Overexpression of GPNMB predicts an unfavorable outcome of epithelial ovarian cancer

Quantitative Proteomics and Phosphoproteomics Analysis of Patient-Derived Ovarian Cancer Stem Cells

High-grade serous ovarian carcinoma (HGSOC) is the deadliest gynecologic cancer. Key to the progression and ultimate lethality of this subtype is the intra-tumoral heterogeneity, which is defined as the coexistence of different cell types and populations within a single tumor. Among those, ovarian cancer stem cells (OCSCs) are a distinct subpopulation of tumor cells endowed with stem-like properties, which can survive current standard therapies, resulting in tumor recurrence. Here, we generated ex vivo primary OCSC-enriched three-dimensional (3D) spheres from 10 distinct treatment naive patient-derived adherent (2D) cultures. We used state-of-the-art quantitative mass spectrometry to characterize the molecular events associated with OCSCs by analyzing their proteome and phosphoproteome. Our data revealed a stemness-related protein signature, shared within a heterogeneous patient cohort, which correlates with chemo-refractoriness in a clinical proteomics dataset. Moreover, we identified targetable deregulated kinases and aberrant PDGF receptor activation in OCSCs. Pharmacological inhibition of PDGFR in adherent OC cells reduced the stemness potential, measured by sphere formation assay. Overall, we provide a valuable resource to identify new OCSC markers and putative targets for OCSC-directed therapies.

Spatial transcriptomics reveals discrete tumour microenvironments and autocrine loops within ovarian cancer subclones

High-grade serous ovarian carcinoma (HGSOC) is genetically unstable and characterised by the presence of subclones with distinct genotypes. Intratumoural heterogeneity is linked to recurrence, chemotherapy resistance, and poor prognosis. Here, we use spatial transcriptomics to identify HGSOC subclones and study their association with infiltrating cell populations. Visium spatial transcriptomics reveals multiple tumour subclones with different copy number alterations present within individual tumour sections. These subclones differentially express various ligands and receptors and are predicted to differentially associate with different stromal and immune cell populations. In one sample, CosMx single molecule imaging reveals subclones differentially associating with immune cell populations, fibroblasts, and endothelial cells. Cell-to-cell communication analysis identifies subclone-specific signalling to stromal and immune cells and multiple subclone-specific autocrine loops. Our study highlights the high degree of subclonal heterogeneity in HGSOC and suggests that subclone-specific ligand and receptor expression patterns likely modulate how HGSOC cells interact with their local microenvironment.

HOMER3 promotes liver hepatocellular carcinoma cancer progression by -upregulating EZH2 and mediating miR-361/GPNMB axis

Liver hepatocellular carcinoma (LIHC) is among the most lethal human cancers. Studies have shown that Homer scaffold protein 3 (HOMER3) plays important roles in various diseases and cancers, but its biological function and molecular mechanism in LIHC have never been investigated. Our study discovered the aberrantly high expression of HOMER3 and its promising diagnostic and prognostic significance in LIHC. Functionally, HOMER3 knockdown inhibited the proliferative and migrative abilities of LIHC cells and tumor growth in vivo. Mechanically, HOMER3 mediated the aggressiveness of LIHC cells via GPNMB. Meanwhile, miR-361 directly targeted GPNMB and attenuated LIHC progression by suppressing GPNMB expression. The regulatory effect of HOMER3 during LIHC progression was exerted through the miR-361/GPNMB axis. Furthermore, EZH2 supplementation or miR-361 depletion effectively abated the tumor-suppressive effect of HOMER3 knockdown on LIHC progression. In conclusion, HOMER3 mediated LIHC progression through the EZH2/miR-361/GPNMB axis.

Construction of a prognostic model for radical esophagectomy based on immunohistochemical prognostic markers combined with clinicopathological factors

Esophageal squamous cell carcinoma (ESCC) has a poor prognosis and lacks effective biomarkers to evaluate prognosis and treatment. Glycoprotein nonmetastatic melanoma protein B (GPNMB) is a protein highly expressed in ESCC tissues screened by isobaric tags for relative and absolute quantitation proteomics, which has significant prognostic value in a variety of malignant tumors, but its relationship with ESCC remains unclear. By immunohistochemical staining of 266 ESCC samples, we analyzed the relationship between GPNMB and ESCC. To explore how to improve the ability of ESCC prognostic assessment, we established a prognostic model of GPNMB and clinicopathological features. The results suggest that GPNMB expression is generally positive in ESCC tissues and is significantly associated with poorer differentiation, more advanced American Joint Council on Cancer (AJCC) stage, and higher tumor aggressiveness (P < .05). Multivariate Cox analysis indicated that GPNMB expression was an independent risk factor for ESCC patients. A total of 188 (70%) patients were randomly selected from the training cohort and the four variables were automatically screened by stepwise regression based on the AIC principle: GPNMB expression, nation, AJCC stage and nerve invasion. Through the weighted term, we calculate the risk score of each patient, and by drawing the receiver operating characteristic curve, we show that the model has good prognostic evaluation performance. The stability of the model was verified by test cohort. Conclusion: GPNMB is a prognostic marker consistent with the characteristics of tumor therapeutic targets. For the first time, we constructed a prognostic model combining immunohistochemical prognostic markers and clinicopathological features in ESCC, which showed higher prognostic efficacy than AJCC staging system in predicting the prognosis of ESCC patients in this region.

Prognostic Value of GPNMB, EGFR, p-PI3K, and Ki-67 in Patients with Esophageal Squamous Cell Carcinoma

Background. GPNMB is a newly discovered tumour-promoting factor that may promote tumour cell progression by activating the PI3K/AKT pathway by EGFR. However, there are insufficient studies about GPNMB in ESCC. This study investigated the relationship between GPNMB and EGFR/PI3K pathway genes in ESCC. Methods. The expression levels of GPNMB, EGFR, p-PI3K, and Ki-67 were examined using immunohistochemistry. Statistical analysis was done by SPSS 22.0 and R. Results. GPNMB mRNA expression is higher in ESCC compared with paracancerous tissues. The expression of EGFR, PIK3CA, PIK3CB, and AKT1 was increased in GPNMB upregulated samples. GPNMB expression was positively correlated with EGFR, p-PI3K, and Ki-67 expression. GPNMB was expressed higher in the AJCC III stage, lymph node metastasis, and moderately poorly differentiated patients. EGFR was higher expressed in patients with vascular invasion; p-PI3K expression in Kazak was higher than that in Han; Ki-67 expression was higher in $\text{tumour}\text{size}\ge 3\text{cm}$ . Patients with high expression of GPNMB, p-PI3K, and Ki-67 had worse OS. p-PI3K, Ki-67, nerve invasion, and lymphatic metastasis were independent risk factors, and postoperative adjuvant therapy was a protective factor in ESCC. Conclusion. As a tumour-promoting factor, GPNMB is expected to be a potential target for ESCC.

GPNMB-Positive Cells in Head and Neck Squamous Cell Carcinoma-Their Roles in Cancer Stemness, Therapy Resistance, and Metastasis

Objective: Despite the use of surgical and chemoradiation therapies, head and neck squamous cell carcinoma (HNSCC) still has a poor prognosis. Immune checkpoint inhibitors have been shown to prolong life expectancy but have limited efficacy. Glycoprotein nonmetastatic melanoma protein B (GPNMB) has received significant attention in breast cancer treatment, in which it has been associated with cancer stem cells (CSCs) and epithelial-mesenchymal transition (EMT); however, the function of GPNMB in HNSCC is completely unknown. This study aimed to clarify the characteristics of GPNMB-positive cells in vitro and their association with the prognosis by immunostaining clinical specimens. Methods: We examined the sphere formation, invasion, and migration ability of GPNMB-positive cells in four HNSCC cell lines in vitro. We also immunostained biopsy specimens with GPNMB from 174 patients with HNSCC diagnosed, treated, and followed-up in our institution to evaluate overall survival and progression-free survival. Results: GPNMB-positive cells showed enhanced sphere formation, invasion, and migration, suggesting that they could have CSC characteristics and the ability to induce EMT, as reported for breast cancer. Clinical specimens showed that overall survival was 39.4% and 57.8% (p = 0.045) and that progression-free survival was 27.6% and 51.6% (p = 0.013) for the high-expression and the low-expression groups, respectively, indicating poor prognosis for the high GPNMB group. The high GPNMB group was also more resistant to chemoradiation and bioradiotherapy. GPNMB was more highly expressed in metastatic lymph nodes than in the primary tumor. Conclusion: GPNMB-positive cells might have CSC characteristics and induce EMT. Detailed functional analyses of GPNMB in HNSCC and the establishment of therapies targeting GPNMB will lead to improved prognoses.

miR-532-3p suppresses proliferation and invasion of ovarian cancer cells via GPNMB/HIF-1α/HK2 axis

OBJECTIVE

Identifying a new target of miR-532-3p and studying its functional mechanism to explore the detailed anti-tumor mechanism of miR-532-3p in ovarian cancer.

METHODS

Biological and molecular methods including real-time quantitative PCR (RT-qPCR), Western blotting, colony formation, in vitro migration and invasion assays, glucose consumption and lactate production assays, RNA interference and tumor xenograft mouse models were used to study the role of miR-532-3p and its target in ovarian cancer. mRNA sequencing, dual-luciferase reporter assay and immunohistochemistry (IHC) were used to identify miR-532-3p target. STRING dataset analysis, qPCR and Western blotting were used to investigate the downstream pathway of the target of miR-532-3p.

RESULTS

Forced expression of miR-532-3p inhibited the proliferation, migration and invasion of ovarian cancer cells in vitro and the tumor growth in nude mice. RNA sequencing found 299 mRNAs were downregulated in miR-532-3p-overexpressed ovarian cancer cells, and bioinformatic analysis indicated Glycoprotein Nonmetastatic Melanoma Protein B (GPNMB), a type I membrane glycoprotein, was the potential target of miR-532-3p. GPNMB was reduced at both RNA and protein levels in miR-532-3p-overexpressed ovarian cancer cells. Dual-luciferase reporter assay determined GPNMB as the target of miR-532-3p. Interference of GPNMB inhibited the proliferation, migration, invasion, glucose consumption and lactate production of ovarian cancer cells. Knocking down of GPNMB reduced the protein level of HIF-1α without affecting HIF-1α mRNA level. Overexpression of GPNMB reversed the antitumor effect of miR-532-3p.

CONCLUSION

miR-532-3p exerted the anti-cancer effect by targeting GPNMB/ HIF-1α/ HK2 pathway to inhibit aerobic glycolysis in ovarian cancer.

GPNMB overexpression is associated with extensive bone metastasis and poor prognosis in renal cell carcinoma

Glycoprotein non-metastatic protein B (GPNMB) promotes bone metastasis (BM) in various types of cancer. However, GPNMB expression and its function in patients with renal cell carcinoma (RCC) and BM is still unknown. Therefore, the clinical significance of GPNMB and its biological function in RCC with BM was investigated in the present study. A total of 31 patients with RCC and BM were retrospectively collected. The association between GPNMB protein expression level on the primary tumor and the clinicopathological characteristics of the patients was analyzed. Kaplan-Meier analysis was used to investigate the association between GPNMB expression and the prognosis of the patients. The effects of GPNMB inhibition on cell proliferation, migration and invasion in RCC cells were investigated using short hairpin (sh)RNA. High GPNMB expression level was significantly associated with the number (P=0.001) and the extent of BM (P=0.001), Fuhrman grade (P=0.037), and ERK expression level (P=0.003) of the primary tumor. In addition, GPNMB overexpression was significantly associated with poor prognosis with respect to overall survival time (P=0.001). Furthermore, a specific shRNA sequence targeting the GPNMB gene was constructed and transduced into the ACHN cell line, using a lentivirus vector to obtain a stable cell line with low mRNA expression level of GPNMB. Low GPNMB expression level inhibited RCC cell proliferation, which was measured using a Cell Counting Kit-8 assay. Cell migration and invasion ability was significantly decreased in GPNMB knockdown RCC cells compared with that in cells transduced with the negative control shRNA. In addition, the protein expression levels of phosphorylated ERK were lower in the GPNMB shRNA-transduced ACHN cells compared with those in the control cells. Therefore, these results suggested that GPNMB plays an important role in tumor progression in RCC with BM. Furthermore, it might serve as a predictive marker for BM and as a poor prognostic factor in RCC with BM. GPNMB downregulation suppressed the proliferation, migration and invasion of the RCC cells, which may be mediated through the inhibition of the ERK signaling pathway.

Low Expression of SLC7A11 Confers Drug Resistance and Worse Survival in Ovarian Cancer via Inhibition of Cell Autophagy as a Competing Endogenous RNA

Drug resistance is the main cause of chemotherapy failure in ovarian cancer (OC), and identifying potential druggable targets of autophagy is a novel and promising approach to overcoming drug resistance. In this study, 131 genes associated with autophagy were identified from three autophagy-related databases, and of these, 14 were differentially expressed in 90 drug-resistant OC tissues versus 197 sensitive tissues according to the Cancer Genome Atlas ovarian cancer cohort. Among these 14 genes, SLC7A11 was significantly decreased in two paclitaxel-resistant OC cells (HeyA8-R and SKOV3-R) and in 90 drug-resistant tissues compared with their controls. In vitro overexpression of SLC7A11 significantly increased the sensitivity of HeyA8-R cells to paclitaxel, inhibited colony formation, induced apoptosis, and arrested cell cycle. Further, low SLC7A11 expression was correlated with poor overall survival (OS), progression-free survival (PFS), and post-progression survival (PPS) in 1815 OC patients. Mechanistically, SLC7A11 strongly regulated cell autophagy as a competing endogenous RNA (ceRNA) based on pan-cancer analyses of 32 tumor types. Specifically, as a ceRNA for autophagy genes STX17, RAB33B, and UVRAG, SLC7A11 was strongly and positively co-expressed with these three genes in 20, 12, and 12 different tumors, respectively, in 379 OC tissues and in 90 drug-resistant OC tissues, and the former two were significantly upregulated in SLC7A11-overexpressed HeyA8-R cells. Further, SLC7A11 induced the protein expression of other autophagy genes, such as LC3, Atg16L1, and Atg7, and the expression of the respective proteins was further increased when the cells were treated with paclitaxel. The results strongly suggest that SLC7A11 regulates autophagy via ceRNA interactions with the three abovementioned genes in pan-cancer and in drug-resistant OC. Moreover, low expression of STX17 and UVRAG also significantly predicted low OS, PFS, and PPS. The combination of SLC7A11 with STX17 was more predictive of OS and PFS than either individually, and the combination of SLC7A11 with UVRAG was highly predictive of OS and PPS. The above results indicated that decreased SLC7A11 resulted in drug resistance and effected low rates of survival in OC patients, probably via ceRNA interactions with autophagy genes, and thus the gene could serve as a therapeutic target and potential biomarker in OC.

Identification of pathological grade and prognosis-associated lncRNA for ovarian cancer

Ovarian carcinoma (OC) is one of the most common malignant tumors in female genitals. In recent years, the therapeutic effect of OC has been significantly improved through the application of effective chemotherapy regimen. However, the 5-year survival rate is also lower than 30% due to high rate of relapse. So, it is needed to screen reliable predictive and prognostic markers of OC. Ovarian cancer gene expression data and corresponding clinical data used were downloaded from Gene Expression Omnibus database. Weighted gene expression network analysis (WGCNA) and Cox proportional hazards regression (PHR) were used to screen Pathological Grade and Prognosis-associated long noncoding RNA (lncRNA). Kaplan-Meier analysis and receiver operating characteristic curves analysis were performed to evaluate the predictive ability of the selected lncRNA. Gene Ontology (GO) enrichment and Gene Set Enrichment Analysis (GSEA) enrichment analysis methods were used to explore the possible mechanisms of the selected lncRNA affecting the development of OC. Five reliably lncRNAs (LINC00664, LINC00667, LINC01139, LINC01419, and LOC286437) was identified through a series of bioinformatics methods. In testing cohorts, we found that the five lncRNAs in predicting the risk of OC recurrence is robustness, and multivariate Cox PHR analysis indicate that the five lncRNAs is an independent risk factor for OC recurrence. Moreover, GO and GSEA enrichment analysis showed that the five lncRNAs are involved in multiple ovarian cancer occurrence mechanism. In summary, all these findings indicated that the five lncRNAs can effectively predict the risk of recurrence of ovarian cancer.