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Luo, Yanxin

0000-0002-5200-3997

Mayo Clinic

Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.

Citations 2

DNA methylation profile in CpG-depleted regions uncovers a high-risk subtype of early-stage colorectal cancer
Yu, Huichuan , Wang, Xiaolin , Tang, Guannan , Cui, Ji , Ding, Yanqing , Cai, Muyan , Huang, Meijin , Gallinger, Steven , Pai, Rish K. , Win, Aung Ko , Wang, Jianping , Luo, Yanxin , Cao, Guangwen , Pai, R K , Luo, Yanxin , Win, Aung K , Yu, Huichuan , Bai, Liangliang , Carter, Kelly , Huang, Pinzhu , Li, Liang , Liu, Huanliang , Cao, Guangwen , Buchanan, Daniel D. , Newcomb, Polly A. , Grady, William M.

JNCI: Journal of the National Cancer Institute | September 29, 2022 | Volume: 115 | Issue: 1 | Pages: 52-61

10.1093/jnci/djac183 Get It

AbstractBackgroundThe current risk stratification system defined by clinicopathological features does not identify the risk of recurrence in early-stage (stage I-II) colorectal cancer (CRC) with sufficient accuracy. We aimed to investigate whether DNA methylation could serve as a novel biomarker for predicting prognosis in early-stage CRC patients.MethodsWe analyzed the genome-wide methylation status of CpG loci using Infinium MethylationEPIC array run on primary tumor tissues and normal mucosa of early-stage CRC patients to identify potential methylation markers for prognosis. The machine-learning approach was applied to construct a DNA methylation–based prognostic classifier for early-stage CRC (MePEC) using the 4 gene methylation markers FAT3, KAZN, TLE4, and DUSP3. The prognostic value of the classifier was evaluated in 2 independent cohorts (n = 438 and 359, respectively).ResultsThe comprehensive analysis identified an epigenetic subtype with high risk of recurrence based on a group of CpG loci in the CpG-depleted region. In multivariable analysis, the MePEC classifier was independently and statistically significantly associated with time to recurrence in validation cohort 1 (hazard ratio = 2.35, 95% confidence interval = 1.47 to 3.76, P < .001) and cohort 2 (hazard ratio = 3.20, 95% confidence interval = 1.92 to 5.33, P < .001). All results were further confirmed after each cohort was stratified by clinicopathological variables and molecular subtypes.ConclusionsWe demonstrated the prognostic statistical significance of a DNA methylation profile in the CpG-depleted region, which may serve as a valuable source for tumor biomarkers. MePEC could identify an epigenetic subtype with high risk of recurrence and improve the prognostic accuracy of current clinical variables in early-stage CRC.
DNA methylation-based signature of CD8+ tumor-infiltrating lymphocytes enables evaluation of immune response and prognosis in colorectal cancer
Zou, Qi , Wang, Xiaolin , Ren, Donglin , Hu, Bang, Tang, Guannan , Zhang, Yu , Huang, Meijin , Pai, Rish K. , Win, Aung Ko , Yu, Huichuan , Luo, Yanxin , Yu, Huichuan , Luo, Yanxin , Win, Aung K , Buchanan, Daniel D. , Newcomb, Polly A. , Grady, William M.

Journal for ImmunoTherapy of Cancer | September 21, 2021 | Volume: 9 | Issue: 9 | Pages: e002671

10.1136/jitc-2021-002671 Get It

Background Tumor-infiltrating lymphocytes (TILs), especially CD8+ TILs, can be used for predicting immunotherapy responsiveness and survival outcome. However, the evaluation of CD8+ TILs currently relies on histopathological methodology with high variability. We therefore aimed to develop a DNA methylation signature for CD8+ TILs (CD8+ MeTIL) that could evaluate immune response and prognosis in colorectal cancer (CRC). Methods A CD8+ MeTIL signature score was constructed by using CD8+ T cell-specific differentially methylated positions (DMPs) that were identified from Illumina EPIC methylation arrays. Immune cells, colon epithelial cells, and two CRC cohorts (n=282 and 335) were used to develop a PCR-based assay for quantitative analysis of DNA methylation at single-base resolution (QASM) to determine CD8 + MeTIL signature score. Results Three CD8+ T cell-specific DMPs were identified to construct the CD8+ MeTIL signature score, which showed a dramatic discriminability between CD8+ T cells and other cells. The QASM assay we developed for CD8+ MeTIL markers could measure CD8+ TILs distributions in a fully quantitative, accurate, and simple manner. The CD8+ MeTIL score determined by QASM assay showed a strong association with histopathology-based CD8+ TIL counts and a gene expression-based immune marker. Furthermore, the low CD8+ MeTIL score (enriched CD8+ TILs) was associated with MSI-H tumors and predicted better survival in CRC cohorts. Conclusions This study developed a quantitative DNA methylation-based signature that was reliable to evaluate CD8+ TILs and prognosis in CRC. This approach has the potential to be a tool for investigations on CD8+ TILs and a biomarker for therapeutic approaches, including immunotherapy.