SHCBP1:乳腺癌治疗候选靶点和潜在预后标志物

探讨SHCBP1在乳腺癌及其不同亚型中的表达特征和预后价值。利用Oncomine, bc-GenExMiner v4.2, Kaplan-Meier plotter, GSE41994及STRING数据库分析乳腺癌病人SHCBP1的mRNA表达水平及其与乳腺癌患者生存率的相关性等。结果:(1)乳腺癌组织中SHCBP1的mRNA水平明显高于正常组织样本,但不同分子亚型的乳腺癌患者中SHCBP1的表达水平不同;(2)SHCBP1表达升高可导致Luminal A亚型更短的无转移生存期(Distant metastasis-free survival,DMFS)和无病生存期(Disease-free survival, DFS);(3)在雌激素受体阳性(ER+)、孕酮受体阳性(PR+)亚型、仅接受辅助化疗、仅接受辅助化疗的ER(+)与接受包括或排除内分泌治疗乳腺癌患者中,SHCBP1表达升高则无复发生存率(Relapse-free survival,RFS)显著缩短;(4)SHCBP1和CDC45 mRNA表达水平之间呈正相关,并可能与KIF23等10种蛋白相互作用。结论:SHCBP1是一种很有前景的乳腺癌预后指标和潜在的治疗靶点。     

Comparative expression analysis of four breast cancer subtypes versus matched normal tissue from the same patients

Gene expression studies have been widely used in an effort to identify signatures that can predict clinical progression of cancer. In this study we focused instead on identifying gene expression differences between breast tumors and adjacent normal tissue, and between different subtypes of tumor classified by clinical marker status. We have collected a set of 20 breast cancer tissues, matched with the adjacent pathologically normal tissue from the same patient. The cancer samples representing each subtype of breast cancer identified by estrogen receptor ER(+/-) and Her2(+/-) status and divided into four subgroups (ER+/Her2+, ER+/Her2-, ER-/Her2+, and ER-/Her2-) were hybridized on Affymetrix HG-133 Plus 2.0 microarrays. By comparing cancer samples with their matched normal controls we have identified 3537 overall differentially expressed genes using data analysis methods from Bioconductor. When we looked at the genes in common of the four subgroups, we found 151 regulated genes, some of them encoding known targets for breast cancer treatment. Unique genes in the four subgroups instead suggested gene regulation dependent on the ER/Her2 markers selection. In conclusion, the results indicate that microarray studies using robust analysis of matched tumor and normal samples from the same patients can be used to identify genes differentially expressed in breast cancer tumor subtypes even when small numbers of samples are considered and can further elucidate molecular features of breast cancer.     

Prognostic correlations with the microbiome of breast cancer subtypes

Alterations to the natural microbiome are linked to different diseases, and the presence or absence of specific microbes is directly related to disease outcomes. We performed a comprehensive analysis with unique cohorts of the four subtypes of breast cancer (BC) characterized by their microbial signatures, using a pan-pathogen microarray strategy. The signature (includes viruses, bacteria, fungi, and parasites) of each tumor subtype was correlated with clinical data to identify microbes with prognostic potential. The subtypes of BC had specific viromes and microbiomes, with ER+ and TN tumors showing the most and least diverse microbiome, respectively. The specific microbial signatures allowed discrimination between different BC subtypes. Furthermore, we demonstrated correlations between the presence and absence of specific microbes in BC subtypes with the clinical outcomes. This study provides a comprehensive map of the oncobiome of BC subtypes, with insights into disease prognosis that can be critical for precision therapeutic intervention strategies.Subject terms: Cancer, Prognostic markers     

Folate Receptor-α (FOLR1) Expression and Function in Triple Negative Tumors

Folate receptor alpha (FOLR1) has been identified as a potential prognostic and therapeutic target in a number of cancers. A correlation has been shown between intense overexpression of FOLR1 in breast tumors and poor prognosis, yet there is limited examination of the distribution of FOLR1 across clinically relevant breast cancer subtypes. To explore this further, we used RNA-seq data from multiple patient cohorts to analyze the distribution of FOLR1 mRNA across breast cancer subtypes comprised of estrogen receptor positive (ER+), human epidermal growth factor receptor positive (HER2+), and triple negative (TNBC) tumors. FOLR1 expression varied within breast tumor subtypes; triple negative/basal tumors were significantly associated with increased expression of FOLR1 mRNA, compared to ER+ and HER2+ tumors. However, subsets of high level FOLR1 expressing tumors were observed in all clinical subtypes. These observations were supported by immunohistochemical analysis of tissue microarrays, with the largest number of 3+ positive tumors and highest H-scores of any subtype represented by triple negatives, and lowest by ER+ tumors. FOLR1 expression did not correlate to common clinicopathological parameters such as tumor stage and nodal status. To delineate the importance of FOLR1 overexpression in triple negative cancers, RNA-interference was used to deplete FOLR1 in overexpressing triple negative cell breast lines. Loss of FOLR1 resulted in growth inhibition, whereas FOLR1 overexpression promoted folate uptake and growth advantage in low folate conditions. Taken together, our data suggests patients with triple negative cancers expressing high FOLR1 expression represent an important population of patients that may benefit from targeted anti-FOLR1 therapy. This may prove particularly helpful for a large number of patients who would typically be classified as triple negative and who to this point have been left without any targeted treatment options.     

乳腺癌中丝／苏氨酸蛋白激酶Plk1mRNA的表达及其预后价值

目的：检测乳腺癌细胞和组织中丝／苏氨酸蛋白激酶Plk1基因mRNA的表达情况并分析其预后价值。方法：应用半定量RT-PCR方法分析3株人乳腺癌细胞和1株正常乳腺上皮细胞中Plk1基因mRNA的表达水平。同时分析84例乳腺癌及对应的癌旁正常乳腺上皮组织中Plk1mRNA的表达水平。统计学分析Plk1mRNA表达水平与乳腺癌患者年龄、肿瘤大小、组织分化程度、淋巴结转移状况、TNM分期和雌激素受体（ER）等临床病理参数之间的关系,以及与预后之间的关系。结果：Plk1基因mRNA在乳腺癌细胞中的相对表达水平显著高于其在正常乳腺上皮细胞中的相对表达水平（P值均小于〈0．05）。另外,Plk1mRNA在乳腺癌组织中平均表达水平（0．88±0．18）显著高于其在癌旁正常乳腺上皮组织中平均表达水平（0．22±0．10;P〈0．01）。统计学分析结果袁明：Plk1mRNA表达水平和乳腺癌患者的淋巴结转移状况及TNM分期密切相关（P=0．009或0．007）。Kaplan—Meier生存曲线分析结果表明：高Plk1mRNA表达水平的乳腺癌患者的5年无疾病进展率及总体生存率均显著低于低Plk1mRNA表达水平的乳腺癌患者（P=0．0026及0．0136）。COX模型的多因素预后分析结果表明：Plk1基因mRNA表达水平是乳腺癌患者的一个独立的预后因素（HR=4．764,95％CI：1．341-6．123,P=0．0025）。结论：Plk1在乳腺癌组织呈现高表达水平,其mRNA表达水平有望成为临床乳腺癌患者一个重要的预后判断分子指标。     

ER/PR阳性和阴性乳腺癌的定量蛋白质组学和生物信息学比较研究

目的:建立雌/孕激素受体(ER/PR)阴性和阳性乳腺癌的蛋白质表达谱,寻找ER/PR阴性和阳性乳腺癌中差异表达蛋白,为乳腺癌患者提供新的预后预测指标和治疗新靶点。方法:应用蛋白质组学i TRAQ技术建立ER/PR阳性和阴性乳腺癌的蛋白质差异表达谱,鉴定两组乳腺癌的差异表达蛋白,对部分差异表达蛋白进行生物信息学分析,包括蛋白功能注释和分类GO分析和KEGG通路分析。结果:应用i TRAQ蛋白质组学技术对乳腺癌组织进行了蛋白组学分析,鉴定出ER/PR阳性和阴性组间有差异表达的蛋白4999种,以ER/PR阳性:ER/PR阴性≥3为上调标准,确定ER/PR阳性组上调蛋白101种。以ER/PR阳性:ER/PR阴性≤0.5为下调标准,ER/PR阳性组下调蛋白122种。GO分析结果显示ER/PR受体阴性和阳性乳腺癌的差异表达蛋白的分子功能、生物过程、细胞定位较为复杂,并且在上调蛋白和下调蛋白上存在分布差异。KEGG通路分析发现部分差异表达蛋白涉及201条信号通路。结论:ER/PR阳性和阴性乳腺癌间存在差异表达蛋白,这些蛋白涉及复杂的分子功能、生物过程和信号通路。     

Characterization of the expression of HTm4 (MS4A3), a cell cycle regulator,in human peripheral blood cells and normal and malignant tissues

HTm4 (MS4A3) is a member of a family of four‐transmembrane proteins designated MS4A. MS4A proteins fulfil diverse functions, acting as cell surface signalling molecules and intracellular adapter proteins. Early reports demonstrated that HTm4 is largely restricted to the haematopoietic lineage, and is involved in cell cycle control, via a regulatory interaction with the kinase‐associated phosphatase, cyclin A and cyclin‐dependent kinase 2 (CDK2). Here we describe the expression pattern of HTm4 in peripheral blood cells using gene expression microarray technology, and in normal foetal and adult human tissues, as well as adult human cancers, using tissue microarray technology. Using oligonucleotide microarrays to evaluate HTm4 mRNA, all peripheral blood cell types demonstrated very low levels of HTm4 expression; however, HTm4 expression was greatest in basophils compared to eosinophils, which showed lower levels of HTm4 expression. Very weak HTm4 expression is found in monocytes, granulocytes and B cells, but not in T cells, by lineage specific haematopoietic cell flow cytometry analysis. Interestingly, phytohaemagglutinin stimulation increases HTm4 protein expression in peripheral blood CD4‐T‐lymphocytes over nearly undetectable baseline levels. Western blotting and immunohistochemical studies show strong HTm4 expression in the developing haematopoietic cells of human foetal liver. Immunohistochemical studies on normal tissue microarrays confirmed HTm4 expression in a subset of leucocytes in nodal, splenic tissues and thymic tissue, and weak staining in small numbers of cell types in non‐haematopoietic tissues. Human foetal brain specimens from 19 to 31 gestational weeks showed that the strongest‐staining cells are ventricular zone cells and the earliest‐born, earliest‐differentiating ‘pioneer’ neurons in the cortical plate, Cajal‐Retzius and, to a lesser extent, subplate‐like neurons. Malignant tissue microarray analysis showed HTm4 expression in a wide variety of adenocarcinomas, including breast, prostate and ovarian. These findings warrant the further study of the role of HTm4 in the cell cycle of both haematopoietic and tumour cells.     

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.     

Kinase–substrate Edge Biomarkers Provide A More Accurate Prognostic Prediction in ER-negative Breast Cancer

The estrogen receptor (ER)-negative breast cancer subtype is aggressive with few treatment options available. To identify specific prognostic factors for ER-negative breast cancer, this study included 705,729 and 1034 breast invasive cancer patients from the Surveillance, Epidemiology, and End Results (SEER) and The Cancer Genome Atlas (TCGA) databases, respectively. To identify key differential kinase–substrate node and edge biomarkers between ER-negative and ER-positive breast cancer patients, we adopted a network-based method using correlation coefficients between molecular pairs in the kinase regulatory network. Integrated analysis of the clinical and molecular data revealed the significant prognostic power of kinase–substrate node and edge features for both subtypes of breast cancer. Two promising kinase–substrate edge features, CSNK1A1–NFATC3 and SRC–OCLN, were identified for more accurate prognostic prediction in ER-negative breast cancer patients.     

Elevation of SIPL1 (SHARPIN) Increases Breast Cancer Risk

SIPL1 (Sharpin) or Sharpin plays a role in tumorigenesis. However, its involvement in breast cancer tumorigenesis remains largely unknown. To investigate this issue, we have systemically analyzed SIPL1 gene amplification and expression data available from Oncomine datasets, which were derived from 17 studies and contained approximately 20,000 genes, 3438 breast cancer cases, and 228 normal individuals. We found a SIPL1 gene amplification in invasive ductal breast cancers compared to normal breast tissues and a significant elevation of SIPL1 mRNA in breast cancers in comparison to non-tumor breast tissues. These results collectively reveal that increases in SIPL1 expression occur during breast cancer tumorigenesis. To further investigate this association, we observed increases in the SIPL1 gene and mRNA in the breast cancer subtypes of estrogen receptor (ER)+, progesterone receptor (PR)+, HER2+, or triple negative. Additionally, a gain of the SIPL1 gene correlated with breast cancer grade and the levels of SIPL1 mRNA associated with both breast cancer stages and grades. Elevation of SIPL1 gene copy and mRNA is linked to a decrease in patient survival, especially for those with PR+, ER+, or HER2- breast cancers. These results are supported by our analysis of SIPL1 protein expression using a tissue microarray containing 224 breast cancer cases, in which higher levels of SIPL1 relate to ER+ and PR+ tumors and AKT activation. Furthermore, we were able to show that progesterone significantly reduced SIPL1 mRNA and protein expression in MCF7 cells. As progesterone enhances breast cancer tumorigenesis in a context dependent manner, inhibition of SIPL1 expression may contribute to progesterone''s non-tumorigenic function which might be countered by SIPL1 upregulation. Taken together, we demonstrate a positive correlation of SIPL1 with BC tumorigenesis.     

Quantitative proteomics study of breast cancer cell lines isolated from a single patient: Discovery of TIMM17A as a marker for breast cancer

The proteins involved in breast cancer initiation and progression are still largely elusive. To gain insights into these processes, we conducted quantitative proteomic analyses with 21T series of breast cell lines, which include a normal, primary tumor and a metastatic tumor that were isolated from a single patient. Stable isotope labeling of amino acid in cell culture followed by LC‐MS/MS analysis was performed and deregulated proteins were identified using statistical analysis. Gene ontology analysis revealed that proteins involved in metabolic processes were the most deregulated in both tumorigenesis and metastasis. Interaction network analysis indicated that ERBB2 signaling played a critical role in tumorigenesis. In addition to known markers such as ERBB2 and E‐cadherin, novel markers, including BRP44L, MTHFD2 and TIMM17A, were found to be overexpressed in 21T breast cancer cells and verified in additional breast cell lines. mRNA expression analysis as well as immunohistochemistry analysis in breast cancer tissues indicated that expression level of TIMM17A was directly correlated with tumor progression, and survival analysis suggested that TIMM17A was a powerful prognosis factor in breast cancer. More interestingly, overexpression and siRNA knockdown experiments indicated an oncogenic activity of TIMM17A in breast cancer. Our study provides a list of potential novel markers for breast cancer tumorigenesis and metastasis using a unique cell model. Further studies on TIMM17A as well as other markers on the list may reveal mechanisms that result in more effective therapeutics for cancer treatment.     

Systematic profiling of invasion-related gene signature predicts prognostic features of lung adenocarcinoma

Due to the high heterogeneity of lung adenocarcinoma (LUAD), molecular subtype based on gene expression profiles is of great significance for diagnosis and prognosis prediction in patients with LUAD. Invasion-related genes were obtained from the CancerSEA database, and LUAD expression profiles were downloaded from The Cancer Genome Atlas. The ConsensusClusterPlus was used to obtain molecular subtypes based on invasion-related genes. The limma software package was used to identify differentially expressed genes (DEGs). A multi-gene risk model was constructed by Lasso-Cox analysis. A nomogram was also constructed based on risk scores and meaningful clinical features. 3 subtypes (C1, C2 and C3) based on the expression of 97 invasion-related genes were obtained. C3 had the worst prognosis. A total of 669 DEGs were identified among the subtypes. Pathway enrichment analysis results showed that the DEGs were mainly enriched in the cell cycle, DNA replication, the p53 signalling pathway and other tumour-related pathways. A 5-gene signature (KRT6A, MELTF, IRX5, MS4A1 and CRTAC1) was identified by using Lasso-Cox analysis. The training, validation and external independent cohorts proved that the model was robust and had better prediction ability than other lung cancer models. The gene expression results showed that the expression levels of MS4A1 and KRT6A in tumour tissues were higher than in normal tissues, while CRTAC1 expression in tumour tissues was lower than in normal tissues. The 5-gene signature prognostic stratification system based on invasion-related genes could be used to assess prognostic risk in patients with LUAD.     

Caspase-7在不同分子亚型乳腺癌中的表达及临床病理意义

目的:探讨含半胱氨酸的天冬氨酸蛋白水解酶(cysteinyl aspartate specific proteinase,Caspase-7,CASP7)在不同分子亚型乳腺癌中的表达及临床病理意义。方法:应用免疫组织化学方法检测CASP7在254例乳腺癌组织中的表达,重点观察该蛋白在不同分子亚型乳腺癌组织中表达的差异及与临床病理指标间的相关性,Kaplan-Meier法分析该蛋白表达与乳腺癌患者预后之间的关系。结果:Caspase-7在ER+PR+HER2+、ER+PR+HER2-、ER-PR-HER2+、ER-PR-HER2-中阳性表达率分别为37.2%、60.3%、17.0%、40.0%,在ER+/PR+/HER2-型中表达最高,在ER-/PR-/HER2+型中表达低,四组总体表达差异具有统计学意义(P0.001)。与ER、PR表达(均为r=0.194,P=0.002)呈显著正相关,与HER2表达2(r=-0.224,P0.001)呈显著负相关。在ER-PR-HER2+型乳腺癌中,CASP7的表达与肿瘤大小呈负相关(P=0.028),且与术后纵膈转移和脑转移呈正相关(均为r=0.307,P=0.026)。CASP7的表达与乳腺癌患者生存无显著相关性。结论:CASP7在不同分子亚型乳腺癌中表达存在差异,并且可能作为乳腺癌分子分型和预后预测的候选标记物。     

SWATH‐based proteomics reveals processes associated with immune evasion and metastasis in poor prognosis colorectal tumours

Newly emerged proteomic methodologies, particularly data‐independent acquisition (DIA) analysis–related approaches, would improve current gene expression–based classifications of colorectal cancer (CRC). Therefore, this study was aimed to identify protein expression signatures using SWATH‐MS DIA and targeted data extraction, to aid in the classification of molecular subtypes of CRC and advance in the diagnosis and development of new drugs. For this purpose, 40 human CRC samples and 7 samples of healthy tissue were subjected to proteomic and bioinformatic analysis. The proteomic analysis identified three different molecular CRC subtypes: P1, P2 and P3. Significantly, P3 subtype showed high agreement with the mesenchymal/stem‐like subtype defined by gene expression signatures and characterized by poor prognosis and survival. The P3 subtype was characterized by decreased expression of ribosomal proteins, the spliceosome, and histone deacetylase 2, as well as increased expression of osteopontin, SERPINA 1 and SERPINA 3, and proteins involved in wound healing, acute inflammation and complement pathway. This was also confirmed by immunodetection and gene expression analyses. Our results show that these tumours are characterized by altered expression of proteins involved in biological processes associated with immune evasion and metastasis, suggesting new therapeutic options in the treatment of this aggressive type of CRC.     

Expression of insulin-like growth factor binding proteins in human breast cancer correlates with estrogen receptor status

The insulin-like growth factors (IGFs) have been implicated in the growth regulation of human breast cancer. Since the IGFs are associated with specific binding proteins (IGFBPs) which may modulate receptor/ligand interactions, production of IGFBPs by breast cancer cells could alter their IGF-dependent growth. This study examined the expression of IGFBPs 4, 5, and 6 in eight breast cancer cell lines (BCCLs) using ribonuclease (RNase) protection assays. IGFBP-4 mRNA was detected in all BCCLs studied. IGFBP-5 expression was higher in estrogen receptor (ER) positive cells, while IGFBP-6 mRNA was detected in only two ER negative BCCLs. We also found that E₂ treatment enhanced the expression of IGFBPs 2, 4, and 5 in T47-D cells. We next studied IGFBP mRNA expression in 40 primary breast tumors. All tumors expressed mRNA for IGFBPs 2–6 but none expressed IGFBP-1 message. IGFBP-3 expression was higher in ER negative tumors, while that of IGFBP-4 and -5 was higher in ER positive specimens. These differences were statistically significant (P < .05). Ligand blot analysis of tumor extracts confirmed the presence of IGFBPs in breast cancer tissues. Thus, differential IGFBP expression in ER positive and negative tumors suggests an important role for this protein in breast cancer biology.