FGA isoform as an indicator of targeted therapy for EGFR mutated lung adenocarcinoma

Prognostic Indicators for Precision Treatment of Non-Small Cell Lung Carcinoma

Non-small cell lung cancer (NSCLC) has established predictive biomarkers that enable decisions on treatment regimens for many patients. However, resistance to therapy is widespread. It is therefore essential to have a panel of molecular biomarkers that may help overcome therapy resistance and prevent adverse effects of treatment. We performed in silico analysis of NSCLC prognostic indicators, separately for adenocarcinomas and squamous carcinomas, by using The Cancer Genome Atlas (TCGA) and non-TCGA data sources in cBioPortal as well as UALCAN. This review describes lung cancer biology, elaborating on the key genetic alterations and specific genes responsible for resistance to conventional treatments. Importantly, we examined the mechanisms associated with resistance to immune checkpoint inhibitors. Our analysis indicated that a robust prognostic biomarker was lacking for NSCLC, especially for squamous cell carcinomas. In this work, our screening uncovered previously unidentified prognostic gene expression indicators, namely, MYO1E, FAM83 homologs, and DKK1 for adenocarcinoma, and FGA and TRIB1 for squamous cell carcinoma. It was further observed that overexpression of these genes was associated with poor prognosis. Additionally, FAM83 homolog and TRIB1 unexpectedly harbored copy number amplifications. In conclusion, this study elucidated novel prognostic indicators for NSCLC that may serve as targets to overcome therapy resistance toward improved patient outcomes.

Profiling the alterations of serum proteome in dairy cows with retained placenta using high-throughput tandem mass tags quantitative approach

BACKGROUND

Retained placenta (RP), a quite common disorder in dairy cows, shows a high negative impact on their health status and milk production.

AIM

To investigate the difference in the serum proteome between the cows with RP and the physiologic puerperium (PP).

MATERIAL & METHODS

Analysis of serum samples from nine cows with RP and six with PP using high-resolution liquid chromatography-tandem mass spectrometry approach. The proteins differing in the relative abundance between the PP and RP groups were classified using the Protein Analysis Through Evolutionary Relationship tool. For the pathway enrichment analysis, the REACTOME tool, with the human genome as the background, was employed. The criterion for significance was the false discovery rate corrected P-value less than 0.05.

RESULTS

In total 651 proteins were identified with altered relative abundance of ten proteins. Among them, seven had higher, and three showed lower relative abundance in RP than in the PP group. The differently abundant proteins participated in 15 pathways: six related to hemostasis, three involved in lipoprotein metabolism, and the remaining ones associated with for instance redox homeostasis, post-translational modification, and scavenging. Finally, the validation of the proteomic results showed that haptoglobin and lipopolysaccharide-binding protein levels reliably differentiated between the RP and PP groups.

CONCLUSION

The pattern of serum proteome alterations in the cows with RP mirrored several interplaying mechanisms underlying the systematic response to the presence of RP, therefore representing a source to mine for predictive or prognostic biomarkers.

Identification of coagulation-associated subtypes of lung adenocarcinoma and establishment of prognostic models

Lung adenocarcinoma (LUAD), the most common subtype of lung cancer, is a global health challenge with high recurrence and mortality rates. The coagulation cascade plays an essential role in tumor disease progression and leads to death in LUAD. We differentiated two coagulation-related subtypes in LUAD patients in this study based on coagulation pathways collected from the KEGG database. We then demonstrated significant differences between the two coagulation-associated subtypes regarding immune characteristics and prognostic stratification. For risk stratification and prognostic prediction, we developed a coagulation-related risk score prognostic model in the Cancer Genome Atlas (TCGA) cohort. The GEO cohort also validated the predictive value of the coagulation-related risk score in terms of prognosis and immunotherapy. Based on these results, we identified coagulation-related prognostic factors in LUAD, which may serve as a robust prognostic biomarker for therapeutic and immunotherapeutic efficacy. It may contribute to clinical decision-making in patients with LUAD.

The Role of Proteomics and Phosphoproteomics in the Discovery of Therapeutic Targets and Biomarkers in Acquired EGFR-TKI-Resistant Non-Small Cell Lung Cancer

The discovery of potent EGFR-tyrosine kinase inhibitors (EGFR-TKIs) has revolutionized the treatment of EGFR-mutated lung cancer. Despite the fact that EGFR-TKIs have yielded several significant benefits for lung cancer patients, the emergence of resistance to EGFR-TKIs has been a substantial impediment to improving treatment outcomes. Understanding the molecular mechanisms underlying resistance is crucial for the development of new treatments and biomarkers for disease progression. Together with the advancement in proteome and phosphoproteome analysis, a diverse set of key signaling pathways have been successfully identified that provide insight for the discovery of possible therapeutically targeted proteins. In this review, we highlight the proteome and phosphoproteomic analyses of non-small cell lung cancer (NSCLC) as well as the proteome analysis of biofluid specimens that associate with acquired resistance in response to different generations of EGFR-TKI. Furthermore, we present an overview of the targeted proteins and potential drugs that have been tested in clinical studies and discuss the challenges of implementing this discovery in future NSCLC treatment.

E2F1-activated LINC01224 drives esophageal squamous cell carcinoma cell malignant behaviors via targeting miR-6884-5p/DVL3 axis and activating Wnt/β-catenin signaling pathway

Current evidence has unveiled that long non-coding RNAs (lncRNAs) are pivotal regulators in the development of cancers. This study aimed to investigate the potential mechanisms of LINC01224 in esophageal squamous cell carcinoma (ESCC) cells. RT-qPCR analysis was done to test LINC01224 expression in ESCC cells. Functional assays were conducted to assess the influences of LINC01224 on ESCC cell functions. Mechanism assays were carried out to detect the regulatory mechanisms of LINC01224 at post-transcriptional and transcriptional levels. Briefly, LINC01224 expression was remarkably high in ESCC cells. LINC01224 silence restricted the proliferative, migratory, and invasive capabilities of ESCC cells. Moreover, LINC01224 could combine with miR-6884-5p by acting as a ceRNA. Further, DVL3 was proved to be targeted by miR-6884-5p. Importantly, LINC01224 could switch on Wnt/β-catenin signaling pathway by via enhancing DVL3 expression. Additionally, E2F1 could serve as a transcription factor to stimulate LINC01224 transcription. In summary, our study elucidated that E2F1-activated LINC01224 regulated miR-6884-5p/DVL3 to actuate the Wnt/β-catenin signaling pathway, which facilitates multiple phenotype of ESCC cells, including proliferation, migration, and invasion. Our findings might offer potential therapeutic targets for ESCC treatment.

Construction of a Two-Gene Immunogenomic-Related Prognostic Signature in Lung Squamous Cell Carcinoma

Lung cancer has the highest tumor incidence in China. Lung squamous cell carcinoma (LUSC) is the most common type, accounting for 40–51% of primary lung cancers. LUSC is slow in growth and late in metastasis. Immune-related genes (IRGs) and immune infiltrating cells play a vital role in the clinical outcomes of LUSC. It is important to systematically study its immune gene map to help the prognosis of cancer patients. In this study, we combined the prognostic landscape and expression status of IRGs downloaded from the TCGA and InnatedDB databases and systematically analyzed the prognostic information of LUSC patients to obtain IRGs. After systematically exploring the survival analysis, prognosis-related genes were found, and the PPI network revealed that a total of 11 genes were hub genes. A two-gene prognosis risk model was established by multivariate Cox analysis. Two IRGs were closely correlated with the prognosis of LUSC. Based on these two genes, a new independent prognostic risk model was established, and this model was further verified in the GEO database. Moreover, the risk score of the model was correlated with sex, survival status, and lymphatic metastasis in LUSC patients, and the predictive risk of the prognostic risk model was significantly positively correlated with five kinds of immune cells (CD4 T cells, CD8 T cells, neutrophils, macrophages, and dendritic cells). This study comprehensively analyzed immunogenomics and presented immune-related prognostic biomarkers for LUSC.

GLP2-GLP2R signal affects the viability and EGFR-TKIs sensitivity of PC9 and HCC827 cells

Background

The resistance to epidermal growth factor receptor (EGFR)- tyrosine kinase inhibitors (TKIs) therapy is currently the major clinical challenge in the treatment of lung cancer. This study aims to reveal the role of glucagon-like peptide (GLP) 2 and GLP-2 receptor (GLP2R) signaling on the EGFR-TKIs and cisplatin resistance of lung cancer cells.

Methods

The common differentially expressed genes in PC9 and HCC827 cells that were individually resistant to one of the three EGFR-TKIs (dacomitinib, osimertinib and afatinib) were screened. The data were from GSE168043 and GSE163913. The expression of GLP2R in drug-resistant cells was detected by western blot. The effect of GLP2R expression down- or up-regulation on resistance to dacomitinib, osimertinib, afatinib or cisplatin was measured by CCK-8 and flow cytometry assays. The long-acting analog of GLP-2, teduglutide, treated the parental cells.

Results

A total of 143 common differentially expressed genes were identified. Compared with the parent cells, the GLP2R expression in drug-resistant cell lines was significantly up-regulated. The exogenous expression of GLP2R in parental cells enhanced cell viability, while knockdown of GLP2R levels in drug-resistant cell lines inhibited cell viability. In addition, teduglutide treatment also enhanced the viability of lung cancer cells.

Conclusion

GLP2-GLP2R signal may change the sensitivity of cells to EGFR-TKIs and cisplatin. The development of GLP-2 or GLP2R inhibitors may be beneficial to the clinical treatment of lung cancer.

EGFR-Dependent Extracellular Matrix Protein Interactions Might Light a Candle in Cell Behavior of Non-Small Cell Lung Cancer

Lung cancer remains the leading cause of cancer-related death and is associated with a poor prognosis. Lung cancer is divided into 2 main types: the major in incidence is non-small cell lung cancer (NSCLC) and the minor is small cell lung cancer (SCLC). Although NSCLC progression depends on driver mutations, it is also affected by the extracellular matrix (ECM) interactions that activate their corresponding signaling molecules in concert with integrins and matrix metalloproteinases (MMPs). These signaling molecules include cytoplasmic kinases, small GTPases, adapter proteins, and receptor tyrosine kinases (RTKs), particularly the epidermal growth factor receptor (EGFR). In NSCLC, the interplay between ECM and EGFR regulates ECM stiffness, angiogenesis, survival, adhesion, migration, and metastasis. Furthermore, some tumor-promoting ECM components (e.g., glycoproteins and proteoglycans) enhance activation of EGFR and loss of PTEN. On the other hand, other tumor-suppressing glycoproteins and -proteoglycans can inhibit EGFR activation, suppressing cell invasion and migration. Therefore, deciphering the molecular mechanisms underlying EGFR and ECM interactions might provide a better understanding of disease pathobiology and aid in developing therapeutic strategies. This review critically discusses the crosstalk between EGFR and ECM affecting cell behavior of NSCLC, as well as the involvement of ECM components in developing resistance to EGFR inhibition.