UBE2C as an Immune-Related Biomarker for Breast Cancer: A Study Based on Multiple Databases.

Objective To screen the target gene UBE2C and explore its prognostic value and immune correlation in breast cancer (BRCA) using multiple databases. Methods The microarray expression datasets of BRCA were downloaded from the Gene Expresssion Omnibus database (GEO) and analyzed to obtain differentially expressed genes (DEGs). Hub genes were obtained by constructing and visualizing the protein-protein interaction network of DEGs. Then the key gene UBE2C was determined using R language, STRING, and Cytoscape, and the differential expression of UBE2C was verified using the external datasets, The Cancer Genome Atlas (TCGA) , and quantitative real-time PCR (qRT-PCR). The prognostic value and immunological correlation of UBE2C in BRCA were explored using R language, TIMER, and Gene Set Enrichment Analysis (GSEA).Results The expression of UBE2C was differentially upregulated in BRCA, as verified by TCGA and qRT-PCR. Prognostic analysis revealed that UBE2C served as an independent prognostic factor. High expression of UBE2C was associated with decreased immune infiltration levels of B cells, CD4+ T cells, CD8+ T cells, macrophages, and myeloid dendritic cells in BRCA tissue. The expression of UBE2C in BRCA showed a significant correlation with PDCD1, CD274, and CTLA4 expressions. There was a positive correlation between the expression of UBE2C and the tumor mutational burden and microsatellite instability. GSEA demonstrated that UBE2C expression significantly enriched 786 immune-related gene sets.Conclusions UBE2C expression in BRCA tissues can predict the survivals and prognosis of BRCA patients. Also, it is closely related to the BRCA immune microenvironment and can predict the effecacy of immunotherapy in BRCA patients. Therefore, UBE2C may be an potential immune-related prognostic biomarker for BRCA.

CD3, CD8, IFN-γ, tumor and stroma inflammatory cells as prognostic indicators for surgically resected SCLC: evidences from a 10-year retrospective study and immunohistochemical analysis.

Current clinical guidelines limit surgical intervention to patients with cT1-2N0M0 small cell lung cancer (SCLC). Our objective was to reassess the role of surgery in SCLC management, and explore novel prognostic indicators for surgically resected SCLC. We reviewed all patients diagnosed with SCLC from January 2011 to April 2021 in our institution. Survival analysis was conducted using the Kaplan-Meier method, and independent prognostic factors were assessed through the Cox proportional hazard model. In addition, immunohistochemistry (IHC) staining was performed to evaluate the predictive value of selected indicators in the prognosis of surgically resected SCLC patients. In the study, 177 SCLC patients undergoing surgical resection were ultimately included. Both univariate and multivariate Cox analysis revealed that incomplete postoperative adjuvant therapy emerged as an independent risk factor for adverse prognosis (p < 0.001, HR 2.96). Survival analysis revealed significantly superior survival among pN0-1 patients compared to pN2 patients (p < 0.0001). No significant difference in postoperative survival was observed between pN1 and pN0 patients (p = 0.062). Patients with postoperative stable disease (SD) exhibited lower levels of tumor inflammatory cells (TIC) (p = 0.0047) and IFN-γ expression in both area and intensity (p < 0.0001 and 0.0091, respectively) compared to those with postoperative progressive disease (PD). Conversely, patients with postoperative SD showed elevated levels of stromal inflammatory cells (SIC) (p = 0.0453) and increased counts of CD3+ and CD8+ cells (p = 0.0262 and 0.0330, respectively). Survival analysis indicated that high levels of SIC, along with low levels of IFN-γ+ cell area within tumor tissue, may correlate positively with improved prognosis in surgically resected SCLC (p = 0.017 and 0.012, respectively). In conclusion, the present study revealed that the patients with pT1-2N1M0 staging were a potential subgroup of SCLC patients who may benefit from surgery. Complete postoperative adjuvant therapy remains an independent factor promoting a better prognosis for SCLC patients undergoing surgical resection. Moreover, CD3, CD8, IFN-γ, TIC, and SIC may serve as potential indicators for predicting the prognosis of surgically resected SCLC.

Clinicopathological factors predict residual lymph node metastasis in locally advanced rectal cancer with ypT0-2 after neoadjuvant chemoradiotherapy.

PURPOSE: Residual lymph node metastases (RLNM) remained a great concern in the implementation of organ-preserving strategies and led to poor prognosis in locally advanced rectal cancer (LARC). In this study, we aimed to identify the clinicopathological factors correlated with RLNM in LARC patients with ypT0-2 after neoadjuvant chemoradiotherapy (NCRT). METHODS: We retrospectively analyzed 417 patients histologically diagnosed middle-low LARC after NCRT and total mesorectal excision (TME), whose pathological staging was ypT0-2. All patients received pelvic magnetic resonance imaging (MRI) before NCRT. The radiation doses were 50-50.6 Gy for the planning gross tumor volume and 41.8-45 Gy for the planning target volume, respectively. A nomogram for predicting RLNM was constructed using a binary logistic regression. Nomogram performance was assessed by receiver operating characteristic (ROC) curve, calibration curve, decision curve analysis (DCA) and clinical impact curve (CIC). RESULTS: After surgery, 191 patients (45.8%) were ypT0, 43 patients (10.3%) were ypT1 and 183 patients (43.9%) were ypT2, and a total of 49 patients (11.8%) were found the presence of RLNM. Multivariable analyses identified MRI-defined mesorectal fascia (MRF)-positive, high-grade histopathology at biopsy, advanced ypT-category, and the presence of perineural invasion (PNI) as the predictive factors. The nomogram, incorporating all these predictors, showed good discrimination and calibration efficacy, with the areas under the ROC curve of 0.690 (95% CI: 0.610-0.771). Both DCA and CIC demonstrated that this nomogram has good clinical usefulness. CONCLUSION: The nomogram model can predict RLNM in patients with ypT0-2 tumors. It can help select suitable patients for performing organ-preserving strategies after NCRT.

Astragaloside IV Alleviates Doxorubicin-Induced Cardiotoxicity by Inhibiting Cardiomyocyte Pyroptosis through the SIRT1/NLRP3 Pathway.

Doxorubicin (DOX) is a powerful anthracycline antineoplastic drug used to treat a wide spectrum of tumors. However, its clinical application is limited due to cardiotoxic side effects. Astragaloside IV (AS IV), one of the major compounds present in aqueous extracts of Astragalus membranaceus, possesses potent cardiovascular protective properties, but the underlying molecular mechanisms are unclear. Thus, the aim of this study was to investigate the effect of AS IV on DOX-induced cardiotoxicity (DIC). Our findings revealed that DOX induced pyroptosis through the caspase-1/gasdermin D (GSDMD) and caspase-3/gasdermin E (GSDME) pathways. AS IV treatment significantly improved the cardiac function and alleviated myocardial injury in DOX-exposed mice by regulating intestinal flora and inhibiting pyroptosis; markedly suppressed the levels of cleaved caspase-1, N-GSDMD, cleaved caspase-3, and N-GSDME; and reversed DOX-induced downregulation of silent information regulator 1 (SIRT1) and activation of the NLR family pyrin domain containing 3 (NLRP3) inflammasome in mice. The SIRT1 inhibitor EX527 significantly blocked the protective effects of AS IV. Collectively, our results suggest that AS IV protects against DIC by inhibiting pyroptosis through the SIRT1/NLRP3 pathway.

Impact of iodinated oil in proton therapy on relative stopping power of liver post-cTACE.

Objective. Conventional transarterial chemoembolization (cTACE) is a common treatment for hepatocellular carcinoma (HCC), often with unsatisfactory local controls. Combining cTACE with radiotherapy shows a promise for unresectable large HCC, with proton therapy preserving healthy liver tissue. However, the proton therapy benefits are subject to the accuracy of tissue relative stopping power (RSP) prediction. The RSP values are typically derived from computed tomography (CT) images using stoichiometric calibration. Lipiodol deposition significantly increases CT numbers in liver regions of post-cTACE. Hence, it is necessary to evaluate the accuracy of RSP in liver regions of post-cTACE.Approach. Liver, water, and iodinated oil samples were prepared. Some liver samples contained iodinated oil. The water equivalent path length (WEPL) of sample was measured through the pullbacks of spread-out Bragg peak (SOBP) depth-dose profiles scanned in a water tank with and without sample in the beam path. Measured RSP values were compared to estimated RSP values derived from the CT number based on the stoichiometric calibration method.Main results. The measured RSP of water was 0.991, confirming measurement system calibration. After removing the RSP contribution from container walls, the pure iodinated oil and liver samples had RSP values of 1.12 and 1.06, while the liver samples mixed with varying oil volumes (5 ml, 10 ml, 15 ml) showed RSP values of 1.05, 1.05 and 1.06. Using the stoichiometric calibration method, pure iodinated oil and liver samples had RSP values of 2.79 and 1.06. Liver samples mixed with iodinated oil (5 ml, 10 ml, 15 ml) had calculated RSP values of 1.21, 1.34, and 1.46. The RSP discrepancy reached 149.1% for pure iodinated oil.Significance.Iodinated oil notably raises CT numbers in liver tissue. However, there is almost no effect on its RSP value. Proton treatment of post-cTACE HCC patients can therefore be overshooting if no proper measures are taken against this specific effect.

AMPK inhibition sensitizes acute leukemia cells to BH3 mimetic-induced cell death.

BH3 mimetics, including the BCL2/BCLXL/BCLw inhibitor navitoclax and MCL1 inhibitors S64315 and tapotoclax, have undergone clinical testing for a variety of neoplasms. Because of toxicities, including thrombocytopenia after BCLXL inhibition as well as hematopoietic, hepatic and possible cardiac toxicities after MCL1 inhibition, there is substantial interest in finding agents that can safely sensitize neoplastic cells to these BH3 mimetics. Building on the observation that BH3 mimetic monotherapy induces AMP kinase (AMPK) activation in multiple acute leukemia cell lines, we report that the AMPK inhibitors (AMPKis) dorsomorphin and BAY-3827 sensitize these cells to navitoclax or MCL1 inhibitors. Cell fractionation and phosphoproteomic analyses suggest that sensitization by dorsomorphin involves dephosphorylation of the proapoptotic BCL2 family member BAD at Ser75 and Ser99, leading BAD to translocate to mitochondria and inhibit BCLXL. Consistent with these results, BAD knockout or mutation to BAD S75E/S99E abolishes the sensitizing effects of dorsomorphin. Conversely, dorsomorphin synergizes with navitoclax or the MCL1 inhibitor S63845 to induce cell death in primary acute leukemia samples ex vivo and increases the antitumor effects of navitoclax or S63845 in several xenograft models in vivo with little or no increase in toxicity in normal tissues. These results suggest that AMPK inhibition can sensitize acute leukemia to multiple BH3 mimetics, potentially allowing administration of lower doses while inducing similar antineoplastic effects.

A model that predicts a real-time tumour surface using intra-treatment skin surface and end-of-expiration and end-of-inhalation planning CT images.

OBJECTIVES: To develop a mapping model between skin surface motion and internal tumour motion and deformation using end-of-exhalation (EOE) and end-of-inhalation (EOI) 3D CT images for tracking lung tumours during respiration. METHODS: Before treatment, skin and tumour surfaces were segmented and reconstructed from the EOE and the EOI 3D CT images. A non-rigid registration algorithm was used to register the EOE skin and tumour surfaces to the EOI, resulting in a displacement vector field that was then used to construct a mapping model. During treatment, the EOE skin surface was registered to the real-time, yielding a real-time skin surface displacement vector field. Using the mapping model generated, the input of a real-time skin surface can be used to calculate the real-time tumour surface. The proposed method was validated with and without simulated noise on 4D CT images from 15 patients at Léon Bérard Cancer Center and the 4D-lung dataset. RESULTS: The average centre position error, dice similarity coefficient (DSC), 95%-Hausdorff distance and mean distance to agreement of the tumour surfaces were 1.29 mm, 0.924, 2.76 mm, and 1.13 mm without simulated noise, respectively. With simulated noise, these values were 1.33 mm, 0.920, 2.79 mm, and 1.15 mm, respectively. CONCLUSIONS: A patient-specific model was proposed and validated that was constructed using only EOE and EOI 3D CT images and real-time skin surface images to predict internal tumour motion and deformation during respiratory motion. ADVANCES IN KNOWLEDGE: The proposed method achieves comparable accuracy to state-of-the-art methods with fewer pre-treatment planning CT images, which holds potential for application in precise image-guided radiation therapy.

Effects of Glutamine Synthetase on Neovascularization in Glioma: In Vivo MR Vessel Size Imaging and Histology.

BACKGROUND: Glutamine Synthetase (GS) could induce vascular sprouting through the improvement of endothelial cell migration in inflammatory diseases. MR vessel-size imaging has been proposed as a valuable approach for visualizing the underlying angiogenic processes in the brain. OBJECTIVE: This study aims to investigate the role of GS in the neovascularization of gliomas through the utilization of MR vessel-size imaging and histopathological techniques. METHODS: In this exploratory animal study, we randomly divided the C6 glioma rat models into a control group and an L-methionine sulfoximine (MSO) treatment group. Daily intraperitoneal injections were administered for three consecutive days, starting from day 10 following the implantation of C6 glioma cells in rats. Subsequently, MR vessel size imaging was conducted using a BRUKER 7 T/200 mm MRI scanner, and the MRI results were validated through histopathological examination. RESULTS: A significant decrease in microvessel density was observed in both the tumor periphery and center areas in the MSO treatment group compared to that in the control group. The mean vessel diameter (mVD) and vessel size index (VSI) did not exhibit significant changes compared to the control group. Moreover, the staining intensity of platelet endothelial cell adhesion molecule-1 (CD31) and GS in the tumor periphery was significantly decreased in the MSO treatment group. Additionally, the MSO treatment demonstrated a substantial inhibition of tumor growth. CONCLUSION: GS inhibitors significantly reduced angiogenesis in the periphery area of C6 glioma, exerting an inhibitory effect on tumor progression. Thus, GS inhibitors could be potential therapeutic agents for treating glioma. Additionally, in vivo MR vessel size imaging detects changes in vascularrelated parameters after tumor treatment, making it a promising method for detecting neovascularization in glioma.

The chemokine CCL20 can assist AFP in serological diagnosis of hepatocellular carcinoma.

The chemokine 20 (CCL20) is a member of the CC chemokine family and plays a role in tumor immunity and autoimmune disease. This work investigated the value of CCL20 as a serum diagnostic marker for primary hepatocellular carcinoma (HCC). Based on the data of hepatocellular carcinoma patients in the TCGA database, the up-regulated genes encoding secretory proteins were analyzed in each pathological stage, and the candidate marker CCL20 gene was selected. Serum concentrations of CCL20 in patients with primary HCC, benign liver disease, and healthy subjects were analyzed by enzyme-linked immunosorbent assay (ELISA). The ROC curve evaluated the efficacy of CCL20 alone or in combination with AFP in the diagnosis of HCC. It was found the expression of CCL20 in HCC patients was significantly higher than that in the benign liver disease group and healthy controls (P < 0.05); The AUC of ROC curve to distinguish HCC patients from healthy controls was 0.859, the sensitivity was 73.42%, and the specificity was 86.84%. After combination with AFP, the AUC increased to 0.968, the sensitivity was 88.16%, and the specificity was 97.37%. Although CCL20 was increased in the serum of patients with benign liver diseases, combined with AFP, the AUC to distinguish HCC patients from non-HCC cohorts (benign liver disease group and healthy control group) was 0.902, with a sensitivity of 91.67% and a specificity of 75.26%. Collectively, serum CCL20 is closely related to the occurrence of HCC, and detection of serum CCL20 can assist AFP in improving the diagnostic sensitivity of HCC.

CT radiomics-based model for predicting TMB and immunotherapy response in non-small cell lung cancer.

BACKGROUND: Tumor mutational burden (TMB) is one of the most significant predictive biomarkers of immunotherapy efficacy in non-small cell lung cancer (NSCLC). Radiomics allows high-throughput extraction and analysis of advanced and quantitative medical imaging features. This study develops and validates a radiomic model for predicting TMB level and the response to immunotherapy based on CT features in NSCLC. METHOD: Pre-operative chest CT images of 127 patients with NSCLC were retrospectively studied. The 3D-Slicer software was used to outline the region of interest and extract features from the CT images. Radiomics prediction model was constructed by LASSO and multiple logistic regression in a training dataset. The model was validated by receiver operating characteristic (ROC) curves and calibration curves using external datasets. Decision curve analysis was used to assess the value of the model for clinical application. RESULTS: A total of 1037 radiomic features were extracted from the CT images of NSCLC patients from TCGA. LASSO regression selected three radiomics features (Flatness, Autocorrelation and Minimum), which were associated with TMB level in NSCLC. A TMB prediction model consisting of 3 radiomic features was constructed by multiple logistic regression. The area under the curve (AUC) value in the TCGA training dataset was 0.816 (95% CI: 0.7109-0.9203) for predicting TMB level in NSCLC. The AUC value in external validation dataset I was 0.775 (95% CI: 0.5528-0.9972) for predicting TMB level in NSCLC, and the AUC value in external validation dataset II was 0.762 (95% CI: 0.5669-0.9569) for predicting the efficacy of immunotherapy in NSCLC. CONCLUSION: The model based on CT radiomic features helps to achieve cost effective improvement in TMB classification and precise immunotherapy treatment of NSCLC patients.

The ypT may better predict the efficacy of neoadjuvant chemoradiotherapy than tumor regression grade in locally advanced rectal cancer patients diagnosed ypT1-4N0.

PURPOSE: This study aimed to assess the impact of ypT stage and tumor regression grade (TRG) on the long-term prognosis of patients with locally advanced rectal cancer (LARC) stage ypT1-4N0 after neoadjuvant chemoradiotherapy (NCRT). METHODS: We retrospectively analyzed 585 patients with histologically diagnosed middle-low LARC (cT3-4 or cN + by pelvic MRI) from 2014 to 2019. All patients underwent NCRT, followed by total mesorectal excision. Disease-free survival (DFS) rates were compared among patients with different ypT stages and TRGs by Kaplan-Meier survival analysis. The chi-square test was used to analyze the relationship between clinicopathological or therapeutic factors and ypT stage. RESULTS: The median follow-up was 35.8 months (range 2.8-71.8 months). The 3-year DFS was 79.5%. A better 3-year DFS was achieved in patients with a pathologic complete response (94.0% vs. 74.3%, p < 0.001) and those in the ypT0-2 (86.5% vs. 66.6%, p < 0.001), ypN0 (85.0% vs. 60.2%, p < 0.001), and TRG0 + 1 (83.1% vs. 73.0%, p = 0.004) subgroups. A total of 309 patients (52.8%) achieved stage ypT1-4N0 after surgery. Among these patients, the ypT1-2N0 subgroup achieved a significantly higher 3-year DFS than the ypT3-4N0 subgroup (85.4% vs. 72.8%, p = 0.018); in contrast, the 3-year DFS did not significantly differ between the TRG1 and TRG2 + 3 subgroups (79.9% vs. 81.1%, p = 0.833). In the ypT1-2N0 or ypT3-4N0 subgroup, different TRG had no significant effect on failure patterns. CONCLUSIONS: For LARC patients with a ypT1-4N0 status after NCRT, ypT stage may be a more effective predictor of long-term prognosis than TRG.

4D-MRI assisted stereotactic body radiation therapy for unresectable colorectal cancer liver metastases.

This study evaluated the feasibilities and outcomes following four-dimensional magnetic resonance imaging (4D-MRI) assisted stereotactic body radiation therapy (SBRT) for unresectable colorectal liver metastases (CRLMs). From March 2018 to January 2022, we identified 76 unresectable CRLMs patients with 123 lesions who received 4D-MRI guided SBRT in our institution. 4D-MRI simulation with or without abdominal compression was conducted for all patients. The prescription dose was 50-65 Gy in 5-12 fractions. The image quality of computed tomography (CT) and MRI were compared using the Clarity Score. Clinical outcomes and toxicity profiles were evaluated. 4D-MRI improved the image quality compared with CT images (mean Clarity Score: 1.67 vs 2.88, P < 0.001). The abdominal compression reduced motions in cranial-caudal direction (P = 0.03) with two phase T2 weighted images assessing tumor motion. The median follow-up time was 12.5 months. For 98 lesions assessed for best response, the complete response, partial response and stable disease rate were 57.1 %, 30.6 % and 12.2 %, respectively. The local control (LC) rate at 1 year was 97.3 %. 46.1 % of patients experienced grade 1-2 toxicities and only 2.6 % patients experienced grade 3 hematologic toxicities. The 4D-MRI technique allowed accurate target delineation and motion tracking in unresectable CRLMs patients. Favorable LC rate and mild toxicities were achieved. This study provided evidence for using 4D-MRI assisted SBRT as an alternative treatment in unresectable CRLMs.

KRAS status predicted by pretreatment MRI radiomics was associated with lung metastasis in locally advanced rectal cancer patients.

BACKGROUND: Mutated KRAS may indicate an invasive nature and predict prognosis in locally advanced rectal cancer (LARC). We aimed to establish a radiomic model using pretreatment T2W MRIs to predict KRAS status and explore the association between the KRAS status or model predictions and lung metastasis. METHODS: In this retrospective multicentre study, LARC patients from two institutions between January 2012 and January 2019 were randomly divided into training and testing cohorts. Least absolute shrinkage and selection operator (LASSO) regression and the support vector machine (SVM) classifier were utilized to select significant radiomic features and establish a prediction model, which was validated by radiomic score distribution and decision curve analysis. The association between the model stratification and lung metastasis was investigated by Cox regression and Kaplan‒Meier survival analysis; the results were compared by the log-rank test. RESULTS: Overall, 103 patients were enrolled (73 and 30 in the training and testing cohorts, respectively). The median follow-up was 38.1 months (interquartile range: 26.9, 49.4). The radiomic model had an area under the curve (AUC) of 0.983 in the training cohort and 0.814 in the testing cohort. Using a cut-off of 0.679 defined by the receiver operating characteristic (ROC) curve, patients with a high radiomic score (RS) had a higher risk for lung metastasis (HR 3.565, 95% CI 1.337, 9.505, p = 0.011), showing similar predictive performances for the mutant and wild-type KRAS groups (HR 3.225, 95% CI 1.249, 8.323, p = 0.016, IDI: 1.08%, p = 0.687; NRI 2.23%, p = 0.766). CONCLUSIONS: We established and validated a radiomic model for predicting KRAS status in LARC. Patients with high RS experienced more lung metastases. The model could noninvasively detect KRAS status and may help individualize clinical decision-making.

Prognostic and risk factor analysis of cancer patients after unplanned ICU admission: a real-world multicenter study.

To investigate the occurrence and 90-day mortality of cancer patients following unplanned admission to the intensive care unit (ICU), as well as to develop a risk prediction model for their 90-day prognosis. We prospectively analyzed data from cancer patients who were admitted to the ICU without prior planning within the past 7 days, specifically between May 12, 2021, and July 12, 2021. The patients were grouped based on their 90-day survival status, and the aim was to identify the risk factors influencing their survival status. A total of 1488 cases were included in the study, with an average age of 63.2 ± 12.4 years. The most common reason for ICU admission was sepsis (n = 940, 63.2%). During their ICU stay, 29.7% of patients required vasoactive drug support (n = 442), 39.8% needed invasive mechanical ventilation support (n = 592), and 82 patients (5.5%) received renal replacement therapy. We conducted a multivariate COX proportional hazards model analysis, which revealed that BMI and a history of hypertension were protective factors. On the other hand, antitumor treatment within the 3 months prior to admission, transfer from the emergency department, general ward, or external hospital, high APACHE score, diagnosis of shock and respiratory failure, receiving invasive ventilation, and experiencing acute kidney injury (AKI) were identified as risk factors for poor prognosis within 90 days after ICU admission. The average length of stay in the ICU was 4 days, while the hospital stay duration was 18 days. A total of 415 patients died within 90 days after ICU admission, resulting in a mortality rate of 27.9%. We selected 8 indicators to construct the predictive model, which demonstrated good discrimination and calibration. The prognosis of cancer patients who are unplanned transferred to the ICU is generally poor. Assessing the risk factors and developing a risk prediction model for these patients can play a significant role in evaluating their prognosis.

Chinese herb related molecules Catechins, Caudatin and Cucurbitacin-I inhibit the proliferation of glioblastoma by activating KDELR2-mediated endoplasmic reticulum stress.

Brain gliomas are difficult in the field of tumor therapy because of their high recurrence rate, high mortality rate, and low selectivity of therapeutic agents. The efficacy of Traditional Chinese Medicine (TCM) in the treatment for tumours has been widely recognized. Here, three Chinese herb related molecules, namely Catechins, Caudatin and Cucurbitacin-I, were screened by bioinformatic means, and were found to inhibit the proliferation of glioblastoma T98G cells using Colony-forming and CCK-8 assays. Notably, the simultaneous use of all three molecules could more significantly inhibit the proliferation of glioma cells. Consistent with this, temozolomide, each in the combination with three molecules, could synergistically inhibit the proliferation of T98G cells. Results of qPCR assay was also showed that this inhibition was through the activation of the KDELR2-mediated endoplasmic reticulum stress (ER) pathway. Molecular docking experiments further revealed that Catechins, Caudatin and Cucurbitacin-I could activate ER stress might by targeting KDELR2. Taken together, these results suggest that these herbal molecules have the potential to inhibit the growth of glioma cells and could provide a reference for clinical therapeutic drug selection.

Expert Consensus on Acute Respiratory Failure in Critically Ill Cancer Patients (2023).

Objective This consensus aims to provide evidence-based recommendations on common questions in the diagnosis and treatment of acute respiratory failure (ARF) for critically ill cancer patients.Methods We developed six clinical questions using the PICO (Population, Intervention, Comparison, and Outcome) principle in diagnosis and treatment for critical ill cancer patients with ARF. Based on literature searching and meta-analyses, recommendations were devised. The GRADE (Grading of Recommendation Assessment, Development and Evaluation) method was applied to each question to reach consensus in the expert panel. Results The panel makes strong recommendations in favor of (1) metagenomic next-generation sequencing (mNGS) tests may aid clinicians in rapid diagnosis in critically ill cancer patients suspected of pulmonary infections; (2) extracorporeal membrane oxygenation (ECMO) therapy should not be used as a routine rescue therapy for acute respiratory distress syndrome in critically ill cancer patients but may benefit highly selected patients after multi-disciplinary consultations; (3) cancer patients who have received immune checkpoint inhibitor therapy have an increased incidence of pneumonitis compared with standard chemotherapy; (4) critically ill cancer patients who are on invasive mechanical ventilation and estimated to be extubated after 14 days may benefit from early tracheotomy; and (5) high-flow nasal oxygen and noninvasive ventilation therapy can be used as a first-line oxygen strategy for critically ill cancer patients with ARFs. A weak recommendation is: (6) for critically ill cancer patients with ARF caused by tumor compression, urgent chemotherapy may be considered as a rescue therapy only in patients determined to be potentially sensitive to the anticancer therapy after multidisciplinary consultations. Conclusions The recommendations based on the available evidence can guide diagnosis and treatment in critically ill cancer patients with acute respiratory failure and improve outcomes.

Expert consensus on the clinical application of totally implantable venous access devices in the upper arm (2022 Edition).

With the widespread adoption of ultrasound guidance, Seldinger puncture techniques, and intracardiac electrical positioning technology for the placement of peripherally inserted central catheters in recent years, an increasing number of medical staff and patients now accept peripheral placement of totally implantable venous access devices (TIVADs) in the upper arm. This approach has the advantage of completely avoiding the risks of hemothorax, pneumothorax, and neck and chest scarring. Medical specialties presently engaged in this study in China include internal medicine, surgery, anesthesiology, and interventional departments. However, command over implantation techniques, treatment of complications, and proper use and maintenance of TIVAD remain uneven among different medical units. Moreover, currently, there are no established quality control standards for implantation techniques or specifications for handling complications. Thus, this expert consensus is proposed to improve the success rate of TIVAD implantation via the upper-arm approach, reduce complication rates, and ensure patient safety. This consensus elaborates on the technical indications and contraindications, procedures and technical points, treatment of complications, and the use and maintenance of upper-arm TIVAD, thus providing a practical reference for medical staff.

Alcoholic Setdb1 suppression promotes hepatosteatosis in mice by strengthening Plin2.

BACKGROUND AND AIMS: Hepatosteatosis is one of the early features of alcoholic liver disease (ALD) and pharmaceutical or genetic interfering of the development of hepatosteatosis will efficiently alleviate the progression of ALD. Currently, the role of histone methyltransferase Setdb1 in ALD is not yet well understood. METHOD: Lieber-De Carli diet mice model and NIAAA mice model were constructed to confirm the expression of Setdb1. The hepatocyte-specific Setdb1-knockout (Setdb1-HKO) mice was established to determine the effects of Setdb1 in vivo. Adenovirus-Setdb1 were produced to rescue the hepatic steatosis in both Setdb1-HKO and Lieber-De Carli mice. The enrichment of H3k9me3 in the upstream sequence of Plin2 and the chaperone-mediated autophagy (CMA) of Plin2 were identified by ChIP and co-IP. Dual-luciferase reporter assay was used to detect the interaction of Setdb1 3'UTR and miR216b-5p in AML12 or HEK 293 T cells. RESULTS: We found that Setdb1 was downregulated in the liver of alcohol-fed mice. Setdb1 knockdown promoted lipid accumulation in AML12 hepatocytes. Meanwhile, hepatocyte-specific Setdb1-knockout (Setdb1-HKO) mice exhibited significant lipid accumulation in the liver. Overexpression of Setdb1 was performed with an adenoviral vector through tail vein injection, which ameliorated hepatosteatosis in both Setdb1-HKO and alcoholic diet-fed mice. Mechanistically, downregulated Setdb1 promoted the mRNA expression of Plin2 by desuppressing H3K9me3-mediated chromatin silencing in its upstream sequence. Pin2 acts as a critical membrane surface-associated protein to maintain lipid droplet stability and inhibit lipase degradation. The downregulation of Setdb1 also maintained the stability of Plin2 protein through inhibiting Plin2-recruited chaperone-mediated autophagy (CMA). To explore the reasons for Setdb1 suppression in ALD, we found that upregulated miR-216b-5p bound to the 3'UTR of Setdb1 mRNA, disturbed its mRNA stability, and eventually aggravated hepatic steatosis. CONCLUSIONS: Setdb1 suppression plays an important role in the progression of alcoholic hepatosteatosis via elevating the expression of Plin2 mRNA and maintaining the stability of Plin2 protein. Targeting hepatic Setdb1 might be a promising diagnostic or therapeutic strategy for ALD.

The identification of a two-gene prognostic model based on cisplatin resistance-related ceRNA network in small cell lung cancer.

BACKGROUND: Small cell lung cancer (SCLC) is a very malignant tumor with rapid growth and early metastasis. Platinum-based chemo-resistance is the major issue for SCLC treatment failure. Identifying a new prognostic model will help to make an accurate treatment decision for SCLC patients. METHODS: Using the genomics of drug sensitivity in cancer (GDSC) database, we identified cisplatin resistance-related lncRNAs in SCLC cells. Based on the competing endogenous RNA (ceRNA) network, we identified the mRNAs correlated with the lncRNAs. Using Cox and LASSO regression analysis, a prognostic model was established. The survival prediction accuracy was evaluated by receiver operating characteristic (ROC) curve and Kaplan-Meier analysis. GSEA, GO, KEGG and CIBERSORT tools were used for functional enrichment and immune cells infiltration analysis. RESULTS: We first screened out 10 differentially expressed lncRNAs between cisplatin resistant and sensitive SCLC cells from GDSC database. Based on ceRNA network, 31 mRNAs were identified with a correlation with the 10 lncRNAs. Furthermore, two genes (LIMK2 and PI4K2B) were identified by Cox and LASSO regression analysis to construct a prognostic model. Kaplan-Meier analysis indicated that the high-risk group had a poor overall survival compared with the low-risk group. The predicted area under the ROC curve (AUC) was 0.853 in the training set, and the AUC was 0.671 in the validation set. In the meanwhile, the low expression of LIMK2 or the high expression of PI4K2B in SCLC tumors was also significantly associated with poor overall survival in both training and validation sets. Functional enrichment analysis showed that the low-risk group was enriched in the apoptosis pathway and high immune infiltration of T cells. Finally, an apoptosis-related gene Cathepsin D (CTSD) was identified to be up-regulated in the low-risk group, and its higher expression correlated with better overall survival in SCLC. CONCLUSION: We established a prognostic model and potential biomarkers (LIMK2, PI4K2B and CTSD), which could help to improve the risk stratification of SCLC patients.