Unlike the traditional staging treatment of tumors, the core of “Green Tumor Treatment” is to divide the treatment of tumors into three stages: Hegemony (directly targeting the cancer focus), Kingship (supporting the body’s vital energy and eliminating pathogenic factors), and Imperialism (improving the internal environment), based on the urgency of the tumor and the patient’s physical condition. This approach guides the clinical treatment of tumors. Its treatment system incorporates all minimally invasive and low-damage treatment methods, combining internal and external treatments, traditional Chinese medicine and Western medicine, as well as local and systemic treatments. It aims to maximize treatment outcomes while ensuring the patient’s quality of life, which is highly consistent with the treatment goals for primary liver cancer. This review aims to explore the integrated Traditional Chinese and Western medicine treatment model for primary liver cancer under the guidance of the Green Tumor Treatment concept.

Metabolic dysfunction-associated steatotic liver disease (MASLD) and sarcopenia frequently coexist, yet their causal relationship and underlying mechanisms remain poorly defined. This study aimed to investigate whether a bidirectional causal link exists between MASLD and sarcopenia and to identify the molecular mediators involved in liver-muscle crosstalk.

We applied Mendelian randomization to test the causal effect of sarcopenia-related traits on MASLD risk. To capture distinct clinical features, we established complementary mouse models, including diet-induced and genetic (ob/ob) MASLD models, a stelic animal model, and a drug-induced muscle atrophy model. Multi-tissue transcriptomic profiling was performed on liver and muscle to uncover altered pathways.

Complementing prior genetic evidence establishing MASLD as a causal factor for sarcopenia, our Mendelian randomization analysis revealed that diminished muscle mass and muscle function contribute to an elevated risk of MASLD. In mice with MASLD, we observed loss of muscle mass, reduced strength, and ectopic lipid deposition in skeletal muscle. Conversely, muscle atrophy exacerbated hepatic steatosis, inflammation, and fibrosis in MASLD mice. Transcriptional profiling revealed that sarcopenia impairs hepatic metabolic homeostasis by enhancing fatty acid uptake and impairing oxidative phosphorylation, while MASLD, in turn, promotes muscle dysfunction by exacerbating inflammatory responses and metabolic dysfunction. We further identified C-C motif chemokine ligand 2 as a key myokine that drives MASLD, and adrenomedullin as a key hepatokine that triggers sarcopenia.

Our findings suggest a potential bidirectional causal relationship between MASLD and sarcopenia, which may be partially mediated by C-C motif chemokine ligand 2 and adrenomedullin.

Primary hepatocellular carcinoma (HCC) remains one of the leading causes of cancer-related mortality worldwide, with curative options still limited for patients with advanced disease. As an emerging modality of cancer immunotherapy, tumor vaccines represent a promising approach that activates the host immune system to recognize and eliminate malignant cells. Multiple vaccine platforms, including peptide vaccines, dendritic-cell vaccines, nucleic-acid vaccines, and viral-vector vaccines, have been explored for HCC. Among these, peptide- and dendritic-cell-based vaccines are supported by the most extensive clinical data, demonstrating favorable safety and immunogenicity profiles. The advent of personalized therapeutic cancer vaccines based on tumor-specific antigens has further refined the precision of vaccine design. Nevertheless, several major challenges persist, including immune suppression within the tumor immune microenvironment, marked tumor heterogeneity, immune-escape mechanisms, and limited vaccine immunogenicity, all of which hinder clinical efficacy. In addition, issues related to standardization, large-scale production, and regulatory oversight remain unresolved. Recent advances in sequencing technology, nanotechnology, and artificial intelligence have opened new avenues for optimizing vaccine platforms and delivery strategies. Combination therapies that integrate cancer vaccines with immune checkpoint inhibitors, chemotherapy, or locoregional treatments are also being actively investigated to improve patient outcomes. In summary, although vaccine-based immunotherapy for HCC is still at an early stage, its integration with personalized medicine and multimodal therapeutic strategies holds great potential for improving the long-term prognosis of patients with HCC. Therefore, this review aims to systematically summarize current advances in tumor vaccine–based immunotherapy for hepatocellular carcinoma, with a particular focus on vaccine platforms, target antigens, clinical trial outcomes, and future challenges for clinical translation.

Autoimmune hepatitis (AIH) frequently coexists with extrahepatic autoimmune diseases (EADs), but their prevalence, characteristics, progression, and treatment effect in the Han Chinese population remain unclear. This study aimed to evaluate the prevalence and spectrum of EADs and to assess their clinical features, disease course, and treatment outcomes in Han Chinese patients with AIH.

Medical records of 371 Han Chinese patients with AIH (diagnosed from March 2016 to October 2023) were retrospectively analyzed.

Among the 371 AIH patients, 304 (81.94%) were female, with a median age of 52.5 years (interquartile range, 46.0–61.0). A total of 23.98% (89/371) had at least one EAD, including 27.06% (82/303) in type 1 AIH, 11.11% (7/63) in antibody-negative AIH, and none in type 2. A single EAD was the most common (20.21%, 75/371). The most frequent EADs were Sjogren’s syndrome (8.63%) and autoimmune thyroid disease (8.36%). Compared with patients without EADs, those with EADs had lower alanine aminotransferase, red blood cell, and hemoglobin levels, but higher aspartate aminotransferase/alanine aminotransferase ratio and antinuclear antibody (ANA) positivity (all P < 0.05). ANA positivity was independently associated with EADs (odds ratio = 2.209, 95% confidence interval = 1.242–3.927, P = 0.007). After three months of treatment, the complete biochemical response rate was lower in the EADs group than in the non-EADs group (40.0% vs. 55.3%, P = 0.024), whereas no significant differences were observed at 6, 12, 24, or 36 months (all P > 0.05).

In the Han Chinese population, 23.98% of AIH patients had EADs, with Sjogren’s syndrome and autoimmune thyroid disease being the most common. ANA positivity was a significant risk factor for EADs. EAD patients had a poorer initial treatment response at three months, but comparable long-term biochemical response from six months.

In the past decade, immune checkpoint inhibitors (ICIs) have dramatically changed cancer treatment, significantly improving outcomes for patients with various malignancies. Nonetheless, their widespread application has resulted in a rise in immune-related adverse events due to excessive immune activation, including immune-mediated hepatotoxicity (IMH). IMH can cause serious complications and even death, underscoring the need for early prediction and intervention. This review outlines the current understanding of risk factors and predictive biomarkers for IMH in cancer patients undergoing ICI therapy, with risk factors divided into patient-associated, tumor-associated, and agent-associated categories. Higher IMH risk is related to female sex, younger age, extreme BMI, Asian ethnicity, and chronic liver disease. Cancer type, prior ICI treatment, dual ICI combination therapy, and the concurrent use of chemotherapy, targeted agents, or other hepatotoxic drugs (e.g., acetaminophen, statins) also increase the risk of IMH. Potential predictive biomarkers encompass circulating blood cells, serum proteins, autoantibodies, cytokines, gene profiles, and the gut microbiome. Despite promising findings, the predictive value of these biomarkers remains inconsistent, and no definitive biomarker has been established for routine clinical use. Large-scale prospective studies are essential to verify the predictive value of these biomarkers and facilitate their integration into clinical practice, thereby providing deeper insights into the early identification and individualized management of IMH during ICI therapy.

The rate of functional cure (HBsAg loss) remains unsatisfactory following pegylated interferon (PEG-IFN) treatment in chronic hepatitis B. To optimize PEG-IFN administration, this study aimed to evaluate virological markers to predict functional cure and/or hepatitis B e antigen (HBeAg) loss.

Relevant studies assessing virologic markers for predicting functional cure and HBeAg loss after PEG-IFN therapy were systematically retrieved from PubMed, Embase, the Cochrane Library, and Web of Science up to November 2023. Predictive effectiveness was evaluated via the summary receiver operating characteristic curve.

We analyzed 38 studies (6,179 patients). HBsAg decline at week 24 had the greatest discriminative ability according to the area under the receiver operating characteristic curve (AUROC) (0.89) and sensitivity (0.88) for predicting functional cure, whereas baseline HBsAg had a comparable AUROC (0.86) and highest specificity (0.79), with both being significantly better than baseline hepatitis B core-related antigen and hepatitis B virus (HBV) RNA (all P < 0.001). For HBeAg loss or seroconversion, HBV RNA, HBV DNA, HBeAg, and HBeAg decline at week 12, as well as HBV DNA and HBeAg decline at week 24, all exhibited comparable predictive values (AUROC = 0.75–0.78). HBV RNA and HBeAg levels at week 24 showed optimal sensitivity (0.87), and HBeAg decline at week 12 had the highest specificity (0.83).

HBsAg decline at week 24 and baseline HBsAg levels are better predictors of functional cure than novel virologic markers, while on-treatment HBV RNA and HBeAg levels and dynamic changes are the most reliable indicators for HBeAg loss.

Human papillomavirus (HPV) is a double-stranded circular DNA virus with a genome of approximately 7–8 kb. This study aimed to establish an overlapping extension polymerase chain reaction method for the amplification of the entire genome of HPV16.

The HPV16 genome was divided into two larger fragments (with lengths of 3.9 kilobases and 5.3 kilobases, respectively), each of which had overlapping regions of more than 500 base pairs. A nested primer (outer primer: Fout/Rout; inner primer: Fin/Rin) was used to amplify each fragment. The key reaction parameters were optimized, including the selection of two highly accurate DNA polymerases; and a series of diluted samples (initial concentration of 2,000 copies/microliter, diluted to 2, 20, 200, and 2,000 copies/microliter) were used for amplification tests to evaluate the sensitivity of this method.

This study demonstrated high sensitivity for HPV16 detection, with effective amplification of samples as low as 2 copies/µL. For low-concentration samples (<200 copies/µL), the Thermo Fisher enzyme showed 50% and 75% effective amplification success rates at 2 copies/µL and 20 copies/µL, respectively, while the Vazyme enzyme achieved 0% success at both concentrations. Both enzymes enabled stable amplification of high-concentration samples (≥200 copies/µL). The amplified products matched the theoretical size, and Illumina sequencing confirmed Q30 ≥ 96% and >98% identity with the HPV16 reference sequence (K02718.1).

This study provides a highly sensitive and specific method for the full-genome sequence analysis of HPV16, which is applicable to HPV16 full-genome sequencing, variation analysis, and other research.