Risk stratification and predictive modeling of postoperative delirium in chronic subdural hematoma.

Background- Postoperative delirium is a common complication associated with the elderly, causing increased morbidity and prolonged hospital stay. However, its risk factors in chronic subdural hematoma patients have not been well studied. Methods- A total of 202 consecutive patients with chronic subdural hematoma at Peking University Third Hospital between January 2018 and January 2023 were enrolled. Various clinical indicators were analyzed to identify independent risk factors for postoperative delirium using univariate and multivariate regression analyses. Delirium risk prediction models were developed as a nomogram and a Markov chain. Results- Out of the 202 patients (age, 71 (IQR, 18); female-to-male ratio, 1:2.7) studied, 63 (31.2%) experienced postoperative delirium. Univariate analysis identified age (p < 0.001), gender (p = 0.014), restraint belt use (p < 0.001), electrolyte imbalance (p < 0.001), visual analog scale score (p < 0.001), hematoma thickness (p < 0.001), midline shift (p < 0.001), hematoma side (p = 0.013), hematoma location (p = 0.018), and urinal catheterization (p = 0.028) as significant factors. Multivariate regression analysis confirmed the significance of restraint belt use (B = 7.657, p < 0.001), electrolyte imbalance (B = -3.993, p = 0.001), visual analog scale score (B = 2.331, p = 0.016), and midline shift (B = 0.335, p = 0.007). Hematoma thickness and age had no significant impact. Conclusion- Increased midline shift and visual analog scale scores, alongside restraint belt use and electrolyte imbalance elevate delirium risk in chronic subdural hematoma surgery. Our prediction models may offer reference value in this context.

Characteristic fingerprint spectrum of α-synuclein mutants on terahertz time-domain spectroscopy.

α-Synuclein, a presynaptic neuronal protein encoded by the SNCA gene, is involved in the pathogenesis of Parkinson's disease. Point mutations and multiplications of α-synuclein (A30P and A53T) are correlated with early-onset Parkinson's disease characterized by rapid progression and poor prognosis. Currently, the clinical identification of SNCA variants, especially disease-related A30P and A53T mutants, remains challenging and also time consuming. This study aimed to develop a novel label-free detection method for distinguishing the SNCA mutants using transmission terahertz (THz) time-domain spectroscopy. The protein was spin-coated onto the quartz to form a thin film, which was measured using THz time-domain spectroscopy. The spectral characteristics of THz broadband pulse waves of α-synuclein protein variants (SNCA wild type, A30P, and A53T) at different frequencies were analyzed via Fourier transform. The amplitude A intensity (AWT, AA30P, and AA53T) and peak occurrence time in THz time-domain spectroscopy sensitively distinguished the three protein variants. The phase φ difference in THz frequency domain followed the trend of φWT > φA30P > φA53T. There was a significant difference in THz frequency amplitude A' corresponding to the frequency ranging from 0.4 to 0.66 THz (A'A53T > A'A30P > A'WT). At a frequency of 0.4-0.6 THz, the transmission T of THz waves distinguished three variants (TA53T > TA30P > TWT), whereas there was no difference in the transmission T at 0.66 THz. The SNCA wild-type protein and two mutant variants (A30P and A53T) had distinct characteristic fingerprint spectra on THz time-domain spectroscopy. This novel label-free detection method has great potential for the differential diagnosis of Parkinson's disease subtypes.

Single-cell transcriptomic Atlas of aging macaque ocular outflow tissues.

The progressive degradation in the trabecular meshwork (TM) is related to age-related ocular diseases like primary open-angle glaucoma. However, the molecular basis and biological significance of the aging process in TM have not been fully elucidated. Here, we established a dynamic single-cell transcriptomic landscape of aged macaque TM, wherein we classified the outflow tissue into 12 cell subtypes and identified mitochondrial dysfunction as a prominent feature of TM aging. Furthermore, we divided TM cells into 13 clusters and performed an in- depth analysis on cluster 0, which had the highest aging score and the most significant changes in cell proportions between the two groups. Ultimately, we found that the APOE gene was an important differentially expressed gene in cluster 0 during the aging process, highlighting the close relationship between cell migration and extracellular matrix regulation, and TM function. Our work further demonstrated that silencing the APOE gene could increase migration and reduce apoptosis by releasing the inhibition on the PI3K-AKT pathway and downregulating the expression of extracellular matrix components, thereby increasing the aqueous outflow rate and maintaining intraocular pressure within the normal range. Our work provides valuable insights for future clinical diagnosis and treatment of glaucoma.

From glioma gloom to immune bloom: unveiling novel immunotherapeutic paradigms-a review.

In tumor therapeutics, the transition from conventional cytotoxic drugs to targeted molecular therapies, such as those targeting receptor tyrosine kinases, has been pivotal. Despite this progress, the clinical outcomes have remained modest, with glioblastoma patients' median survival stagnating at less than 15 months. This underscores the urgent need for more specialized treatment strategies. Our review delves into the progression toward immunomodulation in glioma treatment. We dissect critical discoveries in immunotherapy, such as spotlighting the instrumental role of tumor-associated macrophages, which account for approximately half of the immune cells in the glioma microenvironment, and myeloid-derived suppressor cells. The complex interplay between tumor cells and the immune microenvironment has been explored, revealing novel therapeutic targets. The uniqueness of our review is its exhaustive approach, synthesizing current research to elucidate the intricate roles of various molecules and receptors within the glioma microenvironment. This comprehensive synthesis not only maps the current landscape but also provides a blueprint for refining immunotherapy for glioma, signifying a paradigm shift toward leveraging immune mechanisms for improved patient prognosis.

Prognostic and predictive value of super-enhancer-derived signatures for survival and lung metastasis in osteosarcoma.

BACKGROUND: Risk stratification and personalized care are crucial in managing osteosarcoma due to its complexity and heterogeneity. However, current prognostic prediction using clinical variables has limited accuracy. Thus, this study aimed to explore potential molecular biomarkers to improve prognostic assessment. METHODS: High-throughput inhibitor screening of 150 compounds with broad targeting properties was performed and indicated a direction towards super-enhancers (SEs). Bulk RNA-seq, scRNA-seq, and immunohistochemistry (IHC) were used to investigate SE-associated gene expression profiles in osteosarcoma cells and patient tissue specimens. Data of 212 osteosarcoma patients who received standard treatment were collected and randomized into training and validation groups for retrospective analysis. Prognostic signatures and nomograms for overall survival (OS) and lung metastasis-free survival (LMFS) were developed using Cox regression analyses. The discriminatory power, calibration, and clinical value of nomograms were evaluated. RESULTS: High-throughput inhibitor screening showed that SEs significantly contribute to the oncogenic transcriptional output in osteosarcoma. Based on this finding, focus was given to 10 SE-associated genes with distinct characteristics and potential oncogenic function. With multi-omics approaches, the hyperexpression of these genes was observed in tumor cell subclusters of patient specimens, which were consistently correlated with poor outcomes and rapid metastasis, and the majority of these identified SE-associated genes were confirmed as independent risk factors for poor outcomes. Two molecular signatures were then developed to predict survival and occurrence of lung metastasis: the SE-derived OS-signature (comprising LACTB, CEP55, SRSF3, TCF7L2, and FOXP1) and the SE-derived LMFS-signature (comprising SRSF3, TCF7L2, FOXP1, and APOLD1). Both signatures significantly improved prognostic accuracy beyond conventional clinical factors. CONCLUSIONS: Oncogenic transcription driven by SEs exhibit strong associations with osteosarcoma outcomes. The SE-derived signatures developed in this study hold promise as prognostic biomarkers for predicting OS and LMFS in patients undergoing standard treatments. Integrative prognostic models that combine conventional clinical factors with these SE-derived signatures demonstrate substantially improved accuracy, and have the potential to facilitate patient counseling and individualized management.

Identification and validation of key biomarkers and potential therapeutic targets for primary open-angle glaucoma.

Primary open-angle glaucoma (POAG) is a prevalent cause of blindness worldwide, resulting in degeneration of retinal ganglion cells and permanent damage to the optic nerve. However, the underlying pathogenetic mechanisms of POAG are currently indistinct, and there has been no effective nonsurgical treatment regimen. The objective of this study is to identify novel biomarkers and potential therapeutic targets for POAG. The mRNA expression microarray datasets GSE27276 and GSE138125, as well as the single-cell high-throughput RNA sequencing (scRNA-seq) dataset GSE148371 were utilized to screen POAG-related differentially expressed genes (DEGs). Functional enrichment analyses, protein-protein interaction (PPI) analysis, and weighted gene co-expression network analysis (WGCNA) of the DEGs were performed. Subsequently, the hub genes were validated at a single-cell level, where trabecular cells were annotated, and the mRNA expression levels of target genes in different cell clusters were analyzed. Immunofluorescence and quantitative real-time PCR (qPCR) were performed for further validation. DEGs analysis identified 43 downregulated and 32 upregulated genes in POAG, which were mainly enriched in immune-related pathways, oxidative stress, and endoplasmic reticulum (ER) stress. PPI networks showed that FN1 and DUSP1 were the central hub nodes, while GPX3 and VAV3 were screened out as hub genes through WGCNA and subsequently validated by qPCR. Finally, FN1, GPX3, and VAV3 were determined to be pivotal core genes via single-cell validation. The relevant biomarkers involved in the pathogenesis of POAG, may serve as potential therapeutic targets. Further studies are necessary to unveil the mechanisms underlying the expression variations of these genes in POAG.

Case Report: Paraganglioma in the sellar region: longitudinal observation and surgical outcome.

Background: Paraganglioma in the sellar region is an extremely rare entity, with a limited number of cases reported in the literature. Due to the paucity of clinical evidence, the diagnosis and treatment of paragangliomas in the sellar region remain challenging. Herein, we reported a case of sellar paraganglioma with parasellar and suprasellar extension. Particularly, the dynamic evolution of this benign tumor within a 7-year longitudinal observation was presented. Additionally, the relevant literature regarding sellar paraganglioma was comprehensively reviewed. Case description: A 70-year-old woman presented with progressive visual deterioration and headache. Brain magnetic resonance imaging demonstrated a mass in the sellar region with parasellar and suprasellar extension. The patient refused surgical treatment. Seven years later, brain magnetic resonance imaging showed the lesion significantly progressed. Neurological examination revealed bilateral tubular contraction of visual fields. Laboratory examinations showed endocrine hormone levels were normal. Surgical decompression was performed via a subfrontal approach, and subtotal resection was achieved. Histopathological examination confirmed a diagnosis of paraganglioma. Postoperatively, she developed hydrocephalus, and ventriculoperitoneal shunting was performed. Eight months later, cranial CT showed no recurrence of the residual tumor, and the hydrocephalus had been relieved. Conclusion: Paraganglioma occurring in the sellar region is rare, and the preoperative differential diagnosis is difficult. Owing to the infiltration to the cavernous sinus and internal carotid, complete surgical resection is usually impracticable. There has been no consensus regarding postoperative adjuvant radiochemotherapy for the tumor residue. In-situ recurrence and metastasis have been reported in the literature, and close follow-up is warranted.

Lactate regulates cell cycle by remodelling the anaphase promoting complex.

Lactate is abundant in rapidly dividing cells owing to the requirement for elevated glucose catabolism to support proliferation1-6. However, it is not known whether accumulated lactate affects the proliferative state. Here we use a systematic approach to determine lactate-dependent regulation of proteins across the human proteome. From these data, we identify a mechanism of cell cycle regulation whereby accumulated lactate remodels the anaphase promoting complex (APC/C). Remodelling of APC/C in this way is caused by direct inhibition of the SUMO protease SENP1 by lactate. We find that accumulated lactate binds and inhibits SENP1 by forming a complex with zinc in the SENP1 active site. SENP1 inhibition by lactate stabilizes SUMOylation of two residues on APC4, which drives UBE2C binding to APC/C. This direct regulation of APC/C by lactate stimulates timed degradation of cell cycle proteins, and efficient mitotic exit in proliferative human cells. This mechanism is initiated upon mitotic entry when lactate abundance reaches its apex. In this way, accumulation of lactate communicates the consequences of a nutrient-replete growth phase to stimulate timed opening of APC/C, cell division and proliferation. Conversely, persistent accumulation of lactate drives aberrant APC/C remodelling and can overcome anti-mitotic pharmacology via mitotic slippage. In sum, we define a biochemical mechanism through which lactate directly regulates protein function to control the cell cycle and proliferation.

Screening of rosmarinic acid from Salvia miltiorrhizae acting on the novel target TRPC1 based on the 'homology modelling-virtual screening-molecular docking-affinity assay-activity evaluation' method.

CONTEXT: Salvia miltiorrhizae Bunge (Lamiaceae) is a traditional Chinese medicine (TCM) for the treatment of 'thoracic obstruction'. Transient receptor potential canonical channel 1 (TRPC1) is a important target for myocardial injury treatment. OBJECTIVE: This work screens the active component acting on TRPC1 from Salvia miltiorrhizae. MATERIALS AND METHODS: TCM Systems Pharmacology Database and Analysis Platform (TCMSP) was used to retrieve Salvia miltiorrhiza compounds for preliminary screening by referring to Lipinski's rule of five. Then, the compound group was comprehensively scored by AutoDock Vina based on TRPC1 protein. Surface plasmon resonance (SPR) was used to determine the affinity of the optimal compound to TRPC1 protein. Western blot assay was carried out to observe the effect of the optimal compound on TRPC1 protein expression in HL-1 cells, and Fura-2/AM detection was carried out to observe the effect of the optimal compound on calcium influx in HEK293 cells. RESULTS: Twenty compounds with relatively good characteristic parameters were determined from 202 compounds of Salvia miltiorrhiza. Rosmarinic acid (RosA) was obtained based on the molecular docking scoring function. RosA had a high binding affinity to TRPC1 protein (KD value = 1.27 µM). RosA (50 µM) could reduce the protein levels (417.1%) of TRPC1 after oxygen-glucose deprivation/reperfusion (OGD/R) in HL-1 cells and it could inhibit TRPC1-mediated Ca2+ influx injury (0.07 ΔRatio340/380) in HEK293 cells. DISCUSSION AND CONCLUSIONS: We obtained the potential active component RosA acting on TRPC1 from Salvia miltiorrhizae, and we speculate that RosA may be a promising clinical candidate for myocardial injury therapy.

Architecture of the outbred brown fat proteome defines regulators of metabolic physiology.

Brown adipose tissue (BAT) regulates metabolic physiology. However, nearly all mechanistic studies of BAT protein function occur in a single inbred mouse strain, which has limited the understanding of generalizable mechanisms of BAT regulation over physiology. Here, we perform deep quantitative proteomics of BAT across a cohort of 163 genetically defined diversity outbred mice, a model that parallels the genetic and phenotypic variation found in humans. We leverage this diversity to define the functional architecture of the outbred BAT proteome, comprising 10,479 proteins. We assign co-operative functions to 2,578 proteins, enabling systematic discovery of regulators of BAT. We also identify 638 proteins that correlate with protection from, or sensitivity to, at least one parameter of metabolic disease. We use these findings to uncover SFXN5, LETMD1, and ATP1A2 as modulators of BAT thermogenesis or adiposity, and provide OPABAT as a resource for understanding the conserved mechanisms of BAT regulation over metabolic physiology.

DMSO-soluble smoking particles up-regulate the vascular endothelin receptors through AMPK-SIRT1 and MAPK pathways.

Smoking is a well-known risk factor for cardiovascular diseases. However, the mechanisms behind how smoking leads to vasospasm are not fully elucidated. Endothelin receptors are involved in the pathogenesis of cardiovascular diseases. This study examined whether cigarette smoke could induce up-regulation of vascular endothelin receptors through AMPK-SIRT1 and MAPK pathways. The results show that DMSO-soluble smoking particles (DSP) up-regulated the protein expressions of endothelin receptors and the contractile responses. Furthermore, the inhibition of MAPK or activation of AMPK-SIRT1 markedly attenuated DSP-enhanced vasoconstriction and the protein expression of endothelin receptors. The in vivo study showed that cigarette smoke increased the blood pressure of the rats and down-regulated p-AMPKα, SIRT1, and up-regulated endothelin receptors, p-ERK1/2, and p-P38 protein expressions. However, treatment with resveratrol attenuated vasoconstriction, endothelin receptor proteins expression, and blood pressure in vivo. In conclusion, this suggests that cigarette smoke up-regulates the vascular endothelin receptors through AMPK-SIRT1 and MAPK pathways.

CTSB is a negative prognostic biomarker and therapeutic target associated with immune cells infiltration and immunosuppression in gliomas.

Previous researches have demonstrated the meaning of CTSB for the progress of several tumors, whereas few clues about its immunological characteristic in gliomas. Here we systematically explored its biologic features and clinical significance for gliomas. 699 glioma cases of TCGA and 325 glioma cases of CGGA were respectively included as training and validating cohorts. R software was used for data analysis and mapping. We found that CTSB was remarkably highly-expressed for HGG, IDH wild type, 1p19q non-codeletion type, MGMT promoter unmethylation type and mesenchymal gliomas. CTSB could specifically and sensitively indicate mesenchymal glioma. Upregulated CTSB was an independent hazard correlated with poor survival. CTSB-related biological processes in gliomas chiefly concentrated on immunoreaction and inflammation response. Then we proved that CTSB positively related to most inflammatory metagenes except IgG, including HCK, LCK, MHC II, STAT1 and IFN. More importantly, the levels of glioma-infiltrating immune cells were positively associated with the expression of CTSB, especially for TAMs, MDSCs and Tregs. In conclusion, CTSB is closely related to the malignant pathological subtypes, worse prognosis, immune cells infiltration and immunosuppression of gliomas, which make it a promising biomarker and potential target in the diagnosis, treatment and prognostic assessment of gliomas.

ANXA2 is correlated with the molecular features and clinical prognosis of glioma, and acts as a potential marker of immunosuppression.

Recent studies have shown that ANXA2 is important in the development of many cancers, while its role in glioma-related immune response remains unclear. We aimed to comprehensively investigate its biological characteristics and clinical value in glioma. We analyzed 699 glioma samples from The Cancer Genome Atlas as training cohort and 325 samples from the Chinese Glioma Genome Atlas as validation cohort. All the statistical analyses and figures were generated with R. ANXA2 was overexpressed significantly in high-grade glioma, isocitrate dehydrogenase wild-type and mesenchymal-subtype glioma. ANXA2 was a special indicator of mesenchymal subtype. The survival analysis showed that highly-expressed ANXA2 was related to worse survival status as an independent factor of poor prognosis. Further gene ontology analysis showed that ANXA2 was mainly involved in immune response and inflammatory activities of glioma. Subsequent correlation analysis showed that ANXA2 was positively correlated with HCK, LCK, MHC II, STAT1 and interferon but negatively with IgG. Meanwhile, ANXA2 was positively related to the infiltration of tumor-related macrophages, regulatory T cells and myeloid-derived suppressor cells. Our study revealed that ANXA2 is a biomarker closely related to the malignant phenotype and poor prognosis of glioma, and plays an important role in immune response, inflammatory activity and immunosuppression.

AHA1 upregulates IDH1 and metabolic activity to promote growth and metastasis and predicts prognosis in osteosarcoma.

Osteosarcoma (OS) is the most common primary malignant bone tumor in children and adolescents. Although activator of HSP90 ATPase activity 1 (AHA1) is reported to be a potential oncogene, its role in osteosarcoma progression remains largely unclear. Since metabolism reprogramming is involved in tumorigenesis and cancer metastasis, the relationship between AHA1 and cancer metabolism is unknown. In this study, we found that AHA1 is significantly overexpressed in osteosarcoma and related to the prognosis of osteosarcoma patients. AHA1 promotes the growth and metastasis of osteosarcoma both in vitro and in vivo. Mechanistically, AHA1 upregulates the metabolic activity to meet cellular bioenergetic needs in osteosarcoma. Notably, we identified that isocitrate dehydrogenase 1 (IDH1) is a novel client protein of Hsp90-AHA1. Furthermore, the IDH1 protein level was positively correlated with AHA1 in osteosarcoma. And IDH1 overexpression could partially reverse the effect of AHA1 knockdown on cell growth and migration of osteosarcoma. Moreover, high IDH1 level was also associated with poor prognosis of osteosarcoma patients. This study demonstrates that AHA1 positively regulates IDH1 and metabolic activity to promote osteosarcoma growth and metastasis, which provides novel prognostic biomarkers and promising therapeutic targets for osteosarcoma patients.

Differentiating Hepatic Epithelioid Angiomyolipoma From Hepatocellular Carcinoma and Focal Nodular Hyperplasia via Radiomics Models.

Background: We conduct a study in developing and validating two radiomics-based models to preoperatively distinguish hepatic epithelioid angiomyolipoma (HEAML) from hepatic carcinoma (HCC) as well as focal nodular hyperplasia (FNH). Methods: Totally, preoperative contrast-enhanced computed tomography (CT) data of 170 patients and preoperative contrast-enhanced magnetic resonance imaging (MRI) data of 137 patients were enrolled in this study. Quantitative texture features and wavelet features were extracted from the regions of interest (ROIs) of each patient imaging data. Then two radiomics signatures were constructed based on CT and MRI radiomics features, respectively, using the random forest (RF) algorithm. By integrating radiomics signatures with clinical characteristics, two radiomics-based fusion models were established through multivariate linear regression and 10-fold cross-validation. Finally, two diagnostic nomograms were built to facilitate the clinical application of the fusion models. Results: The radiomics signatures based on the RF algorithm achieved the optimal predictive performance in both CT and MRI data. The area under the receiver operating characteristic curves (AUCs) reached 0.996, 0.879, 0.999, and 0.925 for the training as well as test cohort from CT and MRI data, respectively. Then, two fusion models simultaneously integrated clinical characteristics achieved average AUCs of 0.966 (CT data) and 0.971 (MRI data) with 10-fold cross-validation. Through decision curve analysis, the fusion models were proved to be excellent models to distinguish HEAML from HCC and FNH in comparison between the clinical models and radiomics signatures. Conclusions: Two radiomics-based models derived from CT and MRI images, respectively, performed well in distinguishing HEAML from HCC and FNH and might be potential diagnostic tools to formulate individualized treatment strategies.

Chinese Clinical Named Entity Recognition in Electronic Medical Records: Development of a Lattice Long Short-Term Memory Model With Contextualized Character Representations.

BACKGROUND: Clinical named entity recognition (CNER), whose goal is to automatically identify clinical entities in electronic medical records (EMRs), is an important research direction of clinical text data mining and information extraction. The promotion of CNER can provide support for clinical decision making and medical knowledge base construction, which could then improve overall medical quality. Compared with English CNER, and due to the complexity of Chinese word segmentation and grammar, Chinese CNER was implemented later and is more challenging. OBJECTIVE: With the development of distributed representation and deep learning, a series of models have been applied in Chinese CNER. Different from the English version, Chinese CNER is mainly divided into character-based and word-based methods that cannot make comprehensive use of EMR information and cannot solve the problem of ambiguity in word representation. METHODS: In this paper, we propose a lattice long short-term memory (LSTM) model combined with a variant contextualized character representation and a conditional random field (CRF) layer for Chinese CNER: the Embeddings from Language Models (ELMo)-lattice-LSTM-CRF model. The lattice LSTM model can effectively utilize the information from characters and words in Chinese EMRs; in addition, the variant ELMo model uses Chinese characters as input instead of the character-encoding layer of the ELMo model, so as to learn domain-specific contextualized character embeddings. RESULTS: We evaluated our method using two Chinese CNER datasets from the China Conference on Knowledge Graph and Semantic Computing (CCKS): the CCKS-2017 CNER dataset and the CCKS-2019 CNER dataset. We obtained F1 scores of 90.13% and 85.02% on the test sets of these two datasets, respectively. CONCLUSIONS: Our results show that our proposed method is effective in Chinese CNER. In addition, the results of our experiments show that variant contextualized character representations can significantly improve the performance of the model.

Contrast-enhanced CT radiomics for preoperative evaluation of microvascular invasion in hepatocellular carcinoma: A two-center study.

BACKGROUND: The present study constructed and validated the use of contrast-enhanced computed tomography (CT)-based radiomics to preoperatively predict microvascular invasion (MVI) status (positive vs negative) and risk (low vs high) in patients with hepatocellular carcinoma (HCC). METHODS: We enrolled 637 patients from two independent institutions. Patients from Institution I were randomly divided into a training cohort of 451 patients and a test cohort of 111 patients. Patients from Institution II served as an independent validation set. The LASSO algorithm was used for the selection of 798 radiomics features. Two classifiers for predicting MVI status and MVI risk were developed using multivariable logistic regression. We also performed a survival analysis to investigate the potentially prognostic value of the proposed MVI classifiers. RESULTS: The developed radiomics signature predicted MVI status with an area under the receiver operating characteristic curve (AUC) of .780, .776, and .743 in the training, test, and independent validation cohorts, respectively. The final MVI status classifier that integrated two clinical factors (age and α-fetoprotein level) achieved AUC of .806, .803, and .796 in the training, test, and independent validation cohorts, respectively. For MVI risk stratification, the AUCs of the radiomics signature were .746, .664, and .700 in the training, test, and independent validation cohorts, respectively, and the AUCs of the final MVI risk classifier-integrated clinical stage were .783, .778, and .740, respectively. Survival analysis showed that our MVI status classifier significantly stratified patients for short overall survival or early tumor recurrence. CONCLUSIONS: Our CT radiomics-based models were able to predict MVI status and MVI risk of HCC and might serve as a reliable preoperative evaluation tool.

Targeting Super-Enhancer-Associated Oncogenes in Osteosarcoma with THZ2, a Covalent CDK7 Inhibitor.

PURPOSE: Malignancy of cancer cells depends on the active transcription of tumor-associated genes. Recently, unique clusters of transcriptional enhancers, termed super-enhancers, have been reported to drive the expression of genes that define cell identity. In this study, we characterized specific super-enhancer-associated genes of osteosarcoma, and explored their potential therapeutic value. EXPERIMENTAL DESIGN: Super-enhancer regions were characterized through chromatin immunoprecipitation sequencing (ChIP-seq). RT-qPCR was used to detect the mRNA level of CDK7 in patient specimens and confirm the regulation of sensitive oncogenes by THZ2. The phosphorylation of the initiation-associated sites of RNA polymerase II (RNAPII) C-terminal repeat domain (CTD) was measured using Western blotting. Microarray expression analysis was conducted to explore transcriptional changes after THZ2 treatment. A variety of in vitro and in vivo assays were performed to assess the effects of CDK7 knockdown and THZ2 treatment in osteosarcoma. RESULTS: Super-enhancers were associated with oncogenic transcripts and key genes encoding cell-type-specific transcription factors in osteosarcoma. Knockdown of transcription factor CDK7 reduced phosphorylation of the RNAPII CTD, and suppressed the growth and metastasis of osteosarcoma. A new specific CDK7 inhibitor, THZ2, suppressed cancer biology by inhibition of transcriptional activity. Compared with typical enhancers, osteosarcoma super-enhancer-associated oncogenes were particular vulnerable to this transcriptional disruption. THZ2 exhibited a powerful anti-osteosarcoma effect in vitro and in vivo. CONCLUSIONS: Super-enhancer-associated genes contribute to the malignant potential of osteosarcoma, and selectively targeting super-enhancer-associated oncogenes with the specific CDK7 inhibitor THZ2 might be a promising therapeutic strategy for patients with osteosarcoma.

A radiomics approach based on support vector machine using MR images for preoperative lymph node status evaluation in intrahepatic cholangiocarcinoma.

Purpose: Accurate lymph node (LN) status evaluation for intrahepatic cholangiocarcinoma (ICC) patients is essential for surgical planning. This study aimed to develop and validate a prediction model for preoperative LN status evaluation in ICC patients. Methods and Materials: A group of 106 ICC patients, who were diagnosed between April 2011 and February 2016, was used for prediction model training. Image features were extracted from T1-weighted contrast-enhanced MR images. A support vector machine (SVM) model was built by using the most LN status-related features, which were selected using the maximum relevance minimum redundancy (mRMR) algorithm. The mRMR method ranked each feature according to its relevance to the LN status and redundancy with other features. An SVM score was calculated for each patient to reflect the LN metastasis (LNM) probability from the SVM model. Finally, a combination nomogram was constructed by incorporating the SVM score and clinical features. An independent group of 42 patients who were diagnosed from March 2016 to November 2017 was used to validate the prediction models. The model performances were evaluated on discrimination, calibration, and clinical utility. Results: The SVM model was constructed based on five selected image features. Significant differences were found between patients with LNM and non-LNM in SVM scores in both groups (the training group: 0.5466 (interquartile range (IQR), 0.4059-0.6985) vs. 0.3226 (IQR, 0.0527-0.4659), P<0.0001; the validation group: 0.5831 (IQR, 0.3641-0.8162) vs. 0.3101 (IQR, 0.1029-0.4661), P=0.0015). The combination nomogram based on the SVM score, the CA 19-9 level, and the MR-reported LNM factor showed better discrimination in separating patients with LNM and non-LNM, comparing to the SVM model alone (AUC: the training group: 0.842 vs. 0.788; the validation group: 0.870 vs. 0.787). Favorable clinical utility was observed using the decision curve analysis for the nomogram. Conclusion: The nomogram, incorporating the SVM score, CA 19-9 level and the MR-reported LNM factor, provided an individualized LN status evaluation and helped clinicians guide the surgical decisions.