Convolutional LSTM model for cine image prediction of abdominal motion

Objective.In this study, we tackle the challenge of latency in magnetic resonance linear accelerator (MR-Linac) systems, which compromises target coverage accuracy in gated real-time radiotherapy. Our focus is on enhancing motion prediction precision in abdominal organs to address this issue. We developed a convolutional long short-term memory (convLSTM) model, utilizing 2D cine magnetic resonance (cine-MR) imaging for this purpose.Approach.Our model, featuring a sequence-to-one architecture with six input frames and one output frame, employs structural similarity index measure (SSIM) as loss function. Data was gathered from 17 cine-MRI datasets using the Philips Ingenia MR-sim system and an Elekta Unity MR-Linac equivalent sequence, focusing on regions of interest (ROIs) like the stomach, liver, pancreas, and kidney. The datasets varied in duration from 1 to 10 min.Main results.The study comprised three main phases: hyperparameter optimization, individual training, and transfer learning with or without fine-tuning. Hyperparameters were initially optimized to construct the most effective model. Then, the model was individually applied to each dataset to predict images four frames ahead (1.24-3.28 s). We evaluated the model's performance using metrics such as SSIM, normalized mean square error, normalized correlation coefficient, and peak signal-to-noise ratio, specifically for ROIs with target motion. The average SSIM values achieved were 0.54, 0.64, 0.77, and 0.66 for the stomach, liver, kidney, and pancreas, respectively. In the transfer learning phase with fine-tuning, the model showed improved SSIM values of 0.69 for the liver and 0.78 for the kidney, compared to 0.64 and 0.37 without fine-tuning.Significance. The study's significant contribution is demonstrating the convLSTM model's ability to accurately predict motion for multiple abdominal organs using a Unity-equivalent MR sequence. This advancement is key in mitigating latency issues in MR-Linac radiotherapy, potentially improving the precision and effectiveness of real-time treatment for abdominal cancers.

Chemokine CCL21 determines immunotherapy response in hepatocellular carcinoma by affecting neutrophil polarization

BACKGROUND

The efficacy of immune checkpoint inhibitors (ICIs) in hepatocellular carcinoma (HCC) is poor and great heterogeneity among individuals. Chemokines are highly correlated with tumor immune response. Here, we aimed to identify an effective chemokine for predicting the efficacy of immunotherapy in HCC.

METHODS

Chemokine C-C motif ligand 21 (CCL21) was screened by transcriptomic analysis in tumor tissues from HCC patients with different responses to ICIs. The least absolute shrinkage and selection operator (LASSO) regression analysis was conducted to construct a predictive nomogram. Neutrophils in vitro and HCC subcutaneous tumor model in vivo were applied to explore the role of CCL21 on the tumor microenvironment (TME) of HCC.

RESULTS

Transcriptome analysis showed that CCL21 level was much higher in HCC patients with response to immunotherapy. The predictive nomogram was constructed and validated as a classifier. CCL21 could inhibit N2 neutrophil polarization by suppressing the activation of nuclear factor kappa B (NF-κB) pathway. In addition, CCL21 enhanced the therapeutic efficacy of ICIs.

CONCLUSION

CCL21 may serve as a predictive biomarker for immunotherapy response in HCC patients. High levels of CCL21 in TME inhibit immunosuppressive polarization of neutrophils. CCL21 in combination with ICIs may offer a novel therapeutic strategy for HCC.

Targeting ALK averts ribonuclease 1-induced immunosuppression and enhances antitumor immunity in hepatocellular carcinoma

Tumor-secreted factors contribute to the development of a microenvironment that facilitates the escape of cancer cells from immunotherapy. In this study, we conduct a retrospective comparison of the proteins secreted by hepatocellular carcinoma (HCC) cells in responders and non-responders among a cohort of ten patients who received Nivolumab (anti-PD-1 antibody). Our findings indicate that non-responders have a high abundance of secreted RNase1, which is associated with a poor prognosis in various cancer types. Furthermore, mice implanted with HCC cells that overexpress RNase1 exhibit immunosuppressive tumor microenvironments and diminished response to anti-PD-1 therapy. RNase1 induces the polarization of macrophages towards a tumor growth-promoting phenotype through activation of the anaplastic lymphoma kinase (ALK) signaling pathway. Targeting the RNase1/ALK axis reprograms the macrophage polarization, with increased CD8+ T- and Th1- cell recruitment. Moreover, simultaneous targeting of the checkpoint protein PD-1 unleashes cytotoxic CD8+ T-cell responses. Treatment utilizing both an ALK inhibitor and an anti-PD-1 antibody exhibits enhanced tumor regression and facilitates long-term immunity. Our study elucidates the role of RNase1 in mediating tumor resistance to immunotherapy and reveals an RNase1-mediated immunosuppressive tumor microenvironment, highlighting the potential of targeting RNase1 as a promising strategy for cancer immunotherapy in HCC.

Whole-exome sequencing reveals the metastatic potential of hepatocellular carcinoma from the perspective of tumor and circulating tumor DNA

BACKGROUND

Relapse of hepatocellular carcinoma (HCC) due to vascular invasion is common, but the genomic mechanisms remain unclear, and molecular determinants of high-risk relapse cases are lacking. We aimed to reveal the evolutionary trajectory of microvascular invasion (MVI) and develop a predictive signature for relapse in HCC.

METHODS

Whole-exome sequencing was performed on tumor and peritumor tissues, portal vein tumor thrombus (PVTT), and circulating tumor DNA (ctDNA) to compare the genomic profiles between 5 HCC patients with MVI and 5 patients without MVI. We conducted an integrated analysis of exome and transcriptome to develop and validate a prognostic signature in two public cohorts and one cohort from Zhongshan Hospital, Fudan University.

RESULTS

Shared genomic landscapes and identical clonal origins among tumor, PVTT, and ctDNA were observed in MVI ( +) HCC, suggesting that genomic changes favoring metastasis occur at the primary tumor stage and are inherited in metastatic lesions and ctDNA. There was no clonal relatedness between the primary tumor and ctDNA in MVI ( - ) HCC. HCC had dynamic mutation alterations during MVI and exhibited genetic heterogeneity between primary and metastatic tumors, which can be comprehensively reflected by ctDNA. A relapse-related gene signature named RGSHCC was developed based on the significantly mutated genes associated with MVI and shown to be a robust classifier of HCC relapse.

CONCLUSIONS

We characterized the genomic alterations during HCC vascular invasion and revealed a previously undescribed evolution pattern of ctDNA in HCC. A novel multiomics-based signature was developed to identify high-risk relapse populations.

Dose Constraints and Planning Considerations for Thoracic Radiation Therapy: Delphi Consensus from a National Survey of Experts

PURPOSE/OBJECTIVE(S)

Many physicians refer to trial protocols or published guidelines (NCCN, QUANTEC, HyTEC) for dose-volume histogram (DVH) metrics. However, there may be variation in implementing these metrics during plan optimization. Some studies have suggested better outcomes for patients treated at high-volume, high-expertise centers. These differences may in part be due to greater standardization or center-specific treatment planning processes. We surveyed radiation oncologists with stated thoracic-specific expertise using the Delphi method to formulate consensus DVH metrics that would be considered ideal for high-quality radiation treatment plans.

MATERIALS/METHODS

Thoracic radiation oncology experts were identified using departmental websites of ACGME-accredited radiation oncology programs. After confirming their expertise, panelists were invited to submit their institutional templates and complete three rounds of questions related to normal organ dose constraints, target coverage metrics, prescribing practices, and other planning considerations. Queried radiation schemes included conventional fractionation, twice-daily fractionation, and stereotactic body radiation therapy (3 and 5 fractions). Preliminary consensus statements were generated using median values for DVH metrics and were iteratively refined in subsequent surveys. Consensus was pre-defined as ≥75% agreement among panelists.

RESULTS

A total of 194 experts were invited, and 100 agreed to participate. The panel was 28% female and included experts from 29 states with a median of 11 years of clinical experience (IQR 6-19). 89% specialized in 1-2 disease sites. Response rates for the Demographics, round 1, 2, and 3 surveys were 83%, 78%, 57%, and 55%, respectively. 93% of panelists believed that DVH metrics should provide thresholds for both optimal and acceptable criteria for treatment planning. 49 of the 96 proposed normal tissue dose constraint statements were iterated to consensus (Table 1), and 5 of 7 proposed target coverage metric statements achieved consensus.

CONCLUSION

This study highlights the heterogeneity in metrics used by thoracic radiation oncologists and provides levels of consensus on ideal and acceptable dose constraints as guidance for treatment planning. Future directions include using these statements to develop prescription templates and acceptance criteria for treatment planning systems for widespread use as well as extending this Delphi approach to additional disease sites.

Dual-branch hybrid encoding embedded network for histopathology image classification

Objective.Learning-based histopathology image (HI) classification methods serve as important tools for auxiliary diagnosis in the prognosis stage. However, most existing methods are focus on a single target cancer due to inter-domain differences among different cancer types, limiting their applicability to different cancer types. To overcome these limitations, this paper presents a high-performance HI classification method that aims to address inter-domain differences and provide an improved solution for reliable and practical HI classification.Approach.Firstly, we collect a high-quality hepatocellular carcinoma (HCC) dataset with enough data to verify the stability and practicability of the method. Secondly, a novel dual-branch hybrid encoding embedded network is proposed, which integrates the feature extraction capabilities of convolutional neural network and Transformer. This well-designed structure enables the network to extract diverse features while minimizing redundancy from a single complex network. Lastly, we develop a salient area constraint loss function tailored to the unique characteristics of HIs to address inter-domain differences and enhance the robustness and universality of the methods.Main results.Extensive experiments have conducted on the proposed HCC dataset and two other publicly available datasets. The proposed method demonstrates outstanding performance with an impressive accuracy of 99.09% on the HCC dataset and achieves state-of-the-art results on the other two public datasets. These remarkable outcomes underscore the superior performance and versatility of our approach in multiple HI classification.Significance.The advancements presented in this study contribute to the field of HI analysis by providing a reliable and practical solution for multiple cancer classification, potentially improving diagnostic accuracy and patient outcomes. Our code is available athttps://github.com/lms-design/DHEE-net.

Functions of Key Enzymes of Glycolytic Metabolism in Tumor Microenvironment

The tumor microenvironment (TME) plays a crucial role in tumor initiation, growth and metastasis. Metabolic enzymes involved in tumor glycolytic reprogramming, including hexokinase, pyruvate kinase, and lactate dehydrogenase, not only play key roles in tumorigenesis and maintaining tumor cell survival, but also take part in the modulation of the TME. Many studies have been devoted to the role of key glycolytic enzymes in the TME over the past decades. We summarize the studies on the role of glycolytic enzymes in the TME of these years and found that glycolytic enzymes remodel the TME primarily through regulating immune escape, angiogenesis, and affecting stromal cells and exosomes. Notably, abnormal tumor vascular system, peritumoral stromal cells, and tumor immunosuppressive microenvironment are important contributors to the failure of antitumor therapy. Therefore, we discuss the mechanisms of regulation by key glycolytic enzymes that may contribute to a promising biomarker for therapeutic intervention. We argue that targeting key glycolytic enzymes in combination with antiprogrammed cell death ligand 1 or antivascular endothelial growth factor could emerge as the more integrated and comprehensive antitumor treatment strategy.

Intratumoral PPT1-positive macrophages determine immunosuppressive contexture and immunotherapy response in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a malignancy with limited treatment options and poor prognosis. Macrophages are enriched in the HCC microenvironment and have a significant impact on disease progression and therapy efficacy. We aim to identify critical macrophages subsets involved in HCC development.

METHODS

Macrophage-specific marker genes were identified through single-cell RNA sequencing analyses. The clinical significance of macrophages with palmitoyl-protein thioesterase 1 (PPT1) positive was investigated in 169 patients with HCC from Zhongshan Hospital using immunohistochemistry and immunofluorescence. The immune microenvironment of HCC and the functional phenotype of PPT1+ macrophages were explored using cytometry by time-of-flight (CyTOF) and RNA sequencing.

RESULTS

Single-cell RNA sequencing analyses revealed that PPT1 was predominantly expressed in macrophages in HCC. Intratumoral PPT1+ macrophages abundance was associated with inferior survival durations of patients and an independent risk factor of prognosis for HCC. High throughput analyses of immune infiltrates showed that PPT1+ macrophage-enriched HCCs were characterized by high infiltration of CD8+ T cells with increased programmed death-1 (PD-1) expression. PPT1+ macrophages exhibited higher galectin-9, CD172a, and CCR2 levels but lower CD80 and CCR7 levels than PPT1- macrophages. Pharmacological inhibition of PPT1 by DC661 suppressed mitogen-activated protein kinase (MAPK) pathway activity but activated nuclear factor kappa B (NF-κB) pathway in macrophages. In addition, DC661 enhanced the therapeutic efficacy of anti-PD-1 antibody in the HCC mouse model.

CONCLUSIONS

PPT1 is mainly expressed in macrophages in HCC and promotes immunosuppressive transformation of macrophages and tumor microenvironment. PPT1+ macrophage infiltration is associated with poor prognosis of patients with HCC. Targeting PPT1 may potentiate the efficacy of immunotherapy for HCC.

Disruption of SLFN11 Deficiency-Induced CCL2 Signaling and Macrophage M2 Polarization Potentiates Anti-PD-1 Therapy Efficacy in Hepatocellular Carcinoma

BACKGROUND & AIMS

The therapeutic effect of immune checkpoint inhibitors (ICIs) is poor in hepatocellular carcinoma (HCC) and varies greatly among individuals. Schlafen (SLFN) family members have important functions in immunity and oncology, but their roles in cancer immunobiology remain unclear. We aimed to investigate the role of the SLFN family in immune responses against HCC.

METHODS

Transcriptome analysis was performed in human HCC tissues with or without response to ICIs. A humanized orthotopic HCC mouse model and a co-culture system were constructed, and cytometry by time-of-flight technology was used to explore the function and mechanism of SLFN11 in the immune context of HCC.

RESULTS

SLFN11 was significantly up-regulated in tumors that responded to ICIs. Tumor-specific SLFN11 deficiency increased the infiltration of immunosuppressive macrophages and aggravated HCC progression. HCC cells with SLFN11 knockdown promoted macrophage migration and M2-like polarization in a C-C motif chemokine ligand 2-dependent manner, which in turn elevated their own PD-L1 expression by activating the nuclear factor-κB pathway. Mechanistically, SLFN11 suppressed the Notch pathway and C-C motif chemokine ligand 2 transcription by binding competitively with tripartite motif containing 21 to the RNA recognition motif 2 domain of RBM10, thereby inhibiting tripartite motif containing 21-mediated RBM10 degradation to stabilize RBM10 and promote NUMB exon 9 skipping. Pharmacologic antagonism of C-C motif chemokine receptor 2 potentiated the antitumor effect of anti-PD-1 in humanized mice bearing SLFN11 knockdown tumors. ICIs were more effective in patients with HCC with high serum SLFN11 levels.

CONCLUSIONS

SLFN11 serves as a critical regulator of microenvironmental immune properties and an effective predictive biomarker of ICIs response in HCC. Blockade of C-C motif chemokine ligand 2/C-C motif chemokine receptor 2 signaling sensitized SLFN11^low HCC patients to ICI treatment.

Artificial Intelligence-Assisted Evaluation of the Spatial Relationship between Brain Arteriovenous Malformations and the Corticospinal Tract to Predict Postsurgical Motor Defects

BACKGROUND AND PURPOSE

Preoperative evaluation of brain AVMs is crucial for the selection of surgical candidates. Our goal was to use artificial intelligence to predict postsurgical motor defects in patients with brain AVMs involving motor-related areas.

MATERIALS AND METHODS

Eighty-three patients who underwent microsurgical resection of brain AVMs involving motor-related areas were retrospectively reviewed. Four artificial intelligence-based indicators were calculated with artificial intelligence on TOF-MRA and DTI, including FN5mm/50mm (the proportion of fiber numbers within 5-50mm from the lesion border), FN10mm/50mm (the same but within 10-50mm), FP5mm/50mm (the proportion of fiber voxel points within 5-50mm from the lesion border), and FP10mm/50mm (the same but within 10-50mm). The association between the variables and long-term postsurgical motor defects was analyzed using univariate and multivariate analyses. Least absolute shrinkage and selection operator regression with the Pearson correlation coefficient was used to select the optimal features to develop the machine learning model to predict postsurgical motor defects. The area under the curve was calculated to evaluate the predictive performance.

RESULTS

In patients with and without postsurgical motor defects, the mean FN5mm/50mm, FN10mm/50mm, FP5mm/50mm, and FP10mm/50mm were 0.24 (SD, 0.24) and 0.03 (SD, 0.06), 0.37 (SD, 0.27) and 0.06 (SD, 0.08), 0.06 (SD, 0.10) and 0.01 (SD, 0.02), and 0.10 (SD, 0.12) and 0.02 (SD, 0.05), respectively. Univariate and multivariate logistic analyses identified FN10mm/50mm as an independent risk factor for long-term postsurgical motor defects (P = .002). FN10mm/50mm achieved a mean area under the curve of 0.86 (SD, 0.08). The mean area under the curve of the machine learning model consisting of FN10mm/50mm, diffuseness, and the Spetzler-Martin score was 0.88 (SD, 0.07).

CONCLUSIONS

The artificial intelligence-based indicator, FN10mm/50mm, can reflect the lesion-fiber spatial relationship and act as a dominant predictor for postsurgical motor defects in patients with brain AVMs involving motor-related areas.

Radiation Therapy Decision Making Process and Operations for COVID-19 Positive Patients

Purpose/Objective(s)

A challenging clinical dilemma during the COVID-19 pandemic is management of cancer patients who test positive for COVID. Given the need to balance the risk of disease progression with the risk of transmission to other patients and staff, radiation therapy for these patients requires careful consideration and modification of standard workflows. It is also critical to develop processes to mitigate radiation treatment interruption, which can affect patient outcomes. The objective of this study was to report the clinical operations and outcomes for COVID positive patients receiving radiation therapy during the pandemic at a tertiary cancer center including 2 network locations.

Materials/Methods

During March 2020 to March 2022, the Radiation Oncology COVID committee (RO COVID) developed an integrated process to triage patients, provide treatment recommendations, and implement infection control procedures to safely deliver radiation therapy to COVID positive patients. Policies were created for each center with multidisciplinary input from infectious disease, radiation oncology, radiation therapy, and nursing. All COVID positive patients were presented to the RO COVID group and evaluated for clinical urgency, benefit with radiation, and life expectancy. If deemed necessary, a limited planned break or hypofractionated regimen was recommended to minimize staff exposure. We conducted a retrospective review of COVID positive patients with different primary malignancies treated through the COVID positive pathway.

Results

A total of 68 COVID positive patients were treated with the COVID positive pathway (HN 15, Breast 9, CNS 8, GU 8, GYN, 7, Thoracic 6, GI 5, HEME 5, PED 3, SARC 2). The median age was 57.1 years (IQR 45.8-63.4) and 47% were female. There were 39 patients (57%) who were asymptomatic and were tested for routine pre-radiation screening or due to concerns of COVID exposure. Twenty-three (34%) patients were treated with palliative intent and 8 (12%) were treated for an emergent indication (i.e., spinal cord compression, bleeding). Thirteen (19%) patients were receiving radiation treatment, had a treatment break (7-21 days), and then resumed their radiation course. All treatments were successfully completed without known nosocomial spread of COVID to staff or other patients. Among this heterogenous group of patients, 58 (85%) were alive with a median follow up of 2 months (IQR 0.5-7.5). COVID infection may have contributed to 3 out of 10 deaths (4% of total cohort). The remaining deaths were due to progression of disease or other non-COVID causes.

Conclusion

In this study, COVID positive patients were safely treated with radiation therapy through a comprehensive decision making and clinical operations pathway taking into account evolving COVID guidelines for three different variant surges. Although limited in follow up, patient outcomes are promising with few COVID-related deaths and low overall mortality rates, even with hypofractionated regimens.

A Novel mRNA Signature Related to Immunity to Predict Survival and Immunotherapy Response in Hepatocellular Carcinoma

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and the incidence and mortality rates are increasing. Given the limited treatments of HCC and promising application of immunotherapy for cancer, we aimed to identify an immune-related prognostic signature that can predict overall survival (OS) rates and immunotherapy response in HCC.

METHODS

The initial signature development was conducted using a training dataset from the Cancer Genome Atlas followed by independent internal and external validations from that resource and the Gene Expression Omnibus. A signature based nomogram was generated using multivariate Cox regression analysis. The associations of signature score with tumor immune phenotype and response to immunotherapy were analyzed using single-sample gene set enrichment analysis and tumor immune dysfunction and exclusion algorithm. A cohort from Zhongshan Hospital was employed to verify the predictive robustness of the signature regarding prognostic risk and immunotherapy response.

RESULTS

The prognostic signature, IGS_HCC, consisting of 22 immune-related genes, had independent prognostic ability, with training and validation cohorts. Also, IGS_HCC stratified HCC patients with different outcomes in subgroups. The prognostic accuracy of IGS_HCC was better than three reported prognostic signatures. The IGS_HCC-based nomogram had high accuracy and significant clinical benefits in predicting 3- and 5-year OS. IGS_HCC reflected distinct immunosuppressive phenotypes in low- and high-score groups. Patients with low IGS_HCC scores were more likely than those with high scores to benefit from immunotherapy.

CONCLUSIONS

IGS_HCC predicted HCC prognosis and response to immunotherapy, and contributed to individualized clinical management.

Deglycosylation of SLAMF7 in breast cancers enhances phagocytosis

N-linked glycosylation of proteins is one of the post-translational modifications (PTMs) that shield tumor antigens from immune attack. Signaling lymphocytic activation molecule family 7 (SLAMF7) suppresses cancer cell phagocytosis and is an ideal target under clinical development. PTM of SLAMF7, however, remains less understood. In this study, we investigated the role of N-glycans on SLAMF7 in breast cancer progression. We identified seven N-linked glycosylation motifs on SLAMF7, which are majorly occupied by complex structures. Evolutionally conserved N98 residue is enriched with high mannose and sialylated glycans. Hyperglycosylated SLAMF7 was associated with STT3A expression in breast cancer cells. Inhibition of STT3A by a small molecule inhibitor, N-linked glycosylation inhibitor-1 (NGI-1), reduced glycosylation of SLAMF7, resulting in enhancing antibody affinity and phagocytosis. To provide an on-target effect, we developed an antibody-drug conjugate (ADC) by coupling the anti-SLAMF7 antibody with NGI-1. Deglycosylation of SLAMF7 increases antibody recognition and promotes macrophage engulfment of breast cancer cells. Our work suggests deglycosylation by ADC is a potential strategy to enhance the response of immunotherapeutic agents.

GTPBP4 promotes hepatocellular carcinoma progression and metastasis via the PKM2 dependent glucose metabolism

Guanosine triphosphate binding protein 4 (GTPBP4) is a key regulator of cell cycle progression and MAPK activation. However, how its biological properties intersect with cellular metabolism in hepatocellular carcinoma (HCC) development remains poorly unexplained. Here, high GTPBP4 expression is found to be significantly associated with worse clinical outcomes in patients with HCC. Moreover, GTPBP4 upregulation is paralleled by DNA promoter hypomethylation and regulated by DNMT3A, a DNA methyltransferase. Additionally, both gain- and loss-of-function studies demonstrate that GTPBP4 promotes HCC growth and metastasis in vitro and in vivo. Mechanically, GTPBP4 can induce dimeric pyruvate kinase M2 (PKM2) formation through protein sumoylation modification to promote aerobic glycolysis in HCC. Notably, active GTPBP4 facilitates SUMO1 protein activation by UBA2, and acts as a linker bridging activated SUMO1 protein and PKM2 protein to induce PKM2 sumoylation. Furthermore, SUMO-modified PKM2 relocates from the cytoplasm to the nucleus may also could contribute to HCC progression through activating epithelial-mesenchymal transition (EMT) and STAT3 signaling pathway. Shikonin, a PKM2-specific inhibitor, can attenuate PKM2 dependent HCC glycolytic reprogramming, growth and metastasis promoted by GTPBP4, which offers a promising therapeutic candidate for HCC patients. Our findings indicate that GTPBP4-PKM2 regulatory axis plays a vital role in promoting HCC proliferation as well as metastasis by aerobic glycolysis and offer a promising therapeutic target for HCC patients.

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GTPBP4 promotes HCC progression and metastasis in vitro and in vivo.

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Promoter hypomethylation upregulated GTPBP4 expression.

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GTPBP4 promotes the glycolysis in HCC via inducing dimeric PKM2 formation and sumoylation through UBA2-SUMO1 axis.

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GTPBP4 induces PKM2 nuclear transfer to act as a protein kinase to activate STAT3 and EMT signaling pathway.

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Shikonin induces significant anti-tumor effect in orthotopic mouse models harboring activation of GTPBP4/PKM2 axis.

Tumor associated macrophages-derived exosomes facilitate hepatocellular carcinoma malignance by transferring lncMMPA to tumor cells and activating glycolysis pathway

Background

Tumor-associated macrophages (TAMs), which form a large part of the tumor microenvironment, are normally regulated by metabolic reprogramming. However, the potential mechanisms of the immune-metabolism interaction between hepatocellular carcinoma (HCC) cells and TAMs remain unclear.

Methods

The candidate long non-coding RNAs (lncRNAs) were screened by Smart-seq based scRNA-seq method and then validated by qPCR. Immunostaining analysis was done to examine the levels of markers for TAMs and glycolysis. Exosomes from primary TAMs of human HCC tissues were isolated by centrifugation, and their internalization with lncRNAs was confirmed by immunofluorescence. The underlying mechanism of TAMs-derived exosomal lncRNA to HCC was confirmed by luciferase reporter assay and RNA immunoprecipitation. Metabolism regulation was evaluated through glucose consumption, lactate productions and extracellular acidification rates (ECARs). Mouse xenograft models were used to elucidate the in vivo effect of candidate lncRNAs on tumor growth.

Results

TAMs augment the aerobic glycolysis in HCC cells and their proliferation by the extracellular exosome transmission of a myeloid-derived lncRNA, M2 macrophage polarization associated lncRNA (lncMMPA). Mechanistically, lncMMPA not only could polarize M2 macrophage, but also could act as an microRNA sponge to interact with miR-548 s and increase the mRNA level of ALDH1A3, then further promote glucose metabolism and cell proliferation in HCC. Moreover, lncMMPA increased HCC cell multiplication through interacting with miR-548 s in vivo. Clinically, lncMMPA expression associates with glycolysis in TAMs and reduced survival of HCC patients.

Conclusion

LncMMPA plays an important role in regulating HCC malignancy and metabolic reprogramming of miR-548 s/ALDH1A3 pathway.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02458-3.

The Age-Specific Features and Clinical Significance of NRF2 and MAPK10 Expression in HCC Patients

Background

Nuclear factor (erythroid-derived 2)-like 2 (NRF2) functions decline with age; however, cancer cells can hijack its pathways to ensure survival and aggressiveness. Yet, the role of NRF2 in hepatocellular carcinoma (HCC) is rarely investigated in an age-specific manner. This study investigates the expression of NRF2 and its activator (MAPK10) in different age groups of HCC patients, in addition to the age-specific features of NRF2 and MAPK10 interaction and their clinical significance.

Methods

Tumor and near-tumor tissue samples of 181 HCC patients were used to complete a protein expression analysis of NRF2 and MAPK10. Patients’ survival and clinical data were collected for clinical analysis. Global databases (TCGA, ICGC) were used to collect MAPK10 genetic mutation and mRNA expression data in patients with HCC, colorectal, stomach, and pancreatic cancers.

Results

Our findings revealed an increase in NRF2 protein expression but only in younger HCC patients, along with a decline in MAPK10 ability to activate NRF2 in older patients. We also found an increased MAPK10 genetic mutation rate and decreased mRNA expression in older patients. Low MAPK10 and NRF2 expression levels were associated with shorter survival and poorer prognosis due to positive correlation with microvascular invasion, tumor thrombus, elevated AFP levels, and larger tumor size.

Conclusion

NRF2 expression and oxidative stress mechanism in HCC patients are influenced by age. This magnifies the need to consider patients’ age in treatment strategies and guidelines and re-evaluates the application of studies’ age-standardized findings in older patients who are usually excluded from relevant research.

Tongxin formula protects H9c2 cardiomyocytes from cobalt chloride-induced hypoxic injury via inhibition of apoptosis

In this study, the effect of the Tongxin formula (TXF) on the apoptosis of H9c2 cardiomyocytes induced by cobalt chloride (CoCl₂) was investigated, and the potential mechanism was explored. A hypoxic injury model of H9c2 cardiomyocytes was established using CoCl₂. The cell viability was measured using a Cell Counting Kit-8 assay. The lactate dehydrogenase (LDH) release and caspase-3 activity were measured using spectrophotometry. The apoptosis was measured via Annexin V-FITC/PI staining and flow cytometry. The changes in the mitochondrial membrane potential were examined using immunofluorescence microscopy following the loading of JC-1 probes. The expressions of apoptosis-related proteins and key proteins in the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) pathway were examined via immunoblotting. The different TXF concentrations studied significantly improved the percentage of viability of cardiomyocytes with hypoxic injury, and the LDH release, apoptotic rate, caspase-3 activity, and levels of cleaved caspase-3 protein were reduced in the injured cells. Additionally, the TXF group had increased mitochondrial membrane potential, upregulated expression of Bcl-2 and p-Akt proteins, and significantly reduced expression of cleaved caspase-3 protein in the cells with hypoxic injury. Moreover, in the TXF group, the treatment significantly reduced the BAX protein expression, but the difference was not statistically significant compared with the CoCl2 group. In this study, TXF regulated the expression of apoptosis-related proteins, inhibited apoptosis, increased the mitochondrial membrane potential, and alleviated damage to the mitochondrial membrane, thereby protecting the cardiomyocytes from hypoxic injury. The underlying mechanism could be related to activation of the PI3K/Akt signaling pathway and upregulation of the Bcl-2 protein.

Development and Validation of a Metabolic Gene-Based Prognostic Signature for Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is a malignant tumor with great variation in prognosis among individuals. Changes in metabolism influence disease progression and clinical outcomes. The objective of this study was to determine the overall survival (OS) risk of HCC patients from a metabolic perspective.

Patients and Methods

The model was constructed using the least absolute shrinkage and selection operator (LASSO) COX regression based on The Cancer Genome Atlas (TCGA, n=342) dataset. The International Cancer Genome Consortium (ICGC, n=232), GSE14520 (n=242) datasets, and a clinical cohort (n=64) were then used to assess the prognostic value of the signature.

Results

A 10 metabolic gene-based signature was constructed and verified as a robust and independent prognostic classifier in public and real-world validation cohorts. Meanwhile, the signature enabled the identification of HCC molecular subtypes, yielding an AUC value of 0.678 [95% CI: 0.592–0.763]. Besides, the signature was associated with metabolic processes like glycolysis, supported by a clear correlation between the risk score and expression of rate-limiting enzymes. Furthermore, high-risk tumor was likely to have a high tumor infiltration status of immunosuppressive cells, as well as elevated expression of some immune checkpoint molecules. For final clinical translation, a nomogram integrating the signature and tumor stage was established, and showed improved predictive accuracy of 3- and 5-year OS and brought more net benefit to patients.

Conclusion

We developed a prognostic signature based on 10 metabolic genes, which has proven to be an independent and reliable prognostic predictor for HCC and reflects the metabolic and immune characteristics of tumors.

Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients

Background

Microvascular invasion (MVI) is a significant hazard factor that influences the recurrence and survival of hepatocellular carcinoma (HCC) patients after undergoing hepatectomy. This study aimed to develop and validate a nomogram that combines hematological and imaging features of HCC patients to preoperatively predict MVI, and investigate the effect of wide resection margin (≥1 cm) on the prognosis of MVI-positive HCC patients.

Methods

A total of 709 HCC patients who underwent hepatectomy at the Liver Cancer Institute of Zhongshan Hospital, Fudan University between June 1, 2015 and December 30, 2016 were included in this study and divided into training (496 patients) and validation cohort (213 patients). Least absolute shrinkage and selection operator (Lasso) regression and multivariable logistic regression were used for variables’ selection and development of the predictive model. The model was presented as a nomogram, and its performance was assessed in terms of discrimination, calibration and clinical usefulness.

Results

Independent prognostic factors such as alkaline phosphatase (ALP, >125 U/L), alpha-fetoprotein (AFP, within 20–400 or >400 ng/mL), protein induced by vitamin K absence-II (PVIKA-II, within 40–400 or >400 mAU/mL), tumor number, diameter, pseudo-capsule, tumor growth pattern and intratumor hemorrhage were incorporated in the nomogram. The model showed good discrimination and calibration, with a concordance index (0.82, 95% CI, 0.782–0.857) in the training cohort and C-index (0.80, 95% CI, 0.772–0.837) in the validation cohort. Decision curve analysis (DCA) also showed that this model is clinically useful. Moreover, HCC patients with wide resection margin had a significantly lower 3-year recurrence rate than those with narrower resection margin (0.5–1 cm).

Conclusions

This study presents an optimal model for preoperative prediction of MVI and shows that wide resection margin for MVI-positive HCC patients has a better prognosis. This model can help surgeons choose the best treatment options for HCC patients before and after the operation.

High RPS3A expression correlates with low tumor immune cell infiltration and unfavorable prognosis in hepatocellular carcinoma patients

Despite the use of immune checkpoint blockade (ICB) therapy for hepatocellular carcinoma (HCC), developing more effective immunotherapy and predicting HCC's response to ICB therapy remain top priorities. Ribosomal protein S3A (RPS3A) is a multifunctional molecule, but its association with tumor immune cell infiltration and prognosis in HCC patients is unknown. Thus, we aimed to investigate the correlation of RPS3A with HCC immune cell infiltration and prognosis to explore novel therapeutic strategies and prognostic biomarkers for this disease. Here, we showed that RPS3A expression levels were higher in HCC cell lines and samples than in normal hepatocytes and adjacent tumor-free tissues, respectively, and patients with high RPS3A expression had worse overall and recurrence-free survival durations than did patients with low expression. Moreover, single-sample gene set enrichment analysis (ssGSEA) and immunohistochemistry demonstrated a strongly negative correlation between RPS3A expression and tumor immune cell infiltration. Meanwhile, RPS3A was revealed to be positively correlated with that of most examined immune checkpoint molecules. GSEA also suggested that high RPS3A expression promoted the biological processes related to tumorigenesis, metastasis, and immunosuppression. Finally, RPS3A-based nomograms were constructed and exhibited better predictive accuracy for HCC prognosis and more net clinical benefits when compared with traditional prognosis-prediction staging systems. In short, these findings suggest that high RPS3A expression correlates with low tumor immune cell infiltration and poor prognosis in HCC patients. Furthermore, RPS3A-based nomograms are robust HCC prognostic predictors. RPS3A therefore may serve as a therapeutic target in and predict the efficacy of ICB therapy for HCC.

High RPS11 level in hepatocellular carcinoma associates with poor prognosis after curative resection

Background

Ribosomal protein S11 (RPS11), a member of ribosomal protein family, is reported to overexpress in diverse malignancies and correlates with tumor recurrence. However, our current knowledge on RPS11 in hepatocellular carcinoma (HCC) remains limited. In this study, we are going to explore the potential prognostic value of RPS11 in HCC patients after curative resection.

Methods

Immunohistochemistry (IHC) was performed to evaluate RPS11 expression on tissue microarrays in training cohort comprising 182 HCC patients and validation cohort enrolling 90 HCC patients in Zhongshan Hospital, Fudan University. Western blot and quantitative reverse transcription PCR (qRT-PCR) were also used to determine the expression level of RPS11 in liver cell lines. Two nomograms, calibration curves and decision curve analysis (DCA) were further performed to assess the performance of RPS11 level in predicting clinical outcomes of HCC patients. Additionally, single-sample gene-set enrichment analysis (ssGSEA) was conducted in TCGA liver cancer database to investigate the potential biological pathways involved in RPS11.

Results

Both increased mRNA and protein levels of RPS11 were observed in most HCC cell lines when compared to the normal hepatocytes, and high tumor RPS11 level was associated with shorter overall survival (OS) and recurrence-free survival (RFS) of HCC patients after curative resection. Univariate and multivariate analysis indicated that RPS11 was an independent prognostic factor in HCC. Two nomograms, calibration and DCA curves were further established and displayed a superior prognostic accuracy of OS and RFS, and showed more clinical benefits than traditional staging systems in HCC. Furthermore, several pathways and molecules related to tumor resistance, survival and recurrence were enriched in high RPS11 expression by ssGSEA.

Conclusions

Tumorous RPS11 acts as a potential prognostic biomarker for HCC patients who received curative resection.

Prospects and challenges of circulating tumor DNA in precision medicine of hepatocellular carcinoma

The growing role of precision medicine in hepatocellular carcinoma (HCC) is expected to ameliorate the poor prognosis and high mortality of this highly malignant disease; however, it is faced with challenges such as the low frequency of tissue biopsy. Hence, attention is turning to the circulating tumor DNA (ctDNA), an important component of liquid biopsy. Obtaining molecular information about cancer from blood provides a good prospect in precision oncology including molecular diagnosis, molecular classification, targeted therapy, personalized decision making, and detection of drug-resistance mutations. However, inherent constraints of HCC and ctDNA (like background chronic liver diseases (CLD) and low concentration of ctDNA) along with some technical issues should be well handled and solved before the potential of ctDNA in precision medicine of HCC can be truly realized. In this review, we will focus on the prospects and challenges of ctDNA in HCC precision medicine.

A robust 6-mRNA signature for prognosis prediction of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is one of the most fatal malignancies worldwide. PDAC prognostic and diagnostic biomarkers are still being explored. The aim of this study is to establish a robust molecular signature that can improve the ability to predict PDAC prognosis. 155 overlapping differentially expressed genes between tumor and non-tumor tissues from three Gene Expression Omnibus (GEO) datasets were explored. A least absolute shrinkage and selection operator method (LASSO) Cox regression model was employed for selecting prognostic genes. We developed a 6-mRNA signature that can distinguish high PDAC risk patients from low risk patients with significant differences in overall survival (OS). We further validated this signature prognostic value in three independent cohorts (GEO batch, P < 0.0001; ICGC, P = 0.0036; Fudan, P = 0.029). Furthermore, we found that our signature remained significant in patients with different histologic grade, TNM stage, locations of tumor entity, age and gender. Multivariate cox regression analysis showed that 6-mRNA signature can be an independent prognostic marker in each of the cohorts. Receiver operating characteristic curve (ROC) analysis also showed that our signature possessed a better predictive role of PDAC prognosis. Moreover, the gene set enrichment analysis (GSEA) analysis showed that several tumorigenesis and metastasis related pathways were indeed associated with higher scores of risk. In conclusion, identifying the 6-mRNA signature could provide a valuable classification method to evaluate clinical prognosis and facilitate personalized treatment for PDAC patients. New therapeutic targets may be developed upon the functional analysis of the classifier genes and their related pathways.

A curcumin derivative, WZ35, suppresses hepatocellular cancer cell growthviadownregulating YAP-mediated autophagy

HCC is a common cancer type in the world. Here, we found WZ35, a novel derivative of curcumin, could notably suppress HCC cell growthviainhibiting YAP controlled autophagy, highlighting the potent anti-tumor activity of WZ35 in liver cancer therapy.

RETRACTED: Modulation of macrophage phenotype through controlled release of interleukin-4 from gelatine coatings on titanium surfaces

Pro-inflammatory phenotype (M1) macrophages initiate angiogenesis, while their prolonged activation can induce chronic inflammation. Anti-inflammatory phenotype (M2) macrophages promote vessel maturation and tissue regeneration. Biomaterials which can promote M2 polarisation after appropriate inflammation should enhance angiogenesis and wound healing. Herein, Interleukin-4 (IL-4), an anti-inflammatory cytokine, was adsorbed onto a titanium surface. Then, a genipin cross-linked gelatine hydrogel was coated onto the surface to delay IL-4 release. The cross-linking degree of the hydrogel was modulated by the different amount of genipin to control release of IL-4. When 0.7 wt% (weight %) genipin was used as a cross-linker, the sample (GG07-I) released less IL-4 within the first several days, followed by a sustained release time to 14 d. Meanwhile, the release rate of IL-4 in GG07-I reached a peak between 3 d and 7 d. In culture with macrophages in vitro, GG07-I and GG07 exhibited good cytocompatibility. The phenotypical switch of macrophages stimulated by the samples was determined by FACS, ELISA and PCR. Macrophages cultured with GG07-I, GG07 and PT were firstly activated to the M1 phenotype by interferon-gamma (IFN-γ). Then, due to the release of IL-4 in 5 to 7 d, GG07-I enhanced CD206, increased the secretion and gene expression of M2 marker, such as interleukin-10 (IL-10), arginase-1 (ARG-1) and platelet derived growth factor-BB (PDGF- BB). GG07-I prompted the switch from M1 to M2 phenotype. Those appropriate secretion of cytokines would benefit both vascularisation and osseointegration. Thus, the biomaterial directing inflammatory reaction has good prospects for clinical treatments.

Metabolic changes in methomyl poisoned rats treated by vitamin E

In this study, we developed a serum and urine metabolomic method based on gas chromatography-mass spectrometry (GC-MS) combination with biomedical results to evaluate the effect of vitamin E treatment on methomyl poisoning rats. The rats were divided into three groups: the control group, methomyl poisoning group, and vitamin E treatment group. Partial least squares discriminate analysis (PLS-DA) showed that methomyl poisoning induced metabolic perturbations. Compared to the control group, based on the urinary metabolomics data, the level of ribitol, l-proline, xylitol, hydrocinnamic acid, 11-cis-octadecenoic acid, octadecanoic acid, and hexadecanoic acid of methomyl poisoning group increased, while the level of 2,3,4-trihydroxybutyric acid, ethanimidic acid, pantothenic acid, and retinoic acid decreased. Vitamin E pretreatment effectively normalized the levels of metabolites in rat urine in vitamin E treatment group. There was no significant difference in rat plasma metabolomic data after acute methomyl poisoning. The results indicate that metabolomic method based on GC-MS may be useful to elucidate the vitamin E treatment for methomyl poisoning.

Preliminary Study on HA Coating Percutaneously Implanted in Bone

A comparative investigation on the possibility of hydroxyapatite (HA) coating and pure Ti column to form biological sealing with skin tissue was completed in this study. HA coating and pure Ti column were percutaneously implanted in the tibia of rabbits. Compared with titanium (Ti) implant, HA coating forms epithelial sealing with skin tissue at 6 weeks postoperatively, while the Ti implant may loosen from the implanted site and be lost. The Ti column loosing rate at this time was 50%. However, once the Ti implant becomes fixed with the bone tissue, it can form epithelial sealing with skin tissue just like the HA coating, at 8 weeks postoperatively. At 8 weeks postoperatively, the epithelial sealing is not destroyed in spite of the fact that the HA coating is biodegraded. Our results show that the HA coating can become fixed with the bone faster than the Ti, which is beneficial for epithelial sealing formation. The main role of HA coating for epithelial sealing is beneficial for sealing at the initial period after it is implanted.

Identification of genes alternatively spliced in developing maize endosperm

The process of alternative splicing is critical for the regulation of growth and development of plants. Thus far, little is known about the role of alternative splicing in the regulation of maize (Zea mays L.) endosperm development. RNA sequencing (RNA-seq) data of endosperms from two maize inbred lines, Mo17 and Ji419, at 15 and 25 days after pollination (DAP), respectively, were used to identify genes that were alternatively spliced during endosperm development. Intron retention (IR) in GRMZM2G005887 was further validated using PCR and re-sequencing technologies. In total, 49,000 alternatively spliced events and ca. 20,000 alternatively spliced genes were identified in the two maize inbred lines. Of these, 30 genes involved in amino acid biosynthesis and starch biosynthesis were identified, with IR occurring only in a specific sample, and were significantly co-expressed with ten well-known genes related to maize endosperm development. Moreover, IR in GRMZM2G005887, which encodes a cysteine synthase, was confirmed to occur only in the endosperm of Mo17 at 15 DAP, resulting in the retention of a 121-bp fragment in its 5' untranslated region. Two cis-acting regulatory elements, CAAT-box and TATA-box were observed in the retained fragment in Mo17 at 15 DAP; this could regulate the expression of this gene and influence endosperm development. The results suggest that the 30 genes with IR identified herein might be associated with maize endosperm development, and are likely to play important roles in the developing maize endosperm.

Toll-like receptor 2 costimulation potentiates the antitumor efficacy of CAR T Cells

Chimeric antigen receptor (CAR) T-cell immunotherapies have shown unprecedented success in treating leukemia but limited clinical efficacy in solid tumors. Here, we generated 1928zT2 and m28zT2, targeting CD19 and mesothelin, respectively, by introducing the Toll/interleukin-1 receptor domain of Toll-like receptor 2 (TLR2) to 1928z and m28z. T cells expressing 1928zT2 or m28zT2 showed improved expansion, persistency and effector function against CD19⁺ leukemia or mesothelin⁺ solid tumors respectively in vitro and in vivo. In a patient with relapsed B-cell acute lymphoblastic leukemia, a single dose of 5 × 10⁴/kg 1928zT2 T cells resulted in robust expansion and leukemia eradication and led to complete remission. Hence, our results demonstrate that TLR2 signaling can contribute to the efficacy of CAR T cells. Further clinical trials are warranted to establish the safety and efficacy of this approach.

Differential increments of basal glucagon-like-1 peptide concentration among SLC47A1 rs2289669 genotypes were associated with inter-individual variability in glycaemic response to metformin in Chinese people with newly diagnosed Type 2 diabetes

AIM

To elucidate the effects of rs2289669, an intron variant of the SLC47A1 gene, on glucose response to metformin in Chinese people with newly diagnosed Type 2 diabetes.

METHODS

Rs2289669 was genotyped, using Sequenom, in 291 participants receiving 48 weeks of metformin monotherapy. The changes in HbA_1c were compared among rs2289669 genotypes, and associations with rs2289669 were evaluated using linear regression analysis.

RESULTS

We found that, compared with participants with a homozygous G allele, those carrying the minor A allele had significantly greater HbA_1c reduction and greater increases in basal glucagon-like peptide-1 concentration. Regression analysis showed that there was a significant association between rs2289669 and the glucose response to metformin after adjusting for confounding factors, except for changes in basal glucagon-like peptide-1, for which an association was not observed.

CONCLUSIONS

Our findings suggest that rs2289669 might help predict the glycaemic response to metformin in Chinese people newly diagnosed with Type 2 diabetes, and that differential increases in basal glucagon-like peptide-1 concentration among rs2289669 genotypes might be associated with inter-individual response to metformin.