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. 2021 Mar 16;21(1):282.
doi: 10.1186/s12885-021-07942-1.

A next-generation sequencing-based strategy combining microsatellite instability and tumor mutation burden for comprehensive molecular diagnosis of advanced colorectal cancer

Jian Xiao #  1 , Wenyun Li #  2 , Yan Huang #  3 , Mengli Huang  4 , Shanshan Li  1 , Xiaohui Zhai  1 , Jing Zhao  4 , Chan Gao  4 , Wenzhuan Xie  4 , Hao Qin  5 , Shangli Cai  4 , Yuezong Bai  4 , Ping Lan  6 , Yifeng Zou  7
Affiliations

A next-generation sequencing-based strategy combining microsatellite instability and tumor mutation burden for comprehensive molecular diagnosis of advanced colorectal cancer

Jian Xiao et al. BMC Cancer. .

Abstract

Background: Mismatch repair (MMR)/microsatellite instability (MSI) and tumor mutational burden (TMB) are independent biomarkers that complement each other for predicting immune checkpoint inhibitors (ICIs) efficacy. Here we aim to establish a strategy that integrates MSI and TMB determination for colorectal cancer (CRC) in one single assay.

Methods: Surgical or biopsy specimens retrospectively collected from CRC patients were subjected to NGS analysis. Immunohistochemistry (IHC) and polymerase chain reaction (PCR) were also used to determine MMR/MSI for those having enough tissues. The NGS-MSI method was validated against IHC and PCR. The MSI-high (MSI-H) or microsatellite stable (MSS) groups were further stratified based on tumor mutational burden, followed by validation using the The Cancer Genome Atlas (TCGA) CRC dataset. Immune microenvironment was evaluated for each subgroup be profiling the expression of immune signatures.

Results: Tissues from 430 CRC patients were analyzed using a 381-gene NGS panel. Alterations in KRAS, NRAS, BRAF, and HER2 occurred at a significantly higher incidence among MSI-H tumors than in MSS patients (83.6% vs. 58.4%, p = 0.0003). A subset comprising 98 tumors were tested for MSI/MMR using all three techniques, where NGS proved to be 99.0 and 93.9% concordant with PCR and IHC, respectively. Four of the 7 IHC-PCR discordant cases had low TMB (1.1-8.1 muts/Mb) and were confirmed to have been misdiagnosed by IHC. Intriguingly, 4 of the 66 MSS tumors (as determined by NGS) were defined as TMB-high (TMB-H) using a cut-off of 29 mut/Mb. Likewise, 15 of the 456 MSS tumors in the TCGA CRC cohort were also TMB-H with a cut-off of 9 muts/Mb. Expression of immune signatures across subgroups (MSS-TMB-H, MSI-H-TMB-H, and MSS-TMB-L) confirmed that the microenvironment of the MSS-TMB-H tumors was similar to that of the MSI-H-TMB-H tumors, but significantly more immune-responsive than that of the MSS-TMB-L tumors, indicating that MSI combined with TMB may be more precise than MSI alone for immune microenvironment prediction.

Conclusion: This study demonstrated that NGS panel-based method is both robust and tissue-efficient for comprehensive molecular diagnosis of CRC. It also underscores the importance of combining MSI and TMB information for discerning patients with different microenvironment.

Keywords: Colorectal cancer; Immune checkpoint inhibitor; Microsatellite instability; Next generation sequencing; Tumor mutation burden.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Fig. 1
Fig. 1
Patient Flow. Tissue samples were collected from 430 eligible CRC patients and subjected to genomic profiling using NGS. Of the 430 samples, 98 were also examined for MMR/MSI status using IHC and PCR. NGS MSI method was validated against IHC and PCR. The distribution of TMB between MSS and MSI-H tumors were also investigated using both the 98-patient cohort and the TCGA CRC cohort
Fig. 2
Fig. 2
Genomic landscape of Chinese CRC patients using NGS. a Genomic landscape of 430 patients. The panel on the top shows the effects of the mutations at translational level while the panel at the bottom shows the MSI status, gender and age of each patient. The top 11 most frequently mutated genes are shown on the left. b Genomic landscape of the 98 tumors that were analyzed for MMR/MSI by IHC, PCR, and NGS. The bottom panel illustrates the MMR or MSI detection results for each patient
Fig. 3
Fig. 3
Concordance among IHC, PCR, and NGS for MMR/MSI detection. a A Venn diagram showing the overlap among the dMMR cases by IHC, MSI-H cases by PCR, and the MSI-H cases by NGS; b An Upset plot shows the detail of he consistent diagnosis result between NGS and conventional assays
Fig. 4
Fig. 4
Correlation between TMB and MSI statuses. a TMB distribution across subgroups stratified according to MMR and MSI statuses determined using IHC and PCR; b TMB distribution across subgroups where POLE-mutated tumors were removed from their original groups and analyzed separately; c) Distribution of various MMR-IHC/MSI-PCR statuses between TMB-H versus TMB-L subsets as defined using a cut-off of 29 muts/MB
Fig. 5
Fig. 5
Expression profiles of immune signature genes in subgroups divided according to MSI (by PCR) and TMB (by NGS) statuses using RNAseq data of the TCGA CRC cohort. a Expression profiles of 19 immune activation-related genes; b Expression profiles of 7 immune checkpoint genes
See this image and copyright information in PMC

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