Cancer Res Treat.  2020 Jul;52(3):764-778. 10.4143/crt.2020.044.

Clinical Implication of Concordant or Discordant Genomic Profiling between Primary and Matched Metastatic Tissues in Patients with Colorectal Cancer

• Choi JY
• Choi S
• Lee M
• Park YS
• Sung JS
• Chang WJ
• Kim JW
• Choi YJ
• Kim J
• Kim DS
• Lee SH
• Seok J
• Park KH
• Kim SH
• Kim YH

• KMID: 2504458
• DOI: http://doi.org/10.4143/crt.2020.044

Abstract

Purpose
The purpose of this study was to identify the concordant or discordant genomic profiling between primary and matched metastatic tumors in patients with colorectal cancer (CRC) and to explore the clinical implication.
Materials and Methods
Surgical samples of primary and matched metastatic tissues from 158 patients (335 samples) with CRC at Korea University Anam Hospital were evaluated using the Ion AmpliSeq Cancer Hotspot Panel. We compared genetic variants and classified them as concordant, primary-specific, and metastasis-specific variants. We used a combination of principal components analysis and clustering to find genomic groups. Kaplan-Meier curves were used to appraise survival between genomic groups. We used machine learning to confirm the correlation between genetic variants and metastatic sites.
Results
A total of 282 types of deleterious non-synonymous variants were selected for analysis. Of a total of 897 variants, an average of 40% was discordant. Three genomic groups were yielded based on the genomic discrepancy patterns. Overall survival differed significantly between the genomic groups. The poorest group had the highest proportion of concordant KRAS G12V and additional metastasis-specific SMAD4. Correlation analysis between genetic variants and metastatic sites suggested that concordant KRAS mutations would have more disseminated metastases.
Conclusion
Driver gene mutations were mostly concordant; however, discordant or metastasis-specific mutations were present. Clinically, the concordant driver genetic changes with additional metastasis-specific variants can predict poor prognosis for patients with CRC.

Keyword

Colorectal neoplasms; Genomics; Neoplasm metastasis; Principal component analysis; Survival

Figure

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  Fig. 1. Flow chart for data set.

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  Fig. 2. Genomic profiling between primary tumors (P) and matched metastases (M1). (A) Frequencies of deleterious non-synonymous variants between primary and metastatic tumors compared with the Cancer Genome Atlas (TCGA) data. (B) The schematic concept of concordant, primary-specific, and metastasis-specific variants and schematic illustration of mutational landscape. (C) Comparison of the percentage of mutations identified as primary-specific, metastasis-specific, or concordant between primary and matched metastases. Twelve patients who did not have deleterious non-synonymous variants were excluded from the comparison. The distribution of number of types of variants per patient is shown at the bottom. (D) Frequencies based on the different protein changes of key genes and comparison with TCGA data. X, variant count (number of variants); Y, each position. Different protein changes represent different variant positions. TP53 shows only the top 30 variant positions. The highest frequencies of the top three variant’s positions compared to the TCGA data are shown at the bottom of each graph. The data were calculated based on 158 primary tissue samples. TCGA data were obtained from 212 tissue samples.

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  Fig. 3. Genomic grouping and survival analysis. (A) Three genomic groups were determined using clustering with PC1, PC2, and PC3; group 1 (117, 74.0%, blue), group 2 (24, 15.2%, red), and group 3 (17, 10.8%, green). (B) Overall survival (OS) data. The OS of group 3 was significantly shorter than that of group 1. (C) Genetic frequency between groups and the concordant, primary-specific, and metastasis-specific genes. The frequency of the top 20 concordant (blue), primary-specific (red), and metastasis-specific (green) genes. X denotes each gene, Y denotes percentage of patients with the mutation in each group, and labels denote the number of patients. (D) The proportion of variants of concordant KRAS and metastasis-specific SMAD4 between genomic groups.

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  Fig. 4. Correlation between paired genes (concordant, primary-specific, and metastasis-specific) and metastatic sites (liver only, lung only, both liver and lung, and others). (A) Chi-square test. Blue indicates p < 0.05. (B) Random forest model. In the random forest and lasso regression model, the top five genes with a high coefficient were selected. Blue indicates genes that were significant in the chi-squared test.

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  Fig. 5. Mutations between primary and metastatic tumors for a subgroup of 19 patients with M1 and M2 tumors. (A) Progression type according to synchronous and metachronous metastasis. (B) Heterogeneity according to synchronous and metachronous metastasis. (C) Variant changes of key genes in colorectal cancer between P, M1, and M2.

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