Deciphering intratumoral heterogeneity of hepatocellular carcinoma with microvascular invasion with radiogenomic analysis.

BACKGROUND AND AIMS: The recurrence and metastasis of hepatocellular carcinoma (HCC) are mainly caused by microvascular invasion (MVI). Our study aimed to uncover the cellular atlas of MVI+ HCC and investigate the underlying immune infiltration patterns with radiomics features. METHODS: Three MVI positive HCC and three MVI negative HCC samples were collected for single-cell RNA-seq analysis. 26 MVI positive HCC and 30 MVI negative HCC tissues were underwent bulk RNA-seq analysis. For radiomics analysis, radiomics features score (Radscore) were built using preoperative contrast MRI for MVI prediction and overall survival prediction. We deciphered the metabolism profiles of MVI+ HCC using scMetabolism and scFEA. The correlation of Radscore with the level of APOE+ macrophages and iCAFs was identified. Whole Exome Sequencing (WES) was applied to distinguish intrahepatic metastasis (IM) and multicentric occurrence (MO). Transcriptome profiles were compared between IM and MO. RESULTS: Elevated levels of APOE+ macrophages and iCAFs were detected in MVI+ HCC. There was a strong correlation between the infiltration of APOE+ macrophages and iCAFs, as confirmed by immunofluorescent staining. MVI positive tumors exhibited increased lipid metabolism, which was attributed to the increased presence of APOE+ macrophages. APOE+ macrophages and iCAFs were also found in high levels in IM, as opposed to MO. The difference of infiltration level and Radscore between two nodules in IM was relatively small. Furthermore, we developed Radscore for predicting MVI and HCC prognostication that were also able to predict the level of infiltration of APOE+ macrophages and iCAFs. CONCLUSION: This study demonstrated the interactions of cell subpopulations and distinct metabolism profiles in MVI+ HCC. Besides, MVI prediction Radscore and MVI prognostic Radscore were highly correlated with the infiltration of APOE+ macrophages and iCAFs, which helped to understand the biological significance of radiomics and optimize treatment strategy for MVI+ HCC.

Comprehensive analysis of tumor immune microenvironment and prognosis of m6A-related lncRNAs in gastric cancer.

BACKGROUND: N6-methyladenosine (m6A) modification and long non-coding RNAs (lncRNAs) play pivotal roles in gastric cancer (GC) progression. The emergence of immunotherapy in GC has created a paradigm shift in the approaches of treatment, whereas there is significant heterogeneity with regard to degree of treatment responses, which results from the variability of tumor immune microenvironment (TIME). How the interplay between m6A and lncRNAs enrolling in the shaping of TIME remains unclear. METHODS: The RNA sequencing and clinical data of GC patients were collected from TCGA database. Pearson correlation test and univariate Cox analysis were used to screen out m6A-related lncRNAs. Consensus clustering method was implemented to classify GC patients into two clusters. Survival analysis, the infiltration level of immune cells, Gene set enrichment analysis (GSEA) and the mutation profiles were analyzed and compared between two clusters. A competing endogenous RNA (ceRNA) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of pathways in which m6A-related lncRNAs enriched. Then least absolute shrinkage and selection operator (LASSO) COX regression was implemented to select pivotal lncRNAs, and risk model was constructed accordingly. The prognosis value of the risk model was explored. In addition, the response to immune checkpoint inhibitors (ICIs) therapy were compared between different risk groups. Finally, we performed qRT-PCR to detect expression patterns of the selected lncRNAs in the 35 tumor tissues and their paired adjacent normal tissues, and validated the prognostic value of risk model in our cohort (N = 35). RESULTS: The expression profiles of 15 lncRNAs were included to cluster patients into 2 subtypes. Cluster1 with worse prognosis harbored higher immune score, stromal score, ESTIMATE score and lower mutation rates of the genes. Different immune cell infiltration patterns were also displayed between the two clusters. GSEA showed that cluster1 preferentially enriched in tumor hallmarks and tumor-related biological pathways. KEGG pathway analysis found that the target mRNAs which m6A-related lncRNAs regulated by sponging miRNAs mainly enriched in vascular smooth muscle contraction, cAMP signaling pathway and cGMP-PKG signaling pathway. Next, eight lncRNAs were selected by LASSO regression algorithm to construct risk model. Patients in the high-risk group had poor prognoses, which were consistent in our cohort. As for predicting responses to ICIs therapy, patients from high-risk group were found to have lower tumor mutation burden (TMB) scores and account for large proportion in the Microsatellite Instability-Low (MSI-L) subtype. Moreover, patients had distinct immunophenoscores in different risk groups. CONCLUSION: Our study revealed that the interplay between m6A modification and lncRNAs might have critical role in predicting GC prognosis, sculpting TIME landscape and predicting the responses to ICIs therapy.

Risk stratification of LI-RADS M and LI-RADS 4/5 combined hepatocellular cholangiocarcinoma: prognostic values of MR imaging features and clinicopathological factors.

OBJECTIVES: To investigate the role of clinicopathological factors and MR imaging factors in risk stratification of combined hepatocellular cholangiocarcinoma (cHCC-CCA) patients who were classified as LR-M and LR-4/5. METHODS: We retrospectively identified consecutive patients who were confirmed as cHCC-CCA after surgical surgery in our institution from June 2015 to November 2020. Two radiologists evaluated the preoperative MR imaging features independently, and each lesion was assigned with a LI-RADS category. Preoperative clinical data were also collected. Multivariate Cox proportional hazards model was applied to separately identify the independent factors correlated with the recurrence of cHCC-CCAs in LR-M and LR-4/5. Risk stratifications were conducted separately in LR-M and LR-4/5. Recurrence-free survival (RFS) rates and overall survival (OS) rates were analyzed by using the Kaplan-Meier survival curves and log-rank test. RESULTS: A total of 131 patients with single primary lesion which met the 2019 WHO classification criteria were finally included. Corona enhancement, delayed central enhancement, and microvascular invasion (MVI) were identified as predictors of RFS in LR-M. Mosaic architecture, CA19-9, and MVI were independently associated with RFS in LR-4/5. Based on the number of these independent predictors, patients were stratified into favorable-outcome groups (LR-ML subgroup and LR-4/5L subgroup) and dismal-outcome groups (LR-MH subgroup and LR-4/5H subgroup). The corresponding median RFS for LR-ML, LR-MH, LR-5L, and LR-5H were 25.6 months, 8.2 months, 51.7 months, and 18.1 months. CONCLUSION: Our study explored the prognostic values of imaging and clinicopathological factors for LR-M and LR-4/5 cHCC-CCA patients, and different survival outcomes were observed among four subgroups after conducting risk stratifications. KEY POINTS: • Corona enhancement, delayed central enhancement, and MVI were identified as predictors of RFS in cHCC-CCAs which were classified into LR-M. Mosaic architecture, CA19-9, and MVI were independently associated with RFS in cHCC-CCAs which were classified into LR-4/5. • Based on the identified risk factors, LR-M and LR-4/5 cHCC-CCA patients could be stratified into two subgroups respectively, with significantly different RFS and OS. • cHCC-CCA patients from LR-M did not always have worse RFS and OS than those from LR-4/5 in some cases.

Clinical Study on Systemic Lupus Erythematosus Complicated with Knee Bone Infarction.

Objective: The present study aims to (1) analyze the clinical characteristics and related influencing factors of knee bone infarction in systemic lupus erythematosus (SLE) and (2) improve the understanding of SLE complicated with knee bone infarction. Methods: The data of patients with SLE complicated with knee bone infarction were retrospectively analysed; patients with SLE during the same period who matched in age, gender, and disease duration were selected as control subjects, with a 1 : 1 ratio with the SLE group. The clinical data were collected to analyze the risk factors for SLE complicated with knee bone infarction. Results: In a total of 36 (6.4%) of 563 patients aged 19-33 (25.8 ± 4.8) years who had SLE during the same period, the disease was complicated with knee bone infarction. The diagnosis of knee bone infarction was made at an SLE duration of 7-65 (26.2 ± 15.7) months. During the SLE course, knee bone infarction occurred within 1 year in 6 cases (16.7%), within 1-5 years in 28 cases (77.8%), and in >5 years in 2 cases (5.6%). Raynaud's phenomenon incidence and anti-nRNP antibody positivity were significantly higher in the knee bone infarction group than in the control group (P < 0.01 and P < 0.05, respectively). The cumulative glucocorticoid dose at 1, 3, and 6 months was significantly higher in the knee bone infarction group than in the control group (P < 0.05). SLE complicated with knee necrosis had a statistically significant rank correlation with Raynaud's phenomenon (r = 0.445, P < 0.001), anti-nRNP antibody (r = 0.309, P=0.008), and renal injury (r = 0.252, P=0.032). The multivariate analysis of SLE complicated with knee bone infarction showed that Raynaud's phenomenon was an independent influencing factor for the complicated knee bone infarction in SLE patients (OR = 4.938, P=0.004), and the probability of SLE complicated with knee bone infarction in Raynaud's phenomenon positive patients was 4.938 times that of Raynaud's phenomenon negative patients. Conclusions: The risk of knee bone infarction was relatively high in patients with SLE within a 5-year disease course and in young patients. The risk factors were Raynaud's phenomenon, anti-nRNP antibody positivity, and early high-dose glucocorticoid therapy.

HNRNPAB-regulated lncRNA-ELF209 inhibits the malignancy of hepatocellular carcinoma.

Our previous study demonstrated that heterogeneous nuclear ribonucleoprotein AB (HNRNPAB) is a key gene that facilitates metastasis of hepatocellular carcinoma (HCC). However, the molecular mechanisms behind this relationship are not fully understood. In our study, we utilized long-noncoding RNA (lncRNA) microarrays to identify a HNRNPAB-regulated lncRNA named lnc-ELF209. Our findings from chromatin immunoprecipitation assays indicate that HNRNPAB represses lnc-ELF209 transcription by directly binding to its promoter region. We also analyzed clinical samples from HCC patients and cell lines with quantitative real-time polymerase chain reactions, RNA in situ hybridization and immunohistochemistry, and found that there is a negative relationship between HNRNPAB and lnc-ELF209 expression. Up/downregulation assays and rescue assays indicate that lnc-ELF209 inhibits cell migration, invasion and epithelial-mesenchymal transition regulated by HNRNPAB. This suggests a new regulatory mechanism for HNRNPAB-promoted HCC progression. RNA pull-down and LC-MS/MS were used to determine triosephosphate isomerase, heat shock protein 90-beta and vimentin may be involved in the tumor-suppressed function of lnc-ELF209. Furthermore, we found lnc-ELF209 could stabilize TPI protein expression. We also found that lnc-ELF209 overexpression in HCCLM3 cell resulted in a lower rate of lung metastatic, which suggested a less aggressive HCC phenotype. Collectively, these findings offer new insights into the regulatory mechanisms that underlie HNRNPAB cancer-promoting activities and demonstrate that lnc-ELF209 is a HNRNPAB-regulated lncRNA that may play an important role in the inhibition of HCC progression.

Identification and validation of tumour microenvironment-based immune molecular subgroups for gastric cancer: immunotherapeutic implications.

BACKGROUND: Immunotherapy could trigger durable response in advanced gastric cancer, but it only benefits a minority of patients. We aimed to propose a robust molecular classification of gastric cancer microenvironment to identify ideal candidates for tailoring effective immunotherapy. METHODS: A training cohort of 375 gastric cancer samples with RNA sequencing data was analysed. We virtually microdissected tumour, stromal, and immune cell gene expression patterns employing a non-negative matrix factorization algorithm. These expression patterns were annotated using immune- and stromal-related gene signatures. Validation of immunogenomic classification was performed across six microarray datasets of 1406 samples. RESULTS: We found approximately half of gastric cancer samples to have higher immune cell infiltrates, PD-L1 expression, markers of cytolytic activity, and fewer copy number aberrations (all P < 0.05). We termed this group of tumours the Immune Class, which incorporated two components, namely Immune Activation and Immunosuppressive Subtype, according to immunosuppressive or activated microenvironment. Immune Activation Subtype was associated with improved survival in multivariate survival analysis and shared similar genomic characteristics with responders of anti-PD-1 therapy. Immunosuppressive Subtype featured high immune infiltration, stromal enrichment, and transforming growth factor (TGF)-ß signalling pathway activation and correlated with non-responsiveness signature of checkpoint blockade therapy, which might be suitable for anti-PD-L1 and anti-TGF-ß combined therapy. CONCLUSIONS: We proposed and independently validated three reproducible immune molecular subtypes of gastric cancer, which may provide implications for patient selection of immunotherapy.

Comparative efficacy and safety of immunosuppressive therapies for systemic sclerosis related interstitial lung disease: A Bayesian network analysis.

Objectives: Immunosuppressive therapies for the treatment of patients with systemic sclerosis (SSc) and SSc related interstitial lung diseases (SSc-ILD) include cyclophosphamide (CYC), mycophenolate mofetil (MMF), azathioprine (AZA) and methotrexate (MTX). The objectives were to compare and rank these therapies in term of forced vital capacity (FVC) % predicted, diffusing capacity of the lung for carbon monoxide (DLco) % predicted and adverse events (AEs).Methods: We present pooled estimates of mean difference (MD) and odds rates (ORs) with 95% confidence intervals (CIs) among different therapies. We also ranked these agents with surface under the cumulative ranking probability (SUCRA).Results: CYC plus AZA had the highest SUCRA probability (70%) on reducing risk of the deterioration of FVC compared with CYC, observation (OBS), MMF and AZA. While for the prevention of the deterioration of DLco, MMF showed the highest SUCRA probability (76%) compared with others. Moreover, AZA showed the lowest probability (32%) for AEs among active interventions.Conclusions: CYC plus AZA was the preferred immunosuppressive strategies compared to others on preventing the deterioration of FVC. MMF resulted with the highest probability as the best in preventing the deterioration of DLco. Monotherapy of AZA was less pulmonary function benefit but related less AEs.

Prognostic alternative mRNA splicing signature in hepatocellular carcinoma: a study based on large-scale sequencing data.

Most genes are alternatively spliced and increasing number of evidences show that alternative splicing (AS) is modified and related to tumor progression. Systematic profiles of AS signature in hepatocellular carcinoma (HCC) is absent and urgently needed. Here, differentially spliced AS transcripts between HCC and non-HCC tissues were compared, prognosis-associated AS events by using univariate Cox regression analysis were selected. Our gene functional enrichment analysis demonstrated the potential pathways enriched by survival-associated AS. Prognostic AS signatures were then constructed for HCC prognosis prediction by Lasso regression model. We also analyzed splicing factors (SFs) regulating underlying mechanisms by Pearson correlation and then built corresponding regulatory networks. In addition, we explored the performance of AS signature in the mutated HCC samples. Genome-wide AS events in 377 HCC patients from TCGA were profiled. Among 34 163 AS events in 8985 genes, 3950 AS events in 2403 genes associated with overall survival (OS) significantly for HCC were detected. In addition, computational algorithm results showed that metabolic and ribosome pathways may be the potential molecular mechanisms regulating the poor prognosis. More importantly, survival-associated AS signatures revealed high performance in predicting HCC prognosis. The area under curve for AS signature was 0.806 in all HCC and 0.944 in TP53 mutated HCC samples at 2000 days of OS. We submitted prognostic SFs to build the AS regulatory network, from which we found prognostic AS events were significantly enriched in metabolism-related pathways. A robust AS signature for HCC patients and revealed the regulatory splicing networks contributing to the potential significantly enriched metabolism-related pathways.

Development and validation of a new tumor-based gene signature predicting prognosis of HBV/HCV-included resected hepatocellular carcinoma patients.

BACKGROUND: Due to the phenotypic and molecular diversity of hepatocellular carcinomas (HCC), it is still a challenge to determine patients' prognosis. We aim to identify new prognostic markers for resected HCC patients. METHODS: 274 patients were retrospectively identified and samples collected from Zhongshan hospital, Fudan University. We analyzed the gene expression patterns of tumors and compared expression patterns with patient survival times. We identified a "9-gene signature" associated with survival by using the coefficient and regression formula of multivariate Cox model. This molecular signature was then validated in three patients cohorts from internal cohort (n = 69), TCGA (n = 369) and GEO dataset (n = 80). RESULTS: We identified 9-gene signature consisting of ZC2HC1A, MARCKSL1, PTGS1, CDKN2B, CLEC10A, PRDX3, PRKCH, MPEG1 and LMO2. The 9-gene signature was used, combined with clinical parameters, to fit a multivariable Cox model to the training cohort (concordance index, ci = 0.85), which was successfully validated (ci = 0.86 for internal cohort; ci = 0.78 for in silico cohort). The signature showed improved performance compared with clinical parameters alone (ci = 0.70). Furthermore, the signature predicted patient prognosis than previous gene signatures more accurately. It was also used to stratify early-stage, HBV or HCV-infected patients into low and high-risk groups, leading to significant differences in survival in training and validation (P < 0.001). CONCLUSIONS: The 9-gene signature, in which four were upregulated (ZC2HC1A, MARCKSL1, PTGS1, CDKN2B) and five (CLEC10A, PRDX3, PRKCH, MPEG1, LMO2) were downregulated in HCC with poor prognosis, stratified HCC patients into low and high risk group significantly in different clinical settings, including receiving adjuvant transarterial chemoembolization and especially in early stage disease. This new signature should be validated in prospective studies to stratify patients in clinical decisions.

Efficacy of prophylactic probiotics in combination with antibiotics versus antibiotics alone for colorectal surgery: A meta-analysis of randomized controlled trials.

This meta-analysis aimed to determine whether prophylactic probiotics in combination with antibiotics are superior to antibiotics alone in the prevention of surgical site infection (SSI) after colorectal surgery. Fourteen trials involving 1524 participants were included. Compared with antibiotics alone, prophylactic probiotics in combination with antibiotics reduced the risk of SSI as well as other complications, shortened the cumulative duration of antibiotic therapy. Current evidence suggested that probiotics in combination with antibiotics could be recommended.

Kidney bioengineering in regenerative medicine: An emerging therapy for kidney disease.

The prevalence of end-stage renal disease is emerging as a serious worldwide public health problem because of the shortage of donor organs and the need to take lifelong immunosuppressive medication in patients who receive a transplanted kidney. Recently, tissue bioengineering of decellularization and recellularization scaffolds has emerged as a novel strategy for organ regeneration, and we review the critical technologies supporting these methods. We present a summary of factors associated with experimental protocols that may shed light on the future development of kidney bioengineering and we discuss the cell sources and bioreactor techniques applied to the recellularization process. Finally, we review some artificial renal engineering technologies and their future prospects, such as kidney on a chip and the application of three-dimensional and four-dimensional printing in kidney tissue engineering.

Recent advances in re-engineered liver: de-cellularization and re-cellularization techniques.

Allogeneic transplantation is the definitive treatment for patients with end-stage liver disease but is limited by donor shortage and very high cost. Through de-cellularization and re-cellularization methods, re-engineered liver may provide a promising alternative for treating patients with end-stage liver disease. To achieve this, the prevention of the native extracellular matrix ultrastructure plays a central role in de-cellularization protocol; the re-seeding cell types, as well as re-seeding strategies, need more explorations in re-cellularization protocol. Some success of this approach has been published in a rat model; however, the re-engineered liver remains functional in vivo for only several hours, which suggests that the recent protocol may be far from the ideal target. This Review highlights the challenges still to be overcome and presents an overview and summary of methods of de-cellularization and re-cellularization strategies, together with a view on future directions that may lead to the regeneration of a functional liver.

Downregulation of GPX8 in hepatocellular carcinoma: impact on tumor stemness and migration.

PURPOSE: GPX8, which is found in the endoplasmic reticulum lumen, is a member of the Glutathione Peroxidases (GPXs) family. Its role in hepatocellular carcinoma (HCC) is unknown. METHODS: Immunohistochemical staining was used to detect the protein levels of GPX8 in HCC tissue microarrays. A short hairpin RNA lentivirus was used to knock down GPX8, and the main signaling pathways were investigated using transcriptome sequencing and a phosphorylated kinase array. The sphere formation assays, cloning-formation assays and cell migration assays were used to evaluate the stemness and migration ability of HCC cells. Identifying the GPX8-interacting proteins was accomplished through immunoprecipitation and protein mass spectrometry. RESULTS: The GPX8 protein levels were downregulated in HCC patients. Low expression of GPX8 protein was related to early recurrence and poor prognosis in HCC patients. GPX8 knockdown could enhance the stemness and migration ability of HCC cells. Consistently, Based on transcriptome analysis, multiple signaling pathways that include the PI3K-AKT and signaling pathways that regulate the pluripotency of stem cells, were activated after GPX8 knockdown. The downregulation of GPX8 could increase the expression of the tumor stemness markers KLF4, OCT4, and CD133. The in vivo downregulation of GPX8 could also promote the subcutaneous tumor-forming and migration ability of HCC cells. MK-2206, which is a small-molecule inhibitor of AKT, could reverse the tumor-promoting effects both in vivo and in vitro. We discovered that GPX8 and the 71-kDa heat shock cognate protein (Hsc70) have a direct interaction. The phosphorylation of AKT encouraged the translocation of Hsc70 into the nucleus and the expression of the PI3K p110 subunit, thereby increasing the downregulation of GPX8. CONCLUSION: The findings from this study demonstrate the anticancer activity of GPX8 in HCC by inactivating the Hsc70/AKT pathway. The results suggest a possible therapeutic target for HCC.

CD36+ cancer-associated fibroblasts provide immunosuppressive microenvironment for hepatocellular carcinoma via secretion of macrophage migration inhibitory factor.

Hepatocellular carcinoma (HCC) is an immunotherapy-resistant malignancy characterized by high cellular heterogeneity. The diversity of cell types and the interplay between tumor and non-tumor cells remain to be clarified. Single cell RNA sequencing of human and mouse HCC tumors revealed heterogeneity of cancer-associated fibroblast (CAF). Cross-species analysis determined the prominent CD36+ CAFs exhibited high-level lipid metabolism and expression of macrophage migration inhibitory factor (MIF). Lineage-tracing assays showed CD36+CAFs were derived from hepatic stellate cells. Furthermore, CD36 mediated oxidized LDL uptake-dependent MIF expression via lipid peroxidation/p38/CEBPs axis in CD36+ CAFs, which recruited CD33+myeloid-derived suppressor cells (MDSCs) in MIF- and CD74-dependent manner. Co-implantation of CD36+ CAFs with HCC cells promotes HCC progression in vivo. Finally, CD36 inhibitor synergizes with anti-PD-1 immunotherapy by restoring antitumor T-cell responses in HCC. Our work underscores the importance of elucidating the function of specific CAF subset in understanding the interplay between the tumor microenvironment and immune system.

Targeting IRG1 reverses the immunosuppressive function of tumor-associated macrophages and enhances cancer immunotherapy.

Immune-responsive gene 1 (IRG1) encodes aconitate decarboxylase (ACOD1) that catalyzes the production of itaconic acids (ITAs). The anti-inflammatory function of IRG1/ITA has been established in multiple pathogen models, but very little is known in cancer. Here, we show that IRG1 is expressed in tumor-associated macrophages (TAMs) in both human and mouse tumors. Mechanistically, tumor cells induce Irg1 expression in macrophages by activating NF-κB pathway, and ITA produced by ACOD1 inhibits TET DNA dioxygenases to dampen the expression of inflammatory genes and the infiltration of CD8+ T cells into tumor sites. Deletion of Irg1 in mice suppresses the growth of multiple tumor types and enhances the efficacy of anti-PD-(L)1 immunotherapy. Our study provides a proof of concept that ACOD1 is a potential target for immune-oncology drugs and IRG1-deficient macrophages represent a potent cell therapy strategy for cancer treatment even in pancreatic tumors that are resistant to T cell-based immunotherapy.

Development of a deep pathomics score for predicting hepatocellular carcinoma recurrence after liver transplantation.

BACKGROUND AND PURPOSE: Tumor recurrence after liver transplantation (LT) impedes the curative chance for hepatocellular carcinoma (HCC) patients. This study aimed to develop a deep pathomics score (DPS) for predicting tumor recurrence after liver transplantation using deep learning. PATIENTS AND METHODS: Two datasets of 380 HCC patients who underwent LT were enrolled. Residual convolutional neural networks were used to identify six histological structures of HCC. The individual risk score of each structure and DPS were derived by a modified DeepSurv network. Cox regression analysis and Concordance index were used to evaluate the prognostic significance. The cellular exploration of prognostic immune biomarkers was performed by quantitative and spatial proximity analysis according to three panels of 7-color immunofluorescence. RESULTS: The overall classification accuracy of HCC tissue was 97%. At the structural level, immune cells were the most significant tissue category for predicting post-LT recurrence (HR 1.907, 95% CI 1.490-2.440). The C-indices of DPS achieved 0.827 and 0.794 in the training and validation cohorts, respectively. Multivariate analysis for recurrence-free survival (RFS) showed that DPS (HR 4.795, 95% CI 3.017-7.619) was an independent risk factor. Patients in the high-risk subgroup had a shorter RFS, larger tumor diameter and a lower proportion of clear tumor borders. At the cellular level, a higher infiltration of intratumoral NK cells was negatively correlated with recurrence risk. CONCLUSIONS: This study established an effective DPS. Immune cells were the most significant histological structure related to HCC recurrence. DPS performed well in post-LT recurrence prediction and the identification of clinicopathological features.

Single-cell and spatial architecture of primary liver cancer.

Primary liver cancer (PLC) poses a leading threat to human health, and its treatment options are limited. Meanwhile, the investigation of homogeneity and heterogeneity among PLCs remains challenging. Here, using single-cell RNA sequencing, spatial transcriptomic and bulk multi-omics, we elaborated a molecular architecture of 3 PLC types, namely hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC) and combined hepatocellular-cholangiocarcinoma (CHC). Taking a high-resolution perspective, our observations revealed that CHC cells exhibit internally discordant phenotypes, whereas ICC and HCC exhibit distinct tumor-specific features. Specifically, ICC was found to be the primary source of cancer-associated fibroblasts, while HCC exhibited disrupted metabolism and greater individual heterogeneity of T cells. We further revealed a diversity of intermediate-state cells residing in the tumor-peritumor junctional zone, including a congregation of CPE+ intermediate-state endothelial cells (ECs), which harbored the molecular characteristics of tumor-associated ECs and normal ECs. This architecture offers insights into molecular characteristics of PLC microenvironment, and hints that the tumor-peritumor junctional zone could serve as a targeted region for precise therapeutical strategies.

Crosstalk Between Metabolism and Immune Activity Reveals Four Subtypes With Therapeutic Implications in Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (ccRCC) is characterized by metabolic dysregulation and distinct immunological signatures. The interplay between metabolic and immune processes in the tumor microenvironment (TME) causes the complexity and heterogeneity of immunotherapy responses observed during ccRCC treatment. Herein, we initially identified two distinct metabolic subtypes (C1 and C2 subtypes) and immune subtypes (I1 and I2 subtypes) based on the occurrence of differentially expressed metabolism-related prognostic genes and immune-related components. Notably, we observed that immune regulators with upregulated expression actively participated in multiple metabolic pathways. Therefore, we further delineated four immunometabolism-based ccRCC subtypes (M1, M2, M3, and M4 subtypes) according to the results of the above classification. Generally, we found that high metabolic activity could suppress immune infiltration. Immunometabolism subtype classification was associated with immunotherapy response, with patients possessing the immune-inflamed, metabolic-desert subtype (M3 subtype) that benefits the most from immunotherapy. Moreover, differences in the shifts in the immunometabolism subtype after immunotherapy were observed in the responder and non-responder groups, with patients from the responder group transferring to subtypes with immune-inflamed characteristics and less active metabolic activity (M3 or M4 subtype). Immunometabolism subtypes could also serve as biomarkers for predicting immunotherapy response. To decipher the genomic and epigenomic features of the four subtypes, we analyzed multiomics data, including miRNA expression, DNA methylation status, copy number variations occurrence, and somatic mutation profiles. Patients with the M2 subtype possessed the highest VHL gene mutation rates and were more likely to be sensitive to sunitinib therapy. Moreover, we developed non-invasive radiomic models to reveal the status of immune activity and metabolism. In addition, we constructed a radiomic prognostic score (PRS) for predicting ccRCC survival based on the seven radiomic features. PRS was further demonstrated to be closely linked to immunometabolism subtype classification, immune score, and tumor mutation burden. The prognostic value of the PRS and the association of the PRS with immune activity and metabolism were validated in our cohort. Overall, our study established four immunometabolism subtypes, thereby revealing the crosstalk between immune and metabolic activities and providing new insights into personal therapy selection.

LncRNA USP2-AS1 Promotes Hepatocellular Carcinoma Growth by Enhancing YBX1-Mediated HIF1α Protein Translation Under Hypoxia.

Recently, the role of lncRNAs in tumorigenesis and development has received increasing attention, but the mechanism underlying lncRNAs-mediated tumor growth in the hypoxic microenvironment of solid tumors remains obscure. Using RNA sequencing, 25 hypoxia-related lncRNAs were found to be upregulated in HCC, of which lncRNA USP2-AS1 were significantly increased under hypoxia. We further confirmed that USP2-AS1 was significantly upregulated in liver cancer using FISH assay and that USP2-AS1 was associated with advanced liver cancer and increased tumor size. Furthermore, overexpression of USP2-AS1 under hypoxia dramatically increased HCC proliferation and clone formation, whereas the opposite results were observed after USP2-AS1 knockdown. We also found that overexpression of USP2-AS1 increased migration and invasion of HCC cells, while USP2-AS1 knockdown led to the opposite effect. In addition, USP2-AS1 knockdown can increase the efficacy of lenvatinib in our mice tumor xenograft model. Our findings also suggest that USP2-AS1 could increase the protein level of HIF1α by enhancing YBX1 protein binding to HIF1α mRNA under hypoxia and the therapeutic effect of lenvatinib can be enhanced by combination with HIF1α inhibitors in liver cancer.

MTDH antisense oligonucleotides reshape the immunosuppressive tumor microenvironment to sensitize Hepatocellular Carcinoma to immune checkpoint blockade therapy.

Immune checkpoint blockade (ICB) therapy is an important treatment option for individuals with cancer, but it has certain limitations. Identifying a better target that can overcome tumor immune escape and stimulate T cell activity is critical. This research aimed to delve into the molecular mechanism underlying the immunoregulatory function of metadherin (MTDH), which is a novel and potential therapeutic target in hepatocellular cancer (HCC). A small interfering RNA library was screened using the luciferase reporter assay and PD-L1 promoter. The Cancer Genome Atlas database and HCC tissues were used to investigate the relationship between MTDH and PD-L1. The association between MTDH and ß-catenin/lymphoid enhancer binding factor (LEF-1) was discovered by co-immunoprecipitation. The chromatin immunoprecipitation assay was used to investigate the interaction of MTDH with the PD-L1 promoter when LEF-1 expression was silenced. Locked nucleic acid antisense oligonucleotides (ASOs) were used to inhibit MTDH. We utilized in vitro co-cultures and in vivo syngeneic tumor development experiments to confirm the effectiveness of MTDH ASO combined with PD-1 monoclonal antibody (mAb). MTDH was demonstrated to be a PD-L1 modulator. MTDH increased PD-L1 expression and upregulated PD-L1 transcriptional activity through ß-catenin/LEF-1 signaling. More importantly, MTDH ASO improved the anti-PD-1 response and increased cytotoxic T-cell infiltration in PD-1 mAb-treated malignancies. MTDH effectively predicts the therapeutic efficacy of ICB therapy. Our results imply that combining MTDH ASO with PD-1 mAb could be a promising therapeutic strategy for HCC. In addition, MTDH is a potential novel biomarker for predicting the effectiveness of immune checkpoint inhibitor treatment.