BackgroundLong non-coding RNAs (lncRNAs) have emerged as critical regulators of tumor progression. However, the role and molecular mechanism of lncRNA XIST in gastric cancer is still unknown.MethodsReal-time PCR analysis was performed to measure the expression levels of lncRNA XIST in gastric cancer tissues and cell lines, the correlation between lncRNA XIST expression and clinicopathological characteristics and prognosis was analyzed in gastric cancer patients. The biological function of lncRNA XIST on gastric cancer cells were determined both in vitro and in vivo. The regulating relationship between lncRNA XIST and miR-101 was investigated in gastric cancer cells.ResultslncRNA XIST was significantly up-regulated in gastric cancer tissues and cell lines. Overexpression of lncRNA XIST was markedly associated with larger tumor size, lymph node invasion, distant metastasis and TNM stage in gastric cancer patients. Functionally, knockdown of lncRNA XIST exerted tumor-suppressive effects by inhibiting cell proliferation, migration and invasion in vitro and tumor growth and metastasis in vivo. Furthermore, an inverse relationship between lncRNA XIST and miR-101 was found. Polycomb group protein enhancer of zeste homolog 2 (EZH2), a direct target of miR-101, could mediated the biological effects that lncRNA XIST exerted.ConclusionslncRNA XIST is up-regulated and is associated with aggressive tumor phenotypes and patient survival in gastric cancer, and the newly identified lncRNA XIST/miR-101/EZH2 axis could be a potential biomarkers or therapeutic targets for gastric cancer patients.

Circulating tumor DNA (ctDNA) has emerged as a useful diagnostic and prognostic biomarker in many cancers. Here, we conducted a study to investigate the potential use of ctDNA methylation markers for the diagnosis and prognostication of colorectal cancer (CRC) and used a prospective cohort to validate their effectiveness in screening patients at high risk of CRC. We first identified CRC-specific methylation signatures by comparing CRC tissues to normal blood leukocytes. Then, we applied a machine learning algorithm to develop a predictive diagnostic and a prognostic model using cell-free DNA (cfDNA) samples from a cohort of 801 patients with CRC and 1021 normal controls. The obtained diagnostic prediction model discriminated patients with CRC from normal controls with high accuracy (area under curve = 0.96). The prognostic prediction model also effectively predicted the prognosis and survival of patients with CRC (P < 0.001). In addition, we generated a ctDNA-based molecular classification of CRC using an unsupervised clustering method and obtained two subgroups of patients with CRC with significantly different overall survival (P = 0.011 in validation cohort). Last, we found that a single ctDNA methylation marker, cg10673833, could yield high sensitivity (89.7%) and specificity (86.8%) for detection of CRC and precancerous lesions in a high-risk population of 1493 participants in a prospective cohort study. Together, our findings showed the value of ctDNA methylation markers in the diagnosis, surveillance, and prognosis of CRC.

Side population (SP) cells within tumors are a small fraction of cancer cells with stem-like properties that can be identified by flow cytometry analysis based on their high ability to export certain compounds such as Hoechst 33342 and chemotherapeutic agents. The existence of stem-like SP cells in tumors is considered as a key factor contributing to drug resistance, and presents a major challenge in cancer treatment. Although it has been recognized for some time that tumor tissue niches may significantly affect cancer stem cells (CSCs), the role of key nutrients such as glucose in the microenvironment in affecting stem-like cancer cells and their metabolism largely remains elusive. Here we report that SP cells isolated from human cancer cells exhibit higher glycolytic activity compared to non-SP cells. Glucose in the culture environment exerts a profound effect on SP cells as evidenced by its ability to induce a significant increase in the percentage of SP cells in the overall cancer cell population, and glucose starvation causes a rapid depletion of SP cells. Mechanistically, glucose upregulates the SP fraction through ATP-mediated suppression of AMPK and activation of the Akt pathway, leading to elevated expression of the ATP-dependent efflux pump ABCG2. Importantly, inhibition of glycolysis by 3-BrOP significantly reduces SP cells in vitro and impairs their ability to form tumors in vivo. Our data suggest that glucose is an essential regulator of SP cells mediated by the Akt pathway, and targeting glycolysis may eliminate the drug-resistant SP cells with potentially significant benefits in cancer treatment. Accumulating evidence suggests that tumors of various tissue origins, including the brain, breast, and lung, contain a small subpopulation of special cells with stem-like properties, often referred to as cancer stem cells (CSCs) or tumor-initiating cells. [1][2][3][4][5][6][7] In addition to the ability of CSCs to self-renew and initiate tumor formation, one important biochemical feature of CSCs is their ability to export certain toxic compounds and resistance to many chemotherapeutic agents due in part to their high expression of ATP-dependent efflux pump ABCG2, their increased DNA repair capacity, and activation of survival pathways. [8][9][10] The increase in expression of ABCG2 also confers CSCs the ability to effectively export the DNA-binding dye Hoechst 33342 out of the cells, leading to a low retention of the fluorescent signal in these cells, which appear at the low-left corner in flow cytometry analysis and thus are known as 'side population' or SP cells. 2,11 As SP cells can be readily identified by flow cytometry in a quantitative manner, the measurement of SP cells has been widely used as a quantitative assay for the relative number (%) of stem-like cancer cells in the bulk of the overall cancer cell population. Importantly, as this assay is functionally based on the ability of SP cells to export Hoechst 33342 and certain toxic compounds, it is also a quantitative analysis of the subpopulatio...

Purpose: Golgi phosphoprotein 3 (GOLPH3) has been reported to be involved in various biologic processes. The clinical significance and biologic role of GOLPH3 in breast cancer, however, remains unknown.Experimental Design: Expression of GOLPH3 in normal breast cells, breast cancer cells, and 6-paired breast cancer and adjacent noncancerous tissues were quantified using real-time PCR and Western blotting. GOLPH3 protein expression was analyzed in 258 archived, paraffin-embedded breast cancer samples using immunohistochemistry. The role of GOLPH3 in breast cancer cell proliferation and tumorigenicity was explored in vitro and in vivo. Western blotting and luciferase reporter analyses were used to investigate the effect of GOLPH3 overexpression and silencing on the expression of cell-cycle regulators and FOXO1 transcriptional activity.Results: GOLPH3 was significantly upregulated in breast cancer cells and tissues compared with normal cells and tissues. Immunohistochemical analysis revealed high expression of GOLPH3 in 133 of 258 (51.6%) breast cancer specimens. Statistical analysis showed a significant correlation of GOLPH3 expression with advanced clinical stage and poorer survival. Overexpression and ablation of GOLPH3 promoted and inhibited, respectively, the proliferation and tumorigenicity of breast cancer cells in vitro and in vivo. GOLPH3 overexpression enhanced AKT activity and decreased FOXO1 transcriptional activity, downregulated cyclin-dependent kinase (CDK) inhibitor p21Cip1 , p27 Kip1, and p57 Kip2 , and upregulated the CDK regulator cyclin D1. Conclusion: Our results suggest that high GOLPH3 expression is associated with poor overall survival in patients with breast cancer and that GOLPH3 overexpression increases the proliferation and tumorigenicity of human breast cancer cells. Clin Cancer Res; 18(15); 4059-69. Ó2012 AACR.

Background Although immune checkpoint inhibitor (ICI) is regarded as a breakthrough in cancer therapy, only a limited fraction of patients benefit from it. Cancer stemness can be the potential culprit in ICI resistance, but direct clinical evidence is lacking. Methods Publicly available scRNA-Seq datasets derived from ICI-treated patients were collected and analyzed to elucidate the association between cancer stemness and ICI response. A novel stemness signature (Stem.Sig) was developed and validated using large-scale pan-cancer data, including 34 scRNA-Seq datasets, The Cancer Genome Atlas (TCGA) pan-cancer cohort, and 10 ICI transcriptomic cohorts. The therapeutic value of Stem.Sig genes was further explored using 17 CRISPR datasets that screened potential immunotherapy targets. Results Cancer stemness, as evaluated by CytoTRACE, was found to be significantly associated with ICI resistance in melanoma and basal cell carcinoma (both P < 0.001). Significantly negative association was found between Stem.Sig and anti-tumor immunity, while positive correlations were detected between Stem.Sig and intra-tumoral heterogenicity (ITH) / total mutational burden (TMB). Based on this signature, machine learning model predicted ICI response with an AUC of 0.71 in both validation and testing set. Remarkably, compared with previous well-established signatures, Stem.Sig achieved better predictive performance across multiple cancers. Moreover, we generated a gene list ranked by the average effect of each gene to enhance tumor immune response after genetic knockout across different CRISPR datasets. Then we matched Stem.Sig to this gene list and found Stem.Sig significantly enriched 3% top-ranked genes from the list (P = 0.03), including EMC3, BECN1, VPS35, PCBP2, VPS29, PSMF1, GCLC, KXD1, SPRR1B, PTMA, YBX1, CYP27B1, NACA, PPP1CA, TCEB2, PIGC, NR0B2, PEX13, SERF2, and ZBTB43, which were potential therapeutic targets. Conclusions We revealed a robust link between cancer stemness and immunotherapy resistance and developed a promising signature, Stem.Sig, which showed increased performance in comparison to other signatures regarding ICI response prediction. This signature could serve as a competitive tool for patient selection of immunotherapy. Meanwhile, our study potentially paves the way for overcoming immune resistance by targeting stemness-associated genes.