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在比较同一个体内的胰腺癌样本时,使用反卷积方法对批量RNA测序和估计的细胞类型比例进行的变异分析。

Variation in bulk RNA-seq and estimated cell type proportion using deconvolution when comparing pancreatic cancer samples within the same individual.

作者信息

Jansen Rick J, Munro Sarah A, Antwi Samuel O, Rabe Kari G, Sicotte Hugues

机构信息

Masonic Cancer Center, University of Minnesota, Minneapolis, MN.

Minnesota Supercomputing Institute, University of Minnesota, Minneapolis, MN.

出版信息

medRxiv. 2025 May 6:2025.05.05.25326976. doi: 10.1101/2025.05.05.25326976.

Abstract

INTRODUCTION

There is great promise in using genomic data to inform individual cancer treatment plans. Assessing intratumor genetic heterogeneity, studies have shown it may be possible to target biopsies to tumor subclones driving disease progression or treatment resistance. Here, we explore if the interpretation of tumor gene expression analysis varies across two specimens from the same patient.

METHODS

We performed bulk RNA-seq using FFPE samples from 16 patients who also had a previous separate bulk RNA-seq performed and deposited in TCGA. We used three different deconvolution methods to compare cell type proportions for these paired data. We normalized study-specific gene expression values per gene by calculating transcripts per million and adjusted for batch effect across study to compare median expression values. We also compared the reliability of gene expression measurements. We selected , and , as the most mutated genes in pancreatic cancer, and , and as these tend to be enriched in pancreatic cancer compared with adjacent normal tissue.

RESULTS

We found that average cell type proportion varied the most between studies (i.e., samples for each patient) for NK and macrophages (using adjusted p-value 0.05/21=0.002). For the differential expression analysis, we did not observe significant differences in average expression of any of the selected genes. We observed substantial (kappa=0.75) for only with low to moderate concordance (i.e., Kappa value 0.25-0.5) when using a median cut point for the remaining 8 genes across the two studies.

DISCUSSION

Together, the findings suggest that more than one tumor sample may be needed for effective treatment planning. Any potential difference in observed expression values across the paired samples could be related to the different cell type proportions across the samples. The sample size was small, and each study used different sequencing technologies, so any interpretation should be confirmed with additional studies.

摘要

引言

利用基因组数据为个体癌症治疗方案提供依据具有巨大潜力。评估肿瘤内基因异质性的研究表明,有可能针对驱动疾病进展或治疗耐药的肿瘤亚克隆进行活检。在此,我们探讨同一患者的两个样本中肿瘤基因表达分析的解读是否存在差异。

方法

我们使用了16名患者的福尔马林固定石蜡包埋(FFPE)样本进行批量RNA测序,这些患者之前还进行过一次单独的批量RNA测序并已存入TCGA数据库。我们使用三种不同的反卷积方法来比较这些配对数据的细胞类型比例。我们通过计算每百万转录本对每个基因的研究特异性基因表达值进行归一化,并针对研究间的批次效应进行调整,以比较中位数表达值。我们还比较了基因表达测量的可靠性。我们选择胰腺癌中突变最多的基因 、 和 ,以及与相邻正常组织相比在胰腺癌中往往富集的 、 和 。

结果

我们发现,自然杀伤细胞(NK)和巨噬细胞在不同研究(即每位患者的样本)之间平均细胞类型比例差异最大(使用调整后的p值0.05/21 = 0.002)。对于差异表达分析,我们未观察到任何选定基因的平均表达存在显著差异。在两项研究中,对于其余8个基因使用中位数切点时,我们仅观察到 具有较高一致性(kappa = 0.75),而其他基因的一致性较低至中等(即kappa值为0.25 - 0.5)。

讨论

这些发现共同表明,可能需要不止一个肿瘤样本才能进行有效的治疗规划。配对样本间观察到的表达值的任何潜在差异可能与样本间不同的细胞类型比例有关。样本量较小,且每项研究使用的测序技术不同,因此任何解读都应通过额外的研究来证实。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d8bf/12083591/85eea1b444e7/nihpp-2025.05.05.25326976v1-f0001.jpg

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