.05 was considered as statistically significant.


The Optimal Cutoff Values for NLR, PLR and MLR

The optimal cutoff values of NLR, PLR and MLR were determined by ROC analysis on the basis of maximum joint sensitivity and specificity. According to ROC curves, the area under the curves (AUC) for NLR, PLR and MLR was 0.601 (95% CI: 0.546–0.656, P<0.001), 0.654 (95% CI: 0.601–0.706, P<0.001) and 0.622 (95% CI: 0.568–0.676, P<0.001). The optimal cutoff values were 3.82 for NLR, 140.00 PLR and 0.27 for MLR by ROC curves analysis (Figure 1).

Figure 1 Receiver operating characteristic (ROC) curves for pretreatment NLR, PLR, and MLR for predicting prognosis in HCC patients after interventional treatments. (A) Receiver operating characteristic (ROC) curves for pretreatment NLR. (B) Receiver operating characteristic (ROC) curves for pretreatment PLR. (C) Receiver operating characteristic (ROC) curves for pretreatment MLR.

Characteristics of Patients

A total of 407 patients were included with a median age of 55 (range: 18–75). Flowchart of patients’ selection is shown in Figure 2. The vast majority of patients were male (85.5%, 348/407) while female patients accounted for 14.5% (59/407). Forty-six patients (11.3%) were at T1 stage, 117 patients (28.7%) were at T2 stage, 229 patients (56.3%) were at T3 stage and 15 patients (3.7%) were at T4 stage. About N staging, 294 (72.2%) patients were at N0 stage, and 113 (27.8%) patients were at N1 stage. Concerning M staging, 89.4% (364/407) of patients were in M0 stage, and 43 (10.6%) patients were in M1 stage. According to the BCLC staging, the same number of patients were at stage A (131, 32.2%) and stage B (131, 32.2%). And 143 (35.1%) patients were at stage C while only 2 (0.5%) patients were at stage D. Regarding surgical history, 177 (43.5%) patients underwent surgery before hepatic artery interventional treatment and 230 (56.5%) patients did not have surgery before. In addition, detailed information about hepatic artery interventional therapies of enrolled patients was summarized. More than half of patients underwent TACE treatment (223/407), and about forty percent of patients had TAI therapy (180/407), while only 4 patients had TAE treatment.

Figure 2 Flowchart of patients’ inclusion and exclusion.

High NLR group consisted of 133 (32.7%) patients while 274 (67.3%) patients were in NLR<3.82 group. Our study revealed that NLR was significantly associated with T stage (P=0.002), M stage (P=0.017), BCLC staging (P=0.005), LDH (<0.001), ALP (<0.001), CEA (0.036) and hepatic artery interventional treatment (p=0.019).

Ninety-eight (24.1%) patients were in PLR140.00 group and 309 (75.9%) patients were in PLR<140.00 group. PLR was associated with T stage (P=0.012), BCLC staging (P=0.045), LDH (P<0.001) and ALP (P<0.001).

There were 225 patients (55.3%) in MLR0.27 group and 182 (44.7%) patients were in MLR<0.27 group. MLR had a close connection with N stage (P=0.019), M stage (P=0.019), BCLC staging (P=0.002), LDH (P<0.001), ALP (P<0.001) and CEA (P=0.007).

The correlations between NLR, PLR, MLR and clinical features of HCC patients are shown in Table 1.

Table 1 Correlation Between Peripheral NLR, PLR, MLR, and Clinical Variables of HCC Patients

Prognostic Factors of HCC Patients

The univariate cox proportional hazards analysis showed that age, TNM stages, BCLC staging, NLR, PLR, MLR, LDH, ALP, CEA, AFP and portal vein involvement had a strong connection with the survival outcomes of HCC patients who had undergone hepatic artery interventional therapy (Table 2). The median survival time of patients in NLR3.82 group was 9 months, while the patients in NLR < 3.82 group had a median survival time of 19 months (HR 1.842, 95% CI: 1.457–2.329, P<0.001) (Figure 3A). Comparing with patients in low PLR group, patients in PLR140.00 group appeared to have shorter median survival time (8 months vs 18 months) with hazard ratio being 1.677 (95% CI: 1.302–2.161, P<0.001) (Figure 3B). Patients in MLR0.27 group had a median survival time of 10 months compared to 21 months of patients in MLR < 0.27 group (HR 1.626, 95% CI: 1.291–2.048, P<0.001) (Figure 3C). Our multivariate analysis showed that NLR (P=0.013), LDH (P=0.001), ALP (p=0.017) and portal vein involvement (P<0.001) were independent prognostic factors for survival of HCC patients, while PLR and MLR were revealed not to have independent prognostic values for those patients’ survival (Table 3).

Table 2 Univariate Analysis Estimating the Prognostic Factors for HCC

Table 3 Prognostic Factors for OS as Determined by Multivariate Analysis

Figure 3 Kaplan–Meier survival curves for overall survival (OS) in HCC patients after interventional treatments. (A) OS of patients with NLR3.82 was shorter than those with NLR < 3.82 (p < 0.001, log-rank). (B) OS of patients with PLR140.00 was shorter than those with PLR < 140.00 (p < 0.001, log-rank). (C) OS of patients with MLR Table 1 Correlation between peripheral NLR, PLR, MLR, and clinical variables of hepatic cancer patients.

Analysis of Patients Without Macrovascular Invasion and/or Extrahepatic Disease

A total of 262 HCC patients in BCLC stages A or B were included for the analysis (Table 4). The univariate cox proportional hazards analysis showed that age, NLR, PLR, MLR, LDH, and ALP were significantly associated with the survival outcomes (Table 5). Patients with higher NLR, PLR and MLR were all significantly negatively correlated to median survival time (NLR: 17 vs 26 months, HR: 1.739 (95% CI: 1.279–2.365), P<0.001; PLR: 18 vs 26 months, HR: 1.681 (95% CI: 1.245–2.271), P=0.001; MLR: 20 vs 26 months, HR: 1.589 (95% CI: 1.185–2.129), P=0.002). Multivariate analysis revealed that PLR and LDH were significant prognostic factors for overall survival (Table 6).

Table 4 Correlation Between Peripheral NLR, PLR, MLR, and Clinical Variables of HCC Patients in BCLC Stages A and B

Table 5 Univariate Analysis Estimating the Prognostic Factors for HCC Patients in BCLC Stages A and B

Table 6 Prognostic Factors for OS in HCC Patients with BCLC Stages A and B as Determined by Multivariate Analysis


Inflammation is a protective process from further tissue damage caused by physical, biological or chemical factors.27 It is a complicated reaction which involves many different kinds of immune cells and chemicals released by them.28 But once the acute protective procedure cannot get rid of the etiology, it will develop into chronic inflammation which might develop into cancer.29 Many studies have reported the possible connection, which could predict the prognosis of cancer, between chronic inflammation and oncogenesis.30,31 HCC is also regarded as developing from chronically damaged liver tissue which contains a lot of inflammation cells, and those cells promote the tumorigenesis and tolerance to therapy.32

Recently, an increasing number of studies have focused on the role of NLR and PLR in predicting prognosis of HCC patients after interventional treatment.33,34 However, their study involved a small number of patients and usually included only a single type of hepatic artery interventional therapy.35 In addition, few studies have investigated the prognostic value of MLR in HCC patients. To the best of our knowledge, the present retrospective analysis is the first study to systematically evaluate the prognostic value of NLR, PLR and MLR based on 407 HCC patients after hepatic artery interventional therapy.

Neutrophils, the first cells to assemble at the site of inflammation, not only work as protector of our body, but also play an important role in tumorigenesis.36 Previous studies showed that neutrophils in the tumor microenvironment produce MMP9 (gelatinase B), and this molecule has been proved to promote the angiogenesis, progression, and metastasis of tumor in mouse transplantation models.3739 Reactive oxygen species (ROS) derived from neutrophil participates in cell death pathway during inflammation. However, once ROS fails to destroy cells, it causes direct gene damage which contributes to tumor initiation.40 In addition, neutrophils release neutrophil elastase (NE) by cell degranulation to stimulate inflammation reaction and attack invading organisms.41 NE has been reported to have many protumor effects.42,43 A recent study proved that NE stimulates tumor cell proliferation through phosphatidylinositol 3-kinase (PI-3K) pathway.44 Neutrophils also contribute to tumor cell migration by reducing the expression of cell surface E-cadherin.45 Chen et al demonstrated that neutrophils could be chemotactically confined by IL-8 and substances secreted by tumor cells, which leads to spatially localized tumor cell arrest. However, this process helps adjacent tumor cells extravasate and migrate.46 In HCC, hepatocyte growth factor (HGF) secreted by neutrophils in the liver stimulates cancer cells proliferation through the c-Met pathway.47 In contrast to the pro-tumor effect of neutrophil, lymphocyte work by attacking tumors through differentiating into tumor-specific CD8+ cytotoxic T cell.48 Schumacher K et al also found that the intratumor CD8+ T cell infiltration was an independent positive prognostic factor of esophageal carcinomas.49 Therefore, high NLR might reflect the imbalance in immune response to tumor cells and suggest a relatively worse prognosis as compared with low NLR. In our study, we found patients in high NLR group (NLR3.82) had worse median survival time than those in low NLR group (9 months vs 19 months, P < 0.001). Furthermore, our multivariate analysis showed NLR3.82 was an independent prognostic factor of worse OS (Table 3). Recently, Zhou et al found high NLR value was a predictor of poor prognosis for patients undergoing TACE with unresectable HBV-related HCC,50 which is consistent with our result.

Platelets have already been reported to take part in various stages of cancer progression and using antiplatelet doses of aspirin has been confirmed to prevent cancer migration and poor prognosis.51 One theory is that platelets help tumor cells avoid immune elimination in many ways including secreting TGF-β and platelet-derived growth factor (PDGF) to inhibit NK cell from killing tumor cells, conjugating with fibrinogen and forming a network to prevent tumor cells from interacting with NK cells, and upregulating glucocorticoid-induced TNF-related ligand (GITRL) to suppress cytotoxicity function of NK cells.52,53 Another opinion is that platelets have a significant effect on angiogenesis in the cancer development process by releasing VEGF and other angiogenic cytokines.54 In a word, high PLR might be associated with severe tumor progression and represent poor prognosis for cancer patients. Our results revealed a manifest worse median OS time in high PLR group (≥140) than that in low PLR group (8 months vs 18 months, p<0.001). The multivariate analysis showed that PLR140 was not an independent prognostic indicator of worse OS in HCC patients.

After being recruited into inflammation tissue, monocytes differentiate into two macrophage phenotypes including M1 macrophages and M2 macrophages. Among them, M2 has been reported to stimulate tumor progression.48 Chitinase 3-like protein 1 (CHI3L 1), secreted by M2 macrophage, upregulates the expression of matrix metalloproteinase genes and promotes the metastasis of gastric and breast cancer by activating interleukin-13 receptor α2 (IL-13Rα2).49 In cervical cancer, macrophages were shown to be associated with cancer invasion progress by secreting vascular endothelial growth factor (VEGF) to stimulate angiogenesis.55 In prostate cancer, Soki, Fabiana N. et al demonstrated a decreased bone marrow tumor growth by inducing macrophage apoptosis.56 In addition to pro-tumor functions, macrophages also suppress the anti-tumor function of CD4+ T cell by direct cell–cell interaction. Meanwhile, they can secrete some molecules such as TGF-β and Arg-1, which inhibit the proliferation of T cell.57 Thus, it has been speculated that MLR which represents the relative counts of monocytes and lymphocytes can be a potential negatively correlated prognostic marker for tumors. In the present study, patients with elevated MLR (≥0.27) had significant worse median OS time than patients in low MLR group (10 months vs 21 months, p <0.001), which was in consistence with the finding in the previous study that MLR had a negative correlation with OS of HCC patients after radical resection.58 Notably, our result revealed that MLR was not an independent prognostic factor of survival in HCC patients after hepatic artery interventional therapy.

Several studies have reported that increased circulating inflammatory cell counts, including neutrophil and monocyte, were associated with advanced tumor stage, while lymphocyte counts being inversely related.59 As indicators of systematic inflammation status, neutrophil and monocyte were reported to have participated in tumor cell proliferation and migration, tumor progression and metastasis.60 However, lymphocyte plays a key role in anti-tumor reaction, and lymphocyte cell counts reflect immune response status. Therefore, the levels of NLR, PLR and MLR could indicate the severity of aggressive tumor at certain degree. In our study, patients with higher NLR, PLR, MLR values tend to be diagnosed with more advanced tumor stages and BCLC stages, which were consistent with the results of previous studies.61

A great challenge for the future and also a limitation of our study is to explore recognized demarcation standards of inflammation indexes for clinical use. Moreover, the AUC values for ROC curves were relatively low (between 0.6 and 0.7). However, the predictive models constructed in our study were based on a relatively large sample size, which made our results more reliable. In addition, it is not of great clinical significance to explain the role of a model solely by its AUC value. Therefore, our univariate and multivariate COX regression analysis further identified the significant predictive role of NLR, PLR and MLR. Furthermore, more studies are needed to further investigate the prognostic role of MLR in HCC patients after hepatic artery interventional therapy. Finally, our study was restricted to Chinese Han population, which may not be a good representative for other ethnic groups.


In conclusion, our research was conducted based on a large sample of HCC patients who had undergone hepatic artery interventional therapy and investigated the prognostic roles of pretreatment NLR, PLR, and MLR. The present study confirmed the results of previous studies that high NLR and PLR were associated with poor survival. In addition, MLR was negatively correlated with survival in HCC patients after hepatic artery interventional therapy. Among them, only NLR was an independent index for predicting the prognosis. These inflammation markers are readily available and may help in making clinical decisions. On the basis of the results of our study and previous researches, clinicians can use inflammatory indicators to predict the prognosis of patients before treatment and combine other conditions to determine the best scheme for patients.


NLR, neutrophil to lymphocyte ratio; PLR, platelet to lymphocyte ratio; MLR, monocyte to lymphocyte ratio; HCC, hepatocellular carcinoma; OS, overall survival; TACE, transcatheter arterial chemoembolization; TAE, transcatheter arterial embolization; TAI, transcatheter arterial infusion; AFP, α-fetoprotein; ALP, alkaline phosphatase; CEA, carcinoembryonic antigen; LDH, lactate dehydrogenase; ROC, receiver operating characteristic; AUC, the area under the curves; ROS, reactive oxygen species; NE, neutrophil elastase; PI-3K, phosphatidylinositol 3-kinase; HGF, hepatocyte growth factor; PDGF, platelet-derived growth factor; GITRL, glucocorticoid-induced TNF-related ligand; CHI3L, chitinase 3-like protein; IL-13Rα2, interleukin-13 receptor α2; VEGF, vascular endothelial growth factor.

Data Sharing Statement

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

Ethics Approval and Consent

The study protocol has been approved by the Medical Ethics Committee of West China Hospital, Sichuan University, and all the patients signed informed consent.

Author Contributions

All authors contributed to data analysis, drafting or revising the article, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.


The authors report no conflicts of interest for this work.


1. Yang JD, Roberts LR. Hepatocellular carcinoma: a global view. Nat Rev Gastroenterol Hepatol. 2010;7(8):448–458. doi:10.1038/nrgastro.2010.100

2. Ferlay J, Soerjomataram I, Dikshit R, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2015;136(5):E359–E386. doi:10.1002/ijc.29210

3. European Association For The Study Of The Liver. EASL-EORTC clinical practice guidelines: management of hepatocellular carcinoma. J Hepatol. 2012; 56(4):908–943doi:10.1016/j.jhep.2011.12.001

4. Bruix J, Sherman M. Management of hepatocellular carcinoma: an update. Hepatology. 2011;53(3):1020–1022. doi:10.1002/hep.24199

5. Qian J, Feng GS, Vogl T. Combined interventional therapies of hepatocellular carcinoma. World J Gastroenterol. 2003;9(9):1885–1891. doi:10.3748/wjg.v9.i9.1885

6. Chintalapati SP, Patel A, Conjeevaram H. Gastric and duodenal ischaemia after transarterial chemoembolisation for hepatocellular carcinoma: an unexpected but significant complication. BMJ Case Rep. 2018;2018:doi:10.1136/bcr-2017-223339

7. Hyun MH, Lee YS, Kim JH, et al. Hepatic resection compared to chemoembolization in intermediate- to advanced-stage hepatocellular carcinoma: a meta-analysis of high-quality studies. Hepatology. 2018;68(3):977–993. doi:10.1002/hep.29883

8. Liu H, Xu Y, Xiang J, et al. Targeting alpha-fetoprotein (AFP)-MHC complex with CAR T-cell therapy for liver cancer. Clin Cancer Res. 2017;23(2):478–488.

9. Sturgeon CM, Duffy MJ, Hofmann BR, et al. National Academy of Clinical Biochemistry Laboratory Medicine Practice Guidelines for use of tumor markers in liver, bladder, cervical, and gastric cancers. Clin Chem. 2010;56(6):e1–e48. doi:10.1373/clinchem.2009.133124

10. Ikai I, Arii S, Kojiro M, et al. Reevaluation of prognostic factors for survival after liver resection in patients with hepatocellular carcinoma in a Japanese nationwide survey. Cancer. 2004;101(4):796–802. doi:10.1002/cncr.20426

11. Lerose R, Molinari R, Rocchi E, Manenti F, Villa E. Prognostic features and survival of hepatocellular carcinoma in Italy: impact of stage of disease. Eur J Cancer. 2001;37(2):239–245. doi:10.1016/S0959-8049(00)00354-3

12. Forrest LM, McMillan DC, McArdle CS, Angerson WJ, Dunlop DJ. Evaluation of cumulative prognostic scores based on the systemic inflammatory response in patients with inoperable non-small-cell lung cancer. Br J Cancer. 2003;89(6):1028–1030. doi:10.1038/sj.bjc.6601242

13. Rodriguez-Vita J, Lawrence T. The resolution of inflammation and cancer. Cytokine Growth Factor Rev. 2010;21(1):61–65. doi:10.1016/j.cytogfr.2009.11.006

14. Dondeti MF, El-Maadawy EA, Talaat RM. Hepatitis-related hepatocellular carcinoma: insights into cytokine gene polymorphisms. World J Gastroenterol. 2016;22(30):6800–6816. doi:10.3748/wjg.v22.i30.6800

15. Wang K, Diao F, Ye Z, et al. Prognostic value of systemic immune-inflammation index in patients with gastric cancer. Chin J Cancer. 2017;36(1):75.

16. Huang W, Wang S, Zhang H, Zhang B, Wang C. Prognostic significance of combined fibrinogen concentration and neutrophil-to-lymphocyte ratio in patients with resectable non-small cell lung cancer. Cancer Biol Med. 2018;15(1):88–96. doi:10.20892/j.issn.2095-3941.2017.0124

17. Fan W, Zhang Y, Wang Y, Yao X, Yang J, Li J. Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios as predictors of survival and metastasis for recurrent hepatocellular carcinoma after transarterial chemoembolization. PLoS One. 2015;10(3):e0119312. doi:10.1371/journal.pone.0119312

18. Stotz M, Pichler M, Absenger G, et al. The preoperative lymphocyte to monocyte ratio predicts clinical outcome in patients with stage III colon cancer. Br J Cancer. 2014;110(2):435–440. doi:10.1038/bjc.2013.785

19. Marconato L, Martini V, Stefanello D, et al. Peripheral blood lymphocyte/monocyte ratio as a useful prognostic factor in dogs with diffuse large B-cell lymphoma receiving chemoimmunotherapy. Vet J. 2015;206(2):226–230. doi:10.1016/j.tvjl.2015.07.009

20. Markovic O, Popovic L, Marisavljevic D, et al. Comparison of prognostic impact of absolute lymphocyte count, absolute monocyte count, absolute lymphocyte count/absolute monocyte count prognostic score and ratio in patients with diffuse large B cell lymphoma. Eur J Intern Med. 2014;25(3):296–302. doi:10.1016/j.ejim.2014.01.019

21. Lu A, Li H, Zheng Y, et al. Prognostic significance of neutrophil to lymphocyte ratio, lymphocyte to monocyte ratio, and platelet to lymphocyte ratio in patients with nasopharyngeal carcinoma. Biomed Res Int. 2017;2017:3047802. doi:10.1155/2017/3047802

22. Hirooka M, Hiraoka A, Ochi H, et al. Transcatheter arterial chemoembolization with or without radiofrequency ablation: outcomes in patients with Barcelona clinic liver cancer Stage B hepatocellular carcinoma. AJR Am J Roentgenol. 2018;210(4):891–898. doi:10.2214/AJR.17.18177

23. Liu JB, Chu KJ, Ling CC, et al. Prognosis for intrahepatic cholangiocarcinoma patients treated with postoperative adjuvant transcatheter hepatic artery chemoembolization. Curr Probl Cancer; 2020:100612.doi:10.1016/j.currproblcancer.2020.100612

24. Labadie KP, Sham JG. Adjuvant transcatheter arterial infusion therapy for hepatocellular carcinoma: not yet for everybody. Ann Surg Oncol. 2020;doi:10.1245/s10434-020-08702-4

25. Hirokawa F, Komeda K, Taniguchi K, et al. Is postoperative adjuvant transcatheter arterial infusion therapy effective for patients with hepatocellular carcinoma who underwent hepatectomy? A prospective randomized controlled trial, Ann Surg Oncol;2020:doi:10.1245/s10434-020-08699-w

26. Liu J, Cao G, Liu J, Zhao X, Cao H. Long noncoding RNA MIAT knockdown potentiates the therapeutic effect of transcatheter arterial embolization in liver cancer by regulating the miR203a/HIF1alpha axis. Oncol Rep. 2020. doi:10.3892/or.2020.7618

27. Lu H, Ouyang W, Huang C. Inflammation, a key event in cancer development. Mol Cancer Res. 2006;4(4):221–233. doi:10.1158/1541-7786.MCR-05-0261

28. Alifano M, Mansuet-Lupo A, Lococo F, et al. Systemic inflammation, nutritional status and tumor immune microenvironment determine outcome of resected non-small cell lung cancer. PLoS One. 2014;9(9):e106914. doi:10.1371/journal.pone.0106914

29. Bremnes RM, Al-Shibli K, Donnem T, et al. The role of tumor-infiltrating immune cells and chronic inflammation at the tumor site on cancer development, progression, and prognosis: emphasis on non-small cell lung cancer. J Thorac Oncol. 2011;6(4):824–833. doi:10.1097/JTO.0b013e3182037b76

30. Platz EA, Kulac I, Barber JR, et al. A prospective study of chronic inflammation in benign prostate tissue and risk of prostate cancer: linked PCPT and SELECT cohorts. Cancer Epidemiol Biomarkers Prev. 2017:26(10); 1549–1557. doi:10.1158/1055-9965.EPI-17-0503

31. Qu D, Shen L, Liu S, et al. Chronic inflammation confers to the metabolic reprogramming associated with tumorigenesis of colorectal cancer. Cancer Biol Ther. 2017;18(4):237–244. doi:10.1080/15384047.2017.1294292

32. Hernandez-Gea V, Toffanin S, Friedman SL, Llovet JM. Role of the microenvironment in the pathogenesis and treatment of hepatocellular carcinoma. Gastroenterology. 2013;144(3):512–527. doi:10.1053/j.gastro.2013.01.002

33. Min GT, Li YM, Yao N, et al. The pretreatment neutrophil-lymphocyte ratio may predict prognosis of patients with liver cancer: a systematic review and meta-analysis. Clin Transplant. 2018;32(1):e13151. doi:10.1111/ctr.13151

34. Tian XC, Liu XL, Zeng FR, Chen Z, Wu DH. Platelet-to-lymphocyte ratio acts as an independent risk factor for patients with hepatitis B virus-related hepatocellular carcinoma who received transarterial chemoembolization. Eur Rev Med Pharmacol Sci. 2016;20(11):2302–2309.;.

35. Xu X, Chen W, Zhang L, et al. Prognostic significance of neutrophil to lymphocyte ratio in patients with hepatocellular carcinoma after transcatheter arterial chemoembolization. Chin Med J. 2014;127(24):4204–4209.

36. Zhao Y, Huang X, Ding TW, Gong Z. Enhanced angiogenesis, hypoxia and neutrophil recruitment during Myc-induced liver tumorigenesis in zebrafish. Sci Rep. 2016;6(1):31952. doi:10.1038/srep31952

37. Bekes EM, Schweighofer B, Kupriyanova TA, et al. Tumor-recruited neutrophils and neutrophil TIMP-free MMP-9 regulate coordinately the levels of tumor angiogenesis and efficiency of malignant cell intravasation. Am J Pathol. 2011;179(3):1455–1470. doi:10.1016/j.ajpath.2011.05.031

38. Kapoor S. Neutrophil gelatinase-associated lipocalin and its influence on tumor progression in systemic malignancies. World J Surg. 2013;37(11):2727–2728. doi:10.1007/s00268-013-2131-5

39. Fernandez CA, Yan L, Louis G, et al. The matrix metalloproteinase-9/neutrophil gelatinase-associated lipocalin complex plays a role in breast tumor growth and is present in the urine of breast cancer patients. Clin Cancer Res. 2005;11(15):5390–5395. doi:10.1158/1078-0432.CCR-04-2391

40. Uribe-Querol E, Rosales C. Neutrophils in cancer: two sides of the same coin. J Immunol Res. 2015;2015:983698. doi:10.1155/2015/983698

41. Lengas A, Poletti V, Pacifico L, Di Domizio C, Patelli M, Spiga L. Acute lung inflammation: neutrophil elastase versus neutrophils in the bronchoalveolar lavage–neutrophil elastase reflects better inflammatory intensity. Intensive Care Med. 1994;20(5):354–359. (). doi:10.1007/BF01720908

42. Yamashita J, Ogawa M, Abe M, et al. Tumor neutrophil elastase is closely associated with the direct extension of non-small cell lung cancer into the aorta. Chest. 1997;111(4):885–890. doi:10.1378/chest.111.4.885

43. Shamamian P, Schwartz JD, Pocock B, et al. Activation of progelatinase A (MMP-2) by neutrophil elastase, cathepsin G, and proteinase-3: a role for inflammatory cells in tumor invasion and angiogenesis. J Cell Physiol. 2001:189(2); 197–206. doi:10.1002/jcp.10014

44. Houghton AM, Rzymkiewicz DM, Ji H, et al. Neutrophil elastase-mediated degradation of IRS-1 accelerates lung tumor growth. Nat Med. 2010;16(2):219–223. doi:10.1038/nm.2084

45. Gaida MM, Steffen TG, Gunther F, et al. Polymorphonuclear neutrophils promote dyshesion of tumor cells and elastase-mediated degradation of E-cadherin in pancreatic tumors. Eur J Immunol. 2012;42(12):3369–3380. doi:10.1002/eji.201242628

46. Chen MB, Hajal C, Benjamin DC, et al. Inflamed neutrophils sequestered at entrapped tumor cells via chemotactic confinement promote tumor cell extravasation. Proc Natl Acad Sci U S A. 2018;115(27):7022–7027. doi:10.1073/pnas.1715932115

47. Bozkaya G, Korhan P, Cokakli M, et al. Cooperative interaction of MUC1 with the HGF/c-Met pathway during hepatocarcinogenesis. Mol Cancer. 2012;11(1):64. doi:10.1186/1476-4598-11-64

48. Nielsen SR, Schmid MC. Macrophages as key drivers of cancer progression and metastasis. Mediators Inflamm. 2017;2017:9624760. doi:10.1155/2017/9624760

49. Chen Y, Zhang S, Wang Q, Zhang X. Tumor-recruited M2 macrophages promote gastric and breast cancer metastasis via M2 macrophage-secreted CHI3L1 protein. J Hematol Oncol. 2017;10(1):36doi:10.1186/s13045-017-0408-0

50. Linde N, Casanova-Acebes M, Sosa MS, et al. Macrophages orchestrate breast cancer early dissemination and metastasis. Nat Commun. 2018;9(1):21. doi:10.1038/s41467-017-02481-5

51. Mitrugno A, Sylman JL, Ngo AT, et al. Aspirin therapy reduces the ability of platelets to promote colon and pancreatic cancer cell proliferation: implications for the oncoprotein c-MYC. Am J Physiol Cell Physiol. 2017;312(2):C176–C89. doi:10.1152/ajpcell.00196.2016

52. Amo L, Tamayo-Orbegozo E, Maruri N, et al. Involvement of platelet-tumor cell interaction in immune evasion. Potential role of podocalyxin-like protein 1. Front Oncol. 2014;4:245. doi:10.3389/fonc.2014.00245

53. Placke T, Salih HR, Kopp HG. GITR ligand provided by thrombopoietic cells inhibits NK cell antitumor activity. J Immunol. 2012;189(1):154–160. doi:10.4049/jimmunol.1103194

54. Meikle CK, Kelly CA, Garg P, Wuescher LM, Ali RA, Worth RG. Cancer and thrombosis: the platelet perspective. Front Cell Dev Biol. 2016;4:147. doi:10.3389/fcell.2016.00147

55. Jiang S, Yang Y, Fang M, et al. Co-evolution of tumor-associated macrophages and tumor neo-vessels during cervical cancer invasion. Oncol Lett. 2016;12(4):2625–2631. doi:10.3892/ol.2016.5014

56. Soki FN, Cho SW, Kim YW, et al. Bone marrow macrophages support prostate cancer growth in bone. Oncotarget. 2015;6(34):35782–35796. doi:10.18632/oncotarget.6042

57. Aras S, Zaidi MR. TAMeless traitors: macrophages in cancer progression and metastasis. Br J Cancer. 2017;117(11):1583–1591. doi:10.1038/bjc.2017.356

58. Yang YT, Jiang JH, Yang HJ, Wu ZJ, Xiao ZM, Xiang BD. The lymphocyte-to-monocyte ratio is a superior predictor of overall survival compared to established biomarkers in HCC patients undergoing liver resection. Sci Rep. 2018;8(1):2535

59. Margetts J, Ogle LF, Chan SL, et al. Neutrophils: driving progression and poor prognosis in hepatocellular carcinoma? Br J Cancer. 2018;118(2):248–257. doi:10.1038/bjc.2017.386

60. Chen L, Kong X, Yan C, Fang Y, Wang J. The research progress on the prognostic value of the common hematological parameters in peripheral venous blood in breast cancer. Onco Targets Ther. 2020;13:1397–1412. doi:10.2147/OTT.S227171

61. Gao F, Li X, Geng M, et al. Pretreatment neutrophil-lymphocyte ratio: an independent predictor of survival in patients with hepatocellular carcinoma. Medicine. 2015;94(11):e639. doi:10.1097/MD.0000000000000639

Creative Commons License © 2020 The Author(s). This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.