Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach

How Different Are the Molecular Mechanisms of Nodal and Distant Metastasis in Luminal A Breast Cancer?

Lymph node status is one of the best prognostic factors in breast cancer, however, its association with distant metastasis is not straightforward. Here we compare molecular mechanisms of nodal and distant metastasis in molecular subtypes of breast cancer, with major focus on luminal A patients. We analyze a new cohort of 706 patients (MMCI_706) as well as an independent cohort of 836 primary tumors with full gene expression information (SUPERTAM_HGU133A). We evaluate the risk of distant metastasis, analyze targetable molecular mechanisms in Gene Set Enrichment Analysis and identify relevant inhibitors. Lymph node positivity is generally associated with NF-κB and Src pathways and is related to high risk (OR: 5.062 and 2.401 in MMCI_706 and SUPERTAM_HGU133A, respectively, p < 0.05) of distant metastasis in luminal A patients. However, a part (≤15%) of lymph node negative tumors at the diagnosis develop the distant metastasis which is related to cell proliferation control and thrombolysis. Distant metastasis of lymph node positive patients is mostly associated with immune response. These pro-metastatic mechanisms further vary in other molecular subtypes. Our data indicate that the management of breast cancer and prevention of distant metastasis requires stratified approach based on targeted strategies.

Cancer stem cell property and gene signature in bone-metastatic Breast Cancer cells

The majority of the deaths from breast cancer is due to metastasis. Bone is the most common organ to which breast cancer cells metastasize. The mechanism regulating the bone-metastatic preference remains unclear; there is a lack of a gene signature to distinguish bone-metastatic breast cancer cells. Herein, florescence-labeled MDA-MB-231 cells were transplanted into the fat pads of of the mammary gland in nude mice to generate breast tumors. Tumor cells invaded into the circulation were tracked by in vivo flow cytometry system. Metastatic tumor cells in the bone were isolated using fluorescent-activated cell sorting technique, followed by assays of cell colony formation, migration and invasion, mammosphere formation in vitro, mammary gland tumorigenesis in vivo, and Next-Generation Sequencing analysis as well. Through tumor regeneration and cell sorting, two bone-metastatic cell sublines were derived from MDA-MB-231 cells; which showed higher abilities to proliferate, migrate, invade and epithelial-to-mesenchymal transit in vitro, and stronger ability to regenerate tumors and metastasize to the bone in vivo. Both cell sublines exhibited cancer stem cell-like characteristics including higher expression levels of stem cell markers and stronger ability for mommaspheres formation. Furthermore, a Normal Distribution-like pattern of the bone-metastatic cells invading into circulation was firstly identified. Deep-sequencing analysis indicated upregulation of multiple signaling pathways in regulating EMT, cell membrane budding and morphologic change, lipid metabolism, and protein translation, which are required to provide adequate metabolic enzymes, structural proteins, and energy for the cells undergoing metastasis. In conclusion, we established two bone-metastatic breast cancer cell sublines, carrying higher degree of stemness and malignancy. The gene signature distinguishing the bone-metastatic breast cancer cells holds therapeutic potentials in prevention of breast cancer metastasis to the bone.

Key genes associated with pancreatic cancer and their association with outcomes: A bioinformatics analysis

Pancreatic cancer is a highly malignant neoplastic disease of the digestive system. In the present study, the dataset GSE62165 was downloaded from the Gene Expression Omnibus (GEO) database. GSE62165 contained the data of 118 pancreatic ductal adenocarcinoma samples (38 early‑stage tumors, 62 lymph node metastases and 18 advanced tumors) and 13 control samples. Differences in the expression levels of genes between normal tissues and early‑stage tumors were investigated. A total of 240 differentially expressed genes (DEGs) were identified using R software 3.5 (137 upregulated genes and 103 downregulated genes). Then, the differentially expressed genes were subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. The following 18 core genes were identified using Cytoscape, based on the protein‑interaction network of DEGs determined using the online tool STRING: EGF, ALB, COL17A1, FN1, TIMP1, PLAU, PLA2G1B, IGFBP3, PLAUR, VCAN, COL1A1, PNLIP, CTRL, PRSS3, COMP, CPB1, ITGA2 and CEL. The pathways of the core genes were primarily associated with pancreatic secretion, protein digestion and absorption, and focal adhesion. Finally, survival analyses of core genes in pancreatic cancer were conducted using the UALCAN online database. It was revealed that PLAU and COL17A1 were significantly associated with poor prognosis (P<0.05). The expression levels of genes in primary pancreatic cancer tissues were then compared; only one gene, COL17A1, was identified to be significantly differentially expressed. Finally, another dataset from GEO, GSE28735, was analyzed to verify the upregulated expression of COL17A1. Taken together, the results of the present study have indicated that the expression of COL17A1 gene may be associated with the occurrence and development of pancreatic cancer.

In Situ Drug Delivery to Breast Cancer-Associated Extracellular Matrix

The extracellular matrix (ECM) contributes to tumor progression through changes induced by tumor and stromal cell signals that promote increased ECM density and stiffness. The increase in ECM stiffness is known to promote tumor cell invasion into surrounding tissues and metastasis. In addition, this scar-like ECM creates a protective barrier around the tumor that reduces the effectiveness of innate and synthetic antitumor agents. Herein, clinically approved breast cancer therapies as well as novel experimental approaches that target the ECM are discussed, including in situ hydrogel drug delivery systems, an emerging technology the delivers toxic chemotherapeutics, gene-silencing microRNAs, and tumor suppressing immune cells directly inside the tumor. Intratumor delivery of therapeutic agents has the potential to drastically reduce systemic side effects experienced by the patient and increase the efficacy of these agents. This review also describes the opposing effects of ECM degradation on tumor progression, where some studies report improved drug delivery and delayed cancer progression and others report enhanced metastasis and decreased patient survival. Given the recent increase in ECM-targeting drugs entering preclinical and clinical trials, understanding and addressing the factors that impact the effect of the ECM on tumor progression is imperative for the sake of patient safety and survival outcome.

Identification of core genes and outcome in gastric cancer using bioinformatics analysis

Gastric cancer (GC) is a common malignant neoplasm of gastrointestinal tract. We chose gene expression profile of GSE54129 from GEO database aiming to find key genes during the occurrence and development of GC. 132 samples, including 111 cancer and 21 normal gastric mucosa epitheliums, were included in this analysis. Differentially expressed genes (DEGs) between GC patients and health people were picked out using GEO2R tool, then we performed gene ontology (GO) analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis using The Database for Annotation, Visualization and Integrated Discovery (DAVID). Moreover, Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING) and Molecular Complex Detection (MCODE) plug-in was utilized to visualize protein-protein interaction (PPI) of these DEGs. There were 971 DEGs, including 468 up-regulated genes enriched in focal adhesion, ECM-receptor interaction and PI3K-Akt signaling pathway, while 503 down-regulated genes enriched in metabolism of xenbiotics and drug by cytochrome P450, chemical carcinogenesis, retinol metabolism and gastric acid secretion. Three important modules were detected from PPI network using MCODE software. Besides, Fifteen hub genes with high degree of connectivity were selected, including BGN, MMP2, COL1A1, and FN1. Moreover, the Kaplan–Meier analysis for overall survival and correlation analysis were applied among those genes. In conclusion, this bioinformatics analysis demonstrated that DEGs and hub genes, such as BGN, might promote the development of gastric cancer, especially in tumor metastasis. In addition, it could be used as a new biomarker for diagnosis and to guide the combination medicine of gastric cancer.