Scirrhous Hepatocellular Carcinoma: Systematic Review and Pooled Data Analysis of Clinical, Radiological, and Histopathological Features

Nomogram for prediction of hepatocellular carcinoma recurrence after liver resection

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignancy with high mortality. Liver resection (LR) is a curative treatment for early-stage HCC, but the prognosis of HCC patients after LR is unsatisfactory because of tumor recurrence. Prognostic prediction models with great performance are urgently needed. The present study aimed to establish a novel prognostic nomogram to predict tumor recurrence in HCC patients after LR.

METHODS

We retrospectively analyzed 726 HCC patients who underwent LR between October 2011 and December 2016. Patients were randomly divided into the training cohort (n = 508) and the testing cohort (n = 218). The protein expression of 14 biomarkers in tumor tissues was assessed by immunohistochemistry. The nomogram predicting recurrence-free survival (RFS) was established by a multivariate Cox regression analysis model and was evaluated by calibration curves, Kaplan-Meier survival curves, time-dependent areas under the receiver operating characteristic (ROC) curves (AUCs), and decision curve analyses in both the training and testing cohorts.

RESULTS

Alpha-fetoprotein [hazard ratio (HR) = 1.013, P = 0.002], portal vein tumor thrombosis (HR = 1.833, P < 0.001), ascites (HR = 2.024, P = 0.014), tumor diameter (HR = 1.075, P < 0.001), E-cadherin (HR = 0.859, P = 0.011), EMA (HR = 1.196, P = 0.022), and PCNA (HR = 1.174, P = 0.031) immunohistochemistry scores were found to be independent factors for RFS. The 1-year and 3-year AUCs of the nomogram for RFS were 0.813 and 0.739, respectively. The patients were divided into the high-risk group and the low-risk group by median value which was generated from the nomogram, and Kaplan-Meier analysis revealed that the high-risk group had a shorter RFS than the low-risk group in both the training (P < 0.001) and testing cohorts (P < 0.001).

CONCLUSIONS

Our newly developed nomogram integrated clinicopathological data and key gene expression data, and was verified to have high accuracy in predicting the RFS of HCC patients after LR. This model could be used for early identification of patients at high-risk of postoperative recurrence.

The Organ Procurement and Transplantation Network hepatocellular carcinoma classification: Alignment with Liver Imaging Reporting and Data System, current gaps, and future direction

The Organ Procurement and Transplantation Network (OPTN) updated its allocation policy for liver transplantation to align with the Liver Imaging Reporting and Data System (LI-RADS) for the diagnosis of hepatocellular carcinoma (HCC). LI-RADS computed tomography/magnetic resonance imaging algorithm had achieved congruency with the American Association for the Study of Liver Diseases (AASLD) HCC Practice Guidance in 2018, and therefore, alignment of OPTN, LI-RADS, and AASLD unifies HCC diagnostic approaches. The two changes to the OPTN HCC classification are adoption of LI-RADS terminology or lexicon for HCC major imaging features as well as the modification of OPTN Class-5A through the adoption of LI-RADS-5 criteria. However, despite this significant milestone, the OPTN allocation policy may benefit from further refinements such as adoption of treatment response assessment criteria after locoregional therapy and categorization criteria for lesions with atypical imaging appearances that are not specific for HCC. In this review, we detail the changes to the OPTN HCC classification to achieve alignment with LI-RADS, discuss current limitations of the OPTN classification, and explore future directions.

State-of-the-art review on the correlations between pathological and magnetic resonance features of cirrhotic nodules

Hepatocellular carcinoma (HCC) has become the second greatest cause of cancer-related mortality worldwide and the newest advancements in liver imaging have improved the diagnosis of both overt malignancies and premalignant lesions, such as cirrhotic or dysplastic nodules, which is crucial to improve overall patient survival rate and to choose the best treatment options. The role of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) has grown in the last 20 years. In particular, the introduction of hepatospecific contrast agents has strongly increased the definition of precursor nodules and detection of high-grade dysplastic nodules and early HCCs. Nevertheless, the diagnosis of liver tumours in cirrhotic patients sometimes remains challenging for radiologists, thus, in doubtful cases, biopsy and histological analysis become critical in clinical practice. This current review briefly summarizes the history of imaging and histology for HCC, covering the newest techniques and their limits. Then, the article discusses the links between radiological and pathological characteristics of liver lesions in cirrhotic patients, by describing the multistep process of hepatocarcinogenesis. Explaining the evolution of pathologic change from cirrhotic nodules to malignancy, the list of analyzed lesions provides regenerative nodules, low-grade and high-grade dysplastic nodules, small HCC and progressed HCC, including common subtypes (steatohepatitic HCC, scirrhous HCC, macrotrabecular massive HCC) and more rare forms (clear cell HCC, chromophobe HCC, neutrophil-rich HCC, lymphocyte-rich HCC, fibrolamellar HCC). The last chapter covers the importance of the new integrated morphological-molecular classification and its association with radiological features.

Understanding the Immunoenvironment of Primary Liver Cancer: A Histopathology Perspective

One of the most common cancers worldwide, primary liver cancer remains a major cause of cancer-related mortality. Hepatocellular carcinoma and cholangiocarcinoma represent the majority of primary liver cancer cases. Despite advances in the development of novel anti-cancer therapies that exploit targets within the immune system, survival rates from liver cancer remain poor. Furthermore, responses to immunotherapies, such as immune checkpoint inhibitors, have revealed limited and variable responses amongst patients with hepatocellular carcinoma, although combination immunotherapies have shown recent breakthroughs in clinical trials. This has shifted the focus towards improving our understanding of the underlying immune and molecular characteristics of liver tumours that may influence their response to immune-modulating treatments. In this review, we outline the complex interactions that occur in the tumour microenvironment of hepatocellular carcinoma and cholangiocarcinoma, respectively, from a histopathological perspective. We explore the potential role of a classification system based on immune-specific characteristics within each cancer type, the importance of understanding inter- and intra-tumoural heterogeneity and consider the future role of histopathology and novel technologies within this field.

Epidemiological and Clinical Characteristics of Five Rare Pathological Subtypes of Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is a highly heterogeneous tumor with several rare pathological subtypes and which is still poorly understood. This study aimed to describe the epidemiological and clinical spectrum of five rare HCC subtypes and develop a competing risk nomogram for cancer-specific survival prediction.

Methods

The study cohort was recruited from the Surveillance, Epidemiology, and End Results database. The clinicopathological data of 50,218 patients histologically diagnosed with classic HCC and five rare subtypes (ICD-O-3 Histology Code = 8170/3-8175/3) between 2004 and 2018 were reviewed. The annual percent change (APC) was calculated utilizing Joinpoint regression. The nomogram was developed based on multivariable competing risk survival analyses. Akaike information criterion, Bayesian information criterion, C-index, calibration curve, and area under the receiver operating characteristic curve were obtained to evaluate the prognostic performance. A decision curve analysis was introduced to examine the clinical value of the models.

Results

Despite scirrhous carcinoma, which showed a decreasing trend (APC = -6.8%, P = 0.025), the morbidity of other rare subtypes remained stable from 2004 to 2018. The incidence-based mortality was plateau in all subtypes during the period. Clear cell carcinoma is the most common subtype (n = 551, 1.1%), followed by subtypes of fibrolamellar (n = 241, 0.5%), scirrhous (n = 82, 0.2%), spindle cell (n = 61, 0.1%), and pleomorphic (n = 17, ~0%). The patients with fibrolamellar carcinoma were younger and more likely to have a non-cirrhotic liver and better prognoses. Scirrhous carcinoma shared almost the same macro-clinical characteristics and outcomes as the classic HCC. Clear cell carcinoma tended to occur in the Asia-Pacific elderly male population, and more than half of them were large HCC (Size&gt;5cm). Sarcomatoid (including spindle cell and pleomorphic) carcinoma was associated with a larger tumor size, poorer differentiation, and more dismal prognoses. The pathological subtype, T stage, M stage, surgery, alpha-fetoprotein, and cancer history were confirmed as the independent predictors in patients with rare subtypes. The nomogram showed good calibration, discrimination, and net benefits in clinical practice.

Conclusion

The rare subtypes had unique clinicopathological features and biological behaviors compared with the classic HCC. Our findings could provide a valuable reference for clinicians. The constructed nomogram could predict the prognoses with good performance, which is meaningful to individualized management.