precision-surgery-minimally-invasive-techniques-for-treatment-complex

Precision Surgery and Minimally Invasive Techniques for the Treatment of Complex Biliary Stones Closely Associated with the Middle Hepatic Vein

Hepatectomy is widely used for complex hepatobiliary stones, but when diseased bile ducts involve adjacent vessels, traditional methods, relying on ...

Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology)

Preoperative prediction of recurrence outcome in hepatocellular carcinoma (HCC) facilitates physicians' clinical decision-making. Preoperative imaging and related clinical baseline data of patients are valuable for evaluating prognosis. With the widespread application of machine learning techniques, the present study proposed the ensemble learning method based on efficient feature representations to predict recurrence outcomes within three years after surgery. Radiomics features during arterial phase (AP) and clinical data were selected for training the ensemble models. In order to improve the efficiency of the process, the lesion area was automatically segmented by 3D U-Net. It was found that the mIoU of the segmentation model was 0.8874, and the Light Gradient Boosting Machine (LightGBM) was the most superior, with an average accuracy of 0.7600, a recall of 0.7673, a F score of 0.7553, and an AUC of 0.8338 when inputting radiomics features during AP and clinical baseline indicators. Studies have shown that the proposed strategy can relatively accurately predict the recurrence outcome within three years, which is helpful for physicians to evaluate individual patients before surgery.

Ensemble learning based on efficient features combination can predict the outcome of recurrence-free survival in patients with hepatocellular carcinoma within three years after surgery.

Liver cancer is a common cause of death from cancer in the population, with the 4th highest mortality rate from cancer worldwide. The high recurrence rate of hepatocellular carcinoma after surgery is an important cause of high mortality among patients. In this paper, based on eight scheduled core markers of liver cancer, an improved feature screening algorithm was proposed based on the analysis of the basic principles of the random forest algorithm, and the system was finally applied to liver cancer prognosis prediction to improve the prediction of biomarkers for liver cancer recurrence, and the impact of different algorithmic strategies on the prediction accuracy was compared and analyzed. The results showed that the improved feature screening algorithm was able to reduce the feature set by about 50% while ensuring that the prediction accuracy was reduced within 2%.

Improved prognostic prediction model for liver cancer based on biomarker data screened by combined methods.

Long noncoding RNAs (lncRNA) regulate a number of aspects of cancer biology. Recent research has shown that lncRNAs can encode micropeptides that mediate their functions in tumors. Here, we revealed that the liver-specific putative lncRNA, AC115619, is expressed at low levels in hepatocellular carcinoma (HCC) and encodes a micropeptide, designated as AC115619-22aa. AC115619 played a crucial role in the regulation of tumor progression and was a prognostic indicator in HCC. The encoded micropeptide AC115619-22aa inhibited the progression of HCC by binding to WTAP and impeding the assembly of the N6-methyladenosine (m6A) methyltransferase complex, which regulates the expression of tumor-associated genes, such as SOCS2 and ATG14. AC115619 was cotranscribed with the adjacent upstream coding gene APOB, and hypoxia induced transcriptional repression of both APOB and AC115619 by controlling HIF1A/HDAC3 and HNF4A signaling. In animal and patient-derived models, AC115619-22aa reduced global m6A levels and suppressed tumor growth. In conclusion, this study establishes AC115619 and its encoded micropeptide as potential prognostic markers and therapeutic targets for patients with HCC.

Hypoxia-Responsive lncRNA AC115619 Encodes a Micropeptide That Suppresses m6A Modifications and Hepatocellular Carcinoma Progression.

Mining gene expression data is valuable for discovering novel biomarkers and therapeutic targets in hepatocellular carcinoma (HCC). Although emerging data mining tools are available for pan-cancer-related gene data analysis, few tools are dedicated to HCC. Moreover, tools specifically designed for HCC have restrictions such as small data scale and limited functionality. Therefore, we developed IHGA, a new interactive web server for discovering genes of interest in HCC on a large-scale and comprehensive basis. Integrative HCC Gene Analysis (IHGA) contains over 100 independent HCC patient-derived datasets (with over 10,000 tissue samples) and more than 90 cell models. IHGA allows users to conduct a series of large-scale and comprehensive analyses and data visualizations based on gene mRNA levels, including expression comparison, correlation analysis, clinical characteristics analysis, survival analysis, immune system interaction analysis, and drug sensitivity analysis. This method notably enhanced the richness of clinical data in IHGA. Additionally, IHGA integrates artificial intelligence (AI)-assisted gene screening based on natural language models. IHGA is free, user-friendly, and can effectively reduce time spent during data collection, organization, and analysis. In conclusion, IHGA is competitive in terms of data scale, data diversity, and functionality. It effectively alleviates the obstacles caused by HCC heterogeneity to data mining work and helps advance research on the molecular mechanisms of HCC.

IHGA: An interactive web server for large-scale and comprehensive discovery of genes of interest in hepatocellular carcinoma.

Pringle maneuver (PM) is a double-edged sword in liver resection, which is beneficial in reducing blood loss but also causes ischemia-reperfusion injury which may stimulate the outgrowth of micrometastases. The impact of PM on tumor recurrence remains controversial. This study aimed to assess whether PM has effect on the prognosis of colorectal cancer liver metastases (CRLM) after hepatectomy.

Effect of Pringle maneuver on prognosis of patients with colorectal cancer liver metastases after liver resection: a meta-analysis.

The role of solute carrier family 25 member 15 (SLC25A15), a critical component of the urea cycle, in hepatocellular carcinoma (HCC) progression remains poorly understood. This study investigated the impact of SLC25A15 on HCC progression and its mechanisms.

Deficiency in SLC25A15, a hypoxia-responsive gene, promotes hepatocellular carcinoma by reprogramming glutamine metabolism.

Cleavage stimulation factor subunit 2 (CSTF2) is a fundamental factor in the regulation of 3'-end cleavage and alternative polyadenylation of pre-mRNAs. Previous work has identified a tumor-promoting role of CSTF2, suggesting that it may represent a potential therapeutic target. In this study, we aimed to elucidate the mechanistic function of CSTF2 in hepatocellular carcinoma (HCC). CSTF2 upregulation was frequent in HCC, and elevated levels of CSTF2 correlated with poor patient prognosis. Although CSTF2 inhibition did not suppress HCC growth under nonstress conditions, it supported tolerance and survival of HCC cells under hypoxic conditions. Mechanistically, CSTF2 increased phosphoglycerate kinase 1 (PGK1) protein production to enhance glycolysis, thereby sustaining the energy supply under hypoxic conditions. CSTF2 shortened the 3' untranslated region of PGK1 pre-mRNA by binding near the proximal polyadenylation site. This shortening led to a loss of N6-methyladenosine (m6A) modification sites that are bound by YTH m6A RNA-binding protein F2 and increase degradation of PGK1 mRNA. Concurrently, hypoxia increased m6A modification of PGK1 mRNA near the proximal polyadenylation site that was recognized by the YTH m6A RNA-binding protein C1, which recruited CSTF2 to enhance the shortening of the PGK1 3' untranslated region. A small-molecule screen identified masitinib as an inhibitor of CSTF2. Masitinib counteracted PGK1 upregulation by CSTF2 and suppressed the growth of HCC xenograft and patient-derived organoid models. In conclusion, this study revealed a function of CSTF2 in supporting HCC survival under hypoxia conditions through m6A modification evasion and metabolic reprogramming, indicating that inhibiting CSTF2 may overcome hypoxia tolerance in HCC. Significance: Targeting CSTF2 inhibits hepatocellular carcinoma survival in hypoxic microenvironments, which may be a promising therapeutic strategy for treating liver cancer.

CSTF2 Supports Hypoxia Tolerance in Hepatocellular Carcinoma by Enabling m6A Modification Evasion of PGK1 to Enhance Glycolysis.

According to previous studies, vessels encapsulating tumour clusters (VETC) could promote metastasis of hepatocellular carcinoma (HCC) in a manner independent from epithelial-mesenchymal transition (EMT). However, the prognostic significance of VETC among patients undergoing curative hepatectomy has not been fully explored. This study was performed to assess the prognostic significance of VETC among patients with HCC undergoing curative hepatectomy. A total of 81 patients were included in this study. A predictive model based on VETC was established, then this model was compared with the American Joint Committee on Cancer, Tumor Node Metastasis (AJCC TNM) stage and Barcelona Clinic Liver Cancer (BCLC) system. It was revealed by multivariate Cox regression analysis that a high neutrophil-to-lymphocyte ratio (NLR) [p=0.013, hazard ratio (HR)=6.175, 95% confidence interval (CI) 1.468-25.977], number of tumours (p<0.001, HR=4.119, 95% CI 1.886-8.995) and VETC positivity (p=0.010, HR=2.440, 95% CI 1.235-4.821) were independent predictive factors for disease-free survival (DFS). Additionally, by Kaplan-Meier analysis, we revealed that VETC positivity was associated with worse DFS (p=0.018). The clinical predictive model combining the NLR, number of tumours, and VETC was compared with AJCC TNM stage and BCLC classification system by performing time-dependent receiver operating curve (td-ROC) analysis, revealing that the clinical predictive model was superior to AJCC TNM stage and BCLC system at different timepoints. Additionally, we demonstrated that the clinical model could well predict DFS by plotting calibration curves. VETC could be utilised as an efficient prognostic factor for HCC and the clinical predictive model combining the NLR, number of tumours, and VETC was superior to AJCC TNM stage and BCLC system in predicting cancer recurrence.

Establishment of a clinical model based on vessels encapsulating tumour clusters that could efficiently predict recurrence of patients with hepatocellular carcinoma after curative hepatectomy.

Radiomic features extracted from preoperative contrast-enhanced computed tomography (CT) images have been shown to predict the prognosis of hepatocellular carcinoma (HCC). However, the prognostic role of radiomic features obtained from postoperative contrast-enhanced CT images of the remnant liver remains unclear. This study explored the prognostic value of radiomic features extracted from postoperative contrast-enhanced CT images in patients with HCC.

Radiomic features on contrast-enhanced images of the remnant liver predict the prognosis of hepatocellular carcinoma after partial hepatectomy.

The liver contains a complex structure of blood vessels and bile ducts, and the vascular structure is highly variable. The anatomical segmentation of the liver is still controversial, and the Couinaud segmentation method based on the portal vein is more widely used in clinical practice. The treatment of liver tumors and other lesions is closely related to the liver anatomy. The mechanism of liver tumor invasion and metastasis is complex, and it is currently believed that tumor invasion mainly spreads along the portal vein. Anatomic liver resection is an important surgical method for liver diseases, especially liver tumors. This article reviews the vascular structure of the liver, the development of anatomical hepatectomy, blood flow control, surgical planning, intraoperative navigation, minimally invasive surgery, and precise hepatectomy. Anatomic liver resection is a part of precision liver surgery, which is becoming increasingly more precise in terms of surgical evaluation, surgical planning, and surgical operation. New technologies will facilitate precision surgery with less trauma and greater benefits for patients. With the development and advancement of technology, image-based surgical planning and intraoperative surgical navigation will become more widely used in precision liver surgery.

The evolution of anatomical hepatectomy: Past, present, and future.

Liver cancer is a leading cause of cancer-related death worldwide, and its complexity and heterogeneity pose considerable challenges to conventional treatment. In recent years, the rise of organoid technology has provided new perspectives and tools for precision medicine in oncology. The use of high-fidelity organoids capable of recapitulating patients' genotypic and phenotypic features can further facilitate personalised treatment. In this review, we discuss 1) the advantages of liver cancer organoids as disease models over traditional models; 2) the origin and establishment of liver cancer organoids; 3) the application of liver cancer organoids technology in tumour precision medicine; 4) the technical tools of liver cancer-derived organoids; and 5) current solutions for the deficiencies and challenges of liver cancer organoids. This review should provide both a deeper understanding of the research progress and application prospects of liver cancer organoids, as well as theoretical support and practical guidance for more complete integration of liver cancer research and precision medicine.

The application of liver cancer organoids in tumour precision medicine: A comprehensive review.

By far, non-invasive methods assessing Ki-67 are still scarce. This study was performed to evaluate the capability of radiomics based on contrast-enhanced CT in predicting expression of Ki-67 in hepatocellular carcinoma (HCC).

Article	Year
Ensemble learning based on efficient features combination can predict the outcome of recurrence-free survival in patients with hepatocellular carcinoma within three years after surgery. Frontiers in oncology\| PubMed ID: 36439437	2022
Improved prognostic prediction model for liver cancer based on biomarker data screened by combined methods. Mathematical biosciences and engineering : MBE\| PubMed ID: 36896547	2023
Hypoxia-Responsive lncRNA AC115619 Encodes a Micropeptide That Suppresses m6A Modifications and Hepatocellular Carcinoma Progression. Cancer research\| PubMed ID: 37326474	2023
IHGA: An interactive web server for large-scale and comprehensive discovery of genes of interest in hepatocellular carcinoma. Computational and structural biotechnology journal\| PubMed ID: 37635767	2023
Effect of Pringle maneuver on prognosis of patients with colorectal cancer liver metastases after liver resection: a meta-analysis. Langenbeck's archives of surgery\| PubMed ID: 38316643	2024
Deficiency in SLC25A15, a hypoxia-responsive gene, promotes hepatocellular carcinoma by reprogramming glutamine metabolism. Journal of hepatology\| PubMed ID: 38450598	2024
CSTF2 Supports Hypoxia Tolerance in Hepatocellular Carcinoma by Enabling m6A Modification Evasion of PGK1 to Enhance Glycolysis. Cancer research\| PubMed ID: 39514400	2025
Establishment of a clinical model based on vessels encapsulating tumour clusters that could efficiently predict recurrence of patients with hepatocellular carcinoma after curative hepatectom... Pathology\| PubMed ID: 39668071	2025
Radiomic features on contrast-enhanced images of the remnant liver predict the prognosis of hepatocellular carcinoma after partial hepatectomy. iLIVER\| PubMed ID: 40636723	2024
The evolution of anatomical hepatectomy: Past, present, and future. iLIVER\| PubMed ID: 40636792	2022
The application of liver cancer organoids in tumour precision medicine: A comprehensive review. iLIVER\| PubMed ID: 40741108	2025
CT-Based Radiomics for Non-Invasive Prediction of Ki-67 Expression in Hepatocellular Carcinoma. Journal of hepatocellular carcinoma\| PubMed ID: 41868262	2026

Meilong Wu

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