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R语言生物信息如何解读geo数据集的说明，如何知道样本分类， MDA PCa 79（n = 3）n的含义

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Series GSE32967 系列 GSE32967 Query DataSets for GSE32967 GSE32967的查询数据集
Status 状态 Public on Jan 01, 2012
2012年1月1日公开
Title 标题 Modeling lethal prostate cancer variant with small cell carcinoma features [expression profile]
构建具有小细胞癌特征的致命性前列腺癌变模型[表达谱]
Organism 生物体 Homo sapiens 人类智人
Experiment type 实验类型 Expression profiling by array
通过阵列进行表达谱分析

Summary 摘要 Purpose: Small-cell prostate carcinoma (SCPC) morphology predicts for a distinct clinical behavior, resistance to androgen ablation, and frequent but short responses to chemotherapy. The model systems we report reflect the biology of the human disease and can be used to improve our understanding of SCPC and to develop new therapeutic strategies for it.
目的：小型细胞前列腺癌（SCPC）的形态学预示着独特的临床行为、对雄激素去势的抵抗以及频繁但持续时间短的化疗反应。我们报道的模型系统反映了人类疾病的生物学特性，可用于提高我们对SCPC的理解，并为其开发新的治疗策略。

Experimental Design: We developed a set of CRPC xenografts and examined their fidelity to their human tumors of origin. We compared the expression and genomic profiles of SCPC and large cell neuroendocrine carcinoma (LCNEC) xenografts to those of typical prostate adenocarcinoma xenografts and used a panel of 60 human tumors to validate our findings using immunohistochemistry.
实验设计：我们开发了一套CRPC异种移植模型，并检查了它们与其原发人类肿瘤的一致性。我们比较了SCPC和大细胞神经内分泌癌（LCNEC）异种移植模型的表达和基因组特征，与典型前列腺腺癌异种移植模型的特征，并使用60个人类肿瘤的组面板通过免疫组织化学验证我们的发现。

Results: We show that SCPC and LCNEC xenograft models retain high fidelity to their human tumors of origin and are characterized by a marked upregulation of UBE2C and other M-phase cell cycle genes in the absence of AR, retinoblastoma (RB1) and cyclin D1 (CCND1) expression and confirm these findings in a panel of CRPC patients’ samples. In addition, array comparative genomic hybridization of the xenografts showed that the SCPC/LCNEC tumors display more copy number variations than the adenocarcinoma counterparts and that there is amplification of the UBE2C locus and microdeletions of RB1 in a subset of these, but no AR nor CCND1 deletions. Moreover, the AR, RB1, and CCND1 promoters showed no CpG methylation in the SCPC xenografts.
结果：我们表明SCPC和LCNEC异种移植模型与其起源的人类肿瘤保持高度保真性，并且在缺乏AR、视网膜母细胞瘤（RB1）和细胞周期蛋白D1（CCND1）表达的情况下，表现出UBE2C和其他M期细胞周期基因的显著上调，并在一组CRPC患者样本中证实了这些发现。此外，异种移植的阵列比较基因组杂交显示，SCPC/LCNEC肿瘤比腺癌对应物表现出更多的拷贝数变异，并且在这些肿瘤的亚群中存在UBE2C位点的扩增和RB1的微缺失，但没有AR或CCND1的缺失。此外，AR、RB1和CCND1启动子在SCPC异种移植中没有CpG甲基化。

Conclusion: Modeling human prostate cancer with xenografts allows in-depth and detailed studies of its underlying biology. The detailed clinical annotation of the donor tumors enables associations of anticipated relevance to be made. Futures studies in the xenografts will address the functional significance of the findings.
结论：利用异种移植模拟人类前列腺癌，可以深入细致地研究其潜在生物学。对供体肿瘤的详细临床注释使得可以建立预期相关的关联。未来的研究将解决异种移植中发现的生物学功能的含义。

Overall design 整体设计 22 samples were analysed, that included MDA PCa 79 (n = 3), 117-9 (n = 3), 130 (n = 2), 144-4 (n = 4), 144-13 (n = 5), 146-10 (n = 3), 155-2 (n = 1), and 155-12 (n = 1). MDA PCA 79, 117-9 and 130 samples had the pathologic characteristics of prostate adenocarcinoma and were compared against MDA PCA 144-4, 144-13, 146-10 and 155-12 that have the pathologic features of prostate small cell/ large cell neuroendocrine carcinoma
22个样本被分析，包括MDA PCa 79（n = 3）、117-9（n = 3）、130（n = 2）、144-4（n = 4）、144-13（n = 5）、146-10（n = 3）、155-2（n = 1）和155-12（n = 1）。MDA PCA 79、117-9和130样本具有前列腺腺癌的病理特征，并与具有前列腺小细胞/大细胞神经内分泌癌病理特征的MDA PCA 144-4、144-13、146-10和155-12进行比较。

Contributor(s) 贡献者 Aparicio A, Maity S, Tzelepi V, Jing-Fang L, Kleb B, Navone NM, Zhang J, Liang S
Aparicio A, Maity S, Tzelepi V, Jing-Fang L, Kleb B, Navone NM, Zhang J, Liang S
Citation(s) 引用
Tzelepi V, Zhang J, Lu JF, Kleb B et al. Modeling a lethal prostate cancer variant with small-cell carcinoma features. Clin Cancer Res 2012 Feb 1;18(3):666-77. PMID: 22156612
Tzelepi V，张J，卢JF，克莱布B等。模拟具有小细胞癌特征致命性前列腺癌变体。临床癌症研究2012年2月1日；18(3)：666-77。PMID：22156612
Analyze with GEO2R 分析使用 GEO2R
Submission date 提交日期 Oct 13, 2011 2011年10月13日
Last update date 最后更新日期 Mar 25, 2019 2019年3月25日
Contact name 联系人姓名 Jiexin Zhang 张洁新
E-mail(s) 电子邮件 jiexinzhang@mdanderson.org
jiexinzhang@mdanderson.org

Organization name 组织名称 UT MD Anderson Cancer Center
德克萨斯大学安德森癌症中心

Department 部门 Bioinformatics & Computational Biology
生物信息学与计算生物学

Street address 街道地址 1515 Holcombe Blvd
1515 Holcombe Blvd

City 城市 Houston 休斯顿
State/province 省/州 TX 德克萨斯州
ZIP/Postal code ZIP/邮政编码 77030
Country 国家 USA 美国

Platforms (1) 平台（1）
GPL570 GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array
[HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 微阵列
Samples (22) 样本（22）
Less… Less… 少…
GSM816546 GSM816546 prostatecancer_xenograft_MDAPCa79_rep1
前列腺癌异种移植_MDAPCa79_rep1
GSM816547 GSM816547 prostatecancer_xenograft_MDAPCa79_rep2
前列腺癌异种移植_MDAPCa79_rep2
GSM816548 GSM816548 prostatecancer_xenograft_MDAPCa79_rep3
前列腺癌异种移植_MDAPCa79_rep3
GSM816549 GSM816549 prostatecancer_xenograft_MDAPCa117-9_rep1
前列腺癌异种移植_MDAPCa117-9_rep1
GSM816550 GSM816550 prostatecancer_xenograft_MDAPCa117-9_rep2
前列腺癌异种移植_MDAPCa117-9_rep2
GSM816551 GSM816551 prostatecancer_xenograft_MDAPCa117-9_rep3
前列腺癌异种移植_MDAPCa117-9_rep3
GSM816552 GSM816552 prostatecancer_xenograft_MDAPCa130_rep1
前列腺癌异种移植_MDAPCa130_rep1
GSM816553 GSM816553 prostatecancer_xenograft_MDAPCa130_rep2
前列腺癌异种移植_MDAPCa130_rep2
GSM816554 GSM816554 prostatecancer_xenograft_MDAPCa144-4_rep1
前列腺癌异种移植_MDAPCa144-4_rep1
GSM816555 GSM816555 prostatecancer_xenograft_MDAPCa144-4_rep2
前列腺癌异种移植_MDAPCa144-4_rep2
GSM816556 GSM816556 prostatecancer_xenograft_MDAPCa144-4_rep3
前列腺癌异种移植_MDAPCa144-4_rep3
GSM816557 GSM816557 prostatecancer_xenograft_MDAPCa144-4_rep4
前列腺癌异种移植_MDAPCa144-4_rep4
GSM816558 GSM816558 prostatecancer_xenograft_MDAPCa144-4_rep5
prostatecancer_xenograft_MDAPCa144-4_rep5
GSM816559 GSM816559 prostatecancer_xenograft_MDAPCa144-13_rep1
前列腺癌异种移植_MDAPCa144-13_rep1
GSM816560 GSM816560 prostatecancer_xenograft_MDAPCa144-13_rep2
前列腺癌异种移植_MDAPCa144-13_rep2
GSM816561 GSM816561 prostatecancer_xenograft_MDAPCa144-13_rep3
prostatecancer_xenograft_MDAPCa144-13_rep3
GSM816562 GSM816562 prostatecancer_xenograft_MDAPCa144-13_rep4
前列腺癌异种移植_MDAPCa144-13_rep4
GSM816563 GSM816563 prostatecancer_xenograft_MDAPCa146-10_rep1
前列腺癌异种移植_MDAPCa146-10_rep1
GSM816564 GSM816564 prostatecancer_xenograft_MDAPCa146-10_rep2
前列腺癌异种移植_MDAPCa146-10_rep2
GSM816565 GSM816565 prostatecancer_xenograft_MDAPCa146-10_rep3
前列腺癌异种移植_MDAPCa146-10_rep3
GSM816566 GSM816566 prostatecancer_xenograft_MDAPCa155-2_rep1
前列腺癌异种移植MDAPCa155-2_rep1
GSM816567 GSM816567 prostatecancer_xenograft_MDAPCa155-12_rep1
前列腺癌异种移植MDAPCa155-12_rep1
This SubSeries is part of SuperSeries:
本子系列是超级系列的一部分：
GSE33054 GSE33054 Modeling lethal prostate cancer variant with small cell carcinoma features
建模具有小细胞癌特征的致命性前列腺癌变体

解读

GSE32967 数据集样本分类详细说明

根据GEO数据集GSE32967的描述，以下是22个样本的详细分类信息：

样本分组信息

前列腺腺癌（Adenocarcinoma, ADC）组 - 8个样本

这些样本具有典型前列腺腺癌的病理特征：

• MDA PCa 79 (3个技术重复)

• GSM816546: prostatecancer_xenograft_MDAPCa79_rep1

• GSM816547: prostatecancer_xenograft_MDAPCa79_rep2

• GSM816548: prostatecancer_xenograft_MDAPCa79_rep3

• MDA PCa 117-9 (3个技术重复)

• GSM816549: prostatecancer_xenograft_MDAPCa117-9_rep1

• GSM816550: prostatecancer_xenograft_MDAPCa117-9_rep2

• GSM816551: prostatecancer_xenograft_MDAPCa117-9_rep3

• MDA PCa 130 (2个技术重复)

• GSM816552: prostatecancer_xenograft_MDAPCa130_rep1

• GSM816553: prostatecancer_xenograft_MDAPCa130_rep2

神经内分泌前列腺癌（NEPC）组 - 13个样本

这些样本具有小细胞/大细胞神经内分泌癌的病理特征：

• MDA PCa 144-4 (5个技术重复)

• GSM816554: prostatecancer_xenograft_MDAPCa144-4_rep1

• GSM816555: prostatecancer_xenograft_MDAPCa144-4_rep2

• GSM816556: prostatecancer_xenograft_MDAPCa144-4_rep3

• GSM816557: prostatecancer_xenograft_MDAPCa144-4_rep4

• GSM816558: prostatecancer_xenograft_MDAPCa144-4_rep5

• MDA PCa 144-13 (4个技术重复)

• GSM816559: prostatecancer_xenograft_MDAPCa144-13_rep1

• GSM816560: prostatecancer_xenograft_MDAPCa144-13_rep2

• GSM816561: prostatecancer_xenograft_MDAPCa144-13_rep3

• GSM816562: prostatecancer_xenograft_MDAPCa144-13_rep4

• MDA PCa 146-10 (3个技术重复)

• GSM816563: prostatecancer_xenograft_MDAPCa146-10_rep1

• GSM816564: prostatecancer_xenograft_MDAPCa146-10_rep2

• GSM816565: prostatecancer_xenograft_MDAPCa146-10_rep3

• MDA PCa 155-12 (1个样本)

• GSM816567: prostatecancer_xenograft_MDAPCa155-12_rep1

未明确分类样本 - 1个样本

• MDA PCa 155-2 (1个样本)

• GSM816566: prostatecancer_xenograft_MDAPCa155-2_rep1

创建临床信息数据框的R代码

创建样本信息数据框

cli <- data.frame(
sample_id = c(
“GSM816546”, “GSM816547”, “GSM816548”,
“GSM816549”, “GSM816550”, “GSM816551”,
“GSM816552”, “GSM816553”,
“GSM816554”, “GSM816555”, “GSM816556”, “GSM816557”, “GSM816558”,
“GSM816559”, “GSM816560”, “GSM816561”, “GSM816562”,
“GSM816563”, “GSM816564”, “GSM816565”,
“GSM816566”,
“GSM816567”
),
sample_name = c(
“prostatecancer_xenograft_MDAPCa79_rep1”,
“prostatecancer_xenograft_MDAPCa79_rep2”,
“prostatecancer_xenograft_MDAPCa79_rep3”,
“prostatecancer_xenograft_MDAPCa117-9_rep1”,
“prostatecancer_xenograft_MDAPCa117-9_rep2”,
“prostatecancer_xenograft_MDAPCa117-9_rep3”,
“prostatecancer_xenograft_MDAPCa130_rep1”,
“prostatecancer_xenograft_MDAPCa130_rep2”,
“prostatecancer_xenograft_MDAPCa144-4_rep1”,
“prostatecancer_xenograft_MDAPCa144-4_rep2”,
“prostatecancer_xenograft_MDAPCa144-4_rep3”,
“prostatecancer_xenograft_MDAPCa144-4_rep4”,
“prostatecancer_xenograft_MDAPCa144-4_rep5”,
“prostatecancer_xenograft_MDAPCa144-13_rep1”,
“prostatecancer_xenograft_MDAPCa144-13_rep2”,
“prostatecancer_xenograft_MDAPCa144-13_rep3”,
“prostatecancer_xenograft_MDAPCa144-13_rep4”,
“prostatecancer_xenograft_MDAPCa146-10_rep1”,
“prostatecancer_xenograft_MDAPCa146-10_rep2”,
“prostatecancer_xenograft_MDAPCa146-10_rep3”,
“prostatecancer_xenograft_MDAPCa155-2_rep1”,
“prostatecancer_xenograft_MDAPCa155-12_rep1”
),
model = c(
rep(“MDA PCa 79”, 3),
rep(“MDA PCa 117-9”, 3),
rep(“MDA PCa 130”, 2),
rep(“MDA PCa 144-4”, 5),
rep(“MDA PCa 144-13”, 4),
rep(“MDA PCa 146-10”, 3),
“MDA PCa 155-2”,
“MDA PCa 155-12”
),
path_type = c(
rep(“ADC”, 8), # 前8个是腺癌样本
rep(“NEPC”, 13), # 接下来的13个是NEPC样本
“Unknown” # GSM816566 类型未知
),
stringsAsFactors = FALSE
)

将病理类型转换为因子

cli $path_type <- factor(cli$ path_type, levels = c(“ADC”, “NEPC”, “Unknown”))

显示数据框

print(cli)

数据分析建议

技术重复处理：同一模型的多个技术重复可以考虑取平均值或使用线性模型考虑技术重复效应
未知样本处理：GSM816566 (MDA PCa 155-2) 样本类型未知，建议：
• 在初步分析中排除此样本

• 或通过聚类分析确定其与ADC或NEPC的相似性
差异表达分析：比较ADC组（8个样本）与NEPC组（13个样本）的基因表达差异

NEPC特征验证

根据原始研究，NEPC样本应显示以下分子特征：
• AR、RB1和CCND1表达缺失或下调

• UBE2C和其他M期细胞周期基因上调

• 神经内分泌标志物（如CHGA、CHGB、SYP）表达

您可以通过检查这些标志物的表达模式来验证样本分类：

检查NEPC特征基因表达

nepc_signature_genes <- c(“AR”, “RB1”, “CCND1”, “UBE2C”, “CHGA”, “CHGB”, “SYP”)

假设expr是表达矩阵，行名为基因符号

signature_expr <- expr[rownames(expr) %in% nepc_signature_genes, ]

绘制热图

library(pheatmap)
pheatmap(signature_expr,
annotation_col = data.frame(
PathType = cli $path_type,Model = cli$ model,
row.names = cli$sample_id
),
show_colnames = FALSE,
main = “NEPC Signature Gene Expression in GSE32967”)