Emerging molecular classiifcations and therapeutic implications for gastric cancer

Gastric cancer (GC) is a highly aggressive and life?threatening malignancy. Even with radical surgical removal and front?line chemotherapy, more than half of GCs locally relapse and metastasize at a distant site. The dismal outcomes relfect the ineffectiveness of a one?size?ifts?all approach for a highly heterogeneous disease with diverse etiological causes and complex molecular underpinnings. The recent comprehensive genomic and molecular proifling has led to our deepened understanding of GC. The emerging molecular classiifcation schemes based on the genetic, epigenetic, and molecular signatures are providing great promise for the development of more effective therapeutic strategies in a more personalized and precise manner. To this end, the Cancer Genome Atlas ( TCGA) research network conducted a comprehensive molecular evaluation of primary GCs and proposed a new molecular classiifcation dividing GCs into four subtypes:Epstein?Barr virus?associated tumors, microsatellite unstable tumors, genomically stable tumors, and tumors with chromosomal instability. This review primarily focuses on the TCGA molecular classiifcation of GCs and discusses the implications on novel targeted therapy strategies. We believe that these fundamental ifndings will sup?port the future application of targeted therapies and will guide our efforts to develop more effcacious drugs to treat human GCs.     

Comparison and applicability of molecular classifications for gastric cancer

Gastric Cancer (GC) is a complex and heterogeneous disease, which represents a global health concern. Despite advances in prevention, diagnosis, and therapy, GC is still a leading cause of cancer-related death. Over the last decade, several clinical trials have tested novel agents for advanced GC with mostly disappointing results. Heterogeneity, the absence of molecular selection in clinical trials and powerless predictive biomarkers may be potential explanations. Different molecular classification proposals for GC based on the genetic, epigenetic, and molecular signatures have been published. Molecular characterization of GC may offer new tools for more effective therapeutic strategies, such as the development of therapies for specifically well-defined sets of patients as well as the use of new clinical trial designs, which will ultimately lead to an improvement of medical management of this disease. However, the possibilities of implementation of GC molecular classifications on daily practice and their therapeutic implications remain challenging to date. In this review, we will describe and compare these GC molecular classifications, focusing on their main characteristics as the basis for their potential therapeutic implications and strategies for their clinical application.Key Message: A better understanding of gastric cancer molecular characteristics may lead to further improvements in treatment and outcomes for patients with the disease.     

Identification of lncRNAs based on different patterns of immune infiltration in gastric cancer

BackgroundGastric cancer is one of the most common malignant tumors in the world, which brings great challenges to people’s life and health. The purpose of this study was to investigate immune related-lncRNAs and identify new biomarkers for the prognosis of gastric cancer (GC).MethodsWe downloaded data from The Cancer Genome Atlas (TCGA) and used R software to determine the ESTIMATEScore, ImmuneScore, and StromalScore of each tumor sample. We performed prognostic analysis and identified the differentially expressed lnRNAs, which were then used to construct a prognostic model. Among the 44 hub genes in the competitive endogenous RNA (ceRNA) network, 3 differentially expressed genes were verified by qPCR.ResultsBased on the degree of immune infiltration, cluster A had a higher ESTIMATEScore, ImmuneScore, and StromalScore and higher expression levels of PD-L1 (CD274) and CTLA4 than cluster B. Univariate Cox analysis was conducted for these differential lncRNAs, and 57 lncRNAs were found to have prognostic value (P<0.05). gene cluster A had a worse prognosis than gene cluster B (P=0.021). Then, a prognostic model was constructed. The low-risk group had a significantly higher survival rate. Finally, the qPCR results showed that the expression levels of BMPER, PRUNE2, and RBPMS2 were low in GC cell lines.ConclusionsWe identified a risk score of 19 lncRNAs as a prognostic marker of GC. There was a relationship between these 19 prognostic-related lncRNAs and the subtypes of infiltrating immune cells. An approach for predicting the prognosis of GC was therefore provided in this study.     

MicroRNA profiles in five pairs of early gastric cancer tissues and adjacent non-cancerous tissues

Approximately half of the world''s gastric cancer cases and deaths occur in China. In addition, the incidence and mortality rates of gastric cancer in Gansu province in China are much higher than the average nationwide levels. The present study investigated microRNA (miRNA/miR) profiles in early gastric cancer (EGC) without specific symptoms. miRNA expression levels in five pairs of EGC tissues and adjacent non-cancerous mucosa tissues of patients from Gansu province in China were analyzed using a miRNA microarray. A total of 47 differentially expressed miRNAs (DEMs) were identified. Subsequently, mRNA expression profiles of three pairs of cancer tissues and adjacent non-cancerous tissues from 3 Asian patients with stage I or stage II gastric cancer (stage I/II; American Joint Committee on Cancer classification, Eighth Edition) were obtained from The Cancer Genome Atlas database, and differentially expressed genes (DEGs) were identified. The target genes of DEMs were filtered from the DEGs using the miRDB database and a miRNA-gene network was constructed. The functions of DEMs were evaluated using the tool for annotations of human miRNAs database, and via Gene Ontology analysis, Kyoto Encyclopedia of Genes and Genomes analysis and Gene Set Enrichment Analysis of the target genes. Finally, survival analyses of DEMs, which were in the miRNA-gene network, was performed. The results suggested that a number of miRNAs, including hsa-let-7a-5p, hsa-miR-27a-3p, hsa-miR-126-5p and hsa-miR-424-5p, may serve critical roles in EGC. The present study could provide a basis for the identification of EGC screening biomarkers. Furthermore, the present study may provide a basis for the exploration of the cause of the high incidence of gastric cancer in Gansu province from the perspective of miRNAs.     

不同分子亚型乳腺癌的临床病理特征及预后分析

目的 探讨乳腺癌各分子亚型的临床特点及其预后情况.方法 分析1153例可手术乳腺癌患者的临床病理资料,根据雌激素受体(ER)、孕激素受体(PR)和人表皮生长因子受体2(Her-2)的表达情况将乳腺癌分为4种分子亚型,即Luminal A型、Luminal B型、Her-2过表达型和Basal-like型.分析各分子亚型乳腺癌患者在年龄、肿瘤大小、淋巴结转移状况、临床分期和预后的差异及影响预后的因素.结果 1153例患者中,Luminal A型791例(68.6%),Luminal B型50例(4.3%),Her-2过表达型53例(4.6%),Basal-like型259例(22.5%).各分子亚型在年龄、肿瘤大小、淋巴结转移状况、临床分期的差异均无统计学意义(均P>0.05).有完整随访资料的1006例患者中,Her-2过表达型的远处转移率(17.0%)显著高于其他亚型(P=0.005),而各分子亚型间的局部复发率差异无统计学意义(P>0.05).Kaplan-Meier法分析结果显示,Her-2过表达型患者的7年无病生存率和9年总生存率最低(均P<0.05).单因素和多因素分析结果均显示,淋巴结转移状况和分子分型是影响乳腺癌患者无病生存及总生存的独立预后因素.结论 Her-2过表达型乳腺癌患者的预后最差.乳腺癌的分子分型对判断患者预后可能具有重要临床意义,有望成为今后制订乳腺癌个体化治疗方案的重要依据.

Abstract：

Objective To investigate the clinical characteristics and prognosis of different breast cancer molecular subtypes.Methods Clinicopathological and follow-up data of 1153 cases of operable breast cancer were analyzed retrospectively.Their molecular subtypes were categorized as luminal A, luminal B, Her-2 over-expressing and basal-like subtypes, based on detection of ER, PR, Her-2 expression.The correlation of prognosis of different molecular subtypes with age, tumor size, lymph node status and clinical staging was analyzed.Results Among the 1153 cases, 791 cases (68.6%) were of luminal A subtype, 50 cases (4.3%) luminal B subtype, 53 cases (4.6%) Her-2( + )subtype, and 259 cases (22.5%) basallike subtype.There were no statistically significant differences among different molecular subtypes regarding the age, tumor size, lymph node status, and clinical stage.1006 cases had complete follow-up data and the analysis showed that distant metastasis of Her-2 over-expressing subtype was significantly higher than that in other subtypes ( P = 0.005 ), but the differelices of local recurrence rate in different molecular subtypes was not statistically significant (P >0.05).Kaplan-Meier method was used to analyze the survival prognosis of different molecular subtypes, showing both DFS rate and OS rate of Her-2 over-expressing subtype were the lowest, with a statistically significant difference (Log rank test, P < 0.05 ).Univariate and multivariate analyses showed that molecular typing and lymph node status were independent prognostic factors affecting both DFS and OS.Conclusions Her-2 over-expressing subtype has the worst prognosis.Molecular subtypes may provide important information to predict the prognosis of breast cancer and might be an important basis for individualized treatment of breast cancer in future.     

Prognostic effect analysis of molecular subtype on young breast cancer patients

Objective

To make a prognostic effect analysis of molecular subtype on young breast cancer patients.

Methods

Totally 187 cases of young breast cancer patients less than 40 years old treated in Obstetrics and Gynecology Hospital of Fudan University between June 2005 and June 2011 were included in our study. We described their clinical-pathological characteristics, disease-free survival (DFS) rate, and overall survival (OS) rate after a median follow-up period of 61 months. The factors associated with prognosis were also evaluated by univariate and multivariate analyses.

Results

All patients were premenopausal, with an average age of 35.36±3.88 years old. The mean tumor size was 2.43±1.53 cm. Eighty-one cases had lymph node metastasis (43.3%), 126 cases had lymphovascular invasion (67.4%), and 125 cases had histological grade III (66.8%) disease. Twenty-seven cases (14.4%) were Luminal A subtype, 99 cases (52.9%) were Luminal B subtype, 29 cases (15.5%) were human epidermal growth factor receptor 2 (HER-2) overexpression subtype, while 32 cases (17.1%) were triple negative breast cancer (TNBC) subtype according to 2013 St Gallen expert consensus. One hundred and thirty-five cases underwent mastectomy whereas 52 cases had breast-conserving surgery. One hundred and seventy-eight cases underwent adjuvant or neoadjuvant chemotherapy. Recurrence or metastasis occurred in 29 cases, 13 of which died. The 5-year DFS and OS rates were 84% and 92%. Multivariate analysis showed that nodal status (P=0.041) and molecular subtype (P=0.037) were both independent prognostic factors of DFS, while nodal status (P=0.037) and TNBC subtype (P=0.048) were both independent prognostic factors of OS.

Conclusions

Molecular subtype is an independent prognostic factor of young breast cancer patients. TNBC has a high risk of relapse and death.     

云南省乳腺癌分子分型与临床病理特点分析

目的：了解云南省乳腺癌患者的分子分型与临床病理特点.方法：收集2012年1月-2012年12月云南省肿瘤医院乳腺病科所收治的经根治性手术后病理确诊为原发性乳腺癌的初诊患者587例,统计分析分子分型与患者年龄、民族、病理类型、病灶大小、淋巴结分期、病理分期、p53等的相关性.结果：不同民族、病灶大小、淋巴结分期、p53表达与分子分型之间差异无统计学意义.不同年龄段与分子分型之间差异有统计学意义,P=0.033.不同病理类型与分子分型之间差异有统计学意义,P=0.022.不同病理分期与分子分型之间差异有统计学意义,P=0.004.结论：云南省乳腺癌不同年龄段、不同病理分期的分子分型存在差异.     

Predictive biomarkers along gastric cancer pathogenetic pathways

Introduction: Gastric cancer is the second leading cause of cancer all over the world. Unfortunately, several gastric cancers are diagnosed in an advanced stage and chemotherapy and/or target therapies remain the only options to treat patients.

Areas covered: Herein we evaluate the new molecular proposal of gastric cancer classification, offering the possibility to recognize different pathogenetic mechanisms and molecular biomarkers potentially useful for target therapies.

Expert commentary: The possibility of introducing new specific tests for identification of molecular biomarkers critical for targeted therapies response represents the new frontier in the selection of gastric cancer patients to improve their survival. Besides HER2, already used in clinical settings as a target biomarker for biological therapy in gastric cancer patients with tissue cancer cells overexpressing HER2, other promising target biomarkers which are deregulated in gastric cancer, such as MET and FGFR, could be identified in tissue and then used for therapeutic purposes. In addition immunotherapy represents the most promising possibility of advanced gastric cancer treatment. In particular, as in other solid tumors, PD-1/PDL1 pathway has emerged in several clinical trials as an interesting therapeutic target.     

乳腺癌不同分子亚型的临床特点和生存分析

目的探讨乳腺癌各分子亚型的临床特点及其预后情况。方法回顾性分析482例可手术乳腺癌患者资料．以免疫组织化学技术为基础,把乳腺癌分为4种分子亚型：luminalA型[ER（＋）或PR（＋）且HER-2（-）],luminalB型[ER（＋）或pR（＋）且HER-2（＋）],HER-2过表达型[ER（-）、PR（-）且HER-2（＋）j和basal—like型[ER（-）、PR（-）且HER-2（-）],并分析其临床特点及预后情况。结果全组共482例,其中luminalA型占46．1％（222／482）,luminalB型占14．7％（71／482）,HER-2过表达型占10．4％（50／482）,basal—like型占28．8％（139／482）。运用x。检验各分子亚型在年龄、月经状况、肿瘤大小、淋巴结状况和临床分期等的差异均无统计学意义。全组有完整随访资料者共441例,中位随访时间62个月。随访结果显示．HER-2过表达型和basal—like型的远处转移率均高于luminalA型,且差异有统计学意义（x2=11．659,P=0．009）;运用Kaplan—Meier法分析各分子亚型的生存预后,luminalA型的无病生存率、无远处转移生存率和总生存率最高,HER-2过表达型和basal-like型的预后最差,差异有统计学意义（Log—Rank检验,P均〈0．050）。结论乳腺癌分子分型对患者预后的判断具有重要临床意义,有望成为今后制定乳腺癌个体化治疗的重要依据。     

利用GEO及TCGA数据集分析SMARCA1在胃癌中的表达及其临床意义#br#

目的探讨基因表达汇编（GEO）及癌症和肿瘤基因表达图谱（TCGA）数据集中胃癌组织的SMARCA1表达情况及其与胃癌临床病理特征和预后的关系。 方法利用GEO和TCGA数据集汇总胃癌相关数据,下载胃癌组织SMARCA1表达数据及临床病理参数。分析SMARCA1表达与胃癌临床病理学特征和总生存期（OS）的关系;采用基因集富集分析（GSEA）预测SMARCA1相关的基因通路。 结果在GSE62254数据集中,SMARCA1表达与T分期有关（P=0022）,而与TNM分期、性别、年龄和N分期均无关（P＞005）。在TCGA数据集中,SMARCA1表达与T分期、性别、年龄、N分期、TNM分期和组织学分级均无关（P＞005）。GSE62254数据集中,SMARCA1高、中及低表达组胃癌患者的中位OS分别为364个月、894个月和未达（P=0001）;TCGA数据集中,SMARCA1高、中及低表达组胃癌患者的中位OS分别为237个月、294个月和562个月（P=0033）。GSEA结果显示,SMARCA1高表达样本富集了K Ras、Akt、BMI 1和mTOR通路等基因集。 结论胃癌组织中SMARCA1的表达与T分期有关,高表达患者的预后不良,可作为潜在评估胃癌预后的分子标志物。     

Population analysis of microsatellite genotypes reveals a signature associated with ovarian cancer

Ovarian cancer (OV) ranks fifth in cancer deaths among women, yet there remain few informative biomarkers for this disease. Microsatellites are repetitive genomic regions which we hypothesize could be a source of novel biomarkers for OV and have traditionally been under-appreciated relative to Single Nucleotide Polymorphisms (SNPs). In this study, we explore microsatellite variation as a potential novel source of genomic variation associated with OV. Exomes from 305 OV patient germline samples and 54 tumors, sequenced as part of The Cancer Genome Atlas, were analyzed for microsatellite variation and compared to healthy females sequenced as part of the 1,000 Genomes Project. We identified a subset of 60 microsatellite loci with genotypes that varied significantly between the OV and healthy female populations. Using these loci as a signature set, we classified germline genomes as ‘at risk’ for OV with a sensitivity of 90.1% and a specificity of 87.6%. Cross-analysis with a similar set of breast cancer associated loci identified individuals ‘at risk’ for both diseases. This study revealed a genotype-based microsatellite signature present in the germlines of individuals diagnosed with OV, and provides the basis for a potential novel risk assessment diagnostic for OV and new personal genomics targets in tumors.     

Development and verification of a microsatellite instability-related risk signature for predicting survival and therapy effectiveness in gastric cancer

BackgroundGastric cancer (GC) is one of is one of the most common malignancy among digestive system cancers worldwide. Increasing evidence has revealed that microsatellite instability (MSI) status can affect the survival in various cancers. However, the role of MSI status in GC remains uncertain.MethodsThe RNA-seq and clinicopathological features and mutation data of GC was obtained from The Cancer Genome Atlas (TCGA). Different bioinformatic and statistical methods were combined to construct a robust MSI-related gene signature for prognosis. Gene set enrichment analysis was conducted to explore Kyoto Encyclopedia of Genes and Genomes pathways associated with the MSI-related risk signature. Moreover, Kaplan-Meier (K-M) survival and receiver operating characteristic (ROC) analyses evaluate that the MSI-related risk signature. Immune-associated miRNAs were identified using immune scores calculated by the ssGSEA. In addition, ‘pRRophetic’ R package was used to assess the chemotherapeutic response by the GDSC website.ResultsWe firstly analyzed the influence of MSI status to GC survival based on the data from the TCGA database. GC patients in the TCGA database were divided into MSI-H and MSI-L/MSS groups. We counted the survival conditions of GC patients in these two groups. In addition, we also calculated the difference of TMB between these two groups and found that MSI-H group had a relatively high survival rate. Next, we identified 99 highly mutated genes in MSI-H group and constructed a MSI-related risk signature based on 10 robust genes for predicting the overall survival (OS) of GC patients. Moreover, analyses indicated that the MSI-related risk signature can accurately predict 1-, 3- and 5-year OS of GC patients. Furthermore, enrichment analysis suggested that genes between the high- and low-risk groups mainly involved in mutation and DNA repair related pathways. Finally, we also found that the MSI-related risk signature can affect the TME immune cell infiltration in GC and can be used to predict the clinical response to immunotherapy.ConclusionsIn the present study, we develop a MSI-related risk signature for predicting the survival and therapy of GC, which may contribute to the clinical treatment of GC.     

LRP8在胃癌中的表达及其在胃癌发生过程中的作用

背景 与目的:低密度脂蛋白受体相关蛋白8(low-density lipoprotein receptor-related protein 8,LRP8)在肝癌、肺癌、乳腺癌、结直肠癌等多种肿瘤发生中起重要作用,分析LRP8在胃癌中的表达及其意义,探讨LRP8作为胃癌生物治疗新靶点的可能性.方法:利用人类癌症基因组图谱...     

基于在线分析的磷酸果糖激酶在肺癌中的预后意义探讨

目的:探讨磷酸果糖激酶1（phosphofructokinase 1,PFK1）不同亚型对肺癌预后的预测价值及其可能参与的生物学过程。方法:从癌症基因组图谱(The Cancer Genome Atlas,TCGA)数据库中下载表达PFK1不同亚型(PFKP、PFKL和PFKM)表达谱资料及临床信息资料。分别分析这三个基因的表达与肺癌临床病理学参数的相关性及对预后的影响。采用基因集富集分析(Gene Set Enrichment Analysis,GSEA)方法预测关键基因的相关通路。结果:PFKP亚型与肺癌患者预后存在显著相关性（P<0.05）,且高表达患者预后更差。PFKP表达水平与肿瘤浸润深度（T分期）、淋巴结转移数量（N分期）和性别相关。PFKP高表达样本富集了糖酵解、细胞周期、细胞黏附连接等基因集。结论:肺癌中PFKP高表达是预后不良因素,其表达水平可作为预测肺癌患者预后的潜在生物标志物。     

Bioinformatics analysis identifying FBXO45 gene as a potential oncogene in esophageal cancer

BackgroundF-box protein 45 (FBXO45) is a member of the F-box protein family, and is reportedly involved in the progression of many diseases. However, its role in esophageal cancer (ESCA) remains unclear.MethodsThe expression, clinical characteristics, gene function, pathway, and correlation between the infiltration of different immune cells were analyzed using public data. The pan-cancer expression of FBXO45 was assessed using the TIMER2 database. The expression of FBXO45 in different tumor stages and histology subtypes were evaluated using the UALCAN database. The protein-protein interaction (PPI) network was constructed using the STRING database. Immune cell infiltration data were downloaded from the ImmuCellAI database.ResultsThe top 300 genes most positively correlated with FBXO45 were screened into the enrichment analysis. The functional enrichment results showed that FBXO45 was mainly associated with proteasomal protein catabolic process and the regulation of DNA metabolic processing in the biological process (BP) category; spindle, chromosomal region, and focal adhesion in the cellular component category; and ATPase activity and ubiquitin-protein transferase activity terms in the molecular function category. FBXO45 was overexpressed in ESCA and other cancer types. FBXO45 expression was positively associated with the infiltration levels of immunosuppressive cells, such as CD8⁺ (cluster of differentiation 8+) T cells and NK (natural killer cell) cells, in ESCA. MYCBP2 and SKP1 were most associated with FBXO45.ConclusionsOur results suggested that FBXO45 is a potential oncogene in ESCA. Elevated FBXO45 expression indicates a relatively immunosuppressive microenvironment.