TNFAIP3 Interacting Protein 3 Is an Activator of Hippo-YAP Signaling Protecting Against Hepatic Ischemia/Reperfusion Injury.

BACKGROUND AND AIMS: Hepatic ischemia/reperfusion (I/R) injury, a common clinical problem that occurs during liver surgical procedures, causes a large proportion of early graft failure and organ rejection cases. The identification of key regulators of hepatic I/R injury may provide potential strategies to clinically improve the prognosis of liver surgery. Here, we aimed to identify the role of tumor necrosis factor alpha-induced protein 3-interacting protein 3 (TNIP3) in hepatic I/R injury and further reveal its immanent mechanisms. APPROACH AND RESULTS: In the present study, we found that hepatocyte TNIP3 was markedly up-regulated in livers of both persons and mice subjected to I/R surgery. Hepatocyte-specific Tnip3 overexpression effectively attenuated I/R-induced liver necrosis and inflammation, but improved cell proliferation in mice, whereas TNIP3 ablation largely aggravated liver injury. This inhibitory effect of TNIP3 on hepatic I/R injury was found to be dependent on significant activation of the Hippo-YAP signaling pathway. Mechanistically, TNIP3 was found to directly interact with large tumor suppressor 2 (LATS2) and promote neuronal precursor cell-expressed developmentally down-regulated 4-mediated LATS2 ubiquitination, leading to decreased Yes-associated protein (YAP) phosphorylation at serine 112 and the activated transcription of factors downstream of YAP. Notably, adeno-associated virus delivered TNIP3 expression in the liver substantially blocked I/R injury in mice. CONCLUSIONS: TNIP3 is a regulator of hepatic I/R injury that alleviates cell death and inflammation by assisting ubiquitination and degradation of LATS2 and the resultant YAP activation.TNIP3 represents a promising therapeutic target for hepatic I/R injury to improve the prognosis of liver surgery.

Prognostic nomogram for predicting long-term cancer-specific survival in patients with lung carcinoid tumors.

BACKGROUND: Lung carcinoid is a rare malignant tumor with poor survival. The current study established a nomogram model for predicting cancer-specific survival (CSS) in patients with lung carcinoid tumors. METHODS: A total of 1956 patients diagnosed with primary lung carcinoid tumors were extracted from the Surveillance, Epidemiology, and End Results database. The specific predictors of CSS for lung carcinoid tumors were identified and integrated to build a nomogram. Validation of the nomogram was conducted using parameters concordance index (C-index), calibration plots, decision curve analyses (DCAs), and the receiver operating characteristic (ROC) curve. RESULTS: Age at diagnosis, grade, histological type, N stage, M stage, surgery of the primary site, radiation of the primary site, and tumor size were independent prognostic factors of CSS. High discriminative accuracy of the nomogram model was shown in the training cohort (C-index = 0.873), which was also testified in the internal validation cohort (C-index = 0.861). In both cohorts, the calibration plots showed good concordance between the predicted and observed CSS at 3, 5, and 10 years. The DCA showed great potential for clinical application. The ROC curve showed superior survival predictive ability of the nomogram model (area under the curve = 0.868). CONCLUSIONS: We developed a practical nomogram that provided independent predictions of CSS for patients with lung carcinoid tumors. This nomogram may have the potential to assist clinicians in prognostic evaluations or developing individualized therapies for patients with this neoplasm.

Vacuum sealing drainage with instillation in the treatment of necrotising soft-tissue infection: a retrospective analysis.

OBJECTIVE: Necrotising soft-tissue infection is a rare but life-threatening infectious disease with high morbidity and mortality. It is typically caused by toxin-producing bacteria and characterised clinically by a very rapid progression of the disease with significant local tissue destruction. In this study, we intend to explore effective wound management to control the invasive infection and to decrease the high mortality. METHOD: This retrospective analysis explored the wound management and mortality in patients with necrotising soft-tissue infection. Extensive debridement, vacuum sealing drainage (VSD) with normal saline instillation combined with broad-spectrum or sensitive antibiotics, and supportive therapies were used. RESULTS: All 17 patients included in the analysis survived. The microbiology of 11 patients was found to be polymicrobial. Of the patients, 14 were discharged with completely healed wounds and three were transferred to a local hospital after the systemic and invasive wound infection was controlled. CONCLUSION: Our experiences revealed the outstanding effect of VSD with instillation in removing the debris of necrotising tissue on the wound bed, in the continual and complete drainage of wound exudates, and in prompting wound healing.

The important role of circulating CYFRA21-1 in metastasis diagnosis and prognostic value compared with carcinoembryonic antigen and neuron-specific enolase in lung cancer patients.

BACKGROUND: The roles of carcinoembryonic antigen (CEA), cytokeratin 19 fragments (CYFRA21-1) and neuron-specific enolase (NSE) in metastases occurrence and poor diagnosis in specific histological classifications of lung cancer need further exploring. In this study, we investigated relationship between elevated levels of three biomarkers of CEA, CYFRA21-1 and NSE (individually and in combination) and metastasis, survival status and prognosis in lung cancer patients. METHODS: Eight hundred and sixty eight lung cancer patients including adenocarcinoma (ADC, N = 445), squamous cell carcinoma (SCC, N = 215), small cell lung cancer (SCLC, N = 159) and other types (N = 49) were categorized into negative, moderate and high groups according to serum levels of biomarkers, and were then categorized into negative, single, double and triple groups according to any positive combination of three biomarkers. The cutoff values of three biomarkers for groupings were developed on the training group (N = 432) and verified in a validation group (N = 436). Clinical and laboratory characteristics were then assessed for correlation with occurrence of metastasis, survival status and prognosis between the two groups. Further correlation analyses were also conducted by different subtypes (ADC, SCC and SCLC) and tumor stages (I + II, III and IV) of lung cancers. RESULTS: The consistent results between training and validation group confirmed the rationality of grouping methods. CYFRA21-1 levels had stronger association with metastases and survival status than CEA and NSE in all lung cancer patients. When stratified by subtypes, these significances only existed in ADC patients for CYFRA21-1. Cox regression analyses showed that CYFRA21-1 and NSE were independent prognostic factors for lung cancer patients. However, only CYFRA21-1 was an independent prognostic factor in ADC and SCLC patients subtypes. Cox-regression results also indicated that CYFRA21-1 could act as independent prognostic factor in different stages (I + II, III and IV) of lung cancer. CONCLUSION: CYFRA21-1 was more important in metastasis occurrence and in predicting poor prognosis in lung cancer patients than CEA, NSE and positive numbers of biomarkers.

The TLR7 agonist Imiquimod promote the immunogenicity of mesenchymal stem cells.

BACKGROUND: Mesenchymal stem cells (MSCs) are considered the best candidate in stem cells therapy due to their multipotent differentiation ability, low expression of co-stimulatory molecules (CD80, CD86, CD34 and HLA-II) and immunosuppression effects on in vivo immune responses. MSCs were now widely used in clinical trials but received no encourage results. The major problem was the fate of engrafted MSCs in vivo could not be defined. Some studies indicated that MSCs could induce immune response and result in the damage and rejection of MSCs. As toll like receptors (TLRs) are important in inducing of immune responses, in this study we study the role of TLR7 in mediating the immune status of MSCs isolated from umbilical cord. RESULTS: Our results indicated that TLR7 agonist Imiquimod could increase the proliferation of PBMC isolated from healthy human volunteers and release of lactate dehydrogenase (LDH) in supernatant from PBMC-UCMSCs co-culture system. Flow cytometry and quantitative PCR also confirmed the regulated expression of surface co-stimulatory molecules and pro-inflammatory genes (IL-6, IL-8, IL-12, TGF-ß and TNF-α). And the down-regulation expression of stem cell markers also confirmed the loss of stemness of UCMSCs. We also found that the osteo-differentiation ability of UCMSCs was enhanced in the presence of Imiquimod. CONCLUSION: To our knowledge, this is the first report that activation of TLR7 pathway increases the immunogenicity of UCMSCs. Extensive researches have now been conducted to study whether the change of immune status will be help in tumor rejection based on the tumor-tropism of MSCs.

[Construction of BAD Lentivirus Vector and Its Effect on Proliferation in A549 Cell Lines].

OBJECTIVE: To construct the recombinant lentivirus expressing vector BAD (Bcl-2-associated death protein) gene and to study its effect on A549 cell proliferation. METHODS: The BAD gene was amplified from plasmid pAV-MCMV-BAD-GFP by PCR. The purified BAD gene fragment was inserted into a lentivirus vector (pLVX-IRES-ZsGreen 1), and the insertion was identified by PCR, restriction endonuclease analysis and DNA sequencing. A549 cells were then transfected with the packaged recombinant lentivirus, and resistant cell clones were selected with flow cytometry. The expression of BAD in A549 cell lines stably transduction with a lentivirus was examined using Western blot. The effect of BAD overexpression on proliferation of A549 cells was evaluated by using CCK-8 kit. RESULTS: Restriction enzyme digestion and DNA sequencing showed that the full-length BAD gene (507 bp) had been successfully subcloned into the lentiviral vector to result in the recombinant vector pLVX-IRES-ZsGreen 1. Monoclonal cell lines BAD-A549 was produced after transfection with the recombinant lentivirus and selected with flow cytometry. Stable expression of BAD protein was verified by Western blot. In vitro, the OD value in BAD group was significantly lower than that of control groups from 120-144 h (P<0. 05). CONCLUSION: A549 cell lines stably transduced with a lentivirus expressing the BAD gene had been successfully generated. In vitro, BAD overexpression significantly inhibited A549 cells proliferation.

Identification and validation of PROM1 and CRTC2 mutations in lung cancer patients.

BACKGROUND: Genetic alterations could be responsible lung cancer, the leading cause of worldwide cancer death. METHODS: This study investigated gene mutations in a Han Chinese family of lung cancer using the whole genome exome sequencing and subsequent Sanger sequencing validation and then confirmed alteration of prominin 1(PROM1) and cyclic AMP-response element binding protein-regulated transcription co-activator2 (CRTC2) in blood samples of 343 sporadic lung cancer patients vs. 280 healthy controls as well as in 200 pairs of lung cancer and the corresponding normal tissues using PCR-restriction fragment length polymorphism and directed DNA sequencing of PCR products. RESULTS: The data showed PROM1 (p. S281R) and CRTC2 (p. R379C) mutations, in 5 and 2 cases of these 343 sporadic lung cancer patients, respectively. Notably, these mutations were absent in the healthy controls. Furthermore, in the 200 lung cancer and the matched normal tissues, PROM1 mutation occurred in 3 patients (i.e., one squamous cell carcinoma and two adenocarcinomas) with a mutation frequency of 1.5%, while CRTC2 mutation occurred in 5 patients (two squamous cell carcinomas and three adenocarcinomas) with a mutation frequency of 2.5%. CONCLUSIONS: The data from the current study demonstrated novel PROM1 and CRTC2 mutations, which could promote lung cancer development.

CRTC2 and PROM1 expression in non-small cell lung cancer: analysis by Western blot and immunohistochemistry.

Accumulating evidence supports that genetic factors are another risk factors for lung cancer. Previously, we used whole exome sequencing with sanger sequencing to search for genetic-related mutations in one of four individuals from a pedigree with lung cancer history. Then, we used PCR-RFLP and direct-sequence in the sample size of 318 individuals with lung cancer (cases) and 272 controls. Recently, we detected two new genes including CRTC2 (CREB regulated transcription coactivator 2) and PROM1(human prominin-1,CD133). We investigated the CRTC2 mutation and PROM1 mutation of surgically resected NSCLC tissues (n=200). The presence or absence of CRTC2 and PROM1 mutation was analyzed by direct sequencing. The expression of CRTC2 and PROM1 was studied by western blot and immunohistochemical analysis of the lung cancer tissues which had the mutation of the two genes(cases), the samples without mutations(controls) and the normal lung tissue(controls). CRTC2 and PROM1 mutations in 5 NSCLC tissues and 3 NSCLC tissues out of the samples were identified. The positive results were closely correlated with clinicopathological features, such as male gender, adenocarcinoma, smoker status, and older age (≥55). We found that the CRTC2 and PROM1 expression were significantly higher in tissues of NSCLS with mutations than that without mutations and the normal lung tissue. The results imply that the high expression of CRTC2 and PROM1 may play an important role in the development and hereditary of NSCLC.

Diagnostic efficacy of PET and PET/CT for recurrent lung cancer: a meta-analysis.

BACKGROUND: Lung cancer is one of the most common malignant tumors in the world, and is the leading cause of cancer-related mortality. Although there are no conclusive data to support the survival benefits of early detection or early treatment for recurrence, an early and accurate diagnosis of recurrence is critical to optimize therapy. PURPOSE: To compare the diagnostic value of positron emission tomography (PET) and positron emission tomography/computed tomography (PET/CT) using fluorine-18 deoxyglucose (18FDG) with conventional imaging techniques (CITs) for the detection of lung cancer recurrence. MATERIAL AND METHODS: A meta-analysis was performed, with systematic searches conducted using PubMed and EMBASE databases (up to 31 December 2011). Pooled sensitivity, specificity, and diagnostic odds ratio (DOR) values were calculated for 1035 patients reported in 13 articles. Summary receiver-operating characteristic curves (SROC) were also generated. RESULTS: The pooled sensitivity (95% CI) for PET, PET/CT, and CITs were 0.94 (0.91-0.97), 0.90 (0.84-0.95), and 0.78 (0.71-0.84), respectively. The pooled specificity (95% CI) for PET, PET/CT, and CITs were 0.84 (0.77-0.89), 0.90 (0.87-0.93), and 0.80 (0.75-0.84), respectively. Regarding sensitivity, lower values were associated with CITs than PET (P = 0.000) and PET/CT (P = 0.005), and there was no significant difference between PET/CT and PET (P = 0.102). Regarding specificity, values for PET/CT and PET were significantly higher than for CITs (both P = 0.000), and there was no significant difference between PET/CT and PET (P = 0.273). In the SROC curves, a better diagnostic accuracy was associated with PET/CT than PET and CITs. CONCLUSION: PET/CT and PET were found to be superior modalities for the detection of recurrent lung cancer, and PET/CT was superior to PET.

Mucosal-associated invariant T cells in infectious diseases of respiratory system: recent advancements and applications.

Mucosal-associated invariant T (MAIT) cells are an atypical subset of T lymphocytes, which have a highly conserved semi-constant αß chain of T-cell receptor (TCR) and recognize microbe-derived vitamin B metabolites via major histocompatibility complex class I related-1 molecule (MR1). MAIT cells get activated mainly through unique TCR-dependent and TCR-independent pathways, and express multiple functional and phenotypic traits, including innate-like functionality, T helper (Th) 1 cell immunity, Th 17 cell immunity, and tissue homing. Given the functions, MAIT cells are extensively reported to play a key role in mucosal homeostasis and infectious diseases. In the current work, we review the basic characteristics of MAIT cells and their roles in mucosal homeostasis and development of respiratory infectious diseases as well as their potential therapeutic targets.

DeepLN: A Multi-Task AI Tool to Predict the Imaging Characteristics, Malignancy and Pathological Subtypes in CT-Detected Pulmonary Nodules.

Objectives: Distinction of malignant pulmonary nodules from the benign ones based on computed tomography (CT) images can be time-consuming but significant in routine clinical management. The advent of artificial intelligence (AI) has provided an opportunity to improve the accuracy of cancer risk prediction. Methods: A total of 8950 detected pulmonary nodules with complete pathological results were retrospectively enrolled. The different radiological manifestations were identified mainly as various nodules densities and morphological features. Then, these nodules were classified into benign and malignant groups, both of which were subdivided into finer specific pathological types. Here, we proposed a deep convolutional neural network for the assessment of lung nodules named DeepLN to identify the radiological features and predict the pathologic subtypes of pulmonary nodules. Results: In terms of density, the area under the receiver operating characteristic curves (AUCs) of DeepLN were 0.9707 (95% confidence interval, CI: 0.9645-0.9765), 0.7789 (95%CI: 0.7569-0.7995), and 0.8950 (95%CI: 0.8822-0.9088) for the pure-ground glass opacity (pGGO), mixed-ground glass opacity (mGGO) and solid nodules. As for the morphological features, the AUCs were 0.8347 (95%CI: 0.8193-0.8499) and 0.9074 (95%CI: 0.8834-0.9314) for spiculation and lung cavity respectively. For the identification of malignant nodules, our DeepLN algorithm achieved an AUC of 0.8503 (95%CI: 0.8319-0.8681) in the test set. Pertaining to predicting the pathological subtypes in the test set, the multi-task AUCs were 0.8841 (95%CI: 0.8567-0.9083) for benign tumors, 0.8265 (95%CI: 0.8004-0.8499) for inflammation, and 0.8022 (95%CI: 0.7616-0.8445) for other benign ones, while AUCs were 0.8675 (95%CI: 0.8525-0.8813) for lung adenocarcinoma (LUAD), 0.8792 (95%CI: 0.8640-0.8950) for squamous cell carcinoma (LUSC), 0.7404 (95%CI: 0.7031-0.7782) for other malignant ones respectively in the malignant group. Conclusions: The DeepLN based on deep learning algorithm represented a competitive performance to predict the imaging characteristics, malignancy and pathologic subtypes on the basis of non-invasive CT images, and thus had great possibility to be utilized in the routine clinical workflow.

Elevated BCAA Suppresses the Development and Metastasis of Breast Cancer.

Branched-chain amino acids (BCAAs) are the three essential amino acids including leucine, isoleucine, and valine. BCAA metabolism has been linked with the development of a variety of tumors. However, the impact of dietary BCAA intake on breast tumor progression and metastasis remains to be fully explored. Here, we unexpectedly find that the elevated BCAA, either in the genetic model or via increasing dietary intake in mice, suppresses the tumor growth and lung metastasis of breast cancer. The survival analysis shows that BCAA catabolic gene expression is strongly associated with long-term oncological outcomes in patients with breast cancer. In Pp2cm knockout mice in which BCAAs accumulate due to the genetic defect of BCAA catabolism, the breast tumor growth is suppressed. Interestingly, while the cell proliferation and tumor vasculature remain unaffected, more cell death occurs in the tumor in Pp2cm knockout mice, accompanied with increased natural killer (NK) cells. Importantly, increasing BCAA dietary intake suppresses breast tumor growth in mice. On the other hand, there are fewer lung metastases from primary breast tumor in Pp2cm knockout mice and the high BCAA diet-fed mice, suggesting high BCAA also suppresses the lung metastasis of breast cancer. Furthermore, low BCAA diet promotes lung colonization of breast cancer cells in tail vein model. The migration and invasion abilities of breast cancer cells are impaired by high concentration of BCAA in culture medium. The suppressed tumor metastasis and cell migration/invasion abilities by elevated BCAA are accompanied with reduced N-cadherin expression. Together, these data show high BCAA suppresses both tumor growth and metastasis of breast cancer, demonstrating the potential benefits of increasing BCAA dietary intake in the treatment of breast cancer.

Deep Learning to Predict EGFR Mutation and PD-L1 Expression Status in Non-Small-Cell Lung Cancer on Computed Tomography Images.

OBJECTIVE: The detection of epidermal growth factor receptor (EGFR) mutation and programmed death ligand-1 (PD-L1) expression status is crucial to determine the treatment strategies for patients with non-small-cell lung cancer (NSCLC). Recently, the rapid development of radiomics including but not limited to deep learning techniques has indicated the potential role of medical images in the diagnosis and treatment of diseases. METHODS: Eligible patients diagnosed/treated at the West China Hospital of Sichuan University from January 2013 to April 2019 were identified retrospectively. The preoperative CT images were obtained, as well as the gene status regarding EGFR mutation and PD-L1 expression. Tumor region of interest (ROI) was delineated manually by experienced respiratory specialists. We used 3D convolutional neural network (CNN) with ROI information as input to construct a classification model and established a prognostic model combining deep learning features and clinical features to stratify survival risk of lung cancer patients. RESULTS: The whole cohort (N = 1262) was divided into a training set (N = 882, 70%), validation set (N = 125, 10%), and test set (N = 255, 20%). We used a 3D convolutional neural network (CNN) to construct a prediction model, with AUCs of 0.96 (95% CI: 0.94-0.98), 0.80 (95% CI: 0.72-0.88), and 0.73 (95% CI: 0.63-0.83) in the training, validation, and test cohorts, respectively. The combined prognostic model showed a good performance on survival prediction in NSCLC patients (C-index: 0.71). CONCLUSION: In this study, a noninvasive and effective model was proposed to predict EGFR mutation and PD-L1 expression status as a clinical decision support tool. Additionally, the combination of deep learning features with clinical features demonstrated great stratification capabilities in the prognostic model. Our team would continue to explore the application of imaging markers for treatment selection of lung cancer patients.

Timing of chronic obstructive pulmonary disease diagnosis in lung cancer prognosis: a clinical and genomic-based study.

BACKGROUND: A two-phase study (clinical and genomic-based) was conducted to evaluate the effect of timing of chronic obstructive pulmonary disease (COPD) diagnosis on lung cancer outcomes. METHODS: The prognostic influence of COPD was investigated in a clinical cohort of 1,986 patients who received surgery for stage I lung cancer; 823 (41.4%) of them also had COPD, including 549 (27.6%) incidental COPD (diagnosed within 6-months of lung cancer diagnosis) and 274 (13.8%) prior COPD (>6 months before lung cancer diagnosis). The genomic variations were analyzed from another cohort of 1,549 patients for association with 384 lung cancer-related single nucleotide polymorphisms (SNPs). RESULTS: Older age (≥70 years), smokers, and respiratory symptoms were independent predictors of incidental COPD in lung cancer (all P<0.05). Similar to prior COPD, incidental COPD increased postoperative complications and worsened quality-of-life related to dyspnea (both P<0.05). Multivariate Cox regression analysis showed lung cancer survival decreased significantly in incidental COPD (HR, 1.30; 95% CI, 1.02-1.66), but not in prior COPD (HR, 1.15; 95% CI, 0.87-1.52). Among prior COPD, median survival showed a trend for being better in those with fewer exacerbations (0-1 vs. ≥2 exacerbation/year; 6.1 vs. 4.1 years; P=0.10). The SNP-based analysis identified ADCY2:rs52827085 was significantly associated with risk of incidental COPD (OR, 1.76; 95% CI, 1.30-2.38) and NRXN1:rs1356888 associated with prior COPD complicated with lung cancer (OR, 1.73; 95% CI, 1.29-2.33). CONCLUSIONS: Different long-term survival and genomic variants were observed between lung cancer patients with incidental and with prior COPD, suggesting timing of COPD diagnosis should be considered in lung cancer clinical management and mechanistic research.

A nomogram for predicting cancer-specific survival in patients with osteosarcoma as secondary malignancy.

The prognostic factors for survival among patients with secondary osteosarcoma remain unclear. The aim of this study was to develop a practical nomogram for predicting cancer-specific survival (CSS) in patients with osteosarcoma as a secondary malignancy. The surveillance, epidemiology, and end results database was used for the identification of osteosarcoma cases. The total sample comprised 5860 cases of primary osteosarcoma and 268 cases of secondary osteosarcoma during the period from 1973 to 2015. The CSS and overall survival (OS) of primary and secondary osteosarcomas were analyzed. The predictors of CSS for secondary osteosarcoma were identified and integrated to build a nomogram. Validation of the nomogram was performed using concordance index (C-index) and calibration plots. The results indicated that patients with secondary osteosarcoma had poorer CSS and OS than patients with primary osteosarcoma. The nomogram model exhibited high discriminative accuracy in the training cohort (C-index = 0.826), which was confirmed in the internal validation cohort (C-index = 0.791). In addition, the calibration plots confirmed good concordance for prediction of CSS at 3, 5, and 10 years. In conclusion, we developed a practical nomogram that provided individual predictions of CSS for patients with secondary osteosarcoma. This nomogram may help clinicians with prognostic evaluations and with the development of individualized therapies for this aggressive disease.

IU1 suppresses proliferation of cervical cancer cells through MDM2 degradation.

Previous studies have demonstrated that the antitumor potential of IU1 (a pharmacological compound), which was mediated by selective inhibition of proteasome-associated deubiquitinase ubiquitin-specific protease 14 (USP14). However, the underlying molecular mechanisms remain elusive. It has been well established that mdm2 (Murine double minute 2) gene was amplified and/or overexpressed in a variety of human neoplasms, including cervical cancer. Furthermore, MDM2 is critical to cervical cancer development and progression. Relatively studies have reported that USP15 and USP7 stabilized MDM2 protein levels by removing its ubiquitin chain. In the current study, we studied the cell proliferation status after IU1 treatment and the USP14-MDM2 protein interaction in cervical cancer cells. This study experimentally revealed that IU1 treatment reduced MDM2 protein expression in HeLa cervical cancer cells, along with the activation of autophagy-lysosomal protein degradation and promotion of ubiquitin-proteasome system (UPS) function, thereby blocked G0/G1 to S phase transition, decreased cell growth and triggered cell apoptosis. Thus, these results indicate that IU1 treatment simultaneously targets two major intracellular protein degradation systems, ubiquitin-proteasome and autophagy-lysosome systems, which leads to MDM2 degradation and contributes to the antitumor effect of IU1.

Low T790M relative allele frequency indicates concurrent resistance mechanisms and poor responsiveness to osimertinib.

BACKGROUND: T790M relative allele frequency (RAF) in plasma, calculated by the ratio of T790M to epidermal growth factor receptor (EGFR)-sensitizing mutation allele frequencies (AF), is associated with osimertinib response in patients with progressive non-small cell lung cancer (NSCLC) post 1st generation EGFR-tyrosine kinase inhibitor (TKI) treatment. However, which subgroup of patients carry concurrent resistance mechanisms and have poor responsiveness to osimertinib remains unknown. METHODS: Matched re-biopsy tissue and plasma samples obtained from 32 patients who had progression following 1st generation EGFR-TKI treatment were genotyped using next-generation sequencing (NGS) to investigate which subgroup of patients, classified by plasma position 790 (T790M) RAF, were more likely to carry concurrent resistance mechanisms. In another independent cohort, consisting of 21 T790M-positive patients, we validated whether these patients had a poor response to osimertinib treatment. RESULTS: In the discovery cohort, patients with T790M RAF less than 20% were more likely to harbor concurrent resistance mechanisms (P=0.018), such as MET or ERBB2 amplification, and small cell lung cancer transformation. In the validation cohort, we found that patients with low T790M RAF (<20%) had significantly lower objective response rates (ORRs) (0 vs. 68.8%, P=0.03) and disease control rates (DCRs) (60% vs. 100%, P=0.048) in response to osimertinib compared to patients with high T790M RAF. CONCLUSIONS: In patients with progressive NSCLC post 1st generation EGFR-TKI treatment, plasma T790M RAFs of less than 20% can be used to identify patients who carry concurrent resistance mechanisms, and can predict a poorer response to osimertinib. TRIAL REGISTRATION: This study was registered on http://www.chictr.org.cn (registration number: ChiCTR-DDD-16007900).

Exploiting an early warning Nomogram for predicting the risk of ICU admission in patients with COVID-19: a multi-center study in China.

BACKGROUND: Novel coronavirus disease 2019 (COVID-19) is a global public health emergency. Here, we developed and validated a practical model based on the data from a multi-center cohort in China for early identification and prediction of which patients will be admitted to the intensive care unit (ICU). METHODS: Data of 1087 patients with laboratory-confirmed COVID-19 were collected from 49 sites between January 2 and February 28, 2020, in Sichuan and Wuhan. Patients were randomly categorized into the training and validation cohorts (7:3). The least absolute shrinkage and selection operator and logistic regression analyzes were used to develop the nomogram. The performance of the nomogram was evaluated for the C-index, calibration, discrimination, and clinical usefulness. Further, the nomogram was externally validated in a different cohort. RESULTS: The individualized prediction nomogram included 6 predictors: age, respiratory rate, systolic blood pressure, smoking status, fever, and chronic kidney disease. The model demonstrated a high discriminative ability in the training cohort (C-index = 0.829), which was confirmed in the external validation cohort (C-index = 0.776). In addition, the calibration plots confirmed good concordance for predicting the risk of ICU admission. Decision curve analysis revealed that the prediction nomogram was clinically useful. CONCLUSION: We established an early prediction model incorporating clinical characteristics that could be quickly obtained on hospital admission, even in community health centers. This model can be conveniently used to predict the individual risk for ICU admission of patients with COVID-19 and optimize the use of limited resources.

Development and validation a nomogram for predicting the risk of severe COVID-19: A multi-center study in Sichuan, China.

BACKGROUND: Since December 2019, coronavirus disease 2019 (COVID-19) emerged in Wuhan and spread across the globe. The objective of this study is to build and validate a practical nomogram for estimating the risk of severe COVID-19. METHODS: A cohort of 366 patients with laboratory-confirmed COVID-19 was used to develop a prediction model using data collected from 47 locations in Sichuan province from January 2020 to February 2020. The primary outcome was the development of severe COVID-19 during hospitalization. The least absolute shrinkage and selection operator (LASSO) regression model was used to reduce data size and select relevant features. Multivariable logistic regression analysis was applied to build a prediction model incorporating the selected features. The performance of the nomogram regarding the C-index, calibration, discrimination, and clinical usefulness was assessed. Internal validation was assessed by bootstrapping. RESULTS: The median age of the cohort was 43 years. Severe patients were older than mild patients by a median of 6 years. Fever, cough, and dyspnea were more common in severe patients. The individualized prediction nomogram included seven predictors: body temperature at admission, cough, dyspnea, hypertension, cardiovascular disease, chronic liver disease, and chronic kidney disease. The model had good discrimination with an area under the curve of 0.862, C-index of 0.863 (95% confidence interval, 0.801-0.925), and good calibration. A high C-index value of 0.839 was reached in the interval validation. Decision curve analysis showed that the prediction nomogram was clinically useful. CONCLUSION: We established an early warning model incorporating clinical characteristics that could be quickly obtained on admission. This model can be used to help predict severe COVID-19 and identify patients at risk of developing severe disease.

The Wnt/ß-catenin/VASP positive feedback loop drives cell proliferation and migration in breast cancer.

Previous studies have shown that the main function of VASP is to regulate the cytoskeleton and play an important role in promoting tumor cell metastasis. In this study, we first reveal that VASP is located in the nucleus of breast cancer cells and elucidate a Wnt/ß-catenin/VASP positive feedback loop. We identify that VASP is a target gene of Wnt/ß-catenin signaling pathway, and activation of Wnt/ß-catenin signaling pathway can significantly upregulate VASP protein expression, while upregulated VASP protein can in turn promote translocation of ß-catenin and DVL3 proteins into the nucleus. In the nucleus, VASP, DVL3, ß-catenin, and TCF4 can form VASP/DVL3/ß-catenin/TCF4 protein complex, activating Wnt/ß-catenin signaling pathway, and promoting the expression of target genes VASP, c-myc, and cyclin D1. Thus, our study reveals that there is a Wnt/ß-catenin/VASP malignant positive feedback loop in breast cancer, which promotes the proliferation and migration of breast cancer cells, and breaking this positive feedback loop may provide new strategy for breast cancer treatment.