Elevated expression of a pharmacologic Polycomb signature predicts poor prognosis in gastric and breast cancer

Gastric cancer: An epigenetic view

Gastric cancer (GC) poses a serious threat worldwide with unfavorable prognosis mainly due to late diagnosis and limited therapies. Therefore, precise molecular classification and search for potential targets are required for diagnosis and treatment, as GC is complicated and heterogeneous in nature. Accumulating evidence indicates that epigenetics plays a vital role in gastric carcinogenesis and progression, including histone modifications, DNA methylation and non-coding RNAs. Epigenetic biomarkers and drugs are currently under intensive evaluations to ensure efficient clinical utility in GC. In this review, key epigenetic alterations and related functions and mechanisms are summarized in GC. We focus on integration of existing epigenetic findings in GC for the bench-to-bedside translation of some pivotal epigenetic alterations into clinical practice and also describe the vacant field waiting for investigation.

An integrated classifier improves prognostic accuracy in non-metastatic gastric cancer

The American Joint Committee on Cancer (AJCC) staging system is insufficiently prognostic for gastric cancer (GC) patients and complementary factors are in urgent need. Here we aimed to develop a comprehensive model, consisting of both immune signatures and cancer signaling molecules, which was expected to accurately improve survival prediction in non-metastatic gastric cancer (GC). We first validated the prognostic value of a combination of 18 immune features and 52 cancer-signaling molecules in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Then, their expression and distribution were analyzed in consecutive 1180 GC patients using immunohistochemistry. We developed and validated a novel protein-based prognostic classifier using CDH1, an epithelial–mesenchymal transition (EMT) marker, and five immune features (CD3, CD4, CD274, GZMB, and PAX5) by Cox regression model with group LASSO penalty. We observed significant differences in the overall survival of the high- and low-prognostic risk groups (66.8% VS 27.0%, P < .001). A combination of this classifier with age and pTNM stage had better prognostic value than pTNM alone. The model was further validated in both treatment-naive patients and those treated with neoadjuvant chemotherapy. Moreover, GC patients with high-risk score exhibited a favorable prognosis to adjuvant chemotherapy. This integrated classifier could be automatically analyzed and effectively predict survival of GC patients and may provide a new clinically applicable strategy to identify patients who are more likely to benefit from adjuvant chemotherapy.

Prediction of gastric cancer prognosis in the next-generation sequencing era

Gastric cancer (GC) is one of the most commonly diagnosed malignancies worldwide, and is caused by complex interactions of multiple risk factors such as environmental (Helicobacter pylori and Epstein–Barr Virus), hereditary (genetic alterations and epigenetic modifications), as well as dietary and lifestyle factors. GC is usually detected at an advanced stage, with a dismal prognosis. Even for patients with similar clinical or pathologic stage receiving similar treatment, the outcomes are still uneven and unpredictable. To better incorporate genetic and epigenetic profiles into GC prognostic predication, gene expression signatures have been developed to predict GC outcomes. More recently, the advancement of high-throughput sequencing technology, also known as next-generation sequencing (NGS) technology, and analysis has provided the basis for accurate molecular classification of GC tumors. Here, we summarized and updated the literature related to NGS studies of GC, including whole-genome sequencing, whole-exome sequencing, RNA sequencing, and targeted sequencing, and discussed current progresses. NGS has facilitated the identification of genetic/epigenetic targets for screening as well as development of targeted agent therapy, thus enabling individualized patient management and treatment.

Key actors in cancer therapy: epigenetic modifiers

Epigenetic reprogramming plays a crucial role in the tumorigenicity and maintenance of tumor-specific gene expression that especially occurs through DNA methylation and/or histone modifications. It has well-defined mechanisms. It is known that alterations in the DNA methylation pattern and/or the loss of specific histone acetylation/methylation markers are related to several hallmarks of cancer, such as drug resistance, stemness, epithelial-mesenchymal transition, and metastasis. It has also recently been highlighted that epigenetic alterations are critical for the regulation of the stemlike properties of cancer cells (tumor-initiating cells; cancer stem cells). Cancer stem cells are thought to be responsible for the recurrence of cancer which makes the patient return to the clinic with metastatic tumor tissue. Hence, the dysregulation of epigenetic machinery represents potential new therapeutic targets. Therefore, compounds with epigenetic activities have become crucial for developing new therapy regimens (e.g., antimetastatic agents) in the fight against cancer. Here, we review the epigenetic modifiers that have already been used in the clinic and/or in clinical trials, related preclinical studies in cancer therapy, and the smart combination strategies that target cancer stem cells along with the other cancer cells. The emerging role of epitranscriptome (RNA epigenetic) in cancer therapy has also been included in this review as a new avenue and potential target for the better management of cancer-beneficial epigenetic machinery.

Aberrant Epigenetic Regulation in Head and Neck Cancer Due to Distinct EZH2 Overexpression and DNA Hypermethylation

Enhancer of Zeste homologue 2 (EZH2) overexpression is associated with tumor proliferation, metastasis, and poor prognosis. Targeting and inhibition of EZH2 is a potentially effective therapeutic strategy for head and neck squamous cell carcinoma (HNSCC). We analyzed EZH2 mRNA expression in a well-characterized dataset of 230 (110 original and 120 validation cohorts) human head and neck cancer samples. This study aimed to investigate the effects of inhibiting EZH2, either via RNA interference or via pharmacotherapy, on HNSCC growth. EZH2 upregulation was significantly correlated with recurrence (p < 0.001) and the methylation index of tumor suppressor genes (p < 0.05). DNMT3A was significantly upregulated upon EZH2 upregulation (p = 0.043). Univariate analysis revealed that EZH2 upregulation was associated with poor disease-free survival (log-rank test, p < 0.001). In multivariate analysis, EZH2 upregulation was evaluated as a significant independent prognostic factor of disease-free survival (hazard ratio: 2.085, 95% confidence interval: 1.390–3.127; p < 0.001). Cells treated with RNA interference and DZNep, an EZH2 inhibitor, showed the most dramatic changes in expression, accompanied with a reduction in the growth and survival of FaDu cells. These findings suggest that EZH2 upregulation is correlated with tumor aggressiveness and adverse patient outcomes in HNSCC. Evaluation of EZH2 expression might help predict the prognosis of HNSCC patients.