Nuclear NHERF1 expression as a prognostic marker in breast cancer

Our purpose was to investigate whether Na⁺/H⁺ exchanger regulatory factor 1 (NHERF1) expression could be linked to prognosis in invasive breast carcinomas. NHERF1, an ezrin-radixin-moesin (ERM) binding phosphoprotein 50, is involved in the linkage of integral membrane proteins to the cytoskeleton. It is therefore believed to have an important role in cell signaling associated with changes in cell cytoarchitecture. NHERF1 expression is observed in various types of cancer and is related to tumor aggressiveness. To date the most extensive analyses of the influence of NHERF1 in cancer development have been performed on breast cancer. However, the underlying mechanism and its prognostic significance are still undefined. NHERF1 expression was studied by immunohistochemistry (IHC) in a cohort of 222 breast carcinoma patients. Association of cytoplasmic and nuclear NHERF1 expression with survival was analyzed. Disease-free survival (DFS) and overall survival (OS) were determined based on the Kaplan–Meier method. Cytoplasmic NHERF1 expression was associated with negative progesterone receptor (PgR) (P=0.017) and positive HER2 expression (P=0.023). NHERF1 also showed a nuclear localization and this correlated with small tumor size (P=0.026) and positive estrogen receptor (ER) expression (P=0.010). Multivariate analysis identified large tumor size (P=0.011) and nuclear NHERF1 expression (P=0.049) to be independent prognostic variables for DFS. Moreover, the nuclear NHERF1(−)/ER(−) immunophenotype (27%) was statistically associated with large tumor size (P=0.0276), high histological grade (P=0.0411), PgR-negative tumors (P<0.0001) and high proliferative activity (P=0.0027). These patients had worse DFS compared with patients with nuclear NHERF1(+)/ER(+) tumors (75.4% versus 92.6% P=0.010). These results show that the loss of nuclear NHERF1 expression is associated with reduced survival, and the link between nuclear NHERF1 and ER expression may serve as a prognostic marker for the routine clinical management of breast cancer patients.     

Metastatic risk and resistance to BRAF inhibitors in melanoma defined by selective allelic loss of ATG5

Melanoma is a paradigm of aggressive tumors with a complex and heterogeneous genetic background. Still, melanoma cells frequently retain developmental traits that trace back to lineage specification programs. In particular, lysosome-associated vesicular trafficking is emerging as a melanoma-enriched lineage dependency. However, the contribution of other lysosomal functions such as autophagy to melanoma progression is unclear, particularly in the context of metastasis and resistance to targeted therapy. Here we mined a broad spectrum of cancers for a meta-analysis of mRNA expression, copy number variation and prognostic value of 13 core autophagy genes. This strategy identified heterozygous loss of ATG5 at chromosome band 6q21 as a distinctive feature of advanced melanomas. Importantly, partial ATG5 loss predicted poor overall patient survival in a manner not shared by other autophagy factors and not recapitulated in other tumor types. This prognostic relevance of ATG5 copy number was not evident for other 6q21 neighboring genes. Melanocyte-specific mouse models confirmed that heterozygous (but not homozygous) deletion of Atg5 enhanced melanoma metastasis and compromised the response to targeted therapy (exemplified by dabrafenib, a BRAF inhibitor in clinical use). Collectively, our results support ATG5 as a therapeutically relevant dose-dependent rheostat of melanoma progression. Moreover, these data have important translational implications in drug design, as partial blockade of autophagy genes may worsen (instead of counteracting) the malignant behavior of metastatic melanomas.     

Progress and prospects for the discovery of biomarkers for gastric cancer: a focus on proteomics

Introduction: Patient outcomes from gastric cancer vary due to the complexity of stomach carcinogenesis. Recent research using proteomic technologies has targeted components of all of these systems in order to develop biomarkers to aid the early diagnosis of gastric cancer and to assist in prognostic stratification.

Areas covered: This review is comprised of evidence obtained from literature searches from PubMed. It covers the evidence of diagnostic, prognostic, and predictive biomarkers for gastric cancer using proteomic technologies, and provides up-to-date references.

Expert commentary: The proteomic technologies have not only enabled the screening of a large number of samples, but also enabled the identification of diagnostic, prognostic and predictive biomarkers for gastric cancer. While major challenges still remain, to date, proteomic studies in gastric cancer have provided a wealth of information in revealing proteome alterations associated with the disease.     

Expression of the significance of silent information regulator type-1 in Angioimmunoblastic T-cell lymphoma is greater association with tumorigenesis and has strong implications for adverse prognosis

Silent information regulator type-1 (SIRT1) is the best-studied member of the Sirtuin (Sir2) family of nicotinamide dinucleotide (NAD)-dependent class III histone deacetylases (HDACs). Rrecently, it is suggested that SIRT1 may be involved in the development of malignant tumors including mouse lymphoma, but has not yet been explored in Angioimmunoblastic T-cell lymphoma (AITL). Therefore, we investigated the prevalence and the prognostic impact of SIRT1 expression in AITL. Immunohistochemical expression of SIRT1, p53 were evaluated by using a 2 mm core from 45 AITL patients. Positive expression of SIRT1 was seen in 71.11% (32 of 45) of patients and p53 expression were seen in 53.33% (24 of 45). SIRT1 and p53 expression were significantly associated with shorter PFS by univariate analysis (P=0.009 and P < 0.001, respectively), multivariate analysis also shows that SIRT1 expression relate to worse prognosis. We also suggest inferior survival in AITL with the combined expression of SIRT1 and clinical characteristics of high IPI scores, high clinical stage, increased serum LDH, decreased HGB and increased γ-Globulin. In conclusion, our results indicate that SIRT1 is strongly expressed in AITL and it act as a clinically significant prognostic indicator for AITL patients, may also serve as a therapeutic target in AITL.     

Skp2 is over-expressed in breast cancer and promotes breast cancer cell proliferation

The F box protein Skp2 is oncogenic. Skp2 and Skp2B, an isoform of Skp2 are overexpressed in breast cancer. However, little is known regarding the mechanism by which Skp2B promotes the occurrence and development of breast cancer. Here, we determined the expression and clinical outcomes of Skp2 in breast cancer samples and cell lines using breast cancer database, and investigated the role of Skp2 and Skp2B in breast cancer cell growth, apoptosis and cell cycle arrest. We obtained Skp2 is significantly overexpressed in breast cancer samples and cell lines, and high Skp2 expression positively correlated with poor prognosis of breast cancer. Both Skp2 and Skp2B could promote breast cancer cell proliferation, inhibit cell apoptosis, change the cell cycle distribution and induce the increased S phase cells and therefore induce cell proliferation in breast cancer cells. Moreover, the 2 isoforms could both suppress PIG3 expression via independent pathways in the breast cancer cells. Skp2 suppressed p53 and inhibited PIG3-induced apoptosis, while Skp2B attenuated the function of PIG3 by inhibiting PHB. Our results indicate that Skp2 and Skp2B induce breast cancer cell development and progression, making Skp2 and Skp2B potential molecular targets for breast cancer therapy.     

Cigarette smoking might weaken the prognostic significance of cytochrome P450 2C19*2 polymorphism in acute myocardial infarction patients

Prognostic significance of cytochrome P450 2C19*2 polymorphism in acute myocardial infarction is still not well investigated. The aim of the study was to determine the relationship between the genetic polymorphism and the outcome of the acute myocardial infarction patients, and to further clarify the impact of smoking on such relationship. Six hundred acute myocardial infarction patients were enrolled. All of them provided blood samples and underwent clopidogrel treatment. The genetic polymorphism was determined by polymerase chain reaction–restriction fragment length polymorphism analysis, and the platelet function was assessed using conventional aggregometry. Of the included patients, 287 carried GG wild‐type genotypes, 225 carried GA genotypes and 88 carried AA genotypes. The platelet aggregation rate was significantly elevated in the AA genotype patients, mainly in the non‐smoking patients (P < 0.001) and the former‐smoking patients (P < 0.001). During 5‐year follow‐up period, after adjusted for multiple confounding factors, AA genotypes were associated with the increase in 5‐year mortalities in the non‐smoking patients [OR: 7.06, 95% confidence interval (CI): 2.16–11.49] and the former‐smoking patients (OR: 4.38, 95% CI: 1.05–9.40), but not in the current‐smoking patients (OR: 1.12, 95% CI: 0.60–2.31). In conclusion, the study suggested a potential role of P450 2C19*2 polymorphism as a prognostic indicator in acute myocardial infarction patients. We had also obtained some evidence that current smoking might weaken the prognostic significance of the genetic polymorphism in patients.     

Development of a risk scoring system for patients with papillary thyroid cancer

As the importance of personalized therapeutics in aggressive papillary thyroid cancer (PTC) increases, accurate risk stratification is required. To develop a novel prognostic scoring system for patients with PTC (n = 455), we used mRNA expression and clinical data from The Cancer Genome Atlas. We performed variable selection using Network‐Regularized high‐dimensional Cox‐regression with gene network from pathway databases. The risk score was calculated using a linear combination of regression coefficients and mRNA expressions. The risk score and clinical variables were assessed by several survival analyses. The risk score showed high discriminatory power for the prediction of event‐free survival as well as the presence of metastasis. In multivariate analysis, the risk score and presence of metastasis were significant risk factors among the clinical variables that were examined together. In the current study, we developed a risk scoring system that will help to identify suitable therapeutic options for PTC.     

An estrogen receptor (ER)‐related signature in predicting prognosis of ER‐positive breast cancer following endocrine treatment

Quite a few estrogen receptor (ER)‐positive breast cancer patients receiving endocrine therapy are at risk of disease recurrence and death. ER‐related genes are involved in the progression and chemoresistance of breast cancer. In this study, we identified an ER‐related gene signature that can predict the prognosis of ER‐positive breast cancer patient receiving endocrine therapy. We collected RNA expression profiling from Gene Expression Omnibus database. An ER‐related signature was developed to separate patients into high‐risk and low‐risk groups. Patients in the low‐risk group had significantly better survival than those in the high‐risk group. ROC analysis indicated that this signature exhibited good diagnostic efficiency for the 1‐, 3‐ and 5‐year disease‐relapse events. Moreover, multivariate Cox regression analysis demonstrated that the ER‐related signature was an independent risk factor when adjusting for several clinical signatures. The prognostic value of this signature was validated in the validation sets. In addition, a nomogram was built and the calibration plots analysis indicated the good performance of this nomogram. In conclusion, combining with ER status, our results demonstrated that the ER‐related prognostic signature is a promising method for predicting the prognosis of ER‐positive breast cancer patients receiving endocrine therapy.     

Integrative analysis identifies potential DNA methylation biomarkers for pan-cancer diagnosis and prognosis

DNA methylation status is closely associated with diverse diseases, and is generally more stable than gene expression, thus abnormal DNA methylation could be important biomarkers for tumor diagnosis, treatment and prognosis. However, the signatures regarding DNA methylation changes for pan-cancer diagnosis and prognosis are less explored. Here we systematically analyzed the genome-wide DNA methylation patterns in diverse TCGA cancers with machine learning. We identified seven CpG sites that could effectively discriminate tumor samples from adjacent normal tissue samples for 12 main cancers of TCGA (1216 samples, AUC > 0.99). Those seven potential diagnostic biomarkers were further validated in the other 9 different TCGA cancers and 4 independent datasets (AUC > 0.92). Three out of the seven CpG sites were correlated with cell division, DNA replication and cell cycle. We also identified 12 CpG sites that can effectively distinguish 26 different cancers (7605 samples), and the result was repeatable in independent datasets as well as two disparate tumors with metastases (micro-average AUC > 0.89). Furthermore, a series of potential signatures that could significantly predict the prognosis of tumor patients for 7 different cancer were identified via survival analysis (p-value < 1e-4). Collectively, DNA methylation patterns vary greatly between tumor and adjacent normal tissues, as well as among different types of cancers. Our identified signatures may aid the decision of clinical diagnosis and prognosis for pan-cancer and the potential cancer-specific biomarkers could be used to predict the primary site of metastatic breast and prostate cancers.     

Comparison of five different scoring methods in the evaluation of inflammatory infiltration (tumor‐infiltrating lymphocytes) in superficial spreading and nodular melanoma

The objective of our study was to compare the five different scoring methods of tumor‐infiltrating lymphocytes (TILs) assessment in a group of 213 cases of superficial spreading and nodular melanoma. The scoring methods include (a) Clark scoring; (b) Melanoma Institute Australia system; (c) scoring system used in the study of Saldanha et al.; (d) scoring system used in the TCGA study and modified by Park et al.; and (e) the system recently proposed by the “International Immuno‐Oncology Biomarker Working Group” for TILs scoring in all solid tumors. Prediction of survival with three main outcomes—disease‐specific‐free survival, local recurrence‐free survival, and distant metastasis‐free survival—was evaluated. The prognostic value of TILs showed statistical significance in univariate analysis regarding all three of the outcomes only for three of the five evaluated methods; the Clark scoring, the Melanoma Institute Australia system, and the system proposed by the “International Immuno‐Oncology Biomarker Working Group”. However, in multivariate analysis with covariants including Breslow thickness, type of melanoma, location, sex, and age, we did not find TILs to be an independent prognostic factor.