Non-small cell lung cancer (NSCLC) patients tend to develop brain metastases (BM), but the link between BM occurrence and driver mutations in NSCLC is not very clear. We explored whether activating mutations of epidermal growth factor receptors (EGFRs) in exon 19 deletion or L858R predict BM in NSCLC. A retrospective multivariable logistic regression analysis of 384 patients demonstrated that the presence of mutated-EGFRs was associated with overall BM (OR=2.24, P=0.001) compared to that of wild-type EGFR (WT-EGFR). Moreover, the time-to-event analysis model considering death as a competing risk revealed that, irrespective of survival, mutated-EGFRs predicted subsequent BM (SBM) in stage IIIB-IV patients (37.1% vs. 10.6%, HR=2.98, P=0.002) after adjusting for age (HR=2.00, P=0.012), gender, histological subtype, and smoking history. Notably, the younger mutated-EGFR subgroup was at a higher risk for SBM compared to the older WT-EGFR one (58.1% vs.10.9%, HR=6.57, P<0.001). Additionally, EGFR exon 19 deletion, despite having a slightly longer overall survival (20.6 vs. 14.2 months, P=0.368), was comparable to L858R mutation in predicting SBM (39.5% vs. 34.5%, HR=0.91, P=0.770). In vitro, the overexpression of mutated-EGFRs induced morphological changes towards a mesenchymal-like phenotype and promoted mobility in lung cancer cells. Clinically, mutated-EGFR NSCLC displayed a higher proportion of vimentin-positive expression (75.3% vs. 51.2%; P=0.007) and a shorter median time to SBM (23.5 months vs. not reached, P=0.017) than WT-EGFR NSCLC. These results suggest that NSCLC patients carrying mutated-EGFRs may require a higher frequency of brain imaging assessments than those with WT-EGFR to facilitate earlier SBM detection during follow-up.
T cell factor 4 (TCF4) interacts with beta-catenin in the WNT signaling pathway and transactivates downstream target genes involved in cancer progression. To identify proteins that regulate TCF4-mediated biological responses, we performed a yeast two-hybrid screen to search for a TCF4-binding protein(s) and found that MAD2B interacts with TCF4. We confirmed that MAD2B is a TCF4-binding protein by co-immunoprecipitation. Using the TOPFLASH reporter assay, we found that MAD2B blocks TCF4-mediated transactivation. The MAD2B binding regions of TCF4 were identified by TCF4 deletion mapping and electrophoretic mobility shift assay analysis. TCF4 and MAD2B interactions abolished the DNA binding ability of TCF4. Knockdown of MAD2B in SW480 colorectal cancer cells led to the conversion of epithelial cells to a mesenchymal fibroblastoid phenotype (epithelial-mesenchymal transdifferentiation). An E-cadherin promoter reporter analysis showed that MAD2B modulates TCF4-mediated E-cadherin expression. MAD2B knockdown blocked E-cadherin expression and significantly induced mesenchymal markers, such as N-cadherin and vimentin. Mesenchymal induction was accompanied by F-actin redistribution and the appearance of a fibroblastoid phenotype. MAD2B knockdown also increased both mRNA and protein levels of Slug, a known TCF4-induced E-cadherin transcriptional repressor. A chromatin immunoprecipitation assay showed that MAD2B silencing enhances the ability of TCF4 to bind the Slug promoter. Thus, MAD2B is a novel TCF4-interacting protein. This study provides the first evidence for the involvement of MAD2B in TCF4-mediated epithelial-mesenchymal transdifferentiation.
Abstract Tumor suppressor p53 plays a central role in preventing tumorigenesis. Here, we unravel how p53 modulates mitochondrial dynamics to restrain the metastatic properties of cancer cells. p53 inhibits the mammalian target of rapamycin complex 1 (mTORC1) signaling to attenuate the protein level of mitochondrial fission process 1 (MTFP1), which fosters the pro-fission dynamin-related protein 1 (Drp1) phosphorylation. This regulatory mechanism allows p53 to restrict cell migration and invasion governed by Drp1-mediated mitochondrial fission. Downregulating p53 expression or elevating the molecular signature of mitochondrial fission correlates with aggressive tumor phenotypes and poor prognosis in cancer patients. Upon p53 loss, exaggerated mitochondrial fragmentation stimulates the activation of the extracellular signal-regulated kinase 1/2 (ERK1/2) signaling resulting in epithelial-to-mesenchymal transition (EMT)-like changes in cell morphology, accompanied by accelerated matrix metalloproteinase-9 (MMP9) expression and invasive cell migration. Notably, blocking the activation of mTORC1/MTFP1/Drp1/ERK1/2 axis completely abolishes the p53 deficiency-driven cellular morphological switch, MMP9 expression, and cancer cell dissemination. Our findings unveil a hitherto unrecognized mitochondria-dependent molecular mechanism underlying the metastatic phenotypes of p53-compromised cancers.
Nanoparticles (NPs), such as liposomes, effectively evade the severe toxicity of unexpected accumulation and passively shuttle drugs into tumor tissues by enhanced permeability and retention. In the case of non-small cell lung cancer and pancreatic ductal adenocarcinoma, cancer-associated fibroblasts promote the aggregation of a gel-like extracellular matrix that forms a physical barrier in the desmoplastic stroma of the tumor. These stroma are composed of protein networks and glycosaminoglycans (GAGs) that greatly compromise tumor-penetrating performance, leading to insufficient extravasation and tissue penetration of NPs. Moreover, the presence of heparan sulfate (HS) and related proteoglycans on the cell surface and tumor extracellular matrix may serve as molecular targets for NP-mediated drug delivery. Here, a GAG-binding peptide (GBP) with high affinity for HS and high cell-penetrating activity was used to develop an HS-targeting delivery system. Specifically, liposomal doxorubicin (L-DOX) was modified by post-insertion with the GBP. We show that the in vitro uptake of L-DOX in A549 lung adenocarcinoma cells increased by GBP modification. Cellular uptake of GBP-modified L-DOX (L-DOX-GBP) was diminished in the presence of extracellular HS but not in the presence of other GAGs, indicating that the interaction with HS is critical for the cell surface binding of L-DOX-GBP. The cytotoxicity of doxorubicin positively correlated with the molecular composition of GBP. Moreover, GBP modification improved the in vivo distribution and anticancer efficiency of L-DOX, with enhanced desmoplastic targeting and extensive distribution. Taken together, GBP modification may greatly improve the tissue distribution and delivery efficiency of NPs against HS-abundant desmoplastic stroma-associated neoplasm.
Peer instruction is instructional in guiding students to learn by answering questions, and explaining and discussing their answers with peers. Researchers recommended asking students to write down their answers and explanations before discussion to prevent social loafing. In addition, text-based explanations can be recorded and analyzed. The quality of students' explanations varies, ranging from superficial and low-quality to detailed and in-depth high-quality explanations. In tradition, the qualities of students' explanations were assessed by experts. Recently, machine learning classification models have been developed and applied to classify texts. However, the level of explanations of questions are question-dependent. Thus, each question needs its classification model. Therefore, a feature transformation was applied in this study so that the explanations of different questions could be combined and applied to train the same classification model. An automated explanation quality assessment mechanism was developed based on the similarity of representative explanations of different qualities. Students' text-based explanations were collected and assessed by experts into four levels, ranging from 0 (worst) to 3 (best). The four-level classifications were merged into binary classifications of low (0 and 1) and high (2 and 3). Different classification models, including Support Vector Machine (SVM), Naive Bayes (NB), K Nearest Neighbor (KNN), Logistic Regression (LR), Random Forest (RF), and Bidirectional Encoder Representations from Transformers (BERT) were applied to train models and evaluate the accuracy of the models. In addition, three ensemble learning algorithms, including voting, stacking, and boosting, were applied to combine models chosen from SVM, NB, KNN, LR, and RF. The results showed that RF and RF+KNN+NB with stacking model showed the best accuracy (75.3%) among all four-level classification models whereas RF with boosting model showed the best accuracy (90%) among all binary classification models.
Gram‐negative bacteria cell wall is composed of two layers: the inner phospholipid membrane and the outer membrane with a highly conserved unique lipid called lipopolysaccharide (LPS; endotoxin). LPS acts as a permeability barrier against a number of bactericidal agents. Furthermore, LPS is well known as a potent inducer of the immune system when it is released to blood and often causes septic shock syndromes in human. Some but not every antimicrobial peptide can neutralize LPS stimulated proinflammatory responses. We have developed an easy method to restore antiendotoxin activities of inactive antimicrobial peptides by linking two inactive α‐helical peptides with the AGP sequence. Antibacterial activities were determined by the standard broth micro‐dilution method of National Committee for Clinical Laboratory Standards. Toxicities of the peptides were determined from measuring cell death by the MTT assay against human fibroblast (HFW cells). Dynamic light scattering (DLS) was used to measure the size increase of LPS in the presence of the peptides. The ability of LPS neutralization in vitro was measured by Limulus Amebocyte Lysate (LAL) assay. LPS can induce nitrite oxide (NO) and TNF‐α production in macrophage cells. Experimental mouse endotoxemia model was used to test the antiendotoxin activities of the peptides. Significant antiendotoxin effects were observed in vitro and in vivo with the AGP linked variant of the short α‐helical peptides KR12 and WR6. The results will be used to help us design more potent antimicrobial peptides for clinical application in the future. Support or Funding Information Grant Number 103‐2113‐M‐007‐009‐MY2, Ministry of Science and Technology, Taiwan
Cancer cell plasticity generates heterogeneous oncogenic subpopulations in tumors. How macroautophagy/autophagy, a catabolic system required for sustaining cell homeostasis, affects cancer cell plasticity, remains elusive. In this study, we report that MAP1LC3A/LC3A (microtubule associated protein 1 light chain 3 alpha), a key molecule in autophagy, is negatively associated with histological grade and distant metastasis of lung cancer. This is achieved in part, if not all, by maintaining the mitochondria and energy homeostasis to meet the proliferation demand of lung cancer cells driven by SOX2 (SRY-box transcription factor 2) signaling. Basal autophagy is preferentially active in SOX2-positive lung cancer cells with high-proliferative and low-invasive properties. The high-proliferative cancer cells exhibit higher oxygen consumption rate (OCR), elevated reactive oxygen species (ROS), and profound fragmented mitochondrial patterns compared to their high-invasive counterparts. SOX2 expression promotes LC3A expression and enhances proliferation but attenuates invasion in lung cancer cells. LC3A silencing enriches cells harboring low-proliferative and high-invasive features, concomitant with decreased OCR and ROS levels and reduced expression of SOX2. Our findings provide novel insights into how basal autophagy cross talks with SOX2 proliferation signaling to regulate mitochondrial metabolism and determines cancer cell plasticity with an impact on lung tumor progression.Abbreviations ATG14: autophagy related 14; CDH2: cadherin 2; ChIP-qPCR: chromatin immunoprecipitation quantitative polymerase chain reaction; CQ: chloroquine; ECAR: extracellular acidification rate; EMT: epithelial-mesenchymal transition; EPCAM: epithelial cell adhesion molecule; MAP1LC3A/LC3A: microtubule associated protein 1 light chain 3 alpha; MAP1LC3B/LC3B: microtubule associated protein 1 light chain 3 beta; MAP1LC3C/LC3C: microtubule associated protein 1 light chain 3 gamma; NDUFV2: NADH:ubiquinone oxidoreductase core subunit V2; OCR: oxygen consumption rate; ROS: reactive oxygen species; RT-qPCR: reverse-transcriptase quantitative polymerase chain reaction; SC: scrambled control; shRNA: short hairpin RNA; SNAI2: snail family transcriptional repressor 2; SOX2: SRY-box transcription factor 2; SQSTM1/p62: sequestosome 1; TGFB/TGF-β: transforming growth factor beta; TOMM20: translocase of outer mitochondrial membrane 20; ZEB1: zinc finger E-box binding homeobox 1
The retinoblastoma (RB) transcriptional corepressor 1 (RB1) is a critical tumor suppressor gene, governing diverse cellular processes implicated in cancer biology. Dysregulation or deletion in RB1 contributes to the development and progression of various cancers, making it a prime target for therapeutic intervention. RB1's canonical function in cell cycle control and DNA repair mechanisms underscores its significance in restraining aberrant cell growth and maintaining genomic stability. Understanding the complex interplay between RB1 and cellular pathways is beneficial to fully elucidate its tumor-suppressive role across different cancer types and for therapeutic development. As a result, investigating vulnerabilities arising from RB1 deletion-associated mechanisms offers promising avenues for targeted therapy. Recently, several findings highlighted multiple methods as a promising strategy for combating tumor growth driven by RB1 loss, offering potential clinical benefits in various cancer types. This review summarizes the multifaceted role of RB1 in cancer biology and its implications for targeted therapy.
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