Humoral immune responses against cancer-testis antigens in human malignancies

Analysis of the differential expression and prognostic relationship of DEGs in AML based on TCGA database

BACKGROUND

Acute myeloid leukemia (AML) is a common and lethal hematological malignant hyperplastic disease originating from hematopoietic stem cells. The purpose of this study is to obtain the key differentially expressed gene (DEG) related to the survival of AML by The Cancer Genome Atlas (TCGA) database and to verify these genes by a clinical follow-up investigation, in order to identify valuable predictive and prognostic biomarkers for early diagnosis of AML and predict the survival rates.

METHODS

The RNA sequencing (RNA-Seq) data and clinical information of TCGA-LAML were downloaded from the TCGA database. After that we (1) screened the survival-related DEGs by Cox regression analysis, (2) selected the cytogenetics risk-related DEGs by DESeq2 R package, and (3) filtrated the genes in the top10 pathways of up-regulated and down-regulated of Normalization Enrichment Score (NES) by Gene Set Enrichment Analysis (GSEA). Finally, we focused the intersectional genes of above three parts as the key gene of the present study. The following Multivariate.

Anti-Tumor Effect of Parasitic Protozoans

The immune system may aberrantly silence when against “altered self”, which consequently may develop into malignancies. With the development of tumor immunology and molecular biology, the deepened understanding of the relationship between parasites and tumors shifts the attitude towards parasitic pathogens from elimination to utilization. In recent years, the antitumor impact implemented by protozoan parasites and the derived products has been confirmed. The immune system is activated and enhanced by some protozoan parasites, thereby inhibiting tumor growth, angiogenesis, and metastasis in many animal models. In this work, we reviewed the available information on the antitumor effect of parasitic infection or induced by parasitic antigen, as well as the involved immune mechanisms that modulate cancer progression. Despite the fact that clinical trials of the protozoan parasites against tumors are limited and the specific mechanisms of the effect on tumors are not totally clear, the use of genetically modified protozoan parasites and derived molecules combined with chemotherapy could be an important element for promoting antitumor treatment in the future.

Cancer-testis antigen KK-LC-1 is a potential biomarker associated with immune cell infiltration in lung adenocarcinoma

Background

Cancer-testis antigens (CTAs) have emerged as potential clinical biomarkers targeting immunotherapy. KK-LC-1 is a member of CTAs, which has been demonstrated in a variety of tumors tissues and been found to elicit immune responses in cancer patients. However, the expression level and immune infiltration role of KK-LC-1 in lung adenocarcinoma (LUAD) remains to be elucidated.

Methods

In this study, the mRNA expression and overall survival rate of KK-LC-1 were evaluated by the TIMER and TCGA database in LUAD tissues and KK-LC-1 expression was further validated by clinical serum samples using quantitative RT-PCR. The relationship of KK-LC-1 with clinicopathologic parameters was analyzed. ROC curve result showed that miR-1825 was able to distinguish preoperative breast cancer patients from healthy people and postoperative patients. Then, the ROC curves were used to examine the ability of KK-LC-1 to distinguish preoperative LUAD patients from healthy and postoperative patients. The correlation between KK-LC-1 and infiltrating immune cells and immune marker sets was investigated via TIMER, TISIDB database, and CIBERSORT algorithm. The Kaplan-Meier plotter was used to further evaluate the prognostic value based on the expression levels of KK-LC-1 in related immune cells.

Results

The results showed that KK-LC-1 was significantly over-expressed in LUAD, and high levels of expression of KK-LC-1 were also closely correlated with poor overall survival. We also found that KK-LC-1 associated with TMN stage, NSE and CEA. The ROC curve result showed that KK-LC-1 was able to distinguish preoperative LUAD cancer patients from healthy people and postoperative patients. Moreover, KK-LC-1 had a larger AUC with higher diagnostic sensitivity and specificity than CEA. Based on the TIMER, TISIDB database, and CIBERSORT algorithm, the expression of KK-LC-1 was negatively correlated with CD4+ T cell, Macrophage, and Dendritic Cell in LUAD. Moreover, Based on the TIMER database, KK-LC-1 expression had a remarkable correlation with the type markers of Monocyte, TAM, M1 Macrophage, and M2 Macrophage. Furthermore, KK-LC-1 expression influenced the prognosis of LUAD patients by directly affecting immune cell infiltration by the Kaplan-Meier plotter analysis.

Conclusions

In conclusion, KK-LC-1 may serve as a promising diagnostic and prognostic biomarker in LUAD and correlate with immune infiltration and prognosis.

Cancer-testis antigen ACRBP expression and serum immunoreactivity in ovarian cancer: Its association with prognosis

Introduction

Cancer testis (CT) antigens are attractive targets for cancer immunotherapy because of their expression restriction and immunogenicity. The acrosin binding protein (ACRBP) is a member of CT antigens. This study aimed to evaluate ACRBP expression and immunogenicity in ovarian cancer (OC).

Methods

The expression level of ACRBP in OC tissues, normal ovarian tissues, and cell lines was detected via quantitative real‐time polymerase chain reaction (qRT‐PCR) and immunohistochemistry. We determined the levels of ACRBP antigen and antibody in serum samples collected from patients with OC and healthy donors using enzyme‐linked immunosorbent assays (ELISA), the level of ACRBP in cell‐cultured medium was also tested.

Results

ACRBP mRNA and protein expressions were upregulated in OC tissues relative to normal tissue, especially highly expressed in epithelial ovarian cancer (EOC). Moreover, ACRBP expression was significantly correlated with International Federation of Gynecology and Obstetrics (FIGO) stage and chemosensitivity. Serological analysis showed that anti‐ACRBP antibody was detected in the sera of 16 of the 56 (28.5%) patients with OC but not in healthy donors. The area under the receiver operating characteristic curve for ACRBP antibody was 0.802 (95% confidence interval [CI]: 0.708–0.876), and the sensitivity and specificity for ACRBP antibody was 85.71% and 55.0%, respectively. Kaplan–Meier analysis revealed that the overall survival (OS) and disease‐free survival (DFS) in OC patients with high ACRBP expression were significantly lower than those with low expression (p = 0.040, p = 0.021). However, ACRBP antibody level was not associated with prognosis.

Conclusion

ACRBP expression was upregulated in OC tissues and induced humoral immune response in patients with OC, suggesting that ACRBP is a potential prognostic biomarker and a target of tumor immunotherapy for OC.

Identification of genes of prognostic value in the ccRCC microenvironment from TCGA database

Background

Clear cell renal cell carcinoma (ccRCC) is the most common pathological subtype of renal cell carcinoma. Bioinformatics analyses were used to screen candidate genes associated with the prognosis and microenvironment of ccRCC and elucidate the underlying molecular mechanisms of action.

Methods

The gene expression profiles and clinical data of ccRCC patients were downloaded from The Cancer Genome Atlas database. The ESTIMATE algorithm was used to compute the immune and stromal scores of patients. Based on the median immune/stromal scores, all patients were sorted into low‐ and high‐immune/stromal score groups. Differentially expressed genes (DEGs) were extracted from high‐ versus low‐immune/stromal score groups and were described using functional annotations and protein‒protein interaction (PPI) network.

Results

Patients in the high‐immune/stromal score group had poorer survival outcome. In total, 95 DEGs (48 upregulated and 47 downregulated genes) were screened from the gene expression profiles of patients with high immune and stromal scores. The genes were primarily involved in six signaling pathways. Among the 95 DEGs, 43 were markedly related to overall survival of patients. The PPI network identified the top 10 hub genes—CD19, CD79A, IL10, IGLL5, POU2AF1, CCL19, AMBP, CCL18, CCL21, and IGJ—and four modules. Enrichment analyses revealed that the genes in the most important module were involved in the B‐cell receptor signaling pathway.

Conclusion

This study mainly revealed the relationship between the ccRCC microenvironment and prognosis of patients. These results also increase the understanding of how gene expression patterns can impact the prognosis and development of ccRCC by modulating the tumor microenvironment. The results could contribute to the search for ccRCC biomarkers and therapeutic targets.