Preoperative elevated plasma fibrinogen level predicts tumor recurrence and poor prognosis in patients with hepatocellular carcinoma

Differential Protease Specificity by Collagenase as a Novel Approach to Serum Proteomics That Includes Identification of Extracellular Matrix Proteins without Enrichment

Circulating extracellular matrix (ECM) proteins are serological biomarkers of interest due to their association with pathologies involving disease processes such as fibrosis and cancers. In this study, we investigate the potential for serum biomarker research using differential protease specificity (DPS), leveraging alternate protease specificity as a targeting mechanism to selectively digest circulating ECM protein serum proteins. A proof-of-concept study is presented using serum from patients with cirrhotic liver or hepatocellular carcinoma. The approach uses collagenase DPS for digestion of deglycosylated serum and liquid-chromatography-trapped ion mobility-tandem mass spectrometry (LC-TIMS-MS/MS) to enhance the detection of ECM proteins in serum. It requires no sample enrichment and minimizes the albumin average precursor intensity readout to less than 1.2%. We further demonstrate the capabilities for using the method as a high-throughput matrix-assisted laser/desorption ionization mass spectrometry (MALDI-MS) assay coupled with reference library searching. A goal is to improve the depth and breadth of biofluid proteomics for noninvasive assays.

Prediction model for hepatocellular carcinoma recurrence after hepatectomy: Machine learning-based development and interpretation study

Background

Identifying patients with hepatocellular carcinoma (HCC) at high risk of recurrence after hepatectomy can help to implement timely interventional treatment. This study aimed to develop a machine learning (ML) model to predict the recurrence risk of HCC patients after hepatectomy.

Methods

We retrospectively collected 315 HCC patients who underwent radical hepatectomy at the Third Affiliated Hospital of Sun Yat-sen University from April 2013 to October 2017, and randomly divided them into the training and validation sets at a ratio of 7:3. According to the postoperative recurrence of HCC patients, the patients were divided into recurrence group and non-recurrence group, and univariate and multivariate logistic regression were performed for the two groups. We applied six machine learning algorithms to construct the prediction models and performed internal validation by 10-fold cross-validation. Shapley additive explanations (SHAP) method was applied to interpret the machine learning model. We also built a web calculator based on the best machine learning model to personalize the assessment of the recurrence risk of HCC patients after hepatectomy.

Results

A total of 13 variables were included in the machine learning models. The multilayer perceptron (MLP) machine learning model was proved to achieve optimal predictive value in test set (AUC = 0.680). The SHAP method displayed that γ-glutamyl transpeptidase (GGT), fibrinogen, neutrophil, aspartate aminotransferase (AST) and total bilirubin (TB) were the top 5 important factors for recurrence risk of HCC patients after hepatectomy. In addition, we further demonstrated the reliability of the model by analyzing two patients. Finally, we successfully constructed an online web prediction calculator based on the MLP machine learning model.

Conclusion

MLP was an optimal machine learning model for predicting the recurrence risk of HCC patients after hepatectomy. This predictive model can help identify HCC patients at high recurrence risk after hepatectomy to provide early and personalized treatment.

Preoperative alpha fetoprotein, total bilirubin, fibrinogen, albumin, and lymphocytes predict postoperative survival in hepatocellular carcinoma

AIMS

Our study focused on exploring the feasible prognostic laboratory parameters of HCC and establishing a score model to estimate individualized overall survival (OS) in HCC after resection.

METHODS

Four hundred and sixty-one patients with HCC who underwent hepatectomy between January 2010 and December 2017 was enrolled in this investigation. Cox proportional hazards model was conducted to analyze the prognostic value of laboratory parameters. The score model construction was based on the forest plot results. Overall survival was evaluated by Kaplan-Meier method and the log-rank test. The novel score model was validated in an external validation cohort from a different medical institution.

RESULTS

We identified that alpha fetoprotein (AFP), total bilirubin (TB), fibrinogen (FIB), albumin (ALB), and lymphocyte (LY) were independent prognostic factors. High AFP, TB, FIB (HR > 1, p < 0.05), and low ALB, LY (HR < 1, p < 0.05) were associated with the survival of HCC. The novel score model of OS based on these five independent prognostic factors achieved high C-index of 0.773 (95% confidence interval [CI]: 0.738-0.808), which was significantly higher than those of the single five independent factors (0.572-0.738). The score model was validated in the external cohort whose C-index was 0.7268 (95% CI: 0.6744-0.7792).

CONCLUSION

The novel score model we established was an easy-to-use tool which could enable individualized estimation of OS in patients with HCC who underwent curative hepatectomy.

Prognostic factors for disease-free survival in postoperative patients with hepatocellular carcinoma and construction of a nomogram model

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common type of liver cancer and has a high risk of invasion and metastasis along with a poor prognosis.

AIM

To investigate the independent predictive markers for disease-free survival (DFS) in patients with HCC and establish a trustworthy nomogram.

METHODS

In this study, 445 patients who were hospitalized in The First Affiliated Hospital of Anhui Medical College between December 2009 and December 2014 were retrospectively examined. The survival curve was plotted using the Kaplan–Meier method and survival was determined using the log-rank test. To identify the prognostic variables, multivariate Cox regression analyses were carried out. To predict the DFS in patients with HCC, a nomogram was created. C-indices and receiver operator characteristic curves were used to evaluate the nomogram's performance. Decision curve analysis (DCA) was used to evaluate the clinical application value of the nomogram.

RESULTS

Longer DFS was observed in patients with the following characteristics: elderly, I–II stage, and no history of hepatitis B. The calibration curve showed that this nomogram was reliable and had a higher area under the curve value than the tumor node metastasis (TNM) stage. Moreover, the DCA curve revealed that the nomogram had good clinical applicability in predicting 3- and 5-year DFS in HCC patients after surgery.

CONCLUSION

Age, TNM stage, and history of hepatitis B infection were independent factors for DFS in HCC patients, and a novel nomogram for DFS of HCC patients was created and validated.

TP53 positivity combined with high fibrinogen expression defines a subtype of oral squamous cell carcinoma with an unfavorable prognosis

The number of deaths due to oral squamous cell carcinoma (OSCC), a malignant tumor of the oral cavity, is on the increase. We examined fibrinogen (FIB) expression in patients with OSCC and developed novel immunoprofile classification methods that include FIB. The plasma FIB level in patients with OSCC was elevated compared with that in patients with non-tumor oral disease (non-T); using a cut-off point of 342 mg/dL, we found the area under the curve-receiver operating characteristic level for OSCC was 0.745. Similarly, FIB expression in OSCC tissues was significantly higher compared with that in non-T tissues. Hierarchical clustering based on the immunoprofile of several markers including FIB, p53, and p16 revealed four groups that could be used to categorize OSCC cases (referred to as immunoprofile subtypes [IPS], I-IV). Tumors in IPS-II, which were FIB+/p53+, were associated with a significantly worse overall survival (OS) when compared with the other subtypes. We conclude that our IPS classification system can facilitate prognostic evaluation in OSCC, and that quantification of FIB is an important component of the classification strategy for this disease.

Impact of Change in Body Composition during Follow-Up on the Survival of GEP-NET

Background: Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are heterogeneous rare diseases causing malnutrition and cachexia in which the study of body composition may have an impact in prognosis. Aim: Evaluation of muscle and fat tissues by computed tomography (CT) at the level of the third lumbar (L3 level) at diagnosis and at the end of follow-up in GET-NET patients and their relationships with clinical and biochemical variables as predictors of survival. Methodology: Ninety-eight GEP-NET patients were included. Clinical and biochemical parameters were evaluated. Total body, subcutaneous, visceral and total fat areas and very low-density, low-density, normal density, high-density, very high-density and total muscle areas were obtained from CT images. Results: Body composition measures and overall mortality correlated with age, ECOG (Eastern Cooperative Oncology Group performance status) metastases, lactate dehydrogenase (LDH), albumin and urea levels. Although there was no relationship between body composition variables at diagnosis and overall and specific mortality, an increase in low-density muscle and a decrease in normal-density muscle during follow-up were independently correlated to overall (p <0.05) and tumor-cause mortality (p < 0.05). Conclusion: Although body composition measures obtained by CT at diagnosis did not impact survival of GEP-NET patients, a loss of good quality muscle during follow-up was associated with an increased overall and tumor-related mortality. Nutritional status should therefore be supervised by nutrition specialists and an increase in good quality muscle could improve prognosis.

A model integrated fibrinogen and D-dimer for prediction of hepatocellular carcinoma recurrence following liver transplantation: a multicentre study

BACKGROUND

We aimed to investigate whether D-dimer and fibrinogen levels could predict prognosis of patients with hepatocellular carcinoma (HCC) following liver transplantation.

METHODS

From January 2015 to January 2020, we conducted a study on patients with hepatitis B-related liver cancer. Two hundred seventy (270) liver transplant recipients were recruited. Considering D-dimer and plasma fibrinogen levels, a model was established to predict liver cancer recurrence following liver transplantation. Subsequent verification was performed on a validation cohort of 295 recipients from two other hospitals.

RESULTS

Elevated D-dimer and plasma fibrinogen levels demonstrated independent correlation between overall survival and tumour-free survival among patients with HCC who underwent liver transplantation. Those who had preoperative fibrinogen ≥2.27 g/L had significantly reduced overall survival and tumour-free survival than those who had preoperative fibrinogen <2.27 g/L, in the discovery cohort. Recipients with increased risk had preoperative plasma D-dimer ≥2400 µg/L. The model was: Y= logit (P) =0.91* fibrinogen concentration +0.967* D-dimer +0.585* alpha-fetoprotein +1.623* Milan criteria +0.68* microvascular invasion -3.159. At a cut-off score of -1.524, the validation cohort had area under curve values of 0.764 and 0.828 respectively; analysis of this data optimised predictive performance for overall and tumour-free survival.

CONCLUSIONS

For patients who have undergone liver transplantation for HCC, preoperative D-dimer and fibrinogen levels independently predicted key outcomes such as overall survival and tumour-free survival.

Influence of clear cell carcinoma on the post-hepatectomy prognosis of patients with hepatocellular carcinoma

Aim: The authors aimed to identify factors that independently influence the survival of patients with primary clear cell carcinoma of the liver (PCCCL). Methods: A total of 470 patients with hepatocellular carcinoma were retrospectively analyzed. Multivariate Cox analysis was used to identify potential factors associated with prognosis of PCCCL. Results: Patients with PCCCL showed significantly higher disease-free survival (DFS) and overall survival (OS) compared with patients with non-clear cell hepatocellular carcinoma. Multivariate analysis revealed that AFP level, tumor size, liver cirrhosis and portal vein tumor thrombosis were risk factors for DFS. Tumor size, capsule formation and Ki-67 were risk factors for OS. Satellite nodules acted as a protective factor for DFS and OS. Conclusion: PCCCL is associated with better prognosis in hepatocellular carcinoma. Tumor size and satellite nodules may be independent predictors of OS and DFS.

Screening of a novel autophagy-related prognostic signature and therapeutic targets in hepatocellular carcinoma

BACKGROUND

Many studies have indicated that autophagy plays an important role in multiple cancers, including hepatocellular carcinoma (HCC). This study aimed to establish a prognostic signature for HCC based on autophagy-related genes (ARGs) to predict the prognosis of patients.

METHODS

The list of ARGs was derived from screening National Center for Biotechnology Information (NCBI)-Gene and Molecular Signatures Database (MSigDB) datasets. Differential analysis was conducted via the R limma package in HCC patients based on The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analysis were conducted to identify key prognostic ARGs via the survival package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by clusterProfiler package. The Estimation of Stromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm was used to conduct immune analysis. Finally, the correlation between the prognostic model and clinical characteristics was also assessed, including age, tumor-node-metastasis (TNM) stages, and tumor grades.

RESULTS

Firstly, 106 differential ARGs were identified and 10 candidates were further confirmed via Cox regression analysis, including BAMBI, HIF1A, SERPINE1, EZH2, SLC9A3R1, IGFBP3, HSPB8, DAB2, CXCL1 and PRNP. The receiver operating characteristic (ROC) curve analysis revealed that the ARGs risk model had a well diagnostic positive rate with 1-year area under the curve (AUC) =0.688 and 3-year AUC =0.674. Correlation analysis indicated that only advanced tumor stages were positively associated with high ARGs scores with P=0.0227. There were also significant differences in tumor purity (P=6.71e-05), infiltrating cell analysis (P=7.77e-05), immune analysis (P=7.9e-05), and stromal cells analysis (P=0.0015) in high- and low-risk ARGs samples. The genes HIF1A, IGFBP3, and DAB2 were found to have high frequent missense mutations in samples with high-risk ARGs scores. Lastly, we also established a nomogram to predict overall survival (OS) of HCC by integrating ARGs scores and other clinical parameters.

CONCLUSIONS

Our study established an autophagy-related signature for predicting the prognosis of HCC patients, providing a thorough understanding of the underlying mechanisms of autophagy in HCC.

Early Prediction of Objective Response of Fibrinogen in a Real-World Cohort of Hepatocellular Carcinoma Cases Treated by Programmed Cell Death Receptor-1 and Lenvatinib

Background

This cohort study aimed to investigate the influence of fibrinogen on progression-free survival and overall survival in unresectable HCC cases treated by PD-1 and lenvatinib.

Methods

A total of 57 unresectable HCC cases who received lenvatinib and PD-1, such as toripalimab, camrelizumab, or sintilimab, in Beijing Ditan Hospital Affiliated to Capital Medical University were enrolled in this study.

Results

Vascular invasion, high FIB (>2.83g/L), and metastasis were highly correlated with low PFS. There was a significant correlation between a raised risk of death and metastasis and increased FIB (>2.83g/L).

Conclusion

FIB is associated with outcomes of unresectable HCC cases treated by PD-1 and lenvatinib.

The preoperative elevated plasma fibrinogen level is associated with the prognosis of hilar cholangiocarcinoma

PURPOSE

Elevated fibrinogen (Fbg) levels contribute to tumor progression and metastasis. However, little is known regarding the association of the clinicopathological characteristics and the prognosis of hilar cholangiocarcinoma (HC) with plasma fibrinogen.

METHODS

Data on the plasma Fbg levels, clinicopathological characteristics, and overall survival were retrospectively collected. Plasma fibrinogen concentrations over 4.0 g/L were classified as hyperfibrinogen, elevated fibrinogen, or abnormal fibrinogen levels. We then analyzed the relationships among plasma fibrinogen level, clinicopathological features, and patient prognosis.

RESULTS

A total of 171 HC patients were included. An elevated plasma fibrinogen level was associated with lymph-node metastasis (P < 0.001), the AJCC stage (P < 0.001), the surgical margin (P = 0.005), and vascular invasion (P = 0.027). Univariate analyses revealed that preoperative plasma fibrinogen (P < 0.001), operative blood loss (P = 0.044), vascular invasion (P < 0.001), CA19-9 (P = 0.003), surgical margin (P < 0.001), T stage (P < 0.001), histologic differentiation (P = 0.007), and lymph-node metastasis (P < 0.001) were associated with OS. The survival time of patients with high Fbg levels was shorter than that of patients with normal fibrinogen levels (P < 0.001). Furthermore, a multivariate analysis showed that fibrinogen was negatively and independently associated with the HC prognosis (P = 0.029).

CONCLUSIONS

An elevated plasma Fbg level was associated with lymph-node metastasis, vascular invasion, the surgical margin, and the tumor stage, and the Fbg level might therefore be an independent factor associated with poor outcomes in HC patients.

Nomograms based on clinicopathological factors and inflammatory indicators for prediction of early and late recurrence of hepatocellular carcinoma after surgical resection for patients with chronic hepatitis B

Background

Few studies have focused on the prognostic values of inflammation-related factors for different phases of recurrence in hepatocellular carcinoma (HCC). We aimed to identify the different risk factors for overall, early, and late recurrence, and to establish nomograms based on inflammation-related parameters for predicting the risks of recurrence in a group of HCC patients undergoing hepatectomy.

Methods

We retrospectively enrolled 383 HCC patients with chronic hepatitis B (CHB) who underwent hepatectomy. Univariate and multivariate Cox analyses were conducted to identify independent risk factors for recurrence. Nomograms for overall, early, and late recurrence-free survival (RFS) were established. The discrimination and calibration abilities of the nomograms were evaluated by concordance indexes (C-index), calibration plots, and Kaplan-Meier curves. Finally, receiver operating characteristic (ROC) curves were used to compare the derived nomograms with other existing models.

Results

Fibrinogen, lymphocyte-to-monocyte ratio, and S-index inflammation-related factors were independently related to overall and early RFS, but only the S-index correlated with late recurrence. Nomograms with tumor number, diameter, and pathological differentiation for overall and early RFS were established, while nomogram for late recurrence was constructed with tumor number and Child-Pugh grade. The C-indexes for overall, early, and late RFS were 0.679, 0.677, and 0.728, respectively. The calibration plots fit well. The nomograms showed superior discrimination capacities and better performance prediction with larger areas under the curve for recurrence.

Conclusions

The developed nomograms that integrated inflammation-related factors showed high predictive accuracy for overall, early, and late recurrence in HCC patients with CHB after hepatectomy.