circNOX4 activates an inflammatory fibroblast niche to promote tumor growth and metastasis in NSCLC via FAP/IL-6 axis.

BACKGROUND: Cancer-associated fibroblasts (CAFs) orchestrate a supportive niche that fuels cancer metastatic development in non-small cell lung cancer (NSCLC). Due to the heterogeneity and plasticity of CAFs, manipulating the activated phenotype of fibroblasts is a promising strategy for cancer therapy. However, the underlying mechanisms of fibroblast activation and phenotype switching that drive metastasis remain elusive. METHODS: The clinical implications of fibroblast activation protein (FAP)-positive CAFs (FAP+CAFs) were evaluated based on tumor specimens from NSCLC patients and bioinformatic analysis of online databases. CAF-specific circular RNAs (circRNAs) were screened by circRNA microarrays of primary human CAFs and matched normal fibroblasts (NFs). Survival analyses were performed to assess the prognostic value of circNOX4 in NSCLC clinical samples. The biological effects of circNOX4 were investigated by gain- and loss-of-function experiments in vitro and in vivo. Fluorescence in situ hybridization, luciferase reporter assays, RNA immunoprecipitation, and miRNA rescue experiments were conducted to elucidate the underlying mechanisms of fibroblast activation. Cytokine antibody array, transwell coculture system, and enzyme-linked immunosorbent assay (ELISA) were performed to investigate the downstream effectors that promote cancer metastasis. RESULTS: FAP+CAFs were significantly enriched in metastatic cancer samples, and their higher abundance was correlated with the worse overall survival in NSCLC patients. A novel CAF-specific circRNA, circNOX4 (hsa_circ_0023988), evoked the phenotypic transition from NFs into CAFs and promoted the migration and invasion of NSCLC in vitro and in vivo. Clinically, circNOX4 correlated with the poor prognosis of advanced NSCLC patients. Mechanistically, circNOX4 upregulated FAP by sponging miR-329-5p, which led to fibroblast activation. Furthermore, the circNOX4/miR-329-5p/FAP axis activated an inflammatory fibroblast niche by preferentially inducing interleukin-6 (IL-6) and eventually promoting NSCLC progression. Disruption of the intercellular circNOX4/IL-6 axis significantly suppressed tumor growth and metastatic colonization in vivo. CONCLUSIONS: Our study reveals a role of the circRNA-induced fibroblast niche in tumor metastasis and highlights that targeting the circNOX4/FAP/IL-6 axis is a promising strategy for the intervention of NSCLC metastasis.

Preoperative prediction of disease-free survival in pancreatic ductal adenocarcinoma patients after R0 resection using contrast-enhanced CT and CA19-9.

OBJECTIVES: To investigate the efficiency of a combination of preoperative contrast-enhanced computed tomography (CECT) and carbohydrate antigen 19-9 (CA19-9) in predicting disease-free survival (DFS) after R0 resection of pancreatic ductal adenocarcinoma (PDAC). METHODS: A total of 138 PDAC patients who underwent curative R0 resection were retrospectively enrolled and allocated chronologically to training (n = 91, January 2014-July 2019) and validation cohorts (n = 47, August 2019-December 2020). Using univariable and multivariable Cox regression analyses, we constructed a preoperative clinicoradiographic model based on the combination of CECT features and serum CA19-9 concentrations, and validated it in the validation cohort. The prognostic performance was evaluated and compared with that of postoperative clinicopathological and tumor-node-metastasis (TNM) models. Kaplan-Meier analysis was conducted to verify the preoperative prognostic stratification performance of the proposed model. RESULTS: The preoperative clinicoradiographic model included five independent prognostic factors (tumor diameter on CECT > 4 cm, extrapancreatic organ infiltration, CECT-reported lymph node metastasis, peripheral enhancement, and preoperative CA19-9 levels > 180 U/mL). It better predicted DFS than did the postoperative clinicopathological (C-index, 0.802 vs. 0.787; p < 0.05) and TNM (C-index, 0.802 vs. 0.711; p < 0.001) models in the validation cohort. Low-risk patients had significantly better DFS than patients at the high-risk, defined by the model preoperatively (p < 0.001, training cohort; p < 0.01, validation cohort). CONCLUSIONS: The clinicoradiographic model, integrating preoperative CECT features and serum CA19-9 levels, helped preoperatively predict postsurgical DFS for PDAC and could facilitate clinical decision-making. CLINICAL RELEVANCE STATEMENT: We constructed a simple model integrating clinical and radiological features for the prediction of disease-free survival after curative R0 resection in patients with pancreatic ductal adenocarcinoma; this novel model may facilitate preoperative identification of patients at high risk of recurrence and metastasis that may benefit from neoadjuvant treatments. KEY POINTS: • Existing clinicopathological predictors for prognosis in pancreatic ductal adenocarcinoma (PDAC) patients who underwent R0 resection can only be ascertained postoperatively and do not allow preoperative prediction. • We constructed a clinicoradiographic model, using preoperative contrast-enhanced computed tomography (CECT) features and preoperative carbohydrate antigen 19-9 (CA19-9) levels, and presented it as a nomogram. • The presented model can predict disease-free survival (DFS) in patients with PDAC better than can postoperative clinicopathological or tumor-node-metastasis (TNM) models.

Reclassification of therapeutic response of unresectable hepatocellular carcinoma to anti-angiogenic therapy and immunotherapy using alpha RECIST.

OBJECTIVES: To assess the therapeutic response of HCC to antiangiogenic therapy plus immunotherapy by integrating RECIST 1.1 and alpha-fetoprotein (AFP) response at the 6th week to predict overall survival (OS). METHODS: This retrospective study included 150 and 214 patients with HCC who received combination therapy in training and validation cohorts. The medical images and AFP levels obtained at baseline and 6th week were collected. AFP response stratification: partial response (PR): AFP% ≥ 75% decline; stable disease (SD): AFP% < 75% decline and ≤ 10% elevation; progressive disease (PD): AFP% > 10% elevation. The alpha-RECIST was: PR: RECIST 1.1-PR or AFP-PR; PD: AFP-PD or RECIST 1.1-PD and does not satisfy AFP-PR; SD: neither PR nor PD. OS was compared using Kaplan-Meier curves. The predictive ability of various criteria was evaluated using the concordance index and time-dependent area under the receiver-operating characteristic curve. RESULTS: RECIST 1.1 achieved significant OS stratification (p = 0.020) for AFP < 20 ng/mL. For AFP ≥ 20 ng/mL, alpha-RECIST showed better performance than RECIST 1.1, mRECIST, and AFP response according to C-index (0.73 vs 0.66 vs 0.68 vs 0.69). The National Cancer Center (NCC) strategy utilized RECIST 1.1 for AFP < 20 ng/mL and alpha-RECIST for AFP ≥ 20 ng/mL and showed better performance than RECIST 1.1, mRECIST and AFP response according to C-index (0.73 vs 0.67 vs 0.69 vs 0.64). The performances of alpha-RECIST and NCC Strategy were confirmed in the validation cohort (C-index = 0.77 and 0.74). CONCLUSIONS: The alpha-RECIST and NCC Strategy achieved better survival stratification in patients with HCC under combination therapy in the AFP ≥ 20 ng/mL group and the whole cohort compared to the RECIST 1.1, mRECIST, and AFP response. CLINICAL TRANSLATIONAL RELEVANCE: The alpha-RECIST and National Cancer Center strategy are optimal methods for determining therapeutic response to a combination of anti-angiogenic therapy plus immunotherapy and facilitating accurate prognostic stratification for HCC in the AFP ≥ 20 ng/mL group and the whole cohort, which may help oncologists for early identification of responders and progression at 6 weeks and clinical decision-making. KEY POINTS: • RECIST 1.1 is indicated for patients with baseline alpha-fetoprotein (AFP) < 20 ng/mL. • For patients with baseline AFP ≥ 20 ng/mL, integrating RECIST 1.1 and AFP response (alpha-RECIST) may aid in the early identification of survival benefits and progression definition prior to the administration of additional efficacious drugs. • The National Cancer Center strategy is an optimal stratified strategy for determining therapeutic response to a combination of anti-angiogenic therapy and immunotherapy for HCC based on baseline AFP levels.

Non-intestinal-type adenocarcinoma of the nasal cavity and paranasal sinuses: an analysis of clinical characteristics and prognosis.

BACKGROUND: Non­intestinal adenocarcinoma of the nasal cavity and paranasal sinuses (non­ITAC) is a heterogeneous tumour that has rarely been reported in previous studies. We compared and analysed the symptoms, radiographic and pathological features, treatment methods, and prognosis of patients with low-grade (G1) and high-grade (G3) tumours. METHODS: This was a retrospective study included 22 patients with pathologically confirmed non-ITAC of the nasal cavity and paranasal sinuses who were treated between January 2008 and December 2021 at a single centre. Of these, 11 patients had G1 tumours, and 11 patients had G3 tumours. Clinicopathological features, treatment methods, and survival outcomes were analysed. RESULTS: The median follow-up period was 48.5 months. Nasal congestion was the most common initial symptom, and the nasal cavity was the most frequently involved site. For G1 tumours, the main treatment was simple surgery, 1 and 3­year overall survival (OS) rates were 100 and 88.9%, while the 1 and 3­year local control (LC) rates were 100 and 100%, respectively. For G3 tumours, the main treatments were surgery combined with radiotherapy and/or chemotherapy,1 and 3­year OS rates were 72.7 and 72.7%, while the 1 and 3­year LC rates were 100 and 90.91%, respectively. G3 tumours was associated with significantly shorter overall survival than G1 tumours (P = 0.035). Patients with stage III-IV showed shorter overall survival compared to stage I-II patients (P = 0.035). CONCLUSIONS: Non-ITAC of the nasal cavity and paranasal sinuses may frequently occur in the nasal cavity. The main treatment modality is surgery, supplemented by radiotherapy and chemotherapy. Pathological grade and tumour stage were poor prognostic factors for the disease.

The GRAPHS-CRAFITY score: a novel efficacy predictive tool for unresectable hepatocellular carcinoma treated with immunotherapy.

OBJECTIVES: To investigate MR features associated with prognosis of unresectable HCC receiving immunotherapy and establish a MR feature-based scoring system to predict efficacy of immunotherapy. METHODS: This retrospective study included patients with unresectable HCC who received immunotherapy at 2 hospitals between August 2018 and February 2022. The last follow-up was October 2022. Clinical variables and MR features were assessed using univariate and multivariate Cox regression analyses. A new scoring system was constructed based on independent risk factors and the CRAFITY score consisting of AFP (≥ 100 ng/ml) and CRP (≥ 1 mg/dl). And the predictive performance of CRAFITY core and new score were compared by receiver-operating-characteristics curves (ROCs), area under ROCs (AUCs), and calibration curves. RESULTS: A total of 166 patients (55.6 ± 10.4 years) were included in training cohort and 77 patients (55.4 ± 10.7 years) were included in validation cohort. There were significant differences in BCLC stage, max size, macrovascular invasion, intratumoral artery, and enhancing capsule between the 2 groups. Based on independent risk factors (gross GRowtH type, intratumoral fAt, enhancing tumor caPsule, Sex and CRAFITY score), a novel efficacy predictive tool named the GRAPHS-CRAFITY score was developed to predict OS. The OS was significantly different among the 3 groups according to GRAPHS-CRAFITY score (p value < 0.001). The GRAPHS-CRAFITY score could predict tumor response and disease control (p value < 0.001, p value < 0.001). CONCLUSIONS: The GRAPHS-CRAFITY score is a reliable and easily applicable tool to predict the efficacy of unresectable HCC receiving immunotherapy.

An ultra-small bispecific protein augments tumor penetration and treatment for pancreatic cancer.

PURPOSE: The once highly anticipated antibody-based pathway-targeted therapies have not achieved promising outcomes for deadly pancreatic ductal adenocarcinoma (PDAC), mainly due to drugs' low intrinsic anticancer activity and poor penetration across the dense physiological barrier. This study aims to develop an ultra-small-sized, EGFR/VEGF bispecific therapeutic protein to largely penetrate deep tumor tissue and effectively inhibit PDAC tumor growth in vivo. METHODS: The bispecific protein, Bi-fp50, was constructed by a typical synthetic biology method and labeled with fluorescent dyes for in vitro and in vivo imaging. Physicochemical properties, protein dual-binding affinity, and specificity of the Bi-fp50 were evaluated in several PDAC cell lines. In vitro quantitatively and qualitatively anticancer activity of Bi-fp50 was assessed by live/dead staining, MTT assay, and flow cytometry. In vivo pharmacokinetic and biodistribution were evaluated using blood biopsy samples and near-infrared fluorescence imaging. In vivo real-time tracking of Bi-fp50 in the local tumor was conducted by fibered confocal fluorescence microscopy. The subcutaneous PDAC tumor model was used to assess the in vivo antitumor effect of Bi-fp50. RESULTS: Bi-fp50 with an ultra-small size of 50 kDa (5 ~ 6 nm) showed an excellent binding ability to VEGF and EGFR simultaneously and had enhanced, accumulated binding capability for Bxpc3 PDAC cells compared with anti-VEGF scFv and anti-EGFR scFv alone. Additionally, bi-fp50 significantly inhibited the proliferation and growth of Bxpc3 and Aspc1 PDAC cells even under a relatively low concentration (0.3 µM). It showed synergistically enhanced therapeutic effects relative to two individual scFv and Bi-fp50x control in vitro. The half-life of blood clearance of Bi-fp50 was 4.33 ± 0.23 h. After intravenous injection, Bi-fp50 gradually penetrated the deep tumor, widely distributed throughout the whole tissue, and primarily enriched in the tumor with nearly twice the accumulation than scFv2 in the orthotopic PDAC tumor model. Furthermore, the Bi-fp50 protein could induce broad apoptosis in the whole tumor and significantly inhibited tumor growth 3 weeks after injection in vivo without other noticeable side effects. CONCLUSION: The proof-of-concept study demonstrated that the ultra-small-sized, bispecific protein Bi-fp50 could be a potential tumor suppressor and an efficient, safe theranostic tool for treating PDAC tumors.

Using immunovascular characteristics to predict very early recurrence and prognosis of resectable intrahepatic cholangiocarcinoma.

OBJECTIVE: To predict the very early recurrence (VER) of patients with intrahepatic cholangiocarcinoma (ICC) based on TLSs and MVI status, and further perform prognosis stratifications. METHODS: A total of 160, 51 ICC patients from two institutions between May 2012 and July 2022 were retrospectively included as training, external validation cohort. Clinical, radiological and pathological variables were evaluated and collected. Univariate and multivariate analysis were applied to select the significant factors related to VER of ICC. The factors selected were combined to perform stratification of overall survival (OS) using the Kaplan-Meier method with the log-rank test. RESULTS: Overall, 39 patients (24.4%) had VER, whereas 121 (75.6%) did not (non-VER group). In the training cohort, the median OS was 40.5 months (95% CIs: 33.2-47.7 months). The VER group showed significantly worse OS than the non-VER group (median OS: 14.8, 95% CI:11.6-18.0 months vs. 53.4, 34.3-72.6 months; p<0.001), and it was confirmed in the validation cohort (median OS: 22.1, 95% CI: 8.8-35.4 months vs. 40.1, 21.2-59.0 months; p = 0.003). According to the univariate analysis, four variables were significantly different between the VER group and non-VER group (TLSs status, p = 0.028; differentiation, p = 0.023; MVI status, p = 0.012; diameter, p = 0.028). According to the multivariate analysis, MVI-positive status was independently associated with a higher probability of VER (odds ratio [OR], 2.5; 95% CIs,1.16-5.18; p = 0.018), whereas intra-tumoral TLSs-positive status was associated with lower odds of VER (OR, 0.43; 95% CIs, 0.19-0.97; p = 0.041). Based on the TLSs and MVI status, patients of ICC were categorized into four groups: TLSs-positive and MVI-negative (TP/MN); TLSs-negative and MVI-negative (TN/MN); TLSs-positive and MVI-positive (TP/MP), TLSs-negative and MVI-positive groups (TN/MP). In the training cohort, the four groups could be correlated with OS significantly (p<0.001), and it was confirmed in the validation cohort (p<0.001). CONCLUSION: Intra-tumoral TLSs and MVI status are independent predictive factors of VER after surgery, based on which immunovascular stratifications are constructed and associated with OS significantly of resectable intrahepatic cholangiocarcinoma.

Association Between MRI Radiomics and Intratumoral Tertiary Lymphoid Structures in Intrahepatic Cholangiocarcinoma and Its Prognostic Significance.

BACKGROUND: Tertiary lymphoid structures (TLSs) have prognostic value in intrahepatic cholangiocarcinoma (ICC) patients. Noninvasive tool to preoperatively evaluate TLSs is still lacking. PURPOSE: To explore the association between TLSs status of ICC and preoperative MRI radiomics analysis. STUDY TYPE: Retrospective. SUBJECTS: One hundred and ninety-two patients with ICC, divided into training (T = 105), internal validation groups (V1 = 46), and external validation group (V2 = 41). SEQUENCE: Coronal and axial single-shot fast spin-echo T2-weighted, diffusion-weighted imaging, T1-weighted, and T1WI fat-suppressed spoiled gradient-recall echo LAVA sequence at 3.0 T. ASSESSMENT: The VOIs were drawn manually within the visible borders of the tumors using ITK-SNAP version 3.8.0 software in the axial T2WI, DWI, and portal vein phase sequences. Radiomics features were subjected to least absolute shrinkage and selection operator regression to select the associated features of TLSs and construct the radiomics model. Univariate and multivariate analyses were used to identify the clinical radiological variables associated with TLSs. The performances were evaluated by the area under the receiver operator characteristic curve (AUC). STATISTICAL TESTS: Logistic regression analysis, ROC and AUC, Hosmer-Lemeshow test, Kaplan-Meier method with the log-rank test, calibration curves, and decision curve analysis. P < 0.05 was considered statistically significant. RESULTS: The AUCs of arterial phase diffuse hyperenhancement were 0.59 (95% confidence interval [CI], 0.50-0.67), 0.52 (95% CI, 0.43-0.61), and 0.66 (95% CI, 0.52-0.80) in the T, V1, and V2 cohorts. The AUCs of Rad-score were 0.85 (95% CI, 0.77-0.92), 0.81 (95% CI, 0.67-0.94), and 0.84 (95% CI, 0.71-0.96) in the T, V1, and V2 cohorts, respectively. In cohort T, low-risk group showed significantly better median recurrence-free survival (RFS) than that of the high-risk group, which was also confirmed in cohort V1 and V2. DATA CONCLUSION: A preoperative MRI radiomics signature is associated with the intratumoral TLSs status of ICC patients and correlate significantly with RFS. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Risk stratification of solitary hepatocellular carcinoma ≤ 5 cm without microvascular invasion: prognostic values of MR imaging features based on LI-RADS and clinical parameters.

OBJECTIVES: To estimate the potential of preoperative MR imaging features and clinical parameters in the risk stratification of patients with solitary hepatocellular carcinoma (HCC) ≤ 5 cm without microvascular invasion (MVI) after hepatectomy. METHODS: The study enrolled 166 patients with histopathological confirmed MVI-negative HCC retrospectively. The MR imaging features were evaluated by two radiologists independently. The risk factors associated with recurrence-free survival (RFS) were identified by univariate Cox regression analysis and the least absolute shrinkage and selection operator Cox regression analysis. A predictive nomogram was developed based on these risk factors, and the performance was tested in the validation cohort. The RFS was analyzed by using the Kaplan-Meier survival curves and log-rank test. RESULTS: Among the 166 patients with solitary MVI-negative HCC, 86 patients presented with postoperative recurrence. Multivariate Cox regression analysis indicated that cirrhosis, tumor size, hepatitis, albumin, arterial phase hyperenhancement (APHE), washout, and mosaic architecture were risk factors associated with poor RFS and then incorporated into the nomogram. The nomogram achieved good performance with C-index values of 0.713 and 0.707 in the development and validation cohorts, respectively. Furthermore, patients were stratified into high- and low-risk subgroups, and significant prognostic differences were found between the different subgroups in both cohorts (p < 0.001 and p = 0.024, respectively). CONCLUSION: The nomogram incorporated preoperative MR imaging features, and clinical parameters can be a simple and reliable tool for predicting RFS and achieving risk stratification in patients with solitary MVI-negative HCC. KEY POINTS: • Application of preoperative MR imaging features and clinical parameters can effectively predict RFS in patients with solitary MVI-negative HCC. • Risk factors including cirrhosis, tumor size, hepatitis, albumin, APHE, washout, and mosaic architecture were associated with worse prognosis in patients with solitary MVI-negative HCC. • Based on the nomogram incorporating these risk factors, the MVI-negative HCC patients could be stratified into two subgroups with significant different prognoses.

CT-based quantification of trachea shape to detect invasion by thyroid cancer.

OBJECTIVE: This study aims to develop a CT-based method for quantifying tracheal shape and evaluating its ability to distinguish between cases with or without tracheal invasion in patients with thyroid carcinoma. METHODS: A total of 116 quantitative shape features, including 56 geometric moments and 60 bounding shape features, were defined. The tracheal lumen was semi-automatically defined with a CT threshold of less than - 500 HU. Three contiguous slices with the 1st, 2nd, and 3rd smallest trachea lumen areas were contiguously selected, and the appropriate number of slices to be included was determined. Fifty-six patients with differentiated thyroid carcinoma (DTC) invading the trachea and 22 patients with DTC but without invasion were retrospectively included. A receiver operating characteristic (ROC) curve was applied to select the representative shape features and determine the optimal threshold. RESULTS: 23.3%, 25.9%, and 24.1% of the features displayed an area under the ROC curve (AUC) ≥ 0.800 when derived from 1, 2, and 3 slices, respectively. Calculating feature values from two slices with the 1st and 2nd smallest tracheal lumen area were considered appropriate. Six final features, including 3 geometric moments and 3 bounding shape features, were selected to determine the tracheal invasion status of DTC and displayed AUCs of 0.875-0.918, accuracies of 0.821-0.891, sensitivities of 0.813-0.893, and specificities of 0.818-0.932, outperforming the visual evaluation results. CONCLUSIONS: Geometric moments and bounding shape features can quantify the tracheal shape and are reliable for identifying DTC tracheal invasion. The selected features quantified the extent of tracheal deformity in DTC patients with and without tracheal invasion. CLINICAL RELEVANCE STATEMENT: Six geometric features provide a non-invasive, semi-automated evaluation of the tracheal invasion status of thyroid cancer. KEY POINTS: • A novel method for quantifying tracheal shape using 56 geometric moments and 60 bounding shape features was developed. • Six features identify tracheal invasion by thyroid carcinoma. • The selected features quantified the extent of tracheal deformity in differentiated thyroid carcinoma patients with and without tracheal invasion.

Prediction of lymph node metastasis in stage T1-2 rectal cancers with MRI-based deep learning.

OBJECTIVES: This study aimed to investigate whether a deep learning (DL) model based on preoperative MR images of primary tumors can predict lymph node metastasis (LNM) in patients with stage T1-2 rectal cancer. METHODS: In this retrospective study, patients with stage T1-2 rectal cancer who underwent preoperative MRI between October 2013 and March 2021 were included and assigned to the training, validation, and test sets. Four two-dimensional and three-dimensional (3D) residual networks (ResNet18, ResNet50, ResNet101, and ResNet152) were trained and tested on T2-weighted images to identify patients with LNM. Three radiologists independently assessed LN status on MRI, and diagnostic outcomes were compared with the DL model. Predictive performance was assessed with AUC and compared using the Delong method. RESULTS: In total, 611 patients were evaluated (444 training, 81 validation, and 86 test). The AUCs of the eight DL models ranged from 0.80 (95% confidence interval [CI]: 0.75, 0.85) to 0.89 (95% CI: 0.85, 0.92) in the training set and from 0.77 (95% CI: 0.62, 0.92) to 0.89 (95% CI: 0.76, 1.00) in the validation set. The ResNet101 model based on 3D network architecture achieved the best performance in predicting LNM in the test set, with an AUC of 0.79 (95% CI: 0.70, 0.89) that was significantly greater than that of the pooled readers (AUC, 0.54 [95% CI: 0.48, 0.60]; p < 0.001). CONCLUSION: The DL model based on preoperative MR images of primary tumors outperformed radiologists in predicting LNM in patients with stage T1-2 rectal cancer. KEY POINTS: • Deep learning (DL) models with different network frameworks showed different diagnostic performance for predicting lymph node metastasis (LNM) in patients with stage T1-2 rectal cancer. • The ResNet101 model based on 3D network architecture achieved the best performance in predicting LNM in the test set. • The DL model based on preoperative MR images outperformed radiologists in predicting LNM in patients with stage T1-2 rectal cancer.

Copper-catalyzed 4-HO-TEMPOH mediated phosphorylation of alkenes.

An efficient, practical and regioselective synthesis of (E)-alkenylphosphine oxides has been developed starting from alkenes under copper catalysis and 4-HO-TEMPOH oxidation. Preliminary mechanistic studies clearly reveal that a phosphinoyl radical is involved in this process. Moreover, this method features mild reaction conditions, good functional group tolerance, and excellent regioselectivity and also promises to be efficient for the late-stage functionalization of drug molecular skeletons. The reaction will create an opportunity for the synthesis of complex phosphorus containing bioactive molecules.

Integrated Analysis of DNA Methylation and Gene Expression in Porcine Placental Development.

Proper placental development is crucial for the conceptus to grow and survive, because the placenta is responsible for transporting nutrients and oxygen from the pregnant female to the developing fetus. However, the processes of placental morphogenesis and fold formation remain to be fully elucidated. In this study, we used whole-genome bisulfite sequencing and RNA sequencing to produce a global map of DNA methylation and gene expression changes in placentas from Tibetan pig fetuses 21, 28, and 35 days post-coitus. Substantial changes in morphology and histological structures at the uterine-placental interface were revealed via hematoxylin-eosin staining. Transcriptome analysis identified 3959 differentially expressed genes (DEGs) and revealed the key transcriptional properties in three stages. The DNA methylation level in the gene promoter was negatively correlated with gene expression. We identified a set of differentially methylated regions associated with placental developmental genes and transcription factors. The decrease in DNA methylation level in the promoter was associated with the transcriptional activation of 699 DEGs that were functionally enriched in cell adhesion and migration, extracellular matrix remodeling, and angiogenesis. Our analysis provides a valuable resource for understanding the mechanisms of DNA methylation in placental development. The methylation status of different genomic regions plays a key role in establishing transcriptional patterns from placental morphogenesis to fold formation.

Comprehensive analysis of pre-mRNA alternative splicing regulated by m6A methylation in pig oxidative and glycolytic skeletal muscles.

BACKGROUND: Different types of skeletal myofibers exhibit distinct physiological and metabolic properties that are associated with meat quality traits in livestock. Alternative splicing (AS) of pre-mRNA can generate multiple transcripts from an individual gene by differential selection of splice sites. N6-methyladenosine (m6A) is the most abundant modification in mRNAs, but its regulation for AS in different muscles remains unknown.  RESULTS: We characterized AS events and m6A methylation pattern in pig oxidative and glycolytic muscles. A tota1 of 1294 differential AS events were identified, and differentially spliced genes were significantly enriched in processes related to different phenotypes between oxidative and glycolytic muscles. We constructed the regulatory network between splicing factors and corresponding differential AS events and identified NOVA1 and KHDRBS2 as key splicing factors. AS event was enriched in m6A-modified genes, and the methylation level was positively correlated with the number of AS events in genes. The dynamic change in m6A enrichment was associated with 115 differentially skipping exon (SE-DAS) events within 92 genes involving in various processes, including muscle contraction and myofibril assembly. We obtained 23.4% SE-DAS events (27/115) regulated by METTL3-meditaed m6A and experimentally validated the aberrant splicing of ZNF280D, PHE4DIP, and NEB. The inhibition of m6A methyltransferase METTL3 could induce the conversion of oxidative fiber to glycolytic fiber in PSCs. CONCLUSION: Our study suggested that m6A modification could contribute to significant difference in phenotypes between oxidative and glycolytic muscles by mediating the regulation of AS. These findings would provide novel insights into mechanisms underlying muscle fiber conversion.

Selecting Candidates for Organ-Preserving Strategies After Neoadjuvant Chemoradiotherapy for Rectal Cancer: Development and Validation of a Model Integrating MRI Radiomics and Pathomics.

BACKGROUND: Histopathologic evaluation after surgery is the gold standard to evaluate treatment response to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). However, it cannot be used to guide organ-preserving strategies due to poor timeliness. PURPOSE: To develop and validate a multiscale model incorporating radiomics and pathomics features for predicting pathological good response (pGR) of down-staging to stage ypT0-1N0 after nCRT. STUDY TYPE: Retrospective. POPULATION: A total of 153 patients (median age, 55 years; 109 men; 107 training group; 46 validation group) with clinicopathologically confirmed LARC. FIELD STRENGTH/SEQUENCE: A 3.0-T; fast spin echo T2 -weighted and single-shot EPI diffusion-weighted images. ASSESSMENT: The differences in clinicoradiological variables between pGR and non-pGR groups were assessed. Pretreatment and posttreatment radiomics signatures, and pathomics signature were constructed. A multiscale pGR prediction model was established. The predictive performance of the model was evaluated and compared to that of the clinicoradiological model. STATISTICAL TESTS: The χ2 test, Fisher's exact test, t-test, the minimum redundancy maximum relevance algorithm, the least absolute shrinkage and selection operator logistic regression algorithm, regression analysis, receiver operating characteristic curve (ROC) analysis, Delong method. P < 0.05 indicated a significant difference. RESULTS: Pretreatment radiomics signature (odds ratio [OR] = 2.53; 95% CI: 1.58-4.66), posttreatment radiomics signature (OR = 9.59; 95% CI: 3.04-41.46), and pathomics signature (OR = 3.14; 95% CI: 1.40-8.31) were independent factors for predicting pGR. The multiscale model presented good predictive performance with areas under the curve (AUC) of 0.93 (95% CI: 0.88-0.98) and 0.90 (95% CI: 0.78-1.00) in the training and validation groups, those were significantly higher than that of the clinicoradiological model with AUCs of 0.69 (95% CI: 0.55-0.82) and 0.68 (95% CI: 0.46-0.91) in both groups. DATA CONCLUSION: A model incorporating radiomics and pathomics features effectively predicted pGR after nCRT in patients with LARC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 4.

Added-value of dynamic contrast-enhanced MRI on prediction of tumor recurrence in locally advanced cervical cancer treated with chemoradiotherapy.

OBJECTIVES: To evaluate whether the DCE-MRI derived parameters integrated into clinical and conventional imaging variables may improve the prediction of tumor recurrence for locally advanced cervical cancer (LACC) patients following concurrent chemoradiotherapy (CCRT). METHODS: Between March 2014 and November 2019, 79 consecutive LACC patients who underwent pelvic MRI examinations with DCE-MRI sequence before treatment were prospectively enrolled. The primary outcome was disease-free survival (DFS). DCE-MRI derived parameters, conventional imaging, and clinical factors were collected. Univariate and multivariate Cox hazard regression analyses were performed to evaluate these parameters in the prediction of DFS. The independent and prognostic interested variables were combined to build a prediction model compared with the clinical International Federation of Gynecological (FIGO) staging system. RESULTS: Lymph node metastasis (LNM) and the mean value of ve (ve_mean) were independently associated with tumor recurrence (all p < 0.05). The prediction model based on T stage, LNM, and ve_mean demonstrated a moderate predictive capability in identifying LACC patients with a high risk of tumor recurrence; the model was more accurate than the FIGO staging system alone (c-index: 0.735 vs. 0.661) and the combination of ve_mean and the FIGO staging system (c-index: 0.735 vs. 0.688). Moreover, patients were grouped into low-, medial-, and high-risk levels based on the advanced T stage, positive LNM, and ve_mean < 0.361, with which the 2-year DFS was significantly stratified (p < 0.001). CONCLUSIONS: The ve_mean from DCE-MRI could be used as a useful biomarker to predict DFS in LACC patients treated with CCRT as an assistant of LNM and T stage. KEY POINTS: Lower ve_mean is an independent predictor of poor prognosis for disease-free survival in locally advanced cervical cancer patients treated with concurrent chemoradiotherapy (hazard ratio [HR]: 0.016, p<0.023). A combined prediction model based on advanced T stage, LNM, and ve_mean performed better than the FIGO staging system alone.

A MRI-based radiomics model predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma.

OBJECTIVES: To develop and validate a radiomics-based model for predicting radiation-induced temporal lobe injury (RTLI) in nasopharyngeal carcinoma (NPC) by pretreatment MRI of the temporal lobe. METHODS: A total of 216 patients with diagnosed NPC were retrospectively reviewed. Patients were randomly allocated to the training (n = 136) and the validation cohort (n = 80). Radiomics features were extracted from pretreatment contrast-enhanced T1- or fat-suppressed T2 weighted MRI. A radiomics signature was generated by the least absolute shrinkage and selection operator (LASSO) regression algorithm, Pearson correlation analysis, and univariable logistic analysis. Clinical features were selected with logistic regression analysis. Multivariable logistic regression analysis was conducted to develop three models for RTLI prediction in the training cohort: namely radiomics signature, clinical variables, and clinical-radiomics parameters. A radiomics nomogram was used and assessed with respect to calibration, discrimination, reclassification, and clinical application. RESULTS: The radiomics signature, composed of two radiomics features, was significantly associated with RTLI. The proposed radiomics model demonstrated favorable discrimination in both the training (AUC, 0.89) and the validation cohort (AUC, 0.92), outperforming the clinical prediction model (p < 0.05). Combining radiomics and clinical features, higher AUCs were achieved (AUC, 0.93 and 0.95), as well as a better calibration and improved accuracy of the prediction of RTLI. The clinical-radiomics model showed also excellent performance in predicting RTLI in different clinical-pathologic subgroups. CONCLUSION: A radiomics model derived from pretreatment MRI of the temporal lobe showed persuasive performance for predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma. KEY POINTS: • Radiomics features from pretreatment MRI are associated with radiation-induced temporal lobe injury in nasopharyngeal carcinoma. • The radiomics model shows better predictive performance than a clinical model and was similar to a clinical-radiomics model. • A clinical-radiomics model shows excellent performance in the prediction of radiation-induced temporal lobe injury in different clinical-pathologic subgroups.

Biocompatible Au-Fe3O4 Nanoparticle-based Magnetic Resonance Imaging in the Diagnosis of Liver Tumor.

The study aimed to analyze the value and significance of magnetic resonance imaging (MRI) using biocompatible Au-Fe3O4 nanomaterials in the diagnosis of liver tumors. In this study, 124 patients with liver tumors were selected to perform MRI scanning based on Au-Fe3O4 nanoparticles. The coincidence rate between MRI scanning results and pathological examination results, the detection rate of tumor focus between MRI scanning results and CT detection results were analyzed, to evaluate the diagnostic performance of MRI scanning based on Au-Fe3O4 nanoparticles. The results showed that in the detection of primary tumors, secondary tumors, and focal nodular hyperplasia, the coincidence rate between MRI scanning results and pathological examination results was high, and Kappa values were all greater than 0.8. Compared with the results of CT, the detection rate of tumor lesions smaller than 1 cm by MRI was significantly higher (P<0.05), but there was no significant difference between the two diagnostic methods for tumor lesions larger than 1 cm (P>0.05). Additionally, the accuracy, specificity, and sensitivity of MRI in diagnosing liver tumors were 86.81, 84.29, and 77.27, respectively. Clinically, MRI scanning based on Au-Fe3O4nanoparticles can provide a practical and effective reference for the differential diagnosis of liver tumors.

Detection of early-stage hepatocellular carcinoma in asymptomatic HBsAg-seropositive individuals by liquid biopsy.

Liquid biopsies, based on cell free DNA (cfDNA) and proteins, have shown the potential to detect early stage cancers of diverse tissue types. However, most of these studies were retrospective, using individuals previously diagnosed with cancer as cases and healthy individuals as controls. Here, we developed a liquid biopsy assay, named the hepatocellular carcinoma screen (HCCscreen), to identify HCC from the surface antigen of hepatitis B virus (HBsAg) positive asymptomatic individuals in the community population. The training cohort consisted of individuals who had liver nodules and/or elevated serum α-fetoprotein (AFP) levels, and the assay robustly separated those with HCC from those who were non-HCC with a sensitivity of 85% and a specificity of 93%. We further applied this assay to 331 individuals with normal liver ultrasonography and serum AFP levels. A total of 24 positive cases were identified, and a clinical follow-up for 6-8 mo confirmed four had developed HCC. No HCC cases were diagnosed from the 307 test-negative individuals in the follow-up during the same timescale. Thus, the assay showed 100% sensitivity, 94% specificity, and 17% positive predictive value in the validation cohort. Notably, each of the four HCC cases was at the early stage (<3 cm) when diagnosed. Our study provides evidence that the use of combined detection of cfDNA alterations and protein markers is a feasible approach to identify early stage HCC from asymptomatic community populations with unknown HCC status.

The application of multiple metrics in deformable image registration for target volume delineation of breast tumor bed.

BACKGROUND AND PURPOSE: For postoperative breast cancer patients, deformable image registration (DIR) is challenged due to the large deformations and non-correspondence caused by tumor resection and clip insertion. To deal with it, three metrics (fiducial-, region-, and intensity-based) were jointly used in DIR algorithm for improved accuracy. MATERIALS AND METHODS: Three types of metrics were combined to form a single-objective function in DIR algorithm. Fiducial-based metric was used to minimize the distance between the corresponding point sets of two images. Region-based metric was used to improve the overlap between the corresponding areas of two images. Intensity-based metric was used to maximize the correlation between the corresponding voxel intensities of two images. The two CT images, one before surgery and the other after surgery, were acquired from the same patient in the same radiotherapy treatment position. Twenty patients who underwent breast-conserving surgery and postoperative radiotherapy were enrolled in this study. RESULTS: For target registration error, the difference between the proposed and the conventional registration methods was statistically significant for soft tissue (2.06 vs. 7.82, p = 0.00024 < 0.05) and body boundary (3.70 vs. 6.93, p = 0.021 < 0.05). For visual assessment, the proposed method achieved better matching result for soft tissue and body boundary. CONCLUSIONS: Comparing to the conventional method, the registration accuracy of the proposed method was significantly improved. This method provided a feasible way for target volume delineation of tumor bed in postoperative radiotherapy of breast cancer patients.