Abstract
Immune-related adverse events (irAEs) clinically resemble autoimmune diseases, indicating autoantibodies could be potential biomarkers for the prediction of irAEs. This study aimed to assess the predictive value of peripheral blood antinuclear antibody (ANA) status for irAEs, considering the time and severity of irAEs, as well as treatment outcome in liver cancer patients administered anti-PD-1 therapy. Ninety-three patients with advanced primary liver cancer administered anti-PD-1 treatment were analyzed retrospectively. They were divided into the ANA positive (ANA+, titer ≥ 1:100) and negative (ANA-, titer < 1:100) groups. Development of irAEs, progression-free survival (PFS), and overall survival (OS) were assessed. Compared with ANA- patients, ANA+ cases were more prone to develop irAEs (43.3% vs. 19.2%, P = 0.031). With the increase of ANA titers, the frequency of irAEs increased. The time interval between anti-PD-1 therapy and the onset of irAEs was significantly shorter in ANA+ patients compared with the ANA- group (median, 1.7 months vs. 5.0 months, P = 0.022). Moreover, the time between anti-PD-1 therapy and irAE occurrence decreased with increasing ANA titer. In addition, PFS and OS were decreased in ANA+ patients compared with the ANA− group (median PFS, 2.8 months vs. 4.2 months, P = 0.043; median OS, 21.1 months vs. not reached, P = 0.041). IrAEs occur at higher frequency in ANA+ liver cancer patients undergoing anti-PD-1 therapy. ANA titer could help predict irAE development and treatment outcome in these patients.
Keywords: antinuclear antibody, PD-1, immune-related adverse event, primary liver cancer, common terminology criteria for adverse events
Immune-related adverse events (irAEs) occur at higher frequency in ANA+ liver cancer patients undergoing anti-PD-1 therapy.
Graphical Abstract
Graphical Abstract.
Introduction
Primary liver cancer is the fourth deadliest cancer globally [1]. Hepatocellular carcinoma (HCC) accounts for more than 80% of all primary liver cancer cases while intrahepatic cholangiocarcinoma (ICC) represents 10-15% of the disease burden. The prognosis of patients with primary liver cancer remains dismal, because of advanced stage at the initial diagnosis. Recently, revolutionary efficacy has been achieved in the treatment of advanced primary liver cancer by applying immune checkpoint inhibitors, mostly anti-programmed death 1 (PD-1) [2–4]. Although only 20-30% of primary liver cancer patients benefit from anti-PD-1 therapy, the use of immune checkpoint inhibitors is increasingly utilized because of the limited therapeutic options in both advanced HCC and ICC. Unfortunately, immune checkpoint inhibitors cause immune-related adverse events (irAEs) ranging from mild to severe and to life threatening in terms of severity, affecting multiple organs due to autoimmune-like toxicities [5, 6]. However, clinical biomarkers for predicting irAEs are scarce. This is a major clinical challenge to identify patients susceptible to irAEs, which would avoid overtreatment with immune checkpoint inhibitors, minimize irAEs and prevent fatal irAEs.
Autoantibodies, especially antinuclear antibodies (ANA), are not only utilized as a diagnostic serum marker in autoimmune diseases [7, 8], but increased in serum samples from patients with different types of cancers, suggesting an association between tumor immunity and autoantibodies. In particular, ANA titer is significantly higher in HCC cases than in patients with chronic hepatitis or liver cirrhosis [8–10]. Seroconversion from ANA-negative to ANA-positive status reflects the dynamic nature of autoimmune responses in the transition to HCC. The exact mechanism of irAEs remains unclear. While most irAEs are considered to be predominantly T cell mediated, B cells are correlated with autoimmunity [11, 12], which might be used to identify patients at increased risk of developing autoimmunity-like response before the clinical occurrence of irAEs. It was reported that increased humoral immune response is induced by blocking PD-1 signaling. Since some irAEs have clinical and pathogenic characteristics resembling autoimmune diseases, autoantibodies frequently detected in autoimmune diseases could be the potential biomarkers for the prediction of irAEs. ANA represents an abnormal immune state before or during the process of autoimmunity. This study aimed to assess the predictive value of peripheral blood ANA for irAEs, considering the time and severity of irAEs, as well as treatment outcome in liver cancer patients administered anti-PD-1 immunotherapy.
Methods and Materials
Patients
This retrospective study was approved by the Institutional Review Board of Zhongshan Hospital of Fudan University, Shanghai, China (No. B2022-324), and informed consent was waived due to the retrospective nature of the study. Between September 2018 and May 2020, 93 patients with an initial diagnosis of advanced primary liver cancer (77 HCC and 16 ICC cases) were treated with an anti-PD-1 (nivolumab, pembrolizumab, camrelizumab, tislelizumab, sintilimab, or toripalimab) at the Liver Cancer Institute, Zhongshan Hospital of Fudan University, Shanghai, China, were enrolled. HCC diagnosis was based on liver biopsy or the American Association for the Study of Liver Diseases (AASLD) criteria of typical imaging features (hypervascularity in the arterial phase with washout in the portal venous or delayed phase). ICC was reliably diagnosed by liver biopsy and staged according to the American Joint Committee on Cancer (AJCC) system. All patients received anti-PD-1 therapy intravenously, according to a regimen of 240 mg every 2 weeks for nivolumab; 200 mg every 3 weeks for pembrolizumab, tislelizumab and sintilimab; 240 mg every 3 weeks for toripalimab; or 200 mg every 2 or 3 weeks for camrelizumab. The treatment was continued until tumor progression or presence of unacceptable toxicity. All patients were followed up until death, the last follow-up visit, or the end of the follow-up period. Clinicodemographic data, imaging data, tumor response, irAEs, and survival data were retrieved from electronic medical records.
Indirect immunofluorescence assays
The recruited patients underwent routine serum ANA testing before each administration of anti-PD-1 antibody. ANA was assessed by IIF on a fully automated system (EUROPattern, Euroimmun) in patient serum samples on Hep-2 cell substrate, with staining with fluorescein isothiocyanate-conjugated antibodies plus propidium iodide for counterstaining according to the manufacturer’s instructions. IIF data were acquired under a fluorescence microscope at 200×. The included patients were classified by fluorescence intensity at a serum dilution of 1:100 in the ANA positive (ANA+, titer ≥ 1:100) and negative (ANA-, titer < 1:100) groups.
Immunoblot
Anti-ENA autoantibodies against SCL-70, SS-B, SS-A, Sm, PCNA, RNP, Jo-1, nucleosomes, ribosomal P-proteins, histones, AMA-M2, CENP-B, PM-Scl, and dsDNA were quantitated by semiquantitative immunoblot on EURO blot ONE following the manufacturer’s instructions. During the first incubation, the diluted serum was added to react with the protein bands. To detect bound antibodies, enzyme-labeled anti-human IgG was used for a second incubation followed by the addition of the substrate, resulting in signals whose intensity could be quantitated as specified by the manufacturer.
Safety and response assessment
The development and severity of representative irAEs (e.g., thyroid dysfunction, dermatitis, hepatitis, adrenal insufficiency, interstitial pneumonitis, colitis, and myocarditis) were graded according to the Common Terminology Criteria for Adverse Events (CTCAE 5.0) criteria. IrAEs were determined by the treating oncologist after alternative diagnoses were excluded, based on irAEs, pathology from biopsy, consensus from 2 or more oncologists, or clinical improvement after irAE-based treatment.
According to Response Evaluation Criteria in Solid Tumors (RECIST 1.1) criteria; tumor response was assessed by two investigators by dynamic contrast-enhanced CT or MRI. Complete response (CR) was reflected by a complete disappearance of all target lesions; partial response (PR) and progressive disease (PD) were defined as a >30% decrease and a >20% increase in the sum of the largest diameters of the target lesions, respectively; stable disease (SD) was defined as neither PR nor PD. The objective response rate (ORR) was the sum of CR and PR, and the disease control rate (DCR) was the sum of CR, PR, and SD.
Statistical analysis
Data are mean±standard deviation (SD) or median (interquartile range) for continuous variables, which were compared by the Mann-Whitney U test. Categorical parameters were expressed as number and percentage, and compared by the χ2 or Fisher’s exact test. Univariate logistic regression analysis was performed to assess the significance of each single factor in predicting irAEs, and significant variables were entered in multivariate analysis to identify potential risk factors for irAEs. Odds ratios (ORs) and 95% confidence intervals (CIs) were determined. Progression-free survival (PFS) was measured from the start of anti-PD-1 treatment to disease progression or death from any cause. Overall survival (OS) was determined from the initiation of anti-PD-1 treatment to death from any cause or last follow-up. The Kaplan-Meier method was used to generate survival curves, which were compared by the log-rank test. Univariate and multivariate analyses were performed with the Cox proportional hazard model to identify prognostic factors. Hazard ratios (HRs) and 95% CIs were determined. For the exploratory assessment of the relationship between ANA and irAE prediction, receiver operating characteristic (ROC) curves were plotted. Post-hoc power analyses were performed using G*Power 3.1 software44 to determine whether the sample size could give the acceptable results. Statistical power was computed as a function of significance level α, sample size, and effect size (α error 0.05, effect size w 0.30, degrees of freedom 1). All statistical analyses were performed with Statistical Package for Social Sciences 17.0 (SPSS Inc., Chicago, IL, USA), R version 4.0.5 (R Core Team, Vienna, Austria), and GraphPad Prism 8.0 (GraphPad Software, La Jolla, CA, USA). P < 0.05 was considered statistically significant.
Results
Patient characteristics
The clinical characteristics of the 93 patients enrolled in this study are shown in Table 1. The cohort consisted of 77 patients with HCC and 16 with ICC. There were 70 males and 23 females, aged 57.5 ± 12.8 years. Anti-PD-1 therapy was used as first-line treatment in 7 patients (7.5 %), and as second- or later-line treatment in 86 (92.4%). Of the Anti-PD-1 antibodies, nivolumab, pembrolizumab, camrelizumab, tislelizumab, toripalimab, and sintilimab were administered in 9, 18, 26, 25, 11, and 4 patients, respectively. In addition, as with other autoantibodies tests reporting negative (Supplementary Table 1), ANA test had a significant number of positive results in the studied patients. Out of 93 cases, 67 were ANA+ (titer ≥1:100) and 26 were ANA- (titer <1:100). There were no statistically significant differences in baseline characteristics between the ANA+ and ANA− groups (Table 1). The median duration of anti-PD-1 treatment in ANA+ patients was 2.8 months (range, 0.8–15.7), compared with 4.7 months (range, 0.9–14.9) in the ANA− group.
Table 1.
Baseline characteristics of patients
| Variable | Overall (n = 93) | ANA− (n = 26) | ANA+ (n = 67) | P-value |
|---|---|---|---|---|
| Age (years)† | 57.5 ± 12.8 | 53.9 ± 13.7 | 58.8 ± 12.3 | 0.094 |
| Sex§ | 0.169 | |||
| Male | 70(75.3) | 17(65.4) | 53(79.1) | |
| Female | 23(24.7) | 9(34.6) | 14(20.9) | |
| Diagnosis § | 0.747 | |||
| HCC | 77(82.8) | 21(80.8) | 56(83.6) | |
| ICC | 16(17.2) | 5(19.2) | 11(16.4) | |
| HBsAg § | 0.293 | |||
| Positive | 64(68.8) | 20(76.9) | 44(65.7) | |
| Negative | 29(31.2) | 6(23.1) | 23(34.3) | |
| Child-Pugh grade § | 0.193 | |||
| A | 70(75.3) | 22(84.6) | 48(71.6) | |
| B | 23(24.7) | 4(15.4) | 19(28.4) | |
| ECOG performance status § | 0.705 | |||
| 0 | 9(9.7) | 3(11.5) | 6(9.0) | |
| 1 | 84(90.3) | 23(88.5) | 61(91.0) | |
| AFP (ng/mL) ‡ | 158.2(4.8–5786.8) | 88.4(4.1–12012.8) | 199.5(5.0–2138.0) | 0.680 |
| CEA (ng/mL)‡ | 2.6(1.6–4.9) | 2.1(1.2–4.1) | 2.7(1.9–5.2) | 0.052 |
| CA19-9 (U/mL)‡ | 20.3(10.2–46.9) | 12.5(9.7–43.2) | 26.1(11.8–56.2) | 0.059 |
| PIVKA-Ⅱ(μg/L)‡ | 834(66.8–21412.5) | 1075(111.8–18735.3) | 834(64.8–22966.5) | 0.986 |
| Bilirubin (g/L)‡ | 14.3(9.3–20.1) | 12.5(8.2–17.5) | 14.6(9.5–21.9) | 0.092 |
| Albumin(g/L)‡ | 39(34.5–44.0) | 41.0(37.5–45.0) | 39.0(34.0–44.0) | 0.128 |
| γ-GT (U/L)‡ | 129(49.0–302.0) | 122(45.3–122.0) | 133.0(52.0–304.0) | 0.821 |
| AST (U/L)‡ | 51(33.0–74.5) | 40.5(32.8–64.5) | 54(33.0–82.0) | 0.141 |
| ALT (U/L)‡ | 34(22.0–51.5) | 31(23.8–55.8) | 35(22.0–51.0) | 0.844 |
| ALP (U/L)‡ | 133(103.5–248.5) | 111(88.0–125.8) | 138(106.0–251.0) | 0.213 |
| Tumor number§ | 0.318 | |||
| <4 | 32(34.4) | 11(42.3) | 21(31.3) | |
| ≥4 | 61(65.6) | 15(57.7) | 46(68.7) | |
| Tumor size (mm)‡ | 58(24.3–82.0) | 51(17.0–72.5) | 58(27.0–83.4) | 0.335 |
| Vascular invasion§ | 0.950 | |||
| No | 51(54.8) | 13(50.0) | 38(56.7) | |
| Vp1–2 | 3(3.2) | 1(3.8) | 2(3.0) | |
| Vp3 | 26(28.0) | 8(30.8) | 18(26.9) | |
| Vp4 | 13(14.0) | 4(15.4) | 9(13.4) | |
| Metastasis§ | 0.957 | |||
| Yes | 64(68.8) | 18(69.2) | 46(68.7) | |
| No | 29(31.2) | 8(30.8) | 21(31.3) |
Values were expressed as †the mean (SD), ‡median (range), or §number. ECOG, Eastern Cooperative Oncology Group; AFP, alpha fetoprotein; CA199, carbohydrate antigen199; CEA, carcinoembryonic antigen; PIVKA-II, prothrombin induced by vitamin K absence-II; GGT, ɣ-glutamyl transpeptidase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; ALP, alkaline phosphatase; HCC, hepatocellular carcinoma; ICC, intrahepatic cholangiocarcinoma; Vp1, third branch portal vein invasion; Vp2, second branch portal vein invasion; Vp3, first branch portal vein invasion; Vp4, main portal vein invasion.
Association of ANA with irAE onset
Of the included 93 patients, 34 (34/93, 36.5%) had at least one irAE of any grade during follow-up, with a total of 49 irAEs of any grade; grades 3–4 (G3–4) irAEs were found in 8.6% of patients (8/93). Of the recorded 49 irAEs, the most common were dermatitis (16/49, 32.7%) and hypothyroidism (12/49, 24.5%) (Fig. 1A), with G3–4 irAEs including rash (4/49, 8.2%), hepatitis (2/49, 4.1%), and thrombocytopenia (2/49, 4.1%). IrAEs were managed with systemic corticosteroids (20/49, 40.8%) and supportive care (29/49, 59.2%). The median initial dose of corticosteroids was 25 mg/d (range, 5–160 mg/d), and the median duration of corticosteroid treatment was 25 days (range, 5–96 days).
Figure 1.
Frequencies of irAEs stratified by type (A) and grade (B) in ANA+ and ANA− patients with advanced liver cancer administered anti-PD-1 treatment. ANA, antinuclear antibody; anti-PD-1, anti-programmed death-1; irAE, immune-related adverse event
Of the 34 patients who experienced irAEs, anti-PD-1 treatment was continued in 19 (19/34, 55.9%) and required temporary interruption in 4 (4/34, 11.8%). Discontinuation of anti-PD-1 therapy due to irAEs occurred in 11 patients (11/34, 32.4%), who were all ANA+.
There were no significant differences in endocrine, hepatic, cardiovascular, hematology, and pulmonary irAEs between the ANA+ and ANA− groups; however, ANA+ patients were more likely to develop skin irAEs than the ANA− group (15/67 vs. 1/26, P = 0.033, Fig. 1A). Among ANA+ patients, the amounts of G1, G2, G3, and G4 irAEs were 18, 16, 5, and 3, respectively; meanwhile, 5 grade 1, 2 grade 2, and no G3-4 irAEs were recorded in ANA− patients (Fig. 1B). There was a statistically significant association between ANA status and the severity of irAE (P = 0.017).
Compared with ANA− patients, ANA+ patients were more likely to develop irAEs (43.3% vs. 19.2%, P = 0.031, Fig. 2). Univariate and multivariate logistic regression analyses showed being ANA+ was the only significant risk factor for irAEs (OR, 3.205; 95% CI, 1.079-9.519; P = 0.036; Table 2), suggesting baseline ANA+ with titer ≥ 1:100 is predictive of irAE. The area under the ROC curve (AUC) for ANA titers in the prediction of irAEs was 0.727 (95% CI, 0.654-0.799; P < 0.001; Fig. 3). Furthermore, a sub-analysis of the 93 patients according to ANA titer cutoffs of 1:100, 1:320, and 1:1,000 showed that the frequency of irAEs increased with ANA titer (Fig. 4), suggesting patients with higher ANA titers are more prone to develop irAEs.
Figure 2.
Incidence rates of irAEs in ANA+ and ANA− patients with advanced liver cancer administered anti-PD-1 treatment. ANA, antinuclear antibody; anti-PD-1, anti-programmed death-1; irAE, immune-related adverse event. P-values were calculated by χ2 test analysis
Table 2.
Risk factors for irAEs after anti-PD-1 therapy in patients with liver cancer by univariate and multivariate logistic regression analysis
| Univariable | Multivariable | |||||
|---|---|---|---|---|---|---|
| OR | 95%CI | P-value | OR | 95%CI | P-value | |
| Age (years) | 0.994 | 0.962–1.028 | 0.731 | |||
| Sex | ||||||
| Male | 1.889 | 0.663–5.378 | 0.234 | |||
| Female | 1 (ref) | |||||
| Diagnosis | ||||||
| ICC | 0.342 | 0.09–1.302 | 0.116 | |||
| HCC | 1 (ref) | |||||
| HBsAg | ||||||
| Positive | 1.140 | 0.455–2.854 | 0.780 | |||
| Negative | 1 (ref) | |||||
| Child-Pugh grade | ||||||
| A | 0.529 | 0.186–1.507 | 0.234 | |||
| B | 1 (ref) | |||||
| ECOG performance status | ||||||
| 1 | 2.154 | 0.421–11.015 | 0.357 | |||
| 0 | 1 (ref) | |||||
| AFP (ng/mL) | 1.000 | 1.000–1.000 | 0.700 | |||
| CEA (ng/mL) | 0.984 | 0.934–1.037 | 0.544 | |||
| CA19-9 (U/mL) | 1.000 | 0.999–1.001 | 0.913 | |||
| PIVKA-Ⅱ(μg/L) | 1.000 | 1.000–1.000 | 0.134 | |||
| Bilirubin (g/L) | 0.990 | 0.960–1.021 | 0.515 | |||
| Albumin (g/L) | 1.029 | 0.962–1.101 | 0.405 | |||
| γ-GT (U/L) | 0.999 | 0.997–1.001 | 0.270 | |||
| AST (U/L) | 0.998 | 0.991–1.006 | 0.646 | |||
| ALT (U/L) | 0.997 | 0.983–1.010 | 0.620 | |||
| ALP (U/L) | 0.997 | 0.993–1.000 | 0.080 | |||
| ANA | ||||||
| Positive | 3.205 | 1.079–9.519 | 0.036 | 3.205 | 1.079–9.519 | 0.036 |
| Negative | 1 (ref) | |||||
| Tumor number | ||||||
| ≥4 | 1.427 | 0.576–3.535 | 0.442 | |||
| <4 | 1 (ref) | |||||
| Tumor size (mm) | 0.997 | 0.987–1.008 | 0.635 | |||
| Vascular invasion | ||||||
| No | 0.724 | 0.309–1.699 | 0.458 | |||
| Yes | 1 (ref) | |||||
| Metastasis | ||||||
| No | 0.742 | 0.301–1.827 | 0.516 | |||
| Yes | 1 (ref) | |||||
ECOG, Eastern Cooperative Oncology Group; AFP, alpha fetoprotein; CA199, carbohydrate antigen199; CEA, carcinoembryonic antigen; PIVKA-II, prothrombin induced by vitamin K absence-II; GGT, ɣ-glutamyl transpeptidase; ALT, alanine aminotransferase; AST, aspartate aminotransferase; ALP, alkaline phosphatase; HCC, hepatocellular carcinoma; ICC, intrahepatic cholangiocarcinoma; ANA, antinuclear antibody. Data in bold face are statistically significant.
Figure 3.
ROC curve analysis of ANA status in the prediction of irAE occurrence. The area under the ROC curve (AUC) for ANA titers was 0.727. ROC, receiver operating characteristic; ANA, antinuclear antibody
Figure 4.
Incidence rates of irAEs after anti-PD-1 treatment in advanced liver cancer patients sub-divided according to ANA titers cutoff of 1:100, 1:320, and 1:1,000. (A) Rates of irAEs in patients with ANA titers ≥1:100, ≥1:320, and ≥1:1,000, respectively. (B) Rates of irAEs in patients with ANA titers <1:100, <1:320, and <1:1,000, respectively. ANA, antinuclear antibody; irAE, immune-related adverse event
Given the difference in clinical profiles (epidemiology and malignancy potential) between HCC and ICC (Supplementary Table 2), we further assessed the risk factors for irAEs in HCC patients (n = 77). In multivariate analysis, being ANA+ was the only risk factor for irAEs (OR, 3.957; 95% CI, 1.181-13.253; P = 0.026; Supplementary Table 3), suggesting being ANA+ is positively correlated with irAE incidence in HCC. However, we did not analyze the association of ANA status with irAEs in ICC patients as the small sample size (n = 16), which was limited by the statistical power with 0.224 via the post-hoc power analyses.
Among 34 patients (36.5%) with irAEs, the median time from anti-PD-1 treatment to the onset of irAEs was 2.1 months (range, 1 day to 8.5 months). The time interval between anti-PD-1 treatment and the onset of irAEs was significantly shorter in ANA+ patients compared with the ANA− group [median, 1.7 months (95% CI, 0.992-2.408) vs. 5.0 months (95% CI, 4.070-5.930), P = 0.022]. Moreover, sub-analysis based on ANA titer cut-offs of 1:100, 1:320, and 1:1,000, respectively, showed that the time interval between anti-PD-1 treatment and irAE occurrence decreased with increasing ANA titer (Fig. 5).
Figure 5.
Time intervals between anti-PD-1 treatment and irAE onset. (A) Times from anti-PD-1 treatment to irAE onset in 34 patients with irAEs stratified by ANA status. (B) Median times from anti-PD-1 treatment to irAE onset in all advanced liver cancer patients sub-divided by ANA titer cut-offs of 1:100, 1:320, and 1:1,000, respectively. ANA, antinuclear antibody; anti-PD-1, anti-programmed death-1; irAE, immune-related adverse event. P-values were calculated by the log-rank test
Relationship between ANA status and treatment outcomes
In all patients, the ORR and DCR rates were 17.2% and 28.0%, respectively. ORRs in the ANA+ and ANA− groups were 14.9% and 23.1% (P = 0.310), respectively, and DCRs in ANA+ and ANA− patients were 25.4% and 34.6% (P = 0.317), respectively. Although the ORR and DCR were worse in ANA+ patients than in ANA− patients, none of these parameters reached statistical significance. During the median follow-up time of 30.2 months (95% CI, 20.466-39.867), median PFS and OS were worse in ANA+ patients than in ANA− patients [median PFS, 2.8 months (95% CI, 1.967-3.633) vs. 4.2 months (95% CI, 3.153-5.180), P = 0.043; median OS, 21.1months (95% CI, 12.408-29.792) vs. not reached (range, 1.2-36.1 months), P = 0.041] (Fig. 6). PFS and OS were significant between ANA+ group an ANA- group, whereas ORR and DCR were similar. This may suggest that ANA, reflecting the overall status of the patients, is more closely related to survival benefit from anti-PD-1 treatment, less associated with tumor response. Multivariate analysis showed being ANA+ remained a significant prognostic indicator for poor PFS (HR, 1.680; 95% CI, 1.680-1.010; P = 0.046) and OS (HR, 2.559; 95% CI, 1.123-5.831; P = 0.025; Tables 3 and 4).
Figure 6.
Kaplan–Meier survival curves in advanced liver cancer patients administered anti-PD-1 therapy. (A) PFS in ANA+ and ANA− patients. (B) OS in ANA+ and ANA− patients. ANA, antinuclear antibody; anti-PD-1, anti-programmed death-1; irAE, immune-related adverse event; PFS, progression-free survival; OS, overall survival. P-values were calculated by the log-rank test
Table 3.
Prognostic factors affecting progression-free survival in liver cancer patients receiving anti-PD-1 therapy using univariable and multivariable
| Univariable | Multivariable | |||||
|---|---|---|---|---|---|---|
| HR | 95%CI | P-value | HR | 95%CI | P-value | |
| Age (years) | 1.003 | 0.985–1.003 | 0.747 | |||
| Sex | ||||||
| Male | 1.003 | 0.590–1.706 | 0.991 | |||
| Female | 1 (ref) | |||||
| Diagnosis | ||||||
| ICC | 0.959 | 0.529–0.959 | 0.891 | |||
| HCC | 1 (ref) | |||||
| HBsAg | ||||||
| Positive | 1.010 | 0.622–1.010 | 0.967 | |||
| Negative | 1 (ref) | |||||
| ECOG performance status | ||||||
| 1 | 1.227 | 0.611–1.227 | 0.565 | |||
| 0 | 1 (ref) | |||||
| AFP (ng/mL) | 1.000 | 1.000–1.000 | 0.210 | |||
| Albumin (g/L) | 0.988 | 0.957–0.988 | 0.435 | |||
| γ-GT (U/L) | 1.000 | 0.999–1.000 | 0.332 | |||
| ALT (U/L) | 1.003 | 0.995–1.003 | 0.468 | |||
| ALP (U/L) | 1.000 | 0.999–1.000 | 0.686 | |||
| ANA | ||||||
| Positive | 1.680 | 1.010–1.680 | 0.046 | 1.680 | 1.680–1.010 | 0.046 |
| Negative | 1 (ref) | |||||
| Tumor number | ||||||
| ≥4 | 1.204 | 0.748–1.937 | 0.444 | |||
| <4 | 1 (ref) | |||||
| Tumor size (mm) | 1.000 | 0.994–1.000 | 0.946 | |||
| Metastasis | ||||||
| No | 0.974 | 0.610–0.974 | 0.912 | |||
| Yes | 1 (ref) | |||||
| Vascular invasion | ||||||
| No | 0.984 | 0.631–0.984 | 0.943 | |||
| Yes | 1 (ref) | |||||
| Diagnosis | ||||||
| ICC | 0.959 | 0.529–0.959 | 0.891 | |||
| HCC | 1 (ref) | |||||
ECOG, Eastern Cooperative Oncology Group; AFP, alpha fetoprotein; GGT, ɣ-glutamyl transpeptidase; ALT, alanine aminotransferase; ALP, alkaline phosphatase; HCC, hepatocellular carcinoma; ICC, intrahepatic cholangiocarcinoma; ANA, antinuclear antibody. Data in bold face are statistically significant.
Table 4.
Prognostic factors affecting overall survival in liver cancer patients receiving anti-PD-1 therapy using univariable and multivariable
| Univariable | Multivariable | |||||
|---|---|---|---|---|---|---|
| HR | 95%CI | P-value | HR | 95%CI | P-value | |
| Age (years) | 0.998 | 0.973–1.023 | 0.849 | |||
| Sex | ||||||
| Male | 2.134 | 1.123–4.054 | 0.021 | 2.382 | 1.145–4.557 | 0.009 |
| Female | 1 (ref) | |||||
| Diagnosis | ||||||
| ICC | 0.480 | 0.228–1.012 | 0.054 | |||
| HCC | 1 (ref) | |||||
| HBsAg | ||||||
| Positive | 1.157 | 0.580–2.310 | 0.679 | |||
| Negative | 1 (ref) | |||||
| ECOG performance status | ||||||
| 1 | 1.489 | 0.460–4.825 | 0.507 | |||
| 0 | 1 (ref) | |||||
| AFP (ng/mL) | 1.000 | 1.000–1.000 | 0.164 | |||
| Albumin (g/L) | 0.980 | 0.940–1.023 | 0.354 | |||
| γ–GT (U/L) | 1.000 | 0.999–1.001 | 0.880 | |||
| ALT (U/L) | 0.994 | 0.983–1.005 | 0.313 | |||
| ALP (U/L) | 1.000 | 0.998–1.002 | 0.897 | |||
| ANA | ||||||
| Positive | 2.288 | 1.011–5.179 | 0.047 | 2.559 | 1.123–5.831 | 0.025 |
| Negative | 1 (ref) | |||||
| Tumor number | ||||||
| ≥4 | 1.551 | 0.789–3.052 | 0.203 | |||
| <4 | 1 (ref) | |||||
| Tumor size (mm) | 1.004 | 0.997–1.012 | 0.269 | |||
| Metastasis | ||||||
| No | 0.906 | 0.461–1.781 | 0.776 | |||
| Yes | 1 (ref) | |||||
| Vascular invasion | ||||||
| No | 0.656 | 0.352–1.222 | 0.184 | |||
| Yes | 1 (ref) | |||||
ECOG, Eastern Cooperative Oncology Group; AFP, alpha fetoprotein; GGT, ɣ-glutamyl transpeptidase; ALT, alanine aminotransferase; ALP, alkaline phosphatase; HCC, hepatocellular carcinoma; ICC, intrahepatic cholangiocarcinoma; ANA, antinuclear antibody. Data in bold face are statistically significant.
Discussion
Immune checkpoint inhibitors, especially anti-PD-1, are commonly used in a substantial portion of advanced cancer patients. However, this novel treatment damages the normal tissues in multiple organs in the form of autoimmune-like side effects termed irAEs. Severe and fatal irAEs result in significant morbidity and mortality. Unfortunately, there are no reliable biomarkers for predicting individuals likely to develop irAEs. In this study, peripheral blood ANA titer could predict the development of irAEs in advanced liver cancer patients administered anti-PD-1 therapy, making it a potential sentinel indicator of irAEs to guide future irAE prevention strategy.
Whether autoantibodies, including ANA, could predict the induction of irAEs by anti-PD-1 therapy in cancer patients remains debatable. Previous studies have reported discrepant findings [13, 14]. These inconsistent results may arise from differences in sample size, study location and cancer types, suggesting context-dependent roles for autoantibodies in cancer. In this study, the incidence of irAEs was significantly higher in ANA+ primary liver cancer patients than in ANA− cases. In addition, with ANA titer, the frequency of irAEs increased. Immune-checkpoint inhibitors are increasingly used clinically because of limited therapeutic options for advanced HCC or ICC. Considering the etiological and biological heterogeneities between ICC and HCC, we analyzed the association of ANA status with irAEs, and ANA positivity was the only risk factor for irAE occurrence in HCC patients administered anti-PD-1 treatment. Because of the small number of patients with ICC (n = 16), the statistical power may not be sufficient to detect an association. These results imply that ANA+ liver cancer patients may have enhanced and unwanted immune activation during anti-PD-1 therapy, putting them at higher risk of developing irAEs. Therefore, ANA titer increase can be used as an early warning indicator of irAEs.
Previous studies have reported that a battery of autoantibodies is associated with the occurrence of irAEs in patients with advanced cancer administered the anti-PD-1 antibody nivolumab, and specific autoantibodies can be detected early for monitoring irAEs [15]. The presence of autoantibody markers is associated with the development of irAEs in patients with non-small cell lung cancer administered nivolumab and pembrolizumab, respectively [16]. As a component of autoantibodies, ANA is widely present in the serum of patients with autoimmune diseases, and lung, prostate, uterine, gastrointestinal tract, prostate and liver cancers [17–20]. Although some authors have reported the use of anti-PD-1 therapy in ANA+ patients with multiple malignancies, the sample sizes were small, not including primary liver cancer cases [16, 21, 22]. In this study, up to 67 ANA+ liver cancer patients were included, and multivariate analysis showed the ANA+ status was an independent risk factor for irAEs, with ANA titers having an area under the ROC curve of 0.72, suggesting good predictability.
Most irAEs are classified as autoimmune conditions mediated by immune checkpoint inhibitor-activated T cells, but activated B cells and the production of pathogenic antibodies also play a role. Studies have shown PD-1 is expressed in B cells that mediate humoral immune response regulated by T-cell independent and dependent mechanisms [23, 24]. Anti-PD-1 therapy may activate B cells to produce higher amounts of autoantibodies to cause autoimmune manifestations, triggering irAE development [25, 26]. Compared with ANA- individuals, liver biopsy in ANA+ patients with chronic HCV infection has increased plasma cells, which may be responsible for elevated serum immunoglobulins [27]. In another study examining melanoma patients receiving combined immune checkpoint inhibitors, specific B-cell populations were increased, including plasmablasts that produce antibodies, before the occurrence of irAEs [28].
In HCC patients administered the single anti-PD-1 antibody nivolumab or pembrolizumab, the incidence rates of irAEs were approximately 10-57.7% and 1-14.3% for any grade and grade ≥3 irAEs, respectively [29, 30]. The current results with an overall rate of 36.5% for irAEs of any grade and 8.6% for grade ≥3 irAEs corroborate the above reports. In this study, the time from the initiation of anti-PD-1 treatment to the onset of irAEs had a wide range (1 day to 8.5 months), consistent with previous findings (a few days to nearly a year) [31]. Regardless of grade, most irAEs occurred within 6 months of immunotherapy initiation, as previously reported [31]. The time interval from anti-PD-1 treatment to irAE onset was shorter in ANA+ patients, and as ANA titer increased, irAEs occurred earlier, enabling an appropriate monitoring of irAEs to take preemptive preventive measures.
The association of autoantibodies with the clinical efficacy of immunotherapy is debatable. Studies have shown that increased levels of autoantibodies predict a positive outcome in cancer patients administered anti-PD-1 therapy [16, 22]. However, Barth et al. reported that the presence of autoantibodies at treatment initiation or after treatment is not associated with the therapeutic efficacy of immune checkpoint inhibitors [32]. In the present study, ANA+ patients had shorter PFS and OS after anti-PD-1 treatment, as also found in lung cancer [33, 34]. However, the underlying mechanism is unclear. Recent studies have shown that deficient production of T cell banks after administration of immune checkpoint inhibitors is associated with impaired T-cell-dependent activation of autoreactive B cells and autoantibody production [35, 36]. We also found that the median duration of anti-PD-1 treatment was shorter in ANA+ patients compared with ANA− patients, which might be attributed to elevated incidence of irAEs in the ANA+ group. These could partially explain the poor clinical outcomes observed in ANA+ patients administered anti-PD-1 treatment.
The limitations of this study should be acknowledged. First, this single-center study had inevitable biases due to its retrospective design, e.g., selection bias in patient inclusion. Patients who did not undergo ANA testing were not included in the present study, contributing to a high ANA positive rate. In addition, the sample size was relatively small, without sufficient power for subgroup analyses in ICC patients. Furthermore, the patients were treated with a variety of anti-PD-1 drugs. Future prospective studies are required to confirm the present findings. Lastly, treatment in this study utilized anti-PD-1 antibodies only, and it is unclear whether other immune checkpoint inhibitors such as anti-CTLA-4 antibodies or combined administration of anti-CTLA-4 and anti-PD-1 antibodies would yield similar results.
In summary, ANA+ liver cancer patients are prone to develop irAEs after anti-PD-1 treatment. ANA titer as an early warning indicator could help predict the development of irAEs and treatment outcome in these patients.
Supplementary Material
Acknowledgements
This study was supported by the National Natural Science Foundation of China (grant no. 82073479).
Contributor Information
Shu-Jung Hsu, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China; Department of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai, China.
Yen-Cheng Chao, Department of Pulmonary Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Xia-Hui Lin, Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Shanghai, China.
Hua-Hua Liu, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
Yang Zhang, Department of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai, China.
Wei-Feng Hong, Department of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai, China.
Mao-Pei Chen, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
Xin Xu, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
Lan Zhang, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
Zheng-Gang Ren, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
Shi-Suo Du, Department of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai, China.
Rong-Xin Chen, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
Ethics approval
This study was approved by the Institutional Review Board of Zhongshan Hospital of Fudan University, Shanghai, China (No. B2022-324)
Conflict of interests
The authors declare no conflict of interests.
Data availability
The data are available from the correspondence author upon reasonable request.
Author contributions
S.J.H., Y.C.C., X.H.L., L.H.H., Y.Z., W.F.H., M.P.C., X.X., L.Z., and Z.G.R. contributed to the acquisition, analysis and interpretation of data, and statistical analysis and drafting of the manuscript. S.J.H., Y.C.C., S.S.D., and R.X.C. were responsible for the study concept and design, analysis and interpretation of the data, drafting of the manuscript, and obtaining funding and study supervision. All authors read and approved the final manuscript.
Permission to reproduce (for relevant content)
Not applicable.
The animal research adheres to the ARRIVE guidelines
Not applicable.
Informed consent
The written informed consent of participants was waived due to the retrospective nature of the study.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data are available from the correspondence author upon reasonable request.