MST4 as a novel therapeutic target for autophagy and radiosensitivity in gastric cancer.

BACKGROUND: Mammalian ste20-like kinase 4 (MST4) and autophagy have been implicated in ailments such as inflammatory and cancers. METHODS: In this study, the expression of MST4 data was extracted from TCGA, GTEx, and GEPIA. The infiltration of immune cells and methylation level of MST4 in tumor and normal tissues were extracted from GEPIA 2021, TISIDB, UALCAN, EWAS, MethSurv, and MEXPRESS database. We also predict the efficacy of outcome prediction with receiver operating characteristic curve (ROC). All proteins expressions of MST4, P62, and LC3 were detected by immunohistochemistry (IHC) in paired Gastric cancer (GC) and para-cancerous normal tissue samples. We verify the effects of MST4 on irradiation-induced gastric death, and also investigate effects of MST4 activating autophagy in GC cell lines with various in vitro assays using western blotting. RESULTS: We have confirmed the high transcription level of MST4 from TCGA, USLCAN, HPA, and other portals, but a rapid decrease in protein level. More, MST4 can be considered as an independent prognostic molecule, which has significant prognostic significance in tumor grade, anti-tumor treatment, histological type, and time-dependent ROC curve. The methylation degree of MST4 promoter region in tumor is much lower than that in normal tissue, which may be the main reason for the remarkably high transcription level of MST4. In addition, MST4 transcription level was significantly inversely proportional to the infiltration level of most immune cells. The MST4 up-regulation and the positive association of MST4 with autophagy expression were cross-validated in open-access datasets. CONCLUSIONS: MST4, as an autophagy-associated protein, plays a potential role in inducing cell death by increasing protein content in radiotherapy.

circ_0006528 promotes nonsmall cell lung cancer progression by sponging miR-892a and regulating NRAS expression.

Micro-RNAs play essential roles in developing and progressing nonsmall cell lung cancer (NSCLC) and drug resistance. Nevertheless, the functions and mechanisms are partly explored. Therefore, the present study analyzes the effect of circ_0006528 and the mechanism of regulation of NSCLC cell progression by sponging miR-892a to regulate neuroblastoma rat sarcoma viral oncogene (NRAS) expression. Initially, circ_0006528 is identified using divergent primers-based PCR and RNase R exonuclease treatments. After administration of the designed circ_0006528-specific siRNA, the RT-qPCR analysis is used to determine the interference efficiency of siRNA. At the same time, cell growth, invasion, and migration are assessed by 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT), Transwell, and scratch assays in the NSCLC cell lines (secretory pathway Ca2+-ATPase isoform 1 [SPCA-1] and A549) in vitro, respectively. Further, miR-892a inhibitor is added to the cells for functional recovery assay. Finally, the xenograft mouse model is constructed to explore the effect of circ_0006528 on tumor growth in vivo. The RT-qPCR analysis in 66 pairs of NSCLC cancer and noncancerous tissues revealed that circ_0006528 is highly expressed in NSCLC patient tissues. The RNase R experiments revealed that HSA_circ_0006528 is unaffected by RNase R exonuclease. MTT assay showed that knockdown of hsa_circ_0006528 by siRNA significantly decreased cell proliferation and viability in A549 and SPCA-1 cells. The luciferase reporter assay showed direct binding of hsa_circ_0006528 to miR-892a, and miR-892a targets binding NRAS. In addition, the miR-892a inhibitor terminated the hsa_circ_0006528 siRNA, triggering inhibition of proliferation, invasion, and migration of NSCLC cells. In summary, the study revealed that the knockout of hsa_circ_0006528 downregulation of NRAS expression by sponging miR-892a inhibited NSCLC cell growth and invasion.

Noninvasive Prediction of Ki-67 Expression in Hepatocellular Carcinoma Using Machine Learning-Based Ultrasomics: A Multicenter Study.

OBJECTIVES: To investigate the ability of ultrasomics to predict Ki-67 expression in hepatocellular carcinoma (HCC). METHODS: A total of 244 patients from three hospitals were retrospectively recruited (training dataset, n = 168; test dataset, n = 43; and validation dataset, n = 33). Lesion segmentation of the ultrasound images was performed manually by two radiologists. In total, 1409 ultrasomics features were extracted. Feature selection was conducted using the intra-class correlation coefficient, variance threshold, mutual information, and recursive feature elimination plus eXtreme Gradient Boosting. The support vector machine was combined with the learning curve and grid search parameter tuning to construct the clinical, ultrasomics, and combined models. The predictive performance of the models was assessed using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity and accuracy. RESULTS: The ultrasomics model performed well on the training, test, and validation datasets. The AUC (95% confidence interval [CI]) for these datasets were 0.955 (0.912-0.981), 0.861 (0.721-0.947), and 0.665 (0.480-0.819), respectively. The combination of ultrasomics and clinical features significantly improved model performance on all three datasets. The AUC (95% CI), sensitivity, specificity, and accuracy were 0.986 (0.955-0.998), 0.973, 0.840, and 0.869 on the training dataset; 0.871 (0.734-0.954), 0.750, 0.829, and 0.814 on the test dataset; and 0.742 (0.560-0.878), 0.714, 0.808, and 0.788 on the validation dataset, respectively. CONCLUSIONS: Ultrasomics was proved to be a potential noninvasive method to predict Ki-67 expression in HCC.

The polymorphic terminal-loop of pre-miR-1307 binding with MBNL1 contributes to colorectal carcinogenesis via interference with Dicer1 recruitment.

Colorectal cancer (CRC) is one of the most common malignancies in the world. Studies have demonstrated that single nucleotide polymorphisms (SNPs) in microRNA genes (miRSNPs) are involved in the occurrence of cancers. However, the relationship between the miRSNPs within the terminal-loops of microRNA precursors and the development of CRC is still largely unknown. In this study, we found that a miRSNP rs7911488 T>C in the terminal-loop of pre-miR-1307 was significantly associated with the occurrence of CRC. The C allele of rs7911488 is more prevalent in CRC patients than in healthy controls (P < 0.001), and this C allele prevalence is related to low level of miR-1307 expression. A RNA-binding protein MBNL1 binds with a 'UGCUGC' motif in the terminal-loop of the C-allelic pre-miR-1307 and blocks Dicer processing, resulting in downregulation of miR-1307 expression. Consequently, the antiapoptosis protein Bcl2, which is a direct target of miR-1307, is overexpressed in CRC. Furthermore, MBNL1 participates in processing of both C-allelic and T-allelic pre-miR-1307. In summary, our results show that rs7911488 C-allelic pre-miR-1307 binds to MBNL1 and infers with Dicer processing, leading to reduced miR-1307 and increased Bcl2 expression, thus representing an important process in the initiation of CRC.

Five functional polymorphisms of B7/CD28 co-signaling molecules alter susceptibility to colorectal cancer.

Polymorphisms within the 3'-untranslated region (3'-UTR) of genes have been proved to contribute to the risk of cancers. Here, we determined 16 putatively functional polymorphisms in the 3'-UTR of 11 B7/CD28 genes in 382 colorectal cancer patients and 714 healthy controls. Statistical analysis revealed that ICOS rs4404254-C-allele carriers (p=0.0014), rs1559931-A-allele carriers (p=0.0027), and rs4675379-C-allele carriers (p=0.026) were significantly fewer in patients than those in controls. B7-H4-rs13505-GG homozygotes were more prevalent in patients (p=0.03). CD80-rs7628626-GT was apparently less in the patients with lymph node metastasis (p=0.004) or in advanced stage (p=0.037). Furthermore, we found that these polymorphisms impacted the regulatory role of miR-21-3p, miR-186-5p, miR-323b-5p, miR-1207-5p, miR-1279, miR-2117, and miR-3692-3p in the expression of the B7/CD28 molecules. Our findings suggest that rs7628626, rs13505, rs4404254, rs1559931, and rs4675379, through disrupting the regulatory role of miRNAs in the expression of B7/CD28 molecules, contribute to the occurrence and progress of colorectal cancer.

High-frequency ultrasound in patients with seronegative rheumatoid arthritis.

This study aimed to investigate the value of high-frequency ultrasound (HFUS) in differentiation of the seronegative rheumatoid arthritis (SNRA) and osteoarthritis (OA) and in the diagnosis of SNRA. 83 patients diagnosed with SNRA (SNRA group) and 40 diagnosed with OA (OA group) who received HFUS were retrospectively analyzed. The grayscale (GS) scores, power Doppler (PD) scores, and bone erosion (BE)scores were recorded, and added up to calculate the total scores of US variables. The correlations of the total scores of US variables with the 28-joint disease activity score (DAS28), erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) were analyzed. The diagnostic efficacy of the total scores of US variables for SNRA was assessed. In the SNRA group, the detection rate of abnormal US findings in the joints and tendons by GS and PD as well as BE was higher than those in the OA group. There were significant differences between the two groups in GS scores and PD scores of joints and tendons, and BE scores of joints (P < 0.05). In the SNRA group, the total scores of most US variables were positively correlated with CRP, ESR, and DAS28 (P < 0.05), while such correlations were not observed in the OA group (P > 0.05). Among different US variables, the diagnostic value of total PD scores of the joints was the highest for SNRA. HFUS could be used to differentiate SNRA from OA and make a diagnosis of SNRA based on joint and tendon synovial sheath assessment.

Contrast-Enhanced Ultrasound Parameters and D-Dimer: New Prognostic Parameters for Diffuse Large B-Cell Lymphoma.

Objective: To investigate the predictive role of contrast-enhanced ultrasonography (CEUS) plus D-dimer levels in the prognosis of patients with diffuse large B-cell lymphoma (DLBCL). Methods: CEUS was applied to assess lymph nodes in 186 patients with confirmed DLBCL. The clinical data and laboratory indicators were collected from these patients, and a retrospective analysis was conducted on the relationship between the quantitative parameters of CEUS (TTP, PI, AUC, WOT), D-dimer levels, and clinical features of the DLBCL patients. The Cox regression model was used for univariate and multivariate analyses for the risk factors associated with the prognosis. Results: There was an increase of D-dimer levels in advanced DLBCL patients, who were combined with a significant reduction in TTP and WOT and a significant increase in PI and AUC. D-dimer levels and quantitative parameters of CEUS were strongly correlated with the Ann Arbor, B symptoms, International Prognostic Index (IPI), LDH and CRP levels. The results of the Cox regression model indicated that D-dimer levels, TTP and PI, the quantitative parameters of CEUS, were important prognostic factors for DLBCL. Conclusion: CEUS results and D-dimer levels can be used as independent prognostic factors for DLBCL.

Evaluation of tenosynovitis in patients with seronegative rheumatoid arthritis using microvascular flow imaging.

OBJECTIVES: The purpose of this research was investigate the potential use of MVFI (microvascular flow imaging) in the assessment of tenosynovitis in cases with SNRA (seronegative rheumatoid arthritis). METHODS: Fifty-six SNRA cases and 20 HCs (healthy controls) were enrolled, and all of them were subjected to ultrasonographic examination of the compartments I-VI of the extensor tendons of the wrist, flexor carpi radialis and flexor tendons of the five digits. Each tendon synovial sheath was semi-quantitatively scored by GS (gray-scale) ultrasound, PD (power Doppler) ultrasound, and MVFI. The PD and MVFI scores for each tendon synovial sheath were added up for each patient to get the total scores. GS scores, PD scores, and MVFI scores of tendon synovial sheaths were compared between the two groups. The correlations of total PD scores and total MVFI scores with DAS28 (disease activity scores in 28 joints), ESR (erythrocyte sedimentation rate), and CRP (C-reactive protein) were analyzed. RESULTS: (1) In the HC group (480 tendons), GS revealed abnormalities in 29 (6.04%) tendon synovial sheaths. The GS score was 1.03 ± 0.18 with the predominance of GS grade 1 (96.55%). In the SNRA group (1,344 tendons), GS detected abnormalities in 418 tendon synovial sheaths (31.10%). The GS score was 1.97 ± 0.53 with the predominance of GS grade 2 (71.77%). There were significant differences in the GS examination rate and grade for tenosynovitis between the two groups (P < 0.05). (2) In the SNRA group, involvement of the extensor carpi ulnaris in the 6th dorsal compartment was the most common among all extensor tendons; the flexor tendon of the third digit was the most commonly affected among all flexor tendons. (3) In the HC group, the MVFI and PD scores were 0 for tendon synovial sheaths upon GS examination. In the SNRA group, the blood flow display rate of abnormal tendon synovial sheaths indicated by GS was 83.49% and 64.59% upon MVFI and PD, respectively. The results of the two imaging techniques were significantly different (P < 0.05). The blood flow grade of abnormal tendon synovial sheaths indicated by GS was significantly different between MVFI and PD (P < 0.05), which was higher upon MVFI than PD. (4) The total MVFI score and the total PD score in the SNRA group were correlated positively with CRP, ESR and DAS28 (P < 0.05). CONCLUSION: MVFI is a more sensitive way in detection of blood flow in the tendon synovial sheaths of SNRA cases, which may be used in clinic to evaluate disease activity and tenosynovitis in SNRA cases.

Ultrasomics prediction for cytokeratin 19 expression in hepatocellular carcinoma: A multicenter study.

Objective: The purpose of this study was to investigate the preoperative prediction of Cytokeratin (CK) 19 expression in patients with hepatocellular carcinoma (HCC) by machine learning-based ultrasomics. Methods: We retrospectively analyzed 214 patients with pathologically confirmed HCC who received CK19 immunohistochemical staining. Through random stratified sampling (ratio, 8:2), patients from institutions I and II were divided into training dataset (n = 143) and test dataset (n = 36), and patients from institution III served as external validation dataset (n = 35). All gray-scale ultrasound images were preprocessed, and then the regions of interest were then manually segmented by two sonographers. A total of 1409 ultrasomics features were extracted from the original and derived images. Next, the intraclass correlation coefficient, variance threshold, mutual information, and embedded method were applied to feature dimension reduction. Finally, the clinical model, ultrasonics model, and combined model were constructed by eXtreme Gradient Boosting algorithm. Model performance was assessed by area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. Results: A total of 12 ultrasomics signatures were used to construct the ultrasomics models. In addition, 21 clinical features were used to construct the clinical model, including gender, age, Child-Pugh classification, hepatitis B surface antigen/hepatitis C virus antibody (positive/negative), cirrhosis (yes/no), splenomegaly (yes/no), tumor location, tumor maximum diameter, tumor number, alpha-fetoprotein, alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, glutamyl-transpeptidase, albumin, total bilirubin, conjugated bilirubin, creatinine, prothrombin time, fibrinogen, and international normalized ratio. The AUC of the ultrasomics model was 0.789 (0.621 - 0.907) and 0.787 (0.616 - 0.907) in the test and validation datasets, respectively. However, the performance of the combined model covering clinical features and ultrasomics signatures improved significantly. Additionally, the AUC (95% CI), sensitivity, specificity, and accuracy were 0.867 (0.712 - 0.957), 0.750, 0.875, 0.861, and 0.862 (0.703 - 0.955), 0.833, 0.862, and 0.857 in the test dataset and external validation dataset, respectively. Conclusion: Ultrasomics signatures could be used to predict the expression of CK19 in HCC patients. The combination of clinical features and ultrasomics signatures showed excellent effects, which significantly improved prediction accuracy and robustness.

Safety of Anlotinib Capsules Combined with PD-1 Inhibitor Camrelizumab in the Third-Line Treatment of Advanced Non-Small-Cell Lung Cancer and Their Effect on Serum Tumor Markers.

Objective: To explore the safety of anlotinib capsules combined with the PD-1 inhibitor (camrelizumab) in the third-line treatment of advanced non-small-cell lung cancer (NSCLC) and their effect on serum tumor markers. Methods: 88 patients with advanced NSCLC treated in the Oncology Department of our hospital from December 2018 to December 2019 were selected as research subjects and randomly and equally split into the single treatment group (STG) and combined treatment group (CTG). The levels of serum tumor markers after treatment were detected in both groups, and the incidence of adverse reactions during treatment was recorded. Results: Compared with the STG, CTG achieved obviously higher total effective rate (P < 0.05), lower total incidence of adverse reactions (P < 0.05), lower levels of serum tumor markers and average CFS score (P < 0.001), and higher average KPS score (P < 0.001). Conclusion: Application of anlotinib capsules combined with the PD-1 inhibitor (camrelizumab) in the third-line treatment of advanced NSCLC can effectively reduce the levels of serum tumor markers and cancer fatigue degree of patients, with a better effect than that of simple anlotinib treatment. In addition, further research of the combined treatment is helpful to establish a better therapeutic regimen for patients with advanced NSCLC.

Preoperative prediction of pathological grading of hepatocellular carcinoma using machine learning-based ultrasomics: A multicenter study.

PURPOSE: The present study investigated the value of ultrasomics signatures in the preoperative prediction of the pathological grading of hepatocellular carcinoma (HCC) via machine learning. METHODS: A total of 193 patients were collected from three hospitals. The patients from two hospitals (n = 160) were randomly divided into training set (n = 128) and test set (n = 32) at a 8:2 ratio. The patients from a third hospital were used as an independent validation set (n = 33). The ultrasomics features were extracted from the tumor lesions on the ultrasound images. Support vector machine (SVM) was used to construct three preoperative pathological grading models for HCC on each dataset. The performance of the three models was evaluated by area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy. RESULTS: The ultrasomics signatures extracted from the grayscale ultrasound images could successfully differentiate between high- and low-grade HCC lesions on the training set, test set, and the independent validation set (p < 0.05). On the test set and the validation set, the combined model's performance was the highest, followed by the ultrasomics model and the clinical model successively (p < 0.05). Their AUC (along with 95 %CI) of these models was 0.874(0.709-0.964), 0.789(0.608-0.912), 0.720(0.534-0.863) and 0.849(0.682-0.949), 0.825(0.654-0.935), 0.770(0.591-0.898), respectively. CONCLUSION: Machine learning-based ultrasomics signatures could be used for noninvasive preoperative prediction of pathological grading of HCC. The combined model displayed a better predictive performance for pathological grading of HCC and had a stronger generalization ability.

Clinical Value of Machine Learning-Based Ultrasomics in Preoperative Differentiation Between Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma: A Multicenter Study.

OBJECTIVE: This study aims to explore the clinical value of machine learning-based ultrasomics in the preoperative noninvasive differentiation between hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). METHODS: The clinical data and ultrasonic images of 226 patients from three hospitals were retrospectively collected and divided into training set (n = 149), test set (n = 38), and independent validation set (n = 39). Manual segmentation of tumor lesion was performed with ITK-SNAP, the ultrasomics features were extracted by the pyradiomics, and ultrasomics signatures were generated using variance filtering and lasso regression. The prediction models for preoperative differentiation between HCC and ICC were established by using support vector machine (SVM). The performance of the three models was evaluated by the area under curve (AUC), sensitivity, specificity, and accuracy. RESULTS: The ultrasomics signatures extracted from the grayscale ultrasound images could successfully differentiate between HCC and ICC (p < 0.05). The combined model had a better performance than either the clinical model or the ultrasomics model. In addition to stability, the combined model also had a stronger generalization ability (p < 0.05). The AUC (along with 95% CI), sensitivity, specificity, and accuracy of the combined model on the test set and the independent validation set were 0.936 (0.806-0.989), 0.900, 0.857, 0.868, and 0.874 (0.733-0.961), 0.889, 0.867, and 0.872, respectively. CONCLUSION: The ultrasomics signatures could facilitate the preoperative noninvasive differentiation between HCC and ICC. The combined model integrating ultrasomics signatures and clinical features had a higher clinical value and a stronger generalization ability.

A functional variant at miR-132-3p, miR-212-3p, and miR-361-5p binding site in CD80 gene alters susceptibility to gastric cancer in a Chinese Han population.

A number of single-nucleotide polymorphisms within the 3'-UTR of genes have been shown to relate to the occurrence of cancers. In this study, by using polymerase chain reaction-restriction fragment length analysis method, we determined an SNP rs1599795 in the 3'-UTR of CD80 gene in 183 gastric cancer patients and 348 healthy controls. Statistical analysis results showed that SNP rs1599795 genotypes were significantly correlated with the risk of gastric cancer. Compared with the AA homozygotes, the TA heterozygotes were significantly more prevalent in the patients (OR 1.44, 95 % CI 0.98-2.11) with a larger tumor size (P = 0.001), deeper infiltration (P = 1.5 × 10(-5)), higher possibility of lymph node metastasis (P = 0.003), and more in the late stage (TNM stage III and IV; P = 0.003); the TT homozygotes had larger tumor size (P = 0.001) and lower degree of differentiation (P = 2.2 × 10(-4)). Dual-luciferase reporter assays showed that miR-132-3p, miR-212-3p, and miR-361-5p inhibited the expression of CD80 through binding with the CD80 3'-UTR, and this inhibitory role of miR-132-3p, miR-212-3p, and miR-361-5p was impacted by rs1599795. Our findings have shown that the SNP rs1599795 in CD80 3'-UTR, through disrupting the regulatory role of miR-132-3p, miR-212-3p, and miR-361-5p in CD80 expression, contributed to the occurrence of gastric cancer.