Whole-tumor histogram analysis of multiple non-Gaussian diffusion models at high b values for assessing cervical cancer.

PURPOSE: To assess the diagnostic potential of whole-tumor histogram analysis of multiple non-Gaussian diffusion models for differentiating cervical cancer (CC) aggressive status regarding of pathological types, differentiation degree, stage, and p16 expression. METHODS: Patients were enrolled in this prospective single-center study from March 2022 to July 2023. Diffusion-weighted images (DWI) were obtained including 15 b-values (0 ~ 4000 s/mm2). Diffusion parameters derived from four non-Gaussian diffusion models including continuous-time random-walk (CTRW), diffusion-kurtosis imaging (DKI), fractional order calculus (FROC), and intravoxel incoherent motion (IVIM) were calculated, and their histogram features were analyzed. To select the most significant features and establish predictive models, univariate analysis and multivariate logistic regression were performed. Finally, we evaluated the diagnostic performance of our models by using receiver operating characteristic (ROC) analyses. RESULTS: 89 women (mean age, 55 ± 11 years) with CC were enrolled in our study. The combined model, which incorporated the CTRW, DKI, FROC, and IVIM diffusion models, offered a significantly higher AUC than that from any individual models (0.836 vs. 0.664, 0.642, 0.651, 0.649, respectively; p < 0.05) in distinguishing cervical squamous cell cancer from cervical adenocarcinoma. To distinguish tumor differentiation degree, except the combined model showed a better predictive performance compared to the DKI model (AUC, 0.839 vs. 0.697, respectively; p < 0.05), no significant differences in AUCs were found among other individual models and combined model. To predict the International Federation of Gynecology and Obstetrics (FIGO) stage, only DKI and FROC model were established and there was no significant difference in predictive performance among different models. In terms of predicting p16 expression, the predictive ability of DKI model is significantly lower than that of FROC and combined model (AUC, 0.693 vs. 0.850, 0.859, respectively; p < 0.05). CONCLUSION: Multiple non-Gaussian diffusion models with whole-tumor histogram analysis show great promise to assess the aggressive status of CC.

Dynamic contrast-enhanced and diffusion-weighted MRI of cervical carcinoma: Correlations with Ki-67 proliferation status.

OBJECTIVES: To investigate the association of quantitative parameter (apparent diffusion coefficient [ADC]) from diffusion-weighted imaging (DWI) and various quantitative and semiquantitative parameters from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) with Ki-67 proliferation index (PI) in cervical carcinoma (CC). METHODS: A total of 102 individuals with CC who received 3.0 T MRI examination (DWI and DCE MRI) between October 2016 and December 2022 were enrolled in our investigation. Two radiologists separately assessed the ADC parameter and various quantitative and semiquantitative parameters including (volume transfer constant [Ktrans], rate constant [kep], extravascular extracellular space volume fraction [ve], volume fraction of plasma [vp], time to peak [TTP], maximum concentration [MaxCon], maximal slope [MaxSlope] and area under curve [AUC]) for each tumor. Their association with Ki-67 PI was analyzed by Spearman association analysis. The discrepancy between low-proliferation and high-proliferation groups was subsequently analyzed. The receiver operating characteristic (ROC) curve analysis utilized to identify optimal cut-off points for significant parameters. RESULTS: Both ADC (ρ = -0.457, p < 0.001) and Ktrans (ρ = -0.467, p < 0.001) indicated a strong negative association with Ki-67 PI. Ki-67 PI showed positive correlations with TTP, MaxCon, MaxSlope and AUC (ρ = 0.202, 0.231, 0.309, 0.235, respectively; all p values<0.05). Compared with the low-proliferation group, high-Ki-67 group presented a significantly lower ADC (0.869 ± 0.125 × 10-3 mm2/s vs. 1.149 ± 0.318 × 10-3 mm2/s; p < 0.001) and Ktrans (1.314 ± 1.162 min-1vs. 0.391 ± 0.390 min-1; p < 0.001), also significantly higher MaxCon values (0.756 ± 0.959 vs. 0.422 ± 0.341; p < 0.05) and AUC values (2.373 ± 3.012 vs. 1.273 ± 1.000; p < 0.05). The cut-offs of ADC, Ktrans, MaxCon and AUC for discrimating low- and high-Ki-67 groups were 0.920 × 10-3 mm2/s, 0.304 min-1, 0.209 and 1.918, respectively. CONCLUSIONS: ADC, Ktrans, TTP, MaxCon, MaxSlope and AUC are associated with Ki-67 PI. ADC and Ktrans exhibited high performance to discriminate low and high Ki-67 status of CC.

Neoadjuvant chemoimmunotherapy in resectable locally advanced oral squamous cell carcinoma: a single-center retrospective cohort study.

BACKGROUND: Surgery and postoperative adjuvant therapy is the standard treatment for locally advanced resectable oral squamous cell carcinoma (OSCC), while neoadjuvant chemoimmunotherapy (NACI) is believed to lead better outcomes. This study aims to investigate the effectiveness of NACI regimens in treating locally advanced resectable OSCC. MATERIALS AND METHODS: Patients diagnosed with locally advanced resectable OSCC who received NACI and non-NACI were reviewed between December 2020 and June 2022 in our single center. The pathologic response was evaluated to the efficacy of NACI treatment. Adverse events apparently related to NACI treatment were graded by Common Terminology Criteria for Adverse Events, version 5.0. Disease-free survival (DFS) and overall survival (OS) rate were assessed. RESULTS: Our analysis involved 104 patients who received NACI. Notably, the pathological complete response (PCR) rate was 47.1%, and the major pathological response (MPR) rate was 65.4%. The top three grade 1-2 treatment-related adverse events (TRAEs) were alopecia (104; 100%), anemia (81; 77.9%) and pruritus (62; 59.6%). Importantly, patients achieving MPR exhibited higher programmed cell death-ligand 1 (PD-L1) combined positive score (CPS). The diagnostic value of CPS as a biomarker for NACI efficacy was enhanced when combined total cholesterol level. The 3-year estimated DFS rates were 89.0% in the NACI cohort compared to 60.8% in the non-NACI cohort, while the 3-year estimated OS rates were 91.3% versus 64.0%, respectively. CONCLUSIONS: The NACI treatment showed safe and encouragingly efficacious for locally advanced resectable OSCC patients. The high response rates and favorable prognosis suggest this approach as a potential treatment option. Prospective randomized controlled trials are needed to further validate these findings.

MRI-based deep learning and radiomics for prediction of occult cervical lymph node metastasis and prognosis in early-stage oral and oropharyngeal squamous cell carcinoma: a diagnostic study.

INTRODUCTION: The incidence of occult cervical lymph node metastases (OCLNM) is reported to be 20%-30% in early-stage oral cancer and oropharyngeal cancer. There is a lack of an accurate diagnostic method to predict occult lymph node metastasis and to help surgeons make precise treatment decisions. AIM: To construct and evaluate a preoperative diagnostic method to predict occult lymph node metastasis (OCLNM) in early-stage oral and oropharyngeal squamous cell carcinoma (OC and OP SCC) based on deep learning features (DLFs) and radiomics features. METHODS: A total of 319 patients diagnosed with early-stage OC or OP SCC were retrospectively enrolled and divided into training, test and external validation sets. Traditional radiomics features and DLFs were extracted from their MRI images. The least absolute shrinkage and selection operator (LASSO) analysis was employed to identify the most valuable features. Prediction models for OCLNM were developed using radiomics features and DLFs. The effectiveness of the models and their clinical applicability were evaluated using the area under the curve (AUC), decision curve analysis (DCA) and survival analysis. RESULTS: Seventeen prediction models were constructed. The Resnet50 deep learning (DL) model based on the combination of radiomics and DL features achieves the optimal performance, with AUC values of 0.928 (95% CI: 0.881-0.975), 0.878 (95% CI: 0.766-0.990), 0.796 (95% CI: 0.666-0.927) and 0.834 (95% CI: 0.721-0.947) in the training, test, external validation set1 and external validation set2, respectively. Moreover, the Resnet50 model has great prediction value of prognosis in patients with early-stage OC and OP SCC. CONCLUSION: The proposed MRI-based Resnet50 deep learning model demonstrated high capability in diagnosis of OCLNM and prognosis prediction in the early-stage OC and OP SCC. The Resnet50 model could help refine the clinical diagnosis and treatment of the early-stage OC and OP SCC.

A Generalizable Causal-Invariance-Driven Segmentation Model for Peripancreatic Vessels.

Segmenting peripancreatic vessels in CT, including the superior mesenteric artery (SMA), the coeliac artery (CA), and the partial portal venous system (PPVS), is crucial for preoperative resectability analysis in pancreatic cancer. However, the clinical applicability of vessel segmentation methods is impeded by the low generalizability on multi-center data, mainly attributed to the wide variations in image appearance, namely the spurious correlation factor. Therefore, we propose a causal-invariance-driven generalizable segmentation model for peripancreatic vessels. It incorporates interventions at both image and feature levels to guide the model to capture causal information by enforcing consistency across datasets, thus enhancing the generalization performance. Specifically, firstly, a contrast-driven image intervention strategy is proposed to construct image-level interventions by generating images with various contrast-related appearances and seeking invariant causal features. Secondly, the feature intervention strategy is designed, where various patterns of feature bias across different centers are simulated to pursue invariant prediction. The proposed model achieved high DSC scores (79.69%, 82.62%, and 83.10%) for the three vessels on a cross-validation set containing 134 cases. Its generalizability was further confirmed on three independent test sets of 233 cases. Overall, the proposed method provides an accurate and generalizable segmentation model for peripancreatic vessels and offers a promising paradigm for increasing the generalizability of segmentation models from a causality perspective. Our source codes will be released at https://github.com/SJTUBME-QianLab/PC_VesselSeg.

Integrated Single-cell and Bulk RNA Sequencing Analysis Cross Talk between Ferroptosis-related Genes and Prognosis in Oral Cavity Squamous Cell Carcinoma.

BACKGROUND: Ferroptosis is a new type of programmed apoptosis and plays an important role in tumour inhibition and immunotherapy. OBJECTIVE: In this study, we aimed to explore the potential role of ferroptosis-related genes (FRGs) and the potential therapeutic targets in oral cavity squamous cell carcinoma (OCSCC). METHODS: The transcription data of OCSCC samples were obtained from the Cancer Genome Atlas (TCGA) database as a training dataset. The prognostic FRGs were extracted by univariate Cox regression analysis. Then, we constructed a prognostic model using the least absolute shrinkage and selection operator (LASSO) and Cox analysis to determine the independent prognosis FRGs. Based on this model, risk scores were calculated for the OCSCC samples. The model's capability was further evaluated by the receiver operating characteristic curve (ROC). Then, we used the GSE41613 dataset as an external validation cohort to confirm the model's predictive capability. Next, the immune infiltration and somatic mutation analysis were applied. Lastly, single-cell transcriptomic analysis was used to identify the key cells. RESULTS: A total of 12 prognostic FRGs were identified. Eventually, 6 FRGs were screened as independent predictors and a prognostic model was constructed in the training dataset, which significantly stratified OCSCC samples into high-risk and low-risk groups based on overall survival. The external validation of the model using the GSE41613 dataset demonstrated a satisfactory predictive capability for the prognosis of OCSCC. Further analysis revealed that patients in the highrisk group had distinct immune infiltration and somatic mutation patterns from low-risk patients. Mast cell infiltrations were identified as prognostic immune cells and played a role in OCSCC partly through ferroptosis. CONCLUSION: We successfully constructed a novel 6 FRGs model and identified a prognostic immune cell, which can serve to predict clinical prognoses for OCSCC. Ferroptosis may be a new direction for immunotherapy of OCSCC.

Mutational landscape of head and neck cancer and cervical cancer in Chinese and Western population.

BACKGROUND: We aimed to unbiasedly map the genetic mutation profile of HNSC and CESC associated with HPV status in the Chinese population (SYSU-cohort) and compare them with Western population (TCGA-cohort). METHODS: Fifty-one HNSC patients (SYSU-HNSC) and 38 CESC patients (SYSU-CESC) were enrolled in this study. Genomic alterations were examined, and the profile was produced using the YuanSuTM450 gene panel (OrigiMed, Shanghai, China). The altered genes were inferred and compared to Western patients from TCGA cohorts. RESULTS: Compared to the TCGA-HNSC cohort, FGFR3 mutation was identified as a novel target in SYSU-HNSC with therapeutic potential. Compared to the TCGA-CESC cohort, some epigenetic regulation-associated genes were frequently mutated in SYSU-CESC cohort (KMT2C, KMT2D, KDM5C, KMT2A). CONCLUSION: In summary, our study provides unbiased insights into the genetic landscape of HNSC and CESC in the Chinese population and highlights potential novel therapeutic targets that may benefit Chinese patients.

Evaluation of Quantitative Dual-Energy Computed Tomography Parameters for Differentiation of Parotid Gland Tumors.

RATIONALE AND OBJECTIVES: To assess the diagnostic performance of quantitative parameters from dual-energy CT (DECT) in differentiating parotid gland tumors (PGTs). MATERIALS AND METHODS: 101 patients with 108 pathologically proved PGTs were enrolled and classified into four groups: pleomorphic adenomas (PAs), warthin tumors (WTs), other benign tumors (OBTs), and malignant tumors (MTs). Conventional CT attenuation and DECT quantitative parameters, including iodine concentration (IC), normalized iodine concentration (NIC), effective atomic number (Zeff), electron density (Rho), double energy index (DEI), and the slope of the spectral Hounsfield unit curve (λHU), were obtained and compared between benign tumors (BTs) and MTs, and further compared among the four subgroups. Logistic regression analysis was used to assess the independent parameters and the receiver operating characteristic (ROC) curves were used to analyze the diagnostic performance. RESULTS: Attenuation, Zeff, DEI, IC, NIC, and λHU in the arterial phase (AP) and venous phase (VP) were higher in MTs than in BTs (p < 0.001-0.047). λHU in VP and Zeff in AP were independent predictors with an area under the curve (AUC) of 0.84 after the combination. Furthermore, attenuation, Zeff, DEI, IC, NIC, and λHU in the AP and VP of MTs were higher than those of PAs (p < 0.001-0.047). Zeff and NIC in AP and λHU in VP were independent predictors with an AUC of 0.93 after the combination. Attenuation and Rho in the precontrast phase; attenuation, Rho, Zeff, DEI, IC, NIC, and λHU in AP; and the Rho in the VP of PAs were lower than those of WTs (p < 0.001-0.03). Rho in the precontrast phase and attenuation in AP were independent predictors with an AUC of 0.89 after the combination. MTs demonstrated higher Zeff, DEI, IC, NIC, and λHU in VP and lower Rho in the precontrast phase compared with WTs (p < 0.001-0.04); but no independent predictors were found. CONCLUSION: DECT quantitative parameters can help to differentiate PGTs.

Improving visualization of free fibula flap perforators and reducing radiation dose in dual-energy CT angiography.

Background: The precise assessment of the perforators of the fibula free flap (FFF) is crucial for minimizing procedure-related complications when harvesting the FFF in patients with maxillofacial lesions. This study aims to investigate the utility of virtual noncontrast (VNC) images for radiation dose saving and to determine the optimal energy level of virtual monoenergetic imaging (VMI) reconstructions in dual-energy computed tomography (DECT) for visualization of the perforators of the fibula free flap (FFF). Methods: Data from 40 patients with maxillofacial lesions who received lower extremity DECT examinations in the noncontrast and arterial phase were collected in this retrospective, cross-sectional study. To compare VNC images from the arterial phase with true non-contrast images in a DECT protocol (M_0.5-TNC) and to compare VMI images with 0.5 linear images blending from the arterial phase (M_0.5-C), the attenuation, noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and subjective image quality were assessed in different arteries, muscles, and fat tissues. Two readers evaluated the image quality and visualization of the perforators. The dose-length product (DLP) and CT volume dose index (CTDIvol) were used to determine the radiation dose. Results: Objective and subjective analyses showed no significant difference between the M_0.5-TNC and VNC images in the arteries and muscles (P>0.09 to P>0.99), and VNC imaging could reduce 50% of the radiation dose (P<0.001). Compared with those of the M_0.5-C images, the attenuation and CNR of VMI reconstructions at 40 kiloelectron volt (keV) and 60 keV were higher (P<0.001 to P=0.04). Noise was similar at 60 keV (all P>0.99) and increased at 40 keV (all P<0.001), and the SNR in arteries was increased at 60 keV (P<0.001 to P=0.02) in VMI reconstructions compared with those in the M_0.5-C images. The subjective scores in VMI reconstructions at 40 and 60 keV was higher than those in M_0.5-C images (all P<0.001). The image quality at 60 keV was superior to that at 40 keV (P<0.001), and there was no difference in the visualization of the perforators between 40 and 60 keV (P=0.31). Conclusions: VNC imaging is a reliable technique for replacing M_0.5-TNC and provides radiation dose saving. The image quality of the 40-keV and 60-keV VMI reconstructions was higher than that of the M_0.5-C images, and 60 keV provided the best assessment of perforators in the tibia.

Selective In Situ Analysis of Mature microRNAs in Extracellular Vesicles Using a DNA Cage-Based Thermophoretic Assay.

Mature microRNAs (miRNAs) in extracellular vesicles (EVs) are involved in different stages of cancer progression, yet it remains challenging to precisely detect mature miRNAs in EVs due to the presence of interfering RNAs (such as longer precursor miRNAs, pre-miRNAs) and the low abundance of tumor-associated miRNAs. By leveraging the size-selective ability of DNA cages and polyethylene glycol (PEG)-enhanced thermophoretic accumulation of EVs, we devised a DNA cage-based thermophoretic assay for highly sensitive, selective, and in situ detection of mature miRNAs in EVs with a low limit of detection (LoD) of 2.05 fM. Our assay can profile EV mature miRNAs directly in serum samples without the interference of pre-miRNAs and the need for ultracentrifugation. A clinical study showed that EV miR-21 or miR-155 had an overall accuracy of 90 % for discrimination between breast cancer patients and healthy donors, which outperformed conventional molecular probes detecting both mature miRNAs and pre-miRNAs. We envision that our assay can advance EV miRNA-based diagnosis of cancer.

Comparison of image quality and quantitative parameters in intravoxel incoherent motion imaging at 3-T based on turbo spin-echo and echo-planar imaging in patients with oral cancer.

PURPOSE: To compare the image quality, apparent diffusion coefficient (ADC), and intravoxel incoherent motion- (IVIM) derived parameters of IVIM imaging based on turbo spin-echo (TSE) and echo-planar imaging (EPI) of patients with oral cancer and to assess the equivalence of the ADC and IVIM-derived parameters. METHODS: Thirty patients with oral cancer underwent TSE-IVIM and EPI-IVIM imaging using a 3.0-T system. The distortion ratio (DR), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), qualitative evaluations of image quality, ADC, pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) were compared between the two sequences. The consistency of the quantitative parameters in oral cancer between the TSE and EPI sequences was evaluated using a Bland-Altman analysis. RESULTS: TSE-IVIM had a significantly smaller DR than EPI-IVIM (P < 0.001). The CNR of EPI-IVIM on most of the anatomical sites was significantly higher than that of TSE-IVIM (P < 0.05), while the SNR was not significantly different (P > 0.05). TSE-IVIM had significantly higher image quality, less distortion and artifacts, and lower image contrast compared with EPI-IVIM (P < 0.05). The lesion-edge sharpness and diagnostic confidence of EPI-IVIM were lower than that of TSE-IVIM, although no significant differences existed (P > 0.05). The ADC and D of TSE-IVIM had better reproducibility (intraclass correlation coefficient > 0.9). Although no significant difference existed for the ADC and IVIM-derived parameters of lesions between the two sequences (P > 0.05), wide limits of agreement were found in the Bland-Altman plots. CONCLUSION: TSE-IVIM could be used as an alternative technique to EPI-IVIM for patients with oral cancer because of its better image quality. Furthermore, TSE-IVIM can provide more accurate quantitative parameters. However, the quantitative parameters derived from the two IVIM techniques cannot be used as equivalent parameters for patients with oral cancer.

The Critical Shoulder Angle Can be Accurately and Reliably Determined from Three-Dimensional Computed Tomography Images.

OBJECTIVE: Anteroposterior (AP) radiographs do not necessarily offer the optimal approach to measuring the critical shoulder angle (CSA) due to the malposition of the scapula. Three-dimensional computed tomography (3D-CT) may offer some advantages, including the ability to rotate the scapula for position alignment and pre-operative planning for reducing CSA. This study aimed to investigate the accuracy and reliability of CSA measurement in 3D-CT and to determine whether there is an association between CSA and rotator cuff tears (RCTs). METHODS: In this retrospective study we identified 200 patients who received shoulder arthroscopy from 2019 to 2021, including 142 patients (81 females, 61 males) with RCTs and 58 patients (14 females, 44 males) with non-RCTs. For each participant, CSA was measured from standard shoulder AP radiographs and anterior views of 3D-CT of the scapula by two independent assessors. Inter- and intra-observer agreements were assessed by the intraclass correlation coefficient (ICC). The relationship between the two measurement methodologies was determined by Spearman's correlation coefficient and Bland-Altman plots. Discriminative capacity was calculated by using receiver operating curve (ROC) analyses in the whole cohort and age sub-groups above and below 45 years. RESULTS: We found perfect inter-observer (ICC >0.96) and intra-observer (ICC >0.97) reliabilities for CSA measurements obtained from the standard AP radiographs and the 3D-CT. There was a strong correlation between the two methods (r = 0.960, P < 0.001). The mean CSA was 31.7° ± 4.2° in the standard AP radiographs and 31.8° ± 4.4° in the 3D-CT (mean difference 0.02°, P = 0.940; bias 0.02°, limits of agreement -2.29° to +2.33°). ROC analysis of the whole cohort showed that the CSA measured in the standard AP radiographs (area under the ROC curve [AUC] = 0.812, P < 0.001) and the 3D-CT (AUC = 0.815, P < 0.001) predicted RCT with high confidence. ROC analysis of patients aged ≥45 years showed that the CSA measured from the standard AP radiographs (AUC = 0.869, P < 0.001) and the 3D-CT (AUC = 0.870, P < 0.001) were very good at predicting RCTs. CONCLUSION: CSA measured from standard AP radiographs and 3D-CT showed high consistency, and the CSA could be accurately and reliably measured using 3D-CT. CSAs measured from standard AP radiographs and 3D-CT could predict RCTs, especially in patients aged ≥45 years.

PtSnBi Nanoplates Enable Photoacoustic Imaging-Guided Highly Efficient Photothermal Tumor Ablation.

The development of photothermal agents (PTAs) with robust photostability and high photothermal conversion efficiency is of great importance for cancer photothermal therapy. Herein, a novel PTA was created using two-dimensional intermetallic PtSnBi nanoplates (NPs), which demonstrated excellent photostability and biocompatibility with a high photothermal conversion efficiency of ∼61 % after PEGylation. More importantly, PtSnBi NPs could be employed as photoacoustic imaging contrast agents for tumor visualization due to their strong absorbance in the NIR range. In addition, both in vitro and in vivo experiments confirmed that PtSnBi NPs had a good photothermal efficacy under NIR laser irradiation. Therefore, the remarkable therapeutic characteristics of PtSnBi NPs make them a most promising candidate for cancer theranostics.

RNF186/EPHB2 Axis Is Essential in Regulating TNF Signaling for Colorectal Tumorigenesis in Colorectal Epithelial Cells.

The receptor tyrosine kinase EPHB2 (EPH receptor B2) is highly expressed in many human cancer types, especially in gastrointestinal cancers, such as colorectal cancer. Several coding mutations of the EPHB2 gene have been identified in many cancer types, suggesting that EPHB2 plays a critical role in carcinogenesis. However, the exact functional mechanism of EPHB2 in carcinogenesis remains unknown. In this study, we find that EPHB2 is required for TNF-induced signaling activation and proinflammatory cytokine production in colorectal epithelial cells. Mechanistically, after TNF stimulation, EPHB2 is ubiquitinated by its E3 ligase RNF186. Then, ubiquitinated EPHB2 recruits and further phosphorylates TAB2 at nine tyrosine sites, which is a critical step for the binding between TAB2 and TAK1. Due to defects in TNF signaling in RNF186-knockout colorectal epithelial cells, the phenotype of colitis-propelled colorectal cancer model in RNF186-knockout mice is significantly reduced compared with that in wild-type control mice. Moreover, we find that a genetic mutation in EPHB2 identified in a family with colorectal cancer is a gain-of-function mutation that promoted TNF signaling activation compared with wild-type EPHB2. We provide evidence that the EPHB2-RNF186-TAB2-TAK1 signaling cascade plays an essential role in TNF-mediated signal transduction in colorectal epithelial cells and the carcinogenesis of colorectal cancer, which may provide potential targets for the treatment of colorectal cancer.

ADC and kinetic parameter of primary tumor: Surrogate imaging markers for fertility-sparing vaginal radical trachelectomy in patients with stage IB cervical cancer.

PURPOSE: To investigate the role of ADC and kinetic parameters derived from DCE-MRI in selecting eligible candidates for fertility-sparing vaginal radical trachelectomy (VRT). METHOD: Female patients with FIGO stage IB cervical cancers between March 2019 and January 2022 were retrospectively included. All patients underwent hysterectomy and bilateral lymphadenectomy. According to the surgical pathology, the study population was divided into VRT-eligible group and VRT-ineligible group. ADC, semi-quantitative and quantitative kinetic parameters of the primary tumor were compared between the two groups. Logistic regression analysis was used to determine the independent predictors for VRT eligibility and ROC curve was used to evaluate the predictive performance. RESULTS: 19 patients were deemed eligible for VRT and 50 were ineligible. Compared with VRT-eligible group, time to peak and ADC were significantly lower in VRT-ineligible group (P = 0.004 and 0.001, respectively) while volume fraction of plasma (Vp) was higher in VRT ineligible group (P = 0.001). ADC and Vp were independent predictors for VRT eligibility. Combining Vp and ADC yielded the highest area under the ROC curve of 0.853 compared with that of 0.766 for Vp and 0.764 for ADC, though marginal differences were found (P = 0.109 and 0.078, respectively). CONCLUSIONS: ADC and the kinetic DCE-MRI parameter Vp can be used as surrogate markers to select eligible candidates for fertility-sparing VRT.

Morphologic CT and MRI features of primary parotid squamous cell carcinoma and its predictive factors for differential diagnosis with mucoepidermoid carcinoma.

BACKGROUND: Primary parotid squamous cell carcinoma (SCC) is a rare entity with a poor prognosis. Pathologically, the diagnosis of it requires the exclusion of parotid mucoepidermoid carcinoma (MEC). Currently, the imaging features of primary parotid SCC and the predictive indicators for differential diagnosis of the two entities have not been well reported. Our purpose was to identify the imaging characteristics of primary parotid SCC and to determine the predictive factors for its' differential diagnosis. RESULTS: Thirty-one participants with primary parotid SCC and 59 with primary parotid MEC were enrolled. Clinical, CT and MRI features were reviewed and compared by univariate analysis. Then, multinomial logistic regression was used to determine the predictors to distinguish parotid SCC from MEC. Most primary parotid SCCs exhibited irregular shape, ill-defined margin, incomplete or no capsule, heterogeneous and marked or moderate enhancement, necrosis, local tumor invasiveness (LTI). Age, maximal dimension, shape, degree of enhancement, gradual enhancement, necrosis, and LTI were different between the primary parotid SCCs and MECs in univariate analysis (p < 0.05). While in multinomial logistic regression analysis, only age and necrosis were the independent predictors for distinguishing parotid SCC from MEC, and this model exhibited an area under curve of 0.914 in ROC curve analysis. CONCLUSIONS: Primary parotid SCC has some distinct imaging features including the large tumor size, irregular shape, ill-defined margin, and particularly the marked central necrosis. Patients with age ≥ 51.5 years and necrosis on the image of the primary tumor in the parotid gland could be more likely to be SCCs than MECs.

Preoperative Prediction of the Aggressiveness of Oral Tongue Squamous Cell Carcinoma with Quantitative Parameters from Dual-Energy Computed Tomography.

Objectives: To determine whether quantitative parameters derived from dual-energy computed tomography (DECT) were predictive of the aggressiveness of oral tongue squamous cell carcinoma (OTSCC) including the pathologic stages, histologic differentiation, lymph node status, and perineural invasion (PNI). Methods: Between August 2019 and March 2021, 93 patients (mean age, 54.6 ± 13.8 years; 66 men) with pathologically diagnosed OTSCC were enrolled in this prospective study. Preoperative DECT was performed and quantitative parameters (e.g., slope of the spectral Hounsfield unit curve [λHu], normalized iodine concentration [nIC], normalized effective atomic number [nZeff], and normalized electron density [nRho]) were measured on arterial phase (AP) and venous phase (VP) DECT imaging. Quantitative parameters from DECT were compared between patients with different pathologic stages, histologic differentiation, lymph node statuses, and perineural invasion statuses. Logistic regression analysis was utilized to assess independent parameters and the diagnostic performance was analyzed by the receiver operating characteristic curves (ROC). Results: λHu and nIC in AP and λHu, nZeff, and nIC in VP were significantly lower in stage III-IV lesions than in stage I-II lesions (p < 0.001 to 0.024). λHu in VP was an independent predictor of tumor stage with an odds ratio (OR) of 0.29, and area under the curve (AUC) of 0.80. λHu and nIC were higher in well-differentiated lesions than in poorly differentiated lesions (p < 0.001 to 0.021). The nIC in VP was an independent predictor of histologic differentiation with OR of 0.31, and AUC of 0.78. λHu and nIC in VP were lower in OTSCCs with lymph node metastasis than those without metastasis (p < 0.001 to 0.005). λHu in VP was the independent predictor of lymph node status with OR of 0.42, and AUC of 0.74. No significant difference was found between OTSCCs without PNI and those with PNI in terms of the quantitative DECT parameters. Conclusion: DECT can be a complementary means for the preoperative prediction of the aggressiveness of OTSCC.

DOCK2 regulates antifungal immunity by regulating RAC GTPase activity.

Fungal infections cause ~1.5 million deaths each year worldwide, and the mortality rate of disseminated candidiasis currently exceeds that of breast cancer and malaria. The major reasons for the high mortality of candidiasis are the limited number of antifungal drugs and the emergence of drug-resistant species. Therefore, a better understanding of antifungal host defense mechanisms is crucial for the development of effective preventive and therapeutic strategies. Here, we report that DOCK2 (dedicator of cytokinesis 2) promotes indispensable antifungal innate immune signaling and proinflammatory gene expression in macrophages. DOCK2-deficient macrophages exhibit decreased RAC GTPase (Rac family small GTPase) activation and ROS (reactive oxygen species) production, which in turn attenuates the killing of intracellular fungi and the activation of downstream signaling pathways. Mechanistically, after fungal stimulation, activated SYK (spleen-associated tyrosine kinase) phosphorylates DOCK2 at tyrosine 985 and 1405, which promotes the recruitment and activation of RAC GTPases and then increases ROS production and downstream signaling activation. Importantly, nanoparticle-mediated delivery of in vitro transcribed (IVT) Rac1 mRNA promotes the activity of Rac1 and helps to eliminate fungal infection in vivo. Taken together, this study not only identifies a critical role of DOCK2 in antifungal immunity via regulation of RAC GTPase activity but also provides proof of concept for the treatment of invasive fungal infections by using IVT mRNA.

A Predictive Nomogram for Red Blood Cell Transfusion in Pheochromocytoma Surgery: A Study on Improving the Preoperative Management of Pheochromocytoma.

Purpose: Surgery is the major treatment option for pheochromocytoma but carries potential risks, including hemorrhage and hemodynamic instability. Even with laparoscopic adrenalectomy, intraoperative blood transfusion happens from time to time, but few studies have investigated risk factors. For the first time we develop and validate a nomogram for prediction of red blood cell transfusion in pheochromocytoma surgery. Methods: There were 246 patients in our center and 56 patients in Peking Union Medical College Hospital, who underwent pheochromocytoma surgery, enrolled in the study. We incorporated clinical and radiological risk factors, and presented this with a nomogram. Lasso regression model was used for feature selection. Logistic regression analysis was performed to identify the odd ratios. The performance of the nomogram was assessed with respect to its discrimination, calibration and clinical usefulness. Results: Thirty-two features were reduced to five, which were phenoxybenzamine use, phenoxybenzamine treatment duration, preinduction heart rate, tumor diameter and surgical procedure. The model showed good discrimination (C-index, 0.857; 95% CI, 0.781-0.836) and application in the validation sets also gave good discrimination (internal validation: C-index, 0.831; 95% CI, 0.750-0.822; external validation: C-index, 0.924; 95% CI, 0.766-1.000). Calibration tested with the Hosmer-Lemeshow test yielded a good agreement between prediction and observation (training P=0.358; internal validation P=0.205; external validation P=0.395). Odd ratios of phenoxybenzamine use, phenoxybenzamine treatment duration, preinduction HR, tumor diameter and open surgery were 13.32 (95% CI, 1.48-197.38; P = 0.034), 1.04 (95% CI, 0.99-1.08; P = 0.092), 1.04 (95% CI, 1.01-1.08; P=0.006), 1.03 (95% CI, 1.02-1.06; P<0.001), 17.13 (95% CI, 5.18-78.79; P<0.001), respectively. Decision curve analysis demonstrated the clinical usefulness of the nomogram. Conclusions: This study presents a nomogram that may be used to facilitate the prediction of red blood cell transfusion in pheochromocytoma surgery and help to do the preoperative management more efficiently.

Predictive CT features for the diagnosis of primary pulmonary mucoepidermoid carcinoma: comparison with squamous cell carcinomas and adenocarcinomas.

BACKGROUND: To determine the predictive CT imaging features for diagnosis in patients with primary pulmonary mucoepidermoid carcinomas (PMECs). MATERIALS AND METHODS: CT imaging features of 37 patients with primary PMECs, 76 with squamous cell carcinomas (SCCs) and 78 with adenocarcinomas were retrospectively reviewed. The difference of CT features among the PMECs, SCCs and adenocarcinomas was analyzed using univariate analysis, followed by multinomial logistic regression and receiver operating characteristic (ROC) curve analysis. RESULTS: CT imaging features including tumor size, location, margin, shape, necrosis and degree of enhancement were significant different among the PMECs, SCCs and adenocarcinomas, as determined by univariate analysis (P < 0.05). Only lesion location, shape, margin and degree of enhancement remained independent factors in multinomial logistic regression analysis. ROC curve analysis showed that the area under curve of the obtained multinomial logistic regression model was 0.805 (95%CI: 0.704-0.906). CONCLUSION: The prediction model derived from location, margin, shape and degree of enhancement can be used for preoperative diagnosis of PMECs.