Next Article in Journal
Leveraging Large Language Models for Precision Monitoring of Chemotherapy-Induced Toxicities: A Pilot Study with Expert Comparisons and Future Directions
Next Article in Special Issue
Initial Trans-Arterial Chemo-Embolisation (TACE) Is Associated with Similar Survival Outcomes as Compared to Upfront Percutaneous Ablation Allowing for Follow-Up Treatment in Those with Single Hepatocellular Carcinoma (HCC) ≤ 3 cm: Results of a Real-World Propensity-Matched Multi-Centre Australian Cohort Study
Previous Article in Journal
MERTK Is a Potential Therapeutic Target in Ewing Sarcoma
Previous Article in Special Issue
Intrahepatic Mass-Forming Cholangiocarcinoma: Is There Additional Prognostic Value in Using Gd-EOB Enhanced MRI?
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Cancers
Volume 16
Issue 16
10.3390/cancers16162832
cancers-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

CCL2 Predicts Survival in Patients with Inoperable Hepatocellular Carcinoma Undergoing Selective Internal Radiotherapy

by
Florian Haag
1,2,3,
Severin Gylstorff
1,2,4,
Jasmin Bujok
5,
Maciej Pech
1,2 and
Borna Relja
1,2,4,*
1
Experimental Radiology, Department of Radiology and Nuclear Medicine, Otto-von-Guericke-University, 39120 Magdeburg, Germany
2
Research Campus STIMULATE, Otto-von-Guericke-University, 39120 Magdeburg, Germany
3
Department of Radiology and Nuclear Medicine, University Medical Center Mannheim, Heidelberg University, 68167 Mannheim, Germany
4
Translational and Experimental Trauma Research, Department of Trauma, Hand, Plastic and Reconstructive Surgery, University Ulm, 89081 Ulm, Germany
5
Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, 69115 Heidelberg, Germany
*
Author to whom correspondence should be addressed.
Cancers 2024, 16(16), 2832; https://doi.org/10.3390/cancers16162832
Submission received: 18 July 2024 / Revised: 1 August 2024 / Accepted: 5 August 2024 / Published: 12 August 2024
(This article belongs to the Special Issue Radiology for Diagnosis and Treatment of Liver Cancer)
Browse Figures
Versions Notes

Abstract

:

Simple Summary

Malignant diseases represent a central challenge in modern medicine. Despite improved screening approaches and advanced diagnostics, malignant diseases such as HCC are still diagnosed at non-resectable/advanced stages. In these cases, minimally invasive treatment methods such as SIRT or other radioablation procedures are of particular importance as part of personalized oncological therapy. When choosing the right minimally invasive procedure, it would be useful to be able to use biomarkers as predictors of treatment response. With this background, the aim of this study is to evaluate the usefulness of CCL2 as a predictor of treatment response and survival.

Abstract

Purpose: Hepatocellular carcinoma (HCC) is the largest subgroup of primary liver tumors. Ablative therapies, such as selective internal radiation therapy (SIRT), are used in late stages for patients with unresectable liver metastases and no response to other therapies. CCL2 (C-C motif chemokine ligand 2) is a potent monocyte chemoattractant. It is associated with tumor progression and metastasis. The role of circulating CCL2 as a biomarker in HCC undergoing selective internal radiation therapy remains unclear. Methods: A total of 41 patients (8 female, 33 male) suffering from HCC and undergoing SIRT were enrolled. Pre- and post-therapy changes in circulating CCL2 levels were determined by bead-based immunoassay and compared with clinical laboratory parameters and patient data. Results: A total of 32 patients exhibited survival beyond 60 days. It was observed that levels of CCL2 correlated with scores indicating a higher likelihood of non-survival and with the severity of the disease. Moreover, a significant inverse correlation was discovered between CCL2 levels and the survival of patients over 60 days in relation to counts of leukocytes, granulocytes, monocytes, and C-reactive protein. Conclusions: CCL2 may serve as a potential marker for patient survival after SIRT. The prediction of which HCC patients are likely to benefit from SIRT may be helpful in guiding therapeutic management.

1. Introduction

Globally, cancer is a leading cause of death with increasing incidence and mortality rates. In 2020, primary liver cancer was the sixth most diagnosed cancer and the third leading cause of cancer-related death worldwide [1]. Hepatocellular carcinoma (HCC) is an epithelial tumor that develops in the liver and primarily comprises cells that resemble normal hepatocytes [2]. In Europe, alcohol consumption and the resulting liver cirrhosis are the most prevalent causes, with approximately the most HCC cases [3]. Worldwide, the epidemiology of HCC varies between Eastern and Western cohorts; hepatitis B and C are the most critical risk factors for the genesis of HCC. Other risk factors include nonalcoholic steatohepatitis, nonalcoholic fatty liver disease, and exposure to aflatoxin B1 produced by Aspergillus species [4]. There are many stage-dependent and specific approaches to improve HCC survival and treatment choices. According to the Barcelona Clinic Liver Cancer staging system, which is commonly used to stage HCC, 30% of patients are diagnosed at an advanced stage [5,6]. In the majority (>70%) of cases, HCC has progressed so far that surgical resection or liver transplantation can no longer be performed at the time of diagnosis [7,8]. One treatment option for non-resectable HCCs is the transarterial approach of selective internal radiation therapy (SIRT) [7,8]. SIRT uses an arterial catheter to deliver radioactive material (e.g., Yttrium-90) directly into the bloodstream of the tumor to inhibit perfusion, induce necrosis of the tumor tissue, and stimulate the invasion of immune cells [9]. Owing to the heterogeneity in the population within an advanced stage, the benefits and outcomes of SIRT are considered variable [9,10]. The survival of patients with advanced HCC is monitored using a combination of imaging modalities such as computed tomography (CT), contrast-enhanced magnetic resonance imaging (MRI), and ultrasound. However, to a minor extent, these imaging techniques provide immunological information regarding the response to tumor treatment [11]. Local and systemic immune activation is associated with a sustained response to SIRT in HCC patients [11,12]. Chemokine (C-C motif) ligand 2 (CCL2), also known as chemokine Monocyte chemoattractant protein-1 (MCP-1), belongs to this chemokine group. These are small molecules (8–14 kDa) that are secreted, among others, by cells of the immune system [13,14]. As a pro-inflammatory mediator, CCL2 activates monocytes and other immune cells by binding to the C-C chemokine receptor (CCR2). It induces the differentiation of monocytes into macrophages and tissue invasion [15]. CCR2 is also expressed in tumor cells and possesses a pro-cancerogenic function [16]. In vitro studies have shown that CCL2 promotes HCC cell invasion [17]. Furthermore, data from a CCL2 rat model showed that the inhibition of the MCP-1CCL2/CCR2 axes in animals improves the efficacy of transarterial chemoembolization (TACE) [18]. Our own studies with patients after undergoing interstitial HDR brachytherapy of liver metastases correlations were able to show a positive correlation between baseline circulating levels of CCL2 and the tumor volume as well as threshold doses of irradiation damage [19].
Based on this existing evidence, we hypothesized that CCL2 levels in plasma HCC patients undergoing SIRT have prognostic potential and can be identified as markers for patient therapy outcomes.

2. Materials and Methods

2.1. Ethics

The recent study was conducted in accordance with the Declaration of Helsinki and approved by the institutional ethics committee approval (SWARM RAD298) of the University Hospital of University Magdeburg. Written informed consent was obtained from all the patients.

2.2. Study Settings and Population

A total of 41 patients (female, n = 8; male, n = 33) suffering from HCC who underwent SIRT were included in the study.
Inclusion criteria were: (I) HCC, (II) indication for SIRT, (III) chemotherapy and cortisone therapy paused for a minimum of two weeks before admission, and (IV) >18 years of age.
Exclusion criteria were (I) live expectancy <3 months, (II) hepatic tumor load >70%, (III) chronic infections (HIV and Hepatitis Virus), (IV) pronounced ascites, (V) contraindications for angiography, MRI contrast medium (Gd-EOB-DTPA), X-ray contrast medium, MRI, and CT, (VI) severe cardiovascular diseases (NYHA III/IV), (VII) thrombotic or embolic events in the last six months (stroke/transient ischemic attack), (VIII) immunosuppression (e.g., after transplantation) or human immunodeficiency virus, especially cortisone long-term therapy; and (IX) autoimmune diseases or chronic inflammatory bowel diseases.

2.3. Technique of 90Y-Radioembolization

A detailed description of SIRT is provided elsewhere [20]. Radioembolization was performed using Yttrium-90 (90Y) resin microspheres (SIR-Spheres®, Sirtex Medical, Lane Cove, Australia). Before SIRT, angiography was performed to identify the hepatic arterial tree, and arterial feeders. The hepatic arterial blood supply was isolated by coiling additional feeders. In the next step, 99mTc-MAA (150 MBq, 99mTc-LyoMAA, Covidien, Neustadt/Donau, Germany) was applied to the hepatic artery, and a gamma camera (E.CAM 180, Siemens, Erlangen, Germany) was used to detect the extent of hepatopulmonary shunting. A single-photon emission computed tomography (SPECT) scan of the upper abdomen was performed in order to detect extrahepatic non-target seeding of 99mTc-MAA. The body surface area (BSA) method was used to calculate the activity of 90Y resin microspheres [21]. Two weeks after this procedure, 90Y resin microspheres were delivered selectively into the hepatic arteries via a temporary transfemoral catheter (Figure 1).

2.4. Data Acquisition and Blood Sampling

Blood samples were collected one day before (pre-T) and two days after (post-T) SIRT. Ethylenediaminetetraacetic acid (EDTA) tubes (Becton Vacutainer; Becton Dickinson Diagnostics, Aalst, Belgium) were used to complete the blood count and plasma collection. Serum collection was performed using clot activator tubes (BD Vacutainer SST™ II Advance Tubes; Becton Dickinson Diagnostics, Aalst, Belgium). Citrate tubes (Becton Vacutainer; Becton Dickinson Diagnostics, Aalst, Belgium) were used for determining coagulation parameters. Blood, plasma, citrate, and serum were directly transferred for clinical routine analysis and analyzed according to DIN EN ISO 15189:2014 and DIN EN ISO/IEC 17025:2018 by the Institute for Clinical Chemistry and Pathobiochemistry and University Hospital Magdeburg [22]. The clinical routine included a complete blood count (WBC) (leukocytes, erythrocytes, platelets, neutrophils, immature granulocytes, eosinophils, basophils, lymphocytes, and monocytes). Serum, citrate, and plasma samples were analyzed for coagulation parameters (quick test, international normalized ratio (INR), partial thromboplastin time (PTT), and thrombin time), clinical parameters (creatinine, urea, uric acid, bilirubin, albumin, alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), and gamma-glutamyl transferase (GGT)) and C-reactive protein (CRP). See the experimental design illustrated in Figure 1.

2.5. Quantification of CCL2 by LEGENDPlex™

CCL2 levels in co-isolated plasma samples from patients before and after SIRT liver treatment were measured simultaneously using a multiplex bead-based immunoassay (LEGENDPlexTM Human Neuroinflammation Panel 1, Cat. No. 740795, Biolegend, San Diego, CA, USA). EDTA-treated blood was centrifuged for 15 min at 1500× g and was stored at −80 °C until further analysis. The obtained plasma was diluted 1:2 following the manufacturer’s recommendations. Data were collected from patients by flow cytometry in a FACS Celesta™ Cell Analyzer (BD Biosciences, Franklin Lakes, NJ, USA), and the concentration of each factor was calculated using five-parameter logarithmic curves and compared with the Representative Standard Curve using and within the supplier’s software [23].

2.6. Statistics

The Plasma CCL2 concentrations and the patient’s data were measured pre- and post-SIRT and analyzed using GraphPad Prism 6.0 software (GraphPad Software Inc., San Diego, CA, USA). All data were tested for normality using the Kolmogorov–Smirnov test. Data are presented as the mean ± standard error of the mean or as otherwise indicated. Differences between HCC survivors and non-survivors were determined using the non-parametric Mann–Whitney test and Wilcoxon matched-pairs signed rank test. Correlation analysis was performed using Spearman’s correlation coefficient and Spearman’s r-test. Statistical significance was set at p < 0.05.

3. Results

3.1. Characteristics of the Study Cohort

In total, 41 patients (8 female and 33 male) undergoing SIRT were included. The imaging, biological, and clinical parameters of HCC patients were collected before and after SIRT and correlated with a 60-day survival (hereafter referred to as the HCC cohort). The baseline patient characteristics of this cohort (Table 1 and Table 2) were summarized. A total of 32 of the 41 patients survived longer than 60 days after therapy, and 9 died. The median age of HCC cohort survivors was 69 [range 63.25–78.75], and the median age of non-survivors was 70 [range 62.00–79.50]. The survivors showed a median total liver volume of 1950 cm3 [range 1484–2482] and a tumor fraction of 5.8%, while non-survivors showed a median liver volume of 2790 cm3 [range 1860–3332] and a tumor fraction of 27.40% (Table 1).

3.2. Clinical Parameters

It was shown that prior to treatment, Alkaline phosphate (ALP) and C-reactive protein (CRP) were significantly elevated in the non-survival group compared to the survival group (p = 0.0352 and p = 0.0341, respectively, Table 1 and Figure 2). Following post-therapy, significant differences in CRP levels and aspartate aminotransferase (AST) levels between surviving and non-surviving patients were observed (CRP: p = 0.0094 and AST: p = 0.0070, respectively, Table 1 and Figure 2). In the survival group, urea, albumin, gamma-glutamyl transferase (GGT), and insulin growth factor (IGF) levels were significantly decreased compared to pre-treatment levels (urea: p = 0.0002, albumin: p < 0.0001, GGT: p < 0.0001, and IGF: p = 0.0162, Table 1). Significant changes were detected in creatinine, bilirubin, albumin, AST, and thrombin time levels in the non-survivor group after therapy (pre-T vs. post-T) (creatinine: p = 0.0273, bilirubin: p = 0.0117, albumin: p = 0.0078, AST: p = 0.0234, and thrombin time: p = 0.0156, Table 1).

3.3. Cell Count Pre- and Post-SIRT

In addition to liver parameters, the total number of leukocytes, lymphocytes, granulocytes, monocytes, erythrocytes, and thrombocytes was recorded as part of the study (Table 2 and Figure 2). The cell counts were compared and analyzed pre-T versus post-T and between the survivor group and the non-survivor group (Table 2), as well as within the survivor and non-survivor groups (Table 2). Before therapy, the survivor and non-survivor groups showed significant differences in the levels of leukocytes, neutrophil granulocytes, immature granulocytes, basophil granulocytes, and monocytes (leukocytes: p = 0.0018, neutrophils granulocytes: p = 0.0008, basophil granulocytes: p = 0.0059, and monocytes: p = 0.0109, Figure 2).
After treatment completion, significant differences were observed in the levels of leukocytes, neutrophil granulocytes, immature granulocytes, eosinophil granulocytes, and lymphocytes between surviving and non-surviving patients (leukocytes: p = 0.0313, neutrophil granulocytes: p = 0.0037, immature granulocytes: p = 0.0073, eosinophil granulocytes: p = 0.0462, and lymphocytes: p = 0.0103, Table 2 and Figure 2). In the surviving group, there were significant changes between the pre-T and post-T levels of erythrocytes, thrombocytes, and lymphocytes (erythrocytes: p = 0.0050, thrombocytes: p = 0.0012, and lymphocytes: p = 0.0312, Table 2), while the non-surviving group showed a significant difference in thrombocytes (p = 0.0391, Table 2).

3.4. CCL2 Levels in Patients Receiving SIRT

In addition to blood levels, patients’ CCL2 levels were measured. These levels were compared with the 60-day survival levels. CCL2 blood levels distinguished significantly pre-T and post-T in survivors and non-survivors. CCL2 levels were significantly higher in pre-T non-survivors than in survivors (Figure 3). CCL2 levels were correlated and showed a significant negative correlation (r = −0.378, p = 0.015) with the patient’s 60-day survival (Figure 3). The diagnostic performance of pretreatment CCL2 levels in predicting the 60-day survival by ROC analysis showed a relatively moderate predictive capacity for a response to SIRT with an area under the curve of 0.7639 (CI: 0.6083–0.9195) (Figure 3). At a plasma CCL2 level of 957.1 pg/mL, a sensitivity of 77.78% and a specificity of 75% were observed, resulting in a likelihood ratio of 3.111.

3.5. Treatment Response Associated with CCL2 and 60-Day Survival

The patients showed several correlations between treatment parameters like tumor size, tumor fraction, administered activity dose, and measured levels of leukocytes and ALP, CRP, as well as CLL2. Positive significant correlations were observed between tumor size and pre-T leukocytes, neutrophil granulocytes, immature granulocytes, and CRP levels. The tumor fraction positively correlated with pre-T with ALP. The administered activity dose was positively correlated with post-T leukocyte counts. Pre-T Levels of leukocytes showed a significantly positive correlation with neutrophil granulocytes pre- and post-T, immature granulocytes pre- and post-T as ALP post-T, and CRP pre-T and post-T. A negative correlation was observed between pre-T and pre-T monocyte levels. Positive correlations were also observed between pre-T CCL2 and leukocytes (pre- and post-T), immature granulocytes (pre- and post-T), CRP (pre-T), and CCL2 (post-T). Significant negative correlations with the 60-day survival showed for leukocytes (pre-T and post-T), neutrophil granulocytes (pre- and post-T), immature granulocytes (pre- and post-T), ALP (pre-T), CRP (pre-T and post-T), and pre-T CCL2 (Figure 3). Monocytes (pre-T) showed a positive correlation with a 60-day survival (Table 3).

4. Discussion

Selective internal radiation therapy is a critical component of cancer treatment. It can be used alone or in combination with other therapies. The correct method and approach to treatment often determine how a therapist perceives the treatment situation and predicts outcome and progression. Predictive independent inflammatory biomarkers may play a central role in the assessment of image-guided therapies and the result of these therapies.
Our research suggests that elevated plasma levels of CCL2 measured before (pre-T) treatment in HCC patients are negatively correlated with survival of the SIRT. This observation is consistent with the evidence presented in numerous preceding studies, demonstrating that CCL2 is associated with adverse prognoses across a diverse spectrum of neoplastic disorders [24,25]. In human liver cancers, among others, Xiaoguang Li et al. showed that CCL2 is an independent prognostic factor that is highly expressed, and its concentration negatively correlates with patient survival [26]. Moreover, blocking the CCL2/CCR2 pathway prevents the recruitment and infiltration of inflammatory monocytes and the M2 polarization of tumor-associated macrophages (TAMs). This reverses the immunosuppressive state within the tumor microenvironment and activates an anti-tumor response by CD8+ T cells [26,27]. In a broader context, our study also showed a correlation between CCL2 levels pre-T and the number of measured leukocytes and immature granulocytes, as well as independent pro-inflammatory markers such as CRP. Matching this, we demonstrated that the number of leucocytes, granulocytes, and monocytes also correlated negatively with 60 days of survival. However, although CCL2 should stimulate the differentiation of monocytes into macrophages and their invasion into the tissue [15], we do not see any significant differences in the absolute number of monocytes in the clinical blood counts. One possible explanation for this could be that CCL2, in addition to the differentiation and invasion of monocytes, also affects the recruitment of new monocytes, as has already been shown in other studies [28], and we, therefore, cannot demonstrate any net changes in the total cell count. For a better understanding, further studies in which cell activity and subsets are also specifically investigated would be useful here. Unfortunately, the present results do not allow a description of the cells from which circulating CCL2 is derived. However, it can be assumed that CCL2 originates from immune cells, tumor cells, and endothelial progenitor cells. Specifically, Tuo Deng et al. have demonstrated in HCC that endothelial progenitor cells release a higher quantity of CCL2, which stimulates the upregulation of CD36 and thus supports the pro-metastatic microenvironment [29]. This could explain why there is no significant correlation between the tumor volume or the tumor fraction of the liver, and CCL2 could be proven. Despite the described factors, the influence of CCL2 on the tumor environment should also be mentioned. It has already been shown that cancer-associated fibroblasts, which belong to the tumor microenvironment, secrete CCL2 and induce functional reprogramming of monocytes to immunoinhibitory myeloid-derived suppressor cells [30]. Besides other cell types, these cells are associated with radiation resistance [31].
Given this background, it seems reasonable to hypothesize that affected patients might benefit from a CLL2/CCR2 axis blockade [18]. Tian et al. have already tested this therapeutic approach in an animal model. They showed prolonged survival in rats suffering HCC and receiving TACE in combination with a selective CCR2 antagonist [18,32]. Fitting to the recent study, their work highlights the therapeutic potential in CCL2/CCR2. It raises the assumption that patients undergoing SIRT, which is also a transarterial ablation of cancerous tissue, would benefit from this approach [32]. Thereby, A. Wiesemann et al. showed in mice lungs that inhibiting radiation-induced CCL2 signaling protects the lung from vascular dysfunction and endothelial cell loss [33].
Another important conclusion from the presented results is that CCL2 can be used as a marker for the suitability of patients for SIRT. Although SIRT is well established and considered minimally invasive, it can be tiring for patients who are mostly in a more advanced stage of the disease, especially because of the minimum two-stage procedure. Therefore, it is particularly important to select the patients who are eligible for SIRT carefully. Currently, the evaluation of patient suitability is based on clinical criteria, such as liver function and the patient’s performance status, according to the Eastern Cooperative Oncology Group (ECOG) [34]. Furthermore, previous work identified elevated baseline transaminases (ALT/AST) and an ECOG performance status ≥1 as prognostic factors for breast cancer patients receiving SIRT [35]. Also, high levels of bilirubin and transaminases were shown to be risk factors for HCC patients undergoing SIRT for experiencing a decline in liver function [36]. Taken together, these data underline that the patients have to be evaluated accurately. In this context, the serum level of CCL2 is a promising marker for 60 days of survival after therapy and can be helpful in the therapy decision. Other parameters that were associated with the 60-day survival that can be addressed were the count of leucocytes, neutrophils, and immature granulocytes, as well as ALP and CRP.
The main limitation of the study is the relatively small patient cohort. It has to be investigated if CCL2 is also predictive of a worsened outcome in HCC patients receiving another therapy or patients with other tumors affecting the liver. An additional limitation may be that we are unable to definitively rule out the alcohol intake of patients prior to treatment. As previous studies have shown alcohol consumption can raise CCL2 blood levels [37,38], this cannot be ruled out as a distractor. Also, while our study provides valuable insights, the lack of comprehensive metabolic data and the potential for confounding metabolic syndrome and related conditions should be taken into account when interpreting the results. The presence of metabolic syndrome or diabetes in the comparison groups was not systematically assessed, which could introduce bias given that CCL2 is implicated in these conditions. Additionally, BMI data for all patients were not consistently available. Cachexia in advanced tumor stages can indicate prior obesity, suggesting that baseline BMI measurements and clinical data on weight loss would be valuable. The lack of comprehensive BMI data limits our ability to fully control for obesity-related inflammation. CCR2′s role in adipose tissue inflammation within the context of obesity and metabolic diseases further complicates our findings. While extensively studied in other inflammatory conditions, CCR2′s relevance to metabolic syndrome is debated, necessitating careful interpretation of our results. Due to these gaps, the potential confounding effects of metabolic syndrome and related conditions cannot be entirely ruled out. Future research should include thorough assessments of metabolic health and related clinical parameters to provide more robust findings.

5. Conclusions

In summary, the present work demonstrates that elevated levels of CCL2 in the serum of patients with unresectable HCC are associated with reduced survival after SIRT. This suggests that CCL2 may be a predictor of survival after therapy and may be helpful in making treatment decisions. Similarly, the results suggest that it needs to be investigated whether patients would benefit from a blockade of the CCL2/CCR2 axis.

Author Contributions

Conceptualization, F.H., S.G. and B.R.; methodology, F.H., S.G. and B.R.; validation, F.H. and B.R.; formal analysis, F.H. and B.R.; investigation, F.H., S.G. and B.R.; resources, M.P. and B.R.; data curation, F.H., S.G. and B.R.; writing—original draft preparation, F.H. and B.R.; writing—review and editing, S.G. and J.B.; visualization, F.H. and B.R.; supervision, B.R.; funding acquisition, M.P. and B.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Federal Ministry of Education and Research (BMBF) via the STIMULATE Research Campus, grant number 13GW0473A.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki. All patients included gave written informed consent; data collection and analysis were approved by the local ethics committee and competent authority of the University Hospital of the Otto-von-Guericke University Magdeburg, Germany, with institutional ethics committee approval (SWARM RAD298).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data can be obtained, upon reasonable request, from the corresponding author.

Acknowledgments

We specially thank Lisa Grigartzik for her excellent assistance regarding the methodological and organizational issues of the study (Clinic for Neurology, Neuroimmunology Lab, Otto-von-Guericke University Magdeburg).

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Sung, H.; Ferlay, J.; Siegel, R.L.; Laversanne, M.; Soerjomataram, I.; Jemal, A.; Bray, F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J. Clin. 2021, 71, 209–249. [Google Scholar] [CrossRef] [PubMed]
  2. McGlynn, K.A.; Petrick, J.L.; London, W.T. Global epidemiology of hepatocellular carcinoma: An emphasis on demographic and regional variability. Clin. Liver Dis. 2015, 19, 223–238. [Google Scholar] [CrossRef] [PubMed]
  3. Singal, A.G.; Lampertico, P.; Nahon, P. Epidemiology and surveillance for hepatocellular carcinoma: New trends. J. Hepatol. 2020, 72, 250–261. [Google Scholar] [CrossRef] [PubMed]
  4. McGlynn, K.A.; Petrick, J.L.; El-Serag, H.B. Epidemiology of Hepatocellular Carcinoma. Hepatology 2021, 73 (Suppl. S1), 4–13. [Google Scholar] [CrossRef] [PubMed]
  5. Llovet, J.M.; Kelley, R.K.; Villanueva, A.; Singal, A.G.; Pikarsky, E.; Roayaie, S.; Lencioni, R.; Koike, K.; Zucman-Rossi, J.; Finn, R.S. Hepatocellular carcinoma. Nat. Rev. Dis. Primers 2021, 7, 6. [Google Scholar] [CrossRef] [PubMed]
  6. Prince, D.; Liu, K.; Xu, W.; Chen, M.; Sun, J.-Y.; Lu, X.-J.; Ji, J. Management of patients with intermediate stage hepatocellular carcinoma. Ther. Adv. Med. Oncol. 2020, 12, 1758835920970840. [Google Scholar] [CrossRef] [PubMed]
  7. Vogel, A.; Cervantes, A.; Chau, I.; Daniele, B.; Llovet, J.M.; Meyer, T.; Nault, J.-C.; Neumann, U.; Ricke, J.; Sangro, B.; et al. Hepatocellular carcinoma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann. Oncol. 2018, 29, iv238–iv255. [Google Scholar] [CrossRef] [PubMed]
  8. Wang, E.A.; Stein, J.P.; Bellavia, R.J.; Broadwell, S.R. Treatment options for unresectable HCC with a focus on SIRT with Yttrium-90 resin microspheres. Int. J. Clin. Pract. 2017, 71, 449–453. [Google Scholar] [CrossRef] [PubMed]
  9. Sundram, F.X.; Buscombe, J.R. Selective internal radiation therapy for liver tumours. Clin. Med. 2017, 17, 449–453. [Google Scholar] [CrossRef] [PubMed]
  10. Kennedy, A.; Brown, D.B.; Feilchenfeldt, J.; Marshall, J.; Wasan, H.; Fakih, M.; Gibbs, P.; Knuth, A.; Sangro, B.; Soulen, M.C.; et al. Safety of selective internal radiation therapy (SIRT) with yttrium-90 microspheres combined with systemic anticancer agents: Expert consensus. J. Gastrointest. Oncol. 2017, 8, 1079–1099. [Google Scholar] [CrossRef] [PubMed]
  11. Relja, B.; Pech, M. Transarterielle Radioembolisation: Immuneffekte und Immunonkologie. Radiologe 2020, 60, 693–703. [Google Scholar] [CrossRef] [PubMed]
  12. Chew, V.; Lee, Y.H.; Pan, L.; Nasir, N.J.M.; Lim, C.J.; Chua, C.; Lai, L.; Hazirah, S.N.; Lim, T.K.H.; Goh, B.K.P.; et al. Immune activation underlies a sustained clinical response to Yttrium-90 radioembolisation in hepatocellular carcinoma. Gut 2019, 68, 335–346. [Google Scholar] [CrossRef] [PubMed]
  13. Zlotnik, A.; Yoshie, O. Chemokines: A new classification system and their role in immunity. Immunity 2000, 12, 121–127. [Google Scholar] [CrossRef] [PubMed]
  14. Singh, S.; Anshita, D.; Ravichandiran, V. MCP-1: Function, regulation, and involvement in disease. Int. Immunopharmacol. 2021, 101, 107598. [Google Scholar] [CrossRef] [PubMed]
  15. Yoshimura, T. The chemokine MCP-1 (CCL2) in the host interaction with cancer: A foe or ally? Cell. Mol. Immunol. 2018, 15, 335–345. [Google Scholar] [CrossRef] [PubMed]
  16. Fein, M.R.; He, X.-Y.; Almeida, A.S.; Bružas, E.; Pommier, A.; Yan, R.; Eberhardt, A.; Fearon, D.T.; van Aelst, L.; Wilkinson, J.E.; et al. Cancer cell CCR2 orchestrates suppression of the adaptive immune response. J. Exp. Med. 2020, 217, e20181551. [Google Scholar] [CrossRef] [PubMed]
  17. Zhuang, H.; Cao, G.; Kou, C.; Liu, T. CCL2/CCR2 axis induces hepatocellular carcinoma invasion and epithelial-mesenchymal transition in vitro through activation of the Hedgehog pathway. Oncol. Rep. 2018, 39, 21–30. [Google Scholar] [CrossRef] [PubMed]
  18. Tian, Z.; Hou, X.; Liu, W.; Shao, C.; Gao, L.; Jiang, J.; Zhang, L.; Han, Z.; Wei, L. Targeted blocking of CCR2 and CXCR2 improves the efficacy of transarterial chemoembolization of hepatocarcinoma. Cancer Cell Int. 2022, 22, 362. [Google Scholar] [CrossRef] [PubMed]
  19. Damm, R.; Pech, M.; Cavalli, P.; Haag, F.; Gylstorff, S.; Omari, J.; Thormann, M.; Seidensticker, R.; Ricke, J.; Seidensticker, M.; et al. Correlation of chemokines and growth factors with radiation-induced liver injury after interstitial high dose rate (HDR) brachytherapy of liver metastases. J. Cancer Res. Clin. Oncol. 2022, 148, 2815–2826. [Google Scholar] [CrossRef] [PubMed]
  20. Salem, R.; Thurston, K.G. Radioembolization with 90Yttrium microspheres: A state-of-the-art brachytherapy treatment for primary and secondary liver malignancies. Part 1: Technical and methodologic considerations. J. Vasc. Interv. Radiol. 2006, 17, 1251–1278. [Google Scholar] [CrossRef] [PubMed]
  21. Seidensticker, R.; Seidensticker, M.; Damm, R.; Mohnike, K.; Schütte, K.; Malfertheiner, P.; van Buskirk, M.; Pech, M.; Amthauer, H.; Ricke, J. Hepatic toxicity after radioembolization of the liver using (90)Y-microspheres: Sequential lobar versus whole liver approach. Cardiovasc. Intervent. Radiol. 2012, 35, 1109–1118. [Google Scholar] [CrossRef] [PubMed]
  22. Institut für klinische Chemie und Pathologie der Universitätsklinik Magdeburg. Qualitätsmanagement Institut für Klinische Chemie und Pathologie. Available online: https://www.med.uni-magdeburg.de/fme/institute/ikc/?ikcb,13 (accessed on 1 August 2024).
  23. Dezarn, W.A.; Cessna, J.T.; DeWerd, L.A.; Feng, W.; Gates, V.L.; Halama, J.; Kennedy, A.S.; Nag, S.; Sarfaraz, M.; Sehgal, V.; et al. Recommendations of the American Association of Physicists in Medicine on dosimetry, imaging, and quality assurance procedures for 90Y microsphere brachytherapy in the treatment of hepatic malignancies. Med. Phys. 2011, 38, 4824–4845. [Google Scholar] [CrossRef] [PubMed]
  24. Hua, X.; Kratz, M.; Malen, R.C.; Dai, J.Y.; Lindström, S.; Zheng, Y.; Newcomb, P.A. Association between post-treatment circulating biomarkers of inflammation and survival among stage II-III colorectal cancer patients. Br. J. Cancer 2021, 125, 806–815. [Google Scholar] [CrossRef] [PubMed]
  25. Ji, W.-T.; Chen, H.-R.; Lin, C.-H.; Lee, J.-W.; Lee, C.-C. Monocyte chemotactic protein 1 (MCP-1) modulates pro-survival signaling to promote progression of head and neck squamous cell carcinoma. PLoS ONE 2014, 9, e88952. [Google Scholar] [CrossRef]
  26. Li, X.; Yao, W.; Yuan, Y.; Chen, P.; Li, B.; Li, J.; Chu, R.; Song, H.; Xie, D.; Jiang, X.; et al. Targeting of tumour-infiltrating macrophages via CCL2/CCR2 signalling as a therapeutic strategy against hepatocellular carcinoma. Gut 2017, 66, 157–167. [Google Scholar] [CrossRef] [PubMed]
  27. Yao, W.; Ba, Q.; Li, X.; Li, H.; Zhang, S.; Yuan, Y.; Wang, F.; Duan, X.; Li, J.; Zhang, W.; et al. A Natural CCR2 Antagonist Relieves Tumor-associated Macrophage-mediated Immunosuppression to Produce a Therapeutic Effect for Liver Cancer. EBioMedicine 2017, 22, 58–67. [Google Scholar] [CrossRef] [PubMed]
  28. Raghu, H.; Lepus, C.M.; Wang, Q.; Wong, H.H.; Lingampalli, N.; Oliviero, F.; Punzi, L.; Giori, N.J.; Goodman, S.B.; Chu, C.R.; et al. CCL2/CCR2, but not CCL5/CCR5, mediates monocyte recruitment, inflammation and cartilage destruction in osteoarthritis. Ann. Rheum. Dis. 2017, 76, 914–922. [Google Scholar] [CrossRef] [PubMed]
  29. Deng, T.; Zhao, J.; Tong, Y.; Chen, Z.; He, B.; Li, J.; Chen, B.; Li, R.; Deng, L.; Yu, H.; et al. Crosstalk between endothelial progenitor cells and HCC through periostin/CCL2/CD36 supports formation of the pro-metastatic microenvironment in HCC. Oncogene 2024, 43, 944–961. [Google Scholar] [CrossRef] [PubMed]
  30. Xiang, H.; Ramil, C.P.; Hai, J.; Zhang, C.; Wang, H.; Watkins, A.A.; Afshar, R.; Georgiev, P.; Sze, M.A.; Song, X.S.; et al. Cancer-Associated Fibroblasts Promote Immunosuppression by Inducing ROS-Generating Monocytic MDSCs in Lung Squamous Cell Carcinoma. Cancer Immunol. Res. 2020, 8, 436–450. [Google Scholar] [CrossRef] [PubMed]
  31. Jarosz-Biej, M.; Smolarczyk, R.; Cichoń, T.; Kułach, N. Tumor Microenvironment as A “Game Changer” in Cancer Radiotherapy. Int. J. Mol. Sci. 2019, 20, 3212. [Google Scholar] [CrossRef] [PubMed]
  32. You, R.; Jiang, H.; Xu, Q.; Yin, G. Preintervention MCP-1 serum levels as an early predictive marker of tumor response in patients with hepatocellular carcinoma undergoing transarterial chemoembolization. Transl. Cancer Res. 2021, 10, 966–976. [Google Scholar] [CrossRef] [PubMed]
  33. Wiesemann, A.; Ketteler, J.; Slama, A.; Wirsdörfer, F.; Hager, T.; Röck, K.; Engel, D.R.; Fischer, J.W.; Aigner, C.; Jendrossek, V.; et al. Inhibition of Radiation-Induced Ccl2 Signaling Protects Lungs from Vascular Dysfunction and Endothelial Cell Loss. Antioxid. Redox Signal. 2019, 30, 213–231. [Google Scholar] [CrossRef] [PubMed]
  34. Lee, E.W.; Alanis, L.; Cho, S.-K.; Saab, S. Yttrium-90 Selective Internal Radiation Therapy with Glass Microspheres for Hepatocellular Carcinoma: Current and Updated Literature Review. Korean J. Radiol. 2016, 17, 472–488. [Google Scholar] [CrossRef] [PubMed]
  35. Schatka, I.; Tschernig, M.; Rogasch, J.M.M.; Bluemel, S.; Graef, J.; Furth, C.; Sehouli, J.; Blohmer, J.-U.; Gebauer, B.; Fehrenbach, U.; et al. Selective Internal Radiation Therapy in Breast Cancer Liver Metastases: Outcome Assessment Applying a Prognostic Score. Cancers 2021, 13, 3777. [Google Scholar] [CrossRef] [PubMed]
  36. Gabrielson, A.; Miller, A.; Banovac, F.; Kim, A.; He, A.R.; Unger, K. Outcomes and Predictors of Toxicity after Selective Internal Radiation Therapy Using Yttrium-90 Resin Microspheres for Unresectable Hepatocellular Carcinoma. Front. Oncol. 2015, 5, 292. [Google Scholar] [CrossRef] [PubMed]
  37. Pedersen, N.; Larsen, S.; Seidelin, J.B.; Nielsen, O.H. Alcohol modulates circulating levels of interleukin-6 and monocyte chemoattractant protein-1 in chronic pancreatitis. Scand. J. Gastroenterol. 2004, 39, 277–282. [Google Scholar] [CrossRef]
  38. Harper, K.M.; Knapp, D.J.; Breese, G.R. Withdrawal from Chronic Alcohol Induces a Unique CCL2 mRNA Increase in Adolescent But Not Adult Brain—Relationship to Blood Alcohol Levels and Seizures. Alcohol. Clin. Exp. Res. 2015, 39, 2375–2385. [Google Scholar] [CrossRef] [PubMed]
Cancers 16 02832 g001
Figure 1. Illustration of elective study design of CCL2 before and after internal radiation therapy (SIRT) (created with BioRender.com). (Top) CT scan of a patient with hepatocellular carcinoma (HCC) lesion before and after therapy. The tumor shows typical features such as early contrast enhancement, combined with wash-out in the evaluation phase at the application of 99mTc-MAA via an arterial catheter after isolation of arterial hepatic blood supply. (Bottom) CC chemokine ligand 2 (CCL2) and blood, as well as clinical parameters and standard laboratory parameters, were collected and quantified before (pre-T) and after (post-T) therapy.
Figure 1. Illustration of elective study design of CCL2 before and after internal radiation therapy (SIRT) (created with BioRender.com). (Top) CT scan of a patient with hepatocellular carcinoma (HCC) lesion before and after therapy. The tumor shows typical features such as early contrast enhancement, combined with wash-out in the evaluation phase at the application of 99mTc-MAA via an arterial catheter after isolation of arterial hepatic blood supply. (Bottom) CC chemokine ligand 2 (CCL2) and blood, as well as clinical parameters and standard laboratory parameters, were collected and quantified before (pre-T) and after (post-T) therapy.
Cancers 16 02832 g001
Cancers 16 02832 g002
Figure 2. Immune cell distribution, levels of Alkaline phosphatase (ALP), and C-reactive protein (CRP) depending on tumor patients’ (TP) survival status before and after selective internal radiotherapy (pre-T and post-T). Counts of leukocytes in absolute cell numbers [Gpt/L] (A), neutrophil granulocytes in percentages [%] (B), absolute neutrophil numbers [Gpt/L] (C), immature granulocytes in % (D), absolute immature granulocytes numbers (E), monocytes in % (F), monocytes as absolute cell numbers (G), levels of ALP (H), and CRP (I) in survivors and non-survivors (ns) pre-T and post-T are shown. Data are presented as mean ± standard error of the mean. *: p < 0.05 vs. indicated group.
Figure 2. Immune cell distribution, levels of Alkaline phosphatase (ALP), and C-reactive protein (CRP) depending on tumor patients’ (TP) survival status before and after selective internal radiotherapy (pre-T and post-T). Counts of leukocytes in absolute cell numbers [Gpt/L] (A), neutrophil granulocytes in percentages [%] (B), absolute neutrophil numbers [Gpt/L] (C), immature granulocytes in % (D), absolute immature granulocytes numbers (E), monocytes in % (F), monocytes as absolute cell numbers (G), levels of ALP (H), and CRP (I) in survivors and non-survivors (ns) pre-T and post-T are shown. Data are presented as mean ± standard error of the mean. *: p < 0.05 vs. indicated group.
Cancers 16 02832 g002
Cancers 16 02832 g003
Figure 3. CC chemokine ligand 2 (CCL2) is associated with patient survival status, pre- and post-selective internal radiotherapy. (A) Levels of CCL2 in tumor patient (TP) survivors vs. non-survivors (ns) before (pre-T) and after therapy (post-T). (B) Negative correlation between CCL2 levels before therapy and 60 days survival. (C) Sensitivity and specificity assessment of the prognostic performance of pre-therapy CCL2 levels in the prediction of 60 days survival by receiver operating curve analysis. Data are presented as mean ± standard error of the mean. *: p <0.05 vs. indicated group.
Figure 3. CC chemokine ligand 2 (CCL2) is associated with patient survival status, pre- and post-selective internal radiotherapy. (A) Levels of CCL2 in tumor patient (TP) survivors vs. non-survivors (ns) before (pre-T) and after therapy (post-T). (B) Negative correlation between CCL2 levels before therapy and 60 days survival. (C) Sensitivity and specificity assessment of the prognostic performance of pre-therapy CCL2 levels in the prediction of 60 days survival by receiver operating curve analysis. Data are presented as mean ± standard error of the mean. *: p <0.05 vs. indicated group.
Cancers 16 02832 g003
Table 1. Patient cohort characteristics and clinical parameters: Median value with 75% percentile is given. Median value with 75% percentile is given.
Table 1. Patient cohort characteristics and clinical parameters: Median value with 75% percentile is given. Median value with 75% percentile is given.
VariablesPre-TPost-Tp Value < 0.05
Survivors (n = 32)Non-Survivors (n = 9)Survivors (n = 32)Non-Survivors (n = 9)
Age [median (range)]69.00 (63.25–78.75) 70.00 (62.00–79.50) 69.00 (62.50–79.00) 70.00 (62.00–79.50)
Gender (female, n)71
Total liver volume (cm3) [median (range)]1925 (1484–2482)2790 (1860–3332)
Tumor volume (cm3) [median (range)]174.30 (70.17–529.00)690.00 (133.10–1836.00)
Tumor fraction (%) [median (range)]5.80 (3.81–22.40)27.40 (7.00–42.68)
Administered activity dose (MBq) [median (range)]1190 (1003–1392)1438 (1010–1579)
Creatinine (umol/L) [median (range)]83.50 (66.00–100.50)72.00 (60.50–88.50)82.00 (70.00–105.00)87.00 (73.00–108.00)d
Urea (mmol/L) [median (range)]5.15 (3.36–7.95)4.80 (4.10–7.20)6.60 (4.40–8.80)8.10 (5.25–9.90)c
Uric acid (umol/L) [median (range)]373.00 (284.00–441.00)317.00 (249.00–451.00)350.00 (271.00–393.00)395.00 (251.50–530.00)
Bilirubin (umol/L) [median (range)]10.20 (8.48–15.65)12.40 (8.00–15.85)14.30 (8.90–20.80)17.80 (9.90–23.55)d
Albumin (g/L) [median (range)]39.40 (36.63–42.93)39.40 (34.00–42.15)37.10 (33.50–40.60)36.60 (29.70–39.30)c, d
Alanine aminotransferase (umol/s·L) [median (range)]0.66 (0.43–1.10)0.79 (0.52–1.07)0.71 (0.44–0.99)0.72 (0.55–2.16)
Aspartate aminotransferase (umol/s·L) [median (range)]0.88 (0.66–1.30)1.23 (0.65–2.11)0.73 (0.54–1.35)2.10 (1.06–8.10)b, d
Alkaline phosphatase (umol/s·L) [median (range)]2.19 (1.52–3.18)3.64 (2.20–5.22)1.90 (1.35–2.98)3.10 (1.69–4.03)a, c
Gamma-glutamyl transferase (umol/s·L) [median (range)]2.85 (1.66–6.87)4.84 (2.03–20.50)2.51 (1.64–6.38)3.51 (1.73–23.55)c
Quick value (%) [median (range)]87.00 (76.00–94.00)86.00 (78.00–98.00)81.00 (73.00–96.50)75.00 (57.50–92.50)
INR [median (range)]1.080 (1.030–1.160)1.080 (1.010–1.140)1.120 (1.020–1.175)1.170 (1.040–1.360)
PTT (sec.) [median (range)]29.40 (27.10–34.30)30.50 (25.90–30.85)29.20 (27.05–31.85)30.00 (26.80–33.65)
Thrombin time (sec.) [median (range)]16.80 (16.28–17.85)16.45 (15.65–17.98)17.70 (16.85–18.60)18.45 (16.75–19.38)c, d
C-reactive protein (mg/L) [median (range)]12.30 (4.84–14.10)21.30 (8.80–58.80)6.40 (2.90–11.10)18.70 (8.70–69.25)a, b
HGH (ng/mL) [median (range)]0.586 (0.221–1.320)0.975 (0.317–3.563)0.621 (0.342–1.295)1.91 (0.59–4.37)
IGF (ng/mL) [median (range)]71.15 (58.13–109.00)65.75 (41.55–115.80)61.20 (50.15–92.55)74.30 (39.45–111.80)c
Significance dynamics: (a) pre-T in the survivor group versus the non-survivor group; (b) post-T in the survivor group versus the non-survivor group; (c) survivors pre-T versus post-T; (d) non-survivor pre-T versus post-T.
Table 2. Blood counts before (pre-T) and after (post-T) receiving selective internal radiotherapy. Median value with 75% percentile is given.
Table 2. Blood counts before (pre-T) and after (post-T) receiving selective internal radiotherapy. Median value with 75% percentile is given.
VariablesPre-TPost-Tp Value < 0.05
Survivors (n = 32)Non-Survivors (n = 9)Survivors (n = 32)Non-Survivors (n = 9)
Leukocytes (Gpt/L) [median (range)]6.47 (5.31–7.80)11.20 (6.94–12.85)6.81 (5.08–8.63)10.90 (6.81–14.45)a, b
Erythrocytes (Tpt/L) [median (range)]4.30 (3.63–4.64)4.43 (4.03–4.92)4.29 (3.73–4.54)4.48 (4.06–4.70)c
Thrombocytes (Gpt/L) [median (range)]164.50 (115.80–240.80)244.00 (159.50–467.50)146.00 (99.00–219.00)184.00 (97.50–354.00)c, d
Neutrophil granulocytes (%) [median (range)]67.00 (56.95–73.00)76.30 (73.85–81.45)73.00 (67.40–75.00)87.15 (82.18–92.80)a, b
Neutrophil granulocytes (Gpt/L) [median (range)]4.88 (3.05–5.77)9.85 (8.58–13.95)5.84 (3.76–7.800)12.83 (9.24–19.08)a, b
Immature granulocytes (%) [median (range)]0.00 (0.00–0.01)0.01 (0.00–1.05)0.00 (0.00–0.00)0.01 (0.00–1.89)b
Immature granulocytes (Gpt/L) [median (range)]0.04 (0.02–0.06)0.16 (0.09–0.17)0.04 (0.02–0.06)0.21 (0.08–0.38)a, b
Eosinophil granulocytes (%) [median (range)]2.00 (1.10–2.75)1.25 (0.30–3.25)1.60 (0.00–2.00)0.10 (0.00–0.28)
Eosinophil granulocytes (Gpt/L) [median (range)]0.13 (0.09–0.21)0.16 (0.07–0.57)0.08 (0.05–0.15)0.03 (0.00–0.06)b
Basophil granulocytes (%) [median (range)]1.00 (0.75–1.00)0.40 (0.08–0.58)0.80 (0.00–1.00)0.15 (0.25–0.20)a
Basophil granulocytes (Gpt/L) [median (range)]0.05 (0.04–0.06)0.06 (0.04–0.08)0.05 (0.03–0.06)0.03 (0.02–0.04)
Lymphocytes (%) [median (range)]21.00 (16.00–25.50)15.30 (8.20–19.63)14.00 (11.00–19.20)4.65 (2.08–10.60)b, c
Lymphocytes (Gpt/L) [median (range)]1.43 (1.16–1.72)1.83 (1.35–2.46)1.07 (0.73–1.49)0.68 (0.39–1.26)
Monocytes (%) [median (range)]9.99 (8.35–12.95)5.75 (4.63–7.25)10.00 (9.00–12.00)5.15 (2.90–9.88)a
Monocytes (Gpt/L) [median (range)]0.68 (0.52–0.99)0.81 (0.54–1.14)0.79 (0.54–1.400)0.93 (0.44–1.23)
Significance dynamics: (a) pre-T in the survivor group versus the non-survivor group; (b) post-T in the survivor group versus the non-survivor group; (c) survivors pre-T versus post-T; (d) non-survivor pre-T versus post-T.
Table 3. Correlations between selective internal radiotherapy parameters and the measured levels of leukocytes and Alkaline phosphatase, C-reactive protein, and CC chemokine ligand 2 (CLL2). The table shows the Spearman correlation between the measured parameters before (pre-T) and after therapy (post-T). A p-value <0.05 was considered as significant. Also, the Spearman correlation coefficient r is given.
Table 3. Correlations between selective internal radiotherapy parameters and the measured levels of leukocytes and Alkaline phosphatase, C-reactive protein, and CC chemokine ligand 2 (CLL2). The table shows the Spearman correlation between the measured parameters before (pre-T) and after therapy (post-T). A p-value <0.05 was considered as significant. Also, the Spearman correlation coefficient r is given.
ParametersTumor Size (cm3)Tumor Fraction (%)Administered Activity Dose (MBq)Leukocytes Pre-T (Gpt/L)CCL2 Pre-T (pg/mL)Interval Until
Death (Days)		60 Days Survival
Time Pointrp Valuerp Valuerp Valuerp Valuerp Valuerp Valuerp Value
Leukocytes (Gpt/L)pre-T0.3610.0220.3570.0620.508<0.001 0.3960.0100.3260.201−0.4730.002
post-T0.1230.4570.1270.5210.4510.0040.654<0.0010.4450.0040.0640.808−0.3420.031
Neutrophil granulocytes (%)pre-T0.5290.0350.4000.2860.3260.2020.7440.0010.3140.220−0.2140.645−0.5380.026
post-T−0.0750.790−0.0670.8650.0130.9650.3300.2290.4790.071−0.2510.515−0.7170.003
Neutrophil granulocytes (Gpt/L)pre-T0.7440.0010.5830.0990.5490.0220.958<0.0010.4290.0860.1430.760−0.7360.001
post-T−0.1460.603−0.0170.9660.0930.7420.5090.0520.5630.074−0.0330.932−0.6980.004
Immature granulocytes (%)pre-T0.2120.4310.4400.235−0.1540.5570.1370.599−0.1420.5870.6120.144−0.4680.058
post-T−0.1520.589−0.2660.489−0.1600.5680.1540.5840.0810.774−0.4880.183−0.5220.046
Immature granulocytes (Gpt/L)pre-T0.5340.0330.5990.0880.5310.0280.758<0.0010.5870.0130.7090.074−0.6580.004
post-T−0.0220.9390.2940.4220.1640.5690.5900.0210.5630.0320.1190.761−0.6690.006
Monocytes (%)pre-T−0.3130.238−0.3190.402−0.1510.564−0.5780.015−0.0830.7520.4140.3550.6130.009
post-T−0.4750.074−0.2830.460−0.1710.541−0.3240.240−0.2710.3280.1000.7980.4890.065
Monocytes (Gpt/L)pre-T0.2710.3110.2330.5460.2840.2690.2440.3450.4020.1100.6430.119−0.0570.829
post-T−0.2380.3840.1330.7320.2020.4700.3310.2280.2160.4390.4600.2310.0350.902
Alkaline phosphatase (umol/s·L)pre-T0.2220.1700.3760.049−0.2490.1160.1990.2130.1070.505−0.4800.051−0.3310.034
post-T0.2750.0900.2410.216−0.1430.3780.1520.3510.1640.311−0.4630.061−0.2390.138
C-reactive protein (mg/L)pre-T0.3610.0220.4300.0220.1610.3150.3910.0110.1520.344−0.0590.823−0.3340.033
post-T0.1870.2550.0670.7340.2660.0970.3580.0230.4030.010−0.1020.698−0.4070.009
CCL2 (pg/mL)pre-T0.2410.1350.1910.3290.2710.0870.3960.010 −0.1990.445−0.3780.015
post-T0.1000.5400.1770.3680.0650.6880.1060.5110.537<0.001−0.2650.305−0.1740.276
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Haag, F.; Gylstorff, S.; Bujok, J.; Pech, M.; Relja, B. CCL2 Predicts Survival in Patients with Inoperable Hepatocellular Carcinoma Undergoing Selective Internal Radiotherapy. Cancers 2024, 16, 2832. https://doi.org/10.3390/cancers16162832

AMA Style

Haag F, Gylstorff S, Bujok J, Pech M, Relja B. CCL2 Predicts Survival in Patients with Inoperable Hepatocellular Carcinoma Undergoing Selective Internal Radiotherapy. Cancers. 2024; 16(16):2832. https://doi.org/10.3390/cancers16162832

Chicago/Turabian Style

Haag, Florian, Severin Gylstorff, Jasmin Bujok, Maciej Pech, and Borna Relja. 2024. "CCL2 Predicts Survival in Patients with Inoperable Hepatocellular Carcinoma Undergoing Selective Internal Radiotherapy" Cancers 16, no. 16: 2832. https://doi.org/10.3390/cancers16162832

APA Style

Haag, F., Gylstorff, S., Bujok, J., Pech, M., & Relja, B. (2024). CCL2 Predicts Survival in Patients with Inoperable Hepatocellular Carcinoma Undergoing Selective Internal Radiotherapy. Cancers, 16(16), 2832. https://doi.org/10.3390/cancers16162832

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop