Circulating tumor DNA as a potential prognostic and predictive biomarker during interventional therapy of unresectable primary liver cancer

Prognostic biomarkers associated with immune checkpoint inhibitors in hepatocellular carcinoma

The treatment of hepatocellular carcinoma (HCC), particularly advanced HCC, has been a serious challenge. Immune checkpoint inhibitors (ICIs) are landmark drugs in the field of cancer therapy in recent years, which have changed the landscape of cancer treatment. In the field of HCC treatment, this class of drugs has shown good therapeutic prospects. For example, atezolizumab in combination with bevacizumab has been approved as first-line treatment for advanced HCC due to significant efficacy. However, sensitivity to ICI therapy varies widely among HCC patients. Therefore, there is an urgent need to search for determinants of resistance/sensitivity to ICIs and to screen biomarkers that can predict the efficacy of ICIs. This manuscript reviews the research progress of prognostic biomarkers associated with ICIs in HCC in order to provide a scientific basis for the development of clinically individualised precision medication regimens.

Pre-enrichment-free detection of hepatocellular carcinoma-specific ctDNA via PDMS and MEMS-based microfluidic sensor

The growing interest in microfluidic biosensors has led to improvements in the analytical performance of various sensing mechanisms. Although various sensors can be integrated with microfluidics, electrochemical ones have been most commonly employed due to their ease of miniaturization, integration ability, and low cost, making them an established point-of-care diagnostic method. This concept can be easily adapted to the detection of biomarkers specific to certain cancer types. Pathological profiling of hepatocellular carcinoma (HCC) is heterogeneous and rather complex, and biopsy samples contain limited information regarding the tumor and do not reflect its heterogeneity. Circulating tumor DNAs (ctDNAs), which can contain information regarding cancer characteristics, have been studied tremendously since liquid biopsy emerged as a new diagnostic method. Recent improvements in the accuracy and sensitivity of ctDNA determination also paved the way for genotyping of somatic genomic alterations. In this study, three-electrode (Au-Pt-Ag) glass chips were fabricated and combined with polydimethylsiloxane (PDMS) microchannels to establish an electrochemical microfluidic sensor for detecting c.747G > T hotspot mutations in the TP53 gene of ctDNAs from HCC. The preparation and analysis times of the constructed sensor were as short as 2 h in total, and a relatively high flow rate of 30 µl/min was used during immobilization and hybridization steps. To the best of our knowledge, this is the first time a PDMS-based microfluidic electrochemical sensor has been developed to target HCC ctDNAs. The system exhibited a limit of detection (LOD) of 24.1 fM within the tested range of 2-200 fM. The sensor demonstrated high specificity in tests conducted with fully noncomplementary and one-base mismatched target sequences. The developed platform is promising for detecting HCC-specific ctDNA at very low concentrations without requiring pre-enrichment steps.

Liquid biopsy: New opportunities for precision medicine in hepatocellular carcinoma care

Liquid biopsy, specifically the analysis of circulating tumor DNA (ctDNA), offers a non-invasive approach for hepatocellular carcinoma (HCC) diagnosis and management. However, its implementation in the clinical setting is difficult due to challenges such as low ctDNA yield and difficulty in understanding the mutation signals from background noise. This review highlights the crucial role of artificial intelligence (AI) in addressing these limitations and in improving discoveries in the field of liquid biopsy for HCC care. Combining AI with liquid biopsy data can offer a promising future for the discovery of novel biomarkers and an AI-powered clinical decision support system (CDSS) can turn liquid biopsy into an important tool for personalized management of HCC. Despite the current challenges, the integration of AI shows promise to significantly improve patient outcomes and revolutionize the field of oncology.

Immunotherapy, targeted therapy, and their cross talks in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a challenging malignancy with limited treatment options beyond surgery and chemotherapy. Recent advancements in targeted therapies and immunotherapy, including PD-1 and PD-L1 monoclonal antibodies, have shown promise, but their efficacy has not met expectations. Biomarker testing and personalized medicine based on genetic mutations and other biomarkers represent the future direction for HCC treatment. To address these challenges and opportunities, this comprehensive review discusses the progress made in targeted therapies and immunotherapies for HCC, focusing on dissecting the rationales, opportunities, and challenges for combining these modalities. The liver's unique physiology and the presence of fibrosis in many HCC patients pose additional challenges to drug delivery and efficacy. Ongoing efforts in biomarker development and combination therapy design, especially in the context of immunotherapies, hold promise for improving outcomes in advanced HCC. Through exploring the advancements in biomarkers and targeted therapies, this review provides insights into the challenges and opportunities in the field and proposes strategies for rational combination therapy design.

Minimal residual disease in solid tumors: an overview

Minimal residual disease (MRD) is termed as the small numbers of remnant tumor cells in a subset of patients with tumors. Liquid biopsy is increasingly used for the detection of MRD, illustrating the potential of MRD detection to provide more accurate management for cancer patients. As new techniques and algorithms have enhanced the performance of MRD detection, the approach is becoming more widely and routinely used to predict the prognosis and monitor the relapse of cancer patients. In fact, MRD detection has been shown to achieve better performance than imaging methods. On this basis, rigorous investigation of MRD detection as an integral method for guiding clinical treatment has made important advances. This review summarizes the development of MRD biomarkers, techniques, and strategies for the detection of cancer, and emphasizes the application of MRD detection in solid tumors, particularly for the guidance of clinical treatment.

Advanced development of biomarkers for immunotherapy in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common liver cancer and one of the leading causes of cancer-related deaths in the world. Mono-immunotherapy and combination therapy with immune checkpoint inhibitors (ICIs) and multitargeted tyrosine kinase inhibitors (TKIs) or anti-vascular endothelial growth factor (anti-VEGF) inhibitors have become new standard therapies in advanced HCC (aHCC). However, the clinical benefit of these treatments is still limited. Thus, proper biomarkers which can predict treatment response to immunotherapy to maximize clinical benefit while sparing unnecessary toxicity are urgently needed. Contrary to other malignancies, up until now, no acknowledged biomarkers are available to predict resistance or response to immunotherapy for HCC patients. Furthermore, biomarkers, which are established in other cancer types, such as programmed death ligand 1 (PD-L1) expression and tumor mutational burden (TMB), have no stable predictive effect in HCC. Thus, plenty of research focusing on biomarkers for HCC is under exploration. In this review, we summarize the predictive and prognostic biomarkers as well as the potential predictive mechanism in order to guide future research direction for biomarker exploration and clinical treatment options in HCC.

Blood-based biomarkers for immune-based therapy in advanced HCC: Promising but a long way to go

The introduction of immune checkpoint inhibitors (ICIs) represents a key shift in the management strategy for patients with hepatocellular carcinoma (HCC). However, there is a paucity of predictive biomarkers that facilitate the identification of patients that would respond to ICI therapy. Although several researchers have attempted to resolve the issue, the data is insufficient to alter daily clinical practice. The use of minimally invasive procedures to obtain patient-derived specimen, such as using blood-based samples, is increasingly preferred. Circulating tumor DNA (ctDNA) can be isolated from the blood of cancer patients, and liquid biopsies can provide sufficient material to enable ongoing monitoring of HCC. This is particularly significant for patients for whom surgery is not indicated, including those with advanced HCC. In this review, we summarize the current state of understanding of blood-based biomarkers for ICI-based therapy in advanced HCC, which is promising despite there is still a long way to go.

Establishment of a Prognostic Model for Hepatocellular Carcinoma Based on Bioinformatics and the Role of NR6A1 in the Progression of HCC

BACKGROUND AND AIMS

Generally acceptable prognostic models for hepatocellular carcinoma (HCC) are not available. This study aimed to establish a prognostic model for HCC by identifying immune-related differentially expressed genes (IR-DEGs) and to investigate the potential role of NR6A1 in the progression of HCC.

METHODS

Bioinformatics analysis using The Cancer Genome Atlas and ImmPort databases was used to identify IR-DEGs. Lasso Cox regression and multivariate Cox regression analysis were used to establish a prognostic model of HCC. Kaplan-Meier analysis and the receiver operating characteristic (ROC) curves were used to evaluate the performance of the prognostic model, which was further verified in the International Cancer Genome Consortium (ICGC) database. Gene set enrichment analysis was used to explore the potential pathways of NR6A1. Cell counting kit 8, colony formation, wound healing, and Transwell migration assays using Huh7 cells, and tumor formation models in nude mice were conducted.

RESULTS

A prognostic model established based on ten identified IR-DEGs including HSPA4, FABP6, MAPT, NDRG1, APLN, IL17D, LHB, SPP1, GLP1R, and NR6A1, effectively predicted the prognosis of HCC patients, was confirmed by the ROC curves and verified in ICGC database. NR6A1 expression was significantly up-regulated in HCC patients, and NR6A1 was significantly associated with a low survival rate. Gene set enrichment analysis showed the enrichment of cell cycle, mTOR, WNT, and ERBB signaling pathways in patients with high NR6A1 expression. NR6A1 promoted cell proliferation, invasiveness, migration, and malignant tumor formation and growth in vitro and in vivo.

CONCLUSIONS

An effective prognostic model for HCC, based on a novel signature of 10 immune-related genes, was established. NR6A1 was up-regulated in HCC and was associated with a poor prognosis of HCC. NR6A1 promoted cell proliferation, migration, and growth of HCC, most likely through the cell cycle, mTOR, WNT, and ERBB signaling pathways.

Prognostic Value of Postoperative Circulating Tumor DNA in Patients With Early- and Intermediate-Stage Hepatocellular Carcinoma

Majority of patients with resected early- and intermediate-stage liver cancer will experience postoperative recurrence. This study aimed to investigate the application of ctDNA sequencing in the postoperative period of hepatocellular carcinoma. A total of 96 patients with liver cancer were enrolled in this study. Postoperative peripheral blood samples were collected from all patients after surgery and analyzed using hybridization capture-based next-generation sequencing. Identification of at least one somatic mutation in the peripheral blood was defined as ctDNA+. Five genetic features in tumor tissues were associated with disease-free survival (DFS) using Lasso-Cox model. The area under the receiver operating characteristic curve was 0.813 and 0.882 in training and validation cohorts, respectively. The recurrence rate in ctDNA+ and ctDNA- groups was 60.9% and 27.8%, respectively. Multivariate Cox regression analysis showed that the postoperative ctDNA was an independent prognostic predictor of DFS (HR [hazard ratio]: 6.074, 95% Cl [confidence interval]: 2.648-13.929, P<0.001) and overall survival (OS) (HR: 4.829, 95% CI: 1.508-15.466, P=0.008). Combined ctDNA with AFP improved prediction performance. The median DFS was 2.0, and 8.0 months in ctDNA+/AFP-H and ctDNA+/AFP-L groups, respectively; while ctDNA-/AFP-H and ctDNA-/AFP-L groups had not reached the median time statistically (Log-rank test, P < 0.0001). Furthermore, ctDNA- patients had better prognosis than ctDNA+ patients irrespective of tumor stage. Postoperative ctDNA sequencing has great prognostic value in patients with liver cancer. Patients with positive ctDNA should receive more intensive disease monitoring and more aggressive treatment strategies to improve the survival time.

Clinical Applications of Liquid Biopsy in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common malignant tumor with high mortality and poor prognosis in the world. The low rate of early diagnosis, as well as the high risk of postoperative metastasis and recurrence, led to the poor clinical prognosis of HCC patients. Currently, it mainly depends on serum markers, imaging examination, and tissue biopsy to diagnose and determine the recurrence and metastasis of HCC after treatments. Nevertheless, the accuracy and sensitivity of serum markers and imaging for early HCC diagnosis are suboptimal. Tissue biopsy, containing limited tissue samples, is insufficient to reveal comprehensive tumor biology information and is inappropriate to monitor dynamic tumor progression due to its invasiveness. Thus, low invasive diagnostic methods and novel biomarkers with high sensitivity and reliability must be found to improve HCC detection and prediction. As a non-invasive, dynamic, and repeatable detection method, “liquid biopsy”, has attracted much attention to early diagnosis and monitoring of treatment response, which promotes the progress of precision medicine. This review summarizes the clinical applications of liquid biopsy in HCC, including circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and exosome in early diagnosis, prognostic evaluation, disease monitoring, and guiding personalized treatment.

Personalized nursing improves physical condition and life quality of patients undergoing interventional therapy for liver cancer

Interventional therapy, which can prolong the survival of patients with liver cancer (LC), is an important means to treat the disease. During interventional therapy for LC, it is essential to make a targeted and detailed nursing plan to ameliorate the prognosis. The purpose of this study was to determine the application significance of personalized nursing in patients undergoing interventional therapy for LC. We retrospectively analyzed 136 patients with LC undergoing interventional therapy. Among them, 70 cases receiving personalized nursing were assigned to the observation group (OG), and the remaining 66 cases receiving routine nursing were the control group (CG). After nursing, sleep time of patients in the OG was significantly longer than that in CG. In addition, time to ambulation and hospital stay were shorter in the OG than in the CG. Furthermore, the OG exhibited significantly lower scores of visual analogue scale (VAS) and self-rating anxiety scale (SAS), as well as significantly reduced incidence of adverse reactions than the CG. Compared with the CG, the levels of serum alanine aminotransferase (AST), aspartate aminotransferase (ALT), and total bilirubin (TBIL) were significantly lower in the OG after nursing, while the level of albumin (ALB) was significantly increased. Moreover, patients in the OG showed significantly higher nursing satisfaction and quality of life scores than those in the CG. Therefore, personalized nursing has good prospects for usein interventional therapy for LC.

The Prognostic Value of ctDNA and bTMB on Immune Checkpoint Inhibitors in Human Cancer

Background

Circulating tumor DNA (ctDNA) levels and blood tumor mutation burden (bTMB) have a significant impact on the prognosis of tumor patients. However, their prognostic role in immune checkpoint inhibitors (ICIs) in cancer patients is still unclear.

Methods

We used the Review Manager software (version 5.3) to perform a meta-analysis based on the published literature to explore the prognostic value of ctDNA and bTMB in patients receiving immunotherapy. We extracted the hazard ratios (HRs) of progression-free survival (PFS) and overall survival (OS) for each included study and their respective 95% confidence intervals (CIs) and p-values for analysis.

Results

Thirteen studies were included in the meta-analysis. Higher ctDNA levels were significantly associated with shorter OS (HR = 3.35, 95%CI = 2.49–4.51, p < 0.00001) and PFS (HR = 3.28, 95%CI = 2.47–4.35, p < 0.00001). The results of ctDNA subgroup analysis showed that high posttreatment ctDNA levels significantly correlated with shorter OS in cancer patients receiving ICIs (HR = 5.09, 95%CI = 1.43–18.07, p = 0.01). Moreover, patients with ctDNA clearance had better OS (HR = 4.94, 95%CI = 2.96–8.26, p < 0.00001). Patients with high posttreatment ctDNA levels had shorter PFS (HR = 3.00, 95%CI = 2.02–4.46, p < 0.00001) and those with ctDNA clearance had longer PFS (HR = 4.61, 95%CI = 2.78–7.65, p < 0.00001). However, there was no statistically significant difference in the OS benefits between a high and a low bTMB after ICI therapy (HR = 0.68, 95%CI = 0.33–1.37, p = 0.28).

Conclusions

The host immune system and tumor burden together determine whether cancer patients can benefit from ICI therapy. Our systematic review and meta-analysis revealed for the first time that the levels of pretreatment and posttreatment ctDNA and the clearance of ctDNA can independently be used as prognostic factors for antitumor immunotherapy, while bTMB cannot. In conclusion, ctDNA levels have great potential as an assistant tool for radiological assessments to make clinical therapeutic decisions. The prognostic utility of bTMB still requires further exploration.

Liquid Biopsy in Hepatocellular Carcinoma: Opportunities and Challenges for Immunotherapy

Hepatocellular carcinoma (HCC) is one of the deadliest cancer types worldwide. HCC is often diagnosed at a late stage when the therapeutic options are very limited. However, even at the earlier stages, the best treatment is liver transplantation, surgical resection or ablation. Surgical resection and ablation may carry a high risk of tumor recurrence. The recent introduction of immunotherapies resulted in clinical responses for a subgroup of patients, but there were still no effective predictive markers for response to immunotherapy or for recurrence after surgical therapy. The identification of biomarkers that could correlate and predict response or recurrence would require close monitoring of the patients throughout and after the completion of treatment. However, this would not be performed efficiently by repeated and invasive tissue biopsies. A better approach would be to use liquid biopsies including circulating tumor DNA (ctDNA), circulating RNA (e.g., microRNAs), circulating tumor cells (CTC) and extracellular vesicles (EVs) (e.g., exosomes) for disease monitoring in a non-invasive manner. In this review, we discuss the currently available technology that can enable the use of liquid biopsy as a diagnostic and prognostic tool. Moreover, we discuss the opportunities and challenges of the clinical application of liquid biopsy for immunotherapy of HCC.

Leveraging the Fragment Length of Circulating Tumour DNA to Improve Molecular Profiling of Solid Tumour Malignancies with Next-Generation Sequencing: A Pathway to Advanced Non-invasive Diagnostics in Precision Oncology?

Circulating cell-free DNA (ccfDNA) has emerged as a promising diagnostic tool in oncology. Identification of tumour-derived ccfDNA (i.e. circulating tumour DNA [ctDNA]) provides non-invasive access to a malignancy’s molecular landscape to diagnose, inform therapeutic strategies, and monitor treatment efficacy. Current applications of ccfDNA to detect somatic mutations, however, have been largely constrained to tumour-informed searches and identification of common mutations because of the interaction between ctDNA signal and next-generation sequencing (NGS) noise. Specifically, the low allele frequency of ctDNA associated with non-metastatic and early-stage lesions may be indistinguishable from artifacts that accrue during sample preparation and NGS. Thus, using ccfDNA to achieve non-invasive and personalized molecular profiling to optimize individual patient care is a highly sought goal that remains limited in clinical practice. There is growing evidence, however, that further advances in the field of ccfDNA diagnostics may be achieved by improving detection of somatic mutations through leveraging the inherently shorter fragment lengths of ctDNA compared to non-neoplastic ccfDNA. Here, the origins and rationale for seeking to improve the mutation-based detection of ctDNA by using ccfDNA size profiling are reviewed. Subsequently, in vitro and in silico methods to enrich for a target ccfDNA fragment length are detailed to identify current practices and provide perspective into the potential of using ccfDNA size profiling to impact clinical applications in oncology.