LncRNA SPRY4-IT1 regulates breast cancer cell stemness through competitively binding miR-6882-3p with TCF7L2.

SPRY4-intronic transcript 1 has been found in several kinds of cancers, but the role of SPRY4-IT1 in breast cancer stem cells has not been studied. We investigated whether SPRY4-IT1 is involved in the promotion of breast cancer stem cells (BCSCs). We used qRT-PCR to detect the expression of SPRY4-IT1 in MCF-7 cells and MCF-7 cancer stem cells (MCF-7 CSCs). The effects of SPRY4-IT1 on the proliferation and renewal ability of breast cancer cells were investigated by in vitro and in vivo assays (ie in situ hybridization, colony formation assay, sphere formation assay, flow cytometry assay, western blotting, xenograft model and immunohistochemistry). The mechanism of SPPRY4-IT1 as a ceRNA was studied by a dual-luciferase reporter assay and bioinformatic analysis. In our study, SPRY4-IT1 was up-regulated in MCF-7 CSCs compared with MCF-7 cells, and high SPRY4-IT1 expression was related to reduced breast cancer patient survival. Furthermore, SPRY4-IT1 overexpression promoted breast cancer cell proliferation and stemness in vitro and in vivo. In addition, SPRY4-IT1 knockdown suppressed BCSC renewal ability and stemness maintenance in vivo and in vitro. The dual-luciferase reporter assays indicated that SPRY4-IT1 as a sponge for miR-6882-3p repressed transcription factor 7-like 2 (TCF7L2) expression. Taken together, these findings demonstrated that SPRY4-IT1 promotes proliferation and stemness of breast cancer cells as well as renewal ability and stemness maintenance of BCSCs by increasing the expression of TCF7L2 through targeting miR-6882-3p.

Advances in cancer treatment: a new therapeutic target, Annexin A2.

Annexin A2 (ANXA2) is a calcium regulated phospholipid-binding protein. It is expressed in some tumor cells, endothelial cells, macrophages, and mononuclear cells, affecting cell survival and mediating interactions between intercellular and extracellular microenvironment. Aberrant expression of ANXA2 can be used as a potential predictive factor, diagnostic biomarker and therapeutic target in cancer therapy. Investigators used various technologies to target ANXA2 in a preclinical model of human cancers and demonstrated encouraging results. In this review article, we discuss the diagnosis and prognosis latent capacity of ANXA2 in progressive cancers, focus on the exploration of restorative interventions targeting ANXA2 in cancer treatment. Further, we comment on a promising candidate therapy that is conceivable for clinical translation.

Overexpression of PTPRN Promotes Metastasis of Lung Adenocarcinoma and Suppresses NK Cell Cytotoxicity.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common diagnostic histologic subtype of non-small cell lung cancer, but the role of receptor-type tyrosine-protein phosphatase-like N (PTPRN) in LUAD has not been studied. METHODS: We conducted a bioinformatic analysis to identify the expression of PTPRN on LUAD data from the Cancer Genome Atlas (TCGA) and the relationship between PTPRN and overall survival of LUAD patients. The effects of PTPRN on the migration ability of LUAD cells and the underlying mechanisms were investigated by in vitro and in vivo assays (i.e., wound healing assay, transwell assay, western blotting, xenograft model, and immunohistochemistry). Gene-set enrichment analysis and computational resource were used to analyze the correlation between PTPRN and different tumor-infiltrating immune cells (TIICs). Lactate dehydrogenase assay and Enzyme-linked immunosorbent assay were conducted to examine natural killer (NK) cell cytotoxicity. RESULTS: In our study, we found that PTPRN was up-regulated in LUAD and related to metastasis of LUAD patients. Besides, PTPRN was correlated with poor prognosis in the TCGA-LUAD dataset. PTPRN overexpression promoted LUAD cell migration and the expression of EMT markers by influencing MEK/ERK and PI3K/AKT signaling. Moreover, PTPRN expression was significantly associated with TIICs, especially NK cells. A549 and H1299 cells overexpressed PTPRN inhibited NK cell cytotoxicity. CONCLUSION: Taken together, these findings demonstrated that PTPRN might be a potential and novel therapeutic target modulating antitumor immune response in treatment of LUAD.

A Immune-Related Signature Associated with TME Can Serve as a Potential Biomarker for Survival and Sorafenib Resistance in Liver Cancer.

OBJECTIVE: Although many curative treatments are being applied in the clinic, a significant number of patients with liver hepatocellular carcinoma (LIHC) suffer from drug resistance. The tumour microenvironment (TME) has been found to be closely associated with resistance, suggesting that identification of predictive biomarkers related to the TME for resistance in LIHC will be very rewarding. However, there has been no study dedicated to identifying a TME-related biomarker that has the potential to predict resistance in LIHC. METHODS: An integrated analysis was conducted based on data of patients with LIHC suffering from drug resistance from the TCGA database and four GEO datasets. Subsequently, we also validated the expression levels of the identified genes in paraffin-embedded LIHC samples by immunohistochemistry. RESULTS: In this study, we developed a robust and acute TME-related signature consisted of five immune-related genes (FABP6, CD4, PRF1, EREG and COLEC10) that could independently predict both the RFS and OS of LIHC patients. Moreover, the TME-related signature was significantly associated with the immune score, immune cytolytic activity (CYT), HLA, interferon (IFN) response and tumour-infiltrating lymphocytes (TILs), and it might influence tumour immunity mainly by affecting B cells, CD8+ T cells and dendritic cells. Furthermore, our analysis also indicated that the TME-related signature was correlated with the immunotherapy response and had an enormous potential to predict sorafenib resistance in LIHC. CONCLUSION: Our findings demonstrated a TME-related signature which can independently predict both the RFS and OS of LIHC patients, highlighting the predictive potential of the signature for immunotherapy response and sorafenib resistance, potentially enabling more precise and personalized sorafenib treatment in LIHC in the future.

m6A RNA Methylation Regulators Impact Prognosis and Tumor Microenvironment in Renal Papillary Cell Carcinoma.

Accumulating evidence has proven that N6-methyladenosine (m6A) RNA methylation plays an essential role in tumorigenesis. However, the significance of m6A RNA methylation modulators in the malignant progression of papillary renal cell carcinoma (PRCC) and their impact on prognosis has not been fully analyzed. The present research set out to explore the roles of 17 m6A RNA methylation regulators in tumor microenvironment (TME) of PRCC and identify the prognostic values of m6A RNA methylation regulators in patients afflicted by PRCC. We investigated the different expression patterns of the m6A RNA methylation regulators between PRCC tumor samples and normal tissues, and systematically explored the association of the expression patterns of these genes with TME cell-infiltrating characteristics. Additionally, we used LASSO regression to construct a risk signature based upon the m6A RNA methylation modulators. Two-gene prognostic risk model including IGF2BP3 and HNRNPC was constructed and could predict overall survival (OS) of PRCC patients from the Cancer Genome Atlas (TCGA) dataset. The prognostic signature-based risk score was identified as an independent prognostic indicator in Cox regression analysis. Moreover, we predicted the three most significant small molecule drugs that potentially inhibit PRCC. Taken together, our study revealed that m6A RNA methylation regulators might play a significant role in the initiation and progression of PRCC. The results might provide novel insight into exploration of m6A RNA modification in PRCC and provide essential guidance for therapeutic strategies.

Analysis of immune subtypes based on immunogenomic profiling identifies prognostic signature for cutaneous melanoma.

Skin cutaneous melanoma (SKCM) is the most invasive form of skin cancer with poor prognosis. Growing evidence has demonstrated that tumor immune microenvironment plays a key contributing role in tumorigenesis and predicting clinical outcomes. The aim of this study was to recognize immune classification and a reliable prognostic signature for patients with SKCM. By using single-sample gene set enrichment (ssGSEA) and hierarchical clustering analyses, we evaluated the immune infiltration landscape of SKCM afflicted patients from The Cancer Genome Atlas (TCGA) dataset and named two SKCM subtypes: Immunity-high and Immunity-low. The Immunity-high subgroup was characterized by up-regulation of immune response and favorable survival probability. Seven candidate small molecule drugs which potentially reverse SKCM immune status were identified by using Connectivity map (CMap) database. A prognostic five-immune-associated gene (IAG) signature consisting IFITM1, TNFSF13B, APOBEC3G, CCL8 and KLRK1 with high predictive value was established using the LASSO Cox regression analysis in training set, and validated in testing set as well as Gene Expression Omnibus (GEO) external validation cohort (P < 0.05). Lower tumor purity and active immune-related signaling pathways were obviously presented in low-risk group. Furthermore, a novel composite nomogram based upon the five-IAG signature and other clinical parameters was built with excellent calibration curves. Collectively, comprehensively characterizing the SKCM subtypes based upon immune microenvironment landscape and development of a survival-related IAG signature may provide a promising avenue for improving individualized treatment design and prognosis prediction for patients with SKCM.

Identification of the prognostic value of immune gene signature and infiltrating immune cells for esophageal cancer patients.

BACKGROUND: Esophageal cancer (ESCA) is one of the deadliest solid malignancies with worse survival rate worldwide. Here, we aimed to establish an immune-gene prognostic signature for predicting patients' survival and providing accurate targets for personalized therapy or immunotherapy. METHODS: Gene expression profile of patients with ESCA were download from The Cancer Genome Atlas (TCGA) database (dataset 1: n = 159) and immune-related genes from the ImmPORT database. Dataset 1 was subdivided into two groups (dataset 2: n = 80; dataset 3: n = 79). Kaplan-Meier and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signature on the three datasets. TIMER and CIBERSORT analysis were used to evaluate the correlation between the prognostic signature and infiltrating immune cells. RESULTS: We constructed a prognostic signature composed of six immune genes (HSPA6, S100A12, FABP3, DKK1, OSM and NR2F2). Kaplan-Meier curves validated the good predictive ability of the prognostic signature in datasets 1, 2 and 3 (P = 0.0034, P = 0.0081, and P = 0.0363, respectively). The area under the curve (AUC) of the ROC curves validated the predictive accuracy of the immune signature (AUCs = 0.757, 0.800, and 0.701, respectively). We also revealed the good prognostic value of the immune cells, including activated memory CD4 T cells, T follicular helper cells and monocytes. Potential target drugs, including Olopatadine and Amlexanox, were identified for clinical therapies to improve patients' survival outcomes. CONCLUSION: Our study indicated that the immune-related prognostic signature could serve as a novel biomarker for predicting patients' prognosis and providing new immunotherapy targets in ESCA.

Development of an IFNγ response-related signature for predicting the survival of cutaneous melanoma.

BACKGROUND: The tumor microenvironment (TME) plays a critical role in tumorigenesis, development, and therapeutic efficacy. Major advances have been achieved in the treatment of various cancers through immunotherapy. Nevertheless, only a minority of patients have positive responses to immunotherapy, which is partly due to conditions of the immunosuppressive microenvironment. Therefore, it is essential to identify prognostic biomarkers that reflect heterogeneous landscapes of the TME. METHODS AND MATERIALS: Based upon the ESTIMATE algorithm, we evaluated the infiltrating levels of immune and stromal components derived from patients afflicted by various types of cancer from The Cancer Genome Atlas database (TCGA). According to respective patient immune and stromal scores, we categorized cases into high- and low-scoring subgroups for each cancer type to explore associations between TME and patient prognosis. Gene Set Enrichment Analyses (GSEA) were conducted and genes enriched in IFNγ response signaling pathway were selected to facilitate establishment of a risk model for predicting overall survival (OS). Furthermore, we investigated the associations between the prognostic signature and tumor immune infiltration landscape by using CIBERSORT algorithm and TIMER database. RESULTS: Among the cancers assessed, the immune scores for skin cutaneous melanoma (SKCM) were the most significantly correlated with patients' survival time (P < .0001). We identified and validated a five-IFNγ response-related gene signature (UBE2L6, PARP14, IFIH1, IRF2, and GBP4), which was closely correlated with the prognosis for SKCM afflicted patients. Multivariate Cox regression analysis indicated that this risk model was an independent prognostic factor for SKCM. Tumor-infiltrating lymphocytes and specific immune checkpoint molecules had notably differential levels of expression in high- compared to low-risk samples. CONCLUSION: In this study, we established a novel five-IFNγ response-related gene signature that provided a better and increasingly comprehensive understanding of tumor immune landscape, and which demonstrated good performance in predicting outcomes for patients afflicted by SKCM.