Nomogram for prediction of long-term survival with hepatocellular carcinoma based on NK cell counts

Immune landscape and immunotherapy of hepatocellular carcinoma: focus on innate and adaptive immune cells

Hepatocellular carcinoma (HCC) is responsible for roughly 90% of all cases of primary liver cancer, and the cases are on the rise. The treatment of advanced HCC is a serious challenge. Immune checkpoint inhibitor (ICI) therapy has marked a watershed moment in the history of HCC systemic treatment. Atezolizumab in combination with bevacizumab has been approved as a first-line treatment for advanced HCC since 2020; however, the combination therapy is only effective in a limited percentage of patients. Considering that the tumor immune microenvironment (TIME) has a great impact on immunotherapies for HCC, an in-depth understanding of the immune landscape in tumors and the current immunotherapeutic approaches is extremely necessary. We elaborate on the features, functions, and cross talk of the innate and adaptive immune cells in HCC and highlight the benefits and drawbacks of various immunotherapies for advanced HCC, as well as future projections. HCC consists of a heterogeneous group of cancers with distinct etiologies and immune microenvironments. Almost all the components of innate and adaptive immune cells in HCC have altered, showing a decreasing trend in the number of tumor suppressor cells and an increasing trend in the pro-cancer cells, and there is also cross talk between various cell types. Various immunotherapies for HCC have also shown promising efficacy and application prospect. There are multilayered interwoven webs among various immune cell types in HCC, and emerging evidence demonstrates the promising prospect of immunotherapeutic approaches for HCC.

A Nomogram Prognostic Model for Advanced Hepatocellular Carcinoma Based on the Interaction Between CD8+T Cell Counts and Age

Objective

CD8+T cells are essential components of the adaptive immune system and are crucial in the body's immune system. This study aimed to investigate how the prognosis of patients with advanced hepatocellular carcinoma (HCC) was affected by their CD8+ T cell counts and age and established an effective nomogram model to predict the overall survival (OS).

Methods

A total of 427 patients with advanced HCC from Beijing Ditan Hospital, Capital Medical University, were enrolled in this study and randomly divided into training and validation groups, with 300 and 127 individuals in each group, respectively. Cox regression analysis was used to screen for independent risk factors for advanced HCC, and the interactive relationship between CD8+T cells and patient age was examined to establish a nomogram prediction model.

Results

Cox multivariate regression and interaction analyses indicated that tumor number, tumor size, aspartate aminotransferase (AST), C-reactive protein (CRP), relationship of CD8+T cell counts and age were independent predictors of 6-month OS in patients with advanced HCC, and the nomogram model was established based on these factors. The area under the receiver operating characteristic curve (AUC) of the nomogram model for predicting the 3-month, 6-month, and 12-month OS rates were 0.821, 0.802, and 0.756, respectively. Moreover, in clinical practice, patients with true-positive survival benefit more than true-positive death, therefore, we selected 25% as the clinical decision threshold probability based on probability density functions (PDFs) and clinical utility curves (CUCs), which can distinguish approximately 92% of patients who died and 37% of patients who survived.

Conclusion

The nomogram model based on CD8+T cell counts and age accurately assessed the prognosis of patients with advanced HCC and suggested that high CD8+T cell levels are beneficial to the survival of patients with advanced HCC.

Establishment of Nomogram Model for Minimally Invasive Treatment of Small Hepatocellular Carcinoma Based on CD8+T Cell Counts

Purpose

Minimally invasive treatment of small hepatocellular carcinoma (HCC) is the main way of treatment, which can cause the change of HCC immune microenvironment. T lymphocytes are an important part of the immune microenvironment and may be powerful predictors of prognosis. The purpose of this study was to explore the effect of T lymphocytes on the prognosis of HCC and establish a prognostic model.

Patients and Methods

We conducted a retrospective study of 300 patients with small HCC and developed a clinical prediction model. The selection of modeling variables was performed by combining backward stepwise Cox regression using Akaike’s Information Criteria (AIC) and the Least Absolute Shrinkage and Selection Operator (LASSO) regression. Establish a dynamic nomogram model to predict 1-, 2-, and 3-year overall survival (OS). Receiver operating characteristic curve (ROC curve) was used to verify the model discriminative ability, calibration curve was used to examine the model calibration ability, and decision curve analysis (DCA) was used to evaluate the clinical value.

Results

The nomogram to predict the OS of small HCC includes the following four variables: aspartate aminotransferase (AST), alpha fetoprotein (AFP), C-reactive protein (CRP) and CD8⁺T cell counts, represented liver function index, tumor-related index, Inflammatory index and immune-related index, respectively. The area under the receiver operating characteristic curves (AUC) of predicting 1-, 2-, and 3-year overall survival were 0.846, 0.824 and 0.812, and the model was excellent in discrimination, calibration and clinical applicability.

Conclusion

Our study provides a nomogram based on CD8⁺T cell counts that can help predict the prognosis of small HCC after minimally invasive treatment, which suggests that T lymphocytes can be used as a prognostic factor for HCC. Larger trials are needed to verify our results.