To develop and validate magnetic resonance imaging (MRI)-based pre-Radiomics and delta-Radiomics models for predicting the treatment response of local advanced rectal cancer (LARC) to neoadjuvant chemoradiotherapy (NCRT).Between October 2017 and August 2022, 105 LARC NCRT-naïve patients were enrolled in this study. After careful evaluation, data for 84 patients that met the inclusion criteria were used to develop and validate the NCRT response models. All patients received NCRT, and the post-treatment response was evaluated by pathological assessment. We manual segmented the volume of tumors and 105 radiomics features were extracted from three-dimensional MRIs. Then, the eXtreme Gradient Boosting algorithm was implemented for evaluating and incorporating important tumor features. The predictive performance of MRI sequences and Synthetic Minority Oversampling Technique (SMOTE) for NCRT response were compared. Finally, the optimal pre-Radiomics and delta-Radiomics models were established respectively. The predictive performance of the radionics model was confirmed using 5-fold cross-validation, 10-fold cross-validation, leave-one-out validation, and independent validation. The predictive accuracy of the model was based on the area under the receiver operator characteristic (ROC) curve (AUC).There was no significant difference in clinical factors between patients with good and poor reactions. Integrating different MRI modes and the SMOTE method improved the performance of the radiomics model. The pre-Radiomics model (train AUC: 0.93 ± 0.06; test AUC: 0.79) and delta-Radiomcis model (train AUC: 0.96 ± 0.03; test AUC: 0.83) all have high NCRT response prediction performance by LARC. Overall, the delta-Radiomics model was superior to the pre-Radiomics model.MRI-based pre-Radiomics model and delta-Radiomics model all have good potential to predict the post-treatment response of LARC to NCRT. Delta-Radiomics analysis has a huge potential for clinical application in facilitating the provision of personalized therapy.
KRT81 is involved in carcinogenesis and progression of many types of human cancers. However, little is known about the role of KRT81 in melanoma. In this study, we identified that KRT81 expression is upregulated in melanoma tissues compared with corresponding adjacent nontumor tissues. Overexpression of KRT81 was also found in human melanoma cell lines. Cell functional studies have shown that KRT81 knockdown could inhibit proliferation, colony formation, migration, invasion, and promote apoptosis of A375 cells. Consistently, in vivo tumorigenesis experiments showed that KRT81 knockdown significantly suppressed the growth of xenograft tumors. Moreover, KRT81 knockdown increased the chemosensitivity of A375 cells to DDP. Mechanical exploration revealed that KRT81 knockdown mediated the downregulation of inflammatory cytokine interleukin-8 (IL-8). In conclusion, these findings indicate that downregulation of KRT81 could inhibit progression of melanoma by regulating IL-8. Therefore, KRT81 represents a potential therapeutic target for melanoma therapy.
Abstract Introduction The glycolytic enzyme, α-Enolase (ENO1), catalyzes the production of phosphoenolpyruvate from 2-phosphoglycerate, which enhances glycolysis, and thus contributes to tumor progression. In the present study, we aimed to determine ENO1’s role in malignant melanoma (MM) and the potential underlying mechanism. Methods Western blotting was used to assess the levels of ENO1, c-Myc, β-catenin, MMP-9, PGAM1, and MMP-13 in MM-derived cell lines or tumor tissues from patients with MM. Plasmids pCMV-SPORT6-ENO1 and pET-28a-ENO1siRNA plasmids were used to overexpress and knockdown ENO1 in MM cells, respectively. To determine the function of ENO1 in the malignant behavior of MM cells, we performed wound healing, Cell counting kit 8, Transwell chamber, and flow cytometry analyses. Pyruvate determination and lactic acid kits were used to evaluate the production of pyruvate and lactic acid in tumor cells. Results The protein levels of ENO1 and PGAM1 in MM tissue were significantly higher than that in mole tissue. In MM cells, ENO1 overexpression inhibited apoptosis; promoted invasion, migration, and proliferation; increased pyruvate and lactate production; and increased in β-catenin, MMP-9, MMP-13, and c-Myc levels. The opposite effects were observed in MM cells silenced for ENO1 . Conclusion These results indicated that ENO1 is involved in MM progression by enhancing invasion and proliferation, while inhibiting apoptosis. In addition, ENO1 might have an important function in tumor cell glycolysis. Therefore, ENO1 represents a potential therapeutic target to treat MM.
Objective This study aimed to investigate whether virtual monoenergetic images (VMIs) can aid radiologists and surgeons in better identifying the arc of Riolan (AOR) and to determine the optimal kilo electron volt (keV) level. Methods Thirty-three patients were included. Conventional images (CIs) and VMI (40–100 keV) were reconstructed using arterial phase spectral-based images. The computed tomography (CT) attenuation and noise of the AOR, the CT attenuation of the erector spinal muscle, and the background noise on VMI and CI were measured, respectively. The signal-to-noise ratio, contrast-to-noise ratio (CNR), and signal intensity ratio were calculated. The image quality of the AOR was evaluated according to a 4-point Likert grade. Results The CT attenuation, noise, CNR, and signal intensity ratio of the AOR were significantly higher in VMI at 40 and 50 keV compared with CI ( P < 0.001); VMI at 40 keV was significantly higher than 50 keV ( P < 0.05). No significant difference in signal-to-noise ratio, background noise, and CT attenuation of the spinal erector muscle was observed between VMI and CI ( P > 0.05). virtual monoenergetic image at 40 keV produced the best subjective scores. Conclusions Virtual monoenergetic image at 40 keV makes it easier to observe the AOR with optimized subjective and objective image quality. This may prompt radiologists and surgeons to actively search for it and encourage surgeons to preserve it during splenic flexure takedown.
Abstract Purpose A meta-analysis study was performed to systematically assess the association between tea consumption and CRC risk. Methods Cochrane Library, Embase, PubMed, and Web of Science were retrieved to collect articles in English since 24 July 2023. Databases were searched and evaluated by two reviewers independently.We screened the literature based on inclusion and exclusion criteria. After determining the random effect model or fixed utility model based on a heterogeneity test, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. Results We included fourteen articles in this meta-analysis. We analyzed the data using a random effect model to explore the association between tea consumption and CRC because of apparent heterogeneity ( P < 0.001, I2 = 99.5%). The combined results of all tests showed that there is no statistically significant association between tea consumption and CRC risk (OR = 0.756, 95%CI = 0.470–1.215, P = 0.247). Subsequently, subgroup analysis and sensitivity analysis were performed. Excluding any single study, the overall results ranged from 0.73 (95%CI = 0.44–1.20) to 0.86 (95%CI = 0.53–1.40). It was determined that there was no significant publication bias between tea consumption and CRC risk ( P = 0.064) by Egger's tests. Conclusions The results indicated that tea consumption may not be significantly associated with the development of CRC. Implications of key findings Tea reduces colon cancer risk by 24%, but the estimate is uncertain. The actual effect on risk can range from a reduction of 51% to an increase of 18%, but regional and population differences may cause differences.
Abstract Autophagy plays a dual role in tumor development and autophagy-related genes (ARGs) involved in the development of cancer. However, the correlation between these high and low risk ARGs is still unclear. To systematically study the relationship between ARGs and melanoma patients, the expression profiles of ARGs were integratedly analyzed based on the TCGA and GTEx dataset. The results suggested 8-ARGs marker can predict the prognosis of skin cutaneous melanoma (SKCM), 5-ARGs ( CFLAR , DAPK2 , ITGA6 , DNAJB9 and RGS19 ) were low risk index, 3-ARGs ( EIF2AK2 , EGFR and PTK6 ) were high risk index. Further validation showed CFLAR , DNAJB9 and PTK6 were significant related to SKCM. In tumor immunization, CFLAR and DNAJB9 have stronger correlation with tumor immune cells, and there is a significant positive correlation among the low risk genes. However, there is no significant correlation between the high and low risk factors. In addition, our results also showed that CFLAR and PTK6 were significantly negatively correlated with tumor purity; PTK6 was significantly positively correlated with patient's age, CFLAR was significantly negatively correlated with patient's age; CFLAR and DNAJB9 were significantly positively correlated in purity and age. It provides a new prognostic indicator for patients and a new idea for the mechanism of autophagy in melanoma.
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