Skip to main content
Clinical and Translational Science logoLink to Clinical and Translational Science
. 2024 Mar 7;17(3):e13751. doi: 10.1111/cts.13751

Tumor biomarkers in evaluating the severity and prognosis of idiopathic pulmonary arterial hypertension: A comprehensive analysis

Xin Li 1, Yi Zhang 1,2, Sicheng Zhang 1, Qing Zhao 1, Qi Jin 1,3, Anqi Duan 1, Zhihua Huang 1, Luyang Gao 1, Yijia Wang 1, Sicong Li 1, Zhihui Zhao 1,✉, Qin Luo 1,✉, Zhihong Liu 1,✉
PMCID: PMC10918713  PMID: 38450983

Abstract

Inflammation contributes to development of idiopathic pulmonary arterial hypertension (IPAH), and tumor biomarkers can reflect inflammatory and immune status. We aimed to determine the value of tumor biomarkers in IPAH comprehensively. We enrolled 315 patients with IPAH retrospectively. Tumor biomarkers were correlated with established indicators of pulmonary hypertension severity. Multivariable Cox regression found that AFP (hazard ratio [HR]: 1.587, 95% confidence interval [CI]: 1.014–2.482, p = 0.043) and CA125 (HR: 2.018, 95% CI: 1.163–3.504, p = 0.013) could independently predict prognosis of IPAH. The changes of AFP over time were associated with prognosis of patients, each 1 ng/mL increase in AFP was associated with 5.4% increased risk of clinical worsening (HR: 1.054, 95% CI: 1.001–1.110, p = 0.046), enabling detection of disease progression. Moreover, beyond well‐validated PH biomarkers, CA125 was still of prognostic value in the low‐risk patients (HR: 1.014, 95% CI: 1.004–1.024, p = 0.004), allowing for more accurate risk stratification and prediction of disease outcomes. AFP and CA125 can serve for prognosis prediction, risk stratification, and dynamic monitor in patients with IPAH.


Study Highlights.

  • WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?

The pathogenesis of idiopathic pulmonary arterial hypertension (IPAH) is known to be influenced by the inflammatory processes. Parameters used for risk stratification mainly reflect disease severity and exercise capacity, but cannot adequately capture the inflammatory and immune profiles of patients. According to the risk stratification, the 5‐year mortality for low‐risk patients was still as high as 17.2%.

  • WHAT QUESTION DID THIS STUDY ADDRESS?

In this study, we aimed to identify whether tumor biomarkers were associated with severity and prognosis in patients with IPAH, and whether tumor biomarkers can furnish supplementary prognostic insights in low‐risk patients.

  • WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE?

Serum levels of tumor biomarkers were associated with well‐validated markers reflecting severity of IPAH. Baseline AFP and CA125 can independently predict long‐term outcome of patients with IPAH, and the changes of AFP over time were associated with clinical worsening. CA125 had prognostic value in low‐risk patients according to guideline recommended risk stratification.

  • HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE?

AFP and CA125 cannot only reflect disease severity, but also predict prognosis of patients with IPAH. Changes in AFP over time serve as an indicator of disease alteration, enabling detection of disease progression or treatment response. Moreover, beyond well‐validated PH biomarkers, CA125 had prognostic value in low‐risk patients, allowing for more accurate risk stratification and prediction of disease outcomes.

INTRODUCTION

Idiopathic pulmonary arterial hypertension (IPAH) is characterized by gradual elevation of pulmonary arterial pressure, which could result in right heart decompensation and mortality. 1 Several factors contribute to the development of IPAH, including genetic susceptibility, immune dysfunction, and environmental factors. 2 Previous studies have demonstrated that impaired immunity and altered inflammatory cell metabolism participate in progression of pulmonary arterial hypertension. 3 The 2022 Pulmonary Hypertension (PH) guideline recommend using World Health Organization function class (WHO FC), higher N‐terminal pro‐brain natriuretic peptide (NT‐proBNP) and 6‐minute walk distance (6MWD) for risk stratification, 4 which predominantly reflect disease severity and exercise capacity, but cannot adequately capture the inflammatory and immune profiles of patients. Moreover, according to the risk stratification, the 5‐year mortality for low‐risk patients was still as high as 17.2%, 5 underscoring the presence of residual risk beyond the scope of the recommended three biomarkers' capacity for reflection.

In addition to tumor conditions, tumor biomarkers also aberrantly elevate in inflammatory conditions and serve as indicators of immune status. 6 Previous studies had demonstrated abnormally exaggerated tumor biomarkers expression in patients with cardiovascular diseases. 7 , 8 Moreover, tumor biomarkers including carcinoembryonic antigen (CEA), carbohydrate antigen (CA)125 and CA153 could independently predict cardiovascular morbidity and mortality. 8 Pulmonary hypertension and cardiovascular diseases have shared clinical features and pathophysiological mechanisms. However, the role of tumor biomarkers in pulmonary hypertension has not been systematically investigated.

In the present investigation, our objective was to discern the associations between tumor biomarkers and prognosis in patients with IPAH. Moreover, we aim to identify whether tumor biomarkers can furnish supplementary prognostic insights in low‐risk patients.

MATERIALS AND METHODS

Study design and population

We retrospectively reviewed consecutive patients diagnosed with IPAH according to the current guidelines 2 , 9 between January 2014 and February 2021 at Fuwai Hospital. Inclusion criteria were: (1) patients received right heart catheterization (RHC); (2) patients with tumor biomarker examination results; and (3) patients with follow‐up data. Patients were excluded if they were: (1) diagnosed with malignancy; (2) diagnosed with inflammatory disease; (3) diagnosed with active infection; and (4) lost to follow‐up. Ethical endorsement for the study was obtained from the Ethics Committee of Fuwai Hospital, and informed consent was acquired from all participating patients. Written informed consent to participate in the study was obtained from all participants.

Right heart catheterization

RHC was performed in accordance with previous description. 10 A 7F Swan‐Ganz catheter was introduced to the internal jugular vein or the right femoral vein and advanced to the pulmonary artery. Hemodynamics were measured, which included mixed venous oxygen saturation, right atrial and ventricular pressure, and pulmonary arterial pressure, as well as pulmonary artery wedge pressure. Pulmonary vascular resistance (PVR) and cardiac index were calculated in line with formulates. 11

Tumor biomarkers measurement

Fasting venous blood samples of patients were collected for tumor biomarkers examination on admission. Tumor marker assays were used to measure serum levels of alpha‐fetoprotein (AFP), CEA, CA125 and CA153, and CA199 with automatic chemiluminescence immunoassay analyzer (Beckman Coulter, UniCel DxI 800).

Follow‐up

Patients with IPAH were followed up every 6 months through a telephone call or inpatient/outpatient examination from discharge to the outcome events or censored date, namely March 31, 2022.

Outcome

The outcome of this study was clinical worsening, including all cause death, rehospitalization for PH deterioration, lung transplant, and escalation of PH targeted therapy to parenteral prostanoids. Clinical worsening‐free survival time was calculated as the time from date of baseline RHC to clinical worsening or the censored date (March 31, 2022). Adjudication of outcome events was carried out by two clinicians independently.

Statistical analysis

Normality of parameters was examined by Kolmogorov‐Smirnova test. Continuous parameters with a normal distribution were demonstrated as the mean ± standard deviation and assessed using independent‐sample t tests. Conversely, continuous parameters with an abnormal distribution were demonstrated as the median (interquartile range) and assessed using the Mann–Whitney U test. Categorical parameters were represented as counts (percentages), and the comparison of differences between groups was conducted using the Chi‐square test. Associations between tumor biomarkers and other parameters were evaluated by Spearman correlation coefficient. Receiver operator characteristic (ROC) curve analysis was used to identify the best cutoff of parameters in predicting clinical worsening. The Kaplan–Meier method, accompanied by the log rank test, was used to assess disparities in prognosis across the groups. A restricted cubic spline analysis incorporating three knots was conducted to ascertain linearity between tumor biomarkers and clinical worsening. Univariable Cox regression analyses were applied to explore predictors of clinical worsening. Then, statistically or clinically significant parameters entered multivariable Cox regression analysis. Bootstrapping with 500 repetitions was applied for internal validation. A two‐sided p value less than 0.05 was regarded of statistical significance. R (version 4.3.2, R Foundation for Statistical Computing) was used to perform statistical analysis.

RESULTS

Patients' enrollment

From January 2014 to February 2021, we had 315 patients with IPAH that were included into the current study (Figure S1). Among them, 383 (78.16%) were women and the average age was 39.51 ± 15.69 years. After a median of 718 (262, 1160) days follow‐up, 124 (39.37%) of 315 patients with IPAH experienced clinical worsening, including 15 death and 109 rehospitalization for right heart failure or progression of PH or escalation of PH therapy to parenteral prostanoids.

Demographics were comparable between both groups, whereas patients with clinical worsening had significantly more advanced PH at baseline, which was reflected by poorer WHO FC, higher NT‐proBNP, worse exercise tolerance, and poorer hemodynamics (Table 1).

TABLE 1.

Demographic features of included patients.

Variables Total IPAH (n = 315) IPAH
Non‐CW (n = 191) CW (n = 124) p value
Age, years 32.83 ± 10.89 32.30 ± 10.62 33.65 ± 11.29 0.724
Female, n (%) 250 (79.4) 153 (80.1) 97 (78.2) 0.687
WHO FC <0.001
I and II, n (%) 160 (50.8) 113 (59.2) 47 (37.9)
III and IV, n (%) 155 (49.2) 78 (40.8) 77 (62.1)
NT‐proBNP, ng/L 962.90 (288.00, 2009.00) 622.50 (164.10, 1618.00) 1312.50 (695.60, 2286.50) <0.001
6MWD, m 408.02 ± 101.61 421.77 ± 101.91 386.81 ± 97.90 0.001
PH specific therapy 0.498
None, n (%) 25 (7.9) 18 (9.4) 7 (5.6)
Monotherapy, n (%) 169 (53.7) 97 (50.8) 72 (58.1)
Double, n (%) 115 (36.5) 72 (37.7) 43 (34.7)
Triple, n (%) 6 (1.9) 4 (2.1) 2 (1.6)
Echocardiography
LVEF, % 64.30 ± 6.22 64.78 ± 6.35 63.56 ± 5.96 0.175
RVED/LVED 0.95 ± 0.29 0.92 ± 0.29 0.99 ± 0.29 0.009
TRV, m/s 4.41 ± 0.60 4.39 ± 0.62 4.44 ± 0.57 0.576
RHC
SvO2, % 69.93 ± 6.46 71.19 ± 6.13 68.01 ± 6.50 <0.001
mRAP, mmHg 4 (1, 7) 4 (1, 6) 4 (3, 9) <0.001
mPAP, mmHg 55.97 ± 14.08 55.13 ± 13.02 57.27 ± 15.54 0.388
PAWP, mmHg 7 (4, 9) 7 (4, 9) 7 (4, 9) 0.773
CI, L/min/m2 2.95 ± 0.92 3.08 ± 0.93 2.74 ± 0.87 <0.001
PVR, wood unit 12.67 ± 5.49 11.95 ± 5.39 13.79 ± 5.46 0.001
Tumor biomarker
AFP, ng/mL 3.61 (2.38, 5.50) 3.24 (2.31, 4.92) 4.17 (2.66, 6.20) 0.001
CEA, ng/mL 1.38 (0.91, 2.28) 1.37 (0.87, 2.15) 1.48 (0.94, 2.34) 0.442
CA199, U/mL 9.95 (5.87, 15.92) 9.83 (5.57, 15.91) 10.54 (6.56, 15.97) 0.669
CA125, U/mL 17.84 (11.98, 25.38) 17.10 (10.97, 23.23) 20.32 (13.89, 45.29) <0.001
CA153, U/mL 6.01 (4.61, 8.87) 5.97 (4.62, 9.18) 6.09 (4.60, 8.55) 1.000
Laboratory examination
TP, g/L 73.03 ± 8.95 73.38 ± 8.16 72.50 ± 10.06 0.419
Alb, g/L 44.59 ± 5.84 44.72 ± 5.73 44.37 ± 6.03 0.951
ALT, IU/L 26.00 (17.00, 37.00) 24.00 (16.00, 33.00) 30.00 (19.25, 42.75) <0.001
AST, IU/L 26.00 (21.00, 34.00) 26.00 (21.00, 32.00) 28.00 (21.00, 35.75) 0.110
TBil, μmol/L 22.03 ± 14.47 20.70 ± 14.37 24.07 ± 14.44 0.003
CREA, μmol/L 74.59 ± 14.76 73.34 ± 13.32 76.53 ± 16.61 0.197
ESR, mm/h 2.00 (1.00, 6.00) 2.00 (1.00, 7.00) 2.00 (1.00, 6.00) 0.101
hsCRP, mg/L 1.19 (0.69, 2.52) 1.08 (0.62, 2.10) 1.42 (0.90, 3.06) 0.002

Note: Data are presented as mean ± standard deviation, median (interquartile range) or number (percentage). Significant p values (p < 0.05) are bolded.

Abbreviations: 6MWD, 6‐minute walk distance; Alb, albumin; AFP, alpha‐fetoprotein; ALT, glutamic pyruvic transaminase; AST, aspartate amino transferase; CA125, carbohydrate antigen 125; CA153, carbohydrate antigen 153; CA199, carbohydrate antigen 199; CEA, carcinoembryonic antigen; CI, cardiac index; CW, clinical worsening; CREA, creatinine; ESR, erythrocyte sedimentation rate; hsCRP, high sensitivity C‐reactive protein; IPAH, idiopathic pulmonary arterial hypertension; LVEF, left ventricular ejection fraction; mPAP, mean pulmonary artery pressure; mRAP, mean right atrial pressure; NT‐proBNP, N‐terminal pro‐brain natriuretic peptide; PAWP, pulmonary artery wedge pressure; PH, pulmonary hypertension; PVR, pulmonary vascular resistance; RHC, right heart catheterization; RVED/LVED, the ratio of right ventricular end‐diastolic to left ventricular end‐diastolic diameter; SvO2, mixed venous oxygen saturation; TRV, tricuspid regurgitation velocity; TBil, total bilirubin; TP, total protein; WHO FC, World Health Organization function class.

Distinctively, patients who experienced clinical worsening had significantly higher level of AFP (4.17 [2.66, 6.20] ng/mL vs. 3.24 [2.31, 4.92] ng/mL, p = 0.001) and CA125 (20.32 [13.89, 45.29] U/mL vs. 17.10 [10.97, 23.23] U/mL, p < 0.001) than those without clinical worsening. Besides increased tumor biomarkers, patients who experienced clinical worsening also had worse laboratory examination results, including higher level of glutamic pyruvic transaminase, total bilirubin, erythrocyte sedimentation rate, and C‐reactive protein (shown in Table 1).

Tumor biomarkers and severity of IPAH

As shown in Figure 1, the serum levels of tumor biomarkers had positive correlation with erythrocyte sedimentation rate, C‐reactive protein, NT‐proBNP, WHO FC, and PVR, and had negative association with 6MWD, mixed venous oxygen saturation and cardiac index (Table S1).

FIGURE 1.

FIGURE 1

Associations between the serum levels of tumor biomarkers and parameters reflecting PH severity. 6MWD, 6‐minute walk distance; AFP, alpha‐fetoprotein; CA125, carbohydrate antigen 125; CA153, carbohydrate antigen 153; CA199, carbohydrate antigen 199; CEA, carcinoembryonic antigen; CI, cardiac index; ESR, erythrocyte sedimentation rate; hsCRP, high sensitivity C‐reactive protein; NT‐proBNP, N‐terminal pro‐brain natriuretic peptide; mPAP, mean pulmonary artery pressure; PH, pulmonary hypertension; PVR, pulmonary vascular resistance; RAP, right atrial pressure; SvO2, mixed venous oxygen saturation; WHO FC, World Health Organization function class. The value in the figure is spearman coefficient and the p value of the correlation please kindly refer to Table S1.

Tumor biomarkers and prognosis of IPAH

ROC identified that the cutoff value, with maximum Youden index, in predicting clinical worsening was 3.45 ng/mL for AFP, 36.48 U/mL for CA125, 1.85 ng/mL for CEA, 10.62 U/mL for CA199 and 5.47 U/mL for CA153, respectively (Figure 2). Restricted cubic splines visualized the relationship of tumor biomarkers and clinical worsening (Figure 3). The risk of clinical worsening escalated with the increased serum levels of AFP and CA125. Among these five tumor biomarkers, univariable Cox analysis identified that AFP and CA125 were associated with clinical worsening (shown in Table S2). After adjusting for demographics, hemodynamics, and echocardiographic parameters, AFP (hazard ratio [HR]: 1.587, 95% confidence interval [CI]: 1.014–2.482, p = 0.043) and CA125 (HR: 2.018, 95% CI: 1.163–3.504, p = 0.013) could still independently predict clinical worsening (Table 2). Internal validation further confirmed the value of AFP (C index: 0.572, 95% CI: 0.510–0.634, bias adjusted C index: 0.572) and CA125 (C index: 0.573, 95% CI: 0.516–0.630, bias adjusted C index: 0.572) in predicting prognosis of patients with IPAH. The predictive ability of AFP and CA125 were comparable to that of NT‐proBNP (C index: 0.595, 95% CI: 0.536–0.654, bias adjusted C index: 0.591).

FIGURE 2.

FIGURE 2

Receiver operator characteristic curve of tumor biomarkers. AFP, alpha‐fetoprotein; AUC, area under the curve; CA125, carbohydrate antigen 125; CA153, carbohydrate antigen 153; CA199, carbohydrate antigen 199; CEA, carcinoembryonic antigen; 95% CI, 95% confidence interval.

FIGURE 3.

FIGURE 3

Restricted cubic splines of tumor biomarkers. (a) Restricted cubic splines of CA125; (b) Restricted cubic splines of AFP; (c) Restricted cubic splines of CEA; (d) Restricted cubic splines of CA199; (e) Restricted cubic splines of CA153. AFP, alpha‐fetoprotein; CA125, carbohydrate antigen 125; CA153, carbohydrate antigen 153; CA199, carbohydrate antigen 199; CEA, carcinoembryonic antigen; 95% CI, 95% confidence interval; refvalue, reference value.

TABLE 2.

Multivariable cox analysis for long‐term clinical worsening in patients with IPAH.

Variable HR 95% CI p value
Model 1
AFP (category) 1.587 1.014–2.482 0.043
Age 0.996 0.976–1.017 0.705
Sex 0.748 0.394–1.417 0.373
WHO FC 1.571 1.047–2.357 0.029
6MWD 0.999 0.997–1.001 0.426
NT‐proBNP 1.000 1.000–1.000 0.190
SvO2 0.940 0.887–0.996 0.036
mRAP 1.078 1.019–1.140 0.009
CI 1.383 0.900–2.125 0.139
PVR 1.011 0.959–1.066 0.687
RVED/LVED 0.881 0.361–2.152 0.781
Alb 0.971 0.930–1.013 0.174
ALT 1.009 1.004–1.013 <0.001
TBil 0.985 0.966–1.005 0.130
CREA 1.007 0.988–1.026 0.489
Model 2
CA125 (category) 2.018 1.163–3.504 0.013
Age 0.995 0.977–1.014 0.619
Sex 0.702 0.370–1.331 0.278
WHO FC 1.566 1.037–2.365 0.033
6MWD 0.999 0.997–1.002 0.569
NT‐proBNP 1.000 1.000–1.000 0.128
SvO2 0.946 0.893–1.002 0.060
mRAP 1.058 1.001–1.117 0.046
CI 1.334 0.869–2.049 0.187
PVR 1.026 0.973–1.081 0.344
RVED/LVED 0.738 0.294–1.856 0.519
Alb 0.966 0.924–1.009 0.122
ALT 1.009 1.004–1.013 <0.001
TBil 0.984 0.964–1.004 0.110
CREA 1.008 0.989–1.027 0.402

Note: Significant p values (p < 0.05) are bolded.

Abbreviations: 6MWD, 6‐minute walk distance; Alb, albumin; AFP, alpha‐fetoprotein; ALT, glutamic pyruvic transaminase; CA125, carbohydrate antigen 125; CI, cardiac index; CREA, creatinine; mRAP, mean right atrial pressure; mPAP, mean pulmonary artery pressure; NT‐proBNP, N‐terminal pro‐brain natriuretic peptide; PVR, pulmonary vascular resistance; RVED/LVED, the ratio of right ventricular end‐diastolic to left ventricular end‐diastolic diameter; SvO2, mixed venous oxygen saturation; TBil, total bilirubin; TRV, tricuspid regurgitation velocity; WHO FC, World Health Organization function class.

According to Kaplan–Meier curve, patients with CA125 less than 36.48 U/mL had significantly better prognosis compared with their counterparts with CA125 greater than or equal to 36.48 U/mL (log rank p < 0.001; Figure 4); patients with AFP greater than or equal to 3.45 ng/mL exhibited markedly inferior event‐free survival rates and experienced a more abbreviated time to clinical deterioration when contrasted with their counterparts (Figure 4).

FIGURE 4.

FIGURE 4

Kaplan–Meier curve of tumor biomarkers. AFP, alpha‐fetoprotein; CA125, carbohydrate antigen 125. According to Kaplan–Meier curve, patients with AFP greater than or equal to 3.45 ng/mL had significantly worse event‐free survival and shorter time to clinical worsening than those with AFP less than 3.45 ng/mL (a); patients with CA125 less than 36.48 U/mL had significantly better prognosis compared with their counterparts with CA125 greater than or equal to 36.48 U/mL (log rank p < 0.001) (b).

We further explored the association between changes in tumor biomarkers and prognosis, and identified that the changes of AFP over time were associated with prognosis of patients, each 1 ng/mL increase in AFP was associated with 5.4% increased risk of clinical worsening (HR: 1.054, 95% CI: 1.001–1.110, p = 0.046; Table S2).

Risk stratification

According to the 2022 PH guideline recommended risk stratification, we classified patients into four risk strata. As the risk stratification increased, the levels of tumor biomarkers are also increased (Figure 5). Moreover, in the low‐risk stratum, CA125 was still of prognostic value (HR: 1.014, 95% CI: 1.004–1.024, p = 0.004; Table S3).

FIGURE 5.

FIGURE 5

Level of tumor biomarkers according to risk stratification. AFP, alpha‐fetoprotein; CA125, carbohydrate antigen 125; CA153, carbohydrate antigen 153; CA199, carbohydrate antigen 199; CEA, carcinoembryonic antigen; 1: low risk; 2: intermediate low risk; 3: intermediate high risk; 4: high risk.

DISCUSSION

In this study, we comprehensively discussed the feature of tumor biomarkers in IPAH: (1) serum levels of tumor biomarkers were associated with well‐validated markers reflecting severity of IPAH; (2) baseline AFP and CA125 can independently predict long‐term outcome of patients with IPAH, and the changes of AFP over time were associated with clinical worsening; and (3) CA125 had prognostic value in low‐risk patients according to guideline recommended risk stratification, allowing for more accurate risk stratification and prediction of disease outcomes.

AFP is a tumor biomarker primarily used for diagnosis of hepatocellular carcinoma. 12 Besides, AFP is also abnormally elevated in patients with cirrhosis 12 and patients with advanced cardiovascular disease. 8 In advanced PH, the liver is predominantly impaired and AFP is subsequently abnormally elevated. The underlying mechanism might be attributable to compromised cardiac output in right heart decompensation. Hypoperfusion leads to hepatic hypoxia, precipitating angiogenesis, and fibrogenesis of the liver. Moreover, right heart failure impairs venous backflow. Secondary to hemodynamic congestion, sheer stress in liver microvascular is elevated, leading to hepatic endothelium impairment and peri sinusoidal edema. In the early stage, liver impairment is reversible when right heart failure is alleviated. In advanced cases, chronic congestive hepatopathy could progress to liver fibrosis or even liver cirrhosis. 13 Hepatic fibrosis secondary to advanced PH 14 could lead to regeneration of injured hepatocytes, abnormally increasing production of AFP. 15 This may explain why the serum levels of AFP was correlated with severity and prognosis of IPAH. Changes in AFP over time can also predict prognosis of patients, serving as an indicator of disease alteration and allowing for timely adjustments in treatment plans.

CA125 is primarily used for identification and monitor of ovarian and gastrointestinal malignancies, which was produced by serosal cells secondary to inflammation or mechanical congestion. 7 Besides carcinoma, CA125 is also elevated in several cardiovascular diseases, including heart failure, pericardial diseases, coronary artery disease, and PH. 7 , 16 , 17 The elevation of CA125 in patients with IPAH might be attributable to elevated right atrial filling pressure secondary to right heart failure, mechanically stretching mesothelial cells, leading to increased production of cytokines and CA125. Previous studies elucidated the value of CA125 in predicting prognosis of patients with heart failure 7 and PH, 18 which was consistent with the current study. Moreover, CA125 can predict prognosis of low‐risk patients according to the guidelines, contributing to identification of residual risk in low‐risk patients and more accurate risk stratification.

CEA is a glycoprotein predominantly located in intestinal epithelium and essential for diagnosing and monitoring colorectal cancer. 19 CEA could bind with monocytes and activate cytokine cascade, participating in chronic inflammation. 20 , 21 Previous studies have found that CEA was independently associated with prognosis of the general population 8 and patients with heart failure. 7 In the current study, we found that CEA correlated with markers reflecting severity of IPAH, including NT‐proBNP, 6MWD, and WHO FC. Right heart failure secondary to advanced PH could lead to gastrointestinal congestion, predisposing chronic inflammation, which might account for increased CEA in patients with IPAH. Similar to CEA, CA199, a biomarker primarily applied for diagnosis of pancreatic cancer and synthesized by normal biliary epithelium and tumor tissue, 22 , 23 , 24 is also increased in expression in patients with IPAH and associated with disease severity. However, we did not observe the significant associations between the serum levels of CEA/CA199 and clinical outcome.

LIMITATIONS

The main limitation of the current study was its retrospective nature. Second, the nonstatistically significant associations between serum levels of CEA/CA199 and long‐term prognosis might be attributed to small sample size. Prospective studies with larger sample sizes are warranted to validate the conclusions of current study. Third, we only included IPAH in the present study. Our results should be interpreted with caution when dealing with other forms of PH.

CONCLUSION

AFP and CA125 can not only reflect disease severity, but also predict prognosis of patients with IPAH. Changes in AFP over time serve as an indicator of disease alteration, enabling detection of disease progression or treatment response. Moreover, beyond well‐validated PH biomarkers, CA125 had prognostic value in low‐risk patients, allowing for more accurate risk stratification and prediction of disease outcomes.

AUTHOR CONTRIBUTIONS

Z.H.L., Z.H.Z., Q.L., X.L., Y.Z., and S.C.Z. wrote the manuscript. X.L. and Y.Z. designed the research. Z.H.L., Z.H.Z., Q.L., Q.Z., Q.J., A.Q.D., Z.H.H., L.Y.G., X.L., Y.Z., S.C.Z., Y.J.W., and S.C.L. performed the research. Z.H.L., Z.H.Z., Q.L., Q.Z., Q.J., A.Q.D., Z.H.H., L.Y.G., X.L., Y.Z., S.C.Z., Y.J.W., and S.C.L. analyzed the data.

FUNDING INFORMATION

This research article was supported by National High Level Hospital Clinical Research Funding (2022‐GSP‐GG‐35), Beijing Municipal Science and Technology Project (Z181100001718200); Beijing Municipal Natural Science Foundation (7202168); CAMS Innovation Fund for Medical Sciences (CIFMS; 2020‐I2M‐C&T‐B‐055, 2021‐I2M‐C&T‐B‐032); the Capital's Funds for Health Improvement and Research (CFH; 2020‐2‐4033, 2020‐4‐4035); the Youth Fund of Zhongshan Hospital, Fudan University (2021‐016); the Yangfan Project of Science and Technology Commission of Shanghai Municipality (22YF1439500); and Artificial Intelligence and Information Technology Application Fund of Fuwai Hospital, Chinese Academy of Medical Sciences (2022‐AI01); Young Scientist Fund of Sichuan Provincial People's Hospital (2023QN02). The funding source(s) had no involvement in study design or in the collection, analysis or interpretation of data or in the writing of the report or in the decision to submit the article for publication.

CONFLICT OF INTEREST STATEMENT

The authors declared no competing interests for this work.

Supporting information

Data S1.

CTS-17-e13751-s001.docx (113.5KB, docx)

Li X, Zhang Y, Zhang S, et al. Tumor biomarkers in evaluating the severity and prognosis of idiopathic pulmonary arterial hypertension: A comprehensive analysis. Clin Transl Sci. 2024;17:e13751. doi: 10.1111/cts.13751

Xin Li, Yi Zhang, and Sicheng Zhang contributed equally to this work.

Contributor Information

Zhihui Zhao, Email: 1250167892@qq.com.

Qin Luo, Email: luoqin2009@163.com.

Zhihong Liu, Email: zhihongliufuwai@163.com.

DATA AVAILABILITY STATEMENT

The data used in this study can be obtained from the corresponding author on reasonable request.

REFERENCES

  • 1. Jin Q, Zhang Y, Zhao Z, et al. Impact of the revised hemodynamic definition on the diagnosis of precapillary pulmonary hypertension: a retrospective single‐center study in China. Cardiovasc Diagn Ther. 2021;11(5):1047‐1057. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2. Galie N, Humbert M, Vachiery JL, Gibbs S, Lang I, et al. 2015 ESC/ERS guidelines for the diagnosis and treatment of pulmonary hypertension: the joint task force for the diagnosis and treatment of pulmonary hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS): endorsed by: Association for European Paediatric and Congenital Cardiology (AEPC), International Society for Heart and Lung Transplantation (ISHLT). Eur Heart J. 2016;37(1):67‐119. [DOI] [PubMed] [Google Scholar]
  • 3. Rabinovitch M, Guignabert C, Humbert M, Nicolls MR. Inflammation and immunity in the pathogenesis of pulmonary arterial hypertension. Circ Res. 2014;115(1):165‐175. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Humbert M, Kovacs G, Hoeper MM, Badagliacca R, Berger RMF, et al. 2022 ESC/ERS guidelines for the diagnosis and treatment of pulmonary hypertension. Eng Eur Respir J. 2023;61(1):2200879. [DOI] [PubMed] [Google Scholar]
  • 5. Hoeper MM, Pausch C, Olsson KM, et al. COMPERA 2.0: a refined 4‐strata risk assessment model for pulmonary arterial hypertension. Eur Respir J. 2021;60:2102311. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Jiang X, Wang J, Deng X, et al. The role of microenvironment in tumor angiogenesis. J Exp Clin Cancer Res. 2020;39(1):204. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Shi C, van der Wal HH, Silljé HHW, et al. Tumour biomarkers: association with heart failure outcomes. J Intern Med. 2020;288(2):207‐218. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Bracun V, Suthahar N, Shi C, et al. Established tumour biomarkers predict cardiovascular events and mortality in the general population. Front Cardiovasc Med. 2021;8:753885. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Galiè N, Hoeper MM, Humbert M, Torbicki A, Vachiery J‐L, et al. Guidelines for the diagnosis and treatment of pulmonary hypertension: the task force for the diagnosis and treatment of pulmonary hypertension of the European Society of Cardiology (ESC) and the European Respiratory Society (ERS), endorsed by the International Society of Heart and Lung Transplantation (ISHLT). Eur Heart J. 2009;30(20):2493‐2537. [DOI] [PubMed] [Google Scholar]
  • 10. Jin Q, Luo Q, Yang T, et al. Improved hemodynamics and cardiopulmonary function in patients with inoperable chronic thromboembolic pulmonary hypertension after balloon pulmonary angioplasty. Respir Res. 2019;20(1):250. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. Maron BA, Brittain EL, Hess E, et al. Pulmonary vascular resistance and clinical outcomes in patients with pulmonary hypertension: a retrospective cohort study. Lancet Respir Med. 2020;8(9):873‐884. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Okuda K. Hepatocellular carcinoma. J Hepatol. 2000;32(1 Suppl):225‐237. [DOI] [PubMed] [Google Scholar]
  • 13. Samsky MD, Patel CB, DeWald TA, Smith AD, Felker GM, et al. Cardiohepatic interactions in heart failure: An overview and clinical implications. J Am Coll Cardiol. 2013;61(24):2397‐2405. [DOI] [PubMed] [Google Scholar]
  • 14. Dai D‐F, Swanson PE, Krieger EV, Liou IW, Carithers RL, Yeh MM. Congestive hepatic fibrosis score: a novel histologic assessment of clinical severity. Mod Pathol. 2014;27(12):1552‐1558. [DOI] [PubMed] [Google Scholar]
  • 15. Lu L‐G, Zeng M‐D, Wan M‐B, et al. Grading and staging of hepatic fibrosis, and its relationship with noninvasive diagnostic parameters. World J Gastroenterol. 2003;9(11):2574‐2578. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Stanciu AE, Stanciu MM, Vatasescu RG. NT‐proBNP and CA 125 levels are associated with increased pro‐inflammatory cytokines in coronary sinus serum of patients with chronic heart failure. Cytokine. 2018;111:13‐19. [DOI] [PubMed] [Google Scholar]
  • 17. Núñez J, Miñana G, Núñez E, Chorro FJ, Bodí V, Sanchis J. Clinical utility of antigen carbohydrate 125 in heart failure. Heart Fail Rev. 2014;19(5):575‐584. [DOI] [PubMed] [Google Scholar]
  • 18. Zhang Y, Jin Q, Zhao Z, et al. Carbohydrate antigen 125 is a biomarker of the severity and prognosis of pulmonary hypertension. Front Cardiovasc Med. 2021;8:699904. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Su B‐B, Shi H, Wan J. Role of serum carcinoembryonic antigen in the detection of colorectal cancer before and after surgical resection. World J Gastroenterol. 2012;18(17):2121‐2126. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Ganguly A, Yeltsin E, Robbins J. Identification of a carcinoembryonic antigen binding protein on monocytes. Biochem Biophys Res Commun. 2003;311(2):319‐323. [DOI] [PubMed] [Google Scholar]
  • 21. Pavlou M, Ambler G, Seaman SR, et al. How to develop a more accurate risk prediction model when there are few events. BMJ. 2015;351:h3868. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Kosar F, Aksoy Y, Ozguntekin G, Ozerol I, Varol E. Relationship between cytokines and tumour markers in patients with chronic heart failure. Eur J Heart Fail. 2006;8(3):270‐274. [DOI] [PubMed] [Google Scholar]
  • 23. Varol E, Ozaydin M, Dogan A, Kosar F. Tumour marker levels in patients with chronic heart failure. Eur J Heart Fail. 2005;7(5):840‐843. [DOI] [PubMed] [Google Scholar]
  • 24. Swords DS, Firpo MA, Scaife CL, Mulvihill SJ. Biomarkers in pancreatic adenocarcinoma: current perspectives. Onco Targets Ther. 2016;9:7459‐7467. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Data S1.

CTS-17-e13751-s001.docx (113.5KB, docx)

Data Availability Statement

The data used in this study can be obtained from the corresponding author on reasonable request.


Articles from Clinical and Translational Science are provided here courtesy of Wiley

RESOURCES