GPR50 regulates neuronal development as a mitophagy receptor.

Neurons rely heavily on high mitochondrial metabolism to provide sufficient energy for proper development. However, it remains unclear how neurons maintain high oxidative phosphorylation (OXPHOS) during development. Mitophagy plays a pivotal role in maintaining mitochondrial quality and quantity. We herein describe that G protein-coupled receptor 50 (GPR50) is a novel mitophagy receptor, which harbors the LC3-interacting region (LIR) and is required in mitophagy under stress conditions. Although it does not localize in mitochondria under normal culturing conditions, GPR50 is recruited to the depolarized mitochondrial membrane upon mitophagy stress, which marks the mitochondrial portion and recruits the assembling autophagosomes, eventually facilitating the mitochondrial fragments to be engulfed by the autophagosomes. Mutations Δ502-505 and T532A attenuate GPR50-mediated mitophagy by disrupting the binding of GPR50 to LC3 and the mitochondrial recruitment of GPR50. Deficiency of GPR50 causes the accumulation of damaged mitochondria and disrupts OXPHOS, resulting in insufficient ATP production and excessive ROS generation, eventually impairing neuronal development. GPR50-deficient mice exhibit impaired social recognition, which is rescued by prenatal treatment with mitoQ, a mitochondrially antioxidant. The present study identifies GPR50 as a novel mitophagy receptor that is required to maintain mitochondrial OXPHOS in developing neurons.

Validation of a built-in software in automatically reconstructing the tomographic images of the levator ani muscle.

INTRODUCTION AND HYPOTHESIS: Transperineal ultrasound (TPUS) is an effective tool for evaluating the integrity of the levator ani muscle (LAM). Several operating steps are required to obtain the standard multi-slice image of the LAM, which is experience dependent and time consuming. This study was aimed at evaluating the feasibility and reproducibility of the built-in software, Smart-pelvic™, in reconstructing standard tomographic images of LAM from 3D/4D TPUS volumes. METHODS: This study was conducted at a tertiary teaching hospital, enrolling women who underwent TPUS. Tomographic images of the LAM were automatically reconstructed by Smart-pelvicTM and rated by two experienced observers as standard or nonstandard. The anteroposterior diameter (APD) of the levator hiatus was also measured on the mid-sagittal plane of the automatically and manually reconstructed images. The APD measurements of each approach were compared using Bland-Altman plots, and interclass correlation coefficient (ICC) was used to evaluate intra- and inter-observer reproducibility. Meanwhile, the time taken for the reconstruction process of both methods was also recorded. RESULTS: The ultrasound volume of a total of 104 patients were included in this study. Using Smart-pelvicTM, the overall success rate of the tomographic image reconstruction was 98%. Regarding measurements of APD, the ICC between the automatic and manual reconstruction methods was 0.99 (0.98, 0.99). The average time taken for reconstruction per case was 2.65 ± 0.52 s and 22.08 ± 3.45 s, respectively. CONCLUSIONS: Using Smart-pelvicTM to reconstruct tomographic images of LAM is feasible, and it can promote TPUS by reducing operator dependence and improving examination efficiency in a clinical setting.

Super-Structured Wet-Adhesive Hydrogel with Ultralow Swelling, Ultrahigh Burst Pressure Tolerance, and Anti-Postoperative Adhesion Properties for Tissue Adhesion.

Wet-adhesive hydrogels have been developed as an attractive strategy for tissue repair. However, achieving simultaneously low swelling and high burst pressure tolerance of wet-adhesive hydrogels is crucial for in vivo application which remains challenges. Herein, a novel super-structured porous hydrogel (denoted as PVA/PAAc-N+ ) is designed via facile moisture-induced phase separation-solvent exchange process for obtaining porous polyvinyl alcohol (PVA) hydrogel as dissipative layer and in situ photocuring technology for entangling quaternary ammonium-functionalized poly(acrylic acid)-based wet-adhesive layer (PAAc-N+ ) with the porous surface of PVA layer. Benefitting from the ionic crosslinking between quaternary ammonium ions and carboxylate ions in PAAc-N+ wet-adhesive layer as well as the high crystallinity induced by abundant hydrogen bonds of PVA layer, the hydrogel has unique ultralow swelling property (0.29) without sacrificing adhesion strength (63.1 kPa). The porous structure of PVA facilitates the mechanical interlock at the interface between PAAc-N+ wet-adhesive layer and tough PVA dissipative layer, leading to the ultrahigh burst pressure tolerance up to 493 mm Hg and effective repair for porcine heart rupture; the PVA layer surface of PVA/PAAc-N+ hydrogel can prevent postoperative adhesion. By integrating ultralow swelling, ultrahigh burst pressure tolerance, and anti-postoperative adhesion properties, PVA/PAAc-N+ hydrogel shows an appealing application prospect for tissue repair.

High-entropy oxides: an emerging anode material for lithium-ion batteries.

High entropy oxides (HEOs) have gained significant attention in multiple research fields, particularly in reversible energy storage. HEOs with rock-salt and spinel structures have shown excellent reversible capacity and longer cycle spans compared to traditional conversion-type anodes. However, research on HEOs and their electrochemical performance remains at an early stage. In this highlight, we review recent progress on HEO materials in the field of lithium-ion batteries (LIBs). Firstly, we introduce the synthesis methods of HEOs and some factors that affect the morphology and electrochemical properties of the synthesized materials. We then elaborate on the structural evolution of HEOs with rock-salt and spinel structures in lithium energy storage and summarize the relationship between morphology, pseudocapacitance effect, oxygen vacancy, and electrochemical performance. In the end, we give the challenges of HEO anodes for LIBs and present our opinions on how to guide the further development of HEOs for advanced anodes.

A pyridine modified naphthol hydrazone Schiff base chemosensor for Al3+ via intramolecular charge transfer process.

A pyridine modified naphthol hydrazone Schiff base chemosensor, NaPy, was prepared in a two-step process to detect aluminum ion (Al3+) in different samples. The probe shows a turn-off emission response towards Al3+ at a 1:1 binding stoichiometry via intramolecular charge transfer (ICT) mechanism, as validated by density functional theory (DFT) calculations and a series of spectroscopic measurements. The response time is slightly over one minute with a limit of detection (LOD) value of 0.164 µM, demonstrating the great sensitivity of the probe. It is also found that NaPy exhibits high selectivity towards Al3+ and resists interference from seventeen other cations. Application investigations in paper strips, water samples and HeLa cells suggest that NaPy can be used as an efficient probe for sensing Al3+ in real environmental samples and biosystems.

Validation of an automatic method for reconstruction, delineation, and measurement of levator hiatus in clinical practice.

OBJECTIVES: To evaluate the concordance between an automatic software program and manual evaluation in reconstructing, delineating, and measuring the levator hiatus (LH) on maximal Valsalva maneuver. METHODS: This was a retrospective study analyzing archived raw ultrasound imaging data of 100 patients underwent transperineal ultrasound (TPUS) examination. Each data were assessed by the automatic Smart Pelvic System software program and manual evaluation. The Dice similarity index (DSI), mean absolute distance (MAD), and Hausdorff distance (HDD) were calculated to quantify delineation accuracy of LH. Agreement between automatic and manual measurement of levator hiatus area was assessed by intraclass correlation coefficient (ICC) and Bland-Altman method. RESULTS: The satisfaction rate of automatic reconstruction was 94%. Six images were recognized as unsatisfactory reconstructed images for some gas in the rectum and anal canal. Compared with satisfactory reconstructed images, DSI of unsatisfactory reconstructed images was lower, MAD and HDD were larger (p = 0.001, p = 0.001, p = 0.006, respectively). The ICC was up to 0.987 in 94 satisfactory reconstructed images. CONCLUSIONS: The Smart Pelvic System software program had good performance in reconstruction, delineation, and measurement of LH on maximal Valsalva maneuver in clinical practice, despite misidentification of the border of posterior aspect of LH due to the influence of gas in the rectum.

Analysis of risk factors for lymph node metastasis and prognosis study in patients with early gastric cancer: A SEER data-based study.

Background: Lymph node status is an important factor in determining the prognosis of patients with early gastric cancer (EGC) and preoperative diagnosis of lymph node metastasis (LNM) has some limitations. This study explored the risk factors and independent prognostic factors of LNM in EGC patients and constructed a clinical prediction model to predict LNM. Methods: Clinicopathological data of EGC patients was collected from the public Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regression was used to identify risk factors for LNM in EGC patients. The performance of the LNM model was evaluated by C-index, calibration curve, receiver operating characteristic (ROC) curve, decision curve analysis (DCA) curve, and clinical impact curve (CIC) based on the results of multivariate regression to develop a nomogram. An independent data set was obtained from China for external validation. The Kaplan-Meier method and Cox regression model were used to identify potential prognostic factors for overall survival (OS) in EGC patients. Results: A total of 3993 EGC patients were randomly allocated to a training cohort (n=2797) and a validation cohort (n=1196). An external cohort of 106 patients from the Second Hospital of Lanzhou University was used for external validation. Univariate and multivariate logistic regression showed that age, tumor size, differentiation, and examined lymph nodes count (ELNC) were independent risk factors for LNM. Nomogram for predicting LNM in EGC patients was developed and validated. The predictive model had a good discriminatory performance with a concordance index (C-index) of 0.702 (95% CI: 0.679-0.725). The calibration plots showed that the predicted LNM probabilities were the same as the actual observations in both the internal validation cohort and external validation cohort. The AUC values for the training cohort, internal validation cohort and external validation cohort were 0.702 (95% CI: 0.679-0.725), 0.709 (95% CI: 0.674-0.744) and 0.750(95% CI: 0.607-0.892), respectively, and the DCA curves and CIC showed good clinical applicability. The Cox regression model identified age, sex, race, primary site, size, pathological type, LNM, distant metastasis, and ELNC were prognostic factors for OS in EGC patients, while a year at diagnosis, grade, marital status, radiotherapy, and chemotherapy were not independent prognostic factors. Conclusion: In this study, we identified risk factors and independent prognostic factors for the development of LNM in EGC patients, and developed a relatively accurate model to predict the development of LNM in EGC patients.

Value of Contrast-Enhanced Ultrasound Parameters in the Evaluation of Adnexal Masses with Ovarian-Adnexal Reporting and Data System Ultrasound.

OBJECTIVE: The aim of this study was to determine whether incorporating qualitative parameters of contrast-enhanced ultrasound (CEUS) can increase the accuracy of adnexal lesion assessments with Ovarian-Adnexal Reporting and Data System (O-RADS) ultrasound category 4 or 5. METHODS: Retrospective analysis of patients with adnexal masses who underwent conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) examinations between January and August of 2020. The study investigators reviewed and analyzed the morphological features of each mass before categorizing the US images independently according to the O-RADS system published by the American College of Radiology. In the CEUS analysis, the initial time and intensity of enhancement involving the wall and/or septation of the mass were compared with the uterine myometrium. Internal components of each mass were observed for signs of enhancement. The sensitivity, specificity, and Youden's index were calculated as the contrast variables and O-RADS. RESULTS: Receiver operating characteristic curve analysis revealed that the best cutoff value was higher than O-RADS 4. When information on the extent of enhancement was applied to selectively upgrade O-RADS category 4 and selectively downgrade O-RADS category 5, the overall sensitivity increased to 90.2%, while the level of specificity (91.3%) remained the same. CONCLUSION: Incorporating additional information from CEUS with respect to the extent of enhancement helped to improve the sensitivity of O-RADS category 4 and 5 masses without loss of specificity.

Multiple Electronic Phases Coexisting under Inhomogeneous Strains in the Correlated Insulator.

Monolayer transition metal dichalcogenides (TMDs) can host exotic phenomena such as correlated insulating and charge-density-wave (CDW) phases. Such properties are strongly dependent on the precise atomic arrangements. Strain, as an effective tuning parameter in atomic arrangements, has been widely used for tailoring material's structures and related properties, yet to date, a convincing demonstration of strain-induced dedicate phase transition at nanometer scale in monolayer TMDs has been lacking. Here, a strain engineering technique is developed to controllably introduce out-of-plane atomic deformations in monolayer CDW material 1T-NbSe2 . The scanning tunneling microscopy and spectroscopy (STM and STS) measurements, accompanied by first-principles calculations, demonstrate that the CDW phase of 1T-NbSe2 can survive under both tensile and compressive strains even up to 5%. Moreover, significant strain-induced phase transitions are observed, i.e., tensile (compressive) strains can drive 1T-NbSe2 from an intrinsic-correlated insulator into a band insulator (metal). Furthermore, experimental evidence of the multiple electronic phase coexistence at the nanoscale is provided. The results shed new lights on the strain engineering of correlated insulator and useful for design and development of strain-related nanodevices.

Two-dimensional shear wave elastography utilized in patients with ascites: a more reliable method than transient elastography for noninvasively detecting the liver stiffness-an original study with 170 patients.

Background: Two dimensional shear wave elastography (2D-SWE) is an ultrasound elastography technique based on shear waves implemented on a diagnostic ultrasound system. Transient elastography (TE) uses an ultrasound displacement M-mode and A-mode image produced by the system. So, TE mechanically induced impulse at tissue surface and difficultly across water. This paper compared the reliability and reproducibility of 2D-SWE with that of TE in patients with chronic hepatic disease. Comparisons were made in terms of the success rate, reliability, reproducibility, operation time, and influence of operator experience. Methods: A total of 170 patients were included in this study. Participants underwent 2D-SWE and TE performed by 2 different operators (a novice and veteran) on the same day. Nonparametric statistical tests were used to compare the technical success rate and reliable measurement rate, and inter-operator reproducibility was evaluated using intra-class correlation coefficients (ICCs). Results: The 2D-SWE technique showed a higher technical success rate than TE. Either 2D-SWE or TE can be utilized in patients with ascites lamella of less than 10 mm or ascites lamella plus skin-capsular distance of less than 25 mm. However, although the reliability rate of liver stiffness measurement with 2D-SWE did not significantly differ between the novice and veteran operators, for TE, there was a significant difference when body mass index (BMI) ≤25 kg/m2. When performed by the novice and veteran operators, 2D-SWE and TE both showed excellent inter-operator agreement, with ICCs of 0.968 and 0.973, respectively. Both 2D-SWE and TE displayed reliable measurement and excellent reproducibility in patients with chronic liver disease, were minimally influenced by operator experience. Conclusions: 2D-SWE may be a more reliable method for clinical application in noninvasive detecting the liver stiffness.

Unveiling Electronic Behaviors in Heterochiral Charge-Density-Wave Twisted Stacking Materials with 1.25 nm Unit Dependence.

Layered charge-density-wave (CDW) materials have gained increasing interest due to their CDW stacking-dependent electronic properties for practical applications. Among the large family of CDW materials, those with star of David (SOD) patterns are very important due to the potentials for quantum spin liquid and related device applications. However, the spatial extension and the spin coupling information down to the nanoscale remain elusive. Here, we report the study of heterochiral CDW stackings in bilayer (BL) NbSe2 with high spatial resolution. We reveal that there exist well-defined heterochiral stackings, which have inhomogeneous electronic states among neighboring CDW units (star of David, SOD), significantly different from the homogeneous electronic states in the homochiral stackings. Intriguingly, the different electronic behaviors are spatially localized within each SOD with a unit size of 1.25 nm, and the gap sizes are determined by the different types of SOD stackings. Density functional theory (DFT) calculations match the experimental measurements well and reveal the SOD-stacking-dependent correlated electronic states and antiferromagnetic/ferromagnetic couplings. Our findings give a deep understanding of the spatial distribution of interlayer stacking and the delicate modulation of the spintronic states, which is very helpful for CDW-based nanoelectronic devices.

An immune, stroma, and epithelial-mesenchymal transition-related signature for predicting recurrence and chemotherapy benefit in stage II-III colorectal cancer.

BACKGROUND: Debates exist on the treatment decision of the stage II/III colorectal cancer (CRC) due to the insufficiency of the current TNM stage-based risk stratification system. Epithelial-mesenchymal transition (EMT) and tumor microenvironment (TME) have both been linked to CRC progression in recent studies. We propose to improve the prognosis prediction of CRC by integrating TME and EMT. METHODS: In total, 2382 CRC patients from seven datasets and one in-house cohort were collected, and 1640 stage II/III CRC patients with complete survival information and gene expression profiles were retained and divided into a training cohort and three independent validation cohorts. Integrated analysis of 398 immune, stroma, and epithelial-mesenchymal transition (ISE)-related genes identified an ISE signature independently associated with the recurrence of CRC. The underlying biological mechanism of the ISE signature and its influence on adjuvant chemotherapy was further explored. RESULTS: We constructed a 26-gene signature which was significantly associated with poor outcome in Training cohort (p < 0.001, HR [95%CI] = 4.42 [3.25-6.01]) and three independent validation cohorts (Validation cohort-1: p < 0.01, HR [95%CI] = 1.70 [1.15-2.51]; Validation cohort-2: p < 0.001, HR [95% CI] = 2.30 [1.67-3.16]; Validation cohort-3: p < 0.01, HR [95% CI] = 2.42 [1.25-4.70]). After adjusting for known clinicopathological factors, multivariate cox analysis confirmed the ISE signature's independent prognostic value. Subgroup analysis found that stage III patients with low ISE score might benefit from adjuvant chemotherapy (p < 0.001, HR [95%CI] = 0.15 [0.04-0.55]). Hypergeometric test and enrichment analysis revealed that low-risk group was enriched in thr immune pathway while high-risk group was associated with the EMT pathway and CMS4 subtype. CONCLUSION: We proposed an ISE signature for robustly predicting the recurrence of stage II/III CRC and help treatment decision by identifying patients who will not benefit from current standard treatment.

CT-based radiogenomic analysis dissects intratumor heterogeneity and predicts prognosis of colorectal cancer: a multi-institutional retrospective study.

BACKGROUND: This study aimed to develop a radiogenomic prognostic prediction model for colorectal cancer (CRC) by investigating the biological and clinical relevance of intratumoural heterogeneity. METHODS: This retrospective multi-cohort study was conducted in three steps. First, we identified genomic subclones using unsupervised deconvolution analysis. Second, we established radiogenomic signatures to link radiomic features with prognostic subclone compositions in an independent radiogenomic dataset containing matched imaging and gene expression data. Finally, the prognostic value of the identified radiogenomic signatures was validated using two testing datasets containing imaging and survival information collected from separate medical centres. RESULTS: This multi-institutional retrospective study included 1601 patients (714 females and 887 males; mean age, 65 years ± 14 [standard deviation]) with CRC from 5 datasets. Molecular heterogeneity was identified using unsupervised deconvolution analysis of gene expression data. The relative prevalence of the two subclones associated with cell cycle and extracellular matrix pathways identified patients with significantly different survival outcomes. A radiogenomic signature-based predictive model significantly stratified patients into high- and low-risk groups with disparate disease-free survival (HR = 1.74, P = 0.003). Radiogenomic signatures were revealed as an independent predictive factor for CRC by multivariable analysis (HR = 1.59, 95% CI:1.03-2.45, P = 0.034). Functional analysis demonstrated that the 11 radiogenomic signatures were predominantly associated with extracellular matrix and immune-related pathways. CONCLUSIONS: The identified radiogenomic signatures might be a surrogate for genomic signatures and could complement the current prognostic strategies.

Management of breech presentation with a large pelvic hydatid cyst in late pregnancy in Tibet: a case report.

BACKGROUND: Hydatid cystic disease (HCD) is primarily a disease of sheep and cattle. Human beings are accidental hosts. It is prevalent in the Tibet Autonomous Region (TAR) of China. In pregnancy, it can cause many complications. CASE PRESENTATION: We present a multigravida with breech presentation at 37 weeks of pregnancy in whom a large pelvic hydatid cyst and multiple hepatic hydatids were diagnosed by ultrasonography. The large pelvic hydatid cyst was drained through the posterior fornix under the guidance of ultrasound, and an external cephalic version was performed. A healthy baby was delivered vaginally with head presentation at term. CONCLUSION: HCD during pregnancy presents with management difficulty. It is important to formulate individualized treatment plans according to the actual situation of the patient and the local level of treatment.

Predicting prognosis and immunotherapy response among colorectal cancer patients based on a tumor immune microenvironment-related lncRNA signature.

Long non-coding RNAs (lncRNAs) remodel the tumor immune microenvironment (TIME) by regulating the functions of tumor-infiltrating immune cells. It remains uncertain the way that TIME-related lncRNAs (TRLs) influence the prognosis and immunotherapy response of colorectal cancer (CRC). Aiming at providing survival and immunotherapy response predictions, a CRC TIME-related lncRNA signature (TRLs signature) was developed and the related potential regulatory mechanisms were explored with a comprehensive analysis on gene expression profiles from 97 immune cell lines, 61 CRC cell lines and 1807 CRC patients. Stratifying CRC patients with the TRLs signature, prolonged survival was observed in the low-risk group, while the patients in the high-risk group had significantly higher pro-tumor immune cells infiltration and higher immunotherapy response rate. Through the complex TRLs-mRNA regulation network, immunoregulation pathways and immunotherapy response pathways were found to be differently activated between the groups. In conclusion, the CRC TRLs signature is capable of making prognosis and immunotherapy response predictions, which may find application in stratifying patients for immunotherapy in the bedside.

A Transcription Factor Signature Can Identify the CMS4 Subtype and Stratify the Prognostic Risk of Colorectal Cancer.

Background: Colorectal cancer (CRC) is a heterogeneous disease, and current classification systems are insufficient for stratifying patients with different risks. This study aims to develop a generalized, individualized prognostic consensus molecular subtype (CMS)-transcription factors (TFs)-based signature that can predict the prognosis of CRC. Methods: We obtained differentially expressed TF signature and target genes between the CMS4 and other CMS subtypes of CRC from The Cancer Genome Atlas (TCGA) database. A multi-dimensional network inference integrative analysis was conducted to identify the master genes and establish a CMS4-TFs-based signature. For validation, an in-house clinical cohort (n = 351) and another independent public CRC cohort (n = 565) were applied. Gene set enrichment analysis (GSEA) and prediction of immune cell infiltration were performed to interpret the biological significance of the model. Results: A CMS4-TFs-based signature termed TF-9 that includes nine TF master genes was developed. Patients in the TF-9 high-risk group have significantly worse survival, regardless of clinical characteristics. The TF-9 achieved the highest mean C-index (0.65) compared to all other signatures reported (0.51 to 0.57). Immune infiltration revealed that the microenvironment in the high-risk group was highly immune suppressed, as evidenced by the overexpression of TIM3, CD39, and CD40, suggesting that high-risk patients may not directly benefit from the immune checkpoint inhibitors. Conclusions: The TF-9 signature allows a more precise categorization of patients with relevant clinical and biological implications, which may be a valuable tool for improving the tailoring of therapeutic interventions in CRC patients.

Segmentation only uses sparse annotations: Unified weakly and semi-supervised learning in medical images.

Since segmentation labeling is usually time-consuming and annotating medical images requires professional expertise, it is laborious to obtain a large-scale, high-quality annotated segmentation dataset. We propose a novel weakly- and semi-supervised framework named SOUSA (Segmentation Only Uses Sparse Annotations), aiming at learning from a small set of sparse annotated data and a large amount of unlabeled data. The proposed framework contains a teacher model and a student model. The student model is weakly supervised by scribbles and a Geodesic distance map derived from scribbles. Meanwhile, a large amount of unlabeled data with various perturbations are fed to student and teacher models. The consistency of their output predictions is imposed by Mean Square Error (MSE) loss and a carefully designed Multi-angle Projection Reconstruction (MPR) loss. Extensive experiments are conducted to demonstrate the robustness and generalization ability of our proposed method. Results show that our method outperforms weakly- and semi-supervised state-of-the-art methods on multiple datasets. Furthermore, our method achieves a competitive performance with some fully supervised methods with dense annotation when the size of the dataset is limited.

SQLE, A Key Enzyme in Cholesterol Metabolism, Correlates With Tumor Immune Infiltration and Immunotherapy Outcome of Pancreatic Adenocarcinoma.

Background: Pancreatic adenocarcinoma (PAAD) is a treatment-refractory cancer with poor prognosis. Accumulating evidence suggests that squalene epoxidase (SQLE) plays a pivotal role in the development and progression of several cancer types in humans. However, the function and underlying mechanism of SQLE in PAAD remain unclear. Methods: SQLE expression data were downloaded from The Cancer Genome Atlas and the Genotype-Tissue Expression database. SQLE alterations were demonstrated based on the cBioPortal database. The upstream miRNAs regulating SQLE expression were predicted using starBase. The function of miRNA was validated by Western blotting and cell proliferation assay. The relationship between SQLE expression and biomarkers of the tumor immune microenvironment (TME) was analyzed using the TIMER and TISIDB databases. The correlation between SQLE and immunotherapy outcomes was assessed using Tumor Immune Dysfunction and Exclusion. The log-rank test was performed to compare prognosis between the high and low SQLE groups. Results: We demonstrated a potential oncogenic role of SQLE. SQLE expression was upregulated in PAAD, and it predicted poor disease-free survival (DFS) and overall survival (OS) in patients with PAAD. "Amplification" was the dominant type of SQLE alteration. In addition, this alteration was closely associated with the OS, disease-specific survival, DFS, and progression-free survival of patients with PAAD. Subsequently, hsa-miR-363-3p was recognized as a critical microRNA regulating SQLE expression and thereby influencing PAAD patient outcome. In vitro experiments suggested that miR-363-3p could knock down the expression of SQLE and inhibit the proliferation of PANC-1. SQLE was significantly associated with tumor immune cell infiltration, immune checkpoints (including PD-1 and CTLA-4), and biomarkers of the TME. KEGG and GO analyses indicated that cholesterol metabolism-associated RNA functions are implicated in the mechanisms of SQLE. SQLE was inversely associated with cytotoxic lymphocytes and predicted immunotherapy outcomes. Conclusions: Collectively, our results indicate that cholesterol metabolism-related overexpression of SQLE is strongly correlated with tumor immune infiltration and immunotherapy outcomes in patients with PAAD.

Multi-Size Deep Learning Based Preoperative Computed Tomography Signature for Prognosis Prediction of Colorectal Cancer.

Background: Preoperative and postoperative evaluation of colorectal cancer (CRC) patients is crucial for subsequent treatment guidance. Our study aims to provide a timely and rapid assessment of the prognosis of CRC patients with deep learning according to non-invasive preoperative computed tomography (CT) and explore the underlying biological explanations. Methods: A total of 808 CRC patients with preoperative CT (development cohort: n = 426, validation cohort: n = 382) were enrolled in our study. We proposed a novel end-to-end Multi-Size Convolutional Neural Network (MSCNN) to predict the risk of CRC recurrence with CT images (CT signature). The prognostic performance of CT signature was evaluated by Kaplan-Meier curve. An integrated nomogram was constructed to improve the clinical utility of CT signature by combining with other clinicopathologic factors. Further visualization and correlation analysis for CT deep features with paired gene expression profiles were performed to reveal the molecular characteristics of CRC tumors learned by MSCNN in radiographic imaging. Results: The Kaplan-Meier analysis showed that CT signature was a significant prognostic factor for CRC disease-free survival (DFS) prediction [development cohort: hazard ratio (HR): 50.7, 95% CI: 28.4-90.6, p < 0.001; validation cohort: HR: 2.04, 95% CI: 1.44-2.89, p < 0.001]. Multivariable analysis confirmed the independence prognostic value of CT signature (development cohort: HR: 30.7, 95% CI: 19.8-69.3, p < 0.001; validation cohort: HR: 1.83, 95% CI: 1.19-2.83, p = 0.006). Dimension reduction and visualization of CT deep features demonstrated a high correlation with the prognosis of CRC patients. Functional pathway analysis further indicated that CRC patients with high CT signature presented down-regulation of several immunology pathways. Correlation analysis found that CT deep features were mainly associated with activation of metabolic and proliferative pathways. Conclusions: Our deep learning based preoperative CT signature can effectively predict prognosis of CRC patients. Integration analysis of multi-omic data revealed that some molecular characteristics of CRC tumor can be captured by deep learning in CT images.

DNA Repair-Related Gene Signature in Predicting Prognosis of Colorectal Cancer Patients.

Background: Increasing evidence have depicted that DNA repair-related genes (DRGs) are associated with the prognosis of colorectal cancer (CRC) patients. Thus, the aim of this study was to evaluate the impact of DNA repair-related gene signature (DRGS) in predicting the prognosis of CRC patients. Method: In this study, we retrospectively analyzed the gene expression profiles from six CRC cohorts. A total of 1,768 CRC patients with complete prognostic information were divided into the training cohort (n = 566) and two validation cohorts (n = 624 and 578, respectively). The LASSO Cox model was applied to construct a prediction model. To further validate the clinical significance of the model, we also validated the model with Genomics of Drug Sensitivity in Cancer (GDSC) and an advanced clear cell renal cell carcinoma (ccRCC) immunotherapy data set. Results: We constructed a prognostic DRGS consisting of 11 different genes to stratify patients into high- and low-risk groups. Patients in the high-risk groups had significantly worse disease-free survival (DFS) than those in the low-risk groups in all cohorts [training cohort: hazard ratio (HR) = 2.40, p < 0.001, 95% confidence interval (CI) = 1.67-3.44; validation-1: HR = 2.20, p < 0.001, 95% CI = 1.38-3.49 and validation-2 cohort: HR = 2.12, p < 0.001, 95% CI = 1.40-3.21). By validating the model with GDSC, we could see that among the chemotherapeutic drugs such as oxaliplatin, 5-fluorouracil, and irinotecan, the IC50 of the cell line in the low-risk group was lower. By validating the model with the ccRCC immunotherapy data set, we can clearly see that the overall survival (OS) of the objective response rate (ORR) with complete response (CR) and partial response (PR) in the low-risk group was the best. Conclusions: DRGS is a favorable prediction model for patients with CRC, and our model can predict the response of cell lines to chemotherapeutic agents and potentially predict the response of patients to immunotherapy.