Genetic and epigenetic strategies for advancing ovarian cancer immunotherapy

Identification of immune-related lncRNA panel for predicting immune checkpoint blockade and prognosis in head and neck squamous cell carcinoma

Purpose

Immunotherapy is changing head and neck squamous cell carcinoma (HNSCC) treatment pattern. According to the Chinese Society of Clinical Oncology (CSCO) guidelines, immunotherapy has been deemed as first‐line recommendation for recurrent/metastatic HNSCC, marking that advanced HNSCC has officially entered the era of immunotherapy. Long non‐coding RNAs (lncRNAs) impact every step of cancer immunity. Therefore, reliable immune‐lncRNAs able to accurately predict the immune landscape and survival of HNSCC are crucial to clinical management.

Methods

In the current study, we downloaded the transcriptomic and clinical data of HNSCC from The Cancer Genome Atlas and identified differentially expressed immune‐related lncRNAs (DEir‐lncRNAs). Further then, Cox and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to identify proper DEir‐lncRNAs to construct optimal risk model. Low‐risk and high‐risk groups were classified based on the optimal cut‐off value generated by the areas under curve for receiver operating characteristic curves (AUC), and Kaplan–Meier survival curves were utilized to validate the prediction model. We then evaluated the model based on the clinical factors, immune cell infiltration, and chemotherapeutic and immunotherapeutic efficacy between two groups.

Results

In our study, we identified 256 Deir‐lncRNAs in HNSCC. A total of 18 Deir‐lncRNA pairs (consisting of 35 Deir‐lncRNAs) were used to construct a risk model significantly associated with survival of HNSCC. Cox proportional hazard regression analysis confirmed that our risk model could be served as an independent prognostic indicator. Besides, HNSCC patients with low‐risk score significantly enriched of CD8⁺ T cell, and corelated with high chemosensitivity and immunotherapeutic sensitivity.

Conclusion

Our risk model could be served as a promising clinical prediction indicator, effective discoursing of the immune cell infiltration of HNSCC patients, and distinguishing patients who could benefit from chemotherapy and immunotherapy.

Prognostic significance of HOXD4 protein expression in human ovarian cancers

Objectives

Ovarian cancer is the most common gynecological malignancy, ranking as the fifth leading cause of cancer-related deaths among females in the United States. Homeobox D4 (HOXD4) is a transcription factor belonging to the homeobox protein family, which plays a critical role in morphogenesis during embryo development. Here we aimed to study the HOXD4 expression in ovarian serous carcinoma (OSC) and determine its clinical significance.

Materials and Methods

Real-time quantitative PCR and immunohistochemistry targeting human OSC tissues and adjacent ovarian tissues were performed to correlate the patterns of HOXD4 expression with clinical characteristics and survival outcomes. Cell lines and nude mice were used for verifying the role of HOXD4 in OSC.

Results

HOXD4 protein was predominantly expressed in OSC tissues compared with nontumorous tissues. The correlation test demonstrated a significant correlation between HOXD4 with tumor FIGO stage. Univariate and multivariate analyses found that HOXD4 expression was associated with poorer overall survival. Furthermore, high expression of HOXD4 protein was observed in OSC cell lines in vitro. Finally, the oncogenic effect of HOXD4 was confirmed by cellular and xenograft experiments.

Conclusion

HOXD4 protein expression may be associated with a poorer prognosis in OSC. The unfavorable prognostic value of HOXD4 in malignancies and its underlying mechanism are worthy of further investigation.

Bioinformatics Analysis of GFAP as a Potential Key Regulator in Different Immune Phenotypes of Prostate Cancer

Tumor immune escape plays an essential role in both cancer progression and immunotherapy responses. For prostate cancer (PC), however, the molecular mechanisms that drive its different immune phenotypes have yet to be fully elucidated. Patient gene expression data were analyzed from The Cancer Genome Atlas-prostate adenocarcinoma (TCGA-PRAD) and the International Cancer Genome Consortium (ICGC) databases. We used a Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) analysis and an unsupervised clustering analysis to identify patient subgroups with distinct immune phenotypes. These distinct phenotypes were then explored for associations for differentially expressed genes (DEGs) and both epigenetic and genetic landscapes. Finally, we used a protein-protein interaction analysis to identify key hub genes. We identified two patient subgroups with independent immune phenotypes associated with the expression of Programmed death-ligand 1 (PD-L1). Patient samples in Cluster 1 (C1) had higher scores for immune-cell subsets compared to Cluster 2 (C2), and C2 samples had higher specific somatic mutations, MHC mutations, and genomic copy number variations compared to C1. We also found additional cluster phenotype differences for DNA methylation, microRNA (miRNA) expression, and long noncoding RNA (lncRNA) expression. Furthermore, we established a 4-gene model to distinguish between clusters by integrating analyses for DEGs, lncRNAs, miRNAs, and methylation. Notably, we found that glial fibrillary acidic protein (GFAP) might serve as a key hub gene within the genetic and epigenetic regulatory networks. These results improve our understanding of the molecular mechanisms underlying tumor immune phenotypes that are associated with tumor immune escape. In addition, GFAP may be a potential biomarker for both PC diagnosis and prognosis.

Expression of B7-H4 and IDO1 is associated with drug resistance and poor prognosis in high-grade serous ovarian carcinomas

High-grade serous ovarian carcinoma (HGSC) is the most lethal gynecologic malignancy. While immune checkpoint inhibitors against PD-L1 and CTLA-4 have shown significant effects in multiple tumor types, the response rate to single-agent immune checkpoint inhibitors is low in HGSC. Alternative biomarkers and targets must be identified to guide patient selection and new therapeutic strategies in HGSC. Here, we aim to investigate the clinical significance of novel immune modulators, including B7-H4, IDO1, Tim3, IL6, and IL-8, in patients with HGSC. A total of 48 patients with HGSCs, comprising 24 cases that were sensitive and 24 that were resistant to standard paclitaxel and carboplatin chemotherapy, were selected for our initial analysis. A NanoString assay including 33 immune-related genes was used to compare the expression of different immune regulatory molecules in the sensitive and resistant groups. Differentially expressed proteins were verified using multiplex immunohistochemical staining on tissue arrays of 202 patients with HGSCs who underwent primary surgery at MDACC. We analyzed the expression levels of immune checkpoints and compared expression profiles with clinicopathologic features including response, progression-free survival, and overall survival. HGSC tumors resistant to therapy expressed higher levels of B7-H4 (69.3%), IDO1 (71.8%), Tim3 (89.1%), and inflammatory factors IL-6 and IL-8, and expressed higher Tim3 in stromal components. High expression of B7-H4 and IDO1 was associated with significantly lower overall survival and progression-free survival. B7-H4 and IDO1 were co-expressed in 49.1% of studied cases. A panel of immunomodulatory proteins including B7-H4, IDO1, Tim3, IL-6, and IL-8 are expressed at high levels in HGSCs. These modulators represent novel targets to enhance immunotherapy in patients with HGSCs.

Downregulated Long Noncoding RNA DGCR5 Acts as a New Promising Biomarker for the Diagnosis and Prognosis of Ovarian Cancer

Emerging evidence have indicated that dysregulated long noncoding ribonucleic acids act as a novel diagnostic and therapeutic target in the progression of ovarian cancer. Long noncoding RNA DiGeorge syndrome critical region gene 5 has been reported to participate in some types of human cancer progresses, but its clinical roles in ovarian cancer had been rarely reported. This study aimed to explore the expression, clinicopathological features, diagnostic, and prognostic values of DiGeorge syndrome critical region gene 5 in ovarian cancer. The total levels of DiGeorge syndrome critical region gene 5 transcript variant 1 (NR_002733.2) and 2 (NR_045121.1) in patients with ovarian cancer were determined by quantitative reverse transcription polymerase chain reaction. The correlation of DiGeorge syndrome critical region gene 5 expression with clinicopathological factors was statistically analyzed by χ² test. Overall survival analysis was carried out with the Kaplan–Meier curves with the log-rank test. Univariate and multivariate Cox regression analyses were performed to identify the prognostic significance of DiGeorge syndrome critical region gene 5 expression. Receiver operating characteristic curves were constructed to estimate the diagnostic and prognostic usefulness of DiGeorge syndrome critical region gene 5 in ovarian cancer. Results showed that relative DiGeorge syndrome critical region gene 5 expression was reduced by 36.81% and 65.79% in ovarian cancer tissues of patients and Gene Expression Omnibus DataSets (GSE119056) in contrast to normal tissues, respectively. Patients with lymph node metastasis and distant metastasis exhibited lower levels of DiGeorge syndrome critical region gene 5 in contrast to those patients with non-lymph node metastasis and non-distant metastasis, respectively. Low expression of DiGeorge syndrome critical region gene 5 was significantly associated with large tumor size, more lymph node metastasis, present distant metastasis, advanced clinical stage, and short overall survival in patients with ovarian cancer. Low expression of DiGeorge syndrome critical region gene 5 was an independent unfavorable prognostic factor for overall survival in patients with ovarian cancer. Receiver operating characteristics curves for prognosis yielded significant area under curves for lymph node metastasis, clinical stage, and overall survival. In conclusion, our study demonstrated that downregulated DiGeorge syndrome critical region gene 5 may be a new promising biomarker for predicting clinical progression and prognosis in patients with ovarian cancer.

DNA fragment translocation through the lipid membrane assisted by carbon nanotube

DNA delivery through cell membrane is a fundamental step for efficiency gene therapy. As a potential DNA carrier, carbon nanotubes (CNTs) have been extensively studied due to its unique properties. However, the mechanism of DNA translocation with CNTs through cell membrane is still not well understood. In this study, the DNA translocation process through POPC (1-palmitoyl-2-oleoylphosphatidylcholine) membrane with the assistance of CNTs was explored by molecular dynamics (MD) simulation. Our simulation results demonstrated that the CNTs could insert steadily into the POPC membrane, and DNA molecules tends to insert into the inner space of CNTs. With the assistance of CNTs, the free energy of nucleotides passing through the POPC membrane decreases. Moreover, the free energy of nucleotides (DA (deoxyadenosine), DT (deoxythymidine), DC (deoxycytidine), and DG (deoxyguanosine)) passing through POPC membrane follows the order: DA (deoxyadenosine) > DG (deoxyguanosine) > DC (deoxycytidine) > DT (deoxythymidine). These results may promote the design and application of CNT-based gene delivery system.