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.

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.

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.

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.

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.

Conversion therapy for initially unresectable hepatocellular carcinoma using a combination of toripalimab, lenvatinib plus TACE: real-world study.

BACKGROUND: Combination conversion therapies afforded curative surgery chance for initially unresectable hepatocellular carcinoma (uHCC). This study aimed to evaluate the conversion rate and clinical outcomes of a first-line conversion regimen of lenvatinib combined with transarterial chemoembolization (TACE) plus immunotherapy for initial uHCC by interpreting real-world data. METHODS: Conversion therapy data of patients with uHCC from November 2018 to January 2021 were analysed. The regimens included triple combination therapy (t-CT: lenvatinib, TACE, plus toripalimab) and dual combination therapy (d-CT: lenvatinib plus TACE). Another study population diagnosed with hepatocellular carcinoma of macrovascular invasion disease were included as the upfront surgery cohort. Treatment responses and conversion rate were primary outcomes. Survival and adverse events were analysed. RESULTS: Fifty-one patients receiving t-CT (n = 30) and d-CT (n = 21) were enrolled. Higher overall response rates (76.7 per cent versus 47.6 per cent, P = 0.042) and disease control rates (90.0 per cent versus 57.1 per cent, P = 0.042) were observed via t-CT than d-CT. Both median overall survival and event-free survival were not reached in the t-CT cohort. A higher rate of curative conversion resection was achieved through t-CT than d-CT (50.0 per cent versus 19.0 per cent, P = 0.039). The disease-free survival of patients undergoing conversion resection in the t-CT cohort (n = 15) was higher than that in the upfront surgery cohort (n = 68, P = 0.039). Both t-CT and d-CT regimens were tolerable. CONCLUSIONS: Better treatment responses and conversion rate for patients with uHCC were obtained with first-line t-CT. Neoadjuvant t-CT before surgery should be recommended for patients with macrovascular invasion.

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.

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.

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.

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.

Targeting HNRNPM Inhibits Cancer Stemness and Enhances Antitumor Immunity in Wnt-activated Hepatocellular Carcinoma.

BACKGROUND & AIMS: Cancer stemness and immune evasion are closely associated and play critical roles in tumor development and resistance to immunotherapy. However, little is known about the underlying molecular mechanisms that coordinate this association. METHODS: The expressions of heterogeneous nuclear ribonucleoprotein M (HNRNPM) in 240 hepatocellular carcinoma (HCC) samples, public databases, and liver development databases were analyzed. Chromatin immunoprecipitation assays were performed to explore the associations between stem-cell transcription factors and HNRNPM. HNRNPM-regulated alternative splicing (AS) and its binding motif were identified by RNA-seq and RIP-seq. HNRNPM-specific antisense oligonucleotides were developed to explore potential therapeutic targets in HCC. CD8+ T cells that were co-cultured with tumor cells were sorted by flow cytometry assays. RESULTS: We identified an elevated oncofetal splicing factor in HCC, HNRNPM, that unifies and regulates the positive association between cancer stemness and immune evasion. HNRNPM knockdown abolished HCC tumorigenesis and diminished cancer stem cell properties in vitro and in vivo. Mechanistically, HNRNPM regulated the AS of MBD2 by binding its flanking introns, whose isoforms played opposing roles. Although MBD2a and MBD2c competitively bound to CpG islands in the FZD3 promoter, MBD2a preferentially increased FZD3 expression and then activated the WNT/ß-catenin pathway. Interestingly, FZD3 and ß-catenin further provided additional regulation by targeting OCT4 and SOX2. We found that HNRNPM inhibition significantly promoted CD8+ T cell activation and that HNRNPM- antisense oligonucleotides effectively inhibited WNT/ß-catenin to enhance anti-programmed cell death protein-1 immunotherapy by promoting CD8+ T cell infiltration. CONCLUSIONS: HNRNPM has a tumor-intrinsic function in generating an immunosuppressive HCC environment through an AS-dependent mechanism and demonstrates proof of the concept of targeting HNRNPM in tailoring HCC immunotherapeutic approaches.

Serial circulating tumor DNA to predict early recurrence in patients with hepatocellular carcinoma: a prospective study.

We studied the value of circulating tumor DNA (ctDNA) in predicting early postoperative tumor recurrence and monitoring tumor burden in patients with hepatocellular carcinoma (HCC). Plasma-free DNA, germline DNA, and tissue DNA were isolated from 41 patients with HCC. Serial ctDNAs were analyzed by next-generation sequencing before and after operation. Whole-exome sequencing was used to detect the DNA of HCC and adjacent tissues. In total, 47 gene mutations were identified in the ctDNA of the 41 patients analyzed before surgery. ctDNA was detected in 63.4% and 46% of the patient plasma pre- and postoperation, respectively. The preoperative ctDNA positivity rate was significantly lower in the nonrecurrence group than in the recurrence group. With a median follow-up of 17.7 months, nine patients (22%) experienced tumor recurrence. ctDNA positivity at two time-points was associated with significantly shorter recurrence-free survival (RFS). Tumors with NRAS, NEF2L2, and MET mutations had significantly shorter times to recurrence than those without mutations and showed high recurrence prediction performance by machine learning. Multivariate analyses showed that the median variant allele frequency (VAF) of mutations in preoperative ctDNA was a strong independent predictor of RFS. ctDNA is a real-time monitoring indicator that can accurately reflect tumor burden. The median VAF of baseline ctDNA is a strong independent predictor of RFS in individuals with HCC.

A multidimensional nomogram combining imaging features and clinical factors to predict the invasiveness and metastasis of combined hepatocellular cholangiocarcinoma.

BACKGROUND: Combined hepatocellular cholangiocarcinoma (CHCC-CCA) is a rare type of primary liver cancer having aggressive behavior. Few studies have investigated the prognostic factors of CHCC-CCA. Therefore, this study aimed to establish a nomogram to evaluate the risk of microvascular invasion (MVI) and the presence of satellite nodules and lymph node metastasis (LNM), which are associated with prognosis. METHODS: One hundred and seventy-one patients pathologically diagnosed with CHCC-CCA were divided into a training set (n=116) and validation set (n=55). Logistic regression analysis was used to assess the relative value of clinical factors associated with the presence of MVI and satellite nodules. The least absolute shrinkage and selection operator (LASSO) algorithm was used to establish the imaging model of all outcomes, and to build clinical model of LNM. Nomograms were constructed by incorporating clinical risk factors and imaging features. The model performance was evaluated on the training and validation sets to determine its discrimination ability, calibration, and clinical utility. Kaplan Meier analysis and time dependent receiver operating characteristic (ROC) were displayed to evaluate the prognosis value of the predicted nomograms of MVI and satellite nodule. RESULTS: A nomogram comprising the platelet to lymphocyte ratio (PLR), albumin-to-alkaline phosphatase ratio (AAPR) and imaging model was established for the prediction of MVI. Carcinoembryonic antigen (CEA) level and size were combined with the imaging model to establish a nomogram for the prediction of the presence of satellite nodules. Favorable calibration and discrimination were observed in the training and validation sets for the MVI nomogram (C-indexes of 0.857 and 0.795), the nomogram for predicting satellite nodules (C-indexes of 0.919 and 0.883) and the LNM nomogram (C-indexes of 0.872 and 0.666). Decision curve analysis (DCA) further confirmed the clinical utility of the nomograms. The preoperatively predicted MVI and satellite nodules by the combined nomograms achieved satisfactory performance in recurrence-free survival (RFS) and overall survival (OS) prediction. CONCLUSIONS: The proposed nomograms incorporating clinical risk factors and imaging features achieved satisfactory performance for individualized preoperative predictions of MVI, the presence of satellite nodules, and LNM. The prediction models were demonstrated to be good indicator for predicting the prognosis of CHCC-CCA, facilitating treatment strategy optimization for patients with CHCC-CCA.

Splicing factor SRSF1 promotes breast cancer progression via oncogenic splice switching of PTPMT1.

BACKGROUND: Intensive evidence has highlighted the effect of aberrant alternative splicing (AS) events on cancer progression when triggered by dysregulation of the SR protein family. Nonetheless, the underlying mechanism in breast cancer (BRCA) remains elusive. Here we sought to explore the molecular function of SRSF1 and identify the key AS events regulated by SRSF1 in BRCA. METHODS: We conducted a comprehensive analysis of the expression and clinical correlation of SRSF1 in BRCA based on the TCGA dataset, Metabric database and clinical tissue samples. Functional analysis of SRSF1 in BRCA was conducted in vitro and in vivo. SRSF1-mediated AS events and their binding motifs were identified by RNA-seq, RNA immunoprecipitation-PCR (RIP-PCR) and in vivo crosslinking followed by immunoprecipitation (CLIP), which was further validated by the minigene reporter assay. PTPMT1 exon 3 (E3) AS was identified to partially mediate the oncogenic role of SRSF1 by the P-AKT/C-MYC axis. Finally, the expression and clinical significance of these AS events were validated in clinical samples and using the TCGA database. RESULTS: SRSF1 expression was consistently upregulated in BRCA samples, positively associated with tumor grade and the Ki-67 index, and correlated with poor prognosis in a hormone receptor-positive (HR+) cohort, which facilitated proliferation, cell migration and inhibited apoptosis in vitro and in vivo. We identified SRSF1-mediated AS events and discovered the SRSF1 binding motif in the regulation of splice switching of PTPMT1. Furthermore, PTPMT1 splice switching was regulated by SRSF1 by binding directly to its motif in E3 which partially mediated the oncogenic role of SRSF1 by the AKT/C-MYC axis. Additionally, PTPMT1 splice switching was validated in tissue samples of BRCA patients and using the TCGA database. The high-risk group, identified by AS of PTPMT1 and expression of SRSF1, possessed poorer prognosis in the stage I/II TCGA BRCA cohort. CONCLUSIONS: SRSF1 exerts oncogenic roles in BRCA partially by regulating the AS of PTPMT1, which could be a therapeutic target candidate in BRCA and a prognostic factor in HR+ BRCA patient.

Exosomal miR-3682-3p Suppresses Angiogenesis by Targeting ANGPT1 via the RAS-MEK1/2-ERK1/2 Pathway in Hepatocellular Carcinoma.

BACKGROUND: Angiogenesis is a crucial process in tumorigenesis and development. The role of exosomes derived from hepatocellular carcinoma (HCC) cells in angiogenesis has not been clearly elucidated. METHODS AND RESULTS: Exosomes were isolated from HCC cell lines (HCCLM3, MHCC97L, and PLC/RFP/5) by ultracentrifugation and identified by nano transmission electron microscopy (TEM), NanoSight analysis and western blotting, respectively. In vitro and in vivo analyses showed that exosomes isolated from highly metastatic HCC cells enhanced the migration, invasion and tube formation of human umbilical vein endothelial cells (HUVECs) compared to exosomes derived from poorly metastatic HCC cells. In addition, microarray analysis of HCC-Exos was conducted to identify potential functional molecules, and miR-3682-3p expression was found to be significantly downregulated in exosomes isolated from highly metastatic HCC cells. By in vitro gain-of-function experiments, we found that HCC cells secreted exosomal miR-3682-3p, which negatively regulates angiopoietin-1 (ANGPT1), and this led to inhibition of RAS-MEK1/2-ERK1/2 signaling in endothelial cells and eventually impaired angiogenesis. CONCLUSION: Our study elucidates that exosomal miR-3682-3p attenuates angiogenesis by targeting ANGPT1 through RAS-MEK1/2-ERK1/2 signaling and provides novel potential targets for liver cancer therapy.

Profiles of alternative splicing landscape in breast cancer and their clinical significance: an integrative analysis based on large-sequencing data.

BACKGROUND: Alternative splicing (AS) is closely correlated with the initiation and progression of carcinoma. The systematic analysis of its biological and clinical significance in breast cancer (BRCA) is, however, lacking. METHODS: Clinical data and RNA-seq were obtained from the TCGA dataset and differentially expressed AS (DEAS) events between tumor and paired normal BRCA tissues were identified. Enrichment analysis was then used to reveal the potential biological functions of DEAS events. We performed protein-protein interaction (PPI) analysis of DEAS events by using STRING and the correlation network between splicing factors (SFs) and AS events was constructed. The LASSO Cox model, Kaplan-Meier and log-rank tests were used to construct and evaluate DEAS-related risk signature, and the association between DEAS events and clinicopathological features were then analyzed. RESULTS: After strict filtering, 35,367 AS events and 973 DEAS events were detected. DEAS corresponding genes were significantly enriched in pivotal pathways including cell adhesion, cytoskeleton organization, and extracellular matrix organization. A total of 103 DEAS events were correlated with disease free survival. The DEAS-related risk signature stratified BRCA patients into two groups and the area under curve (AUC) was 0.754. Moreover, patients in the high-risk group had enriched basel-like subtype, advanced clinical stages, proliferation, and metastasis potency. CONCLUSIONS: Collectively, the profile of DEAS landscape in BRCA revealed the potential biological function and prognostic value of DEAS events.

Identification and validation of a new gene signature predicting prognosis of hepatocellular carcinoma patients by network analysis of stemness indices.

Background: Stem cells play an important role in hepatocellular carcinoma (HCC). However, their precise effect on HCC tumorigenesis and progression remains unclear. The present study aimed to characterize stem cell-related gene expression in HCC.Methods: The mRNA expression-based stemness index (mRNAsi) was used to analyze the clinical characteristics and prognosis of HCC patients. The weighted gene co-expression network analysis (WGCNA) was used to construct a gene co-expression network of 374 HCC patients. Finally, six genes were used to construct the prognosis signature.Results: HCC patients had a higher mRNAsi score than healthy people, suggesting poor prognosis. Two gene modules highly related to mRNAsi were identified. Multivariate Cox analysis was carried out to establish a Cox proportional risk regression model. The risk score for each patient was the sum of the product of each gene expression and its coefficient. Survival analysis suggested that the low-risk group had a significantly better prognosis.Conclusions: The established six-gene signature was able to predict patient prognosis accurately. This new signature should be verified in prospective studies in order to determine patient prognosis in clinical decision-making.