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

BACKGROUND & AIMS: The role of solute carrier family 25 member 15 (SLC25A15), a critical component of the urea cycle, in hepatocellular carcinoma (HCC) progression remains poorly understood. This study investigated the impact of SLC25A15 on HCC progression and its mechanisms. METHODS: We systematically investigated the function of SLC25A15 in HCC progression using large-scale data mining and cell, animal, and organoid models. Furthermore, we analyzed its involvement in reprogramming glutamine metabolism. RESULTS: SLC25A15 expression was significantly decreased in HCC tissues, and patients with low SLC25A15 levels had a poorer prognosis. Hypoxia-exposed HCC cells or tissues had lower SLC25A15 expression. A positive correlation between HNF4A, a transcription factor suppressed by hypoxia, and SLC25A15 was observed in both HCC tissues and cells. Modulating HNF4A levels altered SLC25A15 mRNA levels. SLC25A15 upregulated SLC1A5, increasing glutamine uptake. The reactive metabolic pathway of glutamine was increased in SLC25A15-deficient HCC cells, providing energy for HCC progression through additional lipid synthesis. Ammonia accumulation due to low SLC25A15 levels suppressed the expression of OGDHL (oxoglutarate dehydrogenase L), a switch gene that mediates SLC25A15 deficiency-induced reprogramming of glutamine metabolism. SLC25A15-deficient HCC cells were more susceptible to glutamine deprivation and glutaminase inhibitors. Intervening in glutamine metabolism increased SLC25A15-deficient HCC cells' response to anti-PD-L1 treatment. CONCLUSION: SLC25A15 is hypoxia-responsive in HCC, and low SLC25A15 levels result in glutamine reprogramming through SLC1A5 and OGDHL regulation, promoting HCC progression and regulating cell sensitivity to anti-PD-L1. Interrupting the glutamine-derived energy supply is a potential therapeutic strategy for treating SLC25A15-deficient HCC. IMPACT AND IMPLICATIONS: We first demonstrated the tumor suppressor role of solute carrier family 25 member 15 (SLC25A15) in hepatocellular carcinoma (HCC) and showed that its deficiency leads to reprogramming of glutamine metabolism to promote HCC development. SLC25A15 can serve as a potential biomarker to guide the development of precision therapeutic strategies aimed at targeting glutamine deprivation. Furthermore, we highlight that the use of an inhibitor of glutamine utilization can enhance the sensitivity of low SLC25A15 HCC to anti-PD-L1 therapy.

Risk Models for Predicting the Recurrence and Survival in Patients With Hepatocellular Carcinoma Undergoing Radio-Frequency Ablation.

Background: Hepatocellular carcinoma (HCC) patients have a poor prognosis after radio-frequency ablation (RFA), and investigating the risk factors affecting RFA and establishing predictive models are important for improving the prognosis of HCC patients. Methods: Patients with HCC undergoing RFA in Shenzhen People's Hospital between January 2011 and December 2021 were included in this study. Using the screened independent influences on recurrence and survival, predictive models were constructed and validated, and the predictive models were then used to classify patients into different risk categories and assess the prognosis of different categories. Results: Cox regression model indicated that cirrhosis (hazard ratio [HR] = 1.65), alpha-fetoprotein (AFP) ⩾400 ng/mL (HR = 2.03), tumor number (multiple) (HR = 2.11), tumor diameter ⩾20 mm (HR = 2.30), and platelets (PLT) ⩾ 244 (109/L) (HR = 2.37) were independent influences for recurrence of patients after RFA. On the contrary, AFP ⩾400 ng/mL (HR = 2.48), tumor number (multiple) (HR = 2.52), tumor diameter ⩾20 mm (HR = 2.25), PLT ⩾244 (109/L) (HR = 2.36), and hemoglobin (HGB) ⩾120 (g/L) (HR = 0.34) were regarded as independent influences for survival. The concordance index (C-index) of the nomograms for predicting disease-free survival (DFS) and overall survival (OS) was 0.727 (95% confidence interval [CI] = 0.770-0.684) and 0.770 (95% CI = 0.821-7.190), respectively. The prognostic performance of the nomograms was significantly better than other staging systems by analysis of the time-dependent C-index and decision curves. Each patient was scored using nomograms and influencing factors, and patients were categorized into low-, intermediate-, and high-risk groups based on their scores. In the Kaplan-Meier survival curve, DFS and OS were significantly better in the low-risk group than in the intermediate- and high-risk groups. Conclusions: The 2 prediction models created in this work can effectively predict the recurrence and survival rates of HCC patients following RFA.

Exploring the factors affecting the occurrence of postoperative MVI and the prognosis of hepatocellular carcinoma patients treated with hepatectomy: A multicenter retrospective study.

OBJECTIVE: To investigate the influencing factors affecting the occurrence of microvascular invasion (MVI) and the prognosis of hepatocellular carcinoma (HCC) patients treated with hepatectomy, and to explore how MVI affects prognosis in subgroups with different prognostic factors. METHODS: Clinical data of a total of 1633 patients treated surgically for HCC in four treatment centers were included, including 754 patients with MVI. By using the Cox risk regression model and the Mann-Whitney U-test, the common independent influences on prognosis and MVI were made clear. The incidence of MVI in various subgroups was then examined, as well as the relationship between MVI in various subgroups and prognosis. RESULTS: The Cox risk regression model showed that MVI, Child-Pugh classification, alpha-fetoprotein (AFP), hepatocirrhosis, tumor diameter, lymphocyte-to-monocyte ratio (LMR), and, Barcelona clinic liver cancer (BCLC) grade were independent determinants of overall survival (OS), and MVI, AFP, hepatocirrhosis, tumor diameter, and LMR were influencing determinants for disease-free survival (DFS). The receiver operating characteristic (ROC) curve showed that MVI was most closely associated with patient prognosis compared to other prognostic factors. AFP, hepatocirrhosis, tumor diameter, and LMR were discovered to be common influences on the prognosis of patients with HCC and MVI when combined with the results of the intergroup comparison of MVI. After grouping, it was showed that patients with hepatocirrhosis, positive AFP (AFP ≥ 20 ng/mL), tumor diameter >50 mm, and LMR ≤3.4 had a significantly higher incidence of MVI than patients in other subgroups, and all four subgroups of MVI-positive patients had higher rates of early recurrence and mortality (p < 0.05). CONCLUSIONS: MVI was found to be substantially linked with four subgroups of HCC patients with hepatocirrhosis, positive AFP, tumor diameter >50 mm, and LMR ≤3.4, and the prognosis of MVI-positive patients in all four subgroups tended to be worse.

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

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

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

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

NeRC: Rendering Planar Caustics by Learning Implicit Neural Representations.

Caustics are challenging light transport effects for photo-realistic rendering. Photon mapping techniques play a fundamental role in rendering caustics. However, photon mapping methods render single caustics under the stationary light source in a fixed scene view. They require significant storage and computing resources to produce high-quality results. In this paper, we propose efficiently rendering more diverse caustics of a scene with the camera and the light source moving. We present a novel learning-based volume rendering approach with implicit representations for our proposed task. Considering the variety of materials and textures of planar caustic receivers, we decompose the output appearance into two components: the diffuse and specular parts with a probabilistic module. Unlike NeRF, we construct weights for rendering each component from the implicit signed distance function (SDF). Moreover, we introduce the centering calibration and the sine activation function to improve the performance of the color prediction network. Extensive experiments on the synthetic and real-world datasets illustrate that our method achieves much better performance than baselines in the quantitative and qualitative comparison, for rendering caustics in novel views with the dynamic light source. Especially, our method outperforms the baseline on the temporal consistency across frames. Code will be available at https://github.com/JiaxiongQ/NeRC.

Effects of additives on physical, chemical, and microbiological properties during green waste composting.

Composting is an environmentally friendly and sustainable way to transform Green waste (GW) into a useful product. GW, however, contains substantial quantities of lignocelluloses that extend the composting period unless substances that accelerate composting are added. The objective of this research was to assess the influence of the following additives on GW composting (w/w dry matter contents of the additives were indicated): sugarcane bagasse at 15%; bean dregs at 35%; silage at 45%; flue gas desulfurization gypsum at 5%; maifanite at 4%; and furfural residue at 20%. Based on the composting temperature, compost density, porosity, particle-size distribution, water retention, pH, cation exchange capacity, available nutrient contents, humification coefficient, organic matter loss, microbial populations, and phytotoxicity, the best additives were 45% silage and 5% flue gas desulfurization gypsum. The latter two additives produced a high-quality product in only 35 and 37 days, respectively.

Beer lees and ceramsite amendments enhance the two-stage co-composting of green waste.

Composting is a major way to process green waste (GW), and amendments are important in GW composting. In this study of the two-stage co-composting of GW, beer lees (0, 25, 30%) and/or ceramsite (0, 10, 15%) were assessed as amendments. Changes in bulk density, porosity, temperature, pH, gaseous emissions, dissolved organic carbon (DOC) and nitrogen (DON), lignocellulose degradation, microbial abundances, and phytotoxicity were assessed during GW composting with the amendments. Treatments with a combination of beer lees and ceramsite had positive effects, and 25% beer lees and 15% ceramsite optimized all compost parameters. The optimal combination of amendments extended the thermophilic phase, enhanced the lignocellulose decomposition, and generated a stable and mature product in 20 days. Consequently, the best final compost was not phytotoxic (germination index: 164%), was mature (void space ratio: 48.48, pH: 7.20, and DOC/DON ratio: 0.51), and nutrient-rich (especially for N: 5.13%, P: 1.84%, and K: 0.68%).