Cheng Y, Sun YS, He YM. ST2, PIVKA-II, CEA, CA125 and their combinations in elderly liver metastases cancers: Development of a diagnostic scoring model. World J Gastrointest Oncol 2026; 18(7): 118940 [DOI: 10.4251/wjgo.v18.i7.118940]
Corresponding Author of This Article
Yun Cheng, Research Fellow, Department of Integrated Traditional Chinese Medicine and Western, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, No. 42 Baiziting, Nanjing 210009, Jiangsu Province, China. chengyun_nj@163.com
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Oncology
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Cheng Y, Sun YS, He YM. ST2, PIVKA-II, CEA, CA125 and their combinations in elderly liver metastases cancers: Development of a diagnostic scoring model. World J Gastrointest Oncol 2026; 18(7): 118940 [DOI: 10.4251/wjgo.v18.i7.118940]
Yun Cheng, Yong-Ming He, Department of Integrated Traditional Chinese Medicine and Western, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210009, Jiangsu Province, China
Yan-Sha Sun, Department of Oncology, Huai’an Hospital of Huai’an City, Huai’an 223200, Jiangsu Province, China
Author contributions: Cheng Y was responsible for research design, funding application, data analysis, review and editing, communication and coordination, ethical review, copyright and licensing, and follow-up; Sun YS, He YM were responsible for data analysis and paper writing; He YM participated in research design; and all authors have read and approved the final manuscript.
Institutional review board statement: This study was approved by the Medical Ethics Committee of the Jiangsu Cancer Hospital and Jiangsu Institute of Cancer Research, approval No. KY-2025-028.
Informed consent statement: All research participants or their legal guardians provided written informed consent prior to study registration.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: No other data available.
Corresponding author: Yun Cheng, Research Fellow, Department of Integrated Traditional Chinese Medicine and Western, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, No. 42 Baiziting, Nanjing 210009, Jiangsu Province, China. chengyun_nj@163.com
Received: January 30, 2026 Revised: February 12, 2026 Accepted: April 1, 2026 Published online: July 15, 2026 Processing time: 164 Days and 1.7 Hours
Abstract
BACKGROUND
Liver metastasis worsens prognosis in elderly colorectal and lung cancer patients, yet early diagnosis is hindered by atypical symptoms and suboptimal biomarker sensitivity. Soluble growth-stimulating gene 2 (ST2), protein induced by vitamin K absence or antagonist-II (PIVKA-II), carcinoembryonic antigen (CEA), and carbohydrate antigen 125 (CA125) have each been implicated in tumor progression and hepatic microenvironment remodeling, but their synergistic diagnostic value in this population remains unevaluated. We hypothesize that integrating these four serum markers with clinical risk factors into a weighted scoring model will improve diagnostic accuracy and enable reliable risk stratification in elderly patients.
AIM
To identify optimal biomarkers and develop a diagnostic scoring model for elderly liver metastatic cancers.
METHODS
This retrospective study enrolled 480 elderly patients with colorectal or lung cancer. Patients were randomly divided 7:3 into construction (n = 336) and validation (n = 144) sets. Univariate analysis and binary logistic regression identified independent risk factors for liver metastases. A scoring model incorporating ST2, PIVKA-II, CEA, CA125, and fatty liver history was developed. Model performance was assessed using receiver operating characteristic curves, area under the curve, calibration curves, and C-index.
RESULTS
Serum ST2, PIVKA-II, CEA, and CA125 levels and fatty liver history were significantly higher in the liver metastasis group (P < 0.05). All five were confirmed as independent risk factors for liver metastasis (P < 0.05). The ST2 + PIVKA-II + CEA + CA125 combination achieved the optimal balance between sensitivity and specificity. A scoring model was developed: Fatty liver history (2 points), ST2 ≥ 64.34 pg/mL (2), PIVKA-II ≥ 40 mAU/mL (3), CEA ≥ 5.7 ng/mL (3), CA125 ≥ 35 U/mL (2). Liver metastasis incidence increased with risk level: Low (0-5 points), intermediate (6-9), and high (10-12). The C-index was 0.840 in the construction group and 0.786 in the validation group, with calibration curves closely matching ideal curves.
CONCLUSION
The combined four-marker panel and novel scoring model effectively predict liver metastasis risk, offering a reliable tool for early diagnosis and risk stratification in elderly patients.
Core Tip: Based on the logistic regression analysis, a risk scoring model incorporating soluble growth-stimulating gene 2, protein induced by vitamin K absence or antagonist-II, carcinoembryonic antigen, carbohydrate antigen 125, and fatty liver history was developed to predict liver metastasis in elderly colorectal and lung cancer patients. The soluble growth-stimulating gene 2 + protein induced by vitamin K absence or antagonist-II + carcinoembryonic antigen + carbohydrate antigen 125 combination achieved the optimal diagnostic balance (area under the curve = 0.896), with specificity reaching 98.42%. Risk stratification significantly correlated with metastasis incidence (93.2% in high-risk vs 10.4% in low-risk). This quantitative model provides a simple, non-invasive tool for early identification of high-risk patients, facilitating personalized surveillance and timely intervention.
Citation: Cheng Y, Sun YS, He YM. ST2, PIVKA-II, CEA, CA125 and their combinations in elderly liver metastases cancers: Development of a diagnostic scoring model. World J Gastrointest Oncol 2026; 18(7): 118940
The liver is one of the most frequent metastatic targets of malignant tumors in different regions of the body, in addition to being the target organ of primary hepatocellular carcinoma[1]. The liver is a common location of metastatic cancer and an organ where different malignant tumors are prone to metastasis, according to clinical data statistics[2]. Tumor cells mainly spread to the liver through blood circulation such as portal vein and hepatic artery or lymphatic pathways. The most common liver metastases in clinical practice mostly originate from the colorectal, pancreas, stomach, lung and breast[3]. Among them, the prognosis of patients with colorectal cancer and lung cancer will be seriously affected once liver metastasis occurs, and the final death of most patients is directly related to the occurrence and development of liver metastasis[4]. At present, surgical resection is an important means of treating eligible liver metastases and striving for long-term survival[5]. According to studies[6], patients’ 5-year survival rate can approach 50% following surgical resection of some colorectal cancer and lung cancer liver metastases. However, most patients are already in the late stage of the disease when they are diagnosed with liver metastasis, and they have lost the best time for surgery. The elderly population is a high-incidence group of metastatic carcinoma of liver. Their physiological functions are declining and they often have multiple underlying diseases, which makes the clinical manifestations more atypical and the diagnosis more challenging[7]. Although its sensitivity and specificity are restricted, alpha-fetoprotein (AFP) is currently the most often utilized serological diagnostic for metastatic carcinoma of liver in clinical practice. The diagnostic effectiveness is inadequate in many metastatic carcinoma of liver patients, particularly those with negative or low levels of AFP expression[8]. It has been demonstrated that protein induced by vitamin K absence or antagonist-II (PIVKA-II) has a good diagnostic value for metastatic carcinoma of liver[9]. Numerous epithelial malignancies, such as gastrointestinal and gynecological tumors, have increased levels of carcinoembryonic antigen (CEA) and carbohydrate antigen 125 (CA125). Their diagnostic and assessment significance in metastatic carcinoma of liver, especially in the presence of bile duct cell differentiation or metastasis, is receiving increasing attention[10,11]. Soluble growth-stimulating gene 2 (ST2) is a key regulator of immune inflammatory response and fibrosis, and is closely related to chronic liver inflammation, fibrosis and even carcinogenesis. In recent years, its value as a potential new biomarker for metastatic carcinoma of liver has begun to be explored[12,13]. This study aims to systematically evaluate the application value of four serum biomarkers, ST2, PIVKA-II, CEA and CA125, individually and in different combinations, in the diagnosis of lung cancer and liver metastasis of colorectal cancer in the elderly, and to construct a risk scoring system for metastatic carcinoma of liver, in order to provide corresponding reference for clinical treatment.
MATERIALS AND METHODS
Research object
Of 480 patients with colorectal and lung cancer who were admitted to our hospital between May 2023 and May 2025 were chosen as study participants and split into a validation group (n = 144) and a construction group (n = 336) in a 7:3 ratio. The model was built using data from the construction group and validated using data from the validation group. Patients in the validation group were split into a liver metastasis group (n = 36) and a liver metastasis-free group (n = 108) based on whether liver metastasis had occurred. Similarly, patients in the construction group were split into a liver metastasis group (n = 84) and a liver metastasis-free group (n = 252).
Exclusion and inclusion criteria
Inclusion criteria: (1) Pathologically confirmed colorectal cancer or lung cancer; (2) No prior surgery, radiotherapy, chemotherapy, targeted therapy, or immunotherapy for the primary tumor; (3) Age 60-80 years; and (4) Full clinical and follow-up information.
Exclusion criteria: (1) Comorbid primary or secondary malignant tumors of other organs; and (2) A history of mental illness or cognitive impairment prevents participation in the study.
The diagnostic criteria for lung cancer and liver metastasis of colorectal cancer are as follows: (1) The liver lesion is confirmed as metastatic cancer by pathological examination after puncture or surgical resection; and (2) There is a history of pathologically confirmed colorectal cancer or lung cancer, and imaging examinations indicate a new mass in the liver that meets the typical characteristics of metastatic tumors, and the liver metastasis is clinically diagnosed by a multidisciplinary team.
Observation indicators
Clinical data of patients were collected by reviewing their electronic medical records, including age, gender, blood type, dietary habits, occupation, course of disease, body mass index, clinical stage, history of hepatitis B, history of fatty liver disease, and test values of ST2, PIVKA-II, CEA, and CA125.
Specimen collection and testing
On the morning following admission, after an 8-hour fast, 3 mL of venous blood was collected from the patient and placed in a coagulation-promoting blood collection tube. All samples were tested on the day of collection. Serum ST2 levels were detected using an enzyme-linked immunosorbent assay with a human ST2 assay kit (Jiangsu Jianglai Biotechnology Co., Ltd. JL46324-48T) and a multi-functional microplate reader. PIVKA-II levels were detected using a WAKO i30 fully automated electrophoresis immunofluorescence analyzer (Japan) and its matching reagents. CEA and CA125 Levels were detected using a Roche E602 fully automated electrochemiluminescence analyzer and its matching reagents. The positive threshold for the test results was defined as follows: ST2 ≥ 64.34 pg/mL, PIVKA-II ≥ 40 mAU/mL, CEA ≥ 5.7 ng/mL, CA125 ≥ 35 U/mL.
Statistical analysis
Software called SPSS 21.0 was used to analyze the data. mean ± SD, median, and interquartile range were utilized to express quantitative data, and independent samples t tests were employed to compare groups. Percentages (%) were utilized to express categorical data, and χ2 tests were employed to compare groups. Potential risk variables for liver metastases in the constructed group were examined using univariate analysis. Binary logistic regression analysis also included variables with statistically significant differences. R software 4.0’s RMS package was used to compute the C-index. To assess the model’s correctness, calibration curves were plotted, receiver operating characteristic curves were displayed, and area under the curve was computed to assess the model’s and the scoring system’s discrimination. A P value < 0.05 was considered statistically significant.
RESULTS
Comparison of clinical data between the two groups
This study included 480 patients, who were randomly divided into a construct group (n = 336) and a validation group (n = 144) in a 7:3 ratio. Based on the presence or absence of liver metastasis, the construct group was further divided into a liver metastasis group (n = 84) and a liver metastasis-free group (n = 252), while the validation group was divided into a liver metastasis group (n = 36) and a liver metastasis-free group (n = 108). Clinical data were compared between the two groups, and there were no statistically significant differences (P > 0.05), indicating comparability (Table 1).
Table 1 Comparison of clinical data between the two groups, n (%).
Univariate analysis of liver metastasis in patients in the construct group
Age, sex, blood type, diet, occupation, disease course, body mass index, clinical stage, and history of hepatitis B did not differ statistically significantly between the two patient groups (P > 0.05). However, there were statistically significant differences between the two groups in terms of ST2, PIVKA-II, CEA, CA125 levels, and history of fatty liver disease (P < 0.05), as shown in Table 2.
Table 2 Univariate analysis of liver metastasis in the construct group, n (%).
Multivariate analysis of liver metastasis in patients in the construct group
The primary risk factors for liver metastasis in patients with lung cancer and colorectal cancer were the detection values of ST2, PIVKA-II, CEA, CA125, and a history of fatty liver disease, according to the results of binary logistic regression analysis, as shown in Tables 3 and 4.
Table 3 Explanation and values of independent variables in logistic regression analysis.
Based on the results of the binary logistic regression analysis in this study, scores were assigned according to the OR values of each indicator after rounding and incorporated into the scoring model. Specifically, a history of fatty liver disease, ST2 ≥ 64.34 pg/mL, PIVKA-II ≥ 40 mAU/mL, CEA ≥ 5.7 ng/mL, and CA125 ≥ 35 U/mL were assigned scores of 2, 2, 3, 3, and 2, respectively. The model’s overall score was between 0 and 12. Three degrees of liver metastasis risk were identified based on the distribution of the total score: Low-risk (0-5 points), intermediate-risk (6-9 points), and high-risk (10-12 points). This scoring standard was used to assess the research cases. The incidence of liver metastasis was 93.2% in the high-risk group, 67.8% in the intermediate-risk group, and 10.4% in the low-risk group, indicating a significant increase with increasing risk score.
The value of ST2, PIVKA-II, CEA, and CA125 as single or combined screening for metastatic carcinoma of liver
In this study, ST2 compared to other combinations, the combined detection of the four markers + PIVKA-II + CEA + CA125 had a considerably higher positive rate (P < 0.05). There was no statistically significant difference between the combinations in the liver metastasis-free group (P > 0.05, Table 5). Receiver operating characteristic curves of individual and combined indicators for diagnosing metastatic carcinoma of liver were plotted, revealing that the area under the curve value of ST2 + PIVKA-II + CEA + CA125 was significantly higher than that of other combinations (Figure 1). Table 6 shows that, among different combinations, ST2 The combination of PIVKA-II, CEA, and CA125 achieves a relatively optimal balance between sensitivity and specificity.
Figure 1 Receiver operating characteristic curves of soluble growth-stimulating gene 2, protein induced by vitamin K absence or antagonist-II, carcinoembryonic antigen, and carbohydrate antigen 125 as individual and combined indicators for screening metastatic carcinoma of liver.
ST2: Soluble growth-stimulating gene 2; AUC: Area under the curve; PIVKA-II: Protein induced by vitamin K absence or antagonist-II; CEA: Carcinoembryonic antigen; CA125: Carbohydrate antigen 125.
Table 5 Positive rates of different combinations of soluble growth-stimulating gene 2, protein Induced by vitamin K absence or antagonist-II, carcinoembryonic antigen, and carbohydrate antigen 125, n (%).
Table 6 Receiver operating characteristic curves analysis of soluble growth-stimulating gene 2, protein induced by vitamin K absence or antagonist-II, carcinoembryonic antigen, and carbohydrate antigen 125 individually and in combination.
The construct group’s calibration curve’s C-index was 0.840 (0.737-0.851), and it nearly matched the ideal curve, suggesting that the model has strong calibration performance and is reasonably stable and dependable. The model appears to have high external prediction capacity, as evidenced by the validation group’s calibration curve’s C-index of 0.786 (0.703-0.823), which closely matched the ideal curve (Figure 2).
Figure 2 Calibration curves for the construct group and the validation group.
A: Construct group; B: Validation group.
DISCUSSION
Liver metastasis is a serious event in the progression of lung and colorectal cancer and a major factor affecting long-term survival[14]. Despite the continuous advancement of imaging technology, there is still a problem of insufficient sensitivity in the identification of early, small or diffuse liver metastases[15]. At the same time, although traditional serum tumor markers are widely used, their specificity and sensitivity in the prediction of early liver metastasis are relatively limited, and there are certain false negative and false positive rates[16,17]. The expression of ST2, a member of the interleukin-1 receptor family, is intimately linked to immunological modulation, fibrosis, and tissue inflammation[18,19]. In the context of malignant tumors, ST2 may participate in shaping a suitable microenvironment for metastasis by mediating tumor-related inflammation and immune escape[20,21]. It may function as a novel inflammation-related marker reflecting tumor invasiveness and metastatic potential, as this investigation discovered that it was markedly higher in the blood of patients with liver metastases. PIVKA-II is an abnormal form of vitamin K-dependent coagulation factor II, which is significantly produced in cases of severe hepatocellular dysfunction or hepatocellular carcinoma[22,23]. In this study, the PIVKA-II level in the liver metastasis group was sharply elevated, which may not only be related to the damage to liver parenchymal function after extensive liver invasion, but may also indicate that some metastatic lesions have abnormal protein synthesis characteristics similar to primary liver cancer[24]. As a traditional cell adhesion molecule, CEA is linked to increased tumor cell shedding, invasion, and metastasis and is frequently employed as a marker to track the development of lung and gastrointestinal tract cancer[25,26]. A high molecular weight glycoprotein called CA125 is increased in serosal cavity inflammation and a number of epithelial cancers[27]. The results of this study showed that CA125 was significantly elevated in the liver metastasis group, which may be related to tumor metastasis inducing micrometastasis in the peritoneal cavity or liver capsule, stimulating mesothelial cells to release CA125, or direct secretion by the tumor itself.
The study’s findings demonstrated that the liver metastasis group’s blood levels of ST2, PIVKA-II, CEA, and CA125 were significantly higher than those of the liver metastasis-free group, indicating a tight relationship between the aforementioned four indicators and the liver metastases of colorectal and lung cancers. Single tumor marker detection has certain risks of false positive and false negative, so multiple indicators are often used in clinical practice to improve diagnostic efficacy. This study found that among various combination modes, the combination of ST2, PIVKA-II, CEA and CA125 achieved the best balance between sensitivity and specificity, which helps to realize early identification and differential diagnosis of liver metastasis. In addition, the history of fatty liver disease was established as an independent risk factor for liver metastasis and included in the scoring model, which has a clear pathophysiological basis. Fatty liver, especially nonalcoholic fatty liver disease, is not only the accumulation of fat in the liver, but also a pathological microenvironment accompanied by chronic low-grade inflammation, oxidative stress and fibrosis[28]. The microenvironment promotes the occurrence of liver metastasis from many aspects. First, nonalcoholic fatty liver disease related dysfunction of hepatic sinusoidal endothelial cells and up-regulated expression of adhesion molecules are conducive to the retention and attachment of circulating tumor cells in the hepatic sinuses[29]. Secondly, the inflammatory factors such as tumor necrosis factor-alpha, interleukin-6 and fibrogenic mediators released by steatosis hepatocytes and activated hepatic stellate cells jointly form an immunosuppressive microenvironment to help metastatic cells escape immune surveillance[30]. Finally, the reprogramming of fatty acid metabolism of hepatocytes in fatty liver can lead to the accumulation of local lipid metabolites, which can not only provide energy for tumor cells, but also activate growth promoting pathways such as epidermal growth factor receptor, and directly stimulate the proliferation of metastases[31]. Therefore, the history of fatty liver disease not only suggests liver vulnerability, but also marks a pre metastatic microenvironment conducive to the colonization and progression of metastasis at the molecular and cellular levels. This not only explains its statistical independence, but also supports its early warning value equivalent to that of serum tumor markers. Clinically, patients with lung cancer or colorectal cancer with a history of fatty liver should be alert to the risk of liver metastasis and consider strengthening monitoring. This study identified independent risk factors for liver metastasis through multivariate analysis, including elevated levels of ST2, PIVKA-II, CEA and CA125 and a history of fatty liver disease. Based on the above factors, a liver metastasis risk scoring model was established. This model included five indicators: History of fatty liver disease, ST2, PIVKA-II, CEA, and CA125, with a total score ranging from 0 to 12 points. The model was further divided into three risk levels: Low (0-5 points), intermediate (6-9 points), and high (10-12 points). As risk increased, the incidence of liver metastasis rose dramatically. According to the model validation results, the construct group’s corrected C-index was 0.840 (95% confidence interval: 0.737-0.851), while the validation group’s C-index was 0.786 (95% confidence interval: 0.703-0.823). The model has strong calibration ability and external prediction validity because both calibration curves closely resembled the ideal curves.
CONCLUSION
In summary, ST2, PIVKA-II, CEA, and CA125 are elevated and independent risk factors in patients with liver metastases, and their combined use can improve diagnostic performance. Based on this, the liver metastasis risk prediction scoring model can effectively distinguish patients at different risk levels, providing a quantitative tool for clinical follow-up and management, and contributing to early intervention in liver metastases. This study is a single-center retrospective study with limited sample representativeness; the external applicability of the model still needs further validation through multicenter prospective studies.
Gosavi A, Puranik AD, Shah S, Agrawal A, Purandare NC, Shetty N, Gala K, Kulkarni S, Patkar S, Goel M, Shrikhande S, Ramaswamy A, Ostwal V, Rangarajan V. Prognostic value of lung shunt fraction in hepatocellular carcinoma and unresectable liver dominant metastatic colorectal cancer undergoing transarterial radioembolisation.Nucl Med Commun. 2022;43:24-31.
[RCA] [PubMed] [DOI] [Full Text][Cited by in Crossref: 2][Cited by in RCA: 2][Article Influence: 0.5][Reference Citation Analysis (0)]
Garcia EM, Nerurkar SN, Tan EX, Tan SYS, Peck EW, Quek SXZ, Teh R, Teng M, Tran A, Yeo EJ, Le M, Wong C, Cheung R, Huang DQ. Characteristics and Outcomes of Elderly Hepatocellular Carcinoma Patients following Surgical Resection: Systematic Review and Meta-Analysis.Dig Dis. 2025;43:206-214.
[RCA] [PubMed] [DOI] [Full Text][Cited by in Crossref: 1][Cited by in RCA: 3][Article Influence: 1.0][Reference Citation Analysis (0)]
Hanif H, Ali MJ, Susheela AT, Khan IW, Luna-Cuadros MA, Khan MM, Lau DT. Update on the applications and limitations of alpha-fetoprotein for hepatocellular carcinoma.World J Gastroenterol. 2022;28:216-229.
[PubMed] [DOI] [Full Text]
Ma C, Awosika JA, Monge C, Coffman-D'Annibale K, Xie C, Skorupan N, Hrones DM, Liu M, Ma L, Wood BJ, Levy EB, Kleiner DE, Figg WD, Redd B, McCulloch JA, Fernandes MR, Trinchieri G, Greten TF. Altering the gut microbiome and tumor microenvironment in advanced liver cancer: A phase II study of nivolumab, tadalafil and oral vancomycin in patients with refractory primary hepatocellular carcinoma or liver dominant metastatic cancer from colorectal or pancreatic cancers.Cancer Lett. 2025;632:217975.
[RCA] [PubMed] [DOI] [Full Text][Cited by in RCA: 3][Reference Citation Analysis (0)]
Wang MD, Lv SD, Diao YK, Xu JH, Chen FJ, Li YC, Gu WM, Wang H, Yang YZ, Zeng YY, Zhou YH, Wang XM, Li J, Chen TH, Liang YJ, Yao LQ, Gu LH, Wu H, Xu XF, Li C, Shen F, Yang T. Risk stratification model for predicting distant metastasis after hepatectomy for hepatocellular carcinoma: A multi-institutional analysis.Biosci Trends. 2025;19:211-220.
[RCA] [PubMed] [DOI] [Full Text][Cited by in RCA: 3][Reference Citation Analysis (0)]
Kaneko S, Kurosaki M, Tsuchiya K, Yasui Y, Hayakawa Y, Inada K, Tanaka Y, Ishido S, Kirino S, Yamashita K, Nobusawa T, Matsumoto H, Kakegawa T, Higuchi M, Takaura K, Tanaka S, Maeyashiki C, Tamaki N, Takahashi Y, Nakanishi H, Izumi N. Clinical evaluation of Elecsys PIVKA-II for patients with advanced hepatocellular carcinoma.PLoS One. 2022;17:e0265235.
[RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)][Cited by in RCA: 9][Reference Citation Analysis (0)]
Bernal S, Prieto I, Kavanagh M, Del Real IH, La Manna S, Lázaro I, Quiceno H, López-Sanz L, Picatoste B, Valdecantos MP, Mas-Fontao S, Sala-Vila A, Valverde ÁM, Marasco D, Egido J, Gómez-Guerrero C. Development of SOCS1 mimetics as novel approach to harmonize inflammation, oxidative stress, and fibrogenesis in metabolic dysfunction-associated steatotic liver disease.Redox Biol. 2025;84:103670.
[RCA] [PubMed] [DOI] [Full Text] [Full Text (PDF)][Cited by in Crossref: 3][Cited by in RCA: 6][Article Influence: 6.0][Reference Citation Analysis (0)]
