Downregulation of GPX8 in hepatocellular carcinoma: impact on tumor stemness and migration.

PURPOSE: GPX8, which is found in the endoplasmic reticulum lumen, is a member of the Glutathione Peroxidases (GPXs) family. Its role in hepatocellular carcinoma (HCC) is unknown. METHODS: Immunohistochemical staining was used to detect the protein levels of GPX8 in HCC tissue microarrays. A short hairpin RNA lentivirus was used to knock down GPX8, and the main signaling pathways were investigated using transcriptome sequencing and a phosphorylated kinase array. The sphere formation assays, cloning-formation assays and cell migration assays were used to evaluate the stemness and migration ability of HCC cells. Identifying the GPX8-interacting proteins was accomplished through immunoprecipitation and protein mass spectrometry. RESULTS: The GPX8 protein levels were downregulated in HCC patients. Low expression of GPX8 protein was related to early recurrence and poor prognosis in HCC patients. GPX8 knockdown could enhance the stemness and migration ability of HCC cells. Consistently, Based on transcriptome analysis, multiple signaling pathways that include the PI3K-AKT and signaling pathways that regulate the pluripotency of stem cells, were activated after GPX8 knockdown. The downregulation of GPX8 could increase the expression of the tumor stemness markers KLF4, OCT4, and CD133. The in vivo downregulation of GPX8 could also promote the subcutaneous tumor-forming and migration ability of HCC cells. MK-2206, which is a small-molecule inhibitor of AKT, could reverse the tumor-promoting effects both in vivo and in vitro. We discovered that GPX8 and the 71-kDa heat shock cognate protein (Hsc70) have a direct interaction. The phosphorylation of AKT encouraged the translocation of Hsc70 into the nucleus and the expression of the PI3K p110 subunit, thereby increasing the downregulation of GPX8. CONCLUSION: The findings from this study demonstrate the anticancer activity of GPX8 in HCC by inactivating the Hsc70/AKT pathway. The results suggest a possible therapeutic target for HCC.

Cancer-associated fibroblasts contributed to hepatocellular carcinoma recurrence and metastasis via CD36-mediated fatty-acid metabolic reprogramming.

Cancer-associated fibroblasts (CAFs) are the main components in the tumor microenvironment. Tumors activate fibroblasts from quiescent state into activated state by secreting cytokines, and activated CAFs may in turn promote tumor progression and metastasis. Therefore, studies targeting CAFs could enrich the therapeutic options for tumor treatment. In this study, we demonstrate that the content of lipid droplets and the expression of autophagosomes were higher in CAFs than in peri-tumor fibroblasts (PTFs), which was inhibited by 5-(tetradecyloxy)-2-furoic acid(TOFA). The expression of CD36 in CAFs was higher than that in PTFs at both mRNA and protein levels. Inhibition of CD36 activity using either the CD36 inhibitor SSO or siRNA had a significant negative impact on the proliferation and migration abilities of CAFs, which was associated with reduced levels of relevant activated genes (α-SMA, FAP, Vimentin) and cytokines (IL-6, TGF-ß and VEGF-α). SSO also inhibited HCC growth and tumorigenesis in nude mice orthotopically implanted with CAFs and HCC cells. Our data further show that CD36+CAFs affected the expression of PD-1 in CTLs leading to CTL exhaustion, and that patients with high CD36 expression in CAFs were correlated with shorter overall survival (OS). Together, our data demonstrate that CAFs were active in lipid metabolism with increased lipid content and lipophagy activity. CD36 may play a key role in the regulation of the biological behaviors of CAFs, which may influence the proliferation and migration of tumor cells by reprograming the lipid metabolism in tumor cells. Thus, CD36 could be an effective therapeutic target for the treatment of HCC.

Multiomics analysis reveals metabolic subtypes and identifies diacylglycerol kinase α (DGKA) as a potential therapeutic target for intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) is a highly heterogeneous and lethal hepatobiliary tumor with few therapeutic strategies. The metabolic reprogramming of tumor cells plays an essential role in the development of tumors, while the metabolic molecular classification of iCCA is largely unknown. Here, we performed an integrated multiomics analysis and metabolic classification to depict differences in metabolic characteristics of iCCA patients, hoping to provide a novel perspective to understand and treat iCCA. METHODS: We performed integrated multiomics analysis in 116 iCCA samples, including whole-exome sequencing, bulk RNA-sequencing and proteome analysis. Based on the non-negative matrix factorization method and the protein abundance of metabolic genes in human genome-scale metabolic models, the metabolic subtype of iCCA was determined. Survival and prognostic gene analyses were used to compare overall survival (OS) differences between metabolic subtypes. Cell proliferation analysis, 5-ethynyl-2'-deoxyuridine (EdU) assay, colony formation assay, RNA-sequencing and Western blotting were performed to investigate the molecular mechanisms of diacylglycerol kinase α (DGKA) in iCCA cells. RESULTS: Three metabolic subtypes (S1-S3) with subtype-specific biomarkers of iCCA were identified. These metabolic subtypes presented with distinct prognoses, metabolic features, immune microenvironments, and genetic alterations. The S2 subtype with the worst survival showed the activation of some special metabolic processes, immune-suppressed microenvironment and Kirsten rat sarcoma viral oncogene homolog (KRAS)/AT-rich interactive domain 1A (ARID1A) mutations. Among the S2 subtype-specific upregulated proteins, DGKA was further identified as a potential drug target for iCCA, which promoted cell proliferation by enhancing phosphatidic acid (PA) metabolism and activating mitogen-activated protein kinase (MAPK) signaling. CONCLUSION: Via multiomics analyses, we identified three metabolic subtypes of iCCA, revealing that the S2 subtype exhibited the poorest survival outcomes. We further identified DGKA as a potential target for the S2 subtype.

Single-cell and spatial architecture of primary liver cancer.

Primary liver cancer (PLC) poses a leading threat to human health, and its treatment options are limited. Meanwhile, the investigation of homogeneity and heterogeneity among PLCs remains challenging. Here, using single-cell RNA sequencing, spatial transcriptomic and bulk multi-omics, we elaborated a molecular architecture of 3 PLC types, namely hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC) and combined hepatocellular-cholangiocarcinoma (CHC). Taking a high-resolution perspective, our observations revealed that CHC cells exhibit internally discordant phenotypes, whereas ICC and HCC exhibit distinct tumor-specific features. Specifically, ICC was found to be the primary source of cancer-associated fibroblasts, while HCC exhibited disrupted metabolism and greater individual heterogeneity of T cells. We further revealed a diversity of intermediate-state cells residing in the tumor-peritumor junctional zone, including a congregation of CPE+ intermediate-state endothelial cells (ECs), which harbored the molecular characteristics of tumor-associated ECs and normal ECs. This architecture offers insights into molecular characteristics of PLC microenvironment, and hints that the tumor-peritumor junctional zone could serve as a targeted region for precise therapeutical strategies.

Efficacy of nonpharmacological interventions targeting social function in children and adults with autism spectrum disorder: A systematic review and meta-analysis.

BACKGROUND AND AIMS: This paper aimed to evaluate the use of nonpharmacological interventions for the management of autism spectrum disorder (ASD). The effects of acupuncture and behavioural therapy, two nonpharmalogical interventions, on social function in ASD patients are still controversial. This meta-analysis investigated the impact of these two treatments and compared their effects. METHODS: Seven electronic databases were systematically searched to identify randomized controlled trials (RCTs) on the use of acupuncture or behavioural therapy for ASD. A meta-analysis was carried out using Review Manager 5.4 software. Continuous data are reported as mean differences (MDs) or standardized mean differences (SMDs) with 95% confidence intervals (CIs). An assessment of methodological quality using the Cochrane risk-of-bias (ROB) tool for trials was carried out. The Grading of Recommendation Assessment, Development, and Evaluation (GRADE) was applied to evaluate the quality (certainty) of evidence for results regarding social function indicators. RESULTS: Thirty RCTs on acupuncture and 36 on behavioural therapy were included. Compared with the control condition, body acupuncture (SMD: 0.76, 95% CI: [0.52, 1.01]; low certainty), modern acupuncture technology (SMD: 0.84, 95% CI: [0.32, 1.35]; low certainty), cognitive behavioural therapy (SMD: 0.42, 95% CI: [0.26, 0.58]; high certainty), the Denver model (SMD: 0.61, 95% CI: [0.23, 0.99]; moderate certainty) and social skills training (SMD: 0.56, 95% CI: [0.41, 0.71]; moderate certainty) improved social functioning. CONCLUSION: Behavioural therapies (such as CBT, the Denver model, social skills training), improved the social functioning of patients with ASD in the short and long term, as supported by high- and moderate-quality evidence. Acupuncture (including scalp acupuncture, body acupuncture and use of modern acupuncture technology) also improved social functioning, as supported by low- and very low-quality evidence. More high-quality evidence is needed to confirm the effect of acupoint catgut embedding and Early Intensive Behavioural Intervention (EIBI).

Methyltransferase like 3 inhibition limits intrahepatic cholangiocarcinoma metabolic reprogramming and potentiates the efficacy of chemotherapy.

N6-methyladenosine (m6A) RNA methylation and its associated methyltransferase like 3 (METTL3) are involved in the development and maintenance of various tumors. The present study aimed to evaluate the cross-talk of METTL3 with glucose metabolism and reveal a novel mechanism for intrahepatic cholangiocarcinoma (ICC) progression. Real-time quantitative PCR, western blotting, and immunohistochemistry analyses suggested that METTL3 was highly expressed in ICC, which was correlated with poor patient prognosis. Immunoprecipitation sequencing of m6A-RNA showed that METTL3 upregulated m6A modification of NFAT5, which recruited IGF2BP1 for NFAT5 mRNA stabilization. Elevated expression of NFAT5 increased the expression of the gluconeogenesis-related genes GLUT1 and PGK1, resulting in enhanced aerobic glycolysis, proliferation, and tumor metastasis of ICC. Moreover, higher METTL3 expression was observed in tumor tissues of ICC patients with activated ICC glucose metabolism. Importantly, STM2457, a highly potent METTL3 inhibitor, which inhibited METTL3 activity and acted synergistically with gemcitabine, suggests that reprogramming RNA epigenetic modifications may serve as a potential therapeutic strategy. Overall, our findings highlighted the role of METTL3-mediated m6A modification of NFAT5 in activating glycolytic reprogramming in ICC and proposed that the METTL3/NFAT5 axis was a clinical target for the management of ICC chemoresistance by targeting cancer glycolysis.

Development of a deep pathomics score for predicting hepatocellular carcinoma recurrence after liver transplantation.

BACKGROUND AND PURPOSE: Tumor recurrence after liver transplantation (LT) impedes the curative chance for hepatocellular carcinoma (HCC) patients. This study aimed to develop a deep pathomics score (DPS) for predicting tumor recurrence after liver transplantation using deep learning. PATIENTS AND METHODS: Two datasets of 380 HCC patients who underwent LT were enrolled. Residual convolutional neural networks were used to identify six histological structures of HCC. The individual risk score of each structure and DPS were derived by a modified DeepSurv network. Cox regression analysis and Concordance index were used to evaluate the prognostic significance. The cellular exploration of prognostic immune biomarkers was performed by quantitative and spatial proximity analysis according to three panels of 7-color immunofluorescence. RESULTS: The overall classification accuracy of HCC tissue was 97%. At the structural level, immune cells were the most significant tissue category for predicting post-LT recurrence (HR 1.907, 95% CI 1.490-2.440). The C-indices of DPS achieved 0.827 and 0.794 in the training and validation cohorts, respectively. Multivariate analysis for recurrence-free survival (RFS) showed that DPS (HR 4.795, 95% CI 3.017-7.619) was an independent risk factor. Patients in the high-risk subgroup had a shorter RFS, larger tumor diameter and a lower proportion of clear tumor borders. At the cellular level, a higher infiltration of intratumoral NK cells was negatively correlated with recurrence risk. CONCLUSIONS: This study established an effective DPS. Immune cells were the most significant histological structure related to HCC recurrence. DPS performed well in post-LT recurrence prediction and the identification of clinicopathological features.

CD36+ cancer-associated fibroblasts provide immunosuppressive microenvironment for hepatocellular carcinoma via secretion of macrophage migration inhibitory factor.

Hepatocellular carcinoma (HCC) is an immunotherapy-resistant malignancy characterized by high cellular heterogeneity. The diversity of cell types and the interplay between tumor and non-tumor cells remain to be clarified. Single cell RNA sequencing of human and mouse HCC tumors revealed heterogeneity of cancer-associated fibroblast (CAF). Cross-species analysis determined the prominent CD36+ CAFs exhibited high-level lipid metabolism and expression of macrophage migration inhibitory factor (MIF). Lineage-tracing assays showed CD36+CAFs were derived from hepatic stellate cells. Furthermore, CD36 mediated oxidized LDL uptake-dependent MIF expression via lipid peroxidation/p38/CEBPs axis in CD36+ CAFs, which recruited CD33+myeloid-derived suppressor cells (MDSCs) in MIF- and CD74-dependent manner. Co-implantation of CD36+ CAFs with HCC cells promotes HCC progression in vivo. Finally, CD36 inhibitor synergizes with anti-PD-1 immunotherapy by restoring antitumor T-cell responses in HCC. Our work underscores the importance of elucidating the function of specific CAF subset in understanding the interplay between the tumor microenvironment and immune system.

A RIPK3-independent role of MLKL in suppressing parthanatos promotes immune evasion in hepatocellular carcinoma.

Mixed lineage kinase domain-like (MLKL) is widely accepted as an executioner of necroptosis, in which MLKL mediates necroptotic signaling and triggers cell death in a receptor-interacting protein kinase 3 (RIPK3)-dependent manner. Recently, it is increasingly noted that RIPK3 is intrinsically silenced in hepatocytes, raising a question about the role of MLKL in hepatocellular carcinoma (HCC). This study reports a previously unrecognized role of MLKL in regulating parthanatos, a programmed cell death distinct from necroptosis. In HCC cells with intrinsic RIPK3 deficiency, knockout of MLKL impedes the orthotopic tumor growth, activates the anti-tumor immune response and enhances the therapeutic effect of immune checkpoint blockade in syngeneic HCC tumor models. Mechanistically, MLKL is required for maintaining the endoplasmic reticulum (ER)-mitochondrial Mg2+ dynamics in HCC cells. MLKL deficiency restricts ER Mg2+ release and mitochondrial Mg2+ uptake, leading to ER dysfunction and mitochondrial oxidative stress, which together confer increased susceptibility to metabolic stress-induced parthanatos. Importantly, pharmacological inhibition of poly(ADP-ribose) polymerase to block parthanatos restores the tumor growth and immune evasion in MLKL-knockout HCC tumors. Together, our data demonstrate a new RIPK3-independent role of MLKL in regulating parthanatos and highlight the role of MLKL in facilitating immune evasion in HCC.

Laser-Induced Combinatorial Chemotherapeutic, Chemodynamic, and Photothermal Therapy for Hepatocellular Carcinoma Based on Oxaliplatin-Loaded Metal-Organic Frameworks.

The activation of nanoparticles (NPs) in the tumor microenvironment exerts synergistic therapeutic effects with chemotherapy against multiple cancers. In this study, an NP system prepared using biocompatible MIL-100 NPs was studied as an effective vehicle to deliver oxaliplatin for hepatocellular carcinoma treatment. The NPs were coated with polydopamine (PDA) and NH2-PEGTK-COOH and then loaded with oxaliplatin to create the multi-functional NP Oxa@MIL-PDA-PEGTK. Oxa@MIL-PDA-PEGTK is activated in the tumor microenvironment, causing the generation of cytotoxic reactive oxygen species (ROS) via the Fenton reaction and the release of the loaded oxaliplatin. In addition, under near-infrared (NIR) irradiation, Oxa@MIL-PDA-PEGTK can generate hyperthermia at tumor sites. Moreover, owing to the light-induced activation of the Oxa@MIL-PDA-PEGTK NPs, higher drug delivery efficiency, more precise targeted activation, and reduced off-target toxicity were observed in in vitro and in vivo experiments. Taken together, owing to its improved drug delivery efficiency and multi-functional activities, including the ability for targeted chemotherapy coupled with photothermal and chemodynamic therapy, Oxa@MIL-PDA-PEGTK may serve as a new approach for treating hepatocellular carcinoma.

Monocarboxylate transporter 4 inhibition potentiates hepatocellular carcinoma immunotherapy through enhancing T cell infiltration and immune attack.

BACKGROUND AND AIMS: Monocarboxylate transporter (MCT) 4 is a high-affinity lactate transporter that is primarily involved in the maintenance of intracellular pH homeostasis and highly expressed in different tumors. However, the role of MCT4 in modulating immune responses against HCC remains unknown. APPROACH AND RESULTS: In this study, we demonstrated that MCT4 was overexpressed in HCC, which was associated with poor prognosis in patients. Genetic or pharmacological inhibition of MCT4 using VB124 (a highly potent MCT4 inhibitor) suppressed HCC tumor growth in immunocompetent mice model by enhancing CD8 + T cell infiltration and cytotoxicity. Such improved immunotherapy response by MCT4 targeting was due to combined consequences characterized by the alleviated acidification of tumor microenvironment and elevated the chemokine (C-X-C motif) ligand (CXCL) 9/CXCL10 secretion induced by reactive oxygen species/NF-κB signaling pathway. Combining MCT4 inhibition improved the therapeutic benefit of anti-programmed cell death 1 immunotherapy in HCC and prolonged mice survival. Moreover, higher MCT4 expression was observed in tumor tissues from nonresponder patients with HCC receiving neoadjuvant therapy with toripalimab. CONCLUSIONS: Our results revealed that lactate exportation by MCT4 has a tumor-intrinsic function in generating an immunosuppressive HCC environment and demonstrated the proof of the concept of targeting MCT4 in tailoring HCC immunotherapeutic approaches.

Calibration and Uncertainty in Neural Time-to-Event Modeling.

Models for predicting the time of a future event are crucial for risk assessment, across a diverse range of applications. Existing time-to-event (survival) models have focused primarily on preserving pairwise ordering of estimated event times (i.e., relative risk). We propose neural time-to-event models that account for calibration and uncertainty while predicting accurate absolute event times. Specifically, an adversarial nonparametric model is introduced for estimating matched time-to-event distributions for probabilistically concentrated and accurate predictions. We also consider replacing the discriminator of the adversarial nonparametric model with a survival-function matching estimator that accounts for model calibration. The proposed estimator can be used as a means of estimating and comparing conditional survival distributions while accounting for the predictive uncertainty of probabilistic models. Extensive experiments show that the distribution matching methods outperform existing approaches in terms of both calibration and concentration of time-to-event distributions.

Effectiveness of acupuncture combined with rehabilitation training vs. rehabilitation training alone for post-stroke shoulder pain: A systematic review and meta-analysis of randomized controlled trials.

Background: Post-stroke shoulder pain (PSSP) is characterized by shoulder pain on the hemiplegic side, which can limit physical activity in patients with stroke. Acupuncture combined with rehabilitation training (AR) has been widely used in PSSP, but the evidence of its effectiveness is still unclear. Objective: The study aimed to evaluate the effect and safety of AR vs. rehabilitation training (RT) alone on PSSP. Methods: We searched PubMed, the Cochrane Library, the Chinese Biological Medicine Database (CBM), the Chinese Scientific Journal Database (VIP), China National Knowledge Infrastructure (CNKI), and the WAN FANG database for relevant studies from their inception to February 2022. Only randomized controlled trials (RCTs) comparing the effect of AR with RT alone on PSSP were considered. The primary outcome was shoulder pain. Secondary outcomes included upper limb motor function, activities of daily living (ADL), shoulder range of motion (ROM), and adverse events (AEs). Subgroup analysis and sensitivity analysis were also conducted. Quality assessment was implemented based on Cochrane risk of bias (ROB) criteria, which consist of seven items. When more than four items in a study were judged as low ROB, the overall quality of this study was considered low risk. Results: A total of 40 studies were included in the qualitative analysis, and 35 (87.5%) studies with 2,554 patients were included in the meta-analysis. Of the 40 studies, 14 (35.0%) were of moderate-to-high quality. The meta-analysis results showed that AR is better than RT alone in reducing shoulder pain (MD -1.32, 95% CI -1.58 to -1.07), improving upper limb motor function (MD 6.81, 95% CI 4.95-8.67), ADL (MD 11.17, 95% CI 9.44-12.91), and shoulder ROM (internal rotation: MD 10.48, 95% CI 8.14-12.83; backward extension: MD 7.82, 95% CI 6.00-9.64; anteflexion: MD 12.88, 95% CI 5.47-20.29; external rotation: MD 11.40, 95% CI 6.17-16.64; abduction: MD 16.96, 95% CI 8.61-25.31) without obvious AEs. Conclusion: AR may be better than RT alone for the improvement of shoulder pain, upper limb motor function, ADL, and shoulder ROM, without obvious AEs in patients with PSSP. However, considering the clinical and statistical heterogeneity, our findings need to be interpreted with caution. More rigorous RCTs in this area should be conducted in the future. Systematic review registration: [www.crd.york.ac.uk], identifier [CRD42022326763].

Effectiveness and safety of anti-tau drugs for Alzheimer's disease: Systematic review and meta-analysis.

OBJECTIVE: To assess the cognitive effectiveness and safety of tau-targeting drugs for Alzheimer's disease (AD) METHODS: The MEDLINE, Embase, Cochrane Library, PsycINFO, ClinicalTrials.gov, and WHO International Clinical Trials Registry Platform databases were searched from inception to 22 November 2021. A systematic review and meta-analysis of randomized controlled trials were performed RESULTS: Thirty-four randomized controlled trials comprising 5549 participants, of which fifteen (51.7%) had a low risk of bias, were included. The meta-analysis showed no differences in the cognitive subscale of the AD: Assessment Scale (ADAS-Cog) between anti-tau drugs and placebo (mean difference [MD]: -0.77, 95% CI: -1.64 to 0.10; minimal important difference 3.1-3.8 points, moderate certainty evidence). For ADAS-Cog, the results subgroup analysis suggested a statistical effect of tau posttranslational modifications on drug inhibition (MD: -0.80, 95% CI: -1.43 to -0.17), which was not seen with tau aggregation inhibitors or immunotherapy (interaction p = 0.24). A total of 11.0%, 5.2%, and 4.8% of drugs inhibiting tau aggregation, immunotherapy, and drugs targeting posttranslational modifications, respectively, had a reduced risk of dropouts due to adverse events (AEs). DISCUSSION: Current evidence suggests that anti-tau drugs are unlikely to have an important impact on slowing cognitive impairment. Although the subgroup analysis suggested that inhibition of tau posttranslational modifications is statistically effective and generally safer because of reduced dropouts due to AEs, the analysis has limited credibility. Additional large-scale and well-designed randomized and placebo-controlled trials will be necessary to explore the benefit of a certain type of anti-tau drug for AD.

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

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

Exploring pathological signatures for predicting the recurrence of early-stage hepatocellular carcinoma based on deep learning.

Background: Postoperative recurrence impedes the curability of early-stage hepatocellular carcinoma (E-HCC). We aimed to establish a novel recurrence-related pathological prognosticator with artificial intelligence, and investigate the relationship between pathological features and the local immunological microenvironment. Methods: A total of 576 whole-slide images (WSIs) were collected from 547 patients with E-HCC in the Zhongshan cohort, which was randomly divided into a training cohort and a validation cohort. The external validation cohort comprised 147 Tumor Node Metastasis (TNM) stage I patients from The Cancer Genome Atlas (TCGA) database. Six types of HCC tissues were identified by a weakly supervised convolutional neural network. A recurrence-related histological score (HS) was constructed and validated. The correlation between immune microenvironment and HS was evaluated through extensive immunohistochemical data. Results: The overall classification accuracy of HCC tissues was 94.17%. The C-indexes of HS in the training, validation and TCGA cohorts were 0.804, 0.739 and 0.708, respectively. Multivariate analysis showed that the HS (HR= 4.05, 95% CI: 3.40-4.84) was an independent predictor for recurrence-free survival. Patients in HS high-risk group had elevated preoperative alpha-fetoprotein levels, poorer tumor differentiation and a higher proportion of microvascular invasion. The immunohistochemistry data linked the HS to local immune cell infiltration. HS was positively correlated with the expression level of peritumoral CD14+ cells (p= 0.013), and negatively with the intratumoral CD8+ cells (p< 0.001). Conclusions: The study established a novel histological score that predicted short-term and long-term recurrence for E-HCCs using deep learning, which could facilitate clinical decision making in recurrence prediction and management.

Comprehensive analysis of complement-associated molecular features in hepatocellular carcinoma.

The complement cascade plays a "complementing" role in human immunity. However, the potential roles of complement system in impacting molecular and clinical features of hepatocellular carcinoma (HCC) remain unclear. In this study, eleven public datasets are analyzed to compare the complement status between normal and cancerous samples based on 18 classical complement-associated genes. The complement scores are constructed to quantify complement signatures of individual tumors. HCC patients in the The Cancer Genome Atlas (TCGA) cohort are focused to perform systematical analyses between complement status and immune infiltration, miRNA expression, DNA methylation, clinicopathological features, and drug response. The results show that the complement scores in normal tissues are dramatically higher than those of tumor tissues. Tumor samples in the TCGA cohort are classified into complement score-low and score-high groups. Pathway analysis reveals that tumor-promoting pathways are typically inhibited in complement score-high group. This study also shows that tumor-killing immune cells, such as CD8 + T cells and natural killer cells are abundant and tumor-suppressing miRNAs are upregulated in complement score-high samples. In addition, we identify that complement scores are negatively correlated with certain clinical features, including pathological grade, clinical-stage, and portal vein invasion. Moreover, various molecular features together with complement scores are found to be correlated with response to anti-cancer drugs. This study provides a comprehensive and multidimensional analysis conducive to understanding the role of complement in cancer.

Lead-Free Ultrasonic Phased Array Transducer for Human Heart Imaging.

Substantial advancement has been made in recent years on lead-free piezoelectric materials, but up to date, it is still a challenge to make a true medical imaging ultrasonic array transducer with center frequency <3 MHz. There are two major obstacles: the difficulty of fabricating large enough uniform lead-free piezoelectric materials with high piezoelectric coefficient, and the severe electrical impedance mismatch of an array element to the imaging system due to the relatively low dielectric constant of lead-free materials compared to lead-based piezoelectric materials. We resolved these two issues by employing texture engineering and stacking piezoelectric-layer design, which allowed us to fabricate an 80 element phased array transducer with the center frequency of 2.9 MHz and a bandwidth >80% for human heart imaging. The high-quality lead-free (Ba0.95Ca0.05)(Ti0.94Zr0.06)O3 textured ceramic plate has the size of 23×22×0.8 mm3 with the piezoelectric constant d33 = 570 pC/N. Phantom imaging and internal clinical human heart imaging demonstrated that this lead-free phased array can produce comparable imaging quality to that of a commercial PZT-5H ceramic-based phased array transducer, which demonstrated the practicality of using lead-free materials to replace PZT ceramics in phased array transducers for medical imaging applications.

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

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

Variational Disentanglement for Rare Event Modeling.

Combining the increasing availability and abundance of healthcare data and the current advances in machine learning methods have created renewed opportunities to improve clinical decision support systems. However, in healthcare risk prediction applications, the proportion of cases with the condition (label) of interest is often very low relative to the available sample size. Though very prevalent in healthcare, such imbalanced classification settings are also common and challenging in many other scenarios. So motivated, we propose a variational disentanglement approach to semi-parametrically learn from rare events in heavily imbalanced classification problems. Specifically, we leverage the imposed extreme-distribution behavior on a latent space to extract information from low-prevalence events, and develop a robust prediction arm that joins the merits of the generalized additive model and isotonic neural nets. Results on synthetic studies and diverse real-world datasets, including mortality prediction on a COVID-19 cohort, demonstrate that the proposed approach outperforms existing alternatives.