The researchers identified 3 immune subtypes of esophageal cancer (EC) among the samples, all of which had different prognostic implications.
Researchers say they have identified immune subtypes (IS) specific to esophageal cancer (EC) that offer insight into the complex nature of the immune microenvironment.
Based on their results, the group emphasized the importance of thoroughly evaluating SIs from EC samples to understand the personalized nature of the tumor immune microenvironment (TIME). This, they say, may eventually lead to more personalized treatment for patients with the disease.
Their findings recently appeared in Annals of Medicine.
“Given the complex immune function, a more in-depth description of the overall characteristics of TIME will help improve the level of individualized precision treatment,” wrote the researchers, who found that the distribution of SI in functional modules is different.
They added: âWe have reported for the first time that there is significant within-class heterogeneity in SIs of the EC, conferring different prognostic outcomes. Taken together, these results warn of insufficient therapeutic efficacy and prognosis prediction based on a single immune index.
The researchers identified 3 SI among the samples, all of which had different prognostic implications; IS3 subtypes had a favorable prognosis while IS1 subtypes had a worse prognosis. They also analyzed the association of tumor mutational burden (TMB) – a supported predictive biomarker of immunotherapy – among the 3 subtypes, concluding that TMB in IS1 was significantly higher than in IS2 and IS3.
Data from 2 cohorts were used for the analysis:
- 161 samples with RNA sequencing of esophageal cancer clinical entries Cancer Genome Atlas (the TCGA-ESCA cohort) from the TCGA Genomic Data Commons portal
- 119 GSE53624 DNA microarray data samples with Gene Expression Omnibus survival information
Researchers have also identified key genes in the immune microenvironment of ECâBHLHE22, MXRA8, SLOT2 and SPON1, all of which were associated with the prognosis of EC. Based on the genetic signature, the researchers created a risk score model that they believe can be used for prognosis prediction: -0.16514291 ÃBHLHE22-0.03964046 ÃMXRA8-0.15242778 ÃSLOT2-0.05553572 ÃSPON1.
The risk score, they say, can be used to stratify high-risk and low-risk patients in the TCGA-ESCA cohort and has been independently validated in the GSE53624 cohort.
“Interesting way, SLOT2 expression is downregulated in EC, associated with a poor prognosis, âthe researchers noted. âA previous study showed that miR-1179 promotes cell invasion of [esophageal squamous cell carcinoma] through the SLOT2 / ROBO1 axis. In other types of cancer, SPON1 promotes metastasis to human osteosarcoma, while methylated BHLHE22 / CDO1 / CELF4 panel could be used for endometrial cancer screening. The association of these genes in EC deserves further validation by fundamental and clinical studies.
Xie Y, Shi X, Chen Y et al. The intra-class heterogeneity of immunophenotyping and the immune landscape in esophageal cancer and its clinical implications. Ann Med. 2021; 53 (1): 626-638.