Efficacy of radiotherapy in combined treatment of hepatocellular carcinoma patients with portal vein tumor thrombus: a real-world study.

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) with portal vein tumor thrombus (PVTT) has an extremely poor prognosis. A previous study proved that low-dose radiotherapy (RT) could prolong the prognosis of HCC patients with PVTT. This study aims to explore the sensitivity of PVTT to RT treatment. METHODS: Patients were selected based on imaging diagnosis of HCC accompanied by PVTT and received combined treatment of radiotherapy, antiangiogenic drugs and immune checkpoint inhibitors, followed by hepatectomy or liver transplantation from January 2019 to August 2022. The efficacy was evaluated by Response Evaluation Criteria in Solid Tumors (RECIST) guidelines and pathological assessment. The sensitivity of tumor cells to the treatment was compared between the primary tumor (PT)and PVTT by analyzing their residual tumor and pathologic complete remission (PCR) incidence. RESULTS: Data from 14 patients were collected in the study. After combined treatment, the size of PVTT decreased more significantly than that of the primary tumor in the imaging study (p < 0.05). The residual cancer was significantly more restrictive than that of primary tumor in paired patients based on pathological measurement (p = 0.008). The PCR incidence of the primary tumor (21.42%) was significantly lower (p = 0.008) than that of PVTT in the pathologic study (78.57%). CONCLUSION: PVTT is more sensitive to radiotherapy treatment than the primary tumor in patients with HCC. This combination therapy might be an effective option as a downstaging therapy for patients with HCC with PVTT.

Effectiveness and Safety of the PD-1 Inhibitor Lenvatinib Plus Radiotherapy in Patients with HCC with Main PVTT: Real-World Data from a Tertiary Centre.

Background: Patients with hepatocellular carcinoma (HCC) with portal vein tumour thrombus (PVTT), especially type Vp-4, usually have a poor prognosis. However, the vast majority of Phase III clinical trials exclude this population based on the inclusion criteria. Lenvatinib plus a PD-1 inhibitor has shown promising antitumour activity and tolerable safety in patients with unresectable HCC in Asian populations. Radiotherapy has also demonstrated high response rates and favourable survival for HCC patients with PVTT. This study aimed to explore the preliminary clinical efficacy and safety of lenvatinib plus the PD-1 inhibitor combined with radiotherapy for HCC patients with main portal vein tumour thrombus. Methods: Between 1 March 2018 and 31 October 2020, HCC patients with main PVTT who received lenvatinib plus a PD-1 inhibitor (pembrolizumab, nivolumab or sintilimab) combined with radiotherapy from Beijing Tsinghua Changgung Hospital in China were reviewed for eligibility. The efficacy was evaluated by the survival and PVTT response rate, and the safety was evaluated by the frequency of key adverse events (AEs). Results: In total, 39 eligible HCC patients with type Vp-4 PVTT who received triple therapy were included in this study. The 2-year OS rate was 15.4%, which was the primary end-point of our study. The median overall survival (OS) and progression-free survival (PFS) were 9.4 months (range 2.3 to 57.1) and 4.9 months (range 1.4 to 36.1), respectively. The objective response rate (ORR) of PVTT based on mRECIST was 61.5%. AFP dropped to normal 3 months after radiotherapy and was an independent risk factor associated with OS. All AEs were controlled, and no treatment-related deaths occurred. Conclusion: Lenvatinib plus PD-1 inhibitor combined with radiotherapy had a significant therapeutic effect and manageable AEs in HCC patients with type Vp-4 PVTT and may be a potential treatment option for advanced HCC.

Dysregulation of PLOD2 Promotes Tumor Metastasis and Invasion in Hepatocellular Carcinoma.

Background and Aims: Metastasis is a major factor associated with high recurrence and mortality in hepatocellular carcinoma (HCC) patients while the underlying mechanism of metastasis remains elusive. In our study, procollagen-lysine, 2-oxoglutarate 5-dioxygenase 2 (PLOD2) was shown to be involved in the process of metastasis in HCC. Methods: The Cancer Genome Atlas (TCGA) database and HCC tissue microarrays were used to evaluate the expression of genes. In vitro migration, invasion, in vivo subcutaneous tumor model and in vivo lung metastasis assays were used to determine the role of PLOD2 in tumor growth and metastasis in HCC. RNA sequencing and gene set enrichment analysis were performed to uncover the downstream factor of PLOD2 in HCC cells. A luciferase reporter assay was performed to evaluate the interaction between PLOD2 and interferon regulatory factor 5 (IRF5). Results: The expression of PLOD2 in HCC tissues was higher than that in adjacent tissues, and increased PLOD2 expression was often found in advanced tumors and was correlated with poor prognosis in HCC patients. In vitro experiments, knockdown of PLOD2 reduced the migration and invasion of human HCC cells. Loss of PLOD2 suppressed human HCC growth and metastasis in a subcutaneous tumor model and a lung metastasis model. Baculoviral IAP repeat containing 3 (BIRC3) was proven to be the downstream factor of PLOD2 in human HCC cells. In addition, PLOD2 was transcriptionally regulated by IRF5 in HCC cells. Conclusions: High expression of PLOD2 was regulated by IRF5, which was correlated with the poor survival of HCC patients. PLOD2 enhanced HCC metastasis via BIRC3, suggesting that PLOD2 might be a valuable prognostic biomarker for HCC treatment.

PRMT3-mediated arginine methylation of IGF2BP1 promotes oxaliplatin resistance in liver cancer.

Although oxaliplatin-based chemotherapy has been effective in the treatment of hepatocellular carcinoma (HCC), primary or acquired resistance to oxaliplatin remains a major challenge in the clinic. Through functional screening using CRISPR/Cas9 activation library, transcriptomic profiling of clinical samples, and functional validation in vitro and in vivo, we identify PRMT3 as a key driver of oxaliplatin resistance. Mechanistically, PRMT3-mediated oxaliplatin-resistance is in part dependent on the methylation of IGF2BP1 at R452, which is critical for the function of IGF2BP1 in stabilizing the mRNA of HEG1, an effector of PRMT3-IGF2BP1 axis. Also, PRMT3 overexpression may serve as a biomarker for oxaliplatin resistance in HCC patients. Collectively, our study defines the PRTM3-IGF2BP1-HEG1 axis as important regulators and therapeutic targets in oxaliplatin-resistance and suggests the potential to use PRMT3 expression level in pretreatment biopsy as a biomarker for oxaliplatin-resistance in HCC patients.

A quantum algorithm for heat conduction with symmetrization.

Heat conduction, driven by thermal non-equilibrium, is the transfer of internal thermal energy through physical contacts, and it exists widely in various engineering problems, such as spacecraft and state-of-the-art dilution refrigerators. The mathematical equation for heat conduction is a prototypical partial differential equation. Here we report a quantum algorithm for heat conduction (QHC) that significantly outperforms classical algorithms. We represent the original heat conduction system by a symmetric system with an ancilla qubit so that the quantum circuit complexity is polylogarithmic in the number of discretized grid points. Compared with the existing algorithms based on solving linear equations via the Harrow-Hassidim-Lloyd (HHL) algorithm, our method evolves the linear process directly without phase estimation, which involves complex quantum operations and large output error. Therefore, this algorithm is experimental-friendly and without output error after the discretization procedure. We experimentally implemented the algorithm for a one-dimensional thermal conduction process with two-edge constant temperatures and adiabatic conditions on a nuclear spin quantum processor. The spatial and temporal distributions of the temperature are accurately determined from the experimental results. Our work can be naturally applied to any physical processes that can be reduced to the heat equation.

S100A9 Derived from Chemoembolization-Induced Hypoxia Governs Mitochondrial Function in Hepatocellular Carcinoma Progression.

Transarterial chemoembolization (TACE) is the major treatment for advanced hepatocellular carcinoma (HCC), but it may cause hypoxic environment, leading to rapid progression after treatment. Here, using high-throughput sequencing on different models, S100 calcium binding protein A9 (S100A9) is identified as a key oncogene involved in post-TACE progression. Depletion or pharmacologic inhibition of S100A9 significantly dampens the growth and metastatic ability of HCC. Mechanistically, TACE induces S100A9 via hypoxia-inducible factor 1α (HIF1A)-mediated pathway. S100A9 acts as a scaffold recruiting ubiquitin specific peptidase 10 and phosphoglycerate mutase family member 5 (PGAM5) to form a tripolymer, causing the deubiquitination and stabilization of PGAM5, leading to mitochondrial fission and reactive oxygen species production, thereby promoting the growth and metastasis of HCC. Higher S100A9 level in HCC tissue or in serum predicts a worse outcome for HCC patients. Collectively, this study identifies S100A9 as a key driver for post-TACE HCC progression. Targeting S100A9 may be a promising therapeutic strategy for HCC patients.

A NISQ Method to Simulate Hermitian Matrix Evolution.

As a universal quantum computer requires millions of error-corrected qubits, one of the current goals is to exploit the power of noisy intermediate-scale quantum (NISQ) devices. Based on a NISQ module-layered circuit, we propose a heuristic protocol to simulate Hermitian matrix evolution, which is widely applied as the core for many quantum algorithms. The two embedded methods, with their own advantages, only require shallow circuits and basic quantum gates. Capable to being deployed in near future quantum devices, we hope it provides an experiment-friendly way, contributing to the exploitation of power of current devices.

A detailed assessment of liver function in patients with hepatocellular carcinoma via the modified albumin-bilirubin (mALBI) grade.

Recently, the albumin-bilirubin (ALBI) score, a continuous index consisting of only albumin and bilirubin, has been developed for objectively assessing liver function in patients with hepatocellular carcinoma (HCC). However, the ALBI score was arbitrarily categorized into three ALBI grades based on two artificially predetermined cutoff points with no explanation and statistical grounds, causing a considerable loss of discriminatory ability. This study aims to propose a modified ALBI (mALBI) grade for offering a detailed evaluation of hepatic reserve and specify its role during clinical practice in the HCC setting. The study population comprised 3540 HCC patients treated with mainstream therapies including hepatectomy (n=2056), thermal ablation (n=550), and transcatheter arterial chemoembolization (n=934) from 2002 to 2017. The ALBI score was stratified into four mALBI grades through a recently proposed statistical method aiming to select the optimal cutoff points of a continuous predictive variable by maximizing the discriminative ability in a multivariable Cox regression model. The mALBI grade had an overall better discriminatory ability than the ALBI grade in predicting overall survival through Harrell's C-index (0.614 vs. 0.598, P<0.001). Both visual inspections of Kaplan-Meier curves and calculation of hazard ratios displayed a more subtle evaluation of liver function using the mALBI grade. Moreover, the newly identified cut-point (ALBI score = -2.29) between the mALBI grade 2a and 2b was much closer to a 30% retention rate of indocyanine green at 15 minutes, an indicator for the performance of a subsegmentectomy. The newly proposed mALBI grade provides a more subtle assessment of liver function to guide clinical decision-making and predicts the prognosis of HCC patients more accurately than the original ALBI grade.

Insufficient ablation induces E3-ligase Nedd4 to promote hepatocellular carcinoma progression by tuning TGF-ß signaling.

Thermal ablation is a main curative therapy for early-stage hepatocellular carcinoma (HCC). However, insufficient ablation has been shown to promote HCC progression. E3 ligases have been approved to play important roles in malignant tumors. Whether E3 ligases are involved in HCC progression caused by insufficient ablation remains unclear. Herein, using RNA-sequencing coupled with an in vitro loss-of-function screen, we found that the E3 ligase Neuronal Precursor cell-expressed Developmentally Downregulated 4 (Nedd4) was upregulated in HCC insufficient ablation tissues and promoted HCC cells migration. The upregulation of Nedd4 was induced by METTL14-mediated N6-methyladenosine modification after sublethal heat treatment. Knockdown of Nedd4 inhibited HCC metastasis and growth in vitro and in vivo. Mechanistically, Nedd4 enhanced TGF-ß signal transduction mediated tumor progression by directly binding to TGF-ß type I receptor (TGFBR1) and forming K27-linked ubiquitin at Lysine 391. Additionally, the adverse effect on HCC of sublethal heat treatment was mediated by Nedd4. Clinically, high Nedd4 expression was positively correlated with aggressive tumor phenotypes and poor prognosis in HCC patients. Patient-derived xenograft (PDX) model confirmed this conclusion. Collectively, this study demonstrated that Nedd4 induced by insufficient ablation plays a crucial role in promoting HCC progression and provides a novel therapeutic target for HCC.

DNAcycP: a deep learning tool for DNA cyclizability prediction.

DNA mechanical properties play a critical role in every aspect of DNA-dependent biological processes. Recently a high throughput assay named loop-seq has been developed to quantify the intrinsic bendability of a massive number of DNA fragments simultaneously. Using the loop-seq data, we develop a software tool, DNAcycP, based on a deep-learning approach for intrinsic DNA cyclizability prediction. We demonstrate DNAcycP predicts intrinsic DNA cyclizability with high fidelity compared to the experimental data. Using an independent dataset from in vitro selection for enrichment of loopable sequences, we further verified the predicted cyclizability score, termed C-score, can well distinguish DNA fragments with different loopability. We applied DNAcycP to multiple species and compared the C-scores with available high-resolution chemical nucleosome maps. Our analyses showed that both yeast and mouse genomes share a conserved feature of high DNA bendability spanning nucleosome dyads. Additionally, we extended our analysis to transcription factor binding sites and surprisingly found that the cyclizability is substantially elevated at CTCF binding sites in the mouse genome. We further demonstrate this distinct mechanical property is conserved across mammalian species and is inherent to CTCF binding DNA motif.

RiboDiPA: a novel tool for differential pattern analysis in Ribo-seq data.

Ribosome profiling, also known as Ribo-seq, has become a popular approach to investigate regulatory mechanisms of translation in a wide variety of biological contexts. Ribo-seq not only provides a measurement of translation efficiency based on the relative abundance of ribosomes bound to transcripts, but also has the capacity to reveal dynamic and local regulation at different stages of translation based on positional information of footprints across individual transcripts. While many computational tools exist for the analysis of Ribo-seq data, no method is currently available for rigorous testing of the pattern differences in ribosome footprints. In this work, we develop a novel approach together with an R package, RiboDiPA, for Differential Pattern Analysis of Ribo-seq data. RiboDiPA allows for quick identification of genes with statistically significant differences in ribosome occupancy patterns for model organisms ranging from yeast to mammals. We show that differential pattern analysis reveals information that is distinct and complimentary to existing methods that focus on translational efficiency analysis. Using both simulated Ribo-seq footprint data and three benchmark data sets, we illustrate that RiboDiPA can uncover meaningful pattern differences across multiple biological conditions on a global scale, and pinpoint characteristic ribosome occupancy patterns at single codon resolution.

Patient dissatisfaction following total knee arthroplasty: external validation of a new prediction model.

Tools designed to predict patient satisfaction following total knee arthroplasty (TKA) have the potential to guide patient selection. Our study aimed to validate a model that predicts patient satisfaction following TKA. Phone surveys were administered to 203 patients who underwent TKA between 2009 and 2016 at the University of Illinois. We utilized health records to document age, gender, body mass index (BMI), and comorbidities. First, we compared the descriptive variables between the satisfied and dissatisfied groups. We then performed multivariate linear regression and multiple logistic regression to assess the predictive value of the questions in the Van Onsem et al. model. The true satisfaction rate in our study was 65%. The Van Onsem et al. model predicted a satisfaction rate of 70%. The scatter plot of predicted satisfaction score versus observed satisfaction score showed poor agreement between actual satisfaction and predicted satisfaction. Comparing satisfied and dissatisfied groups, there was a significant difference with respect to pain prior to surgery and BMI. The validity of the Van Onsem et al. prediction tool was not supported. While the predicted satisfaction rate was near the measured satisfaction rate, the model misidentified which patients were likely to be satisfied. Preoperative variables including pain, anxiety/depression, and a patient's ability to control pain symptoms showed potential for inclusion in future prediction models. LEVEL OF EVIDENCE: Level III, developing a decision model.

NMRCloudQ: a quantum cloud experience on a nuclear magnetic resonance quantum computer.

Cloud-based quantum computing is anticipated to be the most useful and reachable form for public users to experience with the power of quantum. As initial attempts, IBM Q has launched influential cloud services on a superconducting quantum processor in 2016, but no other platforms has followed up yet. Here, we report our new cloud quantum computing service - NMRCloudQ (http://nmrcloudq.com/zh-hans/), where nuclear magnetic resonance, one of the pioneer platforms with mature techniques in experimental quantum computing, plays as the role of implementing computing tasks. Our service provides a comprehensive software environment preconfigured with a list of quantum information processing packages, and aims to be freely accessible to either amateurs that look forward to keeping pace with this quantum era or professionals that are interested in carrying out real quantum computing experiments in person. In our current version, four qubits are already usable with in average 99.10% single-qubit gate fidelity and 97.15% two-qubit fidelity via randomized benchmaking tests. Improved control precisions as well as a new seven-qubit processor are also in preparation and will be available later.

Experimental Identification of Non-Abelian Topological Orders on a Quantum Simulator.

Topological orders can be used as media for topological quantum computing-a promising quantum computation model due to its invulnerability against local errors. Conversely, a quantum simulator, often regarded as a quantum computing device for special purposes, also offers a way of characterizing topological orders. Here, we show how to identify distinct topological orders via measuring their modular S and T matrices. In particular, we employ a nuclear magnetic resonance quantum simulator to study the properties of three topologically ordered matter phases described by the string-net model with two string types, including the Z_{2} toric code, doubled semion, and doubled Fibonacci. The third one, non-Abelian Fibonacci order is notably expected to be the simplest candidate for universal topological quantum computing. Our experiment serves as the basic module, built on which one can simulate braiding of non-Abelian anyons and ultimately, topological quantum computation via the braiding, and thus provides a new approach of investigating topological orders using quantum computers.

Transition to synchronization in a Kuramoto model with the first- and second-order interaction terms.

We investigate a Kuramoto model incorporated with the first-order and the second-order interaction terms. We show that the model displays the coexistence of multiattractors and different attractors may be characterized by the phase distributions of oscillators. By investigating the transition diagrams in both forward continuation and backward continuation, we find that the synchronous state with unimodal phase distribution is the most stable one while the state in cluster synchrony with evenly distributed bimodal phase distribution is the least stable one. We also present the phase diagram of the model in the parameter space.

Implantable image sensor based on intra-brain image transmission.

We developed and fabricated a micro-imager based on wireless intra-brain communication using conductive property of living tissues. An pixel array, analog-to-digital converter and transmitter are integrated on a single chip. The dimensions of the chip are 1 mm × 1mm × 0.15 mm. We demonstrate wireless image transmission through phosphate buffer saline as a brain phantom.

Baseband signal transmission experiment for intra-brain communication with implantable image sensor.

We demonstrate image signal transmission for wireless intra-brain communication. As a preliminary experiment, transmission characteristics of the brain phantom were measured. The baseband output signal from an implantable complementary metal-oxide-semiconductor (CMOS) image sensor is transmitted through the phantom. The image was successfully reproduced from the received signal.

Wireless intra-brain communication for image transmission through mouse brain.

We demonstrate wireless image data transmission through a mouse brain. The transmission characteristics of mouse brain is measured. By inserting electrodes into the brain, the transmission efficiency is drastically increased. An AM signal modulated with the image data from an implantable image sensor was launched into the brain and the received signal was demodulated. The data was successfully transmitted through the brain and the image was reproduced.