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Low HDL-cholesterol levels predict hepatocellular carcinoma development in individuals with liver fibrosis

Open AccessPublished:November 15, 2022DOI:https://doi.org/10.1016/j.jhepr.2022.100627

      Highlights:

      • We propose HDL cholesterol as a bona fide novel marker to predict HCC in patients with NASH.
      • Increased waist circumference and deranged metabolic pathways represent additional predisposing factors among patients with low HDL-c.
      • We provide new insights in the comprehension of underlying mechanism in liver carcinogenesis, thus opening new roads for HCC prevention through the integration of healthy lifestyle and clinical surveillance.

      Abstract

      Background & Aims

      Dysmetabolic conditions could drive liver fibrosis in patients with NAFLD increasing susceptibility to Hepatocellular Carcinoma (HCC). We therefore aimed to identify novel predictive biomarkers of HCC in subjects with and without liver fibrosis.

      Methods

      A total of 1,234 putative metabolic patients was consecutively assessed in our Outpatients Clinic recording clinical and biochemical data and then followed-up with liver ultrasonography for five years to detect HCC onset. For the analysis, population was first divided according to HCC diagnosis; then a further subdivision of subjects who did not develop HCC in two additional groups was performed due to the presence or absence of liver fibrosis at time 0.

      Results

      16 HCC cases were recorded in 5 years. No one of our patients had been diagnosed with cirrhosis before HCC was detected. Compared to no-HCC developing subjects, HCC patients had higher liver transaminases and fibrosis scores at time 0 (p<0.001). In addition, they presented with increased HbA1c levels and lower 25-OH Vitamin D levels (p<0.05). Intriguingly, patients with higher liver fibrosis scores who subsequently developed HCC had lower HDL-cholesterol levels at time 0 (p<0.001). Furthermore, subjecting the 484 patients presenting with lower HDL-c at baseline, we found that waist circumference, and then Vitamin D and HbA1c levels, were significantly different in patients who developed HCC, regardless of liver fibrosis (p<0.05).

      Conclusions

      This study elects HDL-c as a bona fide novel marker to predict HCC in patients with NASH. Increased waist circumference and deranged metabolic pathways represent additional predisposing factors among patients with low HDL-c, highlighting the importance of studying cholesterol metabolism and integrating clinical approaches with dietary regimens and a healthy lifestyle to prevent HCC.

      Lay summary

      Visceral adiposity and its associated conditions, such as chronic inflammation and insulin-resistance, may have a pivotal role in Hepatocellular Carcinoma development. We provide new insights in the comprehension of underlying mechanism in its pathogenesis, shedding light on the involvement of low levels of “good” HDL-cholesterol, and recommend integration of healthy lifestyle with clinical surveillance.

      Graphical abstract

      Keywords

      Introduction

      Hepatocellular carcinoma (HCC) represents the sixth most common neoplasm in terms of incidence and the third leading cause of cancer death
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      . To satisfy the increasing energy demand, cancer cells can either increase the de novo synthesis of FAs and cholesterol or promote the uptake of exogenous lipids. Thus, dietary carbohydrates that drive hepatic de novo lipogenesis and dietary lipids could also contribute to an increased risk of cancer development. Moreover, specific lipid classes - including saturated FAs and cholesterol - have been strongly associated with disease progression
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      .
      High Density Lipoproteins (HDL) display a crucial role in preventing atherosclerosis through the Reverse Cholesterol Transport (RCT) pathway by which dietary cholesterol is conveyed from peripheral tissues to the liver and eliminated from the body with the feces. HDL cholesterol (HDL-c) also shows anti-inflammatory and antioxidant properties, and this is why it is known as “good cholesterol”. Furthermore, a negative correlation between HDL-c level and diagnosis of MetS and NAFLD exists
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      and alterations in HDL formation and remodelling might have a direct impact on liver carcinogenesis
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      . Indeed, under the pressure of hyperinsulinemia, hyperglycaemia, and systemic lipid imbalance, hepatocytes rewire their metabolism, including HDL related pathways, thus priming NAFLD development and its progression to CLD and HCC
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      . The potential role of HDL-c in predicting HCC risk have been intensively debated, especially in patients affected by metabolic diseases, since low HDL is one of the criteria associated with MetS and NAFLD. In the general population, low HDL-c levels are associated with an increased mortality rate for cancer, although the relation follows more a J-shaped pattern rather than an inverse one, possibly due to the presence of some genetic variants that might have adverse effects on health outcomes
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      HDL-C is associated with mortality from all causes, cardiovascular disease and cancer in a J-shaped dose-response fashion: a pooled analysis of 37 prospective cohort studies.
      ,
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      . Among metabolic patients, the single diagnostic criteria of MetS were associated with a higher risk of liver cancer, with low HDL-c alone increasing the risk up to 16%
      • Nderitu P.
      • Bosco C.
      • Garmo H.
      • Holmberg L.
      • Malmström H.
      • Hammar N.
      • et al.
      The association between individual metabolic syndrome components, primary liver cancer and cirrhosis: A study in the Swedish AMORIS cohort: Association between individual MetS components, PLC and Cirrhosis.
      . Also, in a cohort of diabetic patients, an increase of 15 mg/dL in the HDL-c values has been associated with a 9% and 6% diminished risk of cancer in men and women, respectively, this inverse association being still present after stratification of the population by race, BMI, smoking, and medication use
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      . Even if it is still unclear whether the observed association is causal or due to preclinical diseases, as dysmetabolism or increased cholesterol influx in hepatic cells, HDL dysfunctions may represent another possible pathogenic link between MetS, NAFLD and liver cancer, in addition to Insulin Resistance and low-grade inflammation.
      In light of the potential involvement of deranged cholesterol metabolism in cancer development, since an accurate low-cost and non-invasive screening to identify the risk of HCC is still missing, in this study a population of 1,234 metabolic patients was screened for lipid biomarker levels and non-invasive liver fibrosis score APRI, to detect if any additional driving condition exists and if its assessment can be considered in defining new predictive biomarkers for HCC development.

      Patients and METHODS

      Study participants

      Patients’ enrolment, anthropometric, biochemical and clinical variables were recorded in the electronic health register of Metabolic Diseases of the Department of Interdisciplinary Medicine at the “Aldo Moro” University of Bari (Italy) from January 2017 to January 2022. First, a total of 1,545 out-patients suspected of Metabolic Syndrome were enrolled in this study. All participants underwent a physical examination, biochemical assessment and abdominal ultrasound.
      Then, patients with reported alcohol abuse, viral hepatitis, benign or primary liver cancer, Inflammatory Bowel Disease, celiac disease, acute heart diseases (cardiac failure, coronary arterial disease, acute arrhythmias), renal and hepatic failure, infections, secondary hypertension caused by renal or endocrine and neurogenic affections as well as aortic coarctation, chronic systemic inflammatory diseases, and neoplastic diseases with recent onset (less than 10 years) and/or under chemotherapy at baseline were excluded, reaching the number of 1,234 patients included in the study.
      At first ultrasonography assessment, no patients had been diagnosed with cirrhosis, consequently they were screened with liver ultrasonography every year in the following five years, according to our institutional screening and follow-up policy for Metabolic Patients. Statistical analysis was performed on a final total population of 1,234 patients (605 males, 629 females). The study was approved by the Ethics Committee of the Azienda Ospedaliero-Universitaria Policlinico di Bari (Bari, Italy) in accordance with the requirements of the Declaration of Helsinki. Written informed consent for the use of clinical data was obtained from all participants in the study. In accordance with the approved Ethics Committee, only patients who were already 18 years old or more were included.

      Clinical assessment

      Anthropometric assessment was performed using standardized procedures. Briefly, WC was measured at the midpoint between the inferior part of the 12th rib and the anterior-superior iliac crest. Body Mass Index (BMI) was computed as weight (kg) divided by the height (m) squared. Average systolic and diastolic blood pressure (BP) parameters were registered for each patient as mean value from three measurements using a manual sphygmomanometer after a period of rest of at least 15 minutes. Abdominal ultrasound was performed to exclude HCC at time 0 with an Esaote My Lab 70 Gold ultrasound system with 2.5–5 MHz convex probes. The cardiovascular risk (CVR) was calculated using the official Framingham Heart Study estimator for cardiovascular disease in the upcoming 10-years adjusted for lipids.
      APRI and FIB-4 were used as non-invasive liver fibrosis indexes. APRI score was calculated as AST (U/L)/platelet count (× 106/L) × 100. The cut-offs adopted were as follows: APRI<0.5 to identify a fibrosis – free liver, APRI≥0.5 for liver fibrosis and APRI≥1.5 for probable cirrhosis. The FIB-4 index was calculated as age × AST (U/L)/platelet count (×106/L) × √ ALT (U/L). The cut-offs adopted were as followed: FIB-4<1.45 for no or moderate fibrosis 1.45<FIB-4<3.25 for moderate fibrosis, FIB-4≥3.25 for extensive fibrosis or cirrhosis
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      AST to Platelet Ratio Index (APRI) is an easy-to-use predictor score for cardiovascular risk in metabolic subjects.
      . Even if no patients had been previously diagnosed with cirrhosis, Child-Pugh
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      and MELD-Na
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      , scores were also computed in patients who later developed HCC.

      Biochemical measurements

      To analyse biochemical markers of glucose and lipid metabolism, serum was collected after overnight fasting and was processed following standardized biochemical procedures.

      Statistical Analysis

      Descriptive statistical analyses of the study sample were performed, and results were expressed as mean±standard deviation (SD). Comparisons of socio-demographic and clinical variables between two groups were conducted with the t-test (for continuous variables) and the Pearson χ2 test (for categorical variables). Statistical analysis between more than two groups was performed through one-way analysis of variance (ANOVA) followed by Bonferroni post-hoc test, where required. Correlation between continuous variables was also analysed and estimated using Pearson’s Correlation Coefficient (r). P-values lower than 0.05 were considered significant. All statistical analyses were performed using the NCSS 12 Statistical Software, version 12.0.2018 (NCSS, LLC Company) and GraphPad Prism, version 9.1.0 (GraphPad Software; San Diego, USA).

      Results

      Clinical characterization of the study population

      A total of 1,234 participants was enrolled for the present study. All data was generated in an age-adjusted model to minimize age-related significant differences. In order to identify a low-cost and non-invasive predictive factor for HCC, patients were categorized on APRI score levels.
      Among the overall population during the first evaluation, 1,084 patients (498 males and 586 females) showed APRI<0.5, which rules out the presence of liver fibrosis
      • Zhong G.-C.
      • Huang S.-Q.
      • Peng Y.
      • Wan L.
      • Wu Y.-Q.-L.
      • Hu T.-Y.
      • et al.
      HDL-C is associated with mortality from all causes, cardiovascular disease and cancer in a J-shaped dose-response fashion: a pooled analysis of 37 prospective cohort studies.
      , and none of them developed liver cancer in the following five years (group 1, NO HCC-APRI<0.5). Conversely, a total of 150 patients showed APRI≥0.5: of these, 134 (94 males and 40 females) did not develop liver cancer (group 2, NO HCC-APRI≥0.5), whereas 16 patients (13 males and 3 females) developed HCC in the following five years (group 3, HCC-APRI≥0.5).
      Statistical comparisons among the three groups pointed out that HCC-APRI≥0.5 patients exhibited increased body weight, BMI, WC, as well as cardiovascular risk (CVR) at baseline when compared to NO HCC-APRI<0.5 and NO HCC-APRI≥0.5 groups, particularly with the first group. Lower HDL-c, GFR and 25-OH Vitamin D values were observed in HCC-APRI≥0.5 patients when compared to the two other groups. No significant differences were found for hs-PCR, ESR, and white blood cells count. Evaluating non-invasive fibrosis scores, HCC-APRI≥0.5 patients presented significantly higher APRI and FIB-4 compared to those who did not develop HCC. Focusing on liver function parameters, no difference in albumin level was found among the three groups (Table 1). Coherently with the absence of cirrhosis in patients who later developed HCC, in HCC-APRI≥0.5 group normal Bilirubin (1.12±0.61 mg\dL) and INR (1.10±0.13) mean values were detected. Moreover, in these patients we found low Child Pugh (5.88±0.88) and MELD-Na (8.81±1.70) mean scores (Supplementary Table).
      Table 1Clinical characterization of the study population.
      Clinical variableNO HCC-APRI<0.5NO HCC-APRI≥0.5HCC-APRI≥0.5p-value
      1084 M:F (498:586)134 M:F (94:40)16 M:F (13:3)
      Mean ± SDMean ± SDMean ± SD
      Weight (Kg)75.84±3.2291.66±2.9995.99±5.98a<0.05
      BMI (Kg/m2)27.04±4.0831.09±3.21a33.81±5.38a<0.05
      Waist circumference (cm)94.29±2.8897.88±4.93107.43±5.23a<0.05
      Cardiovascular risk (Framingham)16.89±1.0226.48±3.29a27.05±6.93a<0.05
      Sistolic blood pressure (mmHg)127.83±3.29130.77±4.10130.95±11.39NS
      Total cholesterol (mg/dL)169.28±5.21179.34±6.23183.05±10.23NS
      HDL-c (mg/dL)57.39±4.9951.34±5.3032.09±8.83a,b<0.001
      LDL-c (mg/dL)104.34±5.23114.23±6.23107.95±11.32NS
      Triglycerides (mg/dL)120.93±6.22146.24±7.12a162.52±19.23a<0.05
      Glucose (mg/dL)94.78±4.33101.74±7.99108.73±9.47a<0.05
      HbA1c (mmol/mol)33.82±1.9239.77±2.4943.72±5.23a,b<0.05
      TSH (mUI/L)1.74±0.931.8±0.781.60±1.38NS
      FT4 (ng/dL)1.05±0.641.07±0.830.94±0.85NS
      FT3 (pg/mL)2.85±0.942.20±0.923.02±1.04NS
      25-OH Vitamin D (ng/mL)25.48±2.3321.77±1.4814.99±2.99a,b<0.05
      Homocysteine (umol/L)12.42±1.7314.94±1.0214.89 ±7.34NS
      Folate (ng/mL)6.75±1.326.23±1.045.25±2.94NS
      hs-CRP (mg/L)4.74±0.943.73±2.83.59±1.79NS
      ESR (mm/h)17.05±15.218.3 ±17.716.8±14.6NS
      Iron (ug/dL)108.97±6.43111.97±7.9991.85 ±15.93NS
      Serum Ferritin (ng/mL)131.57±7.94155.72±7.93153.09±149.23NS
      Creatinine (mg/dL)0.91±0.320.93±0.750.93±0.73NS
      GFR (mL/min)99.23±2.4391.77±1.48a86.41±6.20a<0.05
      WBC (x103/μl)6.05±1.106.77±0.847.33±1.75NS
      Hemoglobin (g/dL)14.55±2.9114.55±3.6214.06±2.93NS
      Neutrophils (%)56.28±3.2356.28±3.2159.81±4.29NS
      Eosinophils (%)2.85±0.932.85±0.843.67±0.99NS
      Basophils (%)0.58±0.350.58±0.320.64±0.75NS
      Lymphocytes (%)31.74±2.1431.74±3.2929.77±6.92NS
      Monocytes (%)6.60±1.026.60±1.019.41±2.92NS
      Platelet count (x103/μL)241.97±6.55167.88±4.62a187.75±15.23a,b<0.05
      GGT (U/L)30.40±3.2355.70±5.93a79.71±19.83a,b<0.001
      AST (U/L)20.70±1.4856.07±3.29a51.82±4.73a<0.05
      ALT (U/L)30.59±1.8349.98±2.94a54.24±5.28a,b<0.05
      ALP (U/L)48.95±2.0253.95±2.0470.76±14.23a,b<0.05
      Insulin (uUI/mL)10.88±1.3913.72±1.8914.27±2.93NS
      NL RATIO1.98±0.931.81±0.842.48±0.99NS
      LM RATIO5.46±0.995.57±0.845.79±1.49NS
      MH RATIO8.18±1.528.77±1.3413.89±1.48a,b<0.05
      ML RATIO0.21±0.120.33±0.090.29±0.39NS
      FIB-4 Index1.12±0.991.88±0.43a2.16±0.56a<0.001
      APRI Score0.31±0.080.62±0.20a0.65±0.23a<0.001
      Data is presented as mean ± SD (standard deviation). Comparisons were performed using one-way ANOVA test followed by Bonferroni’s post-hoc test. Lowercase letter (a) indicates significant difference in comparison with APRI<0.5-NO HCC group only, (b) indicates significant difference in comparison with NO HCC-APRI≥0.5 only. These comparisons were performed by Student T-test.
      Abbreviations: Hepatocellular carcinoma, HCC; AST to Platelet Ratio Index, APRI; Body Mass Index, BMI; high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; glycosylated hemoglobin, HbA1c; high-sensitivity C reactive protein, hs-CRP; erythrocyte sedimentation rate, ESR; Glomerular Filtration Rate, GFR; White blood cells, WBC; gamma-glutamyl transferase, GGT; aspartate transaminase, AST; alanine transaminase, ALT; alkaline phosphatase, ALP; Neutrophil to Lymphocyte Ratio, NL RATIO; Lymphocyte to Monocyte Ratio, LM RATIO; Monocyte to HDL Ratio, MH RATIO; Monocyte to Lymphocyte Ratio, ML RATIO.

      HCC predicting biomarkers

      To better understand the link between visceral obesity and HCC development, we compared WC levels among groups, showing that patients who developed HCC had increased WC at baseline, especially compared to the NO HCC-APRI<0.5 group (Fig.1a). The analysis of CVR, glucose and HbA1c values revealed that these parameters were all increased in the HCC-APRI≥0.5 group, especially when compared to NO HCC-APRI≥0.5 patients (Fig.1b-d).
      Figure thumbnail gr1
      Fig. 1Metabolic Syndrome-associated biomarkers in relation to liver fibrosis and development of HCC. Comparison of Metabolic Syndrome-associated biomarkers among subjects without fibrosis (NO HCC – APRI<0.5) and those with liver fibrosis who will not develop HCC (NO HCC – APRI≥0.5) or develop HCC (HCC – APRI≥0.5). The box plots show the median (second quartile), first and third quartile, Tukey whiskers go 1.5 times the interquartile distance or to the highest or lowest point, whichever is shorter. Any data beyond these whiskers are shown as points. Comparisons were performed using one-way ANOVA test followed by Bonferroni’s post-hoc test. Multiple comparison was performed by Student T-test. Lowercase letter indicates significant difference with NO HCC-APRI<0.5 (a) and NO HCC–APRI≥0.5 (b). Abbreviations: glycosylated hemoglobin, HbA1c.
      Given the potential role of HDL-c in HCC pathogenesis
      • Zhao L.
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      • Zhang X.
      Dietary Fats, Serum Cholesterol and Liver Cancer Risk: A Systematic Review and Meta-Analysis of Prospective Studies.
      , we considered the baseline level of HDL-c in the study population. Intriguingly, we observed that HDL-c was significantly lower at baseline in HCC-APRI≥0.5 patients, compared to both other groups (Fig.1e). This could indicate that patients with fibrosis who will develop HCC display a significantly lower HDL-c level. In contrast, Triglycerides (TG) levels were significantly higher in the HCC-APRI≥0.5 group (Fig.1f).
      Transaminases and liver fibrosis scores
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      Total cholesterol, alanine aminotransferase and the risk of primary liver cancer: A population-based prospective study.
      may be predictive of liver cancer development, therefore, we further analysed AST, ALT, GGT and alkaline phosphatase (ALP) levels, which were all significantly higher in the HCC-APRI≥0.5 group (Fig.2a-d). In particular, AST levels were higher also in NO HCC-APRI≥0.5 patients, whereas the more liver-specific markers ALT and GGT were significantly higher in the HCC-APRI≥0.5 group, even when compared to the NO HCC-APRI≥0.5 one. Therefore, since transaminases are used to determine liver fibrosis scores, it is not surprising that APRI and FIB-4 indexes were higher in the HCC-APRI≥0.5 group (Fig.3a-b).
      Figure thumbnail gr2
      Fig. 2Transaminases level in relation to liver fibrosis and development of HCC. Comparison of Transaminases level among subjects without fibrosis (NO HCC – APRI<0.5) and those with liver fibrosis who will not develop HCC (NO HCC – APRI≥0.5) or develop HCC (HCC – APRI≥0.5). The box plots show the median (second quartile), first and third quartile, Tukey whiskers go 1.5 times the interquartile distance or to the highest or lowest point, whichever is shorter. Any data beyond these whiskers are shown as points. Comparisons were performed using one-way ANOVA test followed by Bonferroni’s post-hoc test. Multiple comparison was performed by Student T-test. Lowercase letter indicates significant difference with with NO HCC-APRI<0.5 (a) and NO HCC–APRI≥0.5 (b). Abbreviations: aspartate transaminase, AST; alanine transaminase, ALT; gamma-glutamyl transferase, GGT; alkaline phosphatase, ALP.
      Figure thumbnail gr3
      Fig. 3Non-invasive liver fibrosis scores, Insulin, and Vitamin D levels in relation to liver fibrosis and development of HCC. Comparison among subjects without fibrosis (NO HCC – APRI<0.5) and those with liver fibrosis who will not develop HCC (NO HCC – APRI≥0.5) or develop HCC (HCC – APRI≥0.5.The box plots show the median (second quartile), first and third quartile, Tukey whiskers go 1.5 times the interquartile distance or to the highest or lowest point, whichever is shorter. Any data beyond these whiskers are shown as points. Comparisons were performed using one-way ANOVA test followed by Bonferroni’s post-hoc test. Multiple comparison was performed by Student T-test. Lowercase letter indicates significant difference with NO HCC-APRI<0.5 (a) and NO HCC–APRI≥0.5 (b). Abbreviations: AST to Platelet Ratio Index, APRI; Fibrosis-4 Index, FIB-4 Index.
      Impaired blood glucose and insulin sensitivity have been variably associated with HCC
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      , and in our population, HCC-APRI≥0.5 patients show significantly higher levels of glucose and HbA1c compared to the other two groups. Moreover, a significant difference was found comparing insulin levels, particularly between NO HCC-APRI<0.5 and HCC-APRI≥0.5 patients (Fig.3c). Finally, to better understand the potential role of Vitamin D in liver cancer prediction
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      , levels of 25-OH Vitamin D were analysed, observing significantly lower baseline values in patients who later developed HCC (Fig.3d).

      HCC prognostic factors in liver fibrosis

      Alterations in WC, HDL-c, TG, glucose, and 25-OH Vitamin D levels have been frequently associated with HCC, and data presented in this study confirms these associations. To further study the relevance of the observations, correlation between these variables in NO HCC-APRI≥0.5 and HCC-APRI≥0.5 patients were evaluated. A strong negative correlation between WC and HDL-c level was detected in HCC-APRI≥0.5 patients (r=0.93, p<0.01) but not in NO HCC-APRI≥0.5 patients (r=0.27, p=NS) (Fig.4a). Similarly, the correlation between increased WC parameters and high TG levels is stronger in HCC-APRI≥0.5 patients (r=0.8, p<0.01) than in NO HCC-APRI≥0.5 patients (r=0.31; p<0.05) (Fig.4b). Analysis of the association between glucose level and WC revealed a stronger significant correlation in HCC-APRI≥0.5 (r=0.63, p<0.05) than in NO HCC-APRI≥0.5 patients (Fig.4c). Finally, a linear regression analysis between 25-OH Vitamin D and HDL had been performed in NO HCC-APRI≥0.5 and HCC-APRI≥0.5 groups, revealing a significant negative correlation only in the second one (Fig.4d). In particular, HCC-APRI≥0.5 patients displayed low HDL-c (<45 mg/dL) with a corresponding low level of Vitamin D (<20 ng/mL), confirming that patients developing HCC are characterized by a concomitant lower level of both HDL-c and Vitamin D.
      Figure thumbnail gr4
      Fig. 4Relationships of waist circumference with metabolic biomarker and of HDL-c with Vitamin D level in patients with APRI≥0.5. r indicates Pearson’s Correlation Coefficient; p indicates statistical significance.

      HCC prognostic factors in patients with low HDL-c

      Dot plot representation of HDL values in the three groups showed that there is a significant number of patients who, despite not being affected by HCC, exhibited lower HDL-c, similar to those in the HCC-APRI≥0.5 group (Fig.5a). To explain why, ceteris paribus, some patients with low HDL developed cancer, the reported maximum value of HDL-c (50.00 mg/dL) in HCC-APRI≥0.5 patients was set as a cut-off value for the overall population, and then biochemical and anthropometric variables which had showed a significant difference in the first analysis were further analysed in 484 patients with HDL-c ≤50.00 mg/dL (374 belonging to the first group, 94 belonging to the second one, 16 developing HCC). Multiple comparisons among the three groups were performed, in an age-adjusted model (Table 2). The statistical significance of higher GGT value was present when comparing both NO HCC-APRI ≥0.5 and HCC-APRI≥0.5 groups to NO HCC-APRI<0.5 group, so does not reliably characterize HCC patients among subjects with HDL-c <50mg/dL and liver fibrosis (Fig.5b). 25-OH Vitamin D kept a significant decrease (Fig.5c). Similarly, although BMI and body weight as well as glycemia retained a positive trend, they lost their statistical power among patients with lower HDL. Conversely, higher HbA1c and WC, strongly maintained their statistical significance (p<0.05) (Fig.5d-e).
      Figure thumbnail gr5
      Fig. 5Comparison among subjects with HDL-c ≤ 50 mg/dL. (a) Dot and box plots representation of HDL-c in subjects without fibrosis (NO HCC – APRI<0.5) and those with liver fibrosis who will not develop HCC (NO HCC – APRI≥0.5) or develop HCC (HCC – APRI≥0.5). Dashed line shows the maximum HDL-c value in HCC-APRI≥0.5 group, that is 50 mg/dL. Comparison of GGT level (b), 25-OH Vitamin D (c), HbA1c (d), and Waist Circumference (e) in these three groups among patients with HDL-c ≤ 50 mg/dL. The box plots show the median (second quartile), first and third quartile, Tukey whiskers go 1.5 times the interquartile distance or to the highest or lowest point, whichever is shorter. Any data beyond these whiskers are shown as points. Comparisons were performed using one-way ANOVA test followed by Bonferroni’s post-hoc test. Multiple comparison was performed by Student T-test. Lowercase letter indicates significant difference with (a) NO HCC-APRI<0.5 and (b) NO HCC – APRI≥0.5. Abbreviations: gamma-glutamyl transferase, GGT; waist circumference, WC.
      Table 2Clinical characterization of the study population with HDL-c ≤ 50 mg/dL.
      Clinical variableNO HCC APRI<0.5NO HCC APRI≥0.5HCC-APRI≥0.5p-value
      374 M:F (229:145)94 M:F (62:32)16 M:F (13:3)
      Mean ± SDMean ± SDMean ± SD
      Weight (Kg)82.01±16.0183.77±17.5896.07±19.46NS
      BMI (Kg/m2)29.16±5.9329.61±5.7532.59±6.89NS
      Waist circumference (cm)98.83±14.04103.52±14.10114.30±11.82a,b<0.05
      Cardiovascular risk (Framingham)22.23±18.1834.30±21.97a34.74±18.98a<0.05
      HDL-c (mg/dL)42.55±6.2339.87±6.1636.72±8.31a,b<0.05
      Triglycerides (mg/dL)175.08±45.60179.13±43.58184.4±45.92NS
      Glucose (mg/dL)109.62±39.18108.59±29-02131.3±65.21NS
      HbA1c (mmol/mol)44.44±15.1642.39±12.2453.11±19.31a,b<0.05
      25-OH Vitamin D(ng/mL)19.48±9.1520.76±9.8317.73±7.26a,b<0.05
      hs-CRP (mg/L)4.94±4.993.77±2.343.93±2.08NS
      ESR (mm/h)17.76±15.2719.88±19.0318.83±16.51NS
      GFR (mL/min)99.23±2.4391.77±1.48a86.41±6.20a<0.05
      Platelet count (103/μL)246.86±65.03180.69±46.68a206.7±49.86a<0.05
      GGT (U/L)34.30±23.6655.35±33.58a51±25.02a<0.05
      AST (U/L)20.50±5.8141.23±22.14a36.6±8.93a<0.05
      ALT (U/L)29.45±11.6756.93±33.98a47±18.16a,b<0.05
      ALP (U/L)73.36±22.6175.58±22.6070.62±20.13NS
      Albumin (g/dL)4.46±0.044.42±0.064.46±0.27NS
      MH RATIO10.93±4.4410.21±3.8110.21±3.81NS
      FIB-4 Index0.95±0.452.11±1.18a1.52±1.25a,b<0.05
      APRI Score0.28±0.010.74±0.34a0.54±0.26a<0.05
      Data is presented as mean ± SD (standard deviation). Comparisons were performed using one-way ANOVA test followed by Bonferroni’s post-hoc test. Lowercase letter (a) indicates significant difference in comparison with APRI<0.5-NO HCC group only, (b) indicates significant difference in comparison with NO HCC-APRI≥0.5 only. These comparisons were performed by Student T-test.
      Abbreviations: Hepatocellular carcinoma, HCC; AST to Platelet Ratio Index, APRI; Body Mass Index, BMI; high-density lipoprotein cholesterol, HDL-c; glycosylated hemoglobin, HbA1c; high-sensitivity C reactive protein, hs-CRP; erythrocyte sedimentation rate, ESR; Glomerular Filtration Rate, GFR; gamma-glutamyl transferase, GGT; aspartate transaminase, AST; alanine transaminase, ALT; alkaline phosphatase, ALP; Monocyte to HDL Ratio, MH RATIO.

      Discussion

      In this study, low HDL-c levels were associated with an increased risk of developing HCC, thus representing an important discriminant factor to predict the onset of HCC among patients without cirrhosis but with liver fibrosis, one of the clinical manifestations of NASH. From a clinical perspective, it is crucial to discriminate timely those patients with fibrosis presenting with a higher risk of progression towards severe forms of liver disease, including HCC.
      Although the degree of fibrosis is the strongest predictive factor for liver-related and all-cause mortality, the causative factors for NASH progression towards fibrosis are still not known
      • Desterke C.
      • Chiappini F.
      Lipid Related Genes Altered in NASH Connect Inflammation in Liver Pathogenesis Progression to HCC: A Canonical Pathway.
      and HDL-c levels have been also proposed to predict decompensation in patients with Chronic Liver Disease
      • Rao B.H.
      • Nair P.
      • Koshy A.K.
      • Krishnapriya S.
      • Greeshma C.R.
      • Venu R.P.
      Role of High-Density Lipoprotein Cholesterol (HDL-C) as a Clinical Predictor of Decompensation in Patients with Chronic Liver Disease (CLD).
      and associated to a more aggressive phenotype
      • Akkiz H.
      • Carr B.I.
      • Guerra V.
      • Donghia R.
      • Yalçın K.
      • Karaoğullarından U.
      • et al.
      Plasma lipids, tumor parameters and survival in HCC patients with HBV and HCV.
      , recurrence after curative resections
      • Tian L.
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      • Dai Q.
      • et al.
      A new use for an old index: preoperative high-density lipoprotein predicts recurrence in patients with hepatocellular carcinoma after curative resections.
      , and worse outcomes in HCC patients
      • Jiang S.-S.
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      • Jiang L.
      • Zhang Y.-J.
      • Pan K.
      • Pan Q.-Z.
      • et al.
      The clinical significance of preoperative serum cholesterol and high-density lipoprotein-cholesterol levels in hepatocellular carcinoma.
      .
      Investigating whether the relationship between HDL-c and cancer incidence is causative, Pirro et al. concluded that several HDL pathway’s components are crucially connected with cancer cells proliferation and survival, speculating that impaired RCT may contribute to cancer onset and progression
      • Pirro M.
      • Ricciuti B.
      • Rader D.J.
      • Catapano A.L.
      • Sahebkar A.
      • Banach M.
      High density lipoprotein cholesterol and cancer: Marker or causative?.
      . Hepatic cancer cell displays a higher receptor-mediated uptake of HDL than normal cells, thus potentially explaining the low plasma HDL-c level found in HCC patients
      • Jiang S.-S.
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      • Jiang L.
      • Zhang Y.-J.
      • Pan K.
      • Pan Q.-Z.
      • et al.
      The clinical significance of preoperative serum cholesterol and high-density lipoprotein-cholesterol levels in hepatocellular carcinoma.
      . Moreover, alterations of Liver X Receptors (LXRs), the master regulator of cholesterol homeostasis and RCT, are involved in the progression of HCC
      • Long H.
      • Guo X.
      • Qiao S.
      • Huang Q.
      Tumor LXR Expression is a Prognostic Marker for Patients with Hepatocellular Carcinoma.
      . Indeed, in physiological conditions, increased amount of the cholesterol by-products oxysterols activates LXRs and promote the expression of their target genes, keeping cholesterol level within a specific range inside the cell and intensifying the production of HDL in liver, adipose tissue, adrenal glands, intestine, and macrophages. However, in rapidly growing cells, characterised by a high-energy demand (just as in cancer cells) a paradoxical suppression of LXR-driven pathways has been detected, suggesting a possible uncoupling between the high cholesterol concentration needed to sustain active proliferation and LXRs activation
      • Lo Sasso G.
      • Celli N.
      • Caboni M.
      • Murzilli S.
      • Salvatore L.
      • Morgano A.
      • et al.
      Down-regulation of the LXR transcriptome provides the requisite cholesterol levels to proliferating hepatocytes.
      ,
      • Lo Sasso G.
      • Bovenga F.
      • Murzilli S.
      • Salvatore L.
      • Di Tullio G.
      • Martelli N.
      • et al.
      Liver X Receptors Inhibit Proliferation of Human Colorectal Cancer Cells and Growth of Intestinal Tumors in Mice.
      .
      In our population, around 30% of patients who did not develop HCC had low levels of HDL, suggesting that higher HDL-c level might protect from developing HCC and that conversely, in patients with lower HDL-c, some additional driving metabolic factors may justify the disease onset. To this end, we found HbA1c and WC were significantly increased in patients who developed HCC and concomitantly presenting with low HDL-c at time 0. The role of WC, but not BMI, in predicting HCC among patients with lower HDL-c highlights one more time the importance of assessing abdominal fat in clinical evaluation and support the concept that visceral adiposity and associated conditions, such as low-grade inflammation, adipokines release, and insulin-resistance, may have a pivotal role in carcinogenesis
      • Crudele L.
      • Piccinin E.
      • Moschetta A.
      Visceral Adiposity and Cancer: Role in Pathogenesis and Prognosis.
      . Consequently, those conditions leading to fat accumulation, such as high-calorie intake and unbalanced lifestyles, could boost HCC development in patients at high risk, mediated by low HDL-c. Accumulation of hepatic lipids, due to altered metabolism or dietary choices (including high carb - high fat diets), favours the production of potentially toxic metabolites, which damage the liver with a consequent increase of scarred hepatic areas
      • Masuzaki R.
      • Karp S.J.
      • Omata M.
      NAFLD as a risk factor for HCC: new rules of engagement?.
      ,
      • Bovenga F.
      • Sabbà C.
      • Moschetta A.
      Uncoupling nuclear receptor LXR and cholesterol metabolism in cancer.
      . Subsequent progressive inflammation and, eventually, chronic necroinflammation and fibrosis, compensatory proliferation, and a chronic regenerative environment contribute to HCC development
      • Anstee Q.M.
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      • Govaere O.
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      From NASH to HCC: current concepts and future challenges.
      ,
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      • Castellanos A.
      • Attolini C.S.-O.
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      Targeting metastasis-initiating cells through the fatty acid receptor CD36.
      . Also, preclinical models have highlighted the impact of dietary choices and excessive caloric-intake on cancer onset and development
      • Chen M.
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      ,
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      • Yeh M.M.
      • Chen Y.
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      Pcsk9 Deletion Promotes Murine Nonalcoholic Steatohepatitis and Hepatic Carcinogenesis: Role of Cholesterol.
      . In this context, it has been shown that dietary cholesterol can also modulate the intestinal microbiota, contributing to the sequential progression of steatosis to steatohepatitis, fibrosis and finally HCC in mice
      • Zhang X.
      • Coker O.O.
      • Chu E.S.
      • Fu K.
      • Lau H.C.H.
      • Wang Y.-X.
      • et al.
      Dietary cholesterol drives fatty liver-associated liver cancer by modulating gut microbiota and metabolites.
      .
      Furthermore, when analysing the subpopulation presenting with low HDL-c, we found that reduced 25-OH Vitamin D level was still associated to the HCC patient population as already detected in the first analysis. At a molecular level, this liposoluble hormone precursor is transformed into 1,25-OH Vitamin D which is the active hormone form binding to the Vitamin D Receptor (VDR), a metabolic nuclear receptor, similar to LXRs, controlling expression of genes involved in bile acid synthesis from cholesterol, calcium metabolism, cell differentiation, apoptosis, and immunity
      • El-Sharkawy A.
      • Malki A.
      Vitamin D Signaling in Inflammation and Cancer: Molecular Mechanisms and Therapeutic Implications.
      . Hepatocytes do not express VDR, while hepatic stellate cells do; therefore, one could speculate that hypovitaminosis D could negatively influence the hepatic inflammation microenvironment, ultimately laying the ground for hepatic tumorigenesis. After all, chronic low-grade inflammation caused by visceral adiposopathy is another MetS feature that has been proposed to explain higher cancer incidence in obese subjects. In a previous study, the combination of elevated iron and low HDL-c plasma levels at the baseline has been proposed to predict cancer risk over almost 15 years
      • Mainous A.G.
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      . However, in our study, no significant differences in iron levels were detected at the baseline.
      In conclusion, our data indicates that low HDL levels together with adiposopathy and its associated biomarkers may be considered as useful variables in defining and validating new non-invasive prognostic factors for HCC development in patients with liver fibrosis. Furthermore, this study provides novel insights into non-invasive prognostic factors with HDL-c level being a significant predictor of HCC development in high-risk patients with liver fibrosis and metabolic derangement. Although this study does not disclose a net molecular mechanism underlying the presented observation, it does provide rationale for studying cholesterol metabolism in HCC. Finally, from a clinical perspective, our findings recommend reducing adiposopathy, and targeting its associated dysmetabolic conditions, in patients with liver fibrosis and low HDL cholesterol, to revert NASH and possibly lower HCC risk, by integrating clinical and therapeutic approaches with dietary regimens and healthy lifestyle.

      Conflict of interest statement

      The authors declare no conflict of interest.

      Data Availability Statement

      The data that supports the findings of this study is available from the corresponding author upon reasonable request.

      Financial support statement

      A.M. is funded by Italian Association for Cancer Research - AIRC IG 2019 Id 23239; EU-JPI HDL-INTIMIC –MIUR FATMAL; MIUR-PON “R&I” 2014–2020 “BIOMIS” cod.ARS01_01220; POR Puglia FESR—FSE 2014– 2020, “INNOMA” cod. 4TCJLV4. E.P. is funded by PON AIM1853334—Attività 2, linea 1.

      Author Contributions

      Conceptualization, A.M.; methodology-visualization, L.C. and C.D.M.; software-formal analysis, C.D.M.; investigation, L.C., C.D.M., and E.D.B.; resources, G.P. and P.S.; data curation, L.C., C.D.M, E.D.B.; writing—original draft preparation, L.C., R.M.G., M.C. and E.P.; writing—review and editing, E.P., A.M.; supervision, C.S., E.P., and A.M.; project administration, A.M.; funding acquisition, A.M. All authors have read and agreed to the published version of the manuscript.

      Acknowledgements

      We thank the physicians and nurses of the Unità Operativa Complessa Universitaria di Medicina Interna “Cesare Frugoni” of the Azienda Ospedaliero—Universitaria Policlinico di Bari for their help and support during the study. A special thanks to Roberta Le Donne and Antonella De Ruvo for their support.

      Abbreviations

      APRI
      AS T to Platelet Ratio Index
      BMI
      Body Mass Index
      BP
      Blood Pressure
      CASH
      Cholesterol Associated Steatohepatitis
      CVR
      Cardiovascular Risk
      DAP
      Diastolic Arterial Blood Pressure
      DM
      Diabetes Mellitus
      FA
      Fatty Acid
      FPG
      Fasting Plasma Glucose
      HbA1c
      Glycosylated Hemoglobin
      HCC
      Hepatocellular Carcinoma
      HDL
      High-density Lipoprotein
      HDL-c
      High-Density Lipoprotein-cholesterol
      LDL-R
      Low-Density Lipoprotein Receptor
      LXR
      Liver X Receptors
      MetS
      Metabolic Syndrome
      NAFLD
      Non-Alcoholic Fatty Liver Disease
      NASH
      Non-Alcoholic Steatohepatitis
      PLC
      Primary Liver Cancer
      RCT
      Reverse Cholesterol Transport
      SAP
      Systolic Arterial Blood Pressure
      TG
      Triglycerides
      WC
      Waist Circumference

      Appendix A. Supplementary data

      The following is the supplementary data to this article:

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