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. 2021 Jul;10(13):4375-4386.
doi: 10.1002/cam4.3987. Epub 2021 May 26.

Comparative genomic signatures in young and old Chinese patients with colorectal cancer

Fei Wang  1 , Huanqing Cheng  2 , Xiao Zhang  3 , Lina Shan  1 , Bingjun Bai  1 , Kangke Chen  1   4 , Feng Lou  5 , Shanbo Cao  5 , Huina Wang  5 , Sheng Dai  1
Affiliations

Comparative genomic signatures in young and old Chinese patients with colorectal cancer

Fei Wang et al. Cancer Med. 2021 Jul.

Abstract

Background: Occurrence at a young age is known to be associated with unique clinical features in colorectal cancer (CRC). However, the genomic differences between young and old patients with CRC are not well elucidated and, to the best of our knowledge, have never been investigated in a Chinese population.

Methods: Tumor tissue samples from 29 young (age ≤50 years) and 46 old (age >50 years) patients with CRC were collected. Targeted sequencing of 808 cancer-related genes was conducted to characterize the genomic landscape for Chinese CRC.

Results: Overall, mutational profiles exhibited notable differences between the two groups. In particular, APC and PIK3CA mutations were more frequently observed in old patients (p = 0.009 and p = 0.012, respectively), while SMAD4 mutations tended to occur in young patients (p = 0.054). Mutation loci distributions of KRAS in the young cohort differed from those in the old cohort, and a higher frequency of KRAS codon 12 mutations was potentially associated with a young age (p = 0.076). The frequencies of clinically actionable alterations were analyzed by defined age categories, which unveiled a distinctive targeted genomic profile in the young group. Furthermore, among patients with mismatch repair-proficient (pMMR) CRC, tumor mutation burden (TMB) was positively correlated with age (Pearson's r = 0.306, p = 0.011), and genomic alterations associated with high TMB in young patients differentiated from those in old patients.

Conclusions: These findings revealed different molecular characterization between young and old Chinese patients with CRC, which may provide novel insights for the personalized treatment of CRC.

Keywords: Chinese; colorectal cancer; genomic landscape; old; young.

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Conflict of interest statement

H.N.W, L.F, and S.B.C are employees of Acornmed Biotechnology Co., Ltd. The other authors have declared that no competing interest exists.

Figures

FIGURE 1
FIGURE 1
Landscape of genomic alterations among 75 Chinese patients with colorectal cancer (CRC). Genetic mutations were identified by targeted next‐generation sequencing of the tumor tissues of patients with CRC. Abbreviations: Multiple mutations, mutant numbers more than 2
FIGURE 2
FIGURE 2
Comprehensive analysis of the associations between genomic mutations of CRC. A, Correlation analysis between mutant allele frequencies in TP53, APC, and KRAS. B, A pairwise association plot for mutant genes in CRC
FIGURE 3
FIGURE 3
Genomic profiling between young and old patients with CRC. A, Genetic mutations in the young CRC group. B, Genetic mutations in the old CRC group
FIGURE 4
FIGURE 4
Distributions of representative genomic alterations between young and old groups with CRC. The comparative analysis of frequencies of APC (A), PIK3CA (B), SMAD4 (C), and KRAS (D) mutations between young and old patients. Abbreviations: WT, wild type
FIGURE 5
FIGURE 5
Overview of targeted genomic profiles between young and old groups with CRC. A, The targeted genomic profile in the young patients with CRC. B, The targeted genomic profile in the old patients with CRC. C, The comparative analysis of prevalence of targeted genomic alterations between the young and old patients
FIGURE 6
FIGURE 6
Comprehensive analysis of the composition of PI3K and DDR signaling pathways between young and old groups with CRC. A, Comparative analysis of the composition of the PI3K signaling pathway between young and old patients. B, Comparative analysis of the composition of the DDR signaling pathway between young and old patients
FIGURE 7
FIGURE 7
Association between TMB and age in CRC. A, Correlation analysis between TMB and age in pMMR patients with CRC. B, Comparison of TMB between young and old patients with CRC. Abbreviations: TMB, tumor mutation burden; pMMR, DNA mismatch repair‐proficient
FIGURE 8
FIGURE 8
Relationship between TMB and certain specific gene mutations in pMMR patients with CRC. A‐D, Comparison of TMB between patients with and without APC, KRAS, FBXW7, and ARID1A in young patients with CRC. E and F, Comparison of TMB between patients with and without PIK3CA and ATM in old patients with CRC
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