Epigenetically associated CCL20 upregulation correlates with esophageal cancer progression and immune disorder

Chemokines and Their Receptors: Predictors of Therapeutic Potential in Tumor Microenvironment on Esophageal Cancer

Esophageal carcinoma (ESCA) is an aggressive solid tumor. The 5-year survival rate for patients with ESCA is estimated to be less than 20%, mainly due to tumor invasion and metastasis. Therefore, it is urgent to improve early diagnostic tools and effective treatments for ESCA patients. Tumor microenvironment (TME) enhances the ability of tumor cells to proliferate, migrate, and escape from the immune system, thus promoting the occurrence and development of tumor. TME contains chemokines. Chemokines consist of four major families, which are mainly composed of CC and CXC families. The main purpose of this review is to understand the CC and CXC chemokines and their receptors in ESCA, to improve the understanding of tumorigenesis of ESCA and determine new biomarkers for the diagnosis and prognosis of ESCA. We reviewed the literature on CC and CXC chemokines and their receptors in ESCA identified by PubMed database. This article introduces the general structures and functions of CC, CXC chemokines and their receptors in TME, as well as their roles in the progress of ESCA. Chemokines are involved in the development of ESCA, such as cancer cell invasion, metastasis, angiogenesis, and radioresistance, and are key determinants of disease progression, which have a great impact on patient prognosis and treatment response. In addition, a full understanding of their mechanism of action is essential to further verify that these chemokines and their receptors may serve as biomarkers or therapeutic targets of ESCA.

miR-147b is an oncomiR acting synergistically with HIPK2 to promote pancreatic carcinogenesis

MicroRNAs (miRs, miRNAs) are known players in the regulatory network of pancreatic tumorigenesis, but the downstream effectors remain poorly characterized. This study addressed this issue based on in silico prediction, in vitro experiments, and in vivo validation. The differentially expressed PCa-related miRNAs and bioinformatics tools predicted downstream regulators. The expression of miR-147b was examined in PCa cell lines. Putative targets of miR-147b were predicted by a publicly available database and confirmed by luciferase activity assay. Mimic/inhibitor, siRNA/overexpression plasmid, or pifithrin-α (p53 inhibitor) were delivered into PCa cells to assess the effect of miR-147b, HIPK2, and p53 on malignant phenotypes of PCa cells. AntagomiR-147b and shRNA targeting HIPK2 were introduced to xenograft-bearing nude mice for in vivo experiments. The expression of miR-147b was significantly increased in PCa cell lines. Ectopic expression of miR-147b promoted the malignant phenotypes of PCa cells and inhibited their apoptosis. HIPK2 was confirmed as a target gene of miR-147b. Inhibiting miR-147b could promote HIPK2 expression and potentially activate the p53 pathway, inhibiting PCa cell growth. In vivo experiments suggested that miR-147b inhibition suppressed the growth of xenograft tumors in nude mice, while HIPK2 knockdown counteracted its effect. Collectively, our work reveals a novel miR-147b-mediated carcinogenic regulatory network in PCa that may be a viable target for PCa treatment.

Spatial distribution of tumor-infiltrating T cells indicated immune response status under chemoradiotherapy plus PD-1 blockade in esophageal cancer

Background

The spatial distribution of tumor-infiltrating T cells and its dynamics during chemoradiotherapy combined with PD-1 blockade is little known in esophageal squamous cell carcinoma (ESCC).

Methods

We applied the multiplex immunofluorescence method to identify T cells (CD4⁺, CD8⁺ T cells, and their PD-1^- or PD-1⁺ subsets) and myeloid-derived cells (CD11c⁺ dendritic cells, CD68⁺ macrophages, and their PD-L1⁺ subpopulations) in paired tumor biopsies (n = 36) collected at baseline and during combination (40 Gy of radiation) from a phase Ib trial (NCT03671265) of ESCC patients treated with first-line chemoradiotherapy plus anti-PD-1 antibody camrelizumab. We used the FoundationOne CDx assay to evaluate tumor mutational burden (TMB) in baseline tumor biopsies (n = 14). We dynamically assessed the nearest distance and proximity of T-cell subsets to tumor cells under combination and estimated the association between T-cell spatial distribution and combination outcome, myeloid-derived subsets, TMB, and patient baseline characteristics.

Findings

We found that the tumor compartment had lower T-cell subsets than the stromal compartment but maintained a comparable level under combination. Both before and under combination, PD-1^- T cells were located closer than PD-1⁺ T cells to tumor cells; T cells, dendritic cells, and macrophages showed the highest accumulation in the 5-10-μm distance. Higher CD4⁺ T cells in the tumor compartment and a shorter nearest distance of T-cell subsets at baseline predicted poor OS. Higher baseline CD4⁺ T cells, dendritic cells, and macrophages were associated with worse OS in less than 10-μm distance to tumor cells, but related with better OS in the farther distance. Higher on-treatment PD-1-positive-expressed CD4⁺ and CD8⁺ T cells within the 100-μm distance to tumor cells predicted longer OS. T cells, dendritic cells, and macrophages showed a positive spatial correlation. Both high TMB and smoking history were associated with a closer location of T cells to tumor cells at baseline.

Conclusions

We firstly illustrated the T-cell spatial distribution in ESCC. Combining chemoradiotherapy with PD-1 blockade could improve the antitumor immune microenvironment, which benefits the treatment outcome. Further understanding the precision spatiality of tumor-infiltrating T cells would provide new evidence for the tumor immune microenvironment and for the combination treatment with immunotherapy.

Guidelines on lung adenocarcinoma prognosis based on immuno-glycolysis-related genes

OBJECTIVES

This study developed a new model for risk assessment of immuno-glycolysis-related genes for lung adenocarcinoma (LUAD) patients to predict prognosis and immunotherapy efficacy.

METHODS

LUAD samples and data obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases are used as training and test columns, respectively. Twenty-two (22) immuno-glycolysis-related genes were screened, the patients diagnosed with LUAD were divided into two molecular subtypes by consensus clustering of these genes. The initial prognosis model was developed using the multiple regression analysis method and Receiver Operating characteristic (ROC) analysis was used to verify its predictive potential. Gene set enrichment analysis (GSEA) showed the immune activities and pathways in different risk populations, we calculated immune checkpoints, immune escape, immune phenomena (IPS), and tumor mutation burden (TMB) based on TCGA datasets. Finally, the relationship between the model and drug sensitivity was analyzed.

RESULTS

Fifteen (15) key differentially expressed genes (DEGs) with prognostic value were screened and a new prognostic model was constructed. Four hundred and forty-three (443) samples were grouped into two different risk cohorts based on median model risk values. It was observed that survival rates in high-risk groups were significantly low. ROC curves were used to evaluate the model's accuracy in determining the survival time and clinical outcome of LUAD patients. Cox analysis of various clinical factors proved that the risk score has great potential as an independent prognostic factor. The results of immunological analysis can reveal the immune infiltration and the activity of related functions in different pathways in the two risk groups, and immunotherapy was more effective in low-risk patients. Most chemotherapeutic agents are more sensitive to low-risk patients, making them more likely to benefit.

CONCLUSION

A novel prognostic model for LUAD patients was established based on IGRG, which could more accurately predict the prognosis and an effective immunotherapy approach for patients.

A Transcriptome Analysis of mRNAs and Long Non-Coding RNAs in Patients with Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder. The number of cases of PD is expected to double by 2030, representing a heavy burden on the healthcare system. Clinical symptoms include the progressive loss of dopaminergic neurons in the substantia nigra of the midbrain, which leads to striatal dopamine deficiency and, subsequently, causes motor dysfunction. Certainly, the study of the transcriptome of the various RNAs plays a crucial role in the study of this neurodegenerative disease. In fact, the aim of this study was to evaluate the transcriptome in a cohort of subjects with PD compared with a control cohort. In particular we focused on mRNAs and long non-coding RNAs (lncRNA), using the Illumina NextSeq 550 DX System. Differential expression analysis revealed 716 transcripts with padj ≤ 0.05; among these, 630 were mRNA (coding protein), lncRNA, and MT_tRNA. Ingenuity pathway analysis (IPA, Qiagen) was used to perform the functional and pathway analysis. The highest statistically significant pathways were: IL-15 signaling, B cell receptor signaling, systemic lupus erythematosus in B cell signaling pathway, communication between innate and adaptive immune cells, and melatonin degradation II. Our findings further reinforce the important roles of mitochondria and lncRNA in PD and, in parallel, further support the concept of inverse comorbidity between PD and some cancers.

A Transcriptome Analysis of mRNAs and Long Non-Coding RNAs in Patients with Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder. The number of cases of PD is expected to double by 2030, representing a heavy burden on the healthcare system. Clinical symptoms include the progressive loss of dopaminergic neurons in the substantia nigra of the midbrain, which leads to striatal dopamine deficiency and, subsequently, causes motor dysfunction. Certainly, the study of the transcriptome of the various RNAs plays a crucial role in the study of this neurodegenerative disease. In fact, the aim of this study was to evaluate the transcriptome in a cohort of subjects with PD compared with a control cohort. In particular we focused on mRNAs and long non-coding RNAs (lncRNA), using the Illumina NextSeq 550 DX System. Differential expression analysis revealed 716 transcripts with padj ≤ 0.05; among these, 630 were mRNA (coding protein), lncRNA, and MT_tRNA. Ingenuity pathway analysis (IPA, Qiagen) was used to perform the functional and pathway analysis. The highest statistically significant pathways were: IL-15 signaling, B cell receptor signaling, systemic lupus erythematosus in B cell signaling pathway, communication between innate and adaptive immune cells, and melatonin degradation II. Our findings further reinforce the important roles of mitochondria and lncRNA in PD and, in parallel, further support the concept of inverse comorbidity between PD and some cancers.