Olfactomedin 4 (OLFM4) expression is associated with nodal metastases in esophageal adenocarcinoma

Prediction of lymph node metastasis in early esophageal cancer

BACKGROUND

Given the poor prognosis of patients with lymph node metastasis, estimating the lymph node status in patients with early esophageal cancer is crucial. Indicators that could be used to predict lymph node metastasis in early esophageal cancer have been reported in many recent studies, but no recent studies have included a review of this subject.

AIM

To review indicators predicting lymph node metastasis in early esophageal squamous cell carcinoma (ESCC) and early esophageal adenocarcinoma (EAC).

METHODS

We searched PubMed with "[early esophageal cancer (Title/Abstract)] and [lymph node (Title/Abstract)]" or "[early esophageal carcinoma (Title/Abstract)] and [lymph node (Title/Abstract)]" or "[superficial esophageal cancer (Title/Abstract)] and [lymph node (Title/Abstract)]." A total of 29 studies were eligible for analysis.

RESULTS

Preoperative imaging (size), serum markers (microRNA-218), postoperative pathology and immunohistochemical analysis (depth of invasion, tumor size, differentiation grade, lymphovascular invasion, neural invasion, expression of PIM-1 < 30%) were predictive factors for lymph node metastasis in both early ESCC and EAC. Serum markers (thymidine kinase 1 ≥ 3.38 pmol/L; cytokeratin 19 fragment antigen 21-1 > 3.30 ng/mL; stathmin-1) and postoperative pathology and immunohistochemical analysis (overexpression of cortactin, mixed-lineage leukaemia 2, and stanniocalcin-1) were predictive for lymph node metastasis in early ESCC. Transcription of CD69, myeloid differentiation protein 88 and toll-like receptor 4 and low expression of olfactomedin 4 were predictive of lymph node metastasis in early EAC. A total of 6 comprehensive models for early ESCC, including logistic regression model, nomogram, and artificial neural network (ANN), were reviewed. The areas under the receiver operating characteristic curve of these models reached 0.789-0.938, and the ANN performed best. As all these models relied on postoperative pathology, further models focusing on serum markers, imaging and immunohistochemical indicators are still needed.

CONCLUSION

Various factors were predictive of lymph node metastasis in early esophageal cancer, and present comprehensive models predicting lymph node metastasis in early ESCC mainly relied on postoperative pathology. Further studies focusing on serum markers, imaging and immunohistochemical indicators are still in need.

Significance of differential expression of OLFM4 in the development of endometrial adenocarcinoma

The incidence of endometrial adenocarcinoma (EA) has increased worldwide in recent years due to the widespread use of estrogen therapy and the overall increase in life expectancy. However, we know of no sensitive molecular index that can be used to predict the onset of EA, evaluate the therapeutic effects of treatment agents, or provide prognostic benefit in post-treatment follow-up. To explore the correlation between human olfactomedin 4 (OLFM4) and the clinicopathologic parameters of EA, and to determine the precise involvement of OLFM4 as a related factor in the occurrence and development of EA. We enrolled 61 gynecologic patients for a retrospective study at the Tai'an Central Hospital of Shandong Province from January 1, 2016, to June 30, 2022. We determined the expression levels of estrogen receptor α (ERα), progesterone receptor (PR), and OLFM4 proteins in endometrial tissue with the immunohistochemical S-P staining method, and analyzed the correlations among ERα, PR, and OLFM4 protein expression levels and with the pathologic stage, histologic grade, myometrial invasiveness, and lymphatic metastasis of EA. The expression levels of OLFM4 in EA were higher than in normal endometrium (P = .036). The expression level of OLFM4 protein in stage II-III patients was higher than that in stage I patients (P = .034), and the expression levels of ERα and PR proteins in EA were lower than those in normal endometrial tissue (P = .014 and P = .0005). While we observed no correlation in endometrial tissues of disparate pathologic types between OLFM4 and the expression levels of ERα and PR proteins, we noted a positive correlation between the expression levels of ERα and PR protein. The expression level of OLFM4 protein increased with the malignant degree of endometrial lesions and OLFM4 protein expression was related to the FIGO stage of EA. And OLFM4 protein can be used as 1 of the potential diagnostic factors for endometrial lesions, which is worthy of further study.

The single cell transcriptional landscape of esophageal adenocarcinoma and its modulation by neoadjuvant chemotherapy

Immune checkpoint blockade has recently proven effective in subsets of patients with esophageal adenocarcinoma (EAC) but little is known regarding the EAC immune microenvironment. We determined the single cell transcriptional profile of EAC in 8 patients who were treatment-naive (n = 4) or had received neoadjuvant chemotherapy (n = 4). Analysis of 52,387 cells revealed 10 major cell subsets of tumor, immune and stromal cells. Prior to chemotherapy tumors were heavy infiltrated by T regulatory cells and exhausted effector T cells whilst plasmacytoid dendritic cells were markedly expanded. Two dominant cancer-associated fibroblast populations were also observed whilst endothelial populations were suppressed. Pathological remission following chemotherapy associated with broad reversal of immune abnormalities together with fibroblast transition and an increase in endothelial cells whilst a chemoresistant epithelial stem cell population correlated with poor response. These findings reveal features that underlie and limit the response to current immunotherapy and identify a range of novel opportunities for targeted therapy.

Olfm4 Is Highly Expressed in HCC Patients and as a Biomarker and Therapeutic Target for HCC

Hepatocellular carcinoma (HCC) is one of the primary types of cancer that claims many lives worldwide, and its incidence continues to increase. Conventional therapies against liver cancer are inadequate, and the pathogenesis of HCC remains unclear. Thus, not only are more effective therapies to treat HCC required but also identification of the key genes involved in its pathogenesis is important for developing such therapies. This study found that olfactomedin 4 (OLFM4) level is higher in HCC patients than in healthy individuals. Furthermore, HCC patients also have higher messenger ribonucleic acid (mRNA) expression level in HCC tissues than in liver paracancerous tissues. OLFM4 has high predictive capacity as a biomarker for HCC and closely correlates to tumor size. It is confirmed that OLFM4 contributes to cancer cell proliferation, and HIF1α is involved in this process. Thus, the OLFM4/HIF-1α axis might be a target signaling pathway for developing novel drugs to treat HCC.

Identification of Prognostic Risk Model Based on DNA Methylation-Driven Genes in Esophageal Adenocarcinoma

Background

DNA methylation is an important part of epigenetic modification, and its abnormality is closely related to esophageal adenocarcinoma (EAC). This study was aimed at using bioinformatics analysis to identify methylation-driven genes (MDGs) in EAC patients and establish a risk model as a biological indicator of EAC prognosis.

Method

Downloaded EAC DNA methylation, transcriptome, and related clinical data from TCGA database. MethylMix was used to identify MDGs. R package clusterProfiler and the ConsensusPathDB online database were used to analyze the rich functions and pathways of these MDGs. The prognostic risk model was established by univariate Cox regression, Lasso regression, and multivariate Cox regression analysis. Finally each MDG in the model were carried out through the survival R package.

Results

A total of 273 MDGs were identified, which were enriched in transcriptional regulation and embryonic organ morphogenesis. Cox regression analysis established a risk model consisting of GPBAR1, OLFM4, FOXI2, and CASP10. In addition, further survival analysis revealed that OLFM4 and its two related sites were significantly related to the EAC patients' survival.

Conclusion

In summary, this study used bioinformatics methods to identify EAC MDGs and established a reliable risk prognosis model. It provided potential biomarkers for the early treatment and prognosis evaluation of EAC.

Infiltration Depth is the Most Relevant Risk Factor for Overall Metastases in Early Esophageal Adenocarcinoma

BACKGROUND

Research in early esophageal adenocarcinoma focused on prediction of lymph node metastases in order to stratify patients for endoscopic treatment instead of esophagectomy. Although distant metastases were described in rates of up to 13% of patients within a follow-up of 3 years, their prediction has been neglected so far.

METHODS

In a secondary analysis, a cohort of 217 patients (53 T1a and 164 T1b) treated by esophagectomy was analyzed for histopathological risk factors. Their ability to predict the combination of lymph node metastases at surgery as well as metachronous locoregional and distant metastases (overall metastatic rate) was assessed by uni- and multivariate logistic regression analysis.

RESULTS

Tumor invasion depth was correlated with both lymph node metastases at surgery (τ = 0.141; P = .012), tumor recurrences (τ = 0.152; P = .014), and distant metastases (τ = 0.122; P = 0.04). Multivariate analysis showed an odds ratio of 1.31 (95% CI 1.02-1.67; P = .033) per increasing tumor invasion depth and of 3.5 (95% CI 1.70-6.56; P < .001) for lymphovascular invasion. The pre-planned subgroup analysis in T1b tumors demonstrated an even lower predictive ability of lymphovascular invasion with an odds ratio of 2.5 (95% CI 1.11-5.65; P = 0.028), whereas the predictive effect of sm2 (odds ratio 3.44; 95% CI 1.00-11.9; P = 0.049) and sm3 (odds ratio 3.44; 95% CI 1.00-11.9; P = 0.049) tumor invasion depth was similar.

CONCLUSIONS

The present report demonstrates the insufficient risk prediction of histopathologic risk factors for the overall metastatic rate.