An optimized machine learning model for predicting hospitalization for COVID-19 infection in the maintenance dialysis population.

COVID-19 has a high rate of infection in dialysis patients and poses a serious risk to human health. Currently, there are no dialysis centers in China that have analyzed the prevalence of COVID-19 infection in dialysis patients and the mortality rate. Although machine learning-based disease prediction methods have proven to be effective, redundant attributes in the data and the interpretability of the predictive models are still worth investigating. Therefore, this paper proposed a wrapper feature selection classification model to achieve the prediction of the risk of COVID-19 infection in dialysis patients. The method was used to optimize the feature set of the sample through an enhanced JAYA optimization algorithm based on the dispersed foraging strategy and the greedy levy mutation strategy. Then, the proposed method combines fuzzy K-nearest neighbor for classification prediction. IEEE CEC2014 benchmark function experiments as well as prediction experiments on the uremia dataset are used to validate the proposed model. The experimental results showed that the proposed method has a high prediction accuracy of 95.61% for the prevalence risk of COVID-19 infection in dialysis patients. Furthermore, it was shown that proalbumin, CRP, direct bilirubin, hemoglobin, albumin, and phosphorus are of great value for clinical diagnosis. Therefore, the proposed method can be considered as a promising method.

An intent classification method for questions in "Treatise on Febrile diseases" based on TinyBERT-CNN fusion model.

"Treatise on Febrile Diseases" is an important classic book in the academic history of Chinese material medica. Based on the knowledge map of traditional Chinese medicine established by the study of "Treatise on Febrile Diseases", a question-answering system of traditional Chinese medicine was established to help people better understand and use traditional Chinese medicine. Intention classification is the basis of the question-answering system of traditional Chinese medicine, but as far as we know, there is no research on question intention classification based on "Treatise on Febrile Diseases". In this paper, the intent classification research is carried out based on the Chinese material medica-related content materials in "Treatise on Febrile Diseases" as data. Most of the existing models perform well on long text classification tasks, with high costs and a lot of memory requirements. However, the intent classification data of this paper has the characteristics of short text, a small amount of data, and unbalanced categories. In response to these problems, this paper proposes a knowledge distillation-based bidirectional Transformer encoder combined with a convolutional neural network model (TinyBERT-CNN), which is used for the task of question intent classification in "Treatise on Febrile Diseases". The model used TinyBERT as an embedding and encoding layer to obtain the global vector information of the text and then completed the intent classification by feeding the encoded feature information into the CNN. The experimental results indicated that the model outperformed other models in terms of accuracy, recall, and F1 values of 96.4%, 95.9%, and 96.2%, respectively. The experimental results prove that the model proposed in this paper can effectively classify the intent of the question sentences in "Treatise on Febrile Diseases", and provide technical support for the question-answering system of "Treatise on Febrile Diseases" later.

An artificial bee bare-bone hunger games search for global optimization and high-dimensional feature selection.

The domains of contemporary medicine and biology have generated substantial high-dimensional genetic data. Identifying representative genes and decreasing the dimensionality of the data can be challenging. The goal of gene selection is to minimize computing costs and enhance classification precision. Therefore, this article designs a new wrapper gene selection algorithm named artificial bee bare-bone hunger games search (ABHGS), which is the hunger games search (HGS) integrated with an artificial bee strategy and a Gaussian bare-bone structure to address this issue. To evaluate and validate the performance of our proposed method, ABHGS is compared to HGS and a single strategy embedded in HGS, six classic algorithms, and ten advanced algorithms on the CEC 2017 functions. The experimental results demonstrate that the bABHGS outperforms the original HGS. Compared to peers, it increases classification accuracy and decreases the number of selected features, indicating its actual engineering utility in spatial search and feature selection.

Prophylactic inguinal lymphadenectomy for high-risk cN0 penile cancer: The optimal surgical timing.

Background: Few reports have investigated the oncologically safe timing of prophylactic inguinal lymphadenectomy for penile cancer patients with clinically normal inguinal lymph nodes (cN0), particularly those who received delayed surgical treatment. Methods: The study included pT1aG2, pT1b-3G1-3 cN0M0 patients with penile cancer who received prophylactic bilateral inguinal lymph nodes dissection (ILND) at the Department of Urology of Tangdu Hospital between October 2002 and August 2019. Patients who received simultaneous resection of primary tumor and inguinal lymph nodes were assigned to the immediate group, while the rest were assigned to the delayed group. The optimal timing of lymphadenectomy was determined based on the time-dependent ROC curves. The disease-specific survival (DSS) was estimated based on the Kaplan-Meier curve. Cox regression analysis was used to evaluate the associations between DSS and the timing of lymphadenectomy and tumor characteristics. The analyses were repeated after stabilized inverse probability of treatment weighting adjustment. Results: A total of 87 patients were enrolled in the study, 35 of them in the immediate group and 52 in the delayed group. The median (range) interval time between primary tumor resection and ILND of the delayed group was 85 (29-225) days. Multivariable Cox analysis demonstrated that immediate lymphadenectomy was associated with a significant survival benefit (HR, 0.11; 95% CI, 0.02-0.57; p = 0.009). An index of 3.5 months was determined as the optimal cut-point for dichotomization in the delayed group. In high-risk patients who received delayed surgical treatment, prophylactic inguinal lymphadenectomy within 3.5 months was associated with a significantly better DSS compared to dissection after 3.5months (77.8% and 0%, respectively; log-rank p<0.001). Conclusions: Immediate and prophylactic inguinal lymphadenectomy in high-risk cN0 patients (pT1bG3 and all higher stage tumours) with penile cancer improves survival. For those patients at high risk who received delayed surgical treatment for any reason, within 3.5 months after resection of the primary tumor seems to be an oncologically safe window for prophylactic inguinal lymphadenectomy.

Intradialytic hypotension prediction using covariance matrix-driven whale optimizer with orthogonal structure-assisted extreme learning machine.

Intradialytic hypotension (IDH) is an adverse event occurred during hemodialysis (HD) sessions with high morbidity and mortality. The key to preventing IDH is predicting its pre-dialysis and administering a proper ultrafiltration prescription. For this purpose, this paper builds a prediction model (bCOWOA-KELM) to predict IDH using indices of blood routine tests. In the study, the orthogonal learning mechanism is applied to the first half of the WOA to improve the search speed and accuracy. The covariance matrix is applied to the second half of the WOA to enhance the ability to get out of local optimum and convergence accuracy. Combining the above two improvement methods, this paper proposes a novel improvement variant (COWOA) for the first time. More, the core of bCOWOA-KELM is that the binary COWOA is utilized to improve the performance of the KELM. In order to verify the comprehensive performance of the study, the paper sets four types of comparison experiments for COWOA based on 30 benchmark functions and a series of prediction experiments for bCOWOA-KELM based on six public datasets and the HD dataset. Finally, the results of the experiments are analyzed separately in this paper. The results of the comparison experiments prove fully that the COWOA is superior to other famous methods. More importantly, the bCOWOA performs better than its peers in feature selection and its accuracy is 92.41%. In addition, bCOWOA improves the accuracy by 0.32% over the second-ranked bSCA and by 3.63% over the worst-ranked bGWO. Therefore, the proposed model can be used for IDH prediction with future applications.

Prediction of recurrent spontaneous abortion using evolutionary machine learning with joint self-adaptive sime mould algorithm.

Recurrent spontaneous abortion (RSA) is a frequent abnormal pregnancy with long-term psychological repercussions that disrupt the peace of the whole family. In the diagnosis and treatment of RSA worsened by thyroid disorders, recurrent spontaneous abortion is also a significant obstacle. The pathogenesis and possible treatment methods for RSA are yet unclear. Using clinical information, vitamin D and thyroid function measurements from normal pregnant women with RSA, we attempt to build a framework for conducting an effective analysis for RSA in this research. The framework is presented by combining the joint self-adaptive sime mould algorithm (JASMA) with the common kernel learning support vector machine with maximum-margin hyperplane theory, abbreviated as JASMA-SVM. The JASMA has a complete set of adaptive parameter change methods, which improves the algorithm's global search and optimization capabilities and guarantees that it speeds convergence and departs from the local optimum. On CEC 2014 benchmarks, the property of JASMA is validated, and then it is utilized to concurrently optimize parameters and select optimal features for SVM on RSA data from VitD, thyroid hormone levels, and thyroid autoantibodies. The statistical results demonstrate that the proposed JASMA-SVM can be treated as a potential tool for RSA with accuracy of 92.998%, MCC of 0.92425, sensitivity of 93.286%, specificity of 93.064%.

Targeting cancer stemness mediated by BMI1 and MCL1 for non-small cell lung cancer treatment.

Lung cancer is the leading cause of cancer-associated death, with a global 5-year survival rate <20%. Early metastasis and recurrence remain major challenges for lung cancer treatment. The stemness property of cancer cells has been suggested to play a key role in cancer plasticity, metastasis and drug-resistance, and is a potential target for drug development. In this study, we found that in non-small cell lung cancer (NSCLC), BMI1 and MCL1 play crucial roles of cancer stemness including invasion, chemo-resistance and tumour initiation. JNK signalling serves as a link between oncogenic pathway or genotoxicity to cancer stemness. The activation of JNK, either by mutant EGFR or chemotherapy agent, stabilized BMI1 and MCL1 proteins through suppressing the expression of E3-ubiquitin ligase HUWE1. In lung cancer patient samples, high level of BMI1 is correlated with poor survival, and the expression of BMI1 is positively correlated with MCL1. A novel small-molecule, BI-44, was developed, which effectively suppressed BMI1/MCL1 expressions and inhibited tumour formation and progression in preclinical models. Targeting cancer stemness mediated by BMI1/MCL1 with BI-44 provides the basis for a new therapeutic approach in NSCLC treatment.

Stabilization of AURKA by the E3 ubiquitin ligase CBLC in lung adenocarcinoma.

CBL family proteins (CBL, CBLB and CBLC in mammals) are E3 ubiquitin ligases of protein tyrosine kinases. CBL mediates the lysosomal degradation of activated EGFR through K63-linked ubiquitination, while CBLC has an oncogenic function by positively regulating EGFR activation through K6 and K11-linked ubiquitination in EGFR mutant lung adenocarcinoma (LAD). Here, we used immunoprecipitation and mass spectrometry to study the CBLC interactome, and found that CBLC is also involved in cell cycle regulation by stabilizing Aurora kinase A (AURKA). CBLC interacted with the kinase domain of AURKA and positively regulated the stability of AURKA by conjugating monoubiquitination and K11/K63-linked polyubiquitination, which are protective from degrading K11/K48 polyubiquitination. CBLC depletion markedly decreased the half-life of AURKA in cycloheximide-treated LAD cells. When LAD cells were synchronized with double thymidine block at the G1/S boundary and then released into mitotic arrest, CBLC depletion delayed the accumulation and activation of AURKA and prevented cancer cells from entering mitosis. CBLC deficiency significantly delayed cell cycle progression, reduced the mitotic population, and increased apoptosis of LAD cells. Targeting CBLC inhibited tumor growth of LAD cells and enhanced their sensitivity to paclitaxel in xenograft models. Immunohistochemical staining of the tissue microarray also revealed a positive correlation between the expression of CBLC and AURKA in normal and LAD tissues, further supporting the positive regulation of AURKA expression by CBLC. In summary, these findings indicate that the oncogenic E3 ligase CBLC plays a role in mitotic entry by stabilizing AURKA via ubiquitination in LAD. This work demonstrates that targeting CBLC combined with paclitaxel might be a potential option for the treatment of LAD patients who have no available targeted therapies.

Impact Position Estimation for Baseball Batting with a Force-Irrelevant Vibration Feature.

In this work we propose a novel method for impact position estimation during baseball batting, which is independent of impact intensity, i.e., force-irrelevant. In our experiments, we mount a piezoelectric vibration sensor on the knob of a wooden bat to record: (1) 3600 vibration signals (waveforms) from ball-bat impacts in the static experiment-30 impacts from each of 40 positions (distributed 1-40 cm from the end of the barrel) and 3 intensities (drop heights at 75, 100, and 125 cm, resp.), and (2) 45 vibration signals from actual battings by three baseball players in the dynamic experiment. The results show that the peak amplitude of the signal in the time domain, and the peaks of the first, second, and third eigenfrequencies (EFs) of the bat all increase with the impact intensity. However, the ratios of peaks at these three EFs (1st/2nd, 2nd/3rd, and 1st/3rd) hardly change with the impact intensity, and the observation is consistent for both the static and dynamic experiments across all impact positions. In conclusion, we have observed that the ratios of peaks at the first three EFs are a force-irrelevant feature, which can be used to estimate the impact position in baseball batting.

AGEs-Induced Calcification and Apoptosis in Human Vascular Smooth Muscle Cells Is Reversed by Inhibition of Autophagy.

Vascular calcification (VC) in macrovascular and peripheral blood vessels is one of the main factors leading to diabetes mellitus (DM) and death. Apart from the induction of vascular calcification, advanced glycation end products (AGEs) have also been reported to modulate autophagy and apoptosis in DM. Autophagy plays a role in maintaining the stabilization of the external and internal microenvironment. This process is vital for regulating arteriosclerosis. However, the internal mechanisms of this pathogenic process are still unclear. Besides, the relationship among autophagy, apoptosis, and calcification in HASMCs upon AGEs exposure has not been reported in detail. In this study, we established a calcification model of SMC through the intervention of AGEs. It was found that the calcification was upregulated in AGEs treated HASMCs when autophagy and apoptosis were activated. In the country, AGEs-activated calcification and apoptosis were suppressed in Atg7 knockout cells or pretreated with wortmannin (WM), an autophagy inhibitor. These results provide new insights to conduct further investigations on the potential clinical applications for autophagy inhibitors in the treatment of diabetes-related vascular calcification.

Alisertib inhibits migration and invasion of EGFR-TKI resistant cells by partially reversing the epithelial-mesenchymal transition.

Epithelial growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have been widely used in the clinical treatment of non-small cell lung cancer (NSCLC) patients with EGFR mutations. Previous studies have shown that Aurora kinase A (AURKA) is overexpressed in a broad spectrum of cancer cells, which can induce epithelial-mesenchymal transition (EMT) and contribute to the occurrence of acquired EGFR-TKI resistance. However, whether the inhibition of AURKA could overcome EGFR-TKI resistance or reverse the EMT in TKI-resistant NSCLC cells remains unclear. In the current study, we established three EGFR-TKI-resistant cell lines and analyzed their expression profiles by RNA sequencing. The results revealed that the EMT pathway is significantly upregulated in the three cell lines with EGFR-TKI resistance. The phosphorylation of AURKA at Thr 288 was also upregulated, suggesting that the activation of AURKA plays an important role in the occurrence of EGFR-TKI resistance. Interestingly, the AURKA inhibitor, alisertib treatment restored the susceptibility of resistant cells to EGFR-TKIs and partially reversed the EMT process, thereby reducing migration and invasion in EGFR-TKI-resistant cells. This study provides evidence that targeting AURKA signaling pathway by alisertib may be a novel approach for overcoming EGFR-TKI resistance and for the treatment of metastatic EGFR-TKIs in NSCLC patients.

TAZ negatively regulates the novel tumor suppressor ANKRD52 and promotes PAK1 dephosphorylation in lung adenocarcinomas.

Lung cancer is the leading cause of cancer death, and therefore the discovery of novel therapeutic targets is crucial. P21-activated kinase (PAK1) is an important oncogene involved in the signaling of actin cytoskeleton organization. Although PAK1 inhibition has been shown to suppress cancer progression, specific PAK1 inhibitors are not available due to the complex structure and insufficient understanding of this kinase. The Hippo signaling effector TAZ is known to be elevated in multiple human cancers and to promote cancer metastasis. This study aimed to explore the role of TAZ in regulating the tumor suppressor ankyrin repeat domain 52 (ANKRD52) and PAK1 activity. A negative correlation between TAZ and ANKRD52 was observed, with knockdown of TAZ leading to enhanced ANKRD52 promoter activity and increased mRNA levels. Moreover, reduced ANKRD52 levels were associated with late-stage lung cancer. Knockdowns of ANKRD52 resulted in elevated cell mobility, while forced ANKRD52 expression attenuated cell mobility. ANKRD52 is a subunit of the protein phosphatase 6 (PP6) holoenzyme. Mass spectrometry analysis revealed the interaction between PAK1 and the ANKRD52-PP6 complex. Knockdown of ANKRD52 or PP6c resulted in upregulated PAK1 phosphorylation. Our study demonstrates that the novel tumor suppressor protein ANKRD52 is transcriptionally inhibited by TAZ, regulating cell mobility through interactions with PP6c and dephosphorylation of PAK1.

Identification of the Prognostic Value and Clinical Significance of Interferon Regulatory Factors (IRFs) in Colon Adenocarcinoma.

BACKGROUND Colon adenocarcinoma (COAD) is one of the most common malignant tumors and has high incidence and mortality rates. The interferon regulatory factor (IRF) family is known as a key transcription factor in the IFN signaling pathway and cellular immunity. This research explored the relationship between the IRF family and COAD through use of bioinformatics technology. MATERIAL AND METHODS Using the UALCAN and GEPIA databases, we analyzed the transcription and prognostic value of IRFs in COAD, and GSCALite was used in cancer genomics analysis. TIMER, LinkedOmics, and Metascape were used to assess the potential function of IRFs in COAD. RESULTS The transcription levels of IRF3 were elevated in COAD tissues, while IRF2/4/6 were downregulated compared with normal patients in subgroup analyses of race, age, weight, sex, nodal metastasis, individual cancer stages, TP53 mutation status, and histological subtypes. IRF3 and IRF7 in COAD were significantly associated with a poor prognosis. Drug sensitivity analysis revealed that the expression level of IRF2/4/8 was negatively associated with drug resistance. A significant correlation was found between the IRF family and immune cell infiltration. Moreover, enrichment analysis revealed that the IRFs were associated with response to tumor necrosis factor, transcription misregulation in cancer, and JAK-STAT signaling pathway. We also identified several kinase and miRNA targets of the IRF family in COAD. CONCLUSIONS We identified IRF3 and IRF7 as prognostic biomarkers in COAD, and the IRF family was associated with immune cell infiltration and gene regulation networks, providing additional evidence showing the significant role of the IRF family in COAD.

Low-Dose Nicotine Activates EGFR Signaling via α5-nAChR and Promotes Lung Adenocarcinoma Progression.

Nicotine in tobacco smoke is considered carcinogenic in several malignancies including lung cancer. The high incidence of lung adenocarcinoma (LAC) in non-smokers, however, remains unexplained. Although LAC has long been less associated with smoking behavior based on previous epidemiological correlation studies, the effect of environmental smoke contributing to low-dose nicotine exposure in non-smoking population could be underestimated. Here we provide experimental evidence of how low-dose nicotine promotes LAC growth in vitro and in vivo. Screening of nicotinic acetylcholine receptor subunits in lung cancer cell lines demonstrated a particularly high expression level of nicotinic acetylcholine receptor subunit α5 (α 5-nAChR) in LAC cell lines. Clinical specimen analysis revealed up-regulation of α 5-nAChR in LAC tumor tissues compared to non-tumor counterparts. In LAC cell lines α 5-nAChR interacts with epidermal growth factor receptor (EGFR), positively regulates EGFR pathway, enhances the expression of epithelial-mesenchymal transition markers, and is essential for low-dose nicotine-induced EGFR phosphorylation. Functionally, low-dose nicotine requires α 5-nAChR to enhance cell migration, invasion, and proliferation. Knockdown of α 5-nAChR inhibits the xenograft tumor growth of LAC. Clinical analysis indicated that high level of tumor α 5-nAChR is correlated with poor survival rates of LAC patients, particularly in those expressing wild-type EGFR. Our data identified α 5-nAChR as an essential mediator for low-dose nicotine-dependent LAC progression possibly through signaling crosstalk with EGFR, supporting the involvement of environmental smoke in tumor progression in LAC patients.

In silico identification of thiostrepton as an inhibitor of cancer stem cell growth and an enhancer for chemotherapy in non-small-cell lung cancer.

Cancer stem cells (CSCs) play an important role in cancer treatment resistance and disease progression. Identifying an effective anti-CSC agent may lead to improved disease control. We used CSC-associated gene signatures to identify drug candidates that may inhibit CSC growth by reversing the CSC gene signature. Thiostrepton, a natural cyclic oligopeptide antibiotic, was the top-ranked candidate. In non-small-cell lung cancer (NSCLC) cells, thiostrepton inhibited CSC growth in vitro and reduced protein expression of cancer stemness markers, including CD133, Nanog and Oct4A. In addition, metastasis-associated Src tyrosine kinase signalling, cell migration and epithelial-to-mesenchymal transition (EMT) were all inhibited by thiostrepton. Mechanistically, thiostrepton treatment led to elevated levels of tumour suppressor miR-98. Thiostrepton combined with gemcitabine synergistically suppressed NSCLC cell growth and induced apoptosis. The inhibition of NSCLC tumours and CSC growth by thiostrepton was also demonstrated in vivo. Our findings indicate that thiostrepton, an established drug identified in silico, is an inhibitor of CSC growth and a potential enhancer of chemotherapy in NSCLC.

Pigment epithelium-derived factor peptide reverses mouse age-related meibomian gland atrophy.

Age-related meibomian gland (MG) atrophy, characterized by decreased meibocyte proliferation, is one of the causes of meibomian gland dysfunction (MGD), which leads to dry eye disease. Currently, there is no available treatment effectively preventing or reversing the decreased cell proliferation and acinar tissue atrophy. In this study, we investigated the therapeutic effects of a pigment epithelium-derived factor (PEDF) peptide in treating this condition. We found abundant expression of PEDF in the nucleus of acinar basal cells, but not in mature meibocytes, and that the expression levels were significantly decreased in the aged mice. We next treated the aged mice (15-month old) with atrophic MGs using a synthetic PEDF-derived peptide 29-mer (residues 93-121). We found that 29-mer effectively stimulated acinar basal cell proliferation and the following mature meibocyte proliferation in the atrophied MGs. In addition, the treatment increased ΔNp63 and Lrig1 expressions in acinar basal cells. Finally, the aged mice receiving the treatment showed MG growth and improved tear film break-up time. In conclusion, the 29-mer treatment is effective in promoting MG acinar basal cell proliferation and enlarging the acinar size of MG, as well as improving MG function in aged mice, suggesting a therapeutic potential of the PEDF-derived short peptide in ameliorating age-related MGD.

Pigment epithelium-derived factor peptide promotes limbal stem cell proliferation through hedgehog pathway.

Expansion of limbal epithelial stem cells (LSCs) is crucial for the success of limbal transplantation. Previous studies showed that pigment epithelium-derived peptide (PEDF) short peptide 44-mer could effectively expand LSCs and maintain them in a stem-cell state, but the mechanism remained unclear. In the current study, we found that pharmacological inhibition of Sonic Hedgehog (SHh) activity reduced the LSC holoclone number and suppressed LSC proliferation in response to 44-mer. In mice subjected to focal limbal injury, 44-mer facilitated the restoration of the LSC population in damaged limbus, and such effect was impeded by the SHh or ATGL (a PEDF receptor) inhibitor. Furthermore, we showed that 44-mer increased nuclear translocation of Gli1 and Gli3 in LSCs. Knockdown of Gli1 or Gli3 suppressed the ability of 44-mer to induce cyclin D1 expression and LSC proliferation. In addition, ATGL inhibitor suppressed the 44-mer-induced phosphorylation of STAT3 at Tyr705 in LSC. Both inhibitors for ATGL and STAT3 attenuated 44-mer-induced SHh activation and LSC proliferation. In conclusion, our data demonstrate that SHh-Gli pathway driven by ATGL/STAT3 signalling accounts for the 44-mer-mediated LSC proliferation.

OCT4B mediates hypoxia-induced cancer dissemination.

Hypoxia, the reduction of oxygen levels in cells or tissues, elicits a set of genes to adjust physiological and pathological demands during normal development and cancer progression. OCT4, a homeobox transcription factor, is essential for self-renewal of embryonic stem cells, but little is known about the role of OCT4 in non-germ-cell tumorigenesis. Here, we report that hypoxia stimulates a short isoform of OCT4, called OCT4B, via a HIF2α-dependent pathway to induce the epithelial-mesenchymal transition (EMT) and facilitate cancer dissemination. OCT4B overexpression decreased epithelial barrier properties, which led to an increase in cell migration and invasion in lung cancer cells. OCT4B knockdown attenuated HIF2α-induced EMT and inhibited cancer dissemination in cell-line and animal models. We observed that OCT4B bound the SLUG promoter and enhanced its expression, and SLUG silencing inhibited OCT4B-mediated EMT, accompanied with decreased cell migration and invasion. Correlation analysis revealed that OCT4B expression was significantly associated with the SLUG level in lung tumors. These results provide novel insights into OCT4B-mediated oncogenesis in cancer dissemination.

Upregulation of E3 Ubiquitin Ligase CBLC Enhances EGFR Dysregulation and Signaling in Lung Adenocarcinoma.

CBLC (CBL proto-oncogene c) belongs to the CBL protein family, which has E3 ubiquitin ligase activity toward activated receptor tyrosine kinases. CBLC is frequently upregulated in non-small cell lung cancer (NSCLC), yet very little is known about the functions of CBLC in tumorigenesis. Here we show that CBLC is an epigenetically demethylated target and its expression can be upregulated in NSCLC after treatment with the DNA methylation inhibitor 5'-azacytidine. Depletion of CBLC significantly inhibited cell viability and clonogenicity in vitro and reduced tumor growth in a xenograft model. CBLC silencing further sensitized EGFR-mutated NSCLC cells to treatment with tyrosine kinase inhibitors. Conversely, ectopic expression of CBLC enhanced the activation of EGFR and downstream ERK1/2 signaling after ligand stimulation by competing with CBL for EGFR binding. Analysis of ubiquitin linkages on activated EGFR (aEGFR) revealed that CBLC ubiquitinated and positively regulated aEGFR stability through the conjugation of polyubiquitin by K6 and K11 linkages. This CBLC-mediated polyubiquitination promoted either preferential recycling of aEGFR back to the plasma membrane or trafficking to the cell nucleus. IHC analyses revealed a positive correlation between phospho-EGFR and CBLC in lung adenocarcinoma. In summary, we demonstrate a novel mechanism by which aEGFR escapes lysosomal degradation in a CBLC/ubiquitin-dependent manner to sustain its activation. Our work identifies CBLC as a potential diagnostic biomarker and also points to its utilization as a novel therapeutic target for NSCLC therapy.Significance: This work demonstrates the role of CBLC expression as a diagnostic biomarker and potential therapeutic target in lung adenocarcinoma. Cancer Res; 78(17); 4984-96. ©2018 AACR.