ABSTRACT
Triple negative breast cancer (TNBC) has negative expression of ER, PR and HER-2. TNBC shows high histological grade and positive rate of lymph node metastasis, easy recurrence and distant metastasis. Molecular typing based on metabolic genes can reflect deeper characteristics of breast cancer and provide support for prognostic evaluation and individualized treatment. Metabolic subtypes of TNBC samples based on metabolic genes were determined by consensus clustering. CIBERSORT method was applied to evaluate the score distribution and differential expression of 22 immune cells in the TNBC samples. Linear discriminant analysis (LDA) established a subtype classification feature index. Kaplan-Meier (KM) and receiver operating characteristic (ROC) curves were generated to validate the performance of prognostic metabolic subtypes in different datasets. Finally, we used weighted correlation network analysis (WGCNA) to cluster the TCGA expression profile dataset and screen the co-expression modules of metabolic genes. Consensus clustering of the TCGA cohort/dataset obtained three metabolic subtypes (MC1, MC2, and MC3). The ROC analysis showed a high prognostic performance of the three clusters in different datasets. Specifically, MC1 had the optimal prognosis, MC3 had a poor prognosis, and the three metabolic subtypes had different prognosis. Consistently, the immune characteristic index established based on metabolic subtypes demonstrated that compared with the other two subtypes, MC1 had a higher IFNγ score, T cell lytic activity and lower angiogenesis score, T cell dysfunction and rejection score. TIDE analysis showed that MC1 patients were more likely to benefit from immunotherapy. MC1 patients were more sensitive to immune checkpoint inhibitors and traditional chemotherapy drugs Cisplatin, Paclitaxel, Embelin, and Sorafenib. Multiclass AUC based on RNASeq and GSE datasets were 0.85 and 0.85, respectively. Finally, based on co-expression network analysis, we screened 7 potential gene markers related to metabolic characteristic index, of which CLCA2, REEP6, SPDEF, and CRAT can be used to indicate breast cancer prognosis. Molecular classification related to TNBC metabolism was of great significance for comprehensive understanding of the molecular pathological characteristics of TNBC, contributing to the exploration of reliable markers for early diagnosis of TNBC and predicting metastasis and recurrence, improvement of the TNBC staging system, guiding individualized treatment.
Subject(s)
Triple Negative Breast Neoplasms , Chloride Channels , Eye Proteins , Humans , Immunotherapy , Lymphatic Metastasis , Membrane Proteins , Neoplasm Staging , Prognosis , Triple Negative Breast Neoplasms/genetics , Triple Negative Breast Neoplasms/pathology , Triple Negative Breast Neoplasms/therapyABSTRACT
Gastric cancer directly affects the quality of human life worldwide. Some members, which belong to carcinoembryonic antigen-related cell adhesion molecule (CEACAM) subfamily, are deregulated in tumors. Of the subfamily, CEACAM19, a new member was the research object. Our study sought to explore the potential role of CEACAM19 in gastric cancer. According to the immunohistochemistry (IHC), RT-PCR and Western blot, CEACAM19 was over-expressed in gastric cancer tissues and cells. Moreover, the Western blot analysis showed that the expression of MMP2 and MMP9 was inhibited in CEACAM19 knockdown gastric cancer cells. Meanwhile, in SGC-7901 and MGC-803â¯cells, the knockdown of CEACAM19 reduced proliferation, migration and invasion. Additionally, the Western blot assay revealed that the phosphorylation levels of Akt and p65 were declined by the knockdown of CEACAM19. Furthermore, the influence of CEACAM19 knockdown was confirmed by the studies in vivo. Collectively, our results revealed that the CEACAM19 knockdown prevented the gastric cancer progression likely related to inactivating the PI3K/Akt and NF-κB signaling pathways. Our findings provided insights into a promising biomarker of gastric cancer and the potential molecule clues for the prevention of gastric cancer.
Subject(s)
Antigens, Neoplasm/metabolism , Biomarkers, Tumor/metabolism , Cell Adhesion Molecules/metabolism , Gene Expression Regulation, Neoplastic , NF-kappa B/metabolism , Phosphatidylinositol 3-Kinases/metabolism , Proto-Oncogene Proteins c-akt/metabolism , Stomach Neoplasms/pathology , Adult , Aged , Aged, 80 and over , Animals , Antigens, Neoplasm/genetics , Apoptosis , Biomarkers, Tumor/genetics , Cell Adhesion Molecules/antagonists & inhibitors , Cell Adhesion Molecules/genetics , Cell Movement , Cell Proliferation , Female , Follow-Up Studies , Humans , Male , Mice , Mice, Inbred BALB C , Mice, Nude , Middle Aged , NF-kappa B/genetics , Phosphatidylinositol 3-Kinases/genetics , Prognosis , Proto-Oncogene Proteins c-akt/genetics , RNA, Small Interfering/genetics , Signal Transduction , Stomach Neoplasms/genetics , Stomach Neoplasms/metabolism , Tumor Cells, Cultured , Xenograft Model Antitumor AssaysABSTRACT
Type 2 diabetes (T2D) is a complex disorder caused by the combined effects of genetic inheritance and environmental factors. The abnormal secretion of albumin via urine is the characteristic feature of a diabetic nephropathy (DN) patient. Moreover, the detection of this observable characteristic feature of DN is quite late. As a result the time, at which DN is observable, large extent of kidney damage has already occurred. Thus, this late observation significantly decreases the chances of efficient management of DN and associated outcomes. The current biomarker used to detect DN is microalbuminuria, the presence of albumin in the urine. However, the current biomarkers often lead to false negative results. The high mobility group box (HMGB)1 is an upcoming molecule being explored for its application in the management of DN. The present review enlightens the current status of HMGB1 in DN.
