Cancers of unknown primary origin (CUP) are characterized by chromosomal instability (CIN) compared to metastasis of know origin

Abstract

Background: Cancers of unknown primary (CUPs) constitute ~5% of all cancers. The tumors have an aggressive biological and clinical behavior. The aim of the present study has been to uncover whether CUPs exhibit distinct molecular features compared to metastases of known origin.

Methods: Employing genome wide transcriptome analysis, Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA), we defined the putative origins of a large series of CUP and how closely related a particular CUP was to corresponding metastases of known origin. LDA predictions were subsequently used to define a universal CUP core set of differentially expressed genes, that by means of gene set enrichment analysis was exploited to depict molecular pathways characterizing CUP.

Results: The analyses show that CUPs are distinct from metastases of known origin. CUPs exhibit inconsistent expression of conventional cancer biomarkers and QDA derived outlier scores show that CUPs are more distantly related to their primary tumor class than corresponding metastases of known origin. Gene set enrichment analysis showed that CUPs display increased expression of genes involved in DNA damage repair and mRNA signatures of chromosome instability (CIN), indicating that CUPs are chromosome unstable compared to metastases of known origin.

Conclusions: CIN may account for the uncommon clinical presentation, chemoresistance and poor outcome in patients with CUP and warrant selective diagnostic strategies and treatment.

Figure 1

Hierachial cluster and principal component analysis of tumor classes. A. Two-way hierachial cluster of 16 tumor classes by the 641 transcript signature. The tumor classes are shown at the top of the cluster and the transcripts are clustered at the left side. B. Principal component analysis (PCA) of primary tumors and known metastases based on the signature. The tumor classes are colored and indicated in association with the corresponding tumor samples.

Figure 2

Patomarkers in primary tumors and CUP. Probeset Ids for 45 common histopatological markers were collected and used to generate a two-way hierarchal cluster with a selection of primary tumors (Panel A) or CUP (Panel B). The variance of the individual markers is shown to the left and the scale is indicated at the top of the clusters. Gene symbols are shown to the right and the different tumor classes are shown below ((Panel A), primary tumors). For the CUP samples (Panel B), groups of markers corresponding to different tumor classes are indicated by the boxes around the gene symbols at the right side of the cluster. The number below the cluster indicated the number of the CUP sample corresponding to the annotation in Table 1.

Figure 3

QDA derived outlier scores in CUP. A) To determine the relationship between prediction error and outlier scores the primary cancers and metastases were divided into ten bins according to the outlier scores and the error rate was calculated for each bin. Each point represents the error rate plotted versus the median outlier score of the bin. The vertical lines show the span of outlier scores within the bins. The plot shows that higher outlier score translates into higher error rate. We modeled the relationship between outlier scores and prediction error by fitting polynomial function to the data points (the orange line), and the function allows us to estimate the expected error rate for new samples of unknown origin, once their outlier scores have been determined. B) Samples from CUP patients tend to have higher outlier scores than other cancer patients. The box plot summarizes the distributions of outlier scores within metastases (MET), primary (PRIM) and CUP tumors. There is a clear tendency for CUP samples to have higher outlier score than metastases and primary cancers. The median outlier score of CUP samples of >1000 suggests the origin prediction error above 30%. On the other hand, most primary cancers and metastases have outlier scores below 800, hence the estimated prediction error from 2-10% (see panel A). Since data for CUP and some primary tumors and metastases were generated at Rigshospitalet, the non-CUP samples from Rigshospitalet are presented as separate group (RH_MET and RH-PRIM), this is to show that the shift in outlier scores was not caused by technical bias. Additionally, the normal, non-cancerous tissue group (NORMAL) is included, and shows the whole range of outlier scores.

Figure 4

Two way hierachial clusters of BRCA1 and SMARCA2 networks in metastases and CUP. (A) The PUJANA_BRCA1_PCC_NETWORK was downloaded from the MSig database (http://www.broadinstitute.org/gsea/msigdb) and used to generate a paired two way hierarchical cluster with known metastases and CUPs. Gene symbols were translated into probe sets and because of the probe set redundancy the data were filtered by a p < 0.001 before clustering. Following filtering 1297 probe sets were included in the clustering. Known metastases are indicated in green and CUP samples are labeled with pink above the cluster. The scale is shown at the right side of the cluster. (B) Two-way cluster of the SHEN_SMARCA2_ TARGETS up- and (C) downregulated transcripts. The sets consists of 360 down- and 430 up-regulated genes that translated into 772 and 1211 probe sets, respectively. The known metastases are indicated in pink and CUP samples are labeled with green below the cluster. The scale is shown at the right side of the cluster.

Figure 5

Signatures of genomic instability in CUPs. Messenger RNA signatures of chromosomal instability (CIN), DNA double-strand break repair, nucleotide excision repair (NER), base excision repair (BER) and mismatch repair (MMR) in CUPs and MOKO were examined with the Broad Institute GSEA v 2 software. The names of the individual signatures, the number of transcripts and the normalized enrichment scores (NES) are indicated. The right panel depicts the transcript ranking on a colometric scale. With the exception of the CIN signature obtained from [10] all gene lists were retrieved from http://www.broadinstitute.org/gsea/msigdb.

Figure 6

Chromosomal instability and outlier scores in CUP. Panel A. Two-way hierachial cluster of the Ferreira_Ewing_Sarcoma_Unstable signature in MOKO and CUPs. MOKO and CUPs are indicated by green and pink labels, respectively. Panel B. Instability scores in Normal tissues, Primary tumors, MOKO and CUPs. The signature of chromosome unstable sarcoma was employed to generate an instability score calculated as the mean of the expression values from the included probe sets of the signature following variance filtering (206 probe sets). Panel C. Linear correlation between outlier scores and instability scores. Primary tumors, metastasis of known origin and CUP are indicated as black, red or green dots, respectively. The lower panel shows the value of the instability scores depicted in a green to red color scale. The p-value of the linear correlation between outlier and instability scores is indicated.