Abstract Background: Liver cancer has one of the highest death rates in the world. Hepatectomy is the most important treatment for liver cancer. Preoperative evaluation of hepatic reserve is required to determine whether hepatectomy is feasible. Indocyanine green (ICG) clearance assay is an effective way to assess liver function prior to hepatectomy. However, due to its high cost and adverse reactions in some patients, we need to find a noninvasive method equivalent to the ICG clearance test. Methods: We retrospectively analyzed 650 clinical data to explore the risk factors that affect liver reserve function. Logistic regression model was established by SPSS, and linear regression was established an equivalent formula for predicting the ICG 15-minute retention rate. Result: We found that spleen volume and the LDY were independent risk factors for the ICG 15-minute retention rate and found a linear correlation between spleen volume and the LDY. Finally, the formula was obtained: LN(Y(ICG-R15))=3.466+0.045X1(LDY)-0.066X2(ALB)-0.002X3(Cr)-0.002X4(PLT)+0.007X6(TBIL)+0.116X7(PT),R20.395. The area under the ROC curve (AUC) was 0.83 for ICG-R15≥10%. The accuracy was 86%. Conclusions: We have found that spleen volume is an independent risk factor for the ICG 15-minute retention rate and can simplify the prediction of liver reserve function through LDY.
Abstract Background: With the progress of hepatocellular carcinoma (HCC) treatment methods, the incidence rate of extrahepatic metastasis (EHM) of HCC has increased, which has a significant impact on patient prognosis. Lipid metabolism reprogramming has emerged as an important feature of HCC. However, the prognostic potential of lipid metabolism-related genes in EHM of HCC has not been comprehensively studied. Methods: Sixty-five metastasis-related differentially expressed genes (DEGs) were obtained from the GEO database. HCC patients in the TCGA database were used as the training cohort for hierarchical clustering, and specimens in the ICGC database were used as the validation cohort. Enrichment analysis was performed by GO, KEGG, and GSEA, and the validated lipid metabolism score methods were used to evaluate lipid metabolism levels. A LASSO regression model was applied to select prognostic genes and construct the LMRMS. The CIBERSORT algorithm and ssGSEA were used to estimate immune infiltration. qPCR and Western blotting were used to detect expression levels of the target genes. Results: First, we obtained two metastasis risk subtypes. The high metastasis risk group had a high lipid metabolism score and poor survival prognosis. Enrichment analysis showed that there were significant differences in a variety of lipid metabolism and drug metabolism pathways between the two subtypes. We further established an LMRMS. Immune infiltration showed different immune landscapes between the two subtypes. The LMRMS can effectively predict overall survival (OS), lipid metabolism level, different immune landscapes, and immunotherapy response and was well verified in the validation cohort. In vitro experiments confirmed that gene expression in the LMRMS was closely related to lipid metabolism, which is worthy of further study. Conclusions: We first studied the prognostic significance and immunometabolic landscape of lipid metabolism-related genes in EHM of HCC. We propose an LMRMS, which can provide vital guidance for early identification of high-risk EHM patients and individualized immunotherapy for patients with EHM of HCC.
It has been reported that postoperative adjuvant TACE (PA-TACE) treatment decreases recurrence and significantly improves the survival of patients who undergo radical resection of hepatocellular carcinoma (HCC) with high-risk recurrence factors. However, when to perform PA-TACE has not been fully studied.We retrospectively collected the clinicopathologic characteristics of the patients with HCC between October 2013 and June 2020. The optimal cutoff value for PA-TACE time was determined based on the R package "maxstat". Logistic regression and Cox regression analysis were used to determine the effect of the choice of PA-TACE timing on prognosis.The analysis was performed on 789 patients with HCC, and 484 patients were finally involved and were divided into training cohort (378) and validation cohort (106). The PA-TACE timing was found to be associated with survival outcomes. Multivariate logistic analysis found independent predictors of the PA-TACE timing, including gender and history of HBV. Multivariate Cox analysis showed that Ki-67, tumor size, MVI and the PA-TACE timing were independent prognostic factors for RFS in HCC patients.Based on this study, HCC patients with high-risk recurrence factors can receive personalized assistance in undergoing PA-TACE treatment and improve their survival outcomes.
The combined application of immune cells and specific biomarkers related to the tumor immune microenvironment has a better predictive value for the prognosis of HCC. The purpose of this study is to construct a new prognostic model based on immune-related genes that regulate cross-talk between immune and tumor cells to assess the prognosis and explore possible mechanisms.The immune cell abundance ratio of 424 cases in the TCGA-LIHC database is obtained through the CIBERSORT algorithm. The differential gene analysis and cox regression analysis is used to screen IRGs. In addition, the function of IRGs was preliminarily explored through the co-culture of M2 macrophages and HCC cell lines. The clinical validation, nomogram establishment and performing tumor microenvironment score were validated.We identified 4 immune cells and 9 hub genes related to the prognosis. Further, we identified S100A9, CD79B, TNFRSF11B as an IRGs signature, which is verified in the ICGC and GSE76427 database. Importantly, IRGs signature is closely related to the prognosis, tumor microenvironment score, clinical characteristics and immunotherapy, and nomogram combined with clinical characteristics is more conducive to clinical promotion. In addition, after co-culture with M2 macrophages, the migration capacity and cell pseudopod of MHCC97H increased significantly. And CD79B and TNFRSF11B were significantly down-regulated in MHCC97H, Huh7 and LM3, while S100A9 was up-regulated.We constructed an IRGs signature and discussed possible mechanisms. The nomogram established based on IRGs can accurately predict the prognosis of HCC patients. These findings may provide a suitable therapeutic target for HCC.
Abstract Hypoxia plays an important role in the metastasis of hepatocellular carcinoma (HCC). Exosomes have been widely studied as mediators of communication between tumours and immune cells. However, the specific mechanism by which hypoxic HCC cell‐derived exosomes suppress antitumor immunity is unclear. Hypoxia scores were determined for The Cancer Genome‐Liver Hepatocellular Carcinoma (TCGA‐LIHC) dataset patients, and HCC patients in the hyperhypoxic group had a higher degree of M2 macrophage infiltration. Patients in the M2 high‐invasion group had a lower probability of survival than those in the low‐invasion group. In vivo and in vitro experiments demonstrated that exosomes secreted by hypoxic HCC cells promote M2 macrophage polarization. This polarization induces apoptosis in CD8+ T cells. Additionally, it encourages epithelial–mesenchymal transition (EMT), which increases HCC migration. Exosomal miRNA sequencing revealed that miR‐1290 was highly expressed in exosomes secreted by hypoxic HCC cells. Mechanistically, miR‐1290 in macrophages inhibited Akt2 while upregulating PD‐L1 to promote M2 polarization, induce apoptosis in CD8 + T cells, and enhance EMT in HCC. Animal studies found that the miR‐1290 antagomir in combination with the immune checkpoint inhibitor produced better antitumor effects than the monotherapies. In conclusion, the secretion of exosome‐derived miR‐1290 from HCC cells in a hypoxic environment supported immune escape by HCC cells by promoting M2 macrophage polarization to induce apoptosis in CD8 + T cells and enhance EMT that promoted HCC metastasis. Therefore, miR‐1290 is an important molecule in antitumor immunity in HCC, and inhibition of miR‐1290 could provide a novel immunotherapeutic approach for HCC treatment.
Robotic pancreatoduodenectomy (RPD) technology is developing rapidly, but there is still a lack of a specific and objective difficulty evaluation system in the field of application and training of RPD surgery.The clinical data of patients who underwent RPD in our hospital from November 2014 to October 2020 were analyzed retrospectively. Univariate and multivariate logistic regression analyses were used to determine the predictors of operation difficulty and convert into a scoring system.A total of 72 patients were enrolled in the group. According to the operation time (25%), intraoperative blood loss (25%), conversion to laparotomy, and major complications, the difficulty of operation was divided into low difficulty (0-2 points) and high difficulty (3-4 points). The multivariate logistic regression model included the thickness of mesenteric tissue (P1) (P = 0.035), the thickness of the abdominal wall (B1) (P = 0.017), and the preoperative albumin (P = 0.032), and the nomogram was established. AUC = 0.773 (0.645-0.901).The RPD difficulty evaluation system based on the specific anatomical relationship between da Vinci's laparoscopic robotic arm and tissues/organs in the operation area can be used as a predictive tool to evaluate the surgical difficulty of patients before operation and guide clinical practice.
Abstract Ajuvant therapy with molecularly targeted drugs has become the effective treatment for advanced hepatocellular carcinoma (HCC). While Hypoxia often induces changes in the tumor immune microenvironment and affects the progression of targeted drug resistance, there is a critically unmet need for effective identification of drug resistance progression to reverse targeted drug resistance. Herein, we identified 64 sorafenib-resistance genes for hierarchical clustering of 374 HCC patients in the TCGA database. The functional enrichment between low (LR-group) and high (HR-group) resistance groups was explored through GO, KEGG, GSVA, ssGSEA, CIBERSORT, XCELL and three hypoxia scoring formula. It was found that the upregulated epithelial-mesenchymal transition (EMT), higher hypoxic scores and lower CD8 + T cell infiltration in HR-group. we further identified that HR-group had higher CD8 + T cell exhaustion, and the immune checkpoints of CD8 + T cell involved in tumor antigen recognition disorders significantly increased. Furthermore, form hypoxia-related resistance gene signature (HDRGs)(including 9 key genes),we derive a risk score: the score correlates strongly with hypoxia, targeted drug resistance, CD8 + T cell infiltration and exhaustion and is accurately verified in TCGA, ICGC and GAO’ HCC Cohort. Additionaly, experimental verification showed that ADM were upregulated under hypoxia, so knockdown of ADM can inhibit EMT under hypoxia and increase the sensitivity of Lenvatinib. Collectively, this study reveals that hypoxia-induced dysfunction of CD8 + T cells causes drug resistance, which can be effectively predicted by our HDRGs, and broadly leveraging this risk score to provide guidance for tumor targeting and combination immunotherapy.
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