L1 Cell Adhesion Molecule and Its Soluble Form sL1 Exhibit Poor Prognosis in Primary Breast Cancer Patients

Integrated Bioinformatics Analysis to Identify a Novel Four-Gene Prognostic Model of Breast Cancer and Reveal Its Association with Immune Infiltration

Liquid-liquid phase separation (LLPS) impact immune signaling in cancer and related genes have shown prognostic value in breast cancer (BRCA). However, the crosstalk between LLPS and immune infiltration in BRCA remain unclear. Therefore, we aimed to develop a novel prognostic model of BRCA related to LLPS and immune infiltration. BRCA-related, liquid-liquid phase separation (LLPS)-related genes, and differentially expressed genes (DEGs) were identified using public databases. Mutation and drug sensitivity analyses were performed using Gene Set Cancer Analysis database. Univariate cox regression and LASSO Cox regression were used for the construction and verification of prognostic model. Kaplan-Meier analysis was performed to evaluate overall survival (OS). Gene set variation analysis was conducted to analyze key pathways. CIBERSORT was used to assess immune infiltration and its correlation with prognostic genes was determined through Pearson analysis. A total of 6056 BRCA-associated genes, 3775 LLPS-associated genes, and 4049 DEGs, resulting in 314 overlapping genes. Twenty-eight prognostic genes were screened, and some of them were mutational and related to drug sensitivity Subsequently, a prognostic model comprising L1CAM, EVL, FABP7, and CST1 was built. Patients in high-risk group had shorter OS than those in low-risk group. The infiltrating levels of CD8+ T cells, macrophages M0, macrophages M2, dendritic cells activated, and mast cells resting was altered in high-risk group of breast cancer patients compared to low-risk group. L1CAM, EVL, FABP7, and CST1 were related to these infiltrating immune cells. L1CAM, EVL, FABP7, and CST1 were potential diagnostic biomarkers and therapeutic targets for BRCA.

Identification of potential molecular targets for the treatment of cluster 1 human pheochromocytoma and paraganglioma via comprehensive proteomic characterization

BACKGROUND

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors. New drug targets and proteins that would assist sensitive PPGL imagining could improve therapy and quality of life of patients with PPGL, namely those with recurrent or metastatic disease. Using a combined proteomic strategy, we looked for such clinically relevant targets among integral membrane proteins (IMPs) upregulated on the surface of tumor cells and non-membrane druggable enzymes in PPGL.

METHODS

We conducted a detailed proteomic analysis of 22 well-characterized human PPGL samples and normal chromaffin tissue from adrenal medulla. A standard quantitative proteomic analysis of tumor lysate, which provides information largely on non-membrane proteins, was accompanied by specific membrane proteome-aimed methods, namely glycopeptide enrichment using lectin-affinity, glycopeptide capture by hydrazide chemistry, and enrichment of membrane-embedded hydrophobic transmembrane segments.

RESULTS

The study identified 67 cell surface integral membrane proteins strongly upregulated in PPGL compared to control chromaffin tissue. We prioritized the proteins based on their already documented direct role in cancer cell growth or progression. Increased expression of the seven most promising drug targets (CD146, CD171, ANO1, CD39, ATP8A1, ACE and SLC7A1) were confirmed using specific antibodies. Our experimental strategy also provided expression data for soluble proteins. Among the druggable non-membrane enzymes upregulated in PPGL, we identified three potential drug targets (SHMT2, ARG2 and autotaxin) and verified their upregulated expression.

CONCLUSIONS

Application of a combined proteomic strategy recently presented as "Pitchfork" enabled quantitative analysis of both, membrane and non-membrane proteome, and resulted in identification of 10 potential drug targets in human PPGL. Seven membrane proteins localized on the cell surface and three non-membrane druggable enzymes proteins were identified and verified as significantly upregulated in PPGL. All the proteins have been previously shown to be upregulated in several human cancers, and play direct role in cancer progression. Marked upregulation of these proteins along with their localization and established direct roles in tumor progression make these molecules promising candidates as drug targets or proteins for sensitive PPGL imaging.

A gene expression signature in HER2+ breast cancer patients related to neoadjuvant chemotherapy resistance, overall survival, and disease-free survival

Breast cancer ranks first in terms of mortality and incidence rates worldwide among women. The HER2+ molecular subtype is one of the most aggressive subtypes; its treatment includes neoadjuvant chemotherapy and the use of a HER2 antibody. Some patients develop resistance despite positive results obtained using this therapeutic strategy. Objective. To identify prognostic markers for treatment and survival in HER2+ patients. Methods. Patients treated with neoadjuvant chemotherapy were assigned to sensitive and resistant groups based on their treatment response. Differentially expressed genes (DEGs) were identified using RNA-seq analysis. KEGG pathway, gene ontology, and interactome analyses were performed for all DEGs. An enrichment analysis Gene set enrichment analysis was performed. All DEGs were analyzed for overall (OS) and disease-free survival (DFS). Results. A total of 94 DEGs were related to treatment resistance. Survival analysis showed that 12 genes (ATF6B, DHRS13, DIRAS1, ERAL1, GRIN2B, L1CAM, IRX3, PRTFDC1, PBX2, S100B, SLC9A3R2, and TNXB) were good predictors of disease-free survival, and eight genes (GNG4, IL22RA2, MICA, S100B, SERPINF2, HLA-A, DIRAS1, and TNXB) were good predictors of overall survival (OS). Conclusion: We highlighted a molecular expression signature that can differentiate the treatment response, overall survival, and DFS of patients with HER2+ breast cancer.

Immunohistochemical analysis of L1 cell adhesion molecule and high endothelial venules in breast cancer brain metastasis

BACKGROUND

The vasculature is a crucial factor in tumor development. Vascular co-option achieved by the L1 cell adhesion molecule (L1CAM) and lymphocyte recruitment inside tumors by high endothelial venules (HEVs) are important prognostic factors in primary breast cancer. Their status in breast cancer brain metastasis is unknown.

AIM OF THE STUDY

To explore the status of L1CAMs and HEVs in this tumor compartment.

MATERIAL AND METHODS

Thirty resected breast cancer brain metastases were immunohistochemically studied for L1CAM and MECA-79, an HEV marker. Clinicopathological factors were recorded.

RESULTS

Age at brain metastasis diagnosis ranged from 37 to 80 years (median 55). The time to brain metastasis development after primary tumor diagnosis ranged from 12 to 187 months (median 57). Median overall survival after brain metastasis diagnosis was 29 months. None of the tumors expressed the factors studied.

CONCLUSION

L1CAM and high endothelial venules are not found in breast cancer brain metastasis.

The prognostic value of COL3A1/FBN1/COL5A2/SPARC-mir-29a-3p-H19 associated ceRNA network in Gastric Cancer through bioinformatic exploration

Increasing studies on malignant tumors have proposed a new competing endogenous RNA (ceRNA) regulatory mechanism that mRNA, miRNA and lncRNA interact with each other. However, the mRNA-miRNA-lncRNA associated ceRNA network in gastric cancer remains unknown. We used online bioinformatic softwares to predict the hub genes and their upstream miRNAs and lncRNAs in gastric cancer, and then performed survival analyses. After collecting gastric cancer tissue samples and performing PCR experiments, the correlations among predicted mRNA, miRNA and lncRNA were further verified. A total of 101 up-regulated significant differentially expressed genes (DEGs) and 219 down-regulated significant DEGs in gastric cancer were confirmed. Functional enrichment analyses of these significant DEGs indicated that they were potentially enriched in some pathways involved in tumor malignant biological processes or metabolism. Then, we identified 20 hub genes in the PPI networks. Combined with expression and survival analyses, 8 up-regulated genes and 1 down-regulated gene were identified as central genes and acted as important prognostic roles in gastric cancer. 17 miRNAs were confirmed that might potentially regulate the expressions of these central genes. But only 8 out of them indicated better outcome in gastric cancer. Further, 79 lncRNAs were predicted that might have the potence to combine with the 8 central miRNAs. The lncRNA H19 was eventually defined as a central lncRNA by survival analyses. Stimultaneously, we found that there were certain interactions among lncRNA, miRNA and mRNAs in 50 gastric cancer tissues by qRT-PCR. Moreover, the high expression of H19 is associated with advanced TNM stage, primary tumor and lymph nodes, indicating a poor prognosis. In summary, we uncovered the prognostic value of COL3A1/FBN1/COL5A2/SPARC-mir-29a-3p-H19 ceRNA network in gastric cancer.

Different Shades of L1CAM in the Pathophysiology of Cancer Stem Cells

L1 cell adhesion molecule (L1CAM) is aberrantly expressed in several tumor types where it is causally linked to malignancy and therapy resistance, acting also as a poor prognosis factor. Accordingly, several approaches have been developed to interfere with L1CAM function or to deliver cytotoxic agents to L1CAM-expressing tumors. Metastatic dissemination, tumor relapse and drug resistance can be fueled by a subpopulation of neoplastic cells endowed with peculiar biological properties that include self-renewal, efficient DNA repair, drug efflux machineries, quiescence, and immune evasion. These cells, known as cancer stem cells (CSC) or tumor-initiating cells, represent, therefore, an ideal target for tumor eradication. However, the molecular and functional traits of CSC have been unveiled only to a limited extent. In this context, it appears that L1CAM is expressed in the CSC compartment of certain tumors, where it plays a causal role in stemness itself and/or in biological processes intimately associated with CSC (e.g., epithelial-mesenchymal transition (EMT) and chemoresistance). This review summarizes the role of L1CAM in cancer focusing on its functional contribution to CSC pathophysiology. We also discuss the clinical usefulness of therapeutic strategies aimed at targeting L1CAM in the context of anti-CSC treatments.

L1CAM High Expression Associates with Poor Prognosis in Glioma but Does Not Correlate with C11orf95-RELA Fusion

The latest WHO guideline of CNS tumor defined a RELA fusion-positive ependymoma type with extremely poor prognosis, and the expression of L1CAM was correlated well with the presence of RELA fusion. However, the L1CAM protein expression in large sample gliomas other than ependymoma, its relationship with the RELA gene and its prognostic significance remained unknown. We examined the expression of L1CAM in 565 glioma cases (WHO grade I-IV). The L1CAM IHC-positive cases were selected to test RELA fusion with FISH break-apart probes. L1CAM was positive in 109 cases (19.29%) of all 565 glioma cases, with 18.27% in low-grade gliomas and 19.84% in high-grade gliomas, respectively. Unlike ependymoma, L1CAM protein expression was not correlated with the C11orf95-RELA fusion gene in other gliomas, but it had correction with the patient age (older than 45-year-old, p = 0.006), ATRX mutation (p = 0.003) and Ki67 (p = 0.007). High expression of L1CAM was an independent prognostic factor in our cohort. Further analysis demonstrated that L1CAM strong positive expression was significantly associated with poor prognosis in gliomas, both in our cohort (p < 0.001) and TCGA (p < 0.009) dataset. Although uncorrelated with C11orf95-RELA fusion, L1CAM was a significant poor prognostic marker in glioma patients. More aggressive treatment should be taken for these patients and L1CAM might be a promising therapeutic target in glioma.

L1 Cell Adhesion Molecule in Cancer, a Systematic Review on Domain-Specific Functions

L1 cell adhesion molecule (L1CAM) is a glycoprotein involved in cancer development and is associated with metastases and poor prognosis. Cellular processing of L1CAM results in expression of either full-length or cleaved forms of the protein. The different forms of L1CAM may localize at the plasma membrane as a transmembrane protein, or in the intra- or extracellular environment as cleaved or exosomal forms. Here, we systematically analyze available literature that directly relates to L1CAM domains and associated signaling pathways in cancer. Specifically, we chart its domain-specific functions in relation to cancer progression, and outline pre-clinical assays used to assess L1CAM. It is found that full-length L1CAM has both intracellular and extracellular targets, including interactions with integrins, and linkage with ezrin. Cellular processing leading to proteolytic cleavage and/or exosome formation results in extracellular soluble forms of L1CAM that may act through similar mechanisms as compared to full-length L1CAM, such as integrin-dependent signals, but also through distinct mechanisms. We provide an algorithm to guide a step-wise analysis on L1CAM in clinical samples, to promote interpretation of domain-specific expression. This systematic review infers that L1CAM has an important role in cancer progression that can be attributed to domain-specific forms. Most studies focus on the full-length plasma membrane L1CAM, yet knowledge on the domain-specific forms is a prerequisite for selective targeting treatment.

Identification of key genes and pathways in seminoma by bioinformatics analysis

Background: Seminoma accounts for the most part of cases of testicular germ cell tumor, which is the most common malignancy among males between ages 15 and 44 years. Understanding the molecular mechanism of tumorigenesis is important for better clinical diagnosis and treatment.

Purpose: We performed bioinformatics analysis to better understand seminoma at the genetic level and to explore potential candidate genes or molecules for diagnosis, treatment, and prognosis.

Methods: A gene expression profile (GSE8607), containing 40 seminoma samples and three healthy testes samples, was analyzed to identify differentially expressed genes (DEGs) associated with the occurrence of seminoma. Functional annotation was then performed using gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. Cytoscape with Search Tool for the Retrieval of Interacting Genes was used to construct a protein–protein interaction (PPI) network of the DEGs and select hub genes. Moreover, validation of expression level and Kaplan–Meier analysis for overall survival were conducted to those hub genes.

Results: A total of 1,636 DEGs were identified between seminoma and healthy samples, including 701 up-regulated in seminoma that were enriched in the regulation of immune responses, defense responses, receptor activity, and signal transducer activity; 935 were down-regulated in seminoma and were associated with reproductive processes, kinase activity, and carbohydrate derivative binding. Five hub genes were selected from the PPI network according to the degree of connectivity: IL6, VEGFA, IL10, CCR5, and CXCR4. Among them, high expression levels of CCR5 and CXCR4 were associated with poor prognosis for seminoma patients. Four modules selected from the PPI network revealed that seminoma was connected with the Janus kinase-signal transducers and activators of transcription signaling pathway, chemokine signaling pathway, endocytosis, and cytokine–cytokine receptor interaction.

Conclusion: These identified DEGs and hub genes facilitate our knowledge of the underlying molecular mechanism of seminoma and have the potential to be used as diagnostic biomarkers or therapeutic targets for seminoma.