Identification of a universal 6-lncRNA prognostic signature for three pathologic subtypes of renal cell carcinoma.

Renal cell carcinoma (RCC) is the most common adult renal epithelial cancer susceptible to metastasis and patients with irresectable RCC always have a poor prognosis. Long noncoding RNAs (lncRNAs) have recently been documented as having critical roles in the etiology of RCC. Nevertheless, the prognostic significance of lncRNA-based signature for outcome prediction in patients with RCC has not been well investigated. Therefore, it is essential to identify a lncRNA-based signature for predicting RCC prognosis. In the current study, we comprehensively analyzed the RNA sequencing data of the three main pathological subtypes of RCC (kidney renal clear cell carcinoma [KIRC], kidney renal papillary cell carcinoma [KIRP], and kidney chromophobe carcinoma [KICH]) from The Cancer Genome Atlas (TCGA) database, and identified a 6-lncRNA prognostic signature with the help of a step-wise multivariate Cox regression model. The 6-lncRNA signature stratified the patients into low- and high-risk groups with significantly different prognosis. Multivariate Cox regression analysis showed that predictive value of the 6-lncRNA signature was independent of other clinical or pathological factors in the entire cohort and in each cohort of RCC subtypes. In addition, the three independent prognostic clinical factors (including age, pathologic stage III, and stage IV) was also stratified into low- and high-risk groups basis on the risk score, and the stratification analyses demonstrated that the high-risk score was a poor prognostic factor. In conclusion, these findings indicate that the 6-lncRNA signature is a novel prognostic biomarker for all three subtypes of RCC, and can increase the accuracy of predicting overall survival.

Identification of a 6-gene signature predicting prognosis for colorectal cancer.

BACKGROUND: An accurate and robust gene signature is of the utmost importance in assisting oncologists to make a more accurate evaluation in clinical practice. In our study, we extracted key mRNAs significantly related to colorectal cancer (CRC) prognosis and we constructed an expression-based gene signature to predict CRC patients' survival. METHODS: mRNA expression profiles and clinicopathological data of colon adenocarcinoma (COAD) cases and rectum adenocarcinoma (READ) were collected from The Cancer Genome Atlas database to investigate gene expression alteration associated to the prognosis of CRC. Differentially expressed mRNAs (DEMs) were detected between COAD/READ and normal tissue samples. Relying on a univariate and multivariate Cox regression analyses, a mRNA panel signature was established and used for predicting the overall survival (OS) in CRC patients. Receiver operating characteristic curve was used to evaluate the prognosis performance of our model through calculating the AUC values corresponding to the 3-year and 5-year survival. To assess the performance of gene signature in the given cancer subgroups (CRC entire cohort, COAD cohort, and READ cohort), a stratified analysis was carried out according to clinical factors. RESULTS: A total of 5341 and 5594 DEMs were collected from COAD vs. normal tissue samples, and READ vs. normal samples respectively. A univariate regression analysis for the common DEMs between COAD and READ cohorts resulted in 14 common mRNAs related to OS. The multivariate Cox regression analysis revealed that 6 of these mRNAs (EPHA6, TIMP1, IRX6, ART5, HIST3H2BB, and FOXD1) had significant prognostic value allowing the discrimination between high- and low-risk patients, implying poor and good outcomes, respectively. The stratified analysis identified 6-gene signature as an independent prognostic signature in predicting CRC patients' survival. CONCLUSIONS: The 6-gene signature could act as an independent biomarker for survival prediction of CRC patients.

Suppression of angiogenesis and tumor growth by recombinant T4 phages displaying extracellular domain of vascular endothelial growth factor receptor 2.

Tumor growth, invasion and metastasis are dependent on angiogenesis. The Vascular endothelial growth factor (VEGF)/VEGF receptor 2 (VEGFR2) signaling pathway plays a pivotal role in tumor angiogenesis and therefore represents a reasonable target for anti-angiogenesis/anti-tumor therapy. In the present study, we generated T4 recombinant phages expressing the extracellular domain of VEGFR2 (T4-VEGFR2) and investigated their anti-angiogenic activity. The T4-VEGFR2 phages were able to bind to VEGF specifically and inhibit VEGF-mediated phosphorylation of VEGFR2 and its downstream kinases such as extracellular signal-regulated kinase (ERK) and p38 mitogen activated protein kinase (MAPK). The in vitro experiments showed that the T4-VEGFR2 phages could inhibit VEGF-stimulated cell proliferation and migration of endothelial cells. Finally, administration of T4-VEGFR2 phages was able to suppress tumor growth and decrease microvascular density in murine models of Lewis lung carcinoma and colon carcinoma, and prolong the survival of tumor bearing mice. In conclusion, this study reveals that the recombinant T4-VEGFR2 phages generated using T4-based phage display system can inhibit VEGF-mediated tumor angiogenesis and the T4 phage display technology can therefore be used for the development of novel anti-cancer strategies.

Identification of key genes for predicting colorectal cancer prognosis by integrated bioinformatics analysis.

Colorectal cancer (CRC) is a life-threatening disease with a poor prognosis. Therefore, it is crucial to identify molecular prognostic biomarkers for CRC. The present study aimed to identify potential key genes that could be used to predict the prognosis of patients with CRC. Three CRC microarray datasets (GSE20916, GSE73360 and GSE44861) were downloaded from the Gene Expression Omnibus (GEO) database, and one dataset was obtained from The Cancer Genome Atlas (TCGA) database. The three GEO datasets were analyzed to detect differentially expressed genes (DEGs) using the BRB-ArrayTools software. Functional and pathway enrichment analyses of these DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery tool. A protein-protein interaction (PPI) network of DEGs was constructed, hub genes were extracted, and modules of the PPI network were analyzed. To investigate the prognostic values of the hub genes in CRC, data from the CRC datasets of TCGA were used to perform the survival analyses based on the sample splitting method and Cox regression model. Correlation among the hub genes was evaluated using Spearman's correlation analysis. In the three GEO datasets, a total of 105 common DEGs were identified, including 51 down- and 54 up-regulated genes in CRC compared with normal colorectal tissues. A PPI network consisting of 100 DEGs and 551 edges was constructed, and 44 nodes were identified as hub genes. Among these 44 genes, the four hub genes TIMP metallopeptidase inhibitor 1 (TIMP1), solute carrier family 4 member 4 (SLC4A4), aldo-keto reductase family 1 member B10 (AKR1B10) and ATP binding cassette subfamily E member 1 (ABCE1) were associated with overall survival (OS) in patients with CRC. Three significant modules were extracted from the PPI network. The hub gene TIMP1 was present in Module 1, ABCE1 was involved in Module 2 and SLC4A4 was identified in Module 3. Univariate analysis revealed that TIMP1, SLC4A4, AKR1B10 and ABCE1 were associated with the OS of patients with CRC. Multivariate analysis demonstrated that SLC4A4 may be an independent prognostic factor associated with OS. Furthermore, the results from correlation analysis revealed that there was no correlation between TIMP1, SLC4A4 and ABCE1, whereas AKR1B10 was positively correlated with SLC4A4. In conclusion, the four key genes TIMP1, SLC4A4, AKR1B10 and ABCE1 associated with the OS of patients with CRC were identified by integrated bioinformatics analysis. These key genes may be used as prognostic biomarkers to predict the survival of patients with CRC, and may therefore represent novel therapeutic targets for CRC.

Silencing of XRCC4 increases radiosensitivity of triple-negative breast cancer cells.

BACKGROUND: Radiotherapy is an important locoregional treatment, and its effect on triple-negative breast cancer (TNBC) needs to be enhanced. The aim of the present study was to investigate the potential effects of XRCC4 on radiosensitivity of TNBC. METHODS: The RNAi technique was implemented to establish the TNBC stable cell line with XRCC4 knockdown. MTT assay was used to detect the effect of XRCC4 knockdown on cell proliferation. Western blot and immunohistochemistry assays were employed to identify protein expression. Colony assay was performed to detect the effect of XRCC4 knockdown on the colony formation ability of TNBC cells with radiation treatment. Comet assay was conducted to evaluate the influence of XRCC4 silencing on DNA repair activity in ionizing radiation. In addition, we performed a survival analysis based on data in TCGA database. RESULTS: XRCC4 knockdown by lentivirus-mediated shRNA had no significant effect on proliferation of TNBC cells. Knockdown of XRCC4 could substantially increase the sensitivity of TNBC cells to ionizing radiation. The DNA damage level was detected to be increased in the XRCC4 knockdown group, indicating there was a significant repair delay in the XRCC4-deleted cells. Clinical sample analysis exhibited that there were various XRCC4 expression in different patients with TNBC. Moreover, survival analysis showed that high expression of XRCC4 was significantly associated with poor progression-free survival after radiotherapy in TNBC patients. Conclusion: Our findings suggest that XRCC4 knockdown sensitizes TNBC cells to ionizing radiation, and could be considered as a novel predictor of radiosensitivity and a promising target for TNBC.

Modification of cytokine-induced killer cells with folate receptor alpha (FRα)-specific chimeric antigen receptors enhances their antitumor immunity toward FRα-positive ovarian cancers.

Folate receptor alpha (FRα) is aberrantly expressed in ovarian cancers but largely absent in normal tissues, and therefore represents an attractive target for immunotherapy. In recent years, modification of T cells with chimeric antigen receptor (CAR) targeting FRα has been reported to improve antitumor immunity of T cells. However, there are limited data regarding CAR-modified cytokine-induced killer (CAR-CIK) cells. In the present study, we modified CIK cells with FRα-specific CARs and investigated their antitumor immunity against ovarian cancers. We found that both non-transduced and mock CAR-transduced CIK cells showed only low antitumor activity against either FRα-positive (FRα+) or FRα-negative (FRα-) targets. However, all three generations of CAR-modified CIK cells showed enhanced antitumor activity against FRα+ targets, but not FRα- targets. First-generation ζ-CAR-CIK cells increased production of IFN-γ, enhanced short-term cytotoxicity against FRα+ ovarian cancer cells, and showed modest and short-term suppression of established tumors; while second-generation 28ζ- and third-generation 28BBζ-CAR-CIK cells showed significant proliferation, enhanced secretion of IL-2, eliminated the FRα+ ovarian cancer cells in long-term co-culture, and showed dramatic and long-term inhibition of tumor growth and prolonged survival of xenograft-bearing mice. It is noteworthy that the 28BBζ-CAR was more potent in the modification of CIK cells than 28ζ-CAR both in vitro and in vivo. Moreover, CAR-CIK cells showed more efficient anticancer activity compared with CAR-T cells in vitro, but less efficient than CAR-T cells in vivo. According to these results, we conclude that modification of CIK cells with FRα-specific CARs enhances their antitumor immunity to FRα+ ovarian cancers. The third-generation 28BB-ζ CAR containing 4-1BB co-stimulation was more efficient in modification of CIK cells than either first-generation ζ-CAR or second-generation CD28-ζ-CAR.