In vivo CRISPR screen identifies LTN1 as a novel tumor suppressor ubiquitinating insulin-like growth factor 2 mRNA-binding protein 1 in hepatocellular carcinoma.

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) is a frequent and aggressive kind of cancer. Although E3 ligases play important roles in HCC development, several E3 ligases remain unknown. APPROACH AND RESULTS: Through in vivo CRISPR knockout (KO) screens targeting related E3 ligase genes in HCC nude mice models, we discovered LTN1 as a novel tumor suppressor in HCC. Co-IP paired with 2D-LC-MS/MS and subsequent western blotting in HCC cells were used to identify the interactome of LTN1. Compared to matched normal tissues, the expression of LTN1 was decreased in human HCC tissues (ANT) (157/209). Clinically, patients with HCC who expressed low levels of LTN1 had a poor prognosis. Forced expression of LTN1 decreased cell growth in vitro and in vivo, whereas knockdown of LTN1 increased cell growth. Mechanistically, elevated LTN1 expression inhibited HCC cell growth by ubiquitinating and destabilizing the IGF2BP1 protein, which inhibited the c-Myc and IGF-1R signaling pathways. There was a negative correlation between the LTN1 protein expression and the IGF2BP1 protein expression in HCC tissues (R2=0.2799, P=0.0165). CONCLUSIONS: LTN1 may be a crucial tumor suppressor for determining the prognosis and a possible therapeutic target since it inhibits the proliferation of HCC cells by ubiquitinating IGF2BP1.

Identification of the mitophagy-related diagnostic biomarkers in hepatocellular carcinoma based on machine learning algorithm and construction of prognostic model.

Background and aims: As a result of increasing numbers of studies most recently, mitophagy plays a vital function in the genesis of cancer. However, research on the predictive potential and clinical importance of mitophagy-related genes (MRGs) in hepatocellular carcinoma (HCC) is currently lacking. This study aimed to uncover and analyze the mitophagy-related diagnostic biomarkers in HCC using machine learning (ML), as well as to investigate its biological role, immune infiltration, and clinical significance. Methods: In our research, by using Least absolute shrinkage and selection operator (LASSO) regression and support vector machine- (SVM-) recursive feature elimination (RFE) algorithm, six mitophagy genes (ATG12, CSNK2B, MTERF3, TOMM20, TOMM22, and TOMM40) were identified from twenty-nine mitophagy genes, next, the algorithm of non-negative matrix factorization (NMF) was used to separate the HCC patients into cluster A and B based on the six mitophagy genes. And there was evidence from multi-analysis that cluster A and B were associated with tumor immune microenvironment (TIME), clinicopathological features, and prognosis. After then, based on the DEGs (differentially expressed genes) between cluster A and cluster B, the prognostic model (riskScore) of mitophagy was constructed, including ten mitophagy-related genes (G6PD, KIF20A, SLC1A5, TPX2, ANXA10, TRNP1, ADH4, CYP2C9, CFHR3, and SPP1). Results: This study uncovered and analyzed the mitophagy-related diagnostic biomarkers in HCC using machine learning (ML), as well as to investigate its biological role, immune infiltration, and clinical significance. Based on the mitophagy-related diagnostic biomarkers, we constructed a prognostic model(riskScore). Furthermore, we discovered that the riskScore was associated with somatic mutation, TIME, chemotherapy efficacy, TACE and immunotherapy effectiveness in HCC patients. Conclusion: Mitophagy may play an important role in the development of HCC, and further research on this issue is necessary. Furthermore, the riskScore performed well as a standalone prognostic marker in terms of accuracy and stability. It can provide some guidance for the diagnosis and treatment of HCC patients.

Down-regulation of circPTTG1IP induces hepatocellular carcinoma development via miR-16-5p/RNF125/JAK1 axis.

Circular RNAs are known to regulate the biological processes of hepatocellular carcinoma (HCC), and humans with Down syndrome are at low risk of developing solid tumors due to the amplification of several tumor suppressor genes on human chromosome 21 (HSA21). Here, we aimed to investigate the potential role of circRNAs originating from HSA21 in the progression of HCC. CircRNA-sequencing was performed to analyze differentially expressed circRNAs in 4 HCC and peritumor tissues, and circRNAs originating from HSA21 were further analyzed. Circ_0061984 (circPTTG1IP) was chosen for further study because it showed the lowest expression in HCC tissues, and qRT-PCR was used to confirm the expression of circPTTG1IP in HCC patient tissues. The biological function of circPTTG1IP was detected in HCC cells both in vivo and in vitro. Moreover, luciferase reporter assays, circRNA immunoprecipitation, and fluorescence in situ hybridization (FISH) were used to investigate the potential mechanism of circPTTG1IP. Finally, the possible mechanisms of filgotinib in circPTTG1IP-driven HCC were assessed. CircPTTG1IP expression was decreased in HCC compared to peritumoral tissues. Moreover, low circPTTG1IP expression was revealed to be associated with a poor prognosis of HCC patients. Elevation of circPTTG1IP was revealed to inhibit HCC development both in vitro and in vivo. Mechanistically, circPTTG1IP was shown to function as a competing endogenous RNA (ceRNA) of RNF125 by binding miR-16-5p to increase the level of the E3 ubiquitin ligase RNF125, which further ubiquitinated and degraded JAK1 protein. Finally, we demonstrated that administration of filgotinib, a JAK1 inhibitor, restricted HCC progression induced by low circPTTG1IP expression. Thus, we revealed that circPTTG1IP is a novel tumor suppresser circRNA in HCC and that a low circPTTG1IP level promotes HCC development via the miR-16-5p/RNF125/JAK1 axis. Patients with low circPTTG1IP may benefit from filgotinib treatment.

Comprehensive analysis of the clinical significance, immune infiltration, and biological role of MARCH ligases in HCC.

The membrane-associated RING-CH (MARCH) family, a member of the E3 ubiquitin ligases, has been confirmed by a growing number of studies to be associated with immune function and has been highlighted as a potential immunotherapy target. In our research, hepatocellular carcinoma (HCC) patients were divided into C1 and C2 MARCH ligase-related patterns by the non-negative matrix factorization (NMF) algorithm. Multiple analyses revealed that the MARCH ligase-related cluster was related to prognosis, clinicopathological characteristics, and the tumor immune microenvironment (TIME). Next, the signature (risk score) of the MARCH prognosis was constructed, including eight genes associated with the MARCH ligase (CYP2C9, G6PD, SLC1A5, SPP1, ANXA10, CDC20, PON1, and FTCD). The risk score showed accuracy and stability. We found that the correlations between risk score and TIME, tumor mutation burden (TMB), prognosis, and clinicopathological characteristics were significant. Additionally, the risk score also had important guiding significance for HCC treatment, including chemotherapy, immunotherapy, and transarterial chemoembolization (TACE).

Can Patients with Pancreatic Cancer and Liver Metastases Obtain Survival Benefit from Surgery? A Population-Based Study.

Background: Surgery for pancreatic cancer with liver metastases (PCL) is not recommended in the international guidelines, and investigation of its clinical significance in patients with PCL is very limited. This study explored whether surgery, especially synchronous resection of the primary tumor and liver metastases (SPL), could improve survival in PCL. Methods: Data of 14,248 patients with PCL from Surveillance, Epidemiology, and End Results database was analyzed. Patients were divided into following groups: SPL, synchronous primary site, and other resection (SPO), single resection of the primary site (SPS), and no resection (NR). Results: In this study, only 93 (0.7%) underwent SPL, 88 (0.6%) for SPO, and 232 (1.6%) for SPS. Multivariate Cox analysis showed surgical procedures of both the primary site and other sites were independent protective prognostic factors for pancreatic cancer cause-specific survival (PCSS) (all P < 0.001). Patients in the SPL group showed the most survival benefit, with a significant and gradually increased difference as compared with the SPO, SPS, and NR groups (median survival: 54, 34, 15, and 3 months, respectively, all P < 0.001). Compared with the NR group, mortalities were significant and gradually declining in the SPS, SPO, and SPL groups, with hazard ratio 0.329 (95% confidence interval [CI], 0.281 to 0.386), 0.220 (95% CI, 0.164 to 0.294), and 0.162 (95% CI, 0.118 to 0.222), respectively (all P < 0.001). Conclusions: Surgical procedures for both primary site and other sites improved survival. SPL, particularly, showed a considerable survival benefit in well-selected patients with PCL.

Impact of Socioeconomic Factors on Prognosis and Clinical Management in Patients with Hepatocellular Carcinoma.

BACKGROUND: The prognosis for patient survival using the tumor-node-metastasis (TNM) staging system may be imperfect, as it based only on biological factors and does not include the socioeconomic factors (SEFs). We integrated the SEFs into the TNM system (TNMSEF), and evaluated whether the novel TNM-SEF staging system showed better prediction capacity and improved clinical guidance in hepatocellular carcinoma (HCC). METHODS: We selected data of 12 514 cases with HCC between 2010 and 2015 from the SEER database. The Kaplan-Meier survival curves and Cox proportional hazards regression were used to analyze cancer-specific survival (CSS) among the TNM-SEF stages. RESULTS: Multivariate Cox analyses showed that insurance status, marital status, year of diagnosis, and income were prominent prognostic SEFs (all P < .05). When compared with the SEF0 stage, the SEF1 stage was significantly associated with a 36.1% increased risk of cancer-specific mortality in HCC overall, a 22.2% increased risk of metastatic HCC, and a 41.8% increased risk of non-metastatic HCC (all P < .001). The concordance index of the TNM-SEF stage (0.768) was better than that of the TNM stage (0.764). Furthermore, patients with SEF0 stage showed higher 5-year CSS than those with SEF1 stage (I: 48.7% vs. 28.1%; II: 41.0% vs. 25.1%; IIIA: 12.8% vs. 5.0%; IIIB: 7.8% vs. 6.0%; IIIC: 6.4% vs. 6.7%; IVA: 8.4% vs. 2.5%; IVB: 2.1% vs. 0.8%; all P < .05). CONCLUSION: We have proved that the SEF stage is an independent predictor for HCC. The combined SEF stage with TNM staging warrants more clinical attention, for improved prognostic prediction and clinical guidance.

A practical nomogram and risk stratification system predicting the cancer-specific survival for patients with early hepatocellular carcinoma.

BACKGROUND: Our purpose was to establish and validate a nomogram model in early hepatocellular carcinoma (HCC) patients for predicting the cancer-specific survival (CSS). METHODS: We extracted eligible data of relevant patients between 2010 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database. Further, we divided all patients into two groups (training and validation cohorts) at random (7:3). Nomogram was established using effective risk factors based on univariate and multivariate analysis. The effective performance of nomogram was evaluated using concordance index (C-index), calibration plots, decision curve analysis (DCA), and receiver operating characteristic curve (ROC). RESULTS: We selected 3620 patients with early HCC including the training cohort (70%, 2536) and the validation cohort (30%, 1084). The nomogram-related C-indexes were 0.755 (95% CI: 0.739-0.771) and 0.737 (95% CI: 0.712-0.762), in the training and validation cohorts, respectively. The calibration plots showed good consistency of 3-and 5-year CSS between the actual observation and the nomogram prediction. The 3-, 5-year DCA curves also indicated that the nomogram has excellent clinical utility. The 3-, 5-year area under curve (AUC) of ROC in the training cohort were 0.783, 0.779, respectively, and 0.767, 0.766 in the validation cohort, respectively. With the establishment of nomogram, a risk stratification system was also established that could divide all patients into three risk groups, and the CSS in different groups (i.e., low risk, intermediate risk, and high risk) had a good regional division. CONCLUSIONS: We developed a practical nomogram in early HCC patients for predicting the CSS, and a risk stratification system follow arisen, which provided an applicable tool for clinical management.